FH535

Clear cell renal cell carcinoma (ccRCC) is a common urological malignancy that is involved in tumor genesis and development. However, few studies have focused on the predictive role of the global histone modification status in ccRCC. A total of 621 patients with complete transcript information and corresponding clinical profiles were obtained from TCGA-KIRC, GSE22541, and EMTAB3267 cohorts. A total of 122 histone modification relevant pathways were derived from MSigDB, and their activation status was quantified using GSVA. Differentially expressed genes (DEGs) were identified and filtrated using univariate Cox regression analysis. The signature was built relied on the least absolute shrinkage and selection operator (LASSO) regression analysis, and evaluated from survival difference, chemotherapy response, and activated pathways. A novel nomogram was established to quantify the probability of death in different patients. Seven risky and fifty-eight protective genes were used in LASSO analysis, and six genes were used to build the histone modification gene (HiMG) signature, which showed significant independent prognostic potential in all three cohorts. The nomogram showed acceptable incremental predictions. CKS2 (p = 0.004) and PD1 (p = 0.002) expression were significantly higher in grade 3 ccRCC than in grades 1-2. CKS2 siRNA in renal cancer cells caused reductions in cellular proliferation, migration, and invasion. Patients with low HiMG may be potential responders to rapamycin, erlotinib and FH535, while AZD6482 and CHIR-99,021 may be more suitable for patients with high HiMG levels. ccRCC histone modification distribution and a clinical signature for prognosis prediction, clinical decision making, and molecular mechanism exploration, were established for risk stratification and personalized treatments.

Cuproptosis, a newly identified form of programmed cell death, is thought to play a role in tumorigenesis. Long non-coding RNAs (lncRNAs) are reported to be associated with tumor progression and prognosis in colon adenocarcinoma (COAD). However, the role and prognostic value of cuproptosis-related lncRNAs in COAD remains unknown. This study is devoted to constructing and validating a cuproptosis-related lncRNA signature that can predict COAD patient outcomes using bioinformatics methods.

The COAD mRNA and lncRNA expression profiles and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and 2,567 cuproptosis-related lncRNAs were obtained. A 10 cuproptosis-related-lncRNA prognostic signature was then constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model and patients were divided into high- and low-risk groups. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve, and a nomogram were employed to evaluate the predictive power of the signature. The immune characteristics and drug sensitivity were also investigated based on the signature. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to verify the risk model. In vitro experiments were conducted to validate the expression of the ten lncRNAs during cuproptosis.

The high-risk group was associated with shorter overall survival (OS) time in COAD patients (p<0.001). Multivariate Cox regression indicated that a high-risk score was an independent risk factor for poor prognosis (p<0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 3 years: 0.879). Gene Ontology (GO) enrichment analysis revealed that the signature was highly correlated with the immune response in biological processes. The immune function, the score of the immune cells, and the expression of immune checkpoints were significantly different between the two risk groups. Three drugs, LAQ824, FH535, YM155, were found to be more sensitive in the high-risk group. Finally, the expression levels of the ten lncRNAs comprising the signature were tested by qRT-PCR.

A ten-cuproptosis-related lncRNA signature was constructed that provided promising insights into personalized prognosis and drug selection among COAD patients.