Next Article in Journal
Substance Delivery across the Blood-Brain Barrier or the Blood-Retinal Barrier Using Organic Cation Transporter Novel Type 2 (OCTN2)
Previous Article in Journal
Eugenol-Rich Essential Oils from Flower Buds and Leaves of Syzygium aromaticum Show Antifungal Activity against Candida and Cryptococcus Species
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Future Pharmacology
Volume 4
Issue 3
10.3390/futurepharmacol4030026
futurepharmacol-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Deciphering the Complex Interplay of Long Noncoding RNAs and Aurora Kinases: Novel Insights into Breast Cancer Development and Therapeutic Strategies

by
Mona Kamal Saadeldin
1,2,*,
Giuseppe Curigliano
3,4 and
Amal Kamal Abdel-Aziz
5,6
1
Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
2
School of Science and Engineering, American University in Cairo, New Cairo 11835, Egypt
3
European Institute of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), 20141 Milan, Italy
4
Department of Oncology and Haematology, University of Milan, 20122 Milan, Italy
5
Department of Pharmacology and Toxicology, Faculty of Pharmacy, Ain Shams University, Cairo 11566, Egypt
6
Smart Health Initiative, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
*
Author to whom correspondence should be addressed.
Future Pharmacol. 2024, 4(3), 466-478; https://doi.org/10.3390/futurepharmacol4030026
Submission received: 23 June 2024 / Revised: 22 July 2024 / Accepted: 24 July 2024 / Published: 30 July 2024
Browse Figures
Versions Notes

Abstract

:
Breast cancer is the most common type of cancer globally and presents an escalating problem and a huge burden on societies. Several strategies are implemented in clinics to treat patients and prevent disease incidence. Efforts to understand the underlying causes of disease emergence are pivotal, and the latest examination of human transcriptomic studies showed the involvement of the noncoding RNA regulatory molecules in influencing both pathological and physiological conditions. Several molecular mechanisms are involved in the process and collaborate to develop tumor plasticity and drug resistance. In this review, we highlight for the first time the interplay between long noncoding RNAs and Aurora kinases in breast cancer and review the latest advances in the field in an attempt to pave the way for a better understanding of the course of the disease and to delineate the targets for treatment strategies in the clinic.

1. Introduction

Breast cancer is the most common type of cancer worldwide, accounting for almost 2.26 million new cases and 685,000 deaths in 2020 [1]. The epidemiology of breast cancer has been prominently altered in the last years owing to the transformation of lifestyle, the immune system activities that influence cancer behavior, the groundbreaking understanding of the genetics and epigenetic factors of breast cancer using different models, and the newly emerging treatment/therapeutic options [2,3,4,5,6,7].
Owing to the limited availability of FDA-approved therapies for treating breast cancer, particularly triple-negative breast cancer, a systematic dissection of the crosstalk between key oncogenic pathways in breast cancer is fundamental for the rational development of novel, targeted therapies to enhance chemosensitivity and prevent relapse. Indeed, a novel approach is to deal with/modulate a historically deemed piece of junk DNA that accounts for 98% of the human genome and codes for noncoding RNA (ncRNA), which has been shown to be a functional regulatory player in the pathogenesis of breast cancer [8,9].
A crucial family of oncoproteins that plays an important role in breast cancer progression are the Aurora serine/threonine kinases [10,11,12,13]. Therefore, a series of small molecules targeting Aurora kinases have been developed [10,11,12,13]. Some examples of Aurora kinase inhibitors are shown in (Table 1). Nevertheless, our present comprehension remains at the tip of the iceberg, and delving into the mechanisms and canonical pathways involved in disease progression is critical to enable an understanding and the future curing/treatment of breast cancer. In this review, we will systematically discuss the potential interplay between noncoding RNAs and Aurora kinases in breast cancer with a particular emphasis on therapeutic implications.

2. Noncoding RNAs: Types and Roles as Regulatory Elements

Genes are regulated by different molecules and mechanisms, among which are the ncRNAs [17], which can control several processes such as transcription, post-transcriptional changes, chromatin remodeling, and other targets in signal transduction pathways [18]. Regulatory ncRNAs are either short ncRNAs (<200 nucleotides), which were discovered several years ago, or long ncRNAs (>200 nucleotides), which are a more recently discovered class of RNAs. Short ncRNAs comprise microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), short interfering RNAs (siRNAs), and small nuclear RNAs (snoRNAs) [19]. These short ncRNAs exhibit epigenetic regulatory functions in both normal and disease conditions. For instance, miRNAs post-transcriptionally regulate the expression of a major part of the genome, siRNAs post-transcriptionally silence coding genes, piRNAs regulate DNA methylation in germ cells and snoRNAs modulate chemical changes that lead to the maturation of other coding and noncoding RNA molecules [8,20,21].
Regarding the long ncRNAs, investigations of the human transcriptome showed their importance in different physiological and pathological settings [22,23,24]. They are not conserved among different species. They act through chromatin remodeling, transcriptional regulation, and post-transcriptional regulation. They may also serve as precursors for siRNAs. Several recent studies using epigenomic, RNA-sequencing, and computational techniques helped with the discovery of many novel long ncRNAs [25,26]. Concerning the recent version of the Encyclopedia of DNA Elements (ENCODE) Project Consortium (GENECODE version 38), it was revealed that 17,944 and 7567 long and small ncRNA genes are present in the human genome [27], but still many of them have an obscure role. Thus, it is important to study/investigate the potential role/involvement of these newly discovered ncRNAs, including long ncRNAs, in different diseases, including breast cancer [28,29,30,31,32,33,34].

3. Aurora Kinases

3.1. Types, Structure, and Subcellular Localization of Aurora Kinases

An effective and commonly used approach to tackle cancer cells is by targeting mitosis and cell division [10,12]. Vinca alkaloids like vinorelbine, vinblastine, and vincristine, and taxanes such as paclitaxel and docetaxel, which target tubulin during mitosis, are commonly used in oncotherapy. However, owing to tubulin’s importance in all cells, the nonspecificity of vinca alkaloids and taxanes limits their use [35]. Rapidly dividing cells are more influenced by agents affecting the mitosis phase of the cell cycle owing to defects in the mitotic checkpoints compared to differentiated normal cells that endure the transient halting of cell growth. Thus, these defects, including the Aurora kinases, that can be selectively targeted by anticancer therapies are considered potential drug targets [36].
Aurora kinases are serine/threonine kinases that are highly conserved, with a structure consisting of an N-terminal subunit, a protein kinase subunit, and a C-terminal subunit. They are involved in the regulation of mitosis. In mammals, three structurally related Aurora kinases exist: Aurora A kinase (AURKA), Aurora B kinase (AURKB), and Aurora C kinase (AURKC); however, they have different functions and subcellular locations [37]. They are expressed in a cell cycle-dependent fashion [38]. AURKA is located in the centrosome, spindle microtubule, and midbody. It is highly expressed in dividing tissues, reaching its highest levels during the G2/M phase, and its main role is in regulating the centrosome and the mitotic spindle arrangement. AURKB is located in different cellular regions throughout the various stages of mitosis, including the inner centromeric region during prophase and metaphase and the spindle midzone and midbody from anaphase to cytokinesis. In rapidly dividing cells, the levels and activity of AURKB are controlled by the cell cycle; its highest levels are present during the G2/M phase, and its highest kinase activity occurs during mitosis. It is a member of the chromosomal passenger protein complex and is crucial in cytokinesis. Thirdly, AURKC is the newest member of the family and has roles that are similar to AURKB. It is also a member of the chromosomal passenger protein complex and exists in the chromosome midbody. However, it plays a role in the formation of sperms in the testes [36,39]. The importance of Aurora kinases became clear after the discovery of their roles in cancer development.

