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Molecular Biomarkers in Cancer and Metabolic Disease 2.0

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 10923

Special Issue Editors


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Guest Editor
Dipartimento di Medicina Sperimentale, Università di Roma "La Sapienza", Viale Regina Elena, 291, 00161 Rome, Italy
Interests: precision medicine; biomarkers; liquid biopsy; brain tumours; Hedgehog-Gli signaling; colorectal cancer; thyroid cancer; melanoma; obesity; diabetes
Special Issues, Collections and Topics in MDPI journals

E-Mail Website1 Website2
Guest Editor
Department of Experimental Medicine, Sapienza University of Rome, Viale Regina Elena, 324, 00161 Rome, Italy
Interests: network medicine; bioinformatics; omics; data integration; cancer; diabetes
Special Issues, Collections and Topics in MDPI journals

E-Mail Website1 Website2
Guest Editor
Department of Molecular Medicine, Sapienza University of Rome, Viale Regina Elena, 291, 00161 Rome, Italy
Interests: targeted therapy; non-coding RNAs; lung cancer; cfDNA; microRNAs; cancer stem cells; tumour escape mechanisms; in vivo models; metabolic disorders
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will cover the role of molecular biomarkers in cancer and metabolic disease. In this era, where precision medicine is taking a central role in patient care, we finally have the tools to identify molecular biomarkers, which are ideal, as they are able to both reflect the disease and characterize each individual patient. The challenge today is not only to determine the biomarkers with increased specificity and sensitivity, but also to move them to a clinical setting, thus approaching translational medicine. This issue is dedicated to some of the latest and most remarkable advances involving molecular biomarkers in different contexts. The selected studies that will be included in this issue will cover molecular biomarkers detected in different biological samples and will include nucleic acid-based biomarkers, such as gene mutations and non-coding RNAs. Finally, the latest developments in how molecular biomarkers can be exploited in the development of new targeted therapies and in patients’ follow-up will be discussed. A number of selected reviews will address personalized medicine in the general notion of precision medicine and how the use of network medicine can contribute to our everlasting confrontation with disease. For this reason, we have put together scientists with long-standing experience in the field, as well as young scientists with innovative ideas, to share their precious contributions.

Prof. Dr. Elisabetta Ferretti
Prof. Dr. Zein Mersini Besharat
Prof. Dr. Agnese Po
Guest Editors

Manuscript Submission Information

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Keywords

  • precision medicine
  • biomarkers
  • cancer
  • metabolic disease
  • liquid biopsy
  • targeted therapy
  • risk stratification
  • network medicine

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Related Special Issue

Published Papers (4 papers)

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Research

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11 pages, 785 KiB  
Article
Neurologic Biomarkers, Neuroimaging, and Cognitive Function in Persistent Atrial Fibrillation: A Cross-Sectional Study
by Josip Kedžo, Tea Domjanović Škopinić, Josipa Domjanović, Maja Marinović Guić, Sanja Lovrić Kojundžić, Leida Tandara, Andrija Matetić and Zrinka Jurišić
Int. J. Mol. Sci. 2023, 24(3), 2902; https://doi.org/10.3390/ijms24032902 - 2 Feb 2023
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Abstract
The aim of this study was to evaluate the specific neurologic biomarkers, neuroimaging findings, and cognitive function in patients with persistent atrial fibrillation (AF) undergoing electrical cardioversion, compared to control subjects. This cross-sectional study included 25 patients with persistent AF undergoing electrical cardioversion [...] Read more.
The aim of this study was to evaluate the specific neurologic biomarkers, neuroimaging findings, and cognitive function in patients with persistent atrial fibrillation (AF) undergoing electrical cardioversion, compared to control subjects. This cross-sectional study included 25 patients with persistent AF undergoing electrical cardioversion and 16 age- and sex-matched control subjects. Plasma levels of glial fibrillary acidic protein (GFAP), neurofilament light protein (NFL), and ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1), as well as parameters of neuroimaging and cognitive function, were compared between the groups. Neuroimaging was performed using the standard magnetic resonance imaging (MRI) protocol. Cognitive function was assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Cognitive Function Index. Further analysis of neurologic biomarkers was performed based on the subsequent electrical cardioversion. There was no significant difference in GFAP (median of 24.7 vs. 28.7 pg/mL, p = 0.347), UCH-L1 (median of 112.8 vs. 117.7 pg/mL, p = 0.885), and NFL (median of 14.2 vs. 15.4 pg/mL, p = 0.886) levels between AF patients and control subjects. Similarly, neuroimaging showed no between-group difference in large cortical and non-cortical lesions (n = 2, 8.0% vs. n = 0, 0.0%, p = 0.246), small non-cortical lesions (n = 5, 20.0% vs. n = 5, 31.3%, p = 0.413), white matter hyperintensity (n = 23, 92.0% vs. n = 14, 87.5%, p = 0.636), and thromboembolic lesions (n = 0, 0.0% vs. n = 1, 6.3%, p = 0.206). Cognitive assessment did not show any between-group difference in the PROMIS index (52.2 ± 9.6 vs. 51.2 ± 6.2, p = 0.706). Finally, there were no significant dynamics in neurologic biomarkers following electrical cardioversion (p > 0.05). This hypothesis-generating study did not find a significant difference in neurologic biomarkers, neuroimaging findings, or cognitive function between patients with persistent AF and controls. The restoration of sinus rhythm was not significantly associated with a change in neurologic biomarkers. Further powered longitudinal studies are needed to re-assess these findings in an AF population. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Cancer and Metabolic Disease 2.0)
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16 pages, 2165 KiB  
Article
Data Integration–Possibilities of Molecular and Clinical Data Fusion on the Example of Thyroid Cancer Diagnostics
by Alicja Płuciennik, Aleksander Płaczek, Agata Wilk, Sebastian Student, Małgorzata Oczko-Wojciechowska and Krzysztof Fujarewicz
Int. J. Mol. Sci. 2022, 23(19), 11880; https://doi.org/10.3390/ijms231911880 - 6 Oct 2022
Cited by 4 | Viewed by 2039
Abstract
The data from independent gene expression sources may be integrated for the purpose of molecular diagnostics of cancer. So far, multiple approaches were described. Here, we investigated the impacts of different data fusion strategies on classification accuracy and feature selection stability, which allow [...] Read more.
The data from independent gene expression sources may be integrated for the purpose of molecular diagnostics of cancer. So far, multiple approaches were described. Here, we investigated the impacts of different data fusion strategies on classification accuracy and feature selection stability, which allow the costs of diagnostic tests to be reduced. We used molecular features (gene expression) combined with a feature extracted from the independent clinical data describing a patient’s sample. We considered the dependencies between selected features in two data fusion strategies (early fusion and late fusion) compared to classification models based on molecular features only. We compared the best accuracy classification models in terms of the number of features, which is connected to the potential cost reduction of the diagnostic classifier. We show that for thyroid cancer, the extracted clinical feature is correlated with (but not redundant to) the molecular data. The usage of data fusion allows a model to be obtained with similar or even higher classification quality (with a statistically significant accuracy improvement, a p-value below 0.05) and with a reduction in molecular dimensionality of the feature space from 15 to 3–8 (depending on the feature selection method). Both strategies give comparable quality results, but the early fusion method provides better feature selection stability. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Cancer and Metabolic Disease 2.0)
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Review

