Protein expression of prognostic genes in primary melanoma and benign nevi

Abstract

Purpose To evaluate the protein expression characteristics of genes employed in a recently introduced prognostic gene expression assay for patients with cutaneous melanoma (CM). Methods We studied 37 patients with CM and 10 with benign (melanocytic) nevi (BN). Immunohistochemistry of primary tumor tissue was performed for eight proteins: COL6A6, DCD, GBP4, KLHL41, KRT9, PIP, SCGB1D2, SCGB2A2. Results The protein expression of most markers investigated was relatively low (e.g., DCD, KRT9, SCGB1D2) and predominantly cytoplasmatic in melanocytes and keratinocytes. COL6A6, GBP4, and KLHL41 expression was significantly enhanced in CM when compared to BN. DCD protein expression was significantly correlated with COL6A6, GBP4, and KLHL41. GBP4 was positively correlated with KLHL41 and inversely correlated with SCGB2B2. The latter was also inversely correlated with serum S100B levels at time of initial diagnosis. The presence of SCGB1D2 expression was significantly associated with ulceration of the primary tumor. KRT9 protein expression was significantly more likely found in acral lentiginous melanoma. The presence of DCD expression was less likely associated with superficial spreading melanoma subtype but significantly associated with non-progressive disease. The absence of SCGB2A2 expression was significantly more often observed in patients who did not progress to stage III or IV. Conclusions The expression levels observed were relatively low but differed in part with those found in BN. Even though we detected some significant correlations between the protein expression levels and clinical parameters (e.g., CM subtype, course of disease), there was no major concordance with the protective or risk-associated functions of the corresponding genes included in a recently introduced prognostic gene expression assay.

Single-cell RNA-sequencing analyses along with abundant machine learning methods develop and validate a novel metabolism-related prognostic model in SKCM

“…Based on these ndings, we identi ed ve prognostic signature genes for SKCM among the DEGs among the three molecular subgroups, namely FCGR2, GBP4, CHRDL1, SLC5A3 and GJA1. The expression level of guanylate-binding protein 4 gene (GBP4) has been shown in a previous study increased in melanoma tissue, which is consistent with our experiment 25 . Gap junction protein alpha 1 gene (GJA1), also called connexin 43 (Cx43), has a tumor suppressor function and can inhibit the progression of melanoma 26 .…”

Machine learning and experimental validation to construct a metastasis-related gene signature and ceRNA network for predicting osteosarcoma prognosis

“…Among the 15 genes considered in this signature, GMDS, SDF2L1, KLHL17, ITGB5, CAT3 and KLHL41 were previously found to be associated with tumors. For example, a mutation in GMDS was shown to induce the proliferation of colon cancer cells [ 16 ], SDF2L1 expression was found to be upregulated when nasopharyngeal carcinoma cell growth was promoted in vitro [ 17 ], KLHL17 was shown to be associated with prostate cancer [ 18 ], ITGB5 was considered to serve as a prognostic biomarker for poor prognosis in gastric cancer [ 19 ], and KLHL41 expression was found to be significantly enhanced in melanoma [ 20 ]. However, the present study is the first to show the association between the expression of these genes and OS.…”

Guanylate binding protein 4 shapes an inflamed tumor microenvironment and identifies immuno-hot tumors

“…Previous studies have shown that the GBP family is highly important for antibacterial defense and that Guanylate binding protein 4 (GBP4) is a key inflammasome adaptor required for prostaglandin biosynthesis and bacterial clearance by neutrophils (Wandel et al 2020 ; Tyrkalska et al 2016 ). GBP4 was also found to be highly expressed in multiple cancer types, including melanoma (Gambichler et al 2022 ) and colorectal cancer (Xu et al 2020 ). In another study, GBP4 expression was shown to be correlated with poor overall survival (OS) in patients with ovarian cancer (Huo et al 2021 ).…”