Background The mechanism of cuproptosis, a novel copper-induced cell death by regulating tricarboxylic acid cycle (TCA)-related genes, has been reported to regulate oxidative phosphorylation system (OXPHOS) in cancers and can be regarded as potential therapeutic strategies in cancer; however, the characteristics of cuproptosis in pan-cancer have not been elucidated. Methods The multi-omics data of The Cancer Genome Atlas were used to evaluate the cuproptosis-associated characteristics across 32 tumor types. A cuproptosis enrichment score (CEScore) was established using a single sample gene enrichment analysis (ssGSEA) in pan-cancer. Spearman correlation analysis was used to identify pathway most associated with CEScore. Lasso-Cox regression was used to screen prognostic genes associated with OXPHOS and further construct a cuproptosis-related prognostic model in clear cell renal cell carcinoma (ccRCC). Results We revealed that most cuproptosis-related genes (CRGs) were differentially expressed between tumors and normal tissues, and somatic copy number alterations contributed to their aberrant expression. We established a CEScore index to indicate cuproptosis status which was associated with prognosis in most cancers. The CEScore was negatively correlated with OXPHOS and significantly featured prognosis in ccRCC. The ccRCC patients with high-risk scores show worse survival outcomes and bad clinical benefits of Everolimus (mTOR inhibitor). Conclusions Our findings indicate the importance of abnormal CRGs expression in cancers. In addition, identified several prognostic CRGs as potential markers for prognostic distinction and drug response in the specific tumor. These results accelerate the understanding of copper-induced death in tumor progression and provide cuproptosis-associated novel therapeutic strategies.

Colorectal cancer (CRC) is one of the most common malignant tumors. 5-fluorouracil (5-FU) has been used for the standard first-line treatment for CRC patients for several decades. Although 5-FU based chemotherapy has increased overall survival (OS) of CRC patients, the resistance of CRC to 5-FU based chemotherapy is the principal cause for treatment failure. Thus, identifying novel biomarkers to predict response to 5-FU based chemotherapy is urgently needed. In the present study, the gene expression profile of GSE3964 from the Gene Expression Omnibus database was used to explore the potential genes related to intrinsic resistance to 5-FU. A gene module containing 81 genes was found to have the highest correlation with chemotherapy response using Weighted Gene Co-expression Network Analysis (WGCNA). Then a protein-protein interaction (PPI) network was constructed and ten hub genes (TGFBI, NID, LEPREL2, COL11A1, CYR61, PCOLCE, IGFBP7, COL4A2, CSPG2, and VTN) were identified using the CytoHubba plugin of Cytoscape. Seven of these hub genes showed significant differences in expression between chemotherapy-sensitive and chemotherapy-resistant samples. The prognostic value of these seven genes was evaluated using TCGA COAD (Colorectal Adenocarcinoma) data. The results showed that TGFBI was highly expressed in chemotherapy-sensitive patients, and patients with high TGFBI expression have better survival.

Background Excessive iron accumulation and lipid peroxidation are primary characteristics of ferroptosis in hepatocellular carcinoma (HCC). Ferroptosis inducer combined with immunotherapy has become a new hope for HCC patients. Therefore, the construction and validation of subtype‐specific sensitivity to ferroptosis inducer will be helpful for hierarchical management and precise individual therapy. Methods RNA‐seq transcriptome and clinical data of HCC patients were extracted from International Cancer Genome Consortium (ICGC) dataset and The Cancer Genome Atlas (TCGA) dataset. Consistency matrix and data clustering of the both cohorts were constructed by ‘ConsensusClusterPlus’ package. Single‐sample gene set enrichment analysis (ssGSEA) analysis was performed to evaluate immune infiltration. Cox analysis was utilized to construct a ferroptosis phenotype‐related prognostic model (FRPM) in HCC. The predictive efficiency of the constructed FRPM was evaluated through Kaplan Meier (K‐M) survival analyses and Receiver Operating Characteristic (ROC) curves. The expression levels of candidate genes were detected and validated by Real‐Time PCR between liver cancer tissues and adjacent non‐tumor liver tissues. Results 45 differentially expressed ferroptosis‐related genes (FRGs) were identified between HCC tissues and non‐tumor liver tissues. Furthermore, four ferroptosis‐associated clusters (FACs) of HCC were established via consensus clustering. Subsequently, we established a FRPM, consisting of four prognostic genes (SLC7A11, SLC1A5, GCLM and SAT1), to evaluate the survival of HCC patients, based on which, patients were divided into high‐risk group and low‐risk group. The high‐risk group exhibited worse survival compared to low‐risk group (p < 0.0001 both in TCGA and ICGC cohorts). Patients belong to different FACs or different risk scores showed distinct clinical characteristics. Moreover, in the validation experiment, the transcriptional expression levels of the four prognostic genes were consistent with the results drew from datasets. Conclusion We revealed a novel FRGs signature, which may provide the molecular characteristic data for effectively prognostic evaluation and potential personalized therapy for HCC patients.

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