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Novel disulfidptosis‐derived gene blueprint stratifying patients with breast cancer
Breast cancer remains the predominant cancer among females, accounting for about 24.2% of all cancer cases. Alarmingly, it is the primary cause of cancer‐related mortality in women under 45. This research analyzed RNA sequencing data from 1082 TCGA‐BRCA and 107 GSE58812 breast cancer patients. Single‐cell RNA data from five patients in the GSE118389 data set were also studied. Using Random forest and COX regression, we developed a prognostic model. Pathway analysis employed GSVA and GO, while immune profiles were assessed via ssGSEA and MCPcounter. Mutation patterns utilized maftools, and drug sensitivity scores were derived from the GDSC database with oncoPredict. Analysis of the GSE118389 data set identified three distinct cell types: immune, epithelial, and stromal. P53 and VEGF were notably enriched. Five key genes (TMEM251, ADAMTSL2, CDC123, PSMD1, TLE1) were pinpointed for their prognostic significance. We introduced a disulfidptosis‐associated score as a novel risk factor for breast cancer prognosis. Survival outcomes varied significantly between training and validation sets. Comprehensive immune profiling revealed no difference in activated CD8‐positive T cells between risk groups, but a positive correlation of NK cells, neutrophils, cytotoxic lymphocytes, and monocytic cells with the riskscore was noted. Importantly, a negative association between the drug Nelarabine and riskscore was identified. This research underscores the significance of a disulfidptosis‐associated gene signature in breast cancer prognosis.
Novel disulfidptosis‐derived gene blueprint stratifying patients with breast cancer
Breast cancer remains the predominant cancer among females, accounting for about 24.2% of all cancer cases. Alarmingly, it is the primary cause of cancer‐related mortality in women under 45. This research analyzed RNA sequencing data from 1082 TCGA‐BRCA and 107 GSE58812 breast cancer patients. Single‐cell RNA data from five patients in the GSE118389 data set were also studied. Using Random forest and COX regression, we developed a prognostic model. Pathway analysis employed GSVA and GO, while immune profiles were assessed via ssGSEA and MCPcounter. Mutation patterns utilized maftools, and drug sensitivity scores were derived from the GDSC database with oncoPredict. Analysis of the GSE118389 data set identified three distinct cell types: immune, epithelial, and stromal. P53 and VEGF were notably enriched. Five key genes (TMEM251, ADAMTSL2, CDC123, PSMD1, TLE1) were pinpointed for their prognostic significance. We introduced a disulfidptosis‐associated score as a novel risk factor for breast cancer prognosis. Survival outcomes varied significantly between training and validation sets. Comprehensive immune profiling revealed no difference in activated CD8‐positive T cells between risk groups, but a positive correlation of NK cells, neutrophils, cytotoxic lymphocytes, and monocytic cells with the riskscore was noted. Importantly, a negative association between the drug Nelarabine and riskscore was identified. This research underscores the significance of a disulfidptosis‐associated gene signature in breast cancer prognosis.
Novel disulfidptosis‐derived gene blueprint stratifying patients with breast cancer
Tang, Xiaojiang (author) / Ping, Baohua (author) / Liu, Yang (author) / Zhou, Yuhui (author)
Environmental Toxicology ; 39 ; 1715-1728
2024-03-01
14 pages
Article (Journal)
Electronic Resource
English
Construction of lncRNA prognostic model related to disulfidptosis in lung adenocarcinoma
| Elsevier | 2024