Prognostic analysis of patients with breast cancer based on tumor mutational burden and DNA damage repair genes

Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature

We employed single-cell analysis techniques, specifically the inferCNV method, to dissect the complex progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) through minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC). This approach enabled the identification of Cluster 6, which was significantly associated with LUAD progression. Our comprehensive analysis included intercellular interaction, transcription factor regulatory networks, trajectory analysis, and gene set variation analysis (GSVA), leading to the development of the lung progression associated signature (LPAS). Interestingly, we discovered that the LPAS not only accurately predicts the prognosis of LUAD patients but also forecasts genomic alterations, distinguishes between 'cold' and 'hot' tumours, and identifies potential candidates suitable for immunotherapy. PSMB1, identified within Cluster 6, was experimentally shown to significantly enhance cancer cell invasion and migration, highlighting the clinical relevance of LPAS in predicting LUAD progression and providing a potential target for therapeutic intervention. Our findings suggest that LPAS offers a novel biomarker for LUAD patient stratification, with significant implications for improving prognostic accuracy and guiding treatment decisions.

Synthetic Lethality between Cohesin and WNT Signaling Pathways in Diverse Cancer Contexts

Cohesin is a highly conserved ring-shaped complex involved in topologically embracing chromatids, gene expression regulation, genome compartmentalization, and genome stability maintenance. Genomic analyses have detected mutations in the cohesin complex in a wide array of human tumors. These findings have led to increased interest in cohesin as a potential target in cancer therapy. Synthetic lethality has been suggested as an approach to exploit genetic differences in cancer cells to influence their selective killing. In this study, we show that mutations in ESCO1, NIPBL, PDS5B, RAD21, SMC1A, SMC3, STAG2, and WAPL genes are synthetically lethal with stimulation of WNT signaling obtained following LY2090314 treatment, a GSK3 inhibitor, in several cancer cell lines. Moreover, treatment led to the stabilization of β-catenin and affected the expression of c-MYC, probably due to the occupancy decrease in cohesin at the c-MYC promoter. Finally, LY2090314 caused gene expression dysregulation mainly involving pathways related to transcription regulation, cell proliferation, and chromatin remodeling. For the first time, our work provides the underlying molecular basis for synthetic lethality due to cohesin mutations and suggests that targeting the WNT may be a promising therapeutic approach for tumors carrying mutated cohesin.

RPTOR mutation: a novel predictor of efficacious immunotherapy in melanoma

Identifying biomarkers to evaluate the therapeutic effect of immune checkpoint inhibitors (ICIs) is crucial. Regulatory Associated Protein of MTOR Complex 1 (RPTOR), one of the genes in the mTOR pathway, plays a role in regulating tumor progression. However, the connection between RPTOR mutation and the efficacy of ICIs in melanoma remains unclear. The data of ICIs-treated melanoma patients in discovery (n = 384) and validation (n = 320) cohorts were obtained from cBioPortal databases. The genomic data in the two cohorts was used to investigate the connection between RPTOR mutation and immunotherapy efficacy. The underlying mechanisms were explored based on data from the The Cancer Genome Atlas (TCGA)-skin cutaneous melanoma (SKCM) cohort. Compared to melanoma patients with RPTOR wildtype (RPTOR-WT), RPTOR-mutation (RPTOR-Mut) patients achieved prolonged overall survival (OS) in both discovery cohort (median OS of 49.3 months vs. 21.7 months; HR = 0.41, 95% CI: 0.18-0.92; P = 0.026) and validation cohorts (not reached vs. 42.0 months; HR = 0.34, 95% CI: 0.11-1.06; P = 0.049). RPTOR-Mut melanoma patients exhibited a higher objective response rate (ORR) than RPTOR-WT patients in the discovery cohort (55.0% vs. 29.0%, P = 0.022). RPTOR-Mut patients exhibited higher TMB than RPTOR-WT patients in both discovery and validation cohorts (P < 0.001). RPTOR-Mut melanoma patients had an increased number of DNA damage response (DDR) mutations in TCGA-SKCM cohort. Immune cell infiltration analysis suggested that activated CD4 memory T cells were more enriched in RPTOR-Mut tumors. RPTOR-Mut melanoma patients had higher expression levels of immune-related genes than the RPTOR-WT patients. Our results suggest that RPTOR mutation could serve as a predictor of effective immunotherapy for melanoma.