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Tumor microenvironment (TME) provides powerful evidences for discerning SKCM, raising the prospect to identify biomarkers of SKCM. Based on the transcriptome profiles of patients with SKCM and the corresponding clinical information from The Cancer Genome Atlas (TCGA), we used ESTIMATE algorithm to calculate ImmuneScore and StromalScore and identified the TME-Related differentially expressed genes (DEGs), than the intersected TME-Related DEGs were used for subsequent functional enrichment analysis. Protein\u2013protein interaction (PPI) analysis was used to identify the functionality-related DEGs and univariate Cox regression analysis was used to identify the survival-related DEGs. Furthermore, SKCM-related DEGs were identified based on two Gene Expression Omnibus (GEO) datasets. Finally, we intersected functionality-related DEGs, survival-related DEGs, and SKCM-related DEGs, ascertaining that six DEGs (<jats:italic>CCL4<\/jats:italic>, <jats:italic>CXCL10<\/jats:italic>, <jats:italic>CCL5<\/jats:italic>, <jats:italic>GZMB<\/jats:italic>, <jats:italic>C1QA<\/jats:italic>, and <jats:italic>C1QB<\/jats:italic>) function as core TME-related genes (CTRGs). Significant differences of <jats:italic>GZMB<\/jats:italic>, <jats:italic>C1QA<\/jats:italic>, and <jats:italic>C1QB<\/jats:italic> expressions were found in gender and clinicopathologic staging of SKCM. High levels of <jats:italic>GZMB<\/jats:italic>, <jats:italic>C1QA<\/jats:italic>, and <jats:italic>C1QB<\/jats:italic> expressions were associated with favorable prognosis. Gene set enrichment analysis (GSEA) showed that cell\u2013cell interaction, cell behavior, and intracellular signaling transduction may be mainly involved in both <jats:italic>C1QA<\/jats:italic>, <jats:italic>C1QB<\/jats:italic> and <jats:italic>GZMB<\/jats:italic> expressions and metabolism of phospholipid and amino acid, transcription, and translation may be implicated in low <jats:italic>GZMB<\/jats:italic> expressions. <jats:italic>C1QA<\/jats:italic>, <jats:italic>C1QB<\/jats:italic>, and <jats:italic>GZMB<\/jats:italic> are novel SKCM-relating CTRGs, providing promising immune-related prognostic biomarkers for SKCM.<\/jats:p>","DOI":"10.1038\/s41598-022-24353-9","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T10:02:33Z","timestamp":1669629753000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["C1QA, C1QB, and GZMB are novel prognostic biomarkers of skin cutaneous melanoma relating tumor microenvironment"],"prefix":"10.1038","volume":"12","author":[{"given":"Zhuoshuai","family":"Liang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingfeng","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jikang","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianbo","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,11,28]]},"reference":[{"key":"24353_CR1","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.det.2018.08.003","volume":"37","author":"EH Tracey","year":"2019","unstructured":"Tracey, E. 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