乳腺癌
生物标志物
基因
医学
肿瘤科
癌症
内科学
癌症研究
计算生物学
生物信息学
生物
遗传学
作者
Bingkun Wang,Nianjin Wei,Meiyu He,Guocai Zhong,Shujun Zhang
标识
DOI:10.2174/0113892029357021250626210819
摘要
Background: Lysosomal dysfunction is significantly associated with tumor progression. This study aimed to identify and develop a new predictive panel for breast cancer (BRCA) and examine its relationship with the immune environment and therapeutical status. Methods: We developed a prognostic panel employing lysosomal genes from The Cancer Genome Atlas Program (TCGA) and then validated and assessed it externally in the Gene Expression Omnibus (GEO). Furthermore, the disparities were identified between high and low-risk subgroups by examining the infiltration of microenvironment cells, gene expression of immune checkpoints, and small molecular compounds. Ultimately, the cancerous function and potential pathway of core LRG were verified using a series of in vitro tests. Results: First, the predictive panel of lysosome-related genes (LRGs) was generated via the least absolute shrinkage and selection operator. High-risk populations showed the shortest survival times. Meanwhile, the area under the curves (AUC) for predicting 1-, 3-, and 5-year survival rates indicated good predictive performance across all cohorts. Subsequent extensive investigations revealed a strong correlation between the risk score and the pathological stage, drug sensitivity, and tumor mutation burden (TMB). Then, we discovered that the levels of GPLD1, PLA2G5, and STX7 were reduced in BRCA tissues, whereas the expressions of PLA2G10, LAMP3, EIF4EBP1, and LPCAT1 were elevated in BRCA tissues compared to paracancerous tissues. Patients exhibiting high EIF4EBP1 expression experienced a more unfavorable outcome compared to those with low expression. EIF4EBP1 disruption dramatically impeded BRCA cell growth and invasive capacity, as demonstrated by CCK8, wound healing, and transwell assays. Moreover, EIF4EBP1 silencing in BRCA cells significantly restricted the TGF-β pathway. Conclusion: Our 9-LRG panel is a promising classifier for assessing the prognosis of BRCA. Notably, targeting EIF4EBP1 could potentially serve as a theoretical foundation for enhancing the prognosis of BRCA patients.
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