3.2. Functions of Aurora Kinases in Diverse Types of Cancer, Including Breast Cancer

The three Aurora kinases AURKA, AURKB, and AURKC that are expressed in human cancers are located in highly unstable chromosomal regions (20q13.2, 17p13.1, and 10q13, respectively) that are vulnerable to different types of mutations [40]. AURKA and AURKB are well studied because of their elevated expression levels in aneuploid cancers (Figure 1) [41,42]. The link between cancer and Aurora kinases fostered the discovery and development of novel Aurora kinase inhibitors [11,12,15,36,40].
Silencing AURKA and AURKB halted the growth of cancer cells and sensitized them to concurrently administered chemotherapeutic agents through several mechanisms, including the deregulation of mitotic checkpoints, leading to polyploidy and the induction of apoptosis [11,43,44,45]. Thus, these studies highlighted the usefulness of Aurora kinases as targets for cancer therapy.
Futurepharmacol 04 00026 g001
Figure 1. Differential expression pattern of Aurora kinases (AURKA, AURKB, and AURKC) between in tumor tissue and adjacent normal tissues across diverse TCGA tumors. Distributions of gene expression levels are illustrated using box plots obtained from the TIMER2.0 database, adapted from [46], Oxford University Press, 2020. Statistical significance was computed using the Wilcoxon test (*: p < 0.05; **: p < 0.01; ***: p < 0.001). TCGA abbreviations: ACC: adrenocortical carcinoma, BLCA: bladder urothelial carcinoma, BRCA: breast invasive carcinoma, CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma, CHOL: cholangiocarcinoma, COAD: colon adenocarcinoma, DLBC: lymphoid neoplasm diffuse large B-cell lymphoma, ESCA: esophageal carcinoma, GBM: glioblastoma multiforme, HNSC: head and neck squamous cell carcinoma, KICH: kidney chromophobe, KIRC: kidney renal clear cell carcinoma, KIRP: kidney renal papillary cell carcinoma, LAMA: acute myeloid leukemia, LGG: brain lower grade glioma, LIHC: liver hepatocellular carcinoma, LUAD: lung adenocarcinoma, LUSC: lung squamous cell carcinoma, MESO: mesothelioma, OV: ovarian serous cystadenocarcinoma, PAAD: pancreatic adenocarcinoma, PCPG: pheochromocytoma and paraganglioma, PRAD: prostate adenocarcinoma, READ: rectum adenocarcinoma, SARC: sarcoma, SKCM: skin cutaneous melanoma, STAD: stomach adenocarcinoma, TGCT: testicular germ cell tumors, THYM: thymoma, THCA: thyroid carcinoma, UCS: uterine carcinosarcoma, UCEC: uterine corpus endometrial carcinoma, and UVM: uveal melanoma.
Figure 1. Differential expression pattern of Aurora kinases (AURKA, AURKB, and AURKC) between in tumor tissue and adjacent normal tissues across diverse TCGA tumors. Distributions of gene expression levels are illustrated using box plots obtained from the TIMER2.0 database, adapted from [46], Oxford University Press, 2020. Statistical significance was computed using the Wilcoxon test (*: p < 0.05; **: p < 0.01; ***: p < 0.001). TCGA abbreviations: ACC: adrenocortical carcinoma, BLCA: bladder urothelial carcinoma, BRCA: breast invasive carcinoma, CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma, CHOL: cholangiocarcinoma, COAD: colon adenocarcinoma, DLBC: lymphoid neoplasm diffuse large B-cell lymphoma, ESCA: esophageal carcinoma, GBM: glioblastoma multiforme, HNSC: head and neck squamous cell carcinoma, KICH: kidney chromophobe, KIRC: kidney renal clear cell carcinoma, KIRP: kidney renal papillary cell carcinoma, LAMA: acute myeloid leukemia, LGG: brain lower grade glioma, LIHC: liver hepatocellular carcinoma, LUAD: lung adenocarcinoma, LUSC: lung squamous cell carcinoma, MESO: mesothelioma, OV: ovarian serous cystadenocarcinoma, PAAD: pancreatic adenocarcinoma, PCPG: pheochromocytoma and paraganglioma, PRAD: prostate adenocarcinoma, READ: rectum adenocarcinoma, SARC: sarcoma, SKCM: skin cutaneous melanoma, STAD: stomach adenocarcinoma, TGCT: testicular germ cell tumors, THYM: thymoma, THCA: thyroid carcinoma, UCS: uterine carcinosarcoma, UCEC: uterine corpus endometrial carcinoma, and UVM: uveal melanoma.
Futurepharmacol 04 00026 g001

3.2.1. Oncogenic Functions Related to Aurora Kinases Overexpression

Aurora kinase A (AURKA) was found to play a role in the cancerous transformation of cells both through (i) its mitotic function of evoking chromosomal instability, thus affecting the cells’ proliferation, and (ii) its non-mitotic functions of activating epithelial–mesenchymal transition and metastasis that lead to the self-renewing ability of cancer stem cells by enhancing the formation of tumor-initiating cells [38].
On the other hand, the overexpression of AURKB exerts its oncogenic effect through its mitotic function by promoting defective chromosomal segregation and aneuploidy, abrogating the DNA damage response, and inhibiting the p53 tumor suppressor gene by decreasing the levels of its cell cycle inhibitor target p21Cip1 [42]. The expression pattern of AURKC in cancer tissues versus normal tissues is still unclear (Figure 1), but a study reported that it may aid in tumorigenesis by overlapping with the function of AURKB; however, its exact mechanism is still unknown [39,40,47].

3.2.2. Oncogenic Functions Related to the Aurora Kinases Networking with Tumor Regulators

p53 Tumor Suppressor Gene

Aurora kinases function in collaboration with different regulatory tumor suppressor genes and oncogenes, forming a complex network that promotes cancer initiation and progression. Among these key players is the p53 gene. AURKA abrogates p53 transcription and promotes its ubiquitination and proteasome-mediated degradation by the E3 ubiquitin protein ligase (mouse double minute 2 homolog: MDM2). It also phosphorylates Ser379 of heterogeneous nuclear ribonucleoprotein K (hnRNPK), a transcriptional p53 coactivator, leading to the consequent inhibition of p53 [48].
In addition to directly interacting with p53 and phosphorylating it at Ser183, Thr211, and Ser215 (like AURKA does), AURKB binds to novel inhibitor of histone acetyltransferase repressor (NIR), forming a complex that facilitates the binding of AURKB to the p53 DNA-binding domain. This results in the phosphorylation of the latter at Thr284 and Ser269, leading to the subsequent inhibition of p53 transcription [49]. Further studies are needed/warranted to investigate the potential interaction between AURKC and p53.
Regarding the feedback loop, when p53 is silenced, p21wAF1/CIP1 expression decreases, leading to an increase in cyclin-dependent kinase 2 (Cdk2) activity, which hyperphosphorylates retinoblastoma transcriptional corepressor 1 (Rb1), causing Rb1 dissociation from the E2F transcription factor 3 (E2F3). The release of the latter binds to the AURKA gene promoter and increases AURKA expression [50]. Moreover, p53 silencing upregulates the oncogenic miRNA miR-25, which in turn decreases the levels of the tumor suppressor gene F-box and WD repeat-containing 7 (FBXW7), resulting in AURKA overexpression in prostatic small cell neuroendocrine carcinoma [51]. Interestingly, FBXW7 inhibits AURKB; thus, nonfunctioning FBXW7 increases the levels of AURKB. Thus, collectively, any defect in the p53/FBXW7/AURKB loop leads to oncogenesis [52].

Myc Oncogene and Other Signaling Pathways Involved in Oncogenesis

Myc oncoproteins promote uncontrolled cell growth. c-Myc, one member of the Myc family of oncogenes, directly increases AURKA and indirectly increases AURKB in different tumors. c-Myc and AURKA upregulate each other: c-Myc binds to the AURKA promoter and increases its transcription, and AURKA can bind to the c-Myc promoter and derepress its transcription [53,54]. AURKA also protects N-myc (a member of the Myc family) and prevents its proteasomal degradation [55].

