In Silico Pharmacol. 2025 Oct 17;13(3):154. doi: 10.1007/s40203-025-00440-3. eCollection 2025.

ABSTRACT

Breast, ovarian, lung, cervical, and colorectal cancers are among the most prevalent malignancies affecting women worldwide. This study aimed to elucidate the common molecular mechanisms of tumorigenesis and identify potential biomarkers using an integrative bioinformatics and network-based approach. Integrative profiling of five microarray datasets identified 66 differentially expressed genes (DEGs) that are common across five cancer types. Gene ontology and KEGG pathway analyses of common DEGs were performed using the DAVID database. The cell cycle processes were the most enriched functions, and oocyte meiosis, oocyte maturation, the p53 signaling pathway, cancer pathways, and cellular senescence were the most important pathways identified. Protein-protein interaction (PPI) networks for the DEGs were constructed using the STRING database, and the resulting networks were visualized in Cytoscape. Through PPI network analysis, ten hub genes were identified, and subsequent survival analysis confirmed that CHEK1, DLGAP5, CCNB2, and CCNA2 are significantly associated with poor patient survivability, establishing them as common biomarkers across multiple cancer types. Subsequently, ten transcription factors (TFs) and ten post-transcriptional regulators were identified through the assessment of regulatory networks involving TFs-DEGs and miRNAs-DEGs. Finally, drug-gene association analysis from the GSCA library was used to anticipate drug-like compounds using the drug repurposing approach. Overall, this comprehensive investigation holds promise for future in vitro and in vivo studies, offering a molecular foundation for the diagnosis, prognosis, and treatment of malignant cancers.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-025-00440-3.

PMID:41113171 | PMC:PMC12534660 | DOI:10.1007/s40203-025-00440-3

Oral Oncol. 2025 Nov;170:107760. doi: 10.1016/j.oraloncology.2025.107760. Epub 2025 Oct 17.

ABSTRACT

Non-viral head and neck squamous cell carcinoma (HNSCC) has poor survival and high recurrence rates. Circulating tumor DNA (ctDNA) is a promising biomarker for understanding tumor biology, assessing treatment response, and monitoring disease progression. While extensively studied in virally mediated HNSCC, its role in non-viral HNSCC remains underexplored. This systematic review and meta-analysis consolidates evidence on the diagnostic, prognostic, and therapeutic value of ctDNA in non-viral HNSCC. A systematic search across Medline, PubMed, Embase, and the Cochrane Library identified 1,915 records, of which 47 were included. Data extraction followed PRISMA guidelines, with overall survival (OS), progression-free survival (PFS), and recurrence-free survival (RFS), pooled as hazard ratios (HRs) with 95% confidence intervals (CIs) using a fixed-effect model. Among 3,574 patients, the most common tumor sites were the oral cavity (35 %) and oropharynx (22 %), with the majority presenting with stage IVA/IVB disease (29 %). Pre-treatment ctDNA detection rates ranged from 50 % to 100 % (median: 83 %), while post-treatment detection rates varied between 28 % and 100 % (median: 48 %). ctDNA detected recurrence in 80 % of patients, with a median lead time of 4.6 months. ctDNA detection was significantly associated with worse OS (HR 10.26, 95 % CI 3.58-29.40; P < 0.0001). Residual ctDNA was strongly correlated with worse PFS (HR 7.32, 95 % CI 4.17-12.86; P < 0.00001) and RFS (HR 7.33, 95 % CI 2.75-19.58; P < 0.0001). ctDNA holds potential for improving diagnostic accuracy, monitoring progression, and predicting survival outcomes in non-viral HNSCC. However, further large-scale studies and standardized guidelines are needed for validation and clinical implementation.

PMID:41108912 | DOI:10.1016/j.oraloncology.2025.107760

Nucleic Acids Res. 2025 Oct 14;53(19):gkaf990. doi: 10.1093/nar/gkaf990.

