Journal of cancer research and clinical oncology · 2023
The evaluation of tumor microenvironment infiltration and the identification of angiogenesis-related subgroups in skin cutaneous melanoma.
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Li Junpeng, Ren Hangjun, Huai Hongyu, Li Junliang, Xie Pan, Li Xiaolu
Аннотация
BACKGROUND: There are limited studies on the association between angiogenesis-related genes (ARGs) and the predictive risk of melanoma, even though angiogenic factors, which are essential for tumor growth and metastasis, might be secreted by angiogenesis-related protein in skin cutaneous melanoma (SKCM). To forecast patient outcomes, this study attempts to develop a predictive risk signature linked to angiogenesis in cutaneous melanoma.
METHODS: In 650 patients with SKCM, the expression and mutation of ARGs were examined, and this information was related to the clinical prognosis. SKCM patients were split into two groups based on how well they performed on the ARG. The link between ARGs, risk genes, and immunological microenvironment was examined using a range of algorithmic analysis techniques. Based on these five risk genes, an angiogenesis risk signature was created. We developed a nomogram and examined the sensitivity of antineoplastic medications to help the proposed risk model's clinical applicability.
RESULTS: The risk model developed by ARGs revealed that the prognosis for the two groups was significantly different. The predictive risk score was negatively connected with memory B cells, activated memory CD4 + T cells, M1 macrophages, and CD8 + T cells, and favorably correlated with dendritic cells, mast cells, and neutrophils.
CONCLUSIONS: Our findings offer fresh perspectives on prognostic evaluation and imply that ARG modulation is implicated in SKCM. Potential medications for the treatment of individuals with various SKCM subtypes were predicted by drug sensitivity analysis.
METHODS: In 650 patients with SKCM, the expression and mutation of ARGs were examined, and this information was related to the clinical prognosis. SKCM patients were split into two groups based on how well they performed on the ARG. The link between ARGs, risk genes, and immunological microenvironment was examined using a range of algorithmic analysis techniques. Based on these five risk genes, an angiogenesis risk signature was created. We developed a nomogram and examined the sensitivity of antineoplastic medications to help the proposed risk model's clinical applicability.
RESULTS: The risk model developed by ARGs revealed that the prognosis for the two groups was significantly different. The predictive risk score was negatively connected with memory B cells, activated memory CD4 + T cells, M1 macrophages, and CD8 + T cells, and favorably correlated with dendritic cells, mast cells, and neutrophils.
CONCLUSIONS: Our findings offer fresh perspectives on prognostic evaluation and imply that ARG modulation is implicated in SKCM. Potential medications for the treatment of individuals with various SKCM subtypes were predicted by drug sensitivity analysis.