Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy

Abstract

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients’ visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment.Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay.Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments.Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

Heterogeneity and molecular landscape of melanoma: implications for targeted therapy

“…Regarding one of the important parts of TME, extracellular matrix, Li et al have developed a prognostic model for UM based on basement membrane genes that can predict the response to immunotherapy. They also analyzed the expression patterns of these genes in different immune cells with the help of single-cell RNA sequencing (scRNA-seq) data [135]. Incidentally, High throughput gene expression analysis with bioinformatic tools paves the way for more analysis in finding different cellular patterns and expression of immunological pathways in TME that are shared by many tumors [136,137].…”

Single cell RNA-sequencing in uveal melanoma: advances in heterogeneity, tumor microenvironment and immunotherapy

“…Moreover, researchers had constructed a m7Grelated prognostic signature by integrating TCGA and GEO database and suggested PAG1 as biomarker for diagnosis and treatment of UM (29). Yunyue Li et al also developed a prognostic risk model based on basement membrane protein-related genes (30), and glycosylation-based gene signature and hypoxia-related gene signature were described as well by integrating single-cell analysis and machine learning (31,32). Re-analyzing publicly available single cell RNA sequencing, researchers found that FOXD1 exclusively expressed in high-risk UM and its expression is associated with a poor prognosis, suggesting FOXD1 as a new biomarker for the diagnosis of UM (33).…”

“…In the study of Yunyue Li et al, ADAMTS10 and ITGA5 were expressed in various immune cell, and ITGA5 showed predominant expression in CD8 +Tex and CD8+ T immune cell populations. Further studies should be carried out to study the function of those basement membrane protein-related genes in TME and immunotherapy of UM (30). Liping Shen et al conducted a pan cancer research of NQO1 and found that NQO1 was significantly upregulated in most cancer types.…”