ABSTRACT

BRCA2 mutations contribute to the pathogenesis and treatment sensitivity of a subset of ovarian, breast, prostate, and pancreatic cancers. When these cancers become therapy resistant, secondary mutations that restore the BRCA2 open reading frame are found in half the cases, but other causes of resistance remain incompletely understood. Here, we identified translational readthrough of a premature termination codon (PTC) as a cause of resistance to poly(ADP-ribose) polymerase inhibitors (PARPis) and cisplatin in cells derived from the BRCA2-mutated ovarian cancer line PEO1 by PARPi selection. Despite persistence of the signature 4965C > G (p.Y1655X) BRCA2 mutation, low-level expression of full-length BRCA2 protein was detectable in these cells by immunoblotting and tandem mass spectrometry. Either BRCA2 knockdown or gene interruption 5' or 3' to the PTC restored treatment sensitivity, implicating BRCA2 in the resistance. Reporter assays demonstrated UAG-selective readthrough in the resistant clones but not parental cells. Moreover, custom searching of global proteomic data indicated readthrough of stop codons, particularly UAGs, in additional proteins in the resistant clones. Finally, multi-omic analysis identified multiple changes in the nonsense-mediated decay and termination machineries that favor readthrough. Accordingly, the present results identify PTC readthrough as a potential mechanism of drug resistance in cells with BRCA2 nonsense mutations.

PMID:41099700 | PMC:PMC12526053 | DOI:10.1093/nar/gkaf990

Cancer Lett. 2025 Oct 11;634:218076. doi: 10.1016/j.canlet.2025.218076. Online ahead of print.

ABSTRACT

The tumor microenvironment (TME) and tumor macroenvironment (TMaE) jointly shape cancer biology by linking local cellular niches with systemic host physiology. The TME provides the immediate soil for tumor initiation, progression, and therapy resistance, whereas the TMaE integrates metabolic, immune, neuroendocrine, microbial, and inflammatory signals that remodel local ecosystems. Recent advances highlight how systemic factors, including aging, energy imbalance, chronic inflammation, cachexia, and psychosocial stress, interact with extracellular matrix remodeling, vascular dynamics, and immune surveillance to influence tumor dormancy, metastatic reactivation, and therapeutic outcomes. However, the conceptual boundaries between TME and TMaE remain unclear, mechanistic insights are limited, and current models insufficiently capture local-systemic crosstalk. Future strategies integrating multi-omics, advanced imaging, and humanized models are essential to map this multidimensional interplay. A deeper understanding of TME-TMaE will be critical to refine precision oncology, advance preventive strategies, and design combinatorial therapies targeting both local and systemic cancer ecosystems. This review highlights the roles of the TME and TMaE in tumor initiation, progression, and heterogeneity, their interactions, and the clinical implications for classification, therapy, and prognosis.

PMID:41083101 | DOI:10.1016/j.canlet.2025.218076

Nat Commun. 2025 Oct 7;16(1):8892. doi: 10.1038/s41467-025-63921-1.

ABSTRACT

Though open chromatin may promote active transcription, gene expression responses may not be directly coordinated with changes in chromatin accessibility. Most existing methods for single-cell multi-omics data focus only on learning stationary, shared information among these modalities, overlooking modality-specific information delineating cellular states and dynamics resulting from causal relations among modalities. To address this, the epigenome-transcriptome relationship can be characterized in relation to time as coupled (changing dependently) or decoupled (changing independently). We propose the framework HALO, adopting a causal approach to model these temporal causal relations on two levels. On the representation level, HALO factorizes these two modalities into both coupled and decoupled latent representations, revealing their dynamic interplay. On the individual gene level, HALO matches gene-peak pairs and characterizes their changes over time. HALO discovers analogous biological functions between modalities, distinguishes epigenetic factors for lineage specification, and identifies temporal cis-regulation interactions relevant to cellular differentiation and human diseases.

PMID:41057364 | PMC:PMC12504611 | DOI:10.1038/s41467-025-63921-1