BRCA Tumor Suppressor Genes and RAS Oncogene

Breast cancer gene 1 (BRCA1) and breast cancer gene 2 (BRCA2) are tumor suppressor genes whose functions are inhibited by AURKA. AURKA can phosphorylate and subsequently inactivate BRCA1, leading to chromosomal instability and tumor progression [56]. Regarding BRCA2, there is an inverse relationship between a functioning BRCA2 and AURKA, where AURKA inactivates BRCA2. In the case of mutated BRCA2, AURKA phosphorylates cell division cycle phosphatase 25B (CDC25B) at Ser353, leading to the activation of cyclin-dependent kinase 1 (CDK1). Therefore, AURKA promotes tumorigenesis and is thus considered a marker of BRCA2 mutation-induced breast cancer [57,58,59].
It is worth mentioning that RAS acts upstream of both AURKA and BRCA2. Indeed, RAS upregulates AURKA and downregulates BRCA2 and ultimately promotes tumorigenesis [60].

Other Signaling Proteins

Protein kinase C (PKC) induces tumor invasion and migration by inducing the phosphorylation of AURKA and AURKB by mitogen-activated protein kinase (MAPK), which leads to further activation of the transcriptional factors nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1) [40]. In addition, AURKA inhibits glycogen synthase kinase 3β (GSK3β), which increases the nuclear translocation and transcription of β-catenin [61]. A third mechanism is through the Akt signaling pathway, where there are Bcr–Abl-mediated elevations of AURKA and AURKB [62].
Inhibiting AURKA suppressed the mammalian target of rapamycin (mTOR) and subsequently activated autophagy, leading to drug resistance in breast cancer [63,64].

3.2.3. Aurora Kinases and Chemoresistance in Breast Cancer

The resistance of estrogen-driven breast cancers to chemotherapy was shown to be partially due to AURKA. Estrogen-induced cell proliferation is mediated through estrogen’s indirect effect on AURKA, which leads to increases in AURKA levels in breast cancer cells during short-term treatment. Indeed, Aurora kinase inhibitors (AKIs) reversed the resistance of estrogen-induced tumors [65].
The Aurora kinase A (AURKA)-mediated phosphorylation of PHLDA1 leads to the degradation of pleckstrin homology-like domain protein (PHLDA1) and promotes cell survival. PHLDA1 also regulates AURKA via negative feedback [66]. Another interesting target is the ZNF217 oncogene, whose expression level increases with AURKA expression levels in breast cancer. Paclitaxel resistance was found to be mediated by ZNF217, which diminishes drug-mediated apoptotic signals [67]. After the knockdown of AURKA, resistant breast cancer cells responded to taxol therapy. Moreover, AURKA silencing abrogated mTOR- and SRC-mediated ERK pathways [68].
Although there was no difference in AURKB protein levels in wild-type triple-negative breast cancer cell lines (including MDA-MB-231 and BT549) and taxol-resistant cell lines (MDA-MB-231/PTX and BT549/PTX), its phosphorylation level in drug-resistant cells was significantly higher than that of wild-type cells [69]. Notably, genetic as well as pharmacological tools that interfere with AURKB phosphorylation effectively reversed paclitaxel resistance in breast cancer cells [69].

4. The Potential Interplay between Aurora Kinases and Noncoding RNAs in Breast Cancer/Aurora Kinases Together with Noncoding RNAs in Breast Cancer

Accumulating evidence emphasizes the prominent roles of lncRNAs in breast cancer (extensively reviewed elsewhere) [69]. In this section, we will shed light on lncRNAs, which are overexpressed in breast cancer [69], and whose expression positively correlated with at least one of the Aurora kinases (Figure 2). To this end, we exploited the invasive breast carcinoma TCGA dataset on cBioPortal (which comprises 994 biospecimens/patients) and identified some lncRNAs whose expression is positively correlated with that of at least one of the Aurora kinases (Figure 2).
The tendency of alterations in certain cancer genes to co-occur suggests that these genes may work in tandem to drive the formation and progression of breast cancer [70]. Therefore, we further investigated the tendency of genetic alterations in lncRNAs overexpressed in breast cancer [69]; the expression of these lncRNAs positively correlated with that of at least one of the Aurora kinases, and this was mutually exclusive or co-occurred in invasive breast cancer (Table 2).

4.1. Thymopoietin Antisense Transcript 1 (TMPO-AS1)

The lncRNA TMPO-AS1 is located on human chromosome 12p23.1. TMPO-AS1 is upregulated in endocrine therapy-resistant breast cancer cells (such as MCF-7) and in docetaxel-resistant breast cancer cells (including MDA-MB-231 and MCF7) compared with the sensitive parental cells [73,74]. TMPO-AS1 promoted hormone-dependent breast cancer progression by interacting with and stabilizing estrogen receptor-1 (ESR1) mRNA [75]. TMPO-AS1 knockdown abrogated the proliferation of estrogen receptor-positive breast cancer cells (such as MCF7) and TNBC cells (such as MDA-MB-231) [74,76]. Knocking down TMPO-AS1 resensitized resistant MDA-MB-231 and MCF7 cells to docetaxel by depleting tripartite motif-containing protein 37 (TRIM37) through the sponging of miR-1179 [73]. Exploiting cancer-targeted polyion complex micelle or nanoball drug delivery systems to interfere with TMPO-AS1 impaired the growth of primary and metastatic TNBC in vivo [76].
Interrogating the invasive breast cancer TCGA dataset revealed that the expression of TMPO-AS1 is significantly positively correlated with the transcript levels of AURKA and AUKRB, but not AURKC (Figure 2A–C). Moreover, the tendency of invasive breast cancer cells to harbor co-occurring genetic alterations in both TMPO-AS1 and AURKA and/or AUKRB is statistically significant (Table 2). These findings are interesting. However, further studies are warranted to systematically investigate the potential regulatory crosstalk between TMPO-AS1 and AUKRA and/or AURKB. It would also be rational to examine whether the co-targeting of TMPO-AS1/AURKA/AUKRB has superior efficacy compared to monotherapy in the treatment of breast cancer.

4.2. Cytoskeleton Regulator Long Noncoding RNA (CYTOR)

Cytoskeleton regulator long noncoding RNA (CYTOR, also known as Linc00152) is located on human chromosome 2p11.2. CYTOR is a potential biomarker that has been detected in the tumor and plasma biospecimens of breast cancer patients [77]. The levels of CYTOR are significantly higher in tamoxifen-resistant breast cancer cells (such as MCF-7/TAM1 and MCF-7/TAM2) and the tissues of tamoxifen-unresponsive patients than in parental breast cancer cells (such as MCF-7 cells) and the tissues of patients who were not treated with tamoxifen simultaneously. Knocking down CYTOR resensitized resistant breast cancer cells to tamoxifen [78]. Digging deeper, CYTOR directly bound and repressed miR-125a-5p expression, which ultimately upregulated serum response factor expression and stimulated Hippo and mitogen-associated protein kinase prosurvival signaling pathways in breast cancer [78]. Of note, the transcript levels of CYTOR positively correlated with those of the Aurora kinases, in particular AURKB and AURKC, in the biospecimens obtained from invasive breast cancer patients (Figure 2D–F). Yet, further studies are needed to uncover whether this association/correlation is causative.

4.3. Plasmacytoma Variant Translocation 1 (PVT1)

Plasmacytoma variant translocation 1 (PVT1) is located on human chromosome 8q24. PVT1 is upregulated in breast cancer cell lines as well as in the plasma and tissues of breast cancer patients [76,79,80]. PVT1 promoted the proliferation metastasis, and glycolysis of breast cancer cells [76,79,80]. The levels of PVT1 lncRNA and Myc protein were positively correlated in diverse types of human primary tumors, including breast cancer [81]. Molecularly, PVT1 increases Myc protein levels in 8q24 gain cancers. Indeed, depleting PVT1, which in turn reduces Myc protein levels, has been proposed as a treatment for Myc-driven cancers [81]. PVT1 lnRNA levels significantly correlated with the transcript levels of Aurora kinases, especially AURKA and AURKB, in the biospecimens of invasive breast cancer patients (Figure 2G–I). There is also a tendency for the genetic alterations in PVT1 and AURKA or AURKB to co-occur in invasive breast cancer (Table 2). These preliminary findings are suggestive and mandate further validation experiments.

