New Prognostic Biomarkers and Drug Targets for Skin Cutaneous Melanoma via Comprehensive Bioinformatic Analysis and Validation

Abstract

Skin cutaneous melanoma (SKCM) is the most aggressive and fatal type of skin cancer. Its highly heterogeneous features make personalized treatments difficult, so there is an urgent need to identify markers for early diagnosis and therapy. Detailed profiles are useful for assessing malignancy potential and treatment in various cancers. In this study, we constructed a co-expression module using expression data for cutaneous melanoma. A weighted gene co-expression network analysis was used to discover a co-expression gene module for the pathogenesis of this disease, followed by a comprehensive bioinformatics analysis of selected hub genes. A connectivity map (CMap) was used to predict drugs for the treatment of SKCM based on hub genes, and immunohistochemical (IHC) staining was performed to validate the protein levels. After discovering a co-expression gene module for the pathogenesis of this disease, we combined GWAS validation and DEG analysis to identify 10 hub genes in the most relevant module. Survival curves indicated that eight hub genes were significantly and negatively associated with overall survival. A total of eight hub genes were positively correlated with SKCM tumor purity, and 10 hub genes were negatively correlated with the infiltration level of CD4+ T cells and B cells. Methylation levels of seven hub genes in stage 2 SKCM were significantly lower than those in stage 3. We also analyzed the isomer expression levels of 10 hub genes to explore the therapeutic target value of 10 hub genes in terms of alternative splicing (AS). All 10 hub genes had mutations in skin tissue. Furthermore, CMap analysis identified cefamandole, ursolic acid, podophyllotoxin, and Gly-His-Lys as four targeted therapy drugs that may be effective treatments for SKCM. Finally, IHC staining results showed that all 10 molecules were highly expressed in melanoma specimens compared to normal samples. These findings provide new insights into SKCM pathogenesis based on multi-omics profiles of key prognostic biomarkers and drug targets. GPR143 and SLC45A2 may serve as drug targets for immunotherapy and prognostic biomarkers for SKCM. This study identified four drugs with significant potential in treating SKCM patients.

The role of CCT5 in human tumors: a pan-cancer analysis

“…To determine whether genetic changes in CCT5 affect clinical outcomes in patients with cancer, we determined that the CCT5 mutation may be a risk factor for patients with skin cutaneous melanoma (SKCM). According to a recent study, approximately 75%-80% of skin cancerrelated deaths each year are caused by SKCM, which suggests that SKCM is one of the most aggressive cancers 48,49 . In addition, these ndings indicate that CCT5 acts as an oncogene in cancer development and may be an indicator for use in clinical applications in cancer prognosis.…”

Comparative transcriptome profiling of hair follicles from forest musk deer (Moschus berezovskii) at different stages

“…Deletion of GPR143 leads to a reduction in melanosomes, which are expressed signi cantly higher in black than in white sheep skin [13]. GPR143 is also closely associated with melanoma metastasis and may serve as a new target for studying the pathogenesis of melanoma [14]. The most signi cantly downregulated gene PDE8B encodes high-a nity phosphodiesterase, which hydrolyzes the second messenger (cAMP).…”

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy

“…28 We obtained three topranked peptides from PMEL, another pigmentation gene and CM antigen, which is considered a highly ranked candidate biomarker in UM. 29 Finally, the gene OCA2 produced two top-ranked peptides for the allele A*02:01. This gene is an attractive target for direct epitope intervention and other therapeutic options since it is a transmembrane protein playing a role in pigmentation and melanin synthesis, which is used as prognostic and predictive marker for CM and primary UM.…”