Identifying Key Lysosome-Related Genes Associated with Drug-Resistant Breast Cancer Using Computational and Systems Biology Approach

Abstract

Background: Drug resistance in breast cancer is an unsolved problem in treating patients. It has been recently discussed that lysosomes contribute to the invasion and angiogenesis of cancer cells. There is evidence that lysosomes can also cause multi-drug resistance. We analyzed this emerging concept in breast cancer through computational and systems biology approaches. Objectives: We aimed to identify the key lysosome-related genes associated with drug-resistant breast cancer. Methods: All genes contributing to the structure and function of lysosomes were inquired through the Human Lysosome Gene Database. The prioritized top 51 genes from the provided lists of Endeavour, ToppGene, and GPSy as prioritization tools were selected. All lysosomal genes and 12 breast cancer-related genes aligned to identify the most similar genes to breast cancer-related genes. Different centralities were applied to score each human protein to calculate the most central lysosomal genes in the human protein-protein interaction (PPI) network. Common genes were extracted from the results of the mentioned methods as a selected gene set. For Gene Ontology enrichment, the selected gene set was analyzed by WebGestalt, DAVID, and KOBAS. The PPI network was constructed via the STRING database. The PPI network was analyzed utilizing Cytoscape for topology network interaction and CytoHubba to extract hub genes. Results: Based on biological studies, literature reviews, and comparing all mentioned analyzing methods, six genes were introduced as essential in breast cancer. This computational approach to all lysosome-related genes suggested that candidate genes include PRF1, TLR9, CLTC, GJA1, AP3B1, and RPTOR. The analyses of these six genes suggest that they may have a crucial role in breast cancer development, which has rarely been evaluated. These genes have a potential therapeutic implication for new drug discovery for chemo-resistant breast cancer. Conclusions: The present work focused on all the functional and structural lysosome-related genes associated with breast cancer. It revealed the top six lysosome hub genes that might serve as therapeutic targets in drug-resistant breast cancer. Since these genes play a pivotal role in the structure and function of lysosomes, targeting them can effectively overcome drug resistance.

WITHDRAWN: Analysis of heterogeneity in subpopulations of breast cancer using single-cell RNA sequencing

“…there was signi cant heterogeneity in gene expression among different subpopulations. For example, GJA1, which was the increased expression in subpopulation 5, has the potential to serve as a cancer biomarker for prognosis, as well as a therapeutic target to inhibit metastasis and chemoresistance in cancer [19]. Subpopulations 14 and 15 exhibited high expression of GRB7, which is often co-ampli ed and overexpressed with HER2 in human breast cancers [20].…”

Molecular subtype identification and prognosis stratification based on lysosome-related genes in breast cancer

“…Lysosomes also participate in some cancer-related signaling pathways, such as autophagy and apoptosis [ 8 , 9 ]. Recent studies have found that some lysosomal-related mechanisms play a key role in the development of breast cancer and are closely related to drug resistance and prognosis in prostate cancer [ 10 , 11 ]. Although lysosomal-related genes (LRGs) may be promising biomarkers for predicting cancer prognosis [ 12 , 13 ], few studies have focused on establishing LRG-based prognostic models for breast cancer.…”