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Review

Cell-Free DNA in the Pathogenesis and Therapy of Non-Infectious Inflammations and Tumors

Department of Internal Medicine and Hematology, Semmelweis University, Szentkirályi Street 46, 1088 Budapest, Hungary
*
Author to whom correspondence should be addressed.
Biomedicines 2022, 10(11), 2853; https://doi.org/10.3390/biomedicines10112853
Submission received: 15 October 2022 / Revised: 31 October 2022 / Accepted: 7 November 2022 / Published: 8 November 2022

Abstract

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The basic function of the immune system is the protection of the host against infections, along with the preservation of the individual antigenic identity. The process of self-tolerance covers the discrimination between self and foreign antigens, including proteins, nucleic acids, and larger molecules. Consequently, a broken immunological self-tolerance results in the development of autoimmune or autoinflammatory disorders. Immunocompetent cells express pattern-recognition receptors on their cell membrane and cytoplasm. The majority of endogenous DNA is located intracellularly within nuclei and mitochondria. However, extracellular, cell-free DNA (cfDNA) can also be detected in a variety of diseases, such as autoimmune disorders and malignancies, which has sparked interest in using cfDNA as a possible biomarker. In recent years, the widespread use of liquid biopsies and the increasing demand for screening, as well as monitoring disease activity and therapy response, have enabled the revival of cfDNA research. The majority of studies have mainly focused on the function of cfDNA as a biomarker. However, research regarding the immunological consequences of cfDNA, such as its potential immunomodulatory or therapeutic benefits, is still in its infancy. This article discusses the involvement of various DNA-sensing receptors (e.g., absent in melanoma-2; Toll-like receptor 9; cyclic GMP–AMP synthase/activator of interferon genes) in identifying host cfDNA as a potent danger-associated molecular pattern. Furthermore, we aim to summarize the results of the experimental studies that we recently performed and highlight the immunomodulatory capacity of cfDNA, and thus, the potential for possible therapeutic consideration.

1. Introduction

The discovery of cell-free deoxynucleic acids (cfDNA) in the sera of cancer patients in 1948, is attributed to Mandel and Métais [1]. Later, a correlation was observed between the concentration of cfDNA and the development of systemic lupus erythematosus [2]. The use of cfDNA in the diagnosis of tumors began in 1977, but was not very effective, due to the limitations of the existing technology [3]. The real-time polymerase chain reaction allowed the detection of RhD and the fetal sex in maternal plasma in 1997 [4]. The real expansion of non-invasive fetal genetic disease detection began in 2011, with the introduction of massive parallel sequencing [5]. Approximately fifty percent of prenatal genetic examinations are performed today via so-called non-invasive prenatal testing (NIPT) [6]. Recently, the spread of liquid biopsies and the increased demand for screening, as well as monitoring disease activity and the therapeutic response, made it possible for cfDNA research to be revived. Though the analysis of the 5′ ends of extracellular DNA demonstrated the unique character of extracellular DNA (i.e., definitely not being a junk molecule) [7], investigations primarily focus on the role of cfDNA as a biomarker, and research regarding the immunological properties of cfDNA, such as its potential immunomodulatory or therapeutic benefits, is still in its infancy. In this review, we aim to summarize the findings of recent experimental studies and highlight the immunobiological effects of cfDNA, as well as the potential for future therapeutic considerations in the context of sterile inflammation and the onset of cancer.

2. Origin, Release, Amount, and Clearance of Cell-Free DNA

Though cfDNA is ubiquitously present in human body fluids [8], and many aspects of its molecular source are known, research to uncover the unknown factors in its origin is growing and may never end. Except for the exogenous sources of cfDNA [9], many possible endogenous origins and related mechanisms have been proposed [10]. Regarding the cellular source of cfDNA, tumorous (i.e., local and circulating tumor cells, micrometastases, and cells of the tumor microenvironment) and non-tumorous cells (e.g., muscle cells, epithelial cells, ovum cells, bone cells, myeloid and lymphoid cells) can be distinguished [10].
The mechanisms responsible for cfDNA release are quite diverse. On the one hand, cell death and clearance mechanisms (i.e., apoptosis, necrosis, pyroptosis, mitotic catastrophe, autophagy, phagocytosis, oncosis, NETosis, and DNA excision repair damage) are partly responsible for the release of cfDNA [11,12]. On the other hand, the active release is also possible via macromolecular structures (DNA-protein complexes, extracellular traps), micronucleation induced by genome instability (extrachromosomal circular DNA), or microvesicles (exosomes) [13,14,15].
Different data is available on the amount of human cfDNA in circulation since no standardized methods exist. The choice of matrix (i.e., serum, plasma, urine, cerebral fluid, etc.), the mode of sample collection (e.g., EDTA-containing tubes or CellSave tubes, etc.), the parameters of centrifugation (i.e., speed, temperature, duration), types of isolation kits, and cfDNA storage conditions can all influence the measurement results [16]. In general, the level of cfDNA in the healthy population is lower, as compared with diseased people. According to the latest data [17], the normal human plasma cfDNA concentration can be as high as 500 ng/μL. In cases of advanced cancers [18,19,20], autoimmune [21,22,23,24,25], inflammatory [26], traumatic [27,28], post-transplantation [29] or infectious diseases [30,31] usually a more increased amount is detected. In addition, cfDNA levels could also be increased, due to vigorous physical exertion (such as intense sports, e.g., half marathon, ultramarathon, TRX exercises) [32,33] and pregnancy [34]. Fetal cfDNA, which is primarily produced by placental trophoblast cells during pregnancy [35], is detected in the maternal circulation, as early as in the first trimester, accounting for 10 to 15% of the total cfDNA concentration [36].
The concentration of cfDNA can increase, not only under the previously mentioned conditions, but also as a result of an increase in release. Ineffective clearance mechanisms could also contribute significantly to the elevated levels of circulating cfDNA. Extracellular nuclease homologs, DNase I and DNase I-like III (DNase I L3), are responsible for the efficient degradation of both free and protein-bound DNA [37]. The enzyme’s ability to recognize and degrade DNA could be influenced by the abnormalities of DNase I activity (e.g., low serum DNase I activity [38], elevated serum levels of DNase I inhibitors [39], novel mutations in the enzyme [40]), molecules that interact with DNA [41], anti-DNase antibodies [42,43], and deficiencies in DNase I activating cofactors, such as the complement component C1q [44], TREX1 DNase [45], serum amyloid P component [46], IgM [47], C-reactive protein [48], and mannan-binding lectin [49]).

3. Cell-Free DNA as a Molecular Marker or a Diagnostic Tool

Based on its close association with a number of human physiological and pathological conditions, the clinical utility of cfDNA as a noninvasive, reliable, sensitive, and rapid diagnostic marker is continuously the subject of intense research (Figure 1).

3.1. cfDNA in Prenatal Diagnosis

Prenatal genetic testing is among the fields in which the utilization of circulating cfDNA has had the most success and is still widely used [50]. NIPT became a clinical reality in 2011 [51]. The fetal-derived cfDNA can be detected as early as the 4th week of gestation [52], and it is quickly eliminated from the maternal bloodstream after delivery [53], emphasizing its pregnancy specificity. The first clinical applications were limited to the identification of alleles present in the fetus and not in the maternal genome (i.e., paternal or de novo mutations) [54]. In contrast, the establishment of autosomal recessive or maternally transmitted autosomal dominant disorders, has been much more complicated, even though several studies have succeeded in determining the exclusion of paternal alleles in recessive conditions. However, thanks to the continuous development of technology, it is now possible to determine the sex, RhD, and blood group of the fetus [55]. In addition, cfDNA also allows the identification of fetal aneuploidies and specific microdeletions [56]. Though the measurement of fetal cfDNA is noninvasive, widely applicable, and available early in pregnancy, it has some limitations. The current detection of aneuploidy is limited to common trisomies [57], therefore the karyotype determination is still necessary. Furthermore, fetal cfDNA determination is currently irrelevant for diagnosing monogenic disorders, autosomal recessive, or X-linked diseases [58]. So, the technique needs to be improved.

3.2. cfDNA in Tumors

The growing interest in tumor-related cfDNA is a direct result of its potential use as a liquid biopsy tool, which has great promise for a wide range of clinical applications [59,60]. Even if a surgical biopsy/histology remains the gold standard for cancer diagnosis and treatment, it has some disadvantages (i.e., it is invasive and provides temporary static images of malignancy) [61]. In contrast, tumor cfDNA detection enables the real-time longitudinal monitoring of cancer, along with capturing tumor heterogeneity [62,63,64]. Moreover, in the last few years, there has been a strong concordance between plasma and tissue-based genomic studies, encouraging the exploration of their potential clinical utility [65,66,67,68]. Tumor cfDNA has received a lot of attention in early tumor detection for several types of cancer [69], however, the process for purification and handling of cfDNA is not yet standardized, and numerous preanalytical variables, such as the purification kits, blood collection tubes, and centrifugation regime, may affect cfDNA’s yield and analysis [70,71]. Thus, more sensitive and reproducible techniques are required. For screening, the combined use of tumor cfDNA and conventional tumor markers seems to be an optimal application [72,73,74]. Several studies have demonstrated that in several types of cancer tumors, cfDNA is suitable for detecting minimal residual disease postoperatively or after chemotherapy [75,76,77], which suggests that it has a high prognostic value with the ability to predict the disease recurrence. The genotyping of tumor cfDNA is useful, not only in choosing the optimal treatment and dynamically monitoring the therapeutic responses [78], but it can also reveal the genetic causes of malignancy progression and therapy resistance, as well [78]. Applications of tumor cfDNA in this direction seem feasible and are close to being introduced into clinical practice.

3.3. cfDNA in Non-Tumor Disorders

In pathological conditions, such as autoimmune diseases [79,80,81,82], stroke [83], myocardial infarction [84,85], and allograft transplant rejection [86], there is substantial interest in the investigation of cfDNA’s clinical utility, but no real medical applications have been developed yet. Elevated levels of cfDNA in SLE patients appear to be associated with antibody titers and active lupus nephritis [82,87], but its correlation with disease activity, as well as the diagnostic and prognostic values, remains uncertain [83,87]. In rheumatoid arthritis (RA) patients, the serum level of cfDNA seems to be quite varied [81,88,89]. The cfDNA concentration of synovial fluid is several times higher than that in circulation, indicating the importance of local inflammation in the cfDNA release [90]. In RA patients, the dynamics of cfDNA appear to be independent of the conventional diagnostic markers, ACPA and RF. Though studies suggest the biomarker potential of cfDNA, further studies with large patient cohorts are necessary to analyze the dynamics of cfDNA in RA, in relation to the disease progression and drug effects.
In cases of stroke, the dynamically determined blood levels of cfDNA appear to be a valid and reliable option for establishing prognostic and diagnostic criteria [91]. While cfDNA has performed well in a number of studies as a stroke biomarker [92,93], none of the so-called stroke biomarkers identified to date have proven useful in medical practice, and there is still a long way to go before its clinical application, either as a standalone marker or as part of a biomarker panel.
cfDNA testing provides an alternative method for monitoring myocardial ischemia and has potential clinical applications for identifying high-risk individuals [94]. However, several biological and technical obstacles were recognized in cell-free DNA testing [95], including the lack of specificity and unsuitable kinetics for early cardiomyocyte damage, the long turnaround time and limited bandwidth, the need for specialized equipment and specialized staff, the absence of standardized or harmonized analytical techniques, the indirect expenses, and the high susceptibility to preanalytical variables [95]. Therefore, it seems acceptable to conclude that the analysis of cell-free DNA in diagnosing myocardial ischemia is not yet ready for commercialization.
In organ transplantation, the diagnostic role of cfDNA has been extensively studied in heart, kidney, and lung transplantations [96]. However, only one study exists on this topic in liver transplantation [97]. Despite the many results supporting the association between the amount and kinetics of donor-derived cfDNA and transplant organ rejection, neither the US Food and Drug Administration nor the European Medicines Agency has approved the use of cfDNA in this context. Based on the objections, clarification is needed on both the threshold and kinetics.

4. Recognition and Immunomodulatory Role of Cell-Free DNA

In addition to being a biomarker and a diagnostic tool, cfDNA has been shown experimentally to have an immunomodulatory effect. It can influence the initiation, progression, or amelioration of inflammation. The presence of self-DNA in the nucleus and mitochondria is necessary for the maintenance of self-tolerance. However, following nuclear or mitochondrial damage, self-DNA enters the cytosol under stress conditions. In the apparent lack of infection, the inflammatory response is likely triggered by the production of endogenous alarmins, known as danger-associated molecular patterns (DAMPs), which trigger immune responses via pattern-recognition receptors (PRR). Cell-free DNA could act as a DAMP [98,99].
The recognition of cfDNA could be performed by the DNA-sensing receptor cyclic guanosine monophosphate (GMP)-adenosine monophosphate (AMP) synthase (cGAS), Toll-like receptor 9 (TLR9), or absent in melanoma-2 (AIM2)-like receptors (ALRs) [100].
The cGAS identifies cytosolic DNA and induces the interferon regulatory factor (IRF) 3-dependent interferon-beta (IFNβ) or type 1 interferons [101]. cGAS recognizes extracellular nucleosomes as well, because they have a higher binding capacity than double-stranded DNA (dsDNA) [101]. Stimulator of interferon genes (STING) participates in the cGAS signaling pathway in response to the recognition of cytosolic DNA [102,103]. The cGAS optimally recognizes 36 base pair long dsDNA (or longer) to activate the cGAS-STING-mediated effectors to generate type 1 interferons and other nuclear factor (NF)-kB-dependent cytokines, regardless of the sequence [100,104,105]. In addition to NF-kB, mitogen-activated protein kinase (MAPK), and signal transducer and activator of transcription 6 (STAT6) activation, STING stimulates the autophagosome formation by facilitating the microtubule-associated protein 1A/1B-light chain 3 (LC3) puncta formation and the autophagy related (Atg) 9a, upon recognizing the cytosolic dsDNA [106,107,108,109]. Beclin-1 (BECN1) interacts with cGAS to restrict cGAMP formation in response to cytosolic dsDNA, by inhibiting the interaction between cGAS and dsDNA. The interplay between cGAS and BECN1 results in the release of Rubicon (negative regulator of autophagy) from BECN1, which activates the class III phosphatidylinositol 3-kinase function to induce autophagy and hence eliminate cytosolic dsDNA [110]. One of the main functions of autophagy is to eliminate cfDNA without causing inflammatory damage. The defected autophagy enhances the inflammatory recognition of cfDNA by various cytosolic PRRs [110].
TLR9 is present in the endoplasmic reticulum (ER), during normal physiologic stages. However, when cytosolic cytosine-phosphate-guanine (CpG)-DNAs or self-DNA enter the endosome or endolysosome, TLR9 migrates to these organelles and recognizes them as essential DAMPs [111,112]. In order to cause inflammation and inflammatory diseases, the TLR9 activation induces a myeloid differentiation primary response 88 (MyD88)-dependent downstream signaling pathway that activates the IRF3-based type1-interferon production and NF-kB-mediated pro-inflammatory cytokine production [113]. The Toll-interleukin-1 receptor (TIR) domain of MyD88 activates the interleukin 1 receptor-associated kinase (IRAK)-4 and IRAK-1 [114,115]. IRAK-4 recruits the tumor necrosis factor receptor-associated factor 6 (TRAF6) to activate the transforming growth factor-β-activated kinase 1 (TAK1) [116]. TAK1 phosphorylates the IκB kinase (IKK) complex via the K63-linked ubiquitination of the NF-kB essential modulator (NEMO), which is crucial for the NF-kB, IRF3, and MAPK signaling [117]. TLR9 recognizes two types of DNA (i.e., pathogen-derived and self-DNA). It was shown that the nucleotide sequence, length, and dimerization properties of synthetic CpG-oligodeoxyribonucleotides (ODNs) and cfDNAs determine their tendency to bind and activate TLR9 [118,119,120]. The intracellular compartmentalization of TLR9 is a mechanism for discriminating between self- and non-self-DNAs [121]. Their binding results in an increase in the dimerization and activation [121].
Platelets are known to express PRRs, which can be triggered upon interaction with DAMPs [122]. Platelets from both murine and human hosts express TLR9 [123,124], which is of importance because, in addition to their hemostatic function, platelets play a crucial role in bridging innate and adaptive immunological responses [122]. Platelet activation results in the platelet production of P-selectin, which enables platelets to attach to other cells, such as granulocytes, leading to the granulocyte activation and recruitment to sites of tissue damage. Platelets are activated by cfDNA, which contributes to the creation of neutrophil extracellular traps (NETs) [122].
AIM2 is an ALR that is activated upon recognizing and binding to self-DNA entering the cytosol, as a result of cellular damage and exosomes containing self-DNA [125]. AIM2 efficiently activates in response to 80–300 base pair self-DNA [126,127]. The HIN (hematopoietic expression, interferon-inducible nature, and nuclear localization) domain of AIM2 recognizes cytosolic DNA, and its pyrin domain (PYD) interacts with the PYD of ASC (apoptosis-associated speck-like protein containing a C-terminal caspase recruitment domain) to form an inflammasome complex that converts procaspase 1 (pro-CASP1) to CASP1 [126,128]. CASP1 releases IL-1 and IL-18 from their preforms [128]. CASP1 also cleaves the Gasdermin D (GSDMD) linker region, finally mediating the release of IL-1 and IL-18 from cells. Additionally, the K+ efflux from the GSDMD pore inhibits the cGAS activity and the cGAS-STING-mediated release of type 1 IFN, as well as induces pyroptosis [129,130,131]. The AIM2-induced GSDMD functions as a negative regulator of type 1 interferon production mediated by cGAS-STING [125]. In addition, the AIM2-ASC inflammasome inhibits the STING-TBK1 (TRAF family member-associated NF-κB activator-binding kinase 1) interaction required for the IRF3-dependent release of type 1 interferons [131,132]. In the absence of certain cytosolic DNAs, AIM2 remains inactive [132]. A schematic representation of the cfDNA recognition and consequent pathway activation is shown in Figure 2.