4.4. HLA Complex P5 (HCP5)

HLA complex P5 (HCP5) is located on human chromosome 6p21.33. HCP5 is upregulated in TNBC cell lines and is associated with the prognosis of breast cancer [82,83]. Mechanistically, HCP5 acts as a competing endogeneous RNA (ceRNA) that competes with BIRC3 baculoviral IAP repeat containing 3 (BIRC3) by sponging miR-219a-5p [83]. Knocking down HCP5 inhibited the proliferation and triggered the apoptosis of TNBC tumors in vitro and in vivo [83]. HCP5 lncRNA levels positively correlated with the transcript levels of AURKA and AURKB (Figure 2J–L). A significant tendency of the genetic alterations in HCP5 and AURKA to co-occur was noted in the biospecimens of invasive breast cancer patients (Table 2).

4.5. Differentiation Antagonizing Non-Protein Coding RNA (DANCR)

Differentiation antagonizing non-protein coding RNA (DANCR) is located on human chromosome 4q12. DANCR is significantly upregulated in primary human breast cancer biospecimens and breast cancer cell lines compared with normal tissues and breast epithelial cells [84,85]. At the molecular level, DANCR promoted the binding of enhancer of zeste homolog 2 (EZH2) to the promoter of suppressor of cytokine signaling 3 (SOCS3) and, hence, epigenetically depressed SOCS3 expression [84]. DANCR also augmented the phosphorylation of serine 49/78 on retinoid X receptor alpha (RXRA) and activated phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) transcription and PI3K/AKT signaling. As expected, ablating DANCR reduced the growth of TNBC in vitro and in vivo [84,85]. DANCR positively correlated with the transcript levels of the Aurora kinases such as AURKB (Figure 2M–O). The genetic alterations in DANCR and AURKA or AURKB demonstrated a tendency to co-occur in the biospecimens of invasive breast cancer patients (Table 2).

5. Conclusions and Future Perspectives

In summary, breast cancer represents an escalating challenge and a massive burden worldwide, necessitating the exploration ofing novel potential strategies for its confrontation and alleviating patients suffering. Numerous efforts have been employed to date aiming at comprehending the disease pathogenesis and several studies demonstrated the pivotal roles played by the ncRNA regulatory molecules and aurora kinases in orchestrating the underlying physiologic and pathologic conditions. Interestingly, the tendency of concomitant alterations often observed in certain lncRNAs cancer-related genes and aurora kinases in breast cancer offers a fertile ground for further investigation. These co-alterations serve as promising prime targets to be further examined in the preclinical and clinical settings, for potential interplays between the the ncRNA regulatory machinery and aurora kinases that could revolutionize breast cancer management through concurrent targeting.
In addition, further validation of the reliability of the associations and correlations between specific ncRNA transcript levels and aurora kinases emerges as a convincing path for future research. This holds the merit of discovering reliable biomarkers, thereby facilitating earlier detection and assessment of the diseases, treatment monitoring, and better prognosis. Moreover, understanding the molecular crosstalks between ncRNA networks and aurora kinases, involving transcriptomics, genomics, proteomics, and functional assays, could potentially guide the discovery of new therapeutic modalities for innovative combinational strategies, that leverage the power of both entities in breast cancer.

Author Contributions

Conceptualization, M.K.S.; investigation, M.K.S. and A.K.A.-A.; formal analysis, M.K.S., A.K.A.-A. and G.C.; validation, M.K.S.; visualization, A.K.A.-A.; writing—original draft preparation, M.K.S. and A.K.A.-A.; writing—review and editing, M.K.S., A.K.A.-A., G.C. 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.

Abbreviations

AURKA: Aurora kinase A, AURKB: Aurora kinase B, AURKC: Aurora kinase C, DANCR: differentiation antagonizing non-protein coding RNA, HCP5: HLA complex P5, ceRNA: competing endogenous RNA, miRNA: microRNA, ncRNA: noncoding RNA, piRNA: piwi-interacting RNA, PVT1: plasmacytoma variant translocation 1, siRNA: short interfering RNA, snoRNA: small nuclear RNA, TMPO-AS1: thymopoietin antisense transcript 1.

