Identification of novel therapeutic target genes in acquired lapatinib-resistant breast cancer by integrative
Young Seok Lee1, Sun Goo Hwang2, Jin Ki Kim1
1Department of Biochemistry, School of Medicine, Konkuk University, Seoul, 143-701, Republic of Korea.
Abstract:
Acquired resistance to lapatinib is a highly problematic clinical barrier that has to be overcome for a successful cancer treatment. Despite efforts to determine the mechanisms underlying acquired lapatinib resistance (ALR), no definitive genetic factors have been reported to be solely responsible for the acquired resistance in breast cancer. Therefore, we performed a cross-platform meta-analysis of three publically available microarray datasets related to breast cancer with ALR, using the R-based RankProd package. From the meta-analysis, we were able to identify a total of 990 differentially expressed genes (DEGs, 406 upregulated, 584 downregulated) that are potentially associated with ALR. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs showed that "response to organic substance" and "p53 signaling pathway" may be largely involved in ALR process. Of these, many of the top 50 upregulated and downregulated DEGs were found in oncogenesis of various tumors and cancers. For the top 50 DEGs, we constructed the gene coexpression and protein-protein interaction networks from a huge database of well-known molecular interactions. By integrative analysis of two systemic networks, we condensed the total number of DEGs to six common genes (LGALS1, PRSS23, PTRF, FHL2, TOB1, and SOCS2). Furthermore, these genes were confirmed in functional module eigens obtained from the weighted gene correlation network analysis of total DEGs in the microarray datasets ("GSE16179" and "GSE52707"). Our integrative meta-analysis could provide a comprehensive perspective into complex mechanisms underlying ALR in breast cancer and a theoretical support for further chemotherapeutic studies.
Insights
Acquired lapatinib resistance (ALR) in breast cancer involves complex genetic factors. A meta-analysis identified six key genes (LGALS1, PRSS23, PTRF, FHL2, TOB1, SOCS2) potentially driving ALR, offering new therapeutic targets.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Acquired resistance to lapatinib presents a significant clinical challenge in breast cancer treatment.
- The precise genetic mechanisms underlying acquired lapatinib resistance (ALR) remain incompletely understood.
- Identifying specific genetic factors is crucial for overcoming treatment resistance.
Purpose of the Study:
- To conduct a cross-platform meta-analysis of gene expression data to identify genes associated with ALR in breast cancer.
- To elucidate the molecular pathways and key genes involved in the development of ALR.
- To provide a theoretical basis for developing novel therapeutic strategies against lapatinib-resistant breast cancer.
Main Methods:
- Utilized a meta-analysis approach combining three public microarray datasets of breast cancer with ALR.
- Employed RankProd package for identifying differentially expressed genes (DEGs).
- Performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, alongside gene coexpression and protein-protein interaction network construction.
Main Results:
- Identified 990 DEGs (406 upregulated, 584 downregulated) potentially linked to ALR.
- Enrichment analyses highlighted "response to organic substance" and "p53 signaling pathway" as significantly involved in ALR.
- Integrated network analysis pinpointed six core genes (LGALS1, PRSS23, PTRF, FHL2, TOB1, SOCS2) crucial for ALR, further validated by weighted gene correlation network analysis.
Conclusions:
- The study successfully identified key genetic factors and pathways implicated in acquired lapatinib resistance in breast cancer.
- The identified genes (LGALS1, PRSS23, PTRF, FHL2, TOB1, SOCS2) represent potential therapeutic targets for overcoming ALR.
- This integrative meta-analysis provides a comprehensive understanding of ALR mechanisms and supports future chemotherapeutic research.
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