5. Cell-Free DNA-Mediated Inflammatory Disorders

The CfDNA-induced inflammation is a pathogenic factor in several diseases. The activation of TLR9, which releases type 1 interferons via cfDNA, increases liver inflammation in metabolic liver diseases (e.g., non-alcoholic steatohepatitis /NASH/ or non-alcoholic fatty liver disease /NAFLD/) by accelerating the non-apoptotic death of hepatocytes [133]. The modulation of high mobility group box 1 (HMGB1) in NASH prevents weight gain and liver inflammation, indicating that TLR9 recognizes the self-DNA bound to HMGB1 in C57BL/6 mice fed a high-fat diet [134]. Dietary steatohepatitis is exacerbated by the TLR9 activation, which upregulates the AIM2 expression and the IL-1β production [135]. In ischemia-reperfusion-induced hepatitis, the AIM2 stimulation in Kupffer cells in response to oxidized mitochondrial cfDNA, also plays a critical role [131,136]. In NASH and NAFLD [137,138], as well as in alcoholic liver disease [139,140], the cGAS-STING system (mainly in Kupffer cells) recognizes mitochondrial cfDNA as a DAMP, which can lead to inflammation and fibrosis.
The TLR9-mediated identification of cfDNA plays a crucial role in the inflammation and insulin resistance index associated with obesity. The level of circulating endogenous cfDNA rises in obese individuals, patients with visceral obesity, and mice fed a high-fat diet [141,142]. The increased circulating endogenous host-derived cfDNAs enhance the accumulation of pro-inflammatory M1 macrophages in adipose tissues upon recognition by TLR9 [142].
Mitochondrial cfDNA may also play a role in obesity, caused by a high-fat diet, since the knockout of STING prevents obesity in mice [143]. In adipocytes, the stress-induced mitochondrial cfDNA release activates phosphodiesterases (PDE3B/4), which causes a decrease in the cAMP levels and the inhibition of protein kinase A signaling, ultimately resulting in a decreased thermogenesis [144]. When a high-fat diet containing palmitic acid is used, the mitochondrial cfDNA-induced cGAS-STING signaling also occurs in endothelial cells, which leads to adipose tissue inflammation, obesity, glucose intolerance, and insulin resistance [144,145].
Atherosclerosis is also related to the cfDNA-mediated TLR9-signaling. According to studies conducted on animals, the angiotensin II infusion increases the plasma concentration of self-DNA recognized by TLR9 expressed on immune cells, such as macrophages, which secrete proinflammatory cytokines promoting atherogenesis in the aortic arch [146]. By turning on the p38MAPK pathway, the TLR9 activation in apolipoprotein E-deficient macrophages worsens the inflammation [146]. Electronic cigarette use has also been demonstrated to raise the level of mitochondrial cfDNA in the blood and induce the expression of TLR9, both of which increase the expression of proinflammatory cytokines in monocytes and macrophages and thereby contribute to the development of atherosclerosis [147]. Circulating cfDNA binding to TLR9 increases, in conjunction with HMGB1 binding [148]. Studies have shown that patients with coronary artery disease (CAD) have higher circulating levels of HMGB1, which is associated with the non-calcified plaque burden in stable CAD patients [148,149]. HMGB1 levels are also linked to CAD in non-diabetic and type 2 diabetes mellitus patients [149,150]. The AIM2 activation may also be involved in the pathophysiology of atherosclerosis. The intravenous administration of poly(dA:dT) (deoxyadenylic-deoxythymidylic) acid, a synthetic analog of the canonical right-handed DNA helix, also known as B-DNA, results in the release of AIM2-dependent proinflammatory cytokines that disrupt the carotid artery reendothelialization [151]. Furthermore, subcutaneous poly(dA: dT) injection activates AIM2, causing the atherosclerotic plaque formation, an increased reactive oxygen species (ROS) production, and the endothelial microparticle release in ApoE-/-mice [151].
Murine models have demonstrated that endosomal TLRs (i.e., TLR7 and TLR9) play a crucial role in SLE and related systemic autoimmune diseases [152,153]. The spontaneous generation of autoantibodies against self-DNA in autoreactive B cells is facilitated by the TLR9 signaling coupled with the B cell receptor signaling [154,155]. The TLR9 deficiency, moreover, worsens SLE, due to the profound activation of lymphocytes and plasmacytoid dendritic cells, as well as an increase in serum immunoglobulin G and IFNα levels [152]. In addition, TLR9 has no effect on the progression of lupus nephritis in susceptible mice [152].
The role of STING in SLE is, however, controversial [156]. Loss of function mutations in the extracellular DNAse1L3 lead to the accumulation of DNA/RNA-associated microparticles in the circulation [157,158]. The genetic deletion of DNAse1L3 in mice causes a disease that is similar to SLE [159]. This disease is caused by a mechanism that depends on TLR7 and TLR9 but not STING [160]. Experimental findings indicate that SLE is driven by extracellular DNA delivered to endosomal TLRs via receptors, such as the B cell receptor, LL37, or FcγRs [156], whereas monogenic autoinflammatory diseases (e.g., Aicardi–Goutières syndrome; type I interferonopathy due to a DNase II deficiency) are driven by the abnormal accumulation of DNA in the cytosol, which is detected by the cGAS/STING pathway [161,162].
The cGAS-STING signaling induced by cfDNA also plays a pivotal role in a variety of sterile inflammatory diseases in humans (including ataxia-telangiectasia, familial amyotrophic lateral sclerosis, frontotemporal dementia, STING-associated vasculopathy with the onset of infancy, erosive inflammatory arthritis, psoriasis, Bloom syndrome, and Huntington’s disease) [138,163,164,165] and in murine experimental autoimmune encephalitis [164].
Alterations of the negative regulators (e.g., protein phosphatase 6 catalytic subunit of protein phosphatase 6, immunity-related GTPase M, Myb-like, SWIRM, and MPN domains 1 protein /MYSM1/) of the cGAS-STING signaling pathway could also lead to the development of human autoimmune diseases [166,167,168,169]. Monocytes isolated from the peripheral blood of SLE patients express less MYSM1 but produce more type 1 interferons [169]. MYSM1 binds to STING and inhibits the cGAS-STING signaling pathway [169]. Furthermore, MYSM1 inhibits inflammation mediated by NOD2 (nucleotide-binding oligomerization domain-containing protein 2), CARD15 (caspase recruitment domain-containing protein 15), or IBD1 (inflammatory bowel disease protein 1), by inactivating the receptor interacting protein 2 (RIP2) complex, thereby preventing the formation of the NOD2-RIP2 complex, which is essential for the inflammatory signaling pathway [170].

6. Cell-Free DNA as a Possible Modulator of Sterile Inflammation

In light of what has been discussed thus far, it is clear that the recognition of cfDNA by PRRs plays an important part in the pathogenesis of a wide variety of sterile inflammatory diseases. Based on these, it makes sense to try using cfDNA as an immunomodulator to change the course of inflammation (Figure 1).
Inflammatory bowel diseases (IBDs) are caused by a dysfunctional mucosal immune response to intestinal microbiota and other luminal antigens. Traditional IBD treatments primarily target aberrant immune responses and inflammatory cascades. However, some of these treatments have limited efficacy and can cause severe side effects. Dextran sulfate sodium (DSS)-colitis, an experimental mouse model of inflammatory bowel disease (IBD), is particularly useful for studying the contributions of the innate immune system (including TLR9-signaling) to the pathomechanism and therapy of colitis [171,172]. The amount of cfDNA is correlated with the severity of the intestinal inflammation in mice with chemically-induced colitis [173]. In experimental murine colitis, the beneficial therapeutic effects of orally administered immunostimulatory DNA sequences and their synthetic oligonucleotide analogs have already been demonstrated [174,175]. In addition, the intraperitoneal (ip) administration of immunostimulatory TLR9-agonist DNA sequences protects mice from DSS-induced colitis via the induction of indoleamine 2,3 dioxygenase-1 [176,177]. It is commonly reported that an ip injection is as effective as an intravenous (iv) injection. However, it has also been demonstrated that the pharmacokinetics of ip DNA analogues are different from those of iv DNA analogues [178,179]. The local administration of a TLR-agonist synthetic oligonucleotide sequence (DIMS0150) in humans has demonstrated clinical efficacy by restoring the glucocorticoid sensitivity, but the colonoscopy-based therapy administration is challenging [180,181,182,183,184]. Consequently, an easier and more convenient route of drug administration (orally or parenterally) will be necessary in the future. To our knowledge, we were among the first to investigate the biological effects of iv administered cfDNA in a therapeutical setting in a mouse model of DSS-colitis.
In a murine DSS-colitis experiment, in which the therapeutic efficacy of iv-administered cfDNA was evaluated [185], we discovered that, under inflammatory conditions, the systemic administration of colitis-derived cfDNA can decrease the clinical and histological severity of DSS-induced murine colitis, possibly by modifying the proinflammatory cytokine expression and the TLR9-related signaling. The subsequent presence of a markedly inflammatory environment, likely caused by the induction of severe colitis, may result in cfDNA with the potential to promote the suppression of inflammation and enhance tissue regeneration.
The connection between TLRs and autophagy, in response to DAMPs has been verified by a number of studies [186,187]. This regulatory cross-talk between them partly serves to trigger the innate immune system. Concerning the TLR9-autophagy linkage in murine DSS-colitis, we have demonstrated for the first time that the final, sometimes beneficial effect of iv administered cfDNA on the autophagy response, depends on two factors: i., the origin of the cfDNA (i.e., inflammatory or non-inflammatory) and ii., the local immunobiological milieu (i.e., inflammatory or not), as well [188].
Based on how cfDNA affects the immune system, it is evident that many studies have been performed to find out what role the DNA-sensing pathway plays in inflammation, by generating and using synthetic ODN sequences. There are numerous subtypes of TLR9 activating/inhibitory synthetic ODNs [189,190]. Type-A CpG-ODNs frequently form large multimeric aggregates spontaneously and are consequently retained in the early endosomes of plasmacytoid dendritic cells (pDCs) for relatively long periods, resulting in the prolonged activation of the signal-transducing complex and the robust IFNα production. Type-B CpG-ODNs, in contrast, stay monomeric and are rapidly transported from early to late endosomes, making them potent B and NK cell stimulators. Type-C ODNs exhibit mixed characteristics; they function as potent stimulators of pDCs’ IFNα production, the antigen presenting cell activation and maturation, indirect NK cell activation, and direct B cell stimulation [189].
In the early stages of RA, it appears that the T cell-dependent B cell activation is necessary for the rheumatoid factor (RF) production. Nonetheless, later in the course of the disease (i.e., after five years), when the majority of patients received immunosuppressive disease-modifying drugs, a dissociation between the T cell reactivity and the RF status was observed [191]. This suggests that T cells are no longer needed for B cells to generate RF. RF and cytokines produced by B cells and monocytes are associated with an increase in the later phase of RA, as a result of the CpG-ODN treatment of peripheral mononuclear blood cells of RA patients. This suggests that B cells (including the RF-producing B cells) may lose their dependence on the T cells. The TLR agonistic CpG-ODNs can maintain the polyclonal memory B cell populations [192], and the patient’s own IgG/cfDNA complexes can activate the B cells effectively [155]. Consequently, as RA progresses, the cfDNA-dependent B cell antibody production increases. It has also been demonstrated that the injection of the human TLR9 agonist CpG-ODN2006 into the articular cavity of mice, led to the development of acute arthritis [193]. Similar to CpG-ODN2006, a CpG motif-rich RA-associated ODN induces joint arthritis [90,194].
In a murine model of Sjögren’s syndrome [195], it was demonstrated that activation of TLR9 by BL-7040 (an antisense ODN against acetylcholinesterase mRNA) results in the non-canonical activation of NF-kB, thereby enhancing the salivary function and suppressing inflammation.
Furthermore, by stimulating the Th1 immune response, early (i.e., one week of age) the CpG-ODN treatment prevented the development of the Th2-driven scleroderma-like syndrome in tight-skin mice [196]. However, delaying the CpG-ODN treatment until six weeks of age was ineffective in preventing the skin disease [196].
Using CpG-ODNs, the pathogenetic role of cfDNA sensing was also highlighted in antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAVs). Circulating ANCA-autoreactive B cells are present in patients with AAVs. Upon stimulation with unmethylated CpG-ODNs, these cells produced ANCA [197]. It cannot be ruled out that stimulating ANCA-autoreactive B cells with CpG-ODNs of other cfDNAs may be a link between infection and AAVs.
The administration of an immunoregulatory GpG-ODN (with a single base switch from CpG to GpG) can reduce the severity of Th1/Th17-mediated EAE in mice [198]. The GpG-ODN inhibited Th1 cytokine production and decreased the expression of the co-stimulatory and MHC molecules by antigen-presenting cells. The GpG-ODN changed the phenotype of autoreactive Th1 cells to a protective Th2 phenotype and the isotype switching of the autoreactive B cells to a protective IgG1 isotype [199]. In addition, the protective mechanism of the GpG-ODN treatment in the NZB/W lupus nephritis model was demonstrated. This mechanism modifies the cytokine profiles of the T cells and activates the B lymphocytes via the inhibition of TLRs, such as TLR-7 and TLR-9 [200].
Based on the above, it can be seen that the immunomodulatory, anti- or proinflammatory effect of cfDNA and synthetic ODNs depends not only on the structure and origin, but also on the time of application (i.e., early vs. later age of a given disease). Furthermore, there is evidence that applying cfDNA as a “preconditioning treatment” before the initiation of inflammation, can ameliorate the inflammatory process and reduce the degree of tissue damage. We found that preconditioning with a single iv dose of colitis-derived cfDNA ameliorated the clinical and histological severity of murine DSS-colitis, as compared to cfDNA of non-colitic origin [201]. In this experimental setting, the TLR9-signaling and inflammation-related gene expressions were altered in a clinically favorable manner. Additionally, in continuation of this experimental setup, we also found that the preconditioning by iv colitic cfDNA, the activation of cell protective autophagy can be achieved in mice with DSS-colitis [202].