References

  1. World Health Organization. Cancer., Cancer 3. 2021. Available online: https://www.who.int/news-room/fact-sheets/detail/cancer (accessed on 21 August 2021).
  2. Bade, B.C.; Dela Cruz, C.S. Lung Cancer 2020: Epidemiology, Etiology, and Prevention. Clin. Chest Med. 2020, 41, 1–24. [Google Scholar] [CrossRef] [PubMed]
  3. Abdel-Aziz, A.K.; Saadeldin, M.K.; D’Amico, P.; Orecchioni, S.; Bertolini, F.; Curigliano, G.; Minucci, S. Preclinical models of breast cancer: Two-way shuttles for immune checkpoint inhibitors from and to patient bedside. Eur. J. Cancer 2019, 122, 22–41. [Google Scholar] [CrossRef] [PubMed]
  4. Milik, S.N.; Abdel-Aziz, A.K.; El-Hendawy, M.M.; El-Gogary, R.I.; Saadeldin, M.K.; Minucci, S.; Klein, C.D.; Abouzid, K.A.M. Insights into the design of inhibitors of the EGFR family with anticancer activity overcoming resistance: A case of optimizing thieno[2,3-d]pyrimidine-based EGFR inhibitors. J. Mol. Struct. 2022, 1259, 132724. [Google Scholar] [CrossRef]
  5. Farnoosh, G.; Saeedi-Boroujeni, A.; Jalali, A.; Keikhaei, B.; Mahmoudian-Sani, M.R. Polymorphisms in Genes Involved in Breast Cancer Among Iranian Patients. Per. Med. 2021, 18, 153–169. [Google Scholar] [CrossRef] [PubMed]
  6. Lehmann, T.P.; Miskiewicz, J.; Szostak, N.; Szachniuk, M.; Grodecka-Gazdecka, S.; Jagodzinski, P.P. In vitro and in silico analysis of MiR-125a with rs12976445 polymorphism in breast cancer patients. Appl. Sci. 2020, 10, 7275. [Google Scholar] [CrossRef]
  7. Leitão, M.; Lopes, S.; Pereira, D.; Medeiros, R.; Vieira, C. Genetic Polymorphisms as Predictors of Survival in Breast Cancer: Future Lessons in Historical Data. Cureus 2022, 14, 3–10. [Google Scholar] [CrossRef] [PubMed]
  8. Youness, R.A.; Gad, M.Z. Long non-coding RNAs: Functional regulatory players in breast cancer. Non-Coding RNA Res. 2019, 4, 36–44. [Google Scholar] [CrossRef] [PubMed]
  9. Sun, L.; Luo, H.T.; Liao, Q.; Bu, D.C.; Zhao, G.G.; Liu, C.N.; Liu, Y.N.; Zhao, Y. Systematic study of human long intergenic non-coding RNAs and their impact on cancer. Sci. China Life Sci. 2013, 56, 324–334. [Google Scholar] [CrossRef] [PubMed]
  10. Gully, C.P.; Zhang, F.; Chen, J.; Yeung, J.A.; Velazquez-torres, G.; Wang, E.; Yeung, S.J.; Lee, M. Antineoplastic effects of an Aurora B kinase inhibitor in breast cancer. Mol. Cancer 2010, 9, 42. [Google Scholar] [CrossRef] [PubMed]
  11. Dokla, E.M.E.E.; Abdel-Aziz, A.K.; Milik, S.N.; Mahmoud, A.H.; Saadeldin, M.K.; McPhillie, M.J.; Minucci, S.; Abouzid, K.A.M.; Kamal, M.; McPhillie, M.J.; et al. Indolin-2-one derivatives as selective Aurora B kinase inhibitors targeting breast cancer. Bioorg. Chem. 2021, 117, 105451. [Google Scholar] [CrossRef] [PubMed]
  12. Lakkaniga, N.R.; Zhang, L.; Belachew, B.; Gunaganti, N.; Frett, B.; Li, H. yu Discovery of SP-96, the first non-ATP-competitive Aurora Kinase B inhibitor, for reduced myelosuppression. Eur. J. Med. Chem. 2020, 203, 112589. [Google Scholar] [CrossRef] [PubMed]
  13. Kawai, M.; Nakashima, A.; Kamada, S.; Kikkawa, U. Midostaurin preferentially attenuates proliferation of triple-negative breast cancer cell lines through inhibition of Aurora kinase family. J. Biomed. Sci. 2015, 22, 48. [Google Scholar] [CrossRef] [PubMed]
  14. Koeffler, P.; Taguchi, H.; Yang, J.; Ikezoe, T.; Taizo, C.; Tasaka, N.; Taniguchi, A.; Kuwayama, Y.; Komatsu, N.; Bandobashi, K.; et al. AZD1152, a novel and selective aurora B kinase inhibitor, induces growth arrest, apoptosis, and sensitization for tubulin depolymerizing agent or topoisomerase IIinhibitor in human acute leukemia cells in vitro and in vivo. Blood 2007, 110, 2034–2040. [Google Scholar]
  15. Borah, N.A.; Reddy, M.M. Aurora Kinase B Inhibition: A Potential Therapeutic Strategy for Cancer. Molecules 2021, 26, 1981. [Google Scholar] [CrossRef] [PubMed]
  16. Ding, Y.H.; Zhou, Z.W.; Ha, C.F.; Zhang, X.Y.; Pan, S.T.; He, Z.X.; Edelman, J.L.; Wang, D.; Yang, Y.X.; Zhang, X.; et al. Alisertib, an Aurora kinase A inhibitor, induces apoptosis and autophagy but inhibits epithelial to mesenchymal transition in human epithelial ovarian cancer cells. Drug Des. Devel. Ther. 2015, 9, 425–464. [Google Scholar] [CrossRef] [PubMed]
  17. Bartel, D.P. MicroRNAs: Genomics, Biogenesis, Mechanism, and Function. Biosens. Bioelectron. 2004, 116, 281–297. [Google Scholar] [CrossRef]
  18. Anastasiadou, E.; Jacob, L.S.; Slack, F.J. Non-coding RNA networks in cancer. Nat. Rev. Cancer 2018, 18, 5–18. [Google Scholar] [CrossRef] [PubMed]
  19. Morceau, F.; Chateauvieux, S.; Gaigneaux, A.; Dicato, M.; Diederich, M. Long and short non-coding RNAs as regulators of hematopoietic differentiation. Int. J. Mol. Sci. 2013, 14, 14744–14770. [Google Scholar] [CrossRef] [PubMed]
  20. Youness, R.A.; El-Tayebi, H.M.; Assal, R.A.; Hosny, K.; Esmat, G.; Abdelaziz, A.I. MicroRNA-486-5p enhances hepatocellular carcinoma tumor suppression through repression of IGF-1R and its downstream mTOR, STAT3 and c-Myc. Oncol. Lett. 2016, 12, 2567–2573. [Google Scholar] [CrossRef] [PubMed]
  21. Gulìa, C.; Baldassarra, S.; Signore, F.; Rigon, G.; Pizzuti, V.; Gaffi, M.; Briganti, V.; Porrello, A.; Piergentili, R. Role of non-coding RNAs in the etiology of bladder cancer. Genes 2017, 8, 339. [Google Scholar] [CrossRef] [PubMed]
  22. Huarte, M. The emerging role of lncRNAs in cancer. Nat. Med. 2015, 21, 1253–1261. [Google Scholar] [CrossRef] [PubMed]
  23. Yu, C.Y.; Kuo, H.C. The emerging roles and functions of circular RNAs and their generation. J. Biomed. Sci. 2019, 26, 29. [Google Scholar] [CrossRef] [PubMed]
  24. Pandini, C.; Pagani, G.; Tassinari, M.; Vitale, E.; Bezzecchi, E.; Saadeldin, M.K.; Doldi, V.; Giannuzzi, G.; Mantovani, R.; Chiara, M.; et al. The pancancer overexpressed NFYCAntisense 1 controls cell cycle mitotic progression through in cis and in trans modes of action. Cell Death Dis. 2024, 15, 206. [Google Scholar] [CrossRef] [PubMed]
  25. Guttman, M.; Amit, I.; Garber, M.; French, C.; Lin, M.F.; Feldser, D.; Huarte, M.; Zuk, O.; Carey, B.W.; Cassady, J.P.; et al. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature 2009, 458, 223–227. [Google Scholar] [CrossRef] [PubMed]
  26. Clark, M.B.; Mercer, T.R.; Bussotti, G.; Leonardi, T.; Haynes, K.R.; Crawford, J.; Brunck, M.E.; Cao, K.A.L.; Thomas, G.P.; Chen, W.Y.; et al. Quantitative gene profiling of long noncoding RNAs with targeted RNA sequencing. Nat. Methods 2015, 12, 339–342. [Google Scholar] [CrossRef] [PubMed]
  27. UCSC. Genome Browser (Genecode Version v. 38). 2002. Available online: https://genome.ucsc.edu/cgi-bin/hgTrackUi?g=knownGene (accessed on 22 October 2021).
