AUTHOR=Yang Ronghua , Wang Zhengguang , Li Jiehua , Pi Xiaobing , Gao Runxing , Ma Jun , Qing Yi , Zhou Sitong 

TITLE=The Identification of the Metabolism Subtypes of Skin Cutaneous Melanoma Associated With the Tumor Microenvironment and the Immunotherapy

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2021.707677

DOI=10.3389/fcell.2021.707677

ISSN=2296-634X

ABSTRACT=Skin cutaneous melanoma (SKCM) is a highly aggressive and resistant cancer with the greatest metabolic heterogeneity. Therefore, we examined the diverse metabolic signatures of SKCM on a comprehensive basis based on non-negative matrix factorization (NMF) categorization, clustered SKCM into three distinct metabolic subtypes(C1, C2, and C3). Next, we evaluated the metadata sets of metabolic signatures, prognostic value, transcriptomic features, tumor microenvironment signature, immune infiltration, clinical features, drug sensitivity, and immunotherapy response of the subtypes and compared the acquired subtypes with prior publications on classification. subtype C1 exhibited high metabolic activity, low immune score, and poor prognosis. subtype C2 displayed low metabolic activity, high immune infiltration, high stromal score, and high expression of immune checkpoints demonstrated the drug sensitivity to PD-1 inhibitors. The C3 subtype manifested moderate metabolic activity, high enrichment in carcinogenesis-relevant pathways, high levels of CpG island methylation phenotype (CIMP), and poor prognosis. Eventually, a 90-gene classifier was produced to implement the SKCM taxonomy and executed a consistency test in different cohorts to validate its reliability. Meanwhile, a preliminary validation was performed to ascertain the role of SLC7A4 from the gene classifier in SKCM. These results indicated that this 90-gene signature can be replicated to identify the metabolism classification of SKCM stably. In this study, a novel SKCM classification approach based on metabolic gene expression profiles was established to further understand the metabolic diversity of SKCM and offered precisely targeted therapy.