7. Cell-Free DNA in Tumors

Since the landmark works of Colotta [203], Hanahan, and Weinberg [204,205], chronic inflammation has been recognized as a hallmark of cancer. Numerous studies have demonstrated that the concentration of cfDNA in the blood of patients with several types of tumorous diseases is elevated. One of the attributes of cfDNA is its ability to induce inflammation. Hence, it seems logical to investigate the carcinogenic role of cfDNA-induced inflammation.
Cell-free DNA sensing by TLR9 has dual-faced effects on tumor cells. In human colorectal cancer (CRC) tissues, the TLR9 overexpression was detected [206]. By adding colon cancer cell-derived cfDNA or the TLR9 agonist CpG-ODN2395 to CRC cell lines, researchers found that the TLR9-MyD88 signaling boosted cell growth, migration, invasion, and IL8 secretion [206]. It has been reported that cfDNA is released from breast cancer primarily through the active secretion and that cfDNA can stimulate the proliferation of hormone-receptor positive breast cancer cells by activating the TLR9-NF-kB-cyclin D1 pathway [207]. Contrarily, it has been demonstrated that host TLR9 after sensing tumor cfDNA modulates the anti-tumor immunity in response to chemotherapy. TLR9 promotes the maturation and migration of DCs from the tumor microenvironment to regional lymph nodes, where DCs activate tumor-specific cytotoxic T lymphocytes, leading to potent anti-tumor effects [208].
During normal mitosis, the nucleosome inhibits the cGAS activation, in response to dsDNA through a competitive inhibition, and cGAS-STING signaling is not fully functional [209]. A low level of cGAS-STING signaling causes phosphorylation and the accumulation of IRF3 during mitotic arrest. This does not increase the production of type 1 interferon, thus does not cause inflammation, but at the same time, it results in apoptotic cell death [209]. Some anti-cancer medications, such as taxol, paclitaxel, or taxane, function in this way [209,210]. Sometimes, the cGAS-STING overexpression in certain tumors decreases the inflammatory immune cell infiltration, resulting in a poor prognosis [210]. The cGAS downregulation in patients with lung adenocarcinoma is also associated with an increase in mortality [211]. Further evidence suggests that the cGAS-STING signaling is important in the immune environment of various tumor microenvironments [212,213]. The activation of the STING signaling pathway improves the immunotherapy’s protective effects [212] and increases the potent tumoricidal T cell-mediated immune response [213]. In mouse models, the nuclear paraspeckle assembly transcript 1 inhibits the cGAS-STING signaling and cytotoxic T cell infiltration into the tumor microenvironment, thereby promoting tumor growth [214].
AIM2 plays an antitumor role in tumor diseases independently of the inflammasome activation [100,215]. This can be confirmed in chemically induced colitis-associated cancer [215], hereditary nonpolyposis colorectal cancer [216], and cutaneous squamous cell carcinoma [217]. At the same time, AIM2 promotes non-small cell lung cancer tumor growth by modifying the mitochondrial dynamics [218,219]. AIM2 also has protumor effects in oral squamous cell carcinoma [220], the start and spread of benign prostate hyperplasia [221], and chemically-induced hepatic cell carcinoma (HCC) [222]. However, in HCC, AIM2 can also displays antitumor properties [223].
The genometastatic hypothesis [224] is accepted as a model that could explain the experimental data inconsistencies concerning the metastasis formation [225]. The ability of tumor-derived cfDNA, including fragments of oncogenes, to behave in similar fashion to oncoviruses, provides an alternative route for the metastasis spread [226,227,228]. This hypothesis has been strengthened by the discovery of a DNA-containing secretome and data proving the horizontal DNA transfer between numerous different in vitro cells and organisms [229].
To prove the existence of genometastasis, human CRC-derived cfDNA containing KRAS, TP53, and HBB gene mutation fragments was isolated [225]. Following 20 days of incubation with this cfDNA, the NIH-3T3 murine tumor cells devoid of this mutant gene pattern were injected subcutaneously into NOD-SCID mice. In aggressive tumors developed from the “transformed” murine tumor cells, the mutant KRAS gene sequences were identified. In a similar experiment with human adipose tissue stem cells as recipients of tumorous cfDNA, however, neither mutant forms of the studied genes nor the tumor formation were observed [225]. In addition, the role of tumor-derived cfDNA in the malignant transformation has been proven in other cell cultures and animal models as well [227,228,230,231].
Regarding the formation of NETs (in which granulocytes release their own DNA decorated with the pathogen catching and killing granules into the extracellular environment) [232], it has been shown that tumor development and metastasis are accompanied by the excessive NET formation, which enhances adhesion, invasion, and sometimes immune escape [233]. In addition to serving as a scaffold and a trapping element, DNA also acts via the CCDC25 receptor binding. Through the TLR4–TLR9 pathway, HMGB1 and neutrophil granule components, such as neutrophil elastase and ROS, activate tumor cells [234].
Alternatively, some evidence suggests that the NET deposition in tumor tissue may have a cytotoxic effect. Researchers discovered that NETs inhibited the growth of cancer cells by inducing apoptosis in Caco-2 and AML cells and by inhibiting the migration and survival of melanoma cells [235,236]. In a CT-26 murine intestinal adenocarcinoma model, the oncolytic vesicular stomatitis virus caused an inflammatory response that included blood clotting in the tumor’s blood vessels that was caused by neutrophils and probably spread by NETs [237]. Table 1 summarizes the putative impacts of cfDNA on tumor formation.

8. Modification of Cell-Free DNA to Influence the Tumor Cell Phenotype

Considering what has been discussed up to this point, it is clear that the structure and origin of cfDNA influence the biological effect it induces. By artificially modifying and then reintroducing self-DNA from tumor cells, the effects on tumor cell viability, metabolic activity, and proliferation were also investigated. In vitro cellular models lacked both the tumor microenvironment and the immune system of the tumor-bearing host. As a result, they enabled us to investigate the pathobiological effects of self-DNA administration in HT29 colon cancer cells.
Different degrees of self-DNA methylation and fragmentation, or their combination, influenced the gene expression of specific TLR9 signaling components and the expression of cytokeratin 20, which indicated the differentiation of undifferentiated HT29 cells [238].
In our next experiment [239], we provided evidence for a close existing interplay between the TLR9-signaling and the autophagy response with remarkable influences on the tumor cell survival in HT29 colon cancer cells, subjected to intact or modified self-DNA treatments. Interestingly, we also found the colonosphere formation with a strong cytoplasmatic CD133 immunoreactivity only in artificially hypermethylated DNA-treated HT29 cells. This phenomenon could indicate the survival of some cancer cells with a stem-like phenotype.
Further, we analyzed the complex interrelated roles of the hepatocyte-derived growth factor receptor (HGFR) inhibition and TLR9/autophagy signaling in HT29 cells subjected to modified self-DNA treatments [240]. We found that the metabolic activity and proliferation of the tumor cells altered according to the used DNAs and inhibitors. The non-modified genomic DNA, HGFR inhibitor, and chloroquine (autophagy inhibitor) reduced cell growth the most. In this situation, the proliferation-stimulating effect of the signal transducer and activator of transcription (STAT)3 overexpression might be offset by LC3B, demonstrating the HGFR-mTOR (mammalian target of rapamycin)-ULK1 (Unc-51 like autophagy activating kinase 1) involvement in the HGFR inhibitor-mediated autophagy. On the contrary, the hypermethylated DNA, TLR9 inhibitor, and HGFR inhibitor co-administration increased the tumor cell proliferation.
In another study [241], we discovered that the tumorous self-DNA and insulin-like growth factor 1 receptor (IGF1R) inhibition display anti-proliferative properties that can be suppressed by inhibiting the TLR9 signaling. The different effects of the IGF1R, TLR9, and autophagy inhibitors on the HT29 cell proliferation and autophagy suggest that the IGF1R-associated and non-IGF1R-associated autophagy machinery are “Janus-faced” regarding cell proliferation. Autophagy induced by self-DNA and inhibitors also resulted in the survival of CD133-positive HT29 stem-like cancer cells, which may play a role in the CRC recurrence.

9. Conclusions

PRRs that recognize cfDNA play a crucial role in maintaining cell homeostasis. Under normal conditions, the host’s DNA is found in the nucleus and mitochondria, which promotes the development of self-tolerance. When cells or tissues undergo stressful conditions, their genetic material is released into the cytosol, due to mitochondrial or nuclear damage. Thus, their recognition by PRRs becomes possible, and they represent a potential threat to the maintenance of homeostasis. The recognition of cytosolic DNA by TLR9 depends on its CpG content, while in the case of cGAS, it mainly depends on its length and curvature. AIM2 recognizes its own DNA as well as DNA from the pathogen, regardless of the CpG content. Since the activation of AIM2 inhibits the cGAS-STING signaling through the GSDMD production in a manner dependent on the type 1 interferon production, it is hypothesized that it has evolved as a negative regulator of excessive inflammation in response to the cGAS activation. Further studies are necessary to reveal the connections and unknown regulatory processes between the DNA-sensing receptors and sterile inflammation, as well as the development of cancer.
In addition to the biomarker and diagnostic roles of cfDNA, further investigation of the immunomodulatory and therapeutic effects of cfDNA is definitely necessary. The creation of new types of combined HGFR, IGF1R, autophagy, and/or TLR9 signaling inhibitors would play a significant role in the development of personalized antitumor therapies. Further research is required to investigate the biological effects of modified own DNA fragments, inhibitory or stimulating CpG-ODNs, as the methylation status or the length of the fragment can also influence the experimental results. However, the present experiments need to be further tested in other cell lines expressing TLR9 (and other DNA-sensing PRRs).

