ArticleScientific reports2022
C1QA, C1QB, and GZMB are novel prognostic biomarkers of skin cutaneous melanoma relating tumor microenvironment.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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18 citing papers in PubMed, 26 citations in OpenAlex.
- Identifying the hub genes in macrophage infiltration and verifying of the role of VSIG4 in IgA nephropathy.Scientific reports · 2026Article
- Cancer immunoediting in the melanoma tumor microenvironment: from immune elimination to therapeutic resistance.Frontiers in immunology · 2026Review
- Integrating of Machine Learning to Characterize Tumor-Infiltrating Immune Cell-Related Signature for Enhancing Prognosis for Glioma Patients.Biological procedures online · 2025Article
- Identification of an E2Fs-based gene signature for predicting prognosis and therapeutic response in colorectal cancer.Discover oncology · 2025Article
- Cyanidin-3-O-glucoside-mediated reduction of regulatory T cells: a therapeutic strategy for multiple myeloma.BMC immunology · 2025Article
- The Role of Complement C1qa in Experimental Intracerebral Hemorrhage.Translational stroke research · 2025Article
- Identification of circulating tumor cells marker genes as prognostic signature in triple-negative breast cancer.Discover oncology · 2025Article
- Defining the high-risk category of patients with cutaneous melanoma: a practical tool based on prognostic modeling.Frontiers in molecular biosciences · 2025Article
- Fast Variational Inference for Bayesian Factor Analysis in Single and Multi-Study Settings.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2025Article
- Single-cell sequencing reveals cellular differences and potential mechanisms in congenital pulmonary airway malformation.Frontiers in medicine · 2025Article
- Identification and experimental validation of prognostic genes related to cytochrome c in breast cancer.Frontiers in genetics · 2025Article
- Establishment of a novel efferocytosis potential index predicts prognosis and immunotherapy response in cancers.Heliyon · 2024Article
- Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics.Briefings in bioinformatics · 2024Article
- Causal relationship between complementFrontiers in genetics · 2024Article
- Review
- An ensemble-based deep learning model for detection of mutation causing cutaneous melanoma.Scientific reports · 2023Article
- Identification of NOTCH-driven matrisome-associated genes as prognostic indicators of multiple myeloma patient survival.Blood cancer journal · 2023Article
- Glucose 6 phosphatase dehydrogenase (G6PD): a novel diagnosis marker related to gastrointestinal cancers.American journal of translational research · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Skin cutaneous melanoma (SKCM) is the most lethal form of skin cancers owing to high invasiveness and high metastatic potential. 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-protein 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 (CCL4, CXCL10, CCL5, GZMB, C1QA, and C1QB) function as core TME-related genes (CTRGs). Significant differences of GZMB, C1QA, and C1QB expressions were found in gender and clinicopathologic staging of SKCM. High levels of GZMB, C1QA, and C1QB expressions were associated with favorable prognosis. Gene set enrichment analysis (GSEA) showed that cell-cell interaction, cell behavior, and intracellular signaling transduction may be mainly involved in both C1QA, C1QB and GZMB expressions and metabolism of phospholipid and amino acid, transcription, and translation may be implicated in low GZMB expressions. C1QA, C1QB, and GZMB are novel SKCM-relating CTRGs, providing promising immune-related prognostic biomarkers for SKCM.
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