  28. Fan, L.; Huang, X.; Chen, J.; Zhang, K.; Gu, Y.H.; Sun, J.; Cui, S.Y. Long noncoding RNA MALAT1 contributes to sorafenib resistance by targeting miR-140-5p/aurora-a signaling in hepatocellular carcinoma. Mol. Cancer Ther. 2020, 19, 1197–1209. [Google Scholar] [CrossRef] [PubMed]
  29. Archer, K.; Broskova, Z.; Bayoumi, A.S.; Teoh, J.P.; Davila, A.; Tang, Y.; Su, H.; Kim, I.M. Long non-coding RNAs as master regulators in cardiovascular diseases. Int. J. Mol. Sci. 2015, 16, 23651–23667. [Google Scholar] [CrossRef] [PubMed]
  30. Bhan, A.; Soleimani, M.; Mandal, S.S. Long noncoding RNA and cancer: A new paradigm. Cancer Res. 2017, 77, 3965–3981. [Google Scholar] [CrossRef] [PubMed]
  31. Qiu, L.; Wang, T.; Tang, Q.; Li, G.; Wu, P.; Chen, K. Long non-coding RNAs: Regulators of viral infection and the interferon antiviral response. Front. Microbiol. 2018, 9, 1621. [Google Scholar] [CrossRef] [PubMed]
  32. Salta, E.; De Strooper, B. Noncoding RNAs in neurodegeneration. Nat. Rev. Neurosci. 2017, 18, 627–640. [Google Scholar] [CrossRef] [PubMed]
  33. Saadeldin, M.K. Highlights from the ‘Noncoding RNA world: From Mechanism to Therapy’ conference, July 21–23, 2021. World Acad. Sci. J. 2021, 3, 64. [Google Scholar] [CrossRef]
  34. Quinn, J.J.; Chang, H.Y. Unique features of long non-coding RNA biogenesis and function. Nat. Rev. Genet. 2016, 17, 47–62. [Google Scholar] [CrossRef] [PubMed]
  35. Jackson, J.R.; Patrick, D.R.; Dar, M.M.; Huang, P.S. Targeted anti-mitotic therapies: Can we improve on tubulin agents? Nat. Rev. Cancer 2007, 7, 107–117. [Google Scholar] [CrossRef] [PubMed]
  36. Colombo, R.; Moll, J. Target validation and biomarker identification in oncology: The example of Aurora kinases. Mol. Diagnosis Ther. 2008, 12, 71–76. [Google Scholar] [CrossRef] [PubMed]
  37. Carmena, M.; Earnshaw, W.C. The cellular geography of Aurora kinases. Nat. Rev. Mol. Cell Biol. 2003, 4, 842–854. [Google Scholar] [CrossRef] [PubMed]
  38. D’Assoro, A.B.; Haddad, T.; Galanis, E. Aurora-A kinase as a promising therapeutic target in cancer. Front. Oncol. 2016, 5, 295. [Google Scholar] [CrossRef]
  39. Sasai, K.; Katayama, H.; Stenoien, D.L.; Fujii, S.; Honda, R.; Kimura, M.; Okano, Y.; Tatsuka, M.; Suzuki, F.; Nigg, E.A.; et al. Aurora-C kinase is a novel chromosomal passenger protein that can complement Aurora-B kinase function in mitotic cells. Cell Motil. Cytoskeleton 2004, 59, 249–263. [Google Scholar] [CrossRef] [PubMed]
  40. Tang, A.; Gao, K.; Chu, L.; Zhang, R.; Yang, J.; Zheng, J. Aurora kinases: Novel therapy targets in cancers. Oncotarget 2017, 8, 23937–23954. [Google Scholar] [CrossRef] [PubMed]
  41. Sakakura, C.; Hagiwara, A.; Yasuoka, R.; Fujita, Y.; Nakanishi, M.; Masuda, K.; Shimomura, K.; Nakamura, Y.; Inazawa, J.; Abe, T.; et al. Tumour-amplified kinase BTAK is amplified and overexpressed in gastric cancers with possible involvement in aneuploid formation. Br. J. Cancer 2001, 84, 824–831. [Google Scholar] [CrossRef]
  42. González-Loyola, A.; Fernández-Miranda, G.; Trakala, M.; Partida, D.; Samejima, K.; Ogawa, H.; Cañamero, M.; de Martino, A.; Martínez-Ramírez, Á.; de Cárcer, G.; et al. Aurora B Overexpression Causes Aneuploidy and p21 Cip1 Repression during Tumor Development. Mol. Cell. Biol. 2015, 35, 3566–3578. [Google Scholar] [CrossRef] [PubMed]
  43. Hata, T.; Furukawa, T.; Sunamura, M.; Egawa, S.; Motoi, F.; Ohmura, N.; Marumoto, T.; Saya, H.; Horii, A. RNA interference targeting aurora kinase A suppresses tumor growth and enhances the taxane chemosensitivity in human pancreatic cancer cells. Cancer Res. 2005, 65, 2899–2905. [Google Scholar] [CrossRef] [PubMed]
  44. Carpinelli, P.; Ceruti, R.; Giorgini, M.L.; Cappella, P.; Gianellini, L.; Croci, V.; Degrassi, A.; Texido, G.; Rocchetti, M.; Vianello, P.; et al. PHA-739358, a potent inhibitor of Aurora kinases with a selective target inhibition profile relevant to cancer. Mol. Cancer Ther. 2007, 6, 3158–3168. [Google Scholar] [CrossRef] [PubMed]
  45. Harrington, E.A.; Bebbington, D.; Moore, J.; Rasmussen, R.K.; Ajose-Adeogun, A.O.; Nakayama, T.; Graham, J.A.; Demur, C.; Hercend, T.; Diu-Hercend, A.; et al. VX-680, a potent and selective small-molecule inhibitor of the Aurora kinases, suppresses tumor growth in vivo. Nat. Med. 2004, 10, 262–267. [Google Scholar] [CrossRef] [PubMed]
  46. Li, T.; Fu, J.; Zeng, Z.; Cohen, D.; Li, J.; Chen, Q.; Li, B.; Liu, X.S. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020, 48, W509–W514. [Google Scholar] [CrossRef] [PubMed]
  47. Zekri, A.; Lesan, V.; Ghaffari, S.H.; Tabrizi, M.H.; Modarressi, M.H. Gene amplification and overexpression of Aurora-C in breast and prostate cancer cell lines. Oncol. Res. 2013, 20, 241–250. [Google Scholar] [CrossRef] [PubMed]
  48. Hsueh, K.; Fu, S.; Huang, C.F.; Lin, C. Aurora-A phosphorylates hnRNPK and disrupts its interaction with p53. FEBS Lett. 2011, 585, 2671–2675. [Google Scholar] [CrossRef] [PubMed]
  49. Gully, C.P.; Velazquez-Torres, G.; Shin, J.H.; Fuentes-Mattei, E.; Wang, E.; Carlock, C.; Chen, J.; Rothenberg, D.; Adams, H.P.; Choi, H.H.; et al. Aurora B kinase phosphorylates and instigates degradation of p53. Proc. Natl. Acad. Sci. USA 2012, 109, 1513–1522. [Google Scholar] [CrossRef] [PubMed]
  50. Yan, M.; Wang, C.; He, B.; Yang, M.; Tong, M.; Long, Z.; Liu, B.; Peng, F.; Xu, L.; Zhang, Y.; et al. Aurora-A Kinase: A Potent Oncogene and Target for Cancer Therapy. Med. Res. Rev. 2016, 36, 1036–1079. [Google Scholar] [CrossRef] [PubMed]
  51. Li, Z.; Sun, Y.; Chen, X.; Squires, J.; Nowroozizadeh, B.; Liang, C.H.J. p53 Mutation Directs AURKA Overexpression via miR-25 and FBXW7 in Prostatic Small Cell Neuroendocrine Carcinoma. Mol. Cancer Res. 2015, 13, 584–591. [Google Scholar] [CrossRef] [PubMed]
  52. Teng, C.L.; Hsieh, Y.C.; Phan, L.; Shin, J.; Gully, C.; Velazquez-Torres, G.; Skerl, S.; Yeung, S.C.J.; Hsu, S.L.; Lee, M.H. FBXW7 is involved in Aurora B degradation. Cell Cycle 2012, 11, 4059–4068. [Google Scholar] [CrossRef] [PubMed]
  53. Lu, L.; Han, H.; Tian, Y.; Li, W.; Zhang, J.; Feng, M.; Li, Y. Aurora kinase A mediates c-Myc’s oncogenic effects in hepatocellular carcinoma. Mol. Carcinog. 2015, 54, 1467–1479. [Google Scholar] [CrossRef] [PubMed]
  54. Den Hollander, J.; Rimpi, S.; Doherty, J.R.; Rudelius, M.; Buck, A.; Hoellein, A.; Kremer, M.; Graf, N.; Scheerer, M.; Hall, M.A.; et al. Aurora kinases A and B are up-regulated by Myc and are essential for maintenance of the malignant state. Blood 2010, 116, 1498–1505. [Google Scholar] [CrossRef]