Author Contributions

G.M., B.B.B., O.S., V.H. and F.S. performed the majority of the writing, editing, and coordinated the writing of the paper. B.B.B., O.S. and V.H. prepared the figures, performed the data acquisition, and contributed to the writing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mandel, P.; Metais, P. Les acides nucléiques du plasma sanguin chez l’homme. C. R. Seances Soc. Biol. Fil. 1948, 142, 241–243. [Google Scholar] [PubMed]
  2. Tan, E.M.; Schur, P.H.; Carr, R.I.; Kunkel, H.G. Deoxybonucleic acid (DNA) and antibodies to DNA in the serum of patients with systemic lupus erythematosus. J. Clin. Investig. 1966, 45, 1732–1740. [Google Scholar] [CrossRef] [PubMed]
  3. Leon, S.A.; Shapiro, B.; Sklaroff, D.M.; Yaros, M.J. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Res. 1977, 37, 646–650. [Google Scholar] [PubMed]
  4. Lo, Y.M.; Corbetta, N.; Chamberlain, P.F.; Rai, V.; Sargent, I.L.; Redman, C.W.; Wainscoat, J.S. Presence of fetal DNA in maternal plasma and serum. Lancet 1997, 350, 485–487. [Google Scholar] [CrossRef]
  5. Palomaki, G.E.; Kloza, E.M.; Lambert-Messerlian, G.M.; Haddow, J.E.; Neveux, L.M.; Ehrich, M.; van den Boom, D.; Bombard, A.T.; Deciu, C.; Grody, W.W.; et al. DNA sequencing of maternal plasma to detect Down syndrome: An international clinical validation study. Genet. Med. 2011, 13, 913–920. [Google Scholar] [CrossRef] [PubMed]
  6. Hill, M.; Barrett, A.N.; White, H.; Chitty, L.S. Uses of cell free fetal DNA in maternal circulation. Best Pract. Res. Clin. Obs. Gynaecol. 2012, 26, 639–654. [Google Scholar] [CrossRef]
  7. Banflavi, G.; Szyfter, K.; Antoni, F. Analysis of 5′-ends of short DNA fragments excreted by phytohemagglutinin stimulated lymphocytes. Biochem. Biophys. Res. Commun. 1984, 118, 140–146. [Google Scholar] [CrossRef]
  8. Ranucci, R. Cell-Free DNA: Applications in Different Diseases. Methods Mol. Biol. 2019, 1909, 3–12. [Google Scholar]
  9. Spisák, S.; Solymosi, N.; Ittzés, P.; Bodor, A.; Kondor, D.; Vattay, G.; Barták, B.K.; Sipos, F.; Galamb, O.; Tulassay, Z.; et al. Complete genes may pass from food to human blood. PLoS ONE 2013, 8, e69805. [Google Scholar] [CrossRef] [Green Version]
  10. Bronkhorst, A.J.; Ungerer, V.; Holdenrieder, S. The emerging role of cell-free DNA as a molecular marker for cancer management. Biomol. Detect. Quantif. 2019, 17, 100087. [Google Scholar] [CrossRef]
  11. Shin, S.H.; Park, W.Y.; Park, D. Characterization of DNA lesions associated with cell-free DNA by targeted deep sequencing. BMC Med. Genom. 2021, 14, 192. [Google Scholar] [CrossRef]
  12. Murao, A.; Aziz, M.; Wang, H.; Brenner, M.; Wang, P. Release mechanisms of major DAMPs. Apoptosis 2021, 26, 152–162. [Google Scholar] [CrossRef]
  13. Fenech, M.; Kirsch-Volders, M.; Natarajan, A.T.; Surralles, J.; Crott, J.W.; Parry, J.; Norppa, H.; Eastmond, D.A.; Tucker, J.D.; Thomas, P. Molecular mechanisms of micronucleus, nucleoplasmic bridge and nuclear bud formation in mammalian and human cells. Mutagenesis 2011, 26, 125–132. [Google Scholar] [CrossRef] [Green Version]
  14. Kustanovich, A.; Schwartz, R.; Peretz, T.; Grinshpun, A. Life and death of circulating cell-free DNA. Cancer Biol. Ther. 2019, 20, 1057–1067. [Google Scholar] [CrossRef] [Green Version]
  15. Bronkhorst, A.J.; Wentzel, J.F.; Aucamp, J.; van Dyk, E.; du Plessis, L.; Pretorius, P.J. Characterization of the cell-free DNA released by cultured cancer cells. Biochim. Biophys. Acta 2016, 1863, 157–165. [Google Scholar] [CrossRef] [Green Version]
  16. Martignano, F. Cell-Free DNA: An Overview of Sample Types and Isolation Procedures. Methods Mol. Biol. 2019, 1909, 13–27. [Google Scholar]
  17. Kılınç, N.; Onbaşılar, M.; Çayır, A. Evaluation of circulating cell-free nucleic acids in health workers occupationally exposed to ionizing radiation. Environ. Sci. Pollut. Res. Int. 2022, 29, 40543–40549. [Google Scholar] [CrossRef]
  18. Zhong, Y.; Fan, Q.; Zhou, Z.; Wang, Y.; He, K.; Lu, J. Plasma cfDNA as a Potential Biomarker to Evaluate the Efficacy of Chemotherapy in Gastric Cancer. Cancer Manag. Res. 2020, 12, 3099–3106. [Google Scholar] [CrossRef]
  19. Kadam, S.K.; Farmen, M.; Brandt, J.T. Quantitative measurement of cell-free plasma DNA and applications for detecting tumor genetic variation and promoter methylation in a clinical setting. J. Mol. Diagn. 2012, 14, 346–356. [Google Scholar] [CrossRef]
  20. Hassan, S.; Shehzad, A.; Khan, S.A.; Miran, W.; Khan, S.; Lee, Y.S. Diagnostic and Therapeutic Potential of Circulating-Free DNA and Cell-Free RNA in Cancer Management. Biomedicines 2022, 10, 2047. [Google Scholar] [CrossRef]
  21. MacKinnon, H.J.; Kolarova, T.R.; Katz, R.; Hedge, J.M.; Vinopal, E.; Lockwood, C.M.; Shree, R.; Delaney, S. The impact of maternal autoimmune disease on cell-free DNA test characteristics. Am. J. Obstet. Gynecol. MFM 2021, 3, 100466. [Google Scholar] [CrossRef] [PubMed]
  22. Feng, C.S.; Lu, B.Y.; Ju, H.H.; Pan, W.J. The failure of non-invasive prenatal testing due to maternal dermatomyositis. Prenat. Diagn. 2019, 39, 958–961. [Google Scholar] [CrossRef] [PubMed]
  23. Zhang, S.; Shu, X.; Tian, X.; Chen, F.; Lu, X.; Wang, G. Enhanced formation and impaired degradation of neutrophil extracellular traps in dermatomyositis and polymyositis: A potential contributor to interstitial lung disease complications. Clin. Exp. Immunol. 2014, 177, 134–141. [Google Scholar] [CrossRef] [PubMed]
  24. Hashimoto, T.; Ueki, S.; Kamide, Y.; Miyabe, Y.; Fukuchi, M.; Yokoyama, Y.; Furukawa, T.; Azuma, N.; Oka, N.; Takeuchi, H.; et al. Increased Circulating Cell-Free DNA in Eosinophilic Granulomatosis with Polyangiitis: Implications for Eosinophil Extracellular Traps and Immunothrombosis. Front. Immunol. 2022, 12, 801897. [Google Scholar] [CrossRef] [PubMed]
  25. Giaglis, S.; Daoudlarian, D.; Voll, R.E.; Kyburz, D.; Venhoff, N.; Walker, U.A. Circulating mitochondrial DNA copy numbers represent a sensitive marker for diagnosis and monitoring of disease activity in systemic lupus erythematosus. RMD Open 2021, 7, e002010. [Google Scholar] [CrossRef] [PubMed]
  26. Camuzi Zovico, P.V.; Gasparini Neto, V.H.; Venâncio, F.A.; Soares Miguel, G.P.; Graça Pedrosa, R.; Kenji Haraguchi, F.; Barauna, V.G. Cell-free DNA as an obesity biomarker. Physiol. Res. 2020, 69, 515–520. [Google Scholar] [CrossRef] [PubMed]
  27. Marcatti, M.; Saada, J.; Okereke, I.; Wade, C.E.; Bossmann, S.H.; Motamedi, M.; Szczesny, B. Quantification of Circulating Cell Free Mitochondrial DNA in Extracellular Vesicles with PicoGreen™ in Liquid Biopsies: Fast Assessment of Disease/Trauma Severity. Cells 2021, 10, 819. [Google Scholar] [CrossRef]
  28. Otawara, M.; Roushan, M.; Wang, X.; Ellett, F.; Yu, Y.M.; Irimia, D. Microfluidic Assay Measures Increased Neutrophil Extracellular Traps Circulating in Blood after Burn Injuries. Sci. Rep. 2018, 8, 16983. [Google Scholar] [CrossRef] [Green Version]
  29. Baumann, A.K.; Beck, J.; Kirchner, T.; Hartleben, B.; Schütz, E.; Oellerich, M.; Wedemeyer, H.; Jaeckel, E.; Taubert, R. Elevated fractional donor-derived cell-free DNA during subclinical graft injury after liver transplantation. Liver Transpl. 2022. [Google Scholar] [CrossRef]
  30. Urosevic, N.; Merritt, A.J.; Inglis, T.J.J. Plasma cfDNA predictors of established bacteraemic infection. Access Microbiol. 2022, 4, acmi000373. [Google Scholar] [CrossRef]
  31. Jing, Q.; Leung, C.H.C.; Wu, A.R. Cell-Free DNA as Biomarker for Sepsis by Integration of Microbial and Host Information. Clin. Chem. 2022, 68, 1184–1195. [Google Scholar] [CrossRef]
  32. Sugasawa, T.; Fujita, S.I.; Kuji, T.; Ishibashi, N.; Tamai, K.; Kawakami, Y.; Takekoshi, K. Dynamics of Specific cfDNA Fragments in the Plasma of Full Marathon Participants. Genes 2021, 12, 676. [Google Scholar] [CrossRef]
  33. Breitbach, S.; Tug, S.; Simon, P. Circulating cell-free DNA: An up-coming molecular marker in exercise physiology. Sports Med. 2012, 42, 565–586. [Google Scholar] [CrossRef]
  34. Konuralp Atakul, B.; Koc, A.; Adiyaman, D.; Kuyucu, M.; Sahingoz Yildirim, A.G.; Saka Guvenc, M.; Erdogan, K.M.; Sengul, B.; Oztekin, D.C. Could high levels of cell-free DNA in maternal blood be associated with maternal health and perinatal outcomes? J. Obstet. Gynaecol. 2020, 40, 797–802. [Google Scholar] [CrossRef]
  35. Bianchi, D.W.; Chudova, D.; Sehnert, A.J.; Bhatt, S.; Murray, K.; Prosen, T.L.; Garber, J.E.; Wilkins-Haug, L.; Vora, N.L.; Warsof, S.; et al. Noninvasive Prenatal Testing and Incidental Detection of Occult Maternal Malignancies. JAMA 2015, 314, 162–169. [Google Scholar] [CrossRef] [Green Version]
  36. Ashoor, G.; Syngelaki, A.; Poon, L.C.; Rezende, J.C.; Nicolaides, K.H. Fetal fraction in maternal plasma cell-free DNA at 11–13 weeks’ gestation: Relation to maternal and fetal characteristics. Ultrasound Obstet. Gynecol. 2013, 41, 26–32. [Google Scholar] [CrossRef]
  37. Han, D.S.C.; Ni, M.; Chan, R.W.Y.; Chan, V.W.H.; Lui, K.O.; Chiu, R.W.K.; Lo, Y.M.D. The Biology of Cell-free DNA Fragmentation and the Roles of DNASE1, DNASE1L3, and DFFB. Am. J. Hum. Genet. 2020, 106, 202–214. [Google Scholar] [CrossRef] [Green Version]
  38. Leffler, J.; Ciacma, K.; Gullstrand, B.; Bengtsson, A.A.; Martin, M.; Blom, A.M. A subset of patients with systemic lupus erythematosus fails to degrade DNA from multiple clinically relevant sources. Arthritis Res. Ther. 2015, 17, 205. [Google Scholar] [CrossRef] [Green Version]
  39. Barra, G.B.; Santa Rita, T.H.; de Almeida Vasques, J.; Chianca, C.F.; Nery, L.F.; Santana Soares Costa, S. EDTA-mediated inhibition of DNases protects circulating cell-free DNA from ex vivo degradation in blood samples. Clin. Biochem. 2015, 48, 976–981. [Google Scholar] [CrossRef] [Green Version]
  40. Bodaño, A.; Amarelo, J.; González, A.; Gómez-Reino, J.J.; Conde, C. Novel DNASE I mutations related to systemic lupus erythematosus. Arthritis Rheum. 2004, 50, 4070–4071. [Google Scholar] [CrossRef]
  41. Duvvuri, B.; Lood, C. Cell-Free DNA as a Biomarker in Autoimmune Rheumatic Diseases. Front. Immunol. 2019, 10, 502. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Hartl, J.; Serpas, L.; Wang, Y.; Rashidfarrokhi, A.; Perez, O.A.; Sally, B.; Sisirak, V.; Soni, C.; Khodadadi-Jamayran, A.; Tsirigos, A.; et al. Autoantibody-mediated impairment of DNASE1L3 activity in sporadic systemic lupus erythematosus. J. Exp. Med. 2021, 218, e20201138. [Google Scholar] [CrossRef] [PubMed]
  43. Felux, J.; Erbacher, A.; Breckler, M.; Hervé, R.; Lemeiter, D.; Mannherz, H.G.; Napirei, M.; Rammensee, H.G.; Decker, P. Deoxyribonuclease 1-Mediated Clearance of Circulating Chromatin Prevents from Immune Cell Activation and Pro-inflammatory Cytokine Production, a Phenomenon Amplified by Low Trap1 Activity: Consequences for Systemic Lupus Erythematosus. Front. Immunol. 2021, 12, 613597. [Google Scholar] [CrossRef] [PubMed]
  44. Gaipl, U.S.; Beyer, T.D.; Heyder, P.; Kuenkele, S.; Böttcher, A.; Voll, R.E.; Kalden, J.R.; Herrmann, M. Cooperation between C1q and DNase I in the clearance of necrotic cell-derived chromatin. Arthritis Rheum. 2004, 50, 640–649. [Google Scholar] [CrossRef] [PubMed]
  45. Fredi, M.; Bianchi, M.; Andreoli, L.; Greco, G.; Olivieri, I.; Orcesi, S.; Fazzi, E.; Cereda, C.; Tincani, A. Typing TREX1 gene in patients with systemic lupus erythematosus. Reumatismo 2015, 67, 1–7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Gillmore, J.D.; Hutchinson, W.L.; Herbert, J.; Bybee, A.; Mitchell, D.A.; Hasserjian, R.P.; Yamamura, K.; Suzuki, M.; Sabin, C.A.; Pepys, M.B. Autoimmunity and glomerulonephritis in mice with targeted deletion of the serum amyloid P component gene: SAP deficiency or strain combination? Immunology 2004, 112, 255–264. [Google Scholar] [CrossRef]
  47. Ogden, C.A.; Kowalewski, R.; Peng, Y.; Montenegro, V.; Elkon, K.B. IGM is required for efficient complement mediated phagocytosis of apoptotic cells in vivo. Autoimmunity 2005, 38, 259–264. [Google Scholar] [CrossRef]
  48. Janko, C.; Franz, S.; Munoz, L.E.; Siebig, S.; Winkler, S.; Schett, G.; Lauber, K.; Sheriff, A.; van der Vlag, J.; Herrmann, M. CRP/anti-CRP antibodies assembly on the surfaces of cell remnants switches their phagocytic clearance toward inflammation. Front. Immunol. 2011, 2, 70. [Google Scholar] [CrossRef] [Green Version]
  49. Saevarsdottir, S.; Steinsson, K.; Ludviksson, B.R.; Grondal, G.; Valdimarsson, H. Mannan-binding lectin may facilitate the clearance of circulating immune complexes-implications from a study on C2-deficient individuals. Clin. Exp. Immunol. 2007, 148, 248–253. [Google Scholar] [CrossRef]
  50. Jelin, A.C.; Sagaser, K.G.; Wilkins-Haug, L. Prenatal Genetic Testing Options. Pediatr. Clin. N. Am. 2019, 66, 281–293. [Google Scholar] [CrossRef]
  51. Papageorgiou, E.A.; Karagrigoriou, A.; Tsaliki, E.; Velissariou, V.; Carter, N.P.; Patsalis, P.C. Fetal-specific DNA methylation ratio permits noninvasive prenatal diagnosis of trisomy 21. Nat. Med. 2011, 17, 510–513. [Google Scholar] [CrossRef] [Green Version]
  52. Karakas, B.; Qubbaj, W.; Al-Hassan, S.; Coskun, S. Noninvasive Digital Detection of Fetal DNA in Plasma of 4-Week-Pregnant Women following In Vitro Fertilization and Embryo Transfer. PLoS ONE 2015, 10, e0126501. [Google Scholar] [CrossRef]
  53. Yu, S.C.; Lee, S.W.; Jiang, P.; Leung, T.Y.; Chan, K.C.; Chiu, R.W.; Lo, Y.M. High-resolution profiling of fetal DNA clearance from maternal plasma by massively parallel sequencing. Clin. Chem. 2013, 59, 1228–1237. [Google Scholar] [CrossRef] [Green Version]
  54. Rabinowitz, T.; Shomron, N. Genome-wide noninvasive prenatal diagnosis of monogenic disorders: Current and future trends. Comput. Struct. Biotechnol. J. 2020, 18, 2463–2470. [Google Scholar] [CrossRef]
  55. Yaşa, B.; Şahin, O.; Öcüt, E.; Seven, M.; Sözer, S. Assessment of Fetal Rhesus D and Gender with Cell-Free DNA and Exosomes from Maternal Blood. Reprod. Sci. 2021, 28, 562–569. [Google Scholar] [CrossRef]
  56. Gil, M.M.; Accurti, V.; Santacruz, B.; Plana, M.N.; Nicolaides, K.H. Analysis of cell-free DNA in maternal blood in screening for aneuploidies: Updated meta-analysis. Ultrasound Obstet. Gynecol. 2017, 50, 302–314. [Google Scholar] [CrossRef] [Green Version]
