Jul 2026· Journal of Visualized Experiments· Vol 233· 0 citations
Medicine
TL;DR
Collectively, m6A-related genes are dysregulated in breast cancer and correlate with patient outcomes, highlighting their biomarker potential, with YTHDF3 warranting in-depth investigation.
Abstract
The expression landscape and prognostic value of N6-methyladenosine (m6A)-related genes remain largely uncharacterized in breast cancer. Here, we performed an integrative analysis of their expression profiles and clinical relevance. Utilizing multi-omics datasets and experimental validation, we conducted a systematic investigation of m6A-related genes in breast cancer. These genes exhibited pronounced differential expression in breast cancer, yet their correlation with molecular features such as promoter methylation and copy number alterations was limited. Univariate survival analysis indicated that aberrant expression of RBM15B, METTL16, HNRNPC, YTHDF1, YTHDF3, and IGF2BP1 was significantly linked to patient prognosis. Multivariate Cox regression further identified elevated YTHDF3 expression as an independent prognostic factor. Functional network analysis indicated YTHDF3 is potentially involved not only in RNA processing and metabolism but also in DNA repair, pri-miRNA processing, telomere stability, and immune infiltration. Moreover, upregulation of YTHDF3 mRNA was confirmed in clinical breast cancer specimens. Collectively, m6A-related genes are dysregulated in breast cancer and correlate with patient outcomes, highlighting their biomarker potential, with YTHDF3 warranting in-depth investigation.
This study integrates multi-omics datasets to identify candidate biomarkers that may influence TNBC progression and modulate therapeutic response and nominate CCND2 and KIF1A as candidate biomarkers and potential therapeutic targets in TNBC.
Roberto Aguilar, Victor Wang, Shane Deng· Journal of Immunology· 0 citations
Introduction: Aberrant m6A regulators contribute to esophageal cancer, yet few studies stratify by subtype and compare prognostic models. Objectives: N6-methyladenosine (m6A) modification broadly regulates cancer progression and prognosis, while its clinical role in esophageal cancer (EC) remains poorly defined. Methods: Based on The Cancer Genome Atlas data, we analyzed 13 m6A regulators in EC and normal tissues, and constructed a prognostic signature using Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Model performance was validated using C-index and time-dependent receiver operating characteristic curves and compared with tumor–node–metastasis (TNM) staging and existing models. Results: Eight m6A regulators (METTL3, KIAA1429, YTHDC1, HNRNPC, WTAP, RBM15, YTHDF1, YTHDF2) were significantly upregulated in EC tumors, with YTHDC1 showing the strongest correlation with METTL14 (r = 0.55). A four-gene m6A-regulator expression signature was identified using LASSO Cox regression. Both univariate and multivariate Cox analyses revealed that the risk score and TNM stage were independent risk factors. High-risk patients had worse overall survival (OS) across all stages and subtypes. Low-risk stage I–II patients had better OS. Combining the risk score with TNM stage improved prognostic accuracy over TNM stage alone, though differences with the risk score model were not significant. Our risk model was particularly effective at predicting 1-year OS, whereas TNM staging and other signatures were better at predicting 3- and 5-year survival. Conclusion: We explored the role of m6A in EC and created a four-gene m6A-regulator expression signature risk model that serves as an independent prognostic biomarker, complementing TNM staging to aid in personalized postoperative care for EC patients.
Xinhua Xu, Changchun Lai, Hao Chen et al.· Eurasian Journal of Medicine...· 0 citations
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CCHC zinc finger protein 10 (ZCCHC10) has been implicated in the progression of multiple malignancies, but its prognostic value and role in immune infiltration in breast cancer remain unclear. In this study, we systematically analyzed ZCCHC10 expression using public databases and validated the findings by immunohistochemistry. Associations with clinicopathological features and patient prognosis were assessed, and a prognostic nomogram was constructed. Co-expression networks and gene set enrichment analysis were used to explore functional pathways, while immune infiltration was evaluated and potential therapeutic agents were predicted. Functional assays, including proliferation and colony formation experiments, were performed to examine the biological role of ZCCHC10 in vitro. Our results demonstrated that ZCCHC10 was significantly upregulated in breast cancer and associated with poor prognosis and adverse clinicopathological characteristics. Enrichment analysis indicated involvement in immune-related pathways, and its expression correlated with immune cell infiltration and immunomodulators. Drug sensitivity prediction suggested Ipatasertib as a candidate targeted therapy requiring experimental verification. Knockdown of ZCCHC10 markedly inhibited breast cancer cell proliferation. Collectively, these findings suggest that ZCCHC10 serves as a prognostic biomarker and a key regulator of immune infiltration in breast cancer.
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Kangyue Sun, Peiyi He, Lu Chen et al.· Functional & Integrative Gen...· 0 citations
MZT1 is a proliferation-associated marker that integrates clinical risk, transcriptional programs, cellular heterogeneity, and predictive modeling in LUAD, providing a potential framework for biomarker development and risk stratification.
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