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16 pages, 665 KiB  
Review
Extracellular Vesicle-microRNAs as Diagnostic Biomarkers in Preterm Neonates
by Emily A. Schiller, Koral Cohen, Xinhua Lin, Rania El-Khawam and Nazeeh Hanna
Int. J. Mol. Sci. 2023, 24(3), 2622; https://doi.org/10.3390/ijms24032622 - 30 Jan 2023
Cited by 9 | Viewed by 3042
Abstract
Neonates born prematurely (<37 weeks of gestation) are at a significantly increased risk of developing inflammatory conditions associated with high mortality rates, including necrotizing enterocolitis, bronchopulmonary dysplasia, and hypoxic-ischemic brain damage. Recently, research has focused on characterizing the content of extracellular vesicles (EVs), [...] Read more.
Neonates born prematurely (<37 weeks of gestation) are at a significantly increased risk of developing inflammatory conditions associated with high mortality rates, including necrotizing enterocolitis, bronchopulmonary dysplasia, and hypoxic-ischemic brain damage. Recently, research has focused on characterizing the content of extracellular vesicles (EVs), particularly microRNAs (miRNAs), for diagnostic use. Here, we describe the most recent work on EVs-miRNAs biomarkers discovery for conditions that commonly affect premature neonates. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Cancer and Metabolic Disease 2.0)
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19 pages, 728 KiB  
Review
Extracellular Vesicles as Biomarkers in Liver Disease
by Rocío Muñoz-Hernández, Ángela Rojas, Sheila Gato, Javier Gallego, Antonio Gil-Gómez, María José Castro, Javier Ampuero and Manuel Romero-Gómez
Int. J. Mol. Sci. 2022, 23(24), 16217; https://doi.org/10.3390/ijms232416217 - 19 Dec 2022
Cited by 12 | Viewed by 3309
Abstract
Extracellular vesicles (EVs) are membrane-derived vesicles released by a variety of cell types, including hepatocytes, hepatic stellate cells, and immune cells in normal and pathological conditions. Depending on their biogenesis, there is a complex repertoire of EVs that differ in size and origin. [...] Read more.
Extracellular vesicles (EVs) are membrane-derived vesicles released by a variety of cell types, including hepatocytes, hepatic stellate cells, and immune cells in normal and pathological conditions. Depending on their biogenesis, there is a complex repertoire of EVs that differ in size and origin. EVs can carry lipids, proteins, coding and non-coding RNAs, and mitochondrial DNA causing alterations to the recipient cells, functioning as intercellular mediators of cell–cell communication (auto-, para-, juxta-, or even endocrine). Nevertheless, many questions remain unanswered in relation to the function of EVs under physiological and pathological conditions. The development and optimization of methods for EV isolation are crucial for characterizing their biological functions, as well as their potential as a treatment option in the clinic. In this manuscript, we will comprehensively review the results from different studies that investigated the role of hepatic EVs during liver diseases, including non-alcoholic fatty liver disease, non-alcoholic steatohepatitis, alcoholic liver disease, fibrosis, and hepatocellular carcinoma. In general, the identification of patients with early-stage liver disease leads to better therapeutic interventions and optimal management. Although more light needs to be shed on the mechanisms of EVs, their use for early diagnosis, follow-up, and prognosis has come into the focus of research as a high-potential source of ‘liquid biopsies’, since they can be found in almost all biological fluids. The use of EVs as new targets or nanovectors in drug delivery systems for liver disease therapy is also summarized. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Cancer and Metabolic Disease 2.0)
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