  57. Gerson, K.D.; O’Brien, B.M. Cell-Free DNA: Screening for Single-Gene Disorders and Determination of Fetal Rhesus D Genotype. Obstet. Gynecol. Clin. N. Am. 2018, 45, 27–39. [Google Scholar] [CrossRef]
  58. Chiu, E.K.L.; Hui, W.W.I.; Chiu, R.W.K. cfDNA screening and diagnosis of monogenic disorders—Where are we heading? Prenat. Diagn. 2018, 38, 52–58. [Google Scholar] [CrossRef] [Green Version]
  59. Ulrich, B.C.; Paweletz, C.P. Cell-Free DNA in Oncology: Gearing up for Clinic. Ann. Lab. Med. 2018, 38, 1–8. [Google Scholar] [CrossRef] [Green Version]
  60. Siravegna, G.; Mussolin, B.; Venesio, T.; Marsoni, S.; Seoane, J.; Dive, C.; Papadopoulos, N.; Kopetz, S.; Corcoran, R.B.; Siu, L.L.; et al. How liquid biopsies can change clinical practice in oncology. Ann. Oncol. 2019, 30, 1580–1590. [Google Scholar] [CrossRef] [Green Version]
  61. Domínguez-Vigil, I.G.; Moreno-Martínez, A.K.; Wang, J.Y.; Roehrl, M.H.A.; Barrera-Saldaña, H.A. The dawn of the liquid biopsy in the fight against cancer. Oncotarget 2017, 9, 2912–2922. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Guo, Q.; Wang, J.; Xiao, J.; Wang, L.; Hu, X.; Yu, W.; Song, G.; Lou, J.; Chen, J. Heterogeneous mutation pattern in tumor tissue and circulating tumor DNA warrants parallel NGS panel testing. Mol. Cancer 2018, 17, 131. [Google Scholar] [CrossRef] [PubMed]
  63. Li, J.; Dittmar, R.L.; Xia, S.; Zhang, H.; Du, M.; Huang, C.C.; Druliner, B.R.; Boardman, L.; Wang, L. Cell-free DNA copy number variations in plasma from colorectal cancer patients. Mol. Oncol. 2017, 11, 1099–1111. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Yu, D.; Liu, Z.; Su, C.; Han, Y.; Duan, X.; Zhang, R.; Liu, X.; Yang, Y.; Xu, S. Copy number variation in plasma as a tool for lung cancer prediction using Extreme Gradient Boosting (XGBoost) classifier. Thorac. Cancer 2020, 11, 95–102. [Google Scholar] [CrossRef] [PubMed]
  65. Willis, J.; Lefterova, M.I.; Artyomenko, A.; Kasi, P.M.; Nakamura, Y.; Mody, K.; Catenacci, D.V.T.; Fakih, M.; Barbacioru, C.; Zhao, J.; et al. Validation of Microsatellite Instability Detection Using a Comprehensive Plasma-Based Genotyping Panel. Clin. Cancer Res. 2019, 25, 7035–7045. [Google Scholar] [CrossRef]
  66. Müller, J.N.; Falk, M.; Talwar, J.; Neemann, N.; Mariotti, E.; Bertrand, M.; Zacherle, T.; Lakis, S.; Menon, R.; Gloeckner, C.; et al. Concordance between Comprehensive Cancer Genome Profiling in Plasma and Tumor Specimens. J. Thorac. Oncol. 2017, 12, 1503–1511. [Google Scholar] [CrossRef] [Green Version]
  67. Park, S.; Olsen, S.; Ku, B.M.; Lee, M.S.; Jung, H.A.; Sun, J.M.; Lee, S.H.; Ahn, J.S.; Park, K.; Choi, Y.L.; et al. High concordance of actionable genomic alterations identified between circulating tumor DNA-based and tissue-based next-generation sequencing testing in advanced non-small cell lung cancer: The Korean Lung Liquid Versus Invasive Biopsy Program. Cancer 2021, 127, 3019–3028. [Google Scholar] [CrossRef]
  68. Schmiegel, W.; Scott, R.J.; Dooley, S.; Lewis, W.; Meldrum, C.J.; Pockney, P.; Draganic, B.; Smith, S.; Hewitt, C.; Philimore, H.; et al. Blood-based detection of RAS mutations to guide anti-EGFR therapy in colorectal cancer patients: Concordance of results from circulating tumor DNA and tissue-based RAS testing. Mol. Oncol. 2017, 11, 208–219. [Google Scholar] [CrossRef] [Green Version]
  69. Phallen, J.; Sausen, M.; Adleff, V.; Leal, A.; Hruban, C.; White, J.; Anagnostou, V.; Fiksel, J.; Cristiano, S.; Papp, E.; et al. Direct detection of early-stage cancers using circulating tumor DNA. Sci. Transl. Med. 2017, 9, eaan2415. [Google Scholar] [CrossRef] [Green Version]
  70. Nesic, M.; Bødker, J.S.; Terp, S.K.; Dybkær, K. Optimization of Preanalytical Variables for cfDNA Processing and Detection of ctDNA in Archival Plasma Samples. Biomed. Res. Int. 2021, 2021, 5585148. [Google Scholar] [CrossRef]
  71. Bredno, J.; Lipson, J.; Venn, O.; Aravanis, A.M.; Jamshidi, A. Clinical correlates of circulating cell-free DNA tumor fraction. PLoS ONE 2021, 16, e0256436. [Google Scholar] [CrossRef]
  72. Cai, Z.; Chen, G.; Zeng, Y.; Dong, X.; Li, Z.; Huang, Y.; Xin, F.; Qiu, L.; Xu, H.; Zhang, W.; et al. Comprehensive Liquid Profiling of Circulating Tumor DNA and Protein Biomarkers in Long-Term Follow-Up Patients with Hepatocellular Carcinoma. Clin. Cancer Res. 2019, 25, 5284–5294. [Google Scholar] [CrossRef]
  73. Isaksson, S.; George, A.M.; Jönsson, M.; Cirenajwis, H.; Jönsson, P.; Bendahl, P.O.; Brunnström, H.; Staaf, J.; Saal, L.H.; Planck, M. Pre-operative plasma cell-free circulating tumor DNA and serum protein tumor markers as predictors of lung adenocarcinoma recurrence. Acta Oncol. 2019, 58, 1079–1086. [Google Scholar] [CrossRef] [Green Version]
  74. Chen, Z.; Liu, L.; Zhu, F.; Cai, X.; Zhao, Y.; Liang, P.; Ou, L.; Zhong, R.; Yu, Z.; Li, C.; et al. Dynamic monitoring serum tumor markers to predict molecular features of EGFR-mutated lung cancer during targeted therapy. Cancer Med. 2022, 11, 3115–3125. [Google Scholar] [CrossRef]
  75. Tarazona, N.; Gimeno-Valiente, F.; Gambardella, V.; Zuñiga, S.; Rentero-Garrido, P.; Huerta, M.; Roselló, S.; Martinez-Ciarpaglini, C.; Carbonell-Asins, J.A.; Carrasco, F.; et al. Targeted next-generation sequencing of circulating-tumor DNA for tracking minimal residual disease in localized colon cancer. Ann. Oncol. 2019, 30, 1804–1812. [Google Scholar] [CrossRef] [Green Version]
  76. Parsons, H.A.; Rhoades, J.; Reed, S.C.; Gydush, G.; Ram, P.; Exman, P.; Xiong, K.; Lo, C.C.; Li, T.; Fleharty, M.; et al. Sensitive Detection of Minimal Residual Disease in Patients Treated for Early-Stage Breast Cancer. Clin. Cancer Res. 2020, 26, 2556–2564. [Google Scholar] [CrossRef] [Green Version]
  77. Powles, T.; Assaf, Z.J.; Davarpanah, N.; Banchereau, R.; Szabados, B.E.; Yuen, K.C.; Grivas, P.; Hussain, M.; Oudard, S.; Gschwend, J.E.; et al. ctDNA guiding adjuvant immunotherapy in urothelial carcinoma. Nature 2021, 595, 432–437. [Google Scholar] [CrossRef]
  78. Keller, L.; Belloum, Y.; Wikman, H.; Pantel, K. Clinical relevance of blood-based ctDNA analysis: Mutation detection and beyond. Br. J. Cancer 2021, 124, 345–358. [Google Scholar] [CrossRef]
  79. Kakitsuka, Y.; Sawamura, S.; Kajihara, I.; Kanemaru, H.; Honda, N.; Makino, K.; Aoi, J.; Makino, T.; Fukushima, S.; Ihn, H. Elevated circulating cell-free DNA levels in autoimmune bullous diseases. J. Dermatol. 2020, 47, e345–e346. [Google Scholar] [CrossRef]
  80. Dunaeva, M.; Buddingh’, B.C.; Toes, R.E.; Luime, J.J.; Lubberts, E.; Pruijn, G.J. Decreased serum cell-free DNA levels in rheumatoid arthritis. Auto Immun. Highlights 2015, 6, 23–30. [Google Scholar] [CrossRef] [Green Version]
  81. Truszewska, A.; Wirkowska, A.; Gala, K.; Truszewski, P.; Krzemień-Ojak, Ł.; Perkowska-Ptasińska, A.; Mucha, K.; Pączek, L.; Foroncewicz, B. Cell-free DNA profiling in patients with lupus nephritis. Lupus 2020, 29, 1759–1772. [Google Scholar] [CrossRef] [PubMed]
  82. Xu, Y.; Song, Y.; Chang, J.; Zhou, X.; Qi, Q.; Tian, X.; Li, M.; Zeng, X.; Xu, M.; Zhang, W.; et al. High levels of circulating cell-free DNA are a biomarker of active SLE. Eur. J. Clin. Investig. 2018, 48, e13015. [Google Scholar] [CrossRef] [PubMed]
  83. Vajpeyee, A.; Wijatmiko, T.; Vajpeyee, M.; Taywade, O.; Pandey, S.; Chauhan, P.S. Clinical Usefulness of Cell-Free DNA as a Prognostic Marker in Acute Ischemic Stroke. Neurologist 2020, 25, 11–13. [Google Scholar] [CrossRef] [PubMed]
  84. Agiannitopoulos, K.; Samara, P.; Papadopoulou, E.; Tsamis, K.; Mertzanos, G.; Babalis, D.; Lamnissou, K. Study on the admission levels of circulating cell-free DNA in patients with acute myocardial infarction using different quantification methods. Scand. J. Clin. Lab. Investig. 2020, 80, 348–350. [Google Scholar] [CrossRef] [PubMed]
  85. Sanchis, J.; García-Blas, S.; Ortega-Paz, L.; Dantas, A.P.; Rodríguez, E.; Abellán, L.; Brugaletta, S.; Valero, E.; Miñana, G.; Garabito, M.; et al. Cell-free DNA and Microvascular Damage in ST-segment Elevation Myocardial Infarction Treated with Primary Percutaneous Coronary Intervention. Rev. Esp. Cardiol. 2019, 72, 317–323. [Google Scholar] [CrossRef]
  86. Agbor-Enoh, S.; Shah, P.; Tunc, I.; Hsu, S.; Russell, S.; Feller, E.; Shah, K.; Rodrigo, M.E.; Najjar, S.S.; Kong, H.; et al. Cell-Free DNA to Detect Heart Allograft Acute Rejection. Circulation 2021, 143, 1184–1197. [Google Scholar] [CrossRef]
  87. Truszewska, A.; Foroncewicz, B.; Pączek, L. The role and diagnostic value of cell-free DNA in systemic lupus erythematosus. Clin. Exp. Rheumatol. 2017, 35, 330–336. [Google Scholar]
  88. Lauková, L.; Konečná, B.; Vlková, B.; Mlynáriková, V.; Celec, P.; Šteňová, E. Anti-cytokine therapy and plasma DNA in patients with rheumatoid arthritis. Rheumatol. Int. 2018, 38, 1449–1454. [Google Scholar] [CrossRef]
  89. Rykova, E.; Sizikov, A.; Roggenbuck, D.; Antonenko, O.; Bryzgalov, L.; Morozkin, E.; Skvortsova, K.; Vlassov, V.; Laktionov, P.; Kozlov, V. Circulating DNA in rheumatoid arthritis: Pathological changes and association with clinically used serological markers. Arthritis Res. Ther. 2017, 19, 85. [Google Scholar] [CrossRef] [Green Version]
  90. Dong, C.; Liu, Y.; Sun, C.; Liang, H.; Dai, L.; Shen, J.; Wei, S.; Guo, S.; Leong, K.W.; Chen, Y.; et al. Identification of Specific Joint-Inflammatogenic Cell-Free DNA Molecules from Synovial Fluids of Patients with Rheumatoid Arthritis. Front. Immunol. 2020, 11, 662. [Google Scholar] [CrossRef]
  91. Glebova, K.V.; Veiko, N.N.; Nikonov, A.A.; Porokhovnik, L.N.; Kostuyk, S.V. Cell-free DNA as a biomarker in stroke: Current status, problems and perspectives. Crit. Rev. Clin. Lab. Sci. 2018, 55, 55–70. [Google Scholar] [CrossRef]
  92. Grosse, G.M.; Blume, N.; Abu-Fares, O.; Götz, F.; Ernst, J.; Leotescu, A.; Gabriel, M.M.; van Gemmeren, T.; Worthmann, H.; Lichtinghagen, R.; et al. Endogenous Deoxyribonuclease Activity and Cell-Free Deoxyribonucleic Acid in Acute Ischemic Stroke: A Cohort Study. Stroke 2022, 53, 1235–1244. [Google Scholar] [CrossRef]
  93. Cui, X.; Du, S.; Liu, H.; Liu, J.; Wu, Q.; Huo, Q.; Qi, Y.; Qin, X.; Yang, Y.; Li, W. The Length and Distribution of Plasma Cell-Free DNA Fragments in Stroke Patients. Biomed. Res. Int. 2020, 2020, 9054196. [Google Scholar] [CrossRef]
  94. Xie, J.; Yang, J.; Hu, P. Correlations of Circulating Cell-Free DNA With Clinical Manifestations in Acute Myocardial Infarction. Am. J. Med. Sci. 2018, 356, 121–129. [Google Scholar] [CrossRef]
  95. Lippi, G.; Sanchis-Gomar, F.; Cervellin, G. Cell-free DNA for diagnosing myocardial infarction: Not ready for prime time. Clin. Chem. Lab. Med. 2015, 53, 1895–1901. [Google Scholar] [CrossRef]
  96. Stawski, R.; Stec-Martyna, E.; Chmielecki, A.; Nowak, D.; Perdas, E. Current Trends in Cell-Free DNA Applications. Scoping Review of Clinical Trials. Biology 2021, 10, 906. [Google Scholar] [CrossRef]
  97. Schütz, E.; Fischer, A.; Beck, J.; Harden, M.; Koch, M.; Wuensch, T.; Stockmann, M.; Nashan, B.; Kollmar, O.; Matthaei, J.; et al. Graft-derived cell-free DNA, a noninvasive early rejection and graft damage marker in liver transplantation: A prospective, observational, multicenter cohort study. PLoS Med. 2017, 14, e1002286. [Google Scholar] [CrossRef] [Green Version]
  98. Stortz, J.A.; Hawkins, R.B.; Holden, D.C.; Raymond, S.L.; Wang, Z.; Brakenridge, S.C.; Cuschieri, J.; Moore, F.A.; Maier, R.V.; Moldawer, L.L.; et al. Cell-free nuclear, but not mitochondrial, DNA concentrations correlate with the early host inflammatory response after severe trauma. Sci. Rep. 2019, 9, 13648. [Google Scholar] [CrossRef] [Green Version]
  99. Hauser, C.J.; Otterbein, L.E. Danger signals from mitochondrial DAMPS in trauma and post-injury sepsis. Eur. J. Trauma Emerg. Surg. 2018, 44, 317–324. [Google Scholar] [CrossRef]
  100. Kumar, V. The Trinity of cGAS, TLR9, and ALRs Guardians of the Cellular Galaxy Against Host-Derived Self-DNA. Front. Immunol. 2021, 11, 624597. [Google Scholar] [CrossRef]
  101. Wang, H.; Zang, C.; Ren, M.; Shang, M.; Wang, Z.; Peng, X.; Zhang, Q.; Wen, X.; Xi, Z.; Zhou, C. Cellular uptake of extracellular nucleosomes induces innate immune responses by binding and activating cGMP-AMP synthase (cGAS). Sci. Rep. 2020, 10, 15385. [Google Scholar] [CrossRef] [PubMed]
  102. Ishikawa, H.; Barber, G.N. STING is an endoplasmic reticulum adaptor that facilitates innate immune signalling. Nature 2008, 455, 674–678, Erratum in Nature 2008, 456, 274. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Ishikawa, H.; Ma, Z.; Barber, G.N. STING regulates intracellular DNA-mediated, type I interferon-dependent innate immunity. Nature 2009, 461, 788–792. [Google Scholar] [CrossRef] [PubMed]
  104. Hooy, R.M.; Sohn, J. The allosteric activation of cGAS underpins its dynamic signaling landscape. Elife 2018, 7, e39984. [Google Scholar] [CrossRef] [PubMed]
  105. Luecke, S.; Holleufer, A.; Christensen, M.H.; Jønsson, K.L.; Boni, G.A.; Sørensen, L.K.; Johannsen, M.; Jakobsen, M.R.; Hartmann, R.; Paludan, S.R. cGAS is activated by DNA in a length-dependent manner. EMBO Rep. 2017, 18, 1707–1715. [Google Scholar] [CrossRef]
  106. Liu, S.; Cai, X.; Wu, J.; Cong, Q.; Chen, X.; Li, T.; Du, F.; Ren, J.; Wu, Y.T.; Grishin, N.V.; et al. Phosphorylation of innate immune adaptor proteins MAVS, STING, and TRIF induces IRF3 activation. Science 2015, 347, aaa2630. [Google Scholar] [CrossRef] [Green Version]
  107. Chen, H.; Sun, H.; You, F.; Sun, W.; Zhou, X.; Chen, L.; Yang, J.; Wang, Y.; Tang, H.; Guan, Y.; et al. Activation of STAT6 by STING is critical for antiviral innate immunity. Cell 2011, 147, 436–446. [Google Scholar] [CrossRef] [Green Version]
  108. Abe, T.; Barber, G.N. Cytosolic-DNA-mediated, STING-dependent proinflammatory gene induction necessitates canonical NF-κB activation through TBK1. J. Virol. 2014, 88, 5328–5341. [Google Scholar] [CrossRef] [Green Version]
  109. Saitoh, T.; Fujita, N.; Hayashi, T.; Takahara, K.; Satoh, T.; Lee, H.; Matsunaga, K.; Kageyama, S.; Omori, H.; Noda, T.; et al. Atg9a controls dsDNA-driven dynamic translocation of STING and the innate immune response. Proc. Natl. Acad. Sci. USA 2009, 106, 20842–20846. [Google Scholar] [CrossRef] [Green Version]