  55. Brockmann, M.; Poon, E.; Berry, T.; Carstensen, A.; Hedwig, E. Europe PMC Funders Group Small Molecule Inhibitors of Aurora-A Induce Proteasomal Degradation of N-Myc in Childhood Neuroblastoma. Cancer Cell 2013, 24, 75–89. [Google Scholar] [CrossRef]
  56. Ertych, N.; Stolz, A.; Valerius, O.; Braus, G.H.; Bastians, O. CHK2-BRCA1 tumor-suppressor axis restrains oncogenic Aurora-A kinase to ensure proper mitotic microtubule assembly. Proc. Natl. Acad. Sci. USA 2016, 113, 1817–1822. [Google Scholar] [CrossRef]
  57. Aradottir, M.; Reynisdottir, S.T.; Stefansson, O.A.; Jonasson, J.G.; Sverrisdottir, A.; Tryggvadottir, L.; Eyfjord, J.E.; Bodvarsdottir, S.K. Aurora A is a prognostic marker for breast cancer arising in BRCA2 mutation carriers. J. Pathol. Clin. Res. 2015, 1, 33–40. [Google Scholar] [CrossRef]
  58. Bodvarsdottir, S.K.; Hilmarsdottir, H.; Birgisdottir, V.; Steinarsdottir, M.; Jonasson, J.G.; Eyfjord, J.E. Aurora-A amplification associated with BRCA2 mutation in breast tumours. Cancer Lett. 2007, 248, 96–102. [Google Scholar] [CrossRef]
  59. Sur, S.; Agrawal, D.K. Phosphatases and Kinases Regulating CDC25 Activity in the Cell Cycle: Clinical Implications of CDC25 Overexpression and Potential Treatment Strategies. Mol. Cell. Biochem. 2016, 416, 33–46. [Google Scholar] [CrossRef] [PubMed]
  60. Yang, G.; Mercado-Uribe, I.; Multani, A.S.; Sen, S.; Shih, I.M.; Wong, K.K.; Gershenson, D.M.; Liu, J. RAS promotes tumorigenesis through genomic instability induced by imbalanced expression of Aurora-A and BRCA2 in midbody during cytokinesis. Int. J. Cancer 2013, 133, 275–285. [Google Scholar] [CrossRef]
  61. Dar, A.A.; Belkhiri, A.; El-Rifai, W. The aurora kinase A regulates GSK-3β in gastric cancer cells. Oncogene 2009, 28, 866–875. [Google Scholar] [CrossRef] [PubMed]
  62. Yang, J.; Ikezoe, T.; Nishioka, C.; Udaka, K.; Yokoyama, A. Bcr-Abl activates AURKA and AURKB in chronic myeloid leukemia cells via AKT signaling. Int. J. Cancer 2014, 134, 1183–1194. [Google Scholar] [CrossRef] [PubMed]
  63. Zou, Z.; Yuan, Z.; Zhang, Q.; Long, Z.; Chen, J.; Tang, Z.; Zhu, Y.; Chen, S.; Xu, J.; Yan, M.; et al. Aurora kinase A inhibition-induced autophagy triggers drug resistance in breast cancer cells. Autophagy 2012, 8, 1798–1810. [Google Scholar] [CrossRef] [PubMed]
  64. Xu, L.Z.; Long, Z.J.; Peng, F.; Liu, Y.; Xu, J.; Wang, C.; Jiang, L.; Guo, T.; Kamran, M.; Li, S.S.; et al. Aurora kinase A suppresses metabolic stress-induced autophagic cell death by activating mTOR signaling in breast cancer cells. Oncotarget 2014, 5, 7498–7511. [Google Scholar] [CrossRef] [PubMed]
  65. Lee, H.H.; Zhu, Y.; Govindasamy, K.M.; Gopalan, G. Downregulation of Aurora-A overrides estrogen-mediated growth and chemoresistance in breast cancer cells. Endocr. Relat. Cancer 2008, 15, 765–775. [Google Scholar] [CrossRef] [PubMed]
  66. Johnson, E.O.; Chang, K.H.; de Pablo, Y.; Ghosh, S.; Mehta, R.; Badve, S.; Shah, K. PHLDA1 is a crucial negative regulator and effector of Aurora A kinase in breast cancer. J. Cell Sci. 2011, 124, 2711–2722. [Google Scholar] [CrossRef] [PubMed]
  67. Thollet, A.; Vendrell, J.A.; Payen, L.; Ghayad, S.E.; Ben Larbi, S.; Grisard, E.; Collins, C.; Villedieu, M.; Cohen, P.A. ZNF217 confers resistance to the pro-apoptotic signals of paclitaxel and aberrant expression of Aurora-A in breast cancer cells. Mol. Cancer 2010, 9, 291. [Google Scholar] [CrossRef] [PubMed]
  68. Li, Y.; Zhou, W.; Tang, K.; Chen, X.; Feng, Z.; Chen, J. Silencing Aurora A leads to re-sensitization of breast cancer cells to Taxol through downregulation of SRC-mediated ERK and mTOR pathways. Oncol. Rep. 2017, 38, 2011–2022. [Google Scholar] [CrossRef] [PubMed]
  69. Liu, M.; Li, Y.; Zhang, C.; Zhang, Q. Role of aurora kinase B in regulating resistance to paclitaxel in breast cancer cells. Hum. Cell 2022, 35, 678–693. [Google Scholar] [CrossRef] [PubMed]
  70. Gao, J.; Aksoy, B.A.; Dogrusoz, U.; Dresdner, G.; Gross, B.; Sumer, S.O.; Sun, Y.; Jacobsen, A.; Sinha, R.; Larsson, E.; et al. Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal Complementary Data Sources and Analysis Options. Sci. Signal. 2013, 6, 1–20. [Google Scholar] [CrossRef] [PubMed]
  71. Cerami, E.; Gao, J.; Dogrusoz, U.; Gross, B.E.; Sumer, S.O.; Aksoy, B.A.; Jacobsen, A.; Byrne, C.J.; Heuer, M.L.; Larsson, E.; et al. The cBio Cancer Genomics Portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012, 2, 401–404. [Google Scholar] [CrossRef] [PubMed]
  72. de Bruijn, I.; Kundra, R.; Mastrogiacomo, B.; Tran, T.N.; Sikina, L.; Mazor, T.; Li, X.; Ochoa, A.; Zhao, G.; Lai, B.; et al. Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal. Cancer Res. 2023, 83, 3861–3867. [Google Scholar] [CrossRef] [PubMed]
  73. Ning, X.; Zhao, J.; He, F.; Yuan, Y.; Li, B.; Ruan, J. Long non-coding RNA TMPO-AS1 facilitates chemoresistance and invasion in breast cancer by modulating the miR-1179/TRIM37 axis. Oncol. Lett. 2021, 22, 500. [Google Scholar] [CrossRef] [PubMed]
  74. Mitobe, Y.; Ikeda, K.; Suzuki, T.; Takagi, K.; Kawabata, H.; Horie-Inoue, K.; Inoue, S. ESR1 -Stabilizing Long Noncoding RNA TMPO-AS1 Promotes Hormone-Refractory Breast Cancer Progression. Mol. Cell. Biol. 2019, 39, e00261-19. [Google Scholar] [CrossRef] [PubMed]
  75. Brzezinka, K.; Nevedomskaya, E.; Lesche, R.; Steckel, M.; Eheim, A.L.; Haegebarth, A.; Stresemann, C. Functional diversity of inhibitors tackling the differentiation blockage of MLL-rearranged leukemia. J. Hematol. Oncol. 2019, 12, 66. [Google Scholar] [CrossRef] [PubMed]
  76. Mitobe, Y.; Ikeda, K.; Sato, W.; Kodama, Y.; Naito, M.; Gotoh, N.; Miyata, K.; Kataoka, K.; Sasaki, H.; Horie-Inoue, K.; et al. Proliferation-associated long noncoding RNA, TMPO-AS1, is a potential therapeutic target for triple-negative breast cancer. Cancer Sci. 2020, 111, 2440–2450. [Google Scholar] [CrossRef] [PubMed]
  77. Moradi, M.T.; Hatami, R.; Rahimi, Z. Circulating CYTOR as a potential biomarker in breast cancer. Int. J. Mol. Cell. Med. 2020, 9, 83–89. [Google Scholar] [CrossRef] [PubMed]
  78. Liu, Y.; Li, M.; Yu, H.; Piao, H. LncRNA CYTOR promotes tamoxifen resistance in breast cancer cells via sponging miR-125a-5p. Int. J. Mol. Med. 2020, 45, 497–509. [Google Scholar] [CrossRef]
  79. Liu, S.; Chen, W.; Hu, H.; Zhang, T.; Wu, T.; Li, X.; Li, Y.; Kong, Q.; Lu, H.; Lu, Z. Long noncoding RNA PVT1 promotes breast cancer proliferation and metastasis by binding miR-128-3p and UPF1. Breast Cancer Res. 2021, 23, 115. [Google Scholar] [CrossRef] [PubMed]
