Identification of anoikis-related subtypes and development of risk stratification system in skin cutaneous melanoma

被引:2
|
作者
Tian, Jun [1 ]
Cao, Zi-jian [2 ]
Zhang, Yuan [3 ]
Zhou, Jin-ke [2 ]
Yang, Li [1 ]
机构
[1] Shaanxi Prov Peoples Hosp, Dept Dermatol, Xian 710068, Peoples R China
[2] 63600 Hosp PLA, Dept Dermatol, Lanzhou 732750, Peoples R China
[3] Shaanxi Prov Peoples Hosp, Dept Oncol, Xian, Peoples R China
关键词
Skin cutaneous melanoma; Anoikis; Prognosis; Immunotherapy; Tumor microenvironment; GASTRIC-CANCER; RESISTANCE; METASTASIS; CELLS; PATHWAYS; THERAPY;
D O I
10.1016/j.heliyon.2023.e16153
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Anoikis, a form of apoptosis induced by cell detachment, plays a key role in cancer metastasis. However, the potential roles of anoikis-related genes (ARGs) in assessing the prog-nosis of skin cutaneous melanoma (SKCM) and the tumor microenvironment (TME) remain unclear. Methods: The data from TCGA corresponding to transcriptomic expression patterns for patients with SKCM were downloaded and utilized to screen distinct molecular subtypes by a non-negative matrix factorization algorithm. The prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) Cox regression and was validated in SKCM patients from the GEO cohort. Moreover, the relationship of the ARG_score with prognosis, tumor -infiltrating immune cells, gene mutation, microsatellite instability (MSI), and immunotherapy efficacy. Results: We screened 100 anoikis-related differentially expressed genes between SKCM tissues and normal skin tissues, which could divide all patients into three different subtypes with significantly distinct prognosis and immune cell infiltration. Then, an anoikis-related signature was developed based on subtype-related DEGs, which could classify all SKCM patients into low and high ARG_score groups with differing overall survival (OS) rates. ARG_score was confirmed to be a strong independent prognostic indicator for SKCM patients. By combining ARG_score with clin-icopathological features, a nomogram was constructed, which could accurately predict the in-dividual OS of patients with SKCM. Moreover, low ARG_score patients presented with higher levels of immune cell infiltration, TME score, higher tumor mutation burden, and better immu-notherapy responses. Conclusions: Our comprehensive analysis of ARGs in SKCM provides important insights into the immunological microenvironment within the tumor of SKCM patients and helps to forecast prognosis and the response to immunotherapy in SKCM patients, thereby making it easier to tailor more effective treatment strategies to individual patients.
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页数:14
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