  110. Liang, Q.; Seo, G.J.; Choi, Y.J.; Kwak, M.J.; Ge, J.; Rodgers, M.A.; Shi, M.; Leslie, B.J.; Hopfner, K.P.; Ha, T.; et al. Crosstalk between the cGAS DNA sensor and Beclin-1 autophagy protein shapes innate antimicrobial immune responses. Cell Host Microbe 2014, 15, 228–238. [Google Scholar] [CrossRef] [Green Version]
  111. Latz, E.; Schoenemeyer, A.; Visintin, A.; Fitzgerald, K.A.; Monks, B.G.; Knetter, C.F.; Lien, E.; Nilsen, N.J.; Espevik, T.; Golenbock, D.T. TLR9 signals after translocating from the ER to CpG DNA in the lysosome. Nat. Immunol. 2004, 5, 190–198. [Google Scholar] [CrossRef]
  112. Miyake, K.; Shibata, T.; Fukui, R.; Sato, R.; Saitoh, S.I.; Murakami, Y. Nucleic Acid Sensing by Toll-Like Receptors in the Endosomal Compartment. Front. Immunol. 2022, 13, 941931. [Google Scholar] [CrossRef]
  113. Miyake, K. Nucleic acid-sensing Toll-like receptors: Beyond ligand search. Adv. Drug. Deliv. Rev. 2008, 60, 782–785. [Google Scholar] [CrossRef]
  114. De Nardo, D.; Balka, K.R.; Cardona Gloria, Y.; Rao, V.R.; Latz, E.; Masters, S.L. Interleukin-1 receptor-associated kinase 4 (IRAK4) plays a dual role in myddosome formation and Toll-like receptor signaling. J. Biol. Chem. 2018, 293, 15195–15207. [Google Scholar] [CrossRef] [Green Version]
  115. Singer, J.W.; Fleischman, A.; Al-Fayoumi, S.; Mascarenhas, J.O.; Yu, Q.; Agarwal, A. Inhibition of interleukin-1 receptor-associated kinase 1 (IRAK1) as a therapeutic strategy. Oncotarget 2018, 9, 33416–33439. [Google Scholar] [CrossRef] [Green Version]
  116. Dong, W.; Liu, Y.; Peng, J.; Chen, L.; Zou, T.; Xiao, H.; Liu, Z.; Li, W.; Bu, Y.; Qi, Y. The IRAK-1-BCL10-MALT1-TRAF6-TAK1 cascade mediates signaling to NF-kappaB from Toll-like receptor 4. J. Biol. Chem. 2006, 281, 26029–26040. [Google Scholar] [CrossRef] [Green Version]
  117. Wu, Z.H.; Wong, E.T.; Shi, Y.; Niu, J.; Chen, Z.; Miyamoto, S.; Tergaonkar, V. ATM- and NEMO-dependent ELKS ubiquitination coordinates TAK1-mediated IKK activation in response to genotoxic stress. Mol. Cell 2010, 40, 75–86. [Google Scholar] [CrossRef] [Green Version]
  118. Pohar, J.; Kužnik Krajnik, A.; Jerala, R.; Benčina, M. Minimal sequence requirements for oligodeoxyribonucleotides activating human TLR9. J. Immunol. 2015, 194, 3901–3908. [Google Scholar] [CrossRef] [Green Version]
  119. Pohar, J.; Lainšček, D.; Ivičak-Kocjan, K.; Cajnko, M.M.; Jerala, R.; Benčina, M. Short single-stranded DNA degradation products augment the activation of Toll-like receptor 9. Nat. Commun. 2017, 8, 15363. [Google Scholar] [CrossRef] [Green Version]
  120. Pohar, J.; Yamamoto, C.; Fukui, R.; Cajnko, M.M.; Miyake, K.; Jerala, R.; Benčina, M. Selectivity of Human TLR9 for Double CpG Motifs and Implications for the Recognition of Genomic DNA. J. Immunol. 2017, 198, 2093–2104. [Google Scholar] [CrossRef] [Green Version]
  121. Barton, G.M.; Kagan, J.C.; Medzhitov, R. Intracellular localization of Toll-like receptor 9 prevents recognition of self DNA but facilitates access to viral DNA. Nat. Immunol. 2006, 7, 49–56. [Google Scholar] [CrossRef] [PubMed]
  122. Jansen, M.P.; Emal, D.; Teske, G.J.; Dessing, M.C.; Florquin, S.; Roelofs, J.J. Release of extracellular DNA influences renal ischemia reperfusion injury by platelet activation and formation of neutrophil extracellular traps. Kidney Int. 2017, 91, 352–364. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Aslam, R.; Speck, E.R.; Kim, M.; Crow, A.R.; Bang, K.W.; Nestel, F.P.; Ni, H.; Lazarus, A.H.; Freedman, J.; Semple, J.W. Platelet Toll-like receptor expression modulates lipopolysaccharide-induced thrombocytopenia and tumor necrosis factor-alpha production in vivo. Blood 2006, 107, 637–641. [Google Scholar] [CrossRef] [PubMed]
  124. Panigrahi, S.; Ma, Y.; Hong, L.; Gao, D.; West, X.Z.; Salomon, R.G.; Byzova, T.V.; Podrez, E.A. Engagement of platelet toll-like receptor 9 by novel endogenous ligands promotes platelet hyperreactivity and thrombosis. Circ. Res. 2013, 112, 103–112. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  125. Lugrin, J.; Martinon, F. The AIM2 inflammasome: Sensor of pathogens and cellular perturbations. Immunol. Rev. 2018, 281, 99–114. [Google Scholar] [CrossRef] [Green Version]
  126. Wang, B.; Tian, Y.; Yin, Q. AIM2 Inflammasome Assembly and Signaling. Adv. Exp. Med. Biol. 2019, 1172, 143–155. [Google Scholar]
  127. Matyszewski, M.; Morrone, S.R.; Sohn, J. Digital signaling network drives the assembly of the AIM2-ASC inflammasome. Proc. Natl. Acad. Sci. USA 2018, 115, E1963–E1972. [Google Scholar] [CrossRef] [Green Version]
  128. Morrone, S.R.; Matyszewski, M.; Yu, X.; Delannoy, M.; Egelman, E.H.; Sohn, J. Assembly-driven activation of the AIM2 foreign-dsDNA sensor provides a polymerization template for downstream ASC. Nat. Commun. 2015, 6, 7827. [Google Scholar] [CrossRef] [Green Version]
  129. Banerjee, I.; Behl, B.; Mendonca, M.; Shrivastava, G.; Russo, A.J.; Menoret, A.; Ghosh, A.; Vella, A.T.; Vanaja, S.K.; Sarkar, S.N.; et al. Gasdermin D Restrains Type I Interferon Response to Cytosolic DNA by Disrupting Ionic Homeostasis. Immunity 2018, 49, 413–426.e5. [Google Scholar] [CrossRef] [Green Version]
  130. Evavold, C.L.; Ruan, J.; Tan, Y.; Xia, S.; Wu, H.; Kagan, J.C. The Pore-Forming Protein Gasdermin D Regulates Interleukin-1 Secretion from Living Macrophages. Immunity 2018, 48, 35–44.e6. [Google Scholar] [CrossRef] [Green Version]
  131. Liu, Z.; Wang, C.; Yang, J.; Zhou, B.; Yang, R.; Ramachandran, R.; Abbott, D.W.; Xiao, T.S. Crystal Structures of the Full-Length Murine and Human Gasdermin D Reveal Mechanisms of Autoinhibition, Lipid Binding, and Oligomerization. Immunity 2019, 51, 43–49.e4. [Google Scholar] [CrossRef]
  132. Yan, S.; Shen, H.; Lian, Q.; Jin, W.; Zhang, R.; Lin, X.; Gu, W.; Sun, X.; Meng, G.; Tian, Z.; et al. Deficiency of the AIM2-ASC Signal Uncovers the STING-Driven Overreactive Response of Type I IFN and Reciprocal Depression of Protective IFN-γ Immunity in Mycobacterial Infection. J. Immunol. 2018, 200, 1016–1026. [Google Scholar] [CrossRef] [Green Version]
  133. Saito, Y.; Hikita, H.; Nozaki, Y.; Kai, Y.; Makino, Y.; Nakabori, T.; Tanaka, S.; Yamada, R.; Shigekawa, M.; Kodama, T.; et al. DNase II activated by the mitochondrial apoptotic pathway regulates RIP1-dependent non-apoptotic hepatocyte death via the TLR9/IFN-β signaling pathway. Cell Death Differ. 2019, 26, 470–486. [Google Scholar]
  134. Montes, V.N.; Subramanian, S.; Goodspeed, L.; Wang, S.A.; Omer, M.; Bobik, A.; Teshigawara, K.; Nishibori, M.; Chait, A. Anti-HMGB1 antibody reduces weight gain in mice fed a high-fat diet. Nutr. Diabetes 2015, 5, e161. [Google Scholar] [CrossRef] [Green Version]
  135. Csak, T.; Pillai, A.; Ganz, M.; Lippai, D.; Petrasek, J.; Park, J.K.; Kodys, K.; Dolganiuc, A.; Kurt-Jones, E.A.; Szabo, G. Both bone marrow-derived and non-bone marrow-derived cells contribute to AIM2 and NLRP3 inflammasome activation in a MyD88-dependent manner in dietary steatohepatitis. Liver Int. 2014, 34, 1402–1413. [Google Scholar] [CrossRef]
  136. Kim, H.Y.; Kim, S.J.; Lee, S.M. Activation of NLRP3 and AIM2 inflammasomes in Kupffer cells in hepatic ischemia/reperfusion. FEBS J. 2015, 282, 259–270. [Google Scholar] [CrossRef]
  137. Yu, Y.; Liu, Y.; An, W.; Song, J.; Zhang, Y.; Zhao, X. STING-mediated inflammation in Kupffer cells contributes to progression of nonalcoholic steatohepatitis. J. Clin. Investig. 2019, 129, 546–555. [Google Scholar] [CrossRef]
  138. Kumar, V. A STING to inflammation and autoimmunity. J. Leukoc. Biol. 2019, 106, 171–185. [Google Scholar] [CrossRef]
  139. Luther, J.; Khan, S.; Gala, M.K.; Kedrin, D.; Sridharan, G.; Goodman, R.P.; Garber, J.J.; Masia, R.; Diagacomo, E.; Adams, D.; et al. Hepatic gap junctions amplify alcohol liver injury by propagating cGAS-mediated IRF3 activation. Proc. Natl. Acad. Sci. USA 2020, 117, 11667–11673. [Google Scholar] [CrossRef]
  140. Petrasek, J.; Iracheta-Vellve, A.; Csak, T.; Satishchandran, A.; Kodys, K.; Kurt-Jones, E.A.; Fitzgerald, K.A.; Szabo, G. STING-IRF3 pathway links endoplasmic reticulum stress with hepatocyte apoptosis in early alcoholic liver disease. Proc. Natl. Acad. Sci. USA 2013, 110, 16544–16549. [Google Scholar] [CrossRef] [Green Version]
  141. Nishimoto, S.; Fukuda, D.; Sata, M. Emerging roles of Toll-like receptor 9 in cardiometabolic disorders. Inflamm. Regen. 2020, 40, 18. [Google Scholar] [CrossRef] [PubMed]
  142. Nishimoto, S.; Fukuda, D.; Higashikuni, Y.; Tanaka, K.; Hirata, Y.; Murata, C.; Kim-Kaneyama, J.R.; Sato, F.; Bando, M.; Yagi, S.; et al. Obesity-induced DNA released from adipocytes stimulates chronic adipose tissue inflammation and insulin resistance. Sci. Adv. 2016, 2, e1501332. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  143. Bai, J.; Cervantes, C.; He, S.; He, J.; Plasko, G.R.; Wen, J.; Li, Z.; Yin, D.; Zhang, C.; Liu, M.; et al. Mitochondrial stress-activated cGAS-STING pathway inhibits thermogenic program and contributes to overnutrition-induced obesity in mice. Commun. Biol. 2020, 3, 257. [Google Scholar] [CrossRef] [PubMed]
  144. Mao, Y.; Luo, W.; Zhang, L.; Wu, W.; Yuan, L.; Xu, H.; Song, J.; Fujiwara, K.; Abe, J.I.; LeMaire, S.A.; et al. STING-IRF3 Triggers Endothelial Inflammation in Response to Free Fatty Acid-Induced Mitochondrial Damage in Diet-Induced Obesity. Arter. Thromb. Vasc. Biol. 2017, 37, 920–929. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  145. Yuan, L.; Mao, Y.; Luo, W.; Wu, W.; Xu, H.; Wang, X.L.; Shen, Y.H. Palmitic acid dysregulates the Hippo-YAP pathway and inhibits angiogenesis by inducing mitochondrial damage and activating the cytosolic DNA sensor cGAS-STING-IRF3 signaling mechanism. J. Biol. Chem. 2017, 292, 15002–15015. [Google Scholar] [CrossRef]
  146. Fukuda, D.; Nishimoto, S.; Aini, K.; Tanaka, A.; Nishiguchi, T.; Kim-Kaneyama, J.R.; Lei, X.F.; Masuda, K.; Naruto, T.; Tanaka, K.; et al. Toll-Like Receptor 9 Plays a Pivotal Role in Angiotensin II-Induced Atherosclerosis. J. Am. Heart Assoc. 2019, 8, e010860. [Google Scholar] [CrossRef] [Green Version]
  147. Li, J.; Huynh, L.; Cornwell, W.D.; Tang, M.S.; Simborio, H.; Huang, J.; Kosmider, B.; Rogers, T.J.; Zhao, H.; Steinberg, M.B.; et al. Electronic Cigarettes Induce Mitochondrial DNA Damage and Trigger TLR9 (Toll-Like Receptor 9)-Mediated Atherosclerosis. Arter. Thromb. Vasc. Biol. 2021, 41, 839–853. [Google Scholar] [CrossRef]
  148. Andrassy, M.; Volz, H.C.; Maack, B.; Schuessler, A.; Gitsioudis, G.; Hofmann, N.; Laohachewin, D.; Wienbrandt, A.R.; Kaya, Z.; Bierhaus, A.; et al. HMGB1 is associated with atherosclerotic plaque composition and burden in patients with stable coronary artery disease. PLoS ONE 2012, 7, e52081. [Google Scholar] [CrossRef]
  149. Yan, X.X.; Lu, L.; Peng, W.H.; Wang, L.J.; Zhang, Q.; Zhang, R.Y.; Chen, Q.J.; Shen, W.F. Increased serum HMGB1 level is associated with coronary artery disease in nondiabetic and type 2 diabetic patients. Atherosclerosis 2009, 205, 544–548. [Google Scholar] [CrossRef]
  150. Belmadani, S.; Matrougui, K. Role of High Mobility Group Box 1 in Cardiovascular Diseases. Inflammation 2022, 45, 1864–1874. [Google Scholar] [CrossRef]
  151. Lüsebrink, E.; Goody, P.R.; Lahrmann, C.; Flender, A.; Niepmann, S.T.; Zietzer, A.; Schulz, C.; Massberg, S.; Jansen, F.; Nickenig, G.; et al. AIM2 Stimulation Impairs Reendothelialization and Promotes the Development of Atherosclerosis in Mice. Front. Cardiovasc. Med. 2020, 7, 582482. [Google Scholar] [CrossRef]
  152. Christensen, S.R.; Shupe, J.; Nickerson, K.; Kashgarian, M.; Flavell, R.A.; Shlomchik, M.J. Toll-like receptor 7 and TLR9 dictate autoantibody specificity and have opposing inflammatory and regulatory roles in a murine model of lupus. Immunity 2006, 25, 417–428. [Google Scholar] [CrossRef] [Green Version]
  153. Santiago-Raber, M.L.; Baudino, L.; Izui, S. Emerging roles of TLR7 and TLR9 in murine SLE. J. Autoimmun. 2009, 33, 231–238. [Google Scholar] [CrossRef]
  154. Viglianti, G.A.; Lau, C.M.; Hanley, T.M.; Miko, B.A.; Shlomchik, M.J.; Marshak-Rothstein, A. Activation of autoreactive B cells by CpG dsDNA. Immunity 2003, 19, 837–847. [Google Scholar] [CrossRef] [Green Version]
  155. Leadbetter, E.A.; Rifkin, I.R.; Hohlbaum, A.M.; Beaudette, B.C.; Shlomchik, M.J.; Marshak-Rothstein, A. Chromatin-IgG complexes activate B cells by dual engagement of IgM and Toll-like receptors. Nature 2002, 416, 603–607. [Google Scholar] [CrossRef]
  156. Motwani, M.; McGowan, J.; Antonovitch, J.; Gao, K.M.; Jiang, Z.; Sharma, S.; Baltus, G.A.; Nickerson, K.M.; Marshak-Rothstein, A.; Fitzgerald, K.A. cGAS-STING Pathway Does Not Promote Autoimmunity in Murine Models of SLE. Front. Immunol. 2021, 12, 605930. [Google Scholar] [CrossRef]
  157. Carbonella, A.; Mancano, G.; Gremese, E.; Alkuraya, F.S.; Patel, N.; Gurrieri, F.; Ferraccioli, G. An autosomal recessive DNASE1L3-related autoimmune disease with unusual clinical presentation mimicking systemic lupus erythematosus. Lupus 2017, 26, 768–772. [Google Scholar] [CrossRef]
  158. Al-Mayouf, S.M.; Sunker, A.; Abdwani, R.; Abrawi, S.A.; Almurshedi, F.; Alhashmi, N.; Al Sonbul, A.; Sewairi, W.; Qari, A.; Abdallah, E.; et al. Loss-of-function variant in DNASE1L3 causes a familial form of systemic lupus erythematosus. Nat. Genet. 2011, 43, 1186–1188. [Google Scholar] [CrossRef]
  159. Sisirak, V.; Sally, B.; D’Agati, V.; Martinez-Ortiz, W.; Özçakar, Z.B.; David, J.; Rashidfarrokhi, A.; Yeste, A.; Panea, C.; Chida, A.S.; et al. Digestion of Chromatin in Apoptotic Cell Microparticles Prevents Autoimmunity. Cell 2016, 166, 88–101. [Google Scholar] [CrossRef] [Green Version]
  160. Soni, C.; Reizis, B. Self-DNA at the Epicenter of SLE: Immunogenic Forms, Regulation, and Effects. Front. Immunol. 2019, 10, 1601. [Google Scholar] [CrossRef] [Green Version]
  161. Crow, Y.J.; Hayward, B.E.; Parmar, R.; Robins, P.; Leitch, A.; Ali, M.; Black, D.N.; van Bokhoven, H.; Brunner, H.G.; Hamel, B.C.; et al. Mutations in the gene encoding the 3’-5’ DNA exonuclease TREX1 cause Aicardi-Goutières syndrome at the AGS1 locus. Nat. Genet. 2006, 38, 917–920. [Google Scholar] [CrossRef] [PubMed]
