Development of a basement membrane gene signature and identification of the potential candidate therapeutic targets for pancreatic cancer

Lin, Kai; Xu, Dong; Wang, Xiaoxiao; Shi, Jun Yi; Gao, Wentao

doi:10.21037/gs-23-24

Cited by 1 publication

(1 citation statement)

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“…Several recent studies have already attempted to mine public databases to identify prognostic gene signatures related to BM proteins in tumors. For example, Cai et al identified a 7-gene signature associated with basement membrane proteins that predicted the prognostic status of breast cancer patients and provided insights for immunotherapy ( Cai et al, 2022 ); Zhou et al developed a risk model using 8 BMRGs, which revealed that clear-cell renal cell carcinoma patients in the low-risk group had a better response to immunotherapy ( Zhou et al, 2022 ); Lin et al established a 7-BMRG signature and identified five small compounds that could potentially be used for the treatment of pancreatic cancer patients, providing new perspectives for a deeper understanding of this disease ( Lin et al, 2023 ). Overall, these studies highlight the significance of basement membrane proteins in the precise treatment of tumors.…”

Section: Discussionmentioning

confidence: 99%

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

Li,

Cai,

Yang

et al. 2023

Front. Pharmacol.

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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.

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Section: Discussionmentioning

confidence: 99%