  80. Tang, J.; Li, Y.; Sang, Y.; Yu, B.; Lv, D.; Zhang, W.; Feng, H. LncRNA PVT1 regulates triple-negative breast cancer through KLF5/beta-catenin signaling. Oncogene 2018, 37, 4723–4734. [Google Scholar] [CrossRef] [PubMed]
  81. Tseng, Y.Y.; Moriarity, B.S.; Gong, W.; Akiyama, R.; Tiwari, A.; Kawakami, H.; Ronning, P.; Reuland, B.; Guenther, K.; Beadnell, T.C.; et al. PVT1 dependence in cancer with MYC copy-number increase. Nature 2014, 512, 82–86. [Google Scholar] [CrossRef] [PubMed]
  82. Li, J.; Gao, C.; Liu, C.; Zhou, C.; Ma, X.; Li, H.; Li, J.; Wang, X.; Qi, L.; Yao, Y.; et al. Four lncRNAs associated with breast cancer prognosis identified by coexpression network analysis. J. Cell. Physiol. 2019, 234, 14019–14030. [Google Scholar] [CrossRef] [PubMed]
  83. Wang, L.; Luan, T.; Zhou, S.; Lin, J.; Yang, Y.; Liu, W.; Tong, X.; Jiang, W. LncRNA HCP5 promotes triple negative breast cancer progression as a ceRNA to regulate BIRC3 by sponging miR-219a-5p. Cancer Med. 2019, 8, 4389–4403. [Google Scholar] [CrossRef] [PubMed]
  84. Zhang, K.J.; Tan, X.L.; Guo, L. The long non-coding RNA DANCR regulates the inflammatory phenotype of breast cancer cells and promotes breast cancer progression via EZH2-dependent suppression of SOCS3 transcription. Mol. Oncol. 2020, 14, 309–328. [Google Scholar] [CrossRef] [PubMed]
  85. Tang, J.; Zhong, G.; Zhang, H.; Yu, B.; Wei, F.; Luo, L.; Kang, Y.; Wu, J.; Jiang, J.; Li, Y.; et al. LncRNA DANCR upregulates PI3K/AKT signaling through activating serine phosphorylation of RXRA. Cell Death Dis. 2018, 9, 1167. [Google Scholar] [CrossRef] [PubMed]
Futurepharmacol 04 00026 g002
Figure 2. Correlation analysis between the expression levels of long noncoding RNAs (lncRNAs) (such as TMPO-AS1, CYTOR, PVT1, HCP5, and DANCR) and Aurora kinases (AURKA, AURKB, and AURKC) in invasive breast carcinoma (TCGA, PanCancer Atlas, 994 samples/patients) dataset deposited in cBioPortal database [70,71,72]. (A–C) Correlation analysis between thymopoietin antisense transcript 1 (TMPO-AS1) and Aurora kinases (AURKA, AURKB, and AURKC). (D–F) Correlation analysis between cytoskeleton regulator long noncoding RNA (CYTOR) and Aurora kinases (AURKA, AURKB, and AURKC). (G–I) Correlation analysis between plasmacytoma variant translocation 1 (PVT1) and Aurora kinases (AURKA, AURKB, and AURKC). (J–L) Correlation analysis between HLA complex P5 (HCP5) and Aurora kinases (AURKA, AURKB, and AURKC). (M–O) Correlation analysis between differentiation antagonizing non-protein coding RNA (DANCR) and Aurora kinases (AURKA, AURKB, and AURKC).
Figure 2. Correlation analysis between the expression levels of long noncoding RNAs (lncRNAs) (such as TMPO-AS1, CYTOR, PVT1, HCP5, and DANCR) and Aurora kinases (AURKA, AURKB, and AURKC) in invasive breast carcinoma (TCGA, PanCancer Atlas, 994 samples/patients) dataset deposited in cBioPortal database [70,71,72]. (A–C) Correlation analysis between thymopoietin antisense transcript 1 (TMPO-AS1) and Aurora kinases (AURKA, AURKB, and AURKC). (D–F) Correlation analysis between cytoskeleton regulator long noncoding RNA (CYTOR) and Aurora kinases (AURKA, AURKB, and AURKC). (G–I) Correlation analysis between plasmacytoma variant translocation 1 (PVT1) and Aurora kinases (AURKA, AURKB, and AURKC). (J–L) Correlation analysis between HLA complex P5 (HCP5) and Aurora kinases (AURKA, AURKB, and AURKC). (M–O) Correlation analysis between differentiation antagonizing non-protein coding RNA (DANCR) and Aurora kinases (AURKA, AURKB, and AURKC).
Futurepharmacol 04 00026 g002
Table 1. List of selected examples of Aurora kinase inhibitors.
Table 1. List of selected examples of Aurora kinase inhibitors.
NameSelectivityRef.
Barasertib (AZD1152)Selective AURKB inhibitor[14,15]
HesperadinSelective AURKB inhibitor[15]
Alisertib (MLN8237)AURKA inhibitor[16]
Danusertib (PHA-739358)Pan-Aurora kinase inhibitor[15]
AT9283Pan-Aurora kinase inhibitor[15]
AMG 900Pan-Aurora kinase inhibitor[15]
VX-680Pan-Aurora kinase inhibitor[15]
Table 2. Analysis of statistically significant tendency towards mutual exclusivity or co-occurrence of genomic alterations in lncRNA (TMPO-AS1, CYTOR, PVT1, HCP5, and DANCR) and Aurora kinases (AURKA, AURKB and AURKC) in invasive breast carcinoma (TCGA, PanCancer Atlas, 994 samples/patients, dataset deposited in cBioPortal database).
Table 2. Analysis of statistically significant tendency towards mutual exclusivity or co-occurrence of genomic alterations in lncRNA (TMPO-AS1, CYTOR, PVT1, HCP5, and DANCR) and Aurora kinases (AURKA, AURKB and AURKC) in invasive breast carcinoma (TCGA, PanCancer Atlas, 994 samples/patients, dataset deposited in cBioPortal database).
Gene AGene BNeitherA Not BB Not ABothLog2 Odds Ratioq-ValueTendency
AURKAAURKB7651373755>3<0.001Co-occurrence
PVT1AURKA599203102901.381<0.001Co-occurrence
TMPO-AS1AURKA76537161311.993<0.001Co-occurrence
TMPO-AS1AURKB8505276161.7830.002Co-occurrence
PVT1AURKB65225049431.1940.002Co-occurrence
DANCRAURKB8643880121.7700.005Co-occurrence
TMPO-AS1DANCR8865840101.9330.005Co-occurrence
DANCRPVT167625268251.3350.007Co-occurrence
HCP5AURKA74755166261.0890.014Co-occurrence
DANCRAURKA77032174181.3160.014Co-occurrencee
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Saadeldin, M.K.; Curigliano, G.; Abdel-Aziz, A.K. Deciphering the Complex Interplay of Long Noncoding RNAs and Aurora Kinases: Novel Insights into Breast Cancer Development and Therapeutic Strategies. Future Pharmacol. 2024, 4, 466-478. https://doi.org/10.3390/futurepharmacol4030026

AMA Style

Saadeldin MK, Curigliano G, Abdel-Aziz AK. Deciphering the Complex Interplay of Long Noncoding RNAs and Aurora Kinases: Novel Insights into Breast Cancer Development and Therapeutic Strategies. Future Pharmacology. 2024; 4(3):466-478. https://doi.org/10.3390/futurepharmacol4030026

Chicago/Turabian Style

Saadeldin, Mona Kamal, Giuseppe Curigliano, and Amal Kamal Abdel-Aziz. 2024. "Deciphering the Complex Interplay of Long Noncoding RNAs and Aurora Kinases: Novel Insights into Breast Cancer Development and Therapeutic Strategies" Future Pharmacology 4, no. 3: 466-478. https://doi.org/10.3390/futurepharmacol4030026

APA Style

Saadeldin, M. K., Curigliano, G., & Abdel-Aziz, A. K. (2024). Deciphering the Complex Interplay of Long Noncoding RNAs and Aurora Kinases: Novel Insights into Breast Cancer Development and Therapeutic Strategies. Future Pharmacology, 4(3), 466-478. https://doi.org/10.3390/futurepharmacol4030026

Article Metrics

Back to TopTop