Necroptosis is a programmed cell death playing a significant role in cancer. Although necroptosis has been related to tumor immune environment (TIME) remodeling and cancer prognosis, however, the role of necroptosis-related genes (NRGs) in glioma is still elusive. In this study, a total of 159 NRGs were obtained, and parameters such as mutation rate, copy number variation (CNV), and relative expression level were assessed. Then, we constructed an 18-NRGs-based necroptosis-related signature (NRS) in the TCGA dataset, which could predict the patient’s prognosis and was validated in two external CGGA datasets. We also explored the correlation between NRS and glioma TIME, chemotherapy sensitivity, and certain immunotherapy-related factors. The two necroptosis-related subtypes were discovered and could also distinguish the patients' prognosis. Through the glioblastoma (GBM) scRNA-seq data analysis, NRGs’ expression levels in different GBM patient tissue cell subsets were investigated and the relative necroptosis status of different cell subsets was assessed, with the microglia score culminating among all. Moreover, we found a high infiltration level of immunosuppressive cells in glioma TIME, which was associated with poor prognosis in the high-NRS glioma patient group. Finally, the necroptosis suppressor CASP8 exhibited a high expression in glioma and was associated with poor prognosis. Subsequent experiments were performed in human glioma cell lines and patients' tissue specimens to verify the bioinformatic analytic findings about CASP8. Altogether, this study provides comprehensive evidence revealing a prognostic value of NRGs in glioma, which is associated with TIME regulation.

Background: Melanoma, as one of the most aggressive and malignant cancers, ranks first in the lethality rate of skin cancers. Cuproptosis has been shown to paly a role in tumorigenesis, However, the role of cuproptosis in melanoma metastasis are not clear. Studying the correlation beteen the molecular subtypes of cuproptosis-related genes (CRGs) and metastasis of melanoma may provide some guidance for the prognosis of melanoma.

Methods: We collected 1085 melanoma samples in The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus(GEO) databases, constructed CRGs molecular subtypes and gene subtypes according to clinical characteristics, and investigated the role of CRGs in melanoma metastasis. We randomly divide the samples into train set and validation set according to the ratio of 1:1. A prognostic model was constructed using data from the train set and then validated on the validation set. We performed tumor microenvironment analysis and drug sensitivity analyses for high and low risk groups based on the outcome of the prognostic model risk score. Finally, we established a metastatic model of melanoma.

Results: According to the expression levels of 12 cuproptosis-related genes, we obtained three subtypes of A₁, B₁, and C₁. Among them, C₁ subtype had the best survival outcome. Based on the differentially expressed genes shared by A₁, B₁, and C₁ genotypes, we obtained the results of three gene subtypes of A₂, B₂, and C₂. Among them, the B₂ group had the best survival outcome. Then, we constructed a prognostic model consisting of 6 key variable genes, which could more accurately predict the 1-, 3-, and 5-year overall survival rates of melanoma patients. Besides, 98 drugs were screened out. Finally, we explored the role of cuproptosis-related genes in melanoma metastasis and established a metastasis model using seven key genes.

Conclusions: In conclusion, CRGs play a role in the metastasis and prognosis of melanoma, and also provide new insights into the underlying pathogenesis of melanoma.