Discover. Oncology最新文献

Permanent hair dyes have been linked to an increased risk of breast cancer (BC), though the underlying mechanisms remain unclear. To address this knowledge gap, our investigation employed an integrated approach combining network toxicology, molecular docking, molecular dynamics simulations, and machine learning to decipher the molecular mechanisms by which permanent hair dyes might promote BC pathogenesis. Five permanent hair dye ingredients classified by IARC as carcinogenic were included in this study: p-phenylenediamine, resorcinol, pyridine, Disperse Yellow 3, and HC Blue No. 2. These chemicals can regulate BC progression through various signaling pathways, with key core targets identified as HSP90AA1, HSP90AB1, ESR1, CDK1, STAT3, MAPK8, HDAC1, and SRC. A machine learning model comprising 128 algorithms confirmed that these eight targets possess strong prognostic predictive capabilities for BC. Subsequent SHAP analysis revealed SRC, HSP90AB1, HSP90AA1 and CDK1 as the key contributors to prognostic prediction, with each being highly expressed in BC and linked to poor clinical prognosis. Notably, among all chemicals screened, Disperse Yellow 3 exhibited the strongest binding affinity to these four key targets, demonstrating the strongest association with BC risk.

Purpose: The heterogeneous nuclear ribonucleoprotein (HNRNP) family plays pivotal roles in multiple aspects of RNA metabolism. Recent studies suggest that HNRNP dysregulation can promote tumor development. Therefore, this study aims to systematically characterize the expression profiles, immunological associations, and prognostic significance of HNRNP family members in LUAD.

Methods: Comprehensive transcriptomic and proteomic analyses were conducted using TCGA, GTEx, GEO, and CPTAC LUAD cohorts. Differential expression, immune infiltration, and survival analyses were performed using bioinformatics approaches including ssGSEA, TIDE, and Cox regression modeling. Functional enrichment and alternative splicing profiling were further applied to explore potential mechanisms, with a focus on HNRNPC.

Results: Multiple HNRNP genes were significantly overexpressed in LUAD tissues across datasets. Their expression levels positively correlated with tumor stage, metastasis, recurrence, and TP53 mutation status. High expression of several HNRNPs was associated with poor overall survival, with HNRNPC identified as an independent prognostic indicator in both TCGA and GEO cohorts. Elevated HNRNP expression was linked to reduced immune cell infiltration and lower stromal, immune, and ESTIMATE scores, alongside increased TIDE and Exclusion scores, suggesting immunosuppressive roles in the tumor microenvironment. Functionally, HNRNPC was associated with the activation of cell cycle progression and DNA damage repair. Alternative splicing analysis revealed that HNRNPC predominantly regulates exon skipping events, with enriched downstream pathways involved in chromatin remodeling and transcriptional regulation.

Conclusion: This study highlights the critical roles of HNRNP family members in LUAD, identifying HNRNPC as a key prognostic biomarker and potential intervention candidate to improve patient outcomes.

Background: Clear cell renal cell carcinoma (ccRCC) exhibits strong heterogeneity and variable therapeutic responses. PANoptosis, an integrated form of inflammatory programmed cell death, may influence tumor immunity and prognosis, yet its role in ccRCC remains unclear.

Methods: Multi-omics data from TCGA database were analyzed to characterize PANoptosis-related genes (PRG), define molecular and gene subtypes, and construct a prognostic PRG score using Cox and LASSO regression. Immune infiltration, drug sensitivity, and predicted immunotherapy response were evaluated. Single-cell RNA sequencing analysis was used to map PRG expression across cell populations. In vitro experiments were performed to validate RBCK1 function in ccRCC.

Results: 14 PRG showed marked CNV alterations and differential expression. Three PRG molecular subtypes displayed distinct survival outcomes and immune landscapes. A three-gene PRG score (RIPK1, PYCARD, RBCK1) independently stratified prognosis and correlated with immune infiltration, mutation burden, and therapy sensitivity. Lower scores predicted better immunotherapy response and higher drug sensitivity. Single-cell analysis revealed broad PRG expression across macrophages, epithelial cells, endothelial cells, and stem-like cells. RBCK1 was significantly upregulated in ccRCC and promoted proliferation and migration, while its knockdown inhibited tumor cell growth.

Conclusions: We delineated the PANoptosis landscape in ccRCC and developed a robust PRG score with strong prognostic and immunological relevance. RBCK1 functions as a key oncogenic regulator and potential therapeutic target. These findings offer a valuable framework for precision risk assessment and treatment optimization in ccRCC.