The development of immunotherapy has changed the treatment landscape of advanced kidney renal clear cell carcinoma (KIRC), offering patients more treatment options. Cuproptosis, a novel cell death mode dependent on copper ions and mitochondrial respiration has not yet been studied in KIRC. We assembled a comprehensive cohort of The Cancer Genome Atlas (TCGA)-KIRC and GSE29609, performed cluster analysis for typing twice using seven cuproptosis-promoting genes (CPGs) as a starting point, and assessed the differences in biological and clinicopathological characteristics between different subtypes. Furthermore, we explored the tumor immune infiltration landscape in KIRC using ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) and the potential molecular mechanisms of cuproptosis in KIRC using enrichment analysis. We constructed a cuproptosis score (CUS) using the Boruta algorithm combined with principal component analysis. We evaluated the impact of CUS on prognosis, targeted therapy, and immunotherapy in patients with KIRC using survival analysis, the predictions from the Cancer Immunome Atlas database, and targeted drug susceptibility analysis. We found that patients with high CUS levels show poor prognosis and efficacy against all four immune checkpoint inhibitors, and their immunosuppression may depend on TGFB1. However, the high-CUS group showed higher sensitivity to sunitinib, axitinib, and elesclomol. Sunitinib monotherapy may reverse the poor prognosis and result in higher progression free survival. Then, we identified two potential CPGs and verified their differential expression between the KIRC and the normal samples. Finally, we explored the effect of the key gene FDX1 on the proliferation of KIRC cells and confirmed the presence of cuproptosis in KIRC cells. We developed a targeted therapy and immunotherapy strategy for advanced KIRC based on CUS. Our findings provide new insights into the relationship among cuproptosis, metabolism, and immunity in KIRC.

Background Chaperonin-containing TCP1 subunit 8 (CCT8) has been proved to be involved in the occurrence and development of some cancers. However, no study has reported the potential role of CCT8 in a pan-cancer manner. Methods TIMER2.0, GEPIA2, UALCAN and Sangerbox were used to explore the expression, prognosis and methylation of CCT8. We used cBioPortal, TISIDB, SangerBox, TIMER2.0 and TISMO to investigate the genetic alteration of CCT8 and the relationship of CCT8 with molecular subtype, immune subtype, immune infiltration and immunotherapy response. CCT8-related genes were screened out through GEPIA and STRING for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. CCK-8, the colony formation assay, the wound healing assay and the Transwell assay were performed to explore the influence of CCT8 on proliferation and migration. Results CCT8 was highly expressed in most cancers with a poor prognosis. The expression level of CCT8, which was affected by the promoter region methylation and genetic alteration, was related to the molecular and immune subtype of cancers. Interestingly, CCT8 was positively associated with the activated CD4 T cells and type 2 T-helper cells. CCT8 played a vital role in the cell cycle and RNA transport of cancers, and it significantly inhibited the proliferation and migration of lung adenocarcinoma cells when it was knocked down. Conclusion CCT8 plays an indispensable role in promoting the proliferation and migration of many cancers. CCT8 might be a biomarker of T-helper type 2 (Th2) cell infiltration and a promising therapeutic target for T-helper type 1(Th1)/Th2 imbalance.

Background The copper metabolism MURR1 domain (COMMD) protein family is involved in tumorigenicity of malignant tumors. However, as the member of COMMD, the role of COMMD2 in human tumors remains unknown. Methods We used The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Human Protein Atlas (HPA) database, Cancer Cell Line Encyclopedia (CCLE) platform, univariate Cox regression analysis, Kaplan–Meier curve, cBioPortal, UALCAN database, Sangerbox online platform, GSCA database gene set enrichment analysis (GSEA), and GeneMANIA to analyze the expression of COMMD2, its prognostic values, genomic alteration patterns, and the correlation with tumor stemness, tumor mutational burden (TMB), microsatellite instability (MSI), and immune infiltrates, drug sensitivity, and gene function enrichment in pan‐cancer. qRT‐PCR, CCK‐8, EdU, wound healing, and transwell migration assays were performed to confirm the function of COMMD2. Results COMMD2 was strongly expressed in most cancer types. Elevated COMMD2 expression affects the prognosis, clinicopathological stage, and molecular or immune subtypes of various tumors. Moreover, promoter hypomethylation and mutations in the COMMD2 gene may be associated with its high expression and poor survival. Additionally, we discovered that COMMD2 expression was linked to tumor stemness, TMB, MSI, immune cell infiltration, immune‐checkpoint inhibitors, and drug sensitivity in pan‐cancer. Furthermore, the COMMD2 gene co‐expression network is constructed with GSEA analysis, displaying significant interaction of COMMD2 with E2F targets, G2‐M checkpoint, and mitotic spindle in bladder cancer (BLCA). Finally, RNA interference data showed suppression of COMMD2 prevented proliferation and migration of BLCA and uterine corpus endometrial carcinoma (UCEC) cells. Conclusion Our findings shed light on the COMMD2 functions in human cancers and demonstrate that it is a promising prognostic biomarker and therapeutic target in pan‐cancer.

BackgroundAbnormalities in centrosome regulatory genes can induce chromosome instability, cell differentiation errors, and tumorigenesis. However, a limited number of comprehensive analyses of centrosome-related genes have been performed in low-grade gliomas (LGG).MethodsLGG data were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. The ConsensusClusterPlus” R package was used for unsupervised clustering. We constructed a centrosome-related genes (CRGs) signature using a random forest model, lasso Cox model, and multivariate Cox model, and quantified the centrosome-related risk score (centS). The prognostic prediction efficacy of centS was evaluated using a Receiver Operating Characteristic (ROC) curve. Immune cell infiltration and genomic mutational landscapes were evaluated using the ESTIMATE algorithm, single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm, and “maftools” R package, respectively. Differences in clinical features, isocitrate dehydrogenase (IDH) mutation, 1p19q codeletion, O6-methylguanine-DNA methyltransferase promoter (MGMTp) methylation, and response to antitumor therapy between the high- and low-centS groups were explored. “pRRophetic” R packages were used for temozolomide (TMZ) sensitivity analysis. qRT-PCR verified the differential expression of the centrosomal gene team, the core of which is CEP135, between LGG cells and normal cells.ResultsTwo distinct CRG-based clusters were identified using consensus unsupervised clustering analysis. The prognosis, biological characteristics, and immune cell infiltration of the two clusters differed significantly. A well-performing centS signature was developed to predict the prognosis of patients with LGG based on 12 potential CRGs. We found that patients in the high-centS group showed poorer prognosis and lower proportion of IDH mutation and 1p19q codeletion compared to those in the low-centS group. Furthermore, patients in the high-centS group showed higher sensitivity to TMZ, higher tumor mutation burden, and immune cell infiltration. Finally, we identified a centrosomal gene team whose core was CEP135, and verified their differential expression between LGG cells and normal glial cells.ConclusionOur findings reveal a novel centrosome-related signature for predicting the prognosis and therapeutic responsiveness of patients with LGG. This may be helpful for the accurate clinical treatment of LGG.