  162. Rodero, M.P.; Tesser, A.; Bartok, E.; Rice, G.I.; Della Mina, E.; Depp, M.; Beitz, B.; Bondet, V.; Cagnard, N.; Duffy, D.; et al. Type I interferon-mediated autoinflammation due to DNase II deficiency. Nat. Commun. 2017, 8, 2176. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. McCauley, M.E.; O’Rourke, J.G.; Yáñez, A.; Markman, J.L.; Ho, R.; Wang, X.; Chen, S.; Lall, D.; Jin, M.; Muhammad, A.K.M.G.; et al. C9orf72 in myeloid cells suppresses STING-induced inflammation. Nature 2020, 585, 96–101. [Google Scholar] [CrossRef] [PubMed]
  164. Gratia, M.; Rodero, M.P.; Conrad, C.; Bou Samra, E.; Maurin, M.; Rice, G.I.; Duffy, D.; Revy, P.; Petit, F.; Dale, R.C.; et al. Bloom syndrome protein restrains innate immune sensing of micronuclei by cGAS. J. Exp. Med. 2019, 216, 1199–1213. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  165. Sharma, M.; Rajendrarao, S.; Shahani, N.; Ramírez-Jarquín, U.N.; Subramaniam, S. Cyclic GMP-AMP synthase promotes the inflammatory and autophagy responses in Huntington disease. Proc. Natl. Acad. Sci. USA 2020, 117, 15989–15999. [Google Scholar] [CrossRef]
  166. Hopfner, K.P.; Hornung, V. Molecular mechanisms and cellular functions of cGAS-STING signalling. Nat. Rev. Mol. Cell Biol. 2020, 21, 501–521. [Google Scholar] [CrossRef]
  167. Ni, G.; Ma, Z.; Wong, J.P.; Zhang, Z.; Cousins, E.; Major, M.B.; Damania, B. PPP6C Negatively Regulates STING-Dependent Innate Immune Responses. mBio 2020, 11, e01728-20. [Google Scholar] [CrossRef]
  168. Jena, K.K.; Mehto, S.; Nath, P.; Chauhan, N.R.; Sahu, R.; Dhar, K.; Das, S.K.; Kolapalli, S.P.; Murmu, K.C.; Jain, A.; et al. Autoimmunity gene IRGM suppresses cGAS-STING and RIG-I-MAVS signaling to control interferon response. EMBO Rep. 2020, 21, e50051. [Google Scholar] [CrossRef]
  169. Tian, M.; Liu, W.; Zhang, Q.; Huang, Y.; Li, W.; Wang, W.; Zhao, P.; Huang, S.; Song, Y.; Shereen, M.A.; et al. MYSM1 Represses Innate Immunity and Autoimmunity through Suppressing the cGAS-STING Pathway. Cell Rep. 2020, 33, 108297. [Google Scholar] [CrossRef]
  170. Panda, S.; Gekara, N.O. The deubiquitinase MYSM1 dampens NOD2-mediated inflammation and tissue damage by inactivating the RIP2 complex. Nat. Commun. 2018, 9, 4654. [Google Scholar] [CrossRef] [Green Version]
  171. Dieleman, L.A.; Ridwan, B.U.; Tennyson, G.S.; Beagley, K.W.; Bucy, R.P.; Elson, C.O. Dextran sulfate sodium-induced colitis occurs in severe combined immunodeficient mice. Gastroenterology 1994, 107, 1643–1652. [Google Scholar] [CrossRef]
  172. Katsandegwaza, B.; Horsnell, W.; Smith, K. Inflammatory Bowel Disease: A Review of Pre-Clinical Murine Models of Human Disease. Int. J. Mol. Sci. 2022, 23, 9344. [Google Scholar] [CrossRef]
  173. Maronek, M.; Gromova, B.; Liptak, R.; Konecna, B.; Pastorek, M.; Cechova, B.; Harsanyova, M.; Budis, J.; Smolak, D.; Radvanszky, J.; et al. Extracellular DNA Correlates with Intestinal Inflammation in Chemically Induced Colitis in Mice. Cells 2021, 10, 81. [Google Scholar] [CrossRef]
  174. Rachmilewitz, D.; Karmeli, F.; Takabayashi, K.; Hayashi, T.; Leider-Trejo, L.; Lee, J.; Leoni, L.M.; Raz, E. Immunostimulatory DNA ameliorates experimental and spontaneous murine colitis. Gastroenterology 2002, 122, 1428–1441. [Google Scholar] [CrossRef]
  175. Rachmilewitz, D.; Karmeli, F.; Shteingart, S.; Lee, J.; Takabayashi, K.; Raz, E. Immunostimulatory oligonucleotides inhibit colonic proinflammatory cytokine production in ulcerative colitis. Inflamm. Bowel Dis. 2006, 12, 339–345. [Google Scholar] [CrossRef]
  176. Ciorba, M.A.; Bettonville, E.E.; McDonald, K.G.; Metz, R.; Prendergast, G.C.; Newberry, R.D.; Stenson, W.F. Induction of IDO-1 by immunostimulatory DNA limits severity of experimental colitis. J. Immunol. 2010, 184, 3907–3916. [Google Scholar] [CrossRef] [Green Version]
  177. Acovic, A.; Gazdic, M.; Jovicic, N.; Harrell, C.R.; Fellabaum, C.; Arsenijevic, N.; Volarevic, V. Role of indoleamine 2,3-dioxygenase in pathology of the gastrointestinal tract. Therap. Adv. Gastroenterol. 2018, 11, 1756284818815334. [Google Scholar] [CrossRef] [Green Version]
  178. Dou, S.; Smith, M.; Wang, Y.; Rusckowski, M.; Liu, G. Intraperitoneal injection is not always a suitable alternative to intravenous injection for radiotherapy. Cancer Biother. Radiopharm. 2013, 28, 335–342. [Google Scholar] [CrossRef] [Green Version]
  179. Liu, X.; Guo, Q.; Zhang, Y.; Li, J.; Li, R.; Wu, Y.; Ma, P.; Yang, X. Intraperitoneal Injection Is Not a Suitable Administration Route for Single-Walled Carbon Nanotubes in Biomedical Applications. Dose Response 2016, 14, 1559325816681320. [Google Scholar] [CrossRef]
  180. Musch, E.; Lutfi, T.; von Stein, P.; Zargari, A.; Admyre, C.; Malek, M.; Löfberg, R.; von Stein, O.D. Topical treatment with the Toll-like receptor agonist DIMS0150 has potential for lasting relief of symptoms in patients with chronic active ulcerative colitis by restoring glucocorticoid sensitivity. Inflamm. Bowel Dis. 2013, 19, 283–292. [Google Scholar] [CrossRef]
  181. Atreya, R.; Bloom, S.; Scaldaferri, F.; Gerardi, V.; Admyre, C.; Karlsson, Å.; Knittel, T.; Kowalski, J.; Lukas, M.; Löfberg, R.; et al. Clinical Effects of a Topically Applied Toll-like Receptor 9 Agonist in Active Moderate-to-Severe Ulcerative Colitis. J. Crohns Colitis 2016, 10, 1294–1302. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  182. Atreya, R.; Reinisch, W.; Peyrin-Biroulet, L.; Scaldaferri, F.; Admyre, C.; Knittel, T.; Kowalski, J.; Neurath, M.F.; Hawkey, C. Clinical efficacy of the Toll-like receptor 9 agonist cobitolimod using patient-reported-outcomes defined clinical endpoints in patients with ulcerative colitis. Dig. Liver Dis. 2018, 50, 1019–1029. [Google Scholar] [CrossRef] [PubMed]
  183. Schmitt, H.; Ulmschneider, J.; Billmeier, U.; Vieth, M.; Scarozza, P.; Sonnewald, S.; Reid, S.; Atreya, I.; Rath, T.; Zundler, S.; et al. The TLR9 Agonist Cobitolimod Induces IL10-Producing Wound Healing Macrophages and Regulatory T Cells in Ulcerative Colitis. J. Crohns Colitis 2020, 14, 508–524. [Google Scholar] [CrossRef] [PubMed]
  184. Scarozza, P.; Schmitt, H.; Monteleone, G.; Neurath, M.F.; Atreya, R. Oligonucleotides-A Novel Promising Therapeutic Option for IBD. Front. Pharmacol. 2019, 10, 314. [Google Scholar] [CrossRef] [PubMed]
  185. Sipos, F.; Műzes, G.; Fűri, I.; Spisák, S.; Wichmann, B.; Germann, T.M.; Constantinovits, M.; Krenács, T.; Tulassay, Z.; Molnár, B. Intravenous administration of a single-dose free-circulating DNA of colitic origin improves severe murine DSS-colitis. Pathol. Oncol. Res. 2014, 20, 867–877. [Google Scholar] [CrossRef]
  186. Delgado, M.A.; Elmaoued, R.A.; Davis, A.S.; Kyei, G.; Deretic, V. Toll-like receptors control autophagy. EMBO J. 2008, 27, 1110–1121. [Google Scholar] [CrossRef] [Green Version]
  187. Delgado, M.A.; Deretic, V. Toll-like receptors in control of immunological autophagy. Cell Death Differ. 2009, 16, 976–983. [Google Scholar] [CrossRef]
  188. Műzes, G.; Kiss, A.L.; Tulassay, Z.; Sipos, F. Cell-free DNA-induced alteration of autophagy response and TLR9-signaling: Their relation to amelioration of DSS-colitis. Comp. Immunol. Microbiol. Infect. Dis. 2017, 52, 48–57. [Google Scholar] [CrossRef]
  189. Martinson, J.A.; Tenorio, A.R.; Montoya, C.J.; Al-Harthi, L.; Gichinga, C.N.; Krieg, A.M.; Baum, L.L.; Landay, A.L. Impact of class A, B and C CpG-oligodeoxynucleotides on in vitro activation of innate immune cells in human immunodeficiency virus-1 infected individuals. Immunology 2007, 120, 526–535. [Google Scholar] [CrossRef]
  190. Hanagata, N. Structure-dependent immunostimulatory effect of CpG oligodeoxynucleotides and their delivery system. Int. J. Nanomed. 2012, 7, 2181–2195. [Google Scholar] [CrossRef] [Green Version]
  191. Davis, J.M., 3rd; Crowson, C.S.; Knutson, K.L.; Achenbach, S.J.; Strausbauch, M.A.; Therneau, T.M.; Matteson, E.L.; Gabriel, S.E.; Wettstein, P.J. Longitudinal relationships between rheumatoid factor and cytokine expression by immunostimulated peripheral blood lymphocytes from patients with rheumatoid arthritis: New insights into B-cell activation. Clin. Immunol. 2020, 211, 108342. [Google Scholar] [CrossRef]
  192. Bernasconi, N.L.; Traggiai, E.; Lanzavecchia, A. Maintenance of serological memory by polyclonal activation of human memory B cells. Science 2002, 298, 2199–2202. [Google Scholar] [CrossRef]
  193. Liang, H.; Peng, B.; Dong, C.; Liu, L.; Mao, J.; Wei, S.; Wang, X.; Xu, H.; Shen, J.; Mao, H.Q.; et al. Cationic nanoparticle as an inhibitor of cell-free DNA-induced inflammation. Nat. Commun. 2018, 9, 4291. [Google Scholar] [CrossRef] [Green Version]
  194. Hashimoto, T.; Yoshida, K.; Hashiramoto, A.; Matsui, K. Cell-Free DNA in Rheumatoid Arthritis. Int. J. Mol. Sci. 2021, 22, 8941. [Google Scholar] [CrossRef]
  195. Gilboa-Geffen, A.; Wolf, Y.; Hanin, G.; Melamed-Book, N.; Pick, M.; Bennett, E.R.; Greenberg, D.S.; Lester, S.; Rischmueller, M.; Soreq, H. Activation of the alternative NFκB pathway improves disease symptoms in a model of Sjogren’s syndrome. PLoS ONE 2011, 6, e28727. [Google Scholar] [CrossRef]
  196. Shen, Y.; Ichino, M.; Nakazawa, M.; Minami, M. CpG oligodeoxynucleotides prevent the development of scleroderma-like syndrome in tight-skin mice by stimulating a Th1 immune response. J. Investig. Dermatol. 2005, 124, 1141–1148. [Google Scholar] [CrossRef]
  197. Hurtado, P.R.; Jeffs, L.; Nitschke, J.; Patel, M.; Sarvestani, G.; Cassidy, J.; Hissaria, P.; Gillis, D.; Peh, C.A. CpG oligodeoxynucleotide stimulates production of anti-neutrophil cytoplasmic antibodies in ANCA associated vasculitis. BMC Immunol. 2008, 9, 34. [Google Scholar] [CrossRef] [Green Version]
  198. Ho, P.P.; Fontoura, P.; Ruiz, P.J.; Steinman, L.; Garren, H. An immunomodulatory GpG oligonucleotide for the treatment of autoimmunity via the innate and adaptive immune systems. J. Immunol. 2003, 171, 4920–4926. [Google Scholar] [CrossRef] [Green Version]
  199. Ho, P.P.; Fontoura, P.; Platten, M.; Sobel, R.A.; DeVoss, J.J.; Lee, L.Y.; Kidd, B.A.; Tomooka, B.H.; Capers, J.; Agrawal, A.; et al. A suppressive oligodeoxynucleotide enhances the efficacy of myelin cocktail/IL-4-tolerizing DNA vaccination and treats autoimmune disease. J. Immunol. 2005, 175, 6226–6234. [Google Scholar] [CrossRef] [Green Version]
  200. Graham, K.L.; Lee, L.Y.; Higgins, J.P.; Steinman, L.; Utz, P.J.; Ho, P.P. Treatment with a toll-like receptor inhibitory GpG oligonucleotide delays and attenuates lupus nephritis in NZB/W mice. Autoimmunity 2010, 43, 140–155. [Google Scholar] [CrossRef]
  201. Műzes, G.; Sipos, F.; Fűri, I.; Constantinovits, M.; Spisák, S.; Wichmann, B.; Valcz, G.; Tulassay, Z.; Molnár, B. Preconditioning with intravenous colitic cell-free DNA prevents DSS-colitis by altering TLR9-associated gene expression profile. Dig. Dis. Sci. 2014, 59, 2935–2946. [Google Scholar] [CrossRef] [PubMed]
  202. Constantinovits, M.; Sipos, F.; LKiss, A.; Műzes, G. Preconditioning with cell-free DNA prevents DSS-colitis by promoting cell protective autophagy. J. Investig. Med. 2020, 68, 992–1001. [Google Scholar] [CrossRef] [PubMed]
  203. Colotta, F.; Allavena, P.; Sica, A.; Garlanda, C.; Mantovani, A. Cancer-related inflammation, the seventh hallmark of cancer: Links to genetic instability. Carcinogenesis 2009, 30, 1073–1081. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  204. Hanahan, D.; Weinberg, R.A. The hallmarks of cancer. Cell 2000, 100, 57–70. [Google Scholar] [CrossRef] [Green Version]
  205. Hanahan, D. Hallmarks of Cancer: New Dimensions. Cancer Discov. 2022, 12, 31–46. [Google Scholar] [CrossRef] [PubMed]
  206. Niu, Z.; Tang, W.; Liu, T.; Xu, P.; Zhu, D.; Ji, M.; Huang, W.; Ren, L.; Wei, Y.; Xu, J. Cell-free DNA derived from cancer cells facilitates tumor malignancy through Toll-like receptor 9 signaling-triggered interleukin-8 secretion in colorectal cancer. Acta Biochim. Biophys. Sin. 2018, 50, 1007–1017. [Google Scholar] [CrossRef] [Green Version]
  207. Wang, W.; Kong, P.; Ma, G.; Li, L.; Zhu, J.; Xia, T.; Xie, H.; Zhou, W.; Wang, S. Characterization of the release and biological significance of cell-free DNA from breast cancer cell lines. Oncotarget 2017, 8, 43180–43191. [Google Scholar] [CrossRef] [Green Version]
  208. Kang, T.H.; Mao, C.P.; Kim, Y.S.; Kim, T.W.; Yang, A.; Lam, B.; Tseng, S.H.; Farmer, E.; Park, Y.M.; Hung, C.F. TLR9 acts as a sensor for tumor-released DNA to modulate anti-tumor immunity after chemotherapy. J. Immunother. Cancer 2019, 7, 260. [Google Scholar] [CrossRef]
  209. Zierhut, C.; Yamaguchi, N.; Paredes, M.; Luo, J.D.; Carroll, T.; Funabiki, H. The Cytoplasmic DNA Sensor cGAS Promotes Mitotic Cell Death. Cell 2019, 178, 302–315.e23. [Google Scholar] [CrossRef]
  210. An, X.; Zhu, Y.; Zheng, T.; Wang, G.; Zhang, M.; Li, J.; Ji, H.; Li, S.; Yang, S.; Xu, D.; et al. An Analysis of the Expression and Association with Immune Cell Infiltration of the cGAS/STING Pathway in Pan-Cancer. Mol. Ther. Nucleic Acids. 2019, 14, 80–89. [Google Scholar] [CrossRef] [Green Version]
  211. Yang, H.; Wang, H.; Ren, J.; Chen, Q.; Chen, Z.J. cGAS is essential for cellular senescence. Proc. Natl. Acad. Sci. USA 2017, 114, E4612–E4620. [Google Scholar] [CrossRef] [Green Version]
  212. Sen, T.; Rodriguez, B.L.; Chen, L.; Corte, C.M.D.; Morikawa, N.; Fujimoto, J.; Cristea, S.; Nguyen, T.; Diao, L.; Li, L.; et al. Targeting DNA Damage Response Promotes Antitumor Immunity through STING-Mediated T-cell Activation in Small Cell Lung Cancer. Cancer Discov. 2019, 9, 646–661. [Google Scholar] [CrossRef] [Green Version]
  213. Wang-Bishop, L.; Wehbe, M.; Shae, D.; James, J.; Hacker, B.C.; Garland, K.; Chistov, P.P.; Rafat, M.; Balko, J.M.; Wilson, J.T. Potent STING activation stimulates immunogenic cell death to enhance antitumor immunity in neuroblastoma. J. Immunother. Cancer 2020, 8, e000282. [Google Scholar] [CrossRef] [Green Version]
  214. Ma, F.; Lei, Y.Y.; Ding, M.G.; Luo, L.H.; Xie, Y.C.; Liu, X.L. LncRNA NEAT1 Interacted with DNMT1 to Regulate Malignant Phenotype of Cancer Cell and Cytotoxic T Cell Infiltration via Epigenetic Inhibition of p53, cGAS, and STING in Lung Cancer. Front. Genet. 2020, 11, 250. [Google Scholar] [CrossRef]
  215. Man, S.M.; Zhu, Q.; Zhu, L.; Liu, Z.; Karki, R.; Malik, A.; Sharma, D.; Li, L.; Malireddi, R.K.; Gurung, P.; et al. Critical Role for the DNA Sensor AIM2 in Stem Cell Proliferation and Cancer. Cell 2015, 162, 45–58. [Google Scholar] [CrossRef]
