A novel m6A/m5C/m1A score signature to evaluate prognosis and its immunotherapy value in colon cancer patients.

BACKGROUND: Colon cancer features strong heterogeneity and invasiveness, with high incidence and mortality rates. Recently, RNA modifications involving m6A, m5C, and m1A play a vital part in tumorigenesis and immune cell infiltration. However, integrated analysis among various RNA modifications in colon cancer has not been performed. METHODS: RNA-seq profiling, clinical data and mutation data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus. We first explored the mutation status and expression levels of m6A/m5C/m1A regulators in colon cancer. Then, different m6A/m5C/m1A clusters and gene clusters were identified by consensus clustering analysis. We further constructed and validated a scoring system, which could be utilized to accurately assess the risk of individuals and guide personalized immunotherapy. Finally, m6A/m5C/m1A regulators were validated by immunohistochemical staining and RT-qPCR. RESULTS: In our study, three m6A/m5C/m1A clusters and gene clusters were identified. Most importantly, we constructed a m6A/m5C/m1A scoring system to assess the clinical risk of the individuals. Besides, the prognostic value of the score was validated with three independent cohorts. Moreover, the level of the immunophenoscore of the low m6A/m5C/m1A score group increased significantly with CTLA-4/PD-1 immunotherapy. Finally, we validated that the mRNA and protein expression of VIRMA and DNMT3B increased in colon cancer tissues. CONCLUSIONS: We constructed and validated a stable and powerful m6A/m5C/m1A score signature to assess the survival outcomes and immune infiltration characteristics of colon cancer patients, which further guides optimization of personalized treatment, making it valuable for clinical translation and implementation.

Identification and validation of a new pyroptosis-associated lncRNA signature to predict survival outcomes, immunological responses and drug sensitivity in patients with gastric cancer.

BACKGROUND: Gastric cancer (GC) ranks fifth in prevalence among carcinomas worldwide. Both pyroptosis and long noncoding RNAs (lncRNAs) play crucial roles in the occurrence and development of gastric cancer. Therefore, we aimed to construct a pyroptosis-associated lncRNA model to predict the outcomes of patients with gastric cancer. METHODS: Pyroptosis-associated lncRNAs were identified through co-expression analysis. Univariate and multivariate Cox regression analyses were performed using the least absolute shrinkage and selection operator (LASSO). Prognostic values were tested through principal component analysis, a predictive nomogram, functional analysis and Kaplan‒Meier analysis. Finally, immunotherapy and drug susceptibility predictions and hub lncRNA validation were performed. RESULTS: Using the risk model, GC individuals were classified into two groups: low-risk and high-risk groups. The prognostic signature could distinguish the different risk groups based on principal component analysis. The area under the curve and the conformance index suggested that this risk model was capable of correctly predicting GC patient outcomes. The predicted incidences of the one-, three-, and five-year overall survivals exhibited perfect conformance. Distinct changes in immunological markers were noted between the two risk groups. Finally, greater levels of appropriate chemotherapies were required in the high-risk group. AC005332.1, AC009812.4 and AP000695.1 levels were significantly increased in gastric tumor tissue compared with normal tissue. CONCLUSIONS: We created a predictive model based on 10 pyroptosis-associated lncRNAs that could accurately predict the outcomes of GC patients and provide a promising treatment option in the future.

A comprehensive analysis and validation of cuproptosis-associated genes across cancers: Overall survival, the tumor microenvironment, stemness scores, and drug sensitivity.

Background: Cuproptosis is a novel type of cell death induced by copper. Cuproptosis-associated genes play a crucial part in oncogenesis and the growth and metastasis of tumors. However, the correlations among cuproptosis-associated genes, overall survival, the tumor microenvironment, and drug sensitivity remain unclear. Therefore, we performed an analysis of cuproptosis-associated genes across cancers. Methods: We downloaded RNA sequence expression data, clinical and survival data, stemness score data, and immune subtype data of cuproptosis-associated genes from the UCSC Xena. Next, we conducted differential analysis, expression analysis and correlation analysis across cancers with various R packages. Moreover, survival analysis and Cox hazard analysis were conducted to investigate the relationships between cuproptosis-associated genes and survival outcomes in various cancer types. Finally, we also analyzed the relationship among the levels of cuproptosis-associated genes across cancers, immune types, the tumor microenvironment, stemness scores, and drug sensitivity. Expression validation of cuproptosis-associated genes in renal cancer and normal tissues by immunohistochemical staining. Results: We found that 10 cuproptosis-associated genes (FDX1, LIAS, LIPT1, DLD, DLAT, PDHA1, PDHB, MTF1, GLS, and CDKN2A) were differently expressed in 18 tumors and normal tissues. Survival outcomes showed that cuproptosis-associated genes had prognostic value in various cancer types. Moreover, we identified that cuproptosis-associated genes had different levels in six immune subtypes. The study also indicated that the levels of most cuproptosis-associated genes were positively correlated with the RNAss and DNAss. FDX1, LIAS, LIPT1, DLD, DLAT, PDHA1, and PDHB were negatively correlated with immune scores and ESTIMATE scores. In addition, we identified the top 16 drugs strongly sensitivity to cuproptosis-associated genes according to the correlation coefficient. Finally, we also found that cuproptosis-associated genes were significantly correlated with immune subtype, clinical features, the tumor microenvironment, and drug sensitivity in Kidney renal clear cell carcinoma. And the results of immunohistochemical staining analysis was very consistent with the previous analysis. Conclusion: We performed an overall analysis to uncover the roles of cuproptosis-associated genes in differential expression, survival outcomes, immune subtypes, the tumor microenvironment, stemness scores, and cancer drug sensitivity across cancers.