Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. Transcriptome data and Percent Spliced In (PSI) values of ovarian cancer patients were downloaded from TCGA database and TCGA SpliceSeq. Totally we identified 1472 AS events that were associated with survival of ovarian serous cystadenocarcinoma (OC) and exon skipping (ES) was the most important type. Univariate and multivariate Cox regression analysis were performed to identify survival-associated AS events and developed the prognostic model based on 11-AS events. The immune cells and different response to cytotoxic T lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) blockers in low-risk and high-risk group of OC patients were analyzed. Ten kinds of immune cells were found up-regulated in low-risk group. Activated B cell, natural killer T cell, natural killer cell and regulatory T cell were associated with survival of OC. The patients in low-risk group had good response to CTLA-4 and PD-1 blockers treatment. Moreover, a regulatory network was established according to the correlation between AS events and splicing factors (SFs). The present study provided valuable insights into the underlying mechanisms of OC. AS events that were correlated with the immune system might be potential therapeutic targets.
Background Cuproptosis, as a copper-induced mitochondrial cell death, has attracted extensive attention recently, especially in cancer. Although some key regulatory genes have been identified in cuproptosis, the related lncRNAs have not been further studied. Exploring the prognostic and diagnostic value of cuproptosis-related lncRNAs (CRLs) in colon adenocarcinoma and providing guidance for individualized immunotherapy for patients are of great significance. Results A total of 2003 lncRNAs were correlated with cuproptosis genes and considered as CRLs. We screened 33 survival-associated CRLs and established a prognostic signature base on 7 CRLs in the training group. The patients in the low-risk group had better outcomes in both training group (P < 0.001) and test group (P = 0.016). More exciting, our model showed good prognosis prediction in both stage I–II (P = 0.020) and stage III–IV (P = 0.001). The nomogram model could further improve the accuracy of prognosis prediction. Interestingly, glucose-related metabolic pathways, which were closely related to cuproptosis, were enriched in the low-risk group. Meanwhile, the immune infiltration scores were lower in the high-risk group. The high-risk group was more sensitive to OSI.906 and ABT.888, while low-risk group was more sensitive to Sorafenib. Three lncRNAs, FALEC, AC083967.1 and AC010997.4, were highly expressed in serum of COAD patients, and the AUC was 0.772, 0.726 and 0.714, respectively, indicating their valuable diagnostic value. Conclusions Our research constructed a prognostic signature based on 7 CRLs and found three promising diagnostic markers for COAD patients. Our results provided a reference to the personalized immunotherapy strategies.
Objective Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of various cancers. In the present study, we aimed to identify specific AS events, which might be prognostic markers and therapeutic targets for ovarian cancer (OV). Methods Transcriptome data, clinical information, and Percent Spliced In (PSI) values were downloaded from TCGA database and TCGA SpliceSeq to explore the role of AS events in the prognosis of OV patients. Univariate and multivariate Cox regression analyses were performed to identify survival-associated AS events and develop multi-AS-based prognostic models. The K-M curves and ROC curves were conducted based on prognostic AS event models. Moreover, a splicing regulatory network was established according to the correlation between AS events and splicing factors (SFs). Finally, we performed functional enrichment analysis by GO terms and KEGG pathways. Results We identified 1,472 AS events that were associated with the survival of OV patients, and exon skipping (ES) was the most important type. We also found that prognostic models based on AS events were good predictors of OV prognosis, which could discriminate the high-risk group from the low-risk group (P < 0.05). Notably, the AUC value of AD, AP, AT, ES, ME, and the whole cohort was more than 0.70, indicating that these six models had valuable prediction strength. The risk score of prognostic models was identified as an independent prognostic factor. Furthermore, the AS-SF correlation network revealed several hub SF genes, including DDX39B, PNN, LUC7L3, ZC3H4 and SRSF11, and so on. Conclusions In the present study, we constructed powerful prognostic predictors for OV patients and uncovered interesting splicing networks. Collectively, our findings provided valuable insights into the underlying mechanisms of OV.
Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. Transcriptome data and Percent Spliced In (PSI) values of OV patients were downloaded from TCGA database and TCGA SpliceSeq. Totally we identified 1,472 AS events that were associated with survival of OV and exon skipping (ES) was the most important type. Univariate and multivariate Cox regression analysis were performed to identify survival-associated AS events and develop the prognostic model based on 11-AS events. The immune cells and different response to cytotoxic T lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) blockers in low-risk and high-risk group of OV patients were analyzed. Ten kinds of immune cells were found up-regulated in low-risk group. Activated B cell, natural killer T cell, natural killer cell and regulatory T cell were associated with survival of OV. The patients in low-risk group had good response to CTLA-4 and PD-1 blockers treatment. Moreover, a regulatory network was established according to the correlation between AS events and splicing factors (SFs). The present study provided valuable insights into the underlying mechanisms of OV. AS events that were correlated with the immune system might be potential therapeutic targets.
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