  216. Schulmann, K.; Brasch, F.E.; Kunstmann, E.; Engel, C.; Pagenstecher, C.; Vogelsang, H.; Krüger, S.; Vogel, T.; Knaebel, H.P.; Rüschoff, J.; et al. HNPCC-associated small bowel cancer: Clinical and molecular characteristics. Gastroenterology 2005, 128, 590–599. [Google Scholar] [CrossRef]
  217. Farshchian, M.; Nissinen, L.; Siljamäki, E.; Riihilä, P.; Piipponen, M.; Kivisaari, A.; Kallajoki, M.; Grénman, R.; Peltonen, J.; Peltonen, S.; et al. Tumor cell-specific AIM2 regulates growth and invasion of cutaneous squamous cell carcinoma. Oncotarget 2017, 8, 45825–45836. [Google Scholar] [CrossRef]
  218. Qi, M.; Dai, D.; Liu, J.; Li, Z.; Liang, P.; Wang, Y.; Cheng, L.; Zhan, Y.; An, Z.; Song, Y.; et al. AIM2 promotes the development of non-small cell lung cancer by modulating mitochondrial dynamics. Oncogene 2020, 39, 2707–2723. [Google Scholar] [CrossRef]
  219. Trotta, A.P.; Chipuk, J.E. Mitochondrial dynamics as regulators of cancer biology. Cell Mol. Life Sci. 2017, 74, 1999–2017. [Google Scholar] [CrossRef]
  220. Kondo, Y.; Nagai, K.; Nakahata, S.; Saito, Y.; Ichikawa, T.; Suekane, A.; Taki, T.; Iwakawa, R.; Enari, M.; Taniwaki, M.; et al. Overexpression of the DNA sensor proteins, absent in melanoma 2 and interferon-inducible 16, contributes to tumorigenesis of oral squamous cell carcinoma with p53 inactivation. Cancer Sci. 2012, 103, 782–790. [Google Scholar] [CrossRef]
  221. Ponomareva, L.; Liu, H.; Duan, X.; Dickerson, E.; Shen, H.; Panchanathan, R.; Choubey, D. AIM2, an IFN-inducible cytosolic DNA sensor, in the development of benign prostate hyperplasia and prostate cancer. Mol. Cancer Res. 2013, 11, 1193–1202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  222. Martínez-Cardona, C.; Lozano-Ruiz, B.; Bachiller, V.; Peiró, G.; Algaba-Chueca, F.; Gómez-Hurtado, I.; Such, J.; Zapater, P.; Francés, R.; González-Navajas, J.M. AIM2 deficiency reduces the development of hepatocellular carcinoma in mice. Int. J. Cancer 2018, 143, 2997–3007. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  223. Ma, X.; Guo, P.; Qiu, Y.; Mu, K.; Zhu, L.; Zhao, W.; Li, T.; Han, L. Loss of AIM2 expression promotes hepatocarcinoma progression through activation of mTOR-S6K1 pathway. Oncotarget 2016, 7, 36185–36197. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  224. García-Olmo, D.; García-Olmo, D.C.; Ontañón, J.; Martinez, E.; Vallejo, M. Tumor DNA circulating in the plasma might play a role in metastasis. The hypothesis of the genometastasis. Histol. Histopathol. 1999, 14, 1159–1164. [Google Scholar] [PubMed]
  225. García-Olmo, D.C.; Domínguez, C.; García-Arranz, M.; Anker, P.; Stroun, M.; García-Verdugo, J.M.; García-Olmo, D. Cell-free nucleic acids circulating in the plasma of colorectal cancer patients induce the oncogenic transformation of susceptible cultured cells. Cancer Res. 2010, 70, 560–567. [Google Scholar] [CrossRef]
  226. Trejo-Becerril, C.; Pérez-Cárdenas, E.; Taja-Chayeb, L.; Anker, P.; Herrera-Goepfert, R.; Medina-Velázquez, L.A.; Hidalgo-Miranda, A.; Pérez-Montiel, D.; Chávez-Blanco, A.; Cruz-Velázquez, J.; et al. Cancer progression mediated by horizontal gene transfer in an in vivo model. PLoS ONE 2012, 7, e52754. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  227. Bergsmedh, A.; Szeles, A.; Henriksson, M.; Bratt, A.; Folkman, M.J.; Spetz, A.L.; Holmgren, L. Horizontal transfer of oncogenes by uptake of apoptotic bodies. Proc. Natl. Acad. Sci. USA 2001, 98, 6407–6411. [Google Scholar] [CrossRef] [Green Version]
  228. Gaiffe, E.; Prétet, J.L.; Launay, S.; Jacquin, E.; Saunier, M.; Hetzel, G.; Oudet, P.; Mougin, C. Apoptotic HPV positive cancer cells exhibit transforming properties. PLoS ONE 2012, 7, e36766. [Google Scholar] [CrossRef]
  229. Beyer, C.; Pisetsky, D.S. The role of microparticles in the pathogenesis of rheumatic diseases. Nat. Rev. Rheumatol. 2010, 6, 21–29. [Google Scholar] [CrossRef]
  230. Lee, T.H.; Chennakrishnaiah, S.; Audemard, E.; Montermini, L.; Meehan, B.; Rak, J. Oncogenic ras-driven cancer cell vesiculation leads to emission of double-stranded DNA capable of interacting with target cells. Biochem. Biophys. Res. Commun. 2014, 451, 295–301. [Google Scholar] [CrossRef] [Green Version]
  231. Abdouh, M.; Floris, M.; Gao, Z.H.; Arena, V.; Arena, M.; Arena, G.O. Colorectal cancer-derived extracellular vesicles induce transformation of fibroblasts into colon carcinoma cells. J. Exp. Clin. Cancer Res. 2019, 38, 257. [Google Scholar] [CrossRef]
  232. Wartha, F.; Henriques-Normark, B. ETosis: A novel cell death pathway. Sci. Signal. 2008, 1, pe25. [Google Scholar] [CrossRef] [PubMed]
  233. Chen, Q.; Zhang, L.; Li, X.; Zhuo, W. Neutrophil Extracellular Traps in Tumor Metastasis: Pathological Functions and Clinical Applications. Cancers 2021, 13, 2832. [Google Scholar] [CrossRef] [PubMed]
  234. Alekseeva, L.; Mironova, N. Role of Cell-Free DNA and Deoxyribonucleases in Tumor Progression. Int. J. Mol. Sci. 2021, 22, 12246. [Google Scholar] [CrossRef] [PubMed]
  235. Arelaki, S.; Arampatzioglou, A.; Kambas, K.; Papagoras, C.; Miltiades, P.; Angelidou, I.; Mitsios, A.; Kotsianidis, I.; Skendros, P.; Sivridis, E.; et al. Gradient Infiltration of Neutrophil Extracellular Traps in Colon Cancer and Evidence for Their Involvement in Tumour Growth. PLoS ONE 2016, 11, e0154484. [Google Scholar] [CrossRef]
  236. Schedel, F.; Mayer-Hain, S.; Pappelbaum, K.I.; Metze, D.; Stock, M.; Goerge, T.; Loser, K.; Sunderkötter, C.; Luger, T.A.; Weishaupt, C. Evidence and impact of neutrophil extracellular traps in malignant melanoma. Pigment. Cell Melanoma Res. 2020, 33, 63–73. [Google Scholar] [CrossRef] [Green Version]
  237. Breitbach, C.J.; De Silva, N.S.; Falls, T.J.; Aladl, U.; Evgin, L.; Paterson, J.; Sun, Y.Y.; Roy, D.G.; Rintoul, J.L.; Daneshmand, M.; et al. Targeting tumor vasculature with an oncolytic virus. Mol. Ther. 2011, 19, 886–894. [Google Scholar] [CrossRef]
  238. Fűri, I.; Sipos, F.; Spisák, S.; Kiszner, G.; Wichmann, B.; Schöller, A.; Tulassay, Z.; Műzes, G.; Molnár, B. Association of self-DNA mediated TLR9-related gene, DNA methyltransferase, and cytokeratin protein expression alterations in HT29-cells to DNA fragment length and methylation status. Sci. World J. 2013, 2013, 293296. [Google Scholar] [CrossRef] [Green Version]
  239. Sipos, F.; Kiss, A.L.; Constantinovits, M.; Tulassay, Z.; Műzes, G. Modified Genomic Self-DNA Influences In Vitro Survival of HT29 Tumor Cells via TLR9- and Autophagy Signaling. Pathol. Oncol. Res. 2019, 25, 1505–1517. [Google Scholar] [CrossRef]
  240. Bohusné Barta, B.; Simon, Á.; Nagy, L.; Dankó, T.; Raffay, R.E.; Petővári, G.; Zsiros, V.; Sebestyén, A.; Sipos, F.; Műzes, G. Survival of HT29 cancer cells is influenced by hepatocyte growth factor receptor inhibition through modulation of self-DNA-triggered TLR9-dependent autophagy response. PLoS ONE 2022, 17, e0268217. [Google Scholar] [CrossRef]
  241. Sipos, F.; Bohusné Barta, B.; Simon, Á.; Nagy, L.; Dankó, T.; Raffay, R.E.; Petővári, G.; Zsiros, V.; Wichmann, B.; Sebestyén, A.; et al. Survival of HT29 Cancer Cells Is Affected by IGF1R Inhibition via Modulation of Self-DNA-Triggered TLR9 Signaling and the Autophagy Response. Pathol. Oncol. Res. 2022, 28, 1610322. [Google Scholar] [CrossRef]
Figure 1. Potential clinical and experimental applications of cfDNA in non-infectious inflammations and tumors. cfDNA has an immunomodulatory effect in non-infectious inflammations, which is mediated by cfDNA sensing, changes in cytokine production, neutrophil activation, and effects on other immune cells. cfDNA by itself can reduce inflammation, promote tissue healing, and is also suitable for protective pretreatments. In addition, it can serve as a promising starting point for drug development. In tumors, it can play a significant role in population-level screenings, early diagnosis, and therapeutic response determination. In addition to being able to predict the course of the disease, it can also be used to determine any residual disease after treatment. It provides information on the heterogeneity of tumor cells, thereby facilitating the selection of the most effective treatment. It can serve as a basis for drug development. Furthermore, it allows for the monitoring of acquired drug resistance.
Figure 1. Potential clinical and experimental applications of cfDNA in non-infectious inflammations and tumors. cfDNA has an immunomodulatory effect in non-infectious inflammations, which is mediated by cfDNA sensing, changes in cytokine production, neutrophil activation, and effects on other immune cells. cfDNA by itself can reduce inflammation, promote tissue healing, and is also suitable for protective pretreatments. In addition, it can serve as a promising starting point for drug development. In tumors, it can play a significant role in population-level screenings, early diagnosis, and therapeutic response determination. In addition to being able to predict the course of the disease, it can also be used to determine any residual disease after treatment. It provides information on the heterogeneity of tumor cells, thereby facilitating the selection of the most effective treatment. It can serve as a basis for drug development. Furthermore, it allows for the monitoring of acquired drug resistance.
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Figure 2. Schematic representation of cell-free DNA sensing and consequent pathway activation. Class III PI3K promotes the internalization of cfDNA and CpG-ODNs into TLR9-containing endosomal vesicles. The intracytoplasmic activation signal is transmitted via the interaction of cfDNA and TLR9. MyD88 is recruited to the Toll–interleukin-1 receptor domain of TLR9, followed by the activation of the IRAK–TRAF6 complex. This activates both the MAPK and the inhibitor of IKK complexes, resulting in the overexpression of transcription factors, such as NF-kB and AP1. cGAS-mediated detection of cytosolic DNA initiates a STING-dependent reaction. The cGAS-STING pathway can also activate IRFs, mTOR, STAT6, and MAPK in a direct or indirect way. In the cytosol, AIM2 binds to the double-stranded DNA, resulting in the creation of the AIM2 inflammasome. This results in the activation of caspase 1, the maturation of proinflammatory cytokines IL-1β and IL-18, and finally pyroptosis. AP1: activator protein 1; red arrows: upregulation.
Figure 2. Schematic representation of cell-free DNA sensing and consequent pathway activation. Class III PI3K promotes the internalization of cfDNA and CpG-ODNs into TLR9-containing endosomal vesicles. The intracytoplasmic activation signal is transmitted via the interaction of cfDNA and TLR9. MyD88 is recruited to the Toll–interleukin-1 receptor domain of TLR9, followed by the activation of the IRAK–TRAF6 complex. This activates both the MAPK and the inhibitor of IKK complexes, resulting in the overexpression of transcription factors, such as NF-kB and AP1. cGAS-mediated detection of cytosolic DNA initiates a STING-dependent reaction. The cGAS-STING pathway can also activate IRFs, mTOR, STAT6, and MAPK in a direct or indirect way. In the cytosol, AIM2 binds to the double-stranded DNA, resulting in the creation of the AIM2 inflammasome. This results in the activation of caspase 1, the maturation of proinflammatory cytokines IL-1β and IL-18, and finally pyroptosis. AP1: activator protein 1; red arrows: upregulation.
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Table 1. The possible effects of cfDNA on tumor formation.
Table 1. The possible effects of cfDNA on tumor formation.
Harmful and Beneficial Impacts of cfDNA in Tumors
Protumor EffectsAnti-Tumor Effects
TLR9-MyD88 + ODN2395boosts cell growth, migration, invasion, and IL8 secretion [206]cfDNA sensing by TLR9modulates anti-tumor immunity in response to chemotherapy [208]
TLR9-NF-kB-Cyclin D1stimulation of cell proliferation [207]promotes maturation and migration of DCs to lymph nodes [208]
cGAS-STING overexpressionreduces intratumoral inflammatory cell infiltration [210]activates tumor-specific cytotoxic T cells [208]
leads to poor prognosis [210]low expression of cGAS-STINGameliorates inflammation [209]
cGAS down-regulationincreases mortality [211]enhances apoptosis [209]
cGAS-STING inhibition by NEAT1promotes tumor growth [214]STING activationimproves the protective effects of immunotherapy [212]
AIM2 cfDNA sensingmodifies mitochondrial dynamics [218,219]enhances T cell-mediated anti-tumor immunity [213]
cfDNA containing secretomefavors to supportive peritumoral milieu [229]AIM2 (regardless of inflammasome activation)favors tumor cell survival [100,215,216,217]
horizontal DNA transferfavors to supportive peritumoral milieu [227,228,230,231]NET depositiondisplays cytotoxic effects [235,236]
NET formationenhances adhesion, invasion, immune escape [232]inhibits cell growth, migration, survival [235,236]
serves as a scaffold and trapping element [234]induces apoptosis [235]
NET + TLR4-TLR9-HMBG1activates neutrophils [234]
activates tumor cells [234]
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Műzes, G.; Bohusné Barta, B.; Szabó, O.; Horgas, V.; Sipos, F. Cell-Free DNA in the Pathogenesis and Therapy of Non-Infectious Inflammations and Tumors. Biomedicines 2022, 10, 2853. https://doi.org/10.3390/biomedicines10112853

AMA Style

Műzes G, Bohusné Barta B, Szabó O, Horgas V, Sipos F. Cell-Free DNA in the Pathogenesis and Therapy of Non-Infectious Inflammations and Tumors. Biomedicines. 2022; 10(11):2853. https://doi.org/10.3390/biomedicines10112853

Chicago/Turabian Style

Műzes, Györgyi, Bettina Bohusné Barta, Orsolya Szabó, Vanessza Horgas, and Ferenc Sipos. 2022. "Cell-Free DNA in the Pathogenesis and Therapy of Non-Infectious Inflammations and Tumors" Biomedicines 10, no. 11: 2853. https://doi.org/10.3390/biomedicines10112853

APA Style

Műzes, G., Bohusné Barta, B., Szabó, O., Horgas, V., & Sipos, F. (2022). Cell-Free DNA in the Pathogenesis and Therapy of Non-Infectious Inflammations and Tumors. Biomedicines, 10(11), 2853. https://doi.org/10.3390/biomedicines10112853

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