An up-date on epigenetic and molecular markers in testicular germ cell tumors

Chieffi, Paolo

doi:10.5582/irdr.2017.01070

Cited by 10 publications

(9 citation statements)

References 32 publications

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“…2. A common TRF was NANOG-miR-373-3p-FRMD4A, in which NANOG was also a biomarker (and a TF) in TGCT 56 ; hence this FFL might have crucial roles in TGCT tumorigenesis. There were 8 common TAFs that included 4 TFs (ERG, JUN, SOX9, and NR2F2), 4 miRNAs (miR-302a-3p, miR-302d-3p, miR-367-3p, and miR-373-3p) and 5 target www.nature.com/scientificreports www.nature.com/scientificreports/ genes (CTTNBP2, PALLD, RND3, TIMP3, and TNS1).…”

Section: Common and Subtype-specific Regulatory Network Topologicalmentioning

confidence: 99%

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MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors

Qin

Mallik

Mitra

et al. 2020

Sci Rep

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Recent studies have revealed that feed-forward loops (FFLs) as regulatory motifs have synergistic roles in cellular systems and their disruption may cause diseases including cancer. FFLs may include two regulators such as transcription factors (TFs) and microRNAs (miRNAs). In this study, we extensively investigated TF and miRNA regulation pairs, their FFLs, and TF-miRNA mediated regulatory networks in two major types of testicular germ cell tumors (TGCT): seminoma (SE) and non-seminoma (NSE). Specifically, we identified differentially expressed mRNA genes and miRNAs in 103 tumors using the transcriptomic data from The Cancer Genome Atlas. Next, we determined significantly correlated TFgene/miRNA and miRNA-gene/TF pairs with regulation direction. Subsequently, we determined 288 and 664 dysregulated TF-miRNA-gene FFLs in SE and NSE, respectively. By constructing dysregulated FFL networks, we found that many hub nodes (12 out of 30 for SE and 8 out of 32 for NSE) in the top ranked FFLs could predict subtype-classification (Random Forest classifier, average accuracy ≥90%). These hub molecules were validated by an independent dataset. Our network analysis pinpointed several SE-specific dysregulated miRNAs (miR-200c-3p, miR-25-3p, and miR-302a-3p) and genes (EPHA2, JUN, KLF4, PLXDC2, RND3, SPI1, and TIMP3) and NSE-specific dysregulated miRNAs (miR-367-3p, miR-519d-3p, and miR-96-5p) and genes (NR2F1 and NR2F2). This study is the first systematic investigation of TF and miRNA regulation and their co-regulation in two major TGCT subtypes. Testicular germ cell tumors (TGCT) occur most frequently in men between ages of 20 and 40 1,2. Accordingly to histology, TGCT can be separated into two major types: seminoma (SE) and non-seminoma (NSE) 1-4 , and NSE has several subtypes. While the etiology of the two TGCT subtypes is well studied, their molecular profiles, signature genetic markers, and regulatory mechanisms have not been systematically investigated, unlike other common cancers. Such an investigation is much needed now to identify molecular signatures either common in two subtypes, or unique in subtype. The molecular signatures may be further useful for clinical implications, such as patient stratification and subtype-based or personalized treatment. Currently, there are several challenges in TGCT treatment. First, TGCT patients have a high risk of relapse with poor prognosis. Second, there are severe side effects for current chemotherapy and radiotherapy that lead to development of other pathologies. Third, since most of the patients are adolescent or young men, there is a heavy burden for the patients and families in the long run 2,3. During the last decade, a number of studies have been conducted to explore insights into the genetic, epigenetic, and molecular mechanisms of TGCT. For example, after collecting TGCT related genes from previous

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Section: Common and Subtype-specific Regulatory Network Topologicalmentioning

confidence: 99%

“…The expression of Yamanaka factors have previously been detected in testicular cancer 61 . In addition, two TF-coding genes (POU5F1 and SOX2) are candidate biomarkers in TGCT 56 . Their roles have been reported in testicular cancer 7,8 .…”

Section: Common and Subtype-specific Regulatory Network Topologicalmentioning

confidence: 99%

MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors

Qin

Mallik

Mitra

et al. 2020

Sci Rep

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“…In premordial germ cells, the genome is typically highly methylated, but when developing TGCT, the genomewide methylation becomes abolished, leading to epigenetic re-programming and initiation of tumorigenesis [68]. The epigenetic profile of TGCTs is characterized by genome-wide demethylation [69]. However, seminomas and non-seminomas exert significantly different promoter methylation profiles, as well as different genetic alterations, environmental component and the familial risk, reflecting specific clinical features including CDDP resistance in TGCT patients [70][71][72].…”

Section: Dna Methylationmentioning

confidence: 99%

Understanding the crosstalk of molecular factors and signaling pathways reveals novel biomarkers of cisplatin resistance in testicular germ cell tumors

Roška

Jurkovičová

2020

neo

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Testicular germ cell tumors (TGCTs) mostly affect young men, but fortunately belong to well curable solid tumors. Today, different treatment strategies are applied reaching excellent outcomes, and introduction of alternative approach of patient active surveillance or adjuvant chemotherapy after orchiectomy decreases number of unnecessary toxic treatments of young patients. Also for relapsing patients, salvage therapy offers high survival rates. However, small percentages of affected young men do not respond to conventional therapy regimen due to intrinsic or acquired therapy resistance. For closely watching of patients during active surveillance, patients' stratification due to their prognosis, detection of therapy resistance and early relapse before treatment initiation, reliable molecular biomarkers and diagnostic tools replacing conventional approaches are still needed. Complex understanding of disease development and progression as well as mechanisms of chemoresistance and their epigenetic or chronobiological regulation prerequisite successful search for such novel biomarkers. In this review, we aimed to highlight the importance of crosstalk of different regulatory mechanisms and their key players affecting treatment response, and focus on their potential as novel molecular biomarkers and/or druggable targets.

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“…However, antimitotic drugs frequently show the appearance of drug resistance, adverse side effects (neurotoxicity) and their clinical effects are not predictable. Aurora inhibitors lack neurotoxicity and could contribute to the treatment of human neoplasia (31)(32)(33)(34).…”

Section: Aurora B and Cancermentioning

confidence: 99%

“…These three drugs have similar potency versus Aurora A, and Aurora B. Each induces a similar phenotype in cell-based assays, characterized by inhibition of phosphorylation of histone H3 on Ser 10 and Ser 28 , inhibition of cytokinesis, and development of polyploidy (28)(29)(30)(31)(32)(33)(34).…”

Section: Aurora B As Therapeutic Targetmentioning

confidence: 99%