Protein arginine methyltransferase (PRMT) plays essential roles in tumor initiation and progression, but its underlying mechanisms in the treatment sensitivity of endometrial cancer (EC) remain unclear and warrant further investigation. Here, a comprehensive analysis of the Cancer Genome Atlas database and Clinical Proteomic Tumor Analysis Consortium database identifies that PRMT3 plays an important role in EC. Specifically, further experiments show that PRMT3 inhibition enhances the susceptibility of EC cells to ferroptosis. Mechanistically, PRMT3 interacts with Methyltransferase 14 (METTL14) and is involved in its arginine methylation. In addition, PRMT3 inhibition‐mediated METTL14 overexpression promotes methylation modification via an m⁶A‐YTHDF2‐dependent mechanism, reducing Glutathione peroxidase 4 (GPX4) mRNA stability, increasing lipid peroxidation levels, and accelerating ferroptosis. Notably, combined PRMT3 blockade and anti‐PD‐1 therapy display more potent antitumor effects by accelerating ferroptosis in cell‐derived xenograft models. The specific PRMT3 inhibitor SGC707 exerts the same immunotherapeutic sensitizing effect in a patient‐derived xenograft model. Notably, blocking PRMT3 improves tumor suppression in response to cisplatin and radiation therapy. Altogether, this work demonstrates that PRMT3 depletion is a promising target for EC.

CAFs are divided into three main subtypes: myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), and antigen-presenting CAFs (apCAFs). CAFs influence treatment outcomes via seven primary mechanisms: physical barrier formation, metabolic reprogramming, exosome secretion, DNA repair enhancement, bypass signaling activation, activation of multidrug resistance proteins and immune checkpoint inhibition. These mechanisms result in resistance to chemotherapy, radiotherapy, and immune escape, underscoring the critical role of CAFs in the TME and their impact on treatment efficacy.

Bladder cancer (BC) is a highly prevalent cancer form of the genitourinary system; however, the effective biomarkers are still ambiguous and deserve deeper investigation. Long non-coding RNA (lncRNA) occupies a prominent position in tumor biology and immunology, and ferroptosis-related genes participate in regulatory processes of cancer. In this study, 538 differentially expressed ferroptosis-related lncRNAs were identified from the The Cancer Genome Atlas database through co-expression method and differential expression analysis. Then, the samples involved were equally and randomly divided into two cohorts for the construction of gene model and accuracy verification. Subsequently, a prediction model containing five ferroptosis-related lncRNAs was constructed by LASSO and Cox regression analysis. Furthermore, in terms of predictive performance, consistent results were achieved in the training set, testing set, and entire set. Kaplan–Meier curve, receiver operating characteristic area under the curve, and principal component analysis results verified the good predictive ability of model, and the gene model was confirmed as an independent prognostic indicator. To further investigate the mechanism, we explored the upstream of five lncRNAs and found that they may be modified by m6A to increase or decrease their expression in BC. Importantly, the low-risk group displayed higher mutation burden of tumors and lower Tumor Immune Dysfunction and Exclusion score, which may be predicted to have a higher response rate to immunotherapy. Interestingly, the patients in the high-risk group appeared to have a higher sensitivity to traditional chemotherapeutic agents through pRRophetic analysis. In general, our research established a five-ferroptosis-related lncRNA signature, which can be served as a promising prognostic biomarker for BC.

The identification of tumor-derived neoantigens that elicit an immune response has led to significant advancements in cancer immunotherapy. We comprehensively investigated the neoantigen atlas in Chinese glioma patients via the integration of whole-exome sequencing, transcriptome, and ribosome profiling. We further proposed MINER (Multi-omics Integration for NEoantigen Recognition) to prioritize neoantigens that integrate HLA-I binding and the TCR response to increase accuracy. In particular, we emphasized the importance of non-canonical open reading frames in neoantigen generation and demonstrated that both gene fusions and somatic mutations contribute to the production of neoantigens complementally. We identified a novel subtype (neo_W) of IDH-wildtype glioma, which was characterized by a higher neoantigen burden and correlated with better survival outcomes. Finally, we experimentally validated therapeutic combinations of immune checkpoint inhibitors that target the RAS-RAF-MEK-ERK signaling pathway for treatment of neo_W glioma patients. Multi-omics-guided characterization of neoantigens provides valuable knowledge for precision therapy of glioma.

Numerous risk factors for oesophageal cancer are linked to lifestyle habits, but the role of early-life factors in its incidence and mortality is unclear. Using UK Biobank data, we explore the association among breastfeeding, maternal smoking, smoking in offspring, and oesophageal cancer risk in adult offspring via multivariable Cox regression. Here, we show that being breastfed, compared with not being breastfed, is associated with a lower risk of oesophageal cancer incidence (HR: 0.83, 95% CI: 0.70–0.98) and mortality (HR: 0.74, 95% CI: 0.61–0.89) in adult offspring. Additionally, it is associated with a reduced impact of smoking in offspring on oesophageal cancer incidence (HR: 0.79, 95% CI: 0.64-0.96) and mortality (HR: 0.73, 95% CI: 0.59-0.91). We subsequently construct a polygenic risk score for oesophageal cancer to explore the influence of genetic factors. Our findings emphasize the importance of breastfeeding, and smoking cessation to prevent oesophageal cancer.