scholarly journals SHP2 promotes Triple Negative Breast Cancer by mediating crosstalk between EGFR and Wnt beta-catenin signaling pathways

2016 ◽  
Author(s):  
Elisha Martin
PLoS ONE ◽  
2014 ◽  
Vol 9 (9) ◽  
pp. e107616 ◽  
Author(s):  
Jae Young So ◽  
Janice J. Lin ◽  
Joseph Wahler ◽  
Karen T. Liby ◽  
Michael B. Sporn ◽  
...  

2021 ◽  
Author(s):  
Aalok N Patwa ◽  
Rikiya Yamashita ◽  
Jin Long ◽  
Leeat Keren ◽  
Michael Angelo ◽  
...  

Triple-negative breast cancer (TNBC), the poorest-prognosis breast cancer subtype, lacks clinically approved biomarkers for patient risk stratification, treatment management, and immunotherapies. Prior literature has shown that interrogation of the tumor-immune microenvironment (TIME) may be a promising approach for the discovery of novel biomarkers that can fill these gaps. Recent developments in high-dimensional tissue imaging technology, such as multiplexed ion beam imaging (MIBI), provide spatial context to protein expression in the TIME, opening doors for in-depth characterization of cellular processes. We developed a computational pipeline for the robust examination of the TIME using MIBI. We discover that profiling the functional proteins involved in cell-to-cell interactions in the TIME predicts recurrence and overall survival in TNBC. The interactions between CD45RO and Beta Catenin and CD45RO and HLA-DR were the most relevant for patient stratification. We demonstrated the clinical relevance of the immunoregulatory proteins PD-1, PD-L1, IDO, and Lag3 by tying their interactions to recurrence and survival. Multivariate analysis revealed that our methods provide additional prognostic information compared to clinical variables. Our novel computational pipeline produces interpretable results, and is generalizable to other cancer types.


Cancers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1559
Author(s):  
Jiande Wu ◽  
Tarun Karthik Kumar Mamidi ◽  
Lu Zhang ◽  
Chindo Hicks

Background: The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). Methods: We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. Results: The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. Conclusion: The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.


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