Biomedical and Biotechnology Research Journal (Jan 2022)
Integrated proteomic, transcriptomic, and genomic analysis identifies fibrinogen beta and fibrinogen gamma as key modulators of breast cancer progression and metastasis
Abstract
Background: As per the WHO, more than 2 million new cases are diagnosed with breast cancer and more than 685,000 deaths have been reported in 2020. Incidence of recurrence and metastasis has also risen and poses a challenge for developing new therapies with the identification of newer targets. Methods: The objective of this study is to analyze and integrate various data across genomic, transcriptomic, and proteomic levels to find promising markers linked with tumor progression and metastasis development in breast cancer. This study begins with the extraction of data of differentially expressed proteins and subsequently analyzes their gene expression changes and genomic alterations to integrate all three omics data. We used curated breast cancer datasets of different proteomic experiments from dbDEPC3.0 and TCGA datasets of the Metastatic Breast Cancer Project to compare gene expressions and genomic alterations. We further used cBioportal, GeneMania, GEPIA2, Reactome, and canSAR computational tools for identifying the most significant genes associated with tumor progression and metastasis. Results: Based on false discovery rate, 14 genes were subjected to pathway analysis in Reactome and the top 25 significant pathways were analyzed out of a total of 170 pathways. Our study found fibrinogen gamma (FGG) and fibrinogen beta (FGB) linked to pathways connecting RAS-MAPK, its downstream mutants, integrin signaling, and extracellular matrix remodeling pathways. Conclusion: Survival analysis suggested that FGG (P = 0.0065) and FGB (P = 0.013) have a significant positive correlation along with their stage-wise changes in copy number variations and genomic alterations play a pivotal role in controlling tumor progression and metastasis.
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