Molecular Alterations in Breast Cancer

Breast Cancer ◽  
1999 ◽  
pp. 143-170
Author(s):  
Ivan Bergstein
2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1034-1034
Author(s):  
Justin Wayne Wong Tiu-lim ◽  
Jun Yin ◽  
Joanne Xiu ◽  
Wolfgang Michael Korn ◽  
Heinz-Josef Lenz ◽  
...  

1034 Background: The Ras-MAPK pathway is a known driver of tumorigenesis and therapeutic target in a variety of cancers. Alterations in this pathway have been linked to decreased tumor immunogenicity. However, molecular alterations in the Ras-MAPK are rare in breast cancer (BC) and their clinical implications remain unclear. As mutational status does not accurately correlate with transcriptional activity, a MAPK pathway activity score (MPAS, Wagle et al., 2018, npj Precision Medicine) is indicative of MAPK activation and correlates with response to MEK (MEKi) or BRAF inhibition (BRAFi). Our goal was to determine the frequency of molecular alterations in the Ras-MAPK and correlate to MAPK pathway activation in MBC. Methods: A total of 6464 BC samples underwent comprehensive molecular profiling at Caris Life Sciences. Analyses included next generation sequencing of DNA (592 Gene Panel, NextSeq; whole exome sequencing, NovaSEQ), RNA (NovaSeq, whole transcriptome sequencing, WTS) and IHC. MPAS and immune cell fraction (ICF, Quantiseq) were assessed by mRNA analysis. Wilcoxon, Fisher’s exact, or Dunnett’s test was used. All results shown were statistically significant (p < 0.05). Results: The predominant alteration of RAS genes was mutation followed by amplification, no fusions were detected (Table). Only 0.17% of all tumors harbor KRAS G12c mutations. The highest MPAS scores were found in KRAS mutants (mut), HRAS mut (Q61, G1213), BRAF V600 (class 1) mut and NRAS Q61 mut (Table) and therefore used to define Genomic MAPK Activated Tumors (GMAT). GMAT compared to wild type (WT) had significantly higher PD-L1 expression, TMB and MSI/dMMR. GMAT had less B cells (3.4% vs 4.4%), more M1 Macrophages (4.4% vs 3.4%) and neutrophils (5.5% vs 2.7%) regardless of HR status but less NK cells (2.3% s 3.0%), MSDCs (0.9% vs 3.0%) only in HR- tumors with respect to WT. GMAT tumors showed more frequent mutation rate (mr) of PIK3CA (HR+: 57.3% vs 40%; HR-: 41.9% vs 17.9%). HR+ tumors had a higher mr of MSH3 (11.8% vs 0.6%) while HR- tumors had higher mr of PIK3R1 (9.6% vs 3.8%), RhoA (5.3% vs 0.5%), DNA repair genes (TERT, 18.2% vs 1.0%; ARID1A, 18.2% vs 5.9%; PRKDC, 3.9% vs 0) and lower TP53 mr (54.5% vs 85.8%) compared to WT. Conclusions: Our study demonstrates that RAS, BRAF and MEK1 mutations are associated with MAPK pathway activation indicative of benefit from MEKi or BRAFi. GMAT warrant further investigation for combinations targeting the RAS-MAPK pathway and immune checkpoint inhibitors.[Table: see text]


2013 ◽  
Vol 64 (5) ◽  
pp. 660-670 ◽  
Author(s):  
Gillian O'Hurley ◽  
Etáin Daly ◽  
Anthony O'Grady ◽  
Robert Cummins ◽  
Cecily Quinn ◽  
...  

2020 ◽  
pp. 71-88 ◽  
Author(s):  
Jayaram Kancherla ◽  
Shruti Rao ◽  
Krithika Bhuvaneshwar ◽  
Rebecca B. Riggins ◽  
Robert A. Beckman ◽  
...  

PURPOSE In this work, we introduce CDGnet (Cancer-Drug-Gene Network), an evidence-based network approach for recommending targeted cancer therapies. CDGnet represents a user-friendly informatics tool that expands the range of targeted therapy options for patients with cancer who undergo molecular profiling by including the biologic context via pathway information. METHODS CDGnet considers biologic pathway information specifically by looking at targets or biomarkers downstream of oncogenes and is personalized for individual patients via user-inputted molecular alterations and cancer type. It integrates a number of different sources of knowledge: patient-specific inputs (molecular alterations and cancer type), US Food and Drug Administration–approved therapies and biomarkers (curated from DailyMed), pathways for specific cancer types (from Kyoto Encyclopedia of Genes and Genomes [KEGG]), gene-drug connections (from DrugBank), and oncogene information (from KEGG). We consider 4 different evidence-based categories for therapy recommendations. Our tool is delivered via an R/Shiny Web application. For the 2 categories that use pathway information, we include an interactive Sankey visualization built on top of d3.js that also provides links to PubChem. RESULTS We present a scenario for a patient who has estrogen receptor (ER)–positive breast cancer with FGFR1 amplification. Although many therapies exist for patients with ER-positive breast cancer, FGFR1 amplifications may confer resistance to such treatments. CDGnet provides therapy recommendations, including PIK3CA, MAPK, and RAF inhibitors, by considering targets or biomarkers downstream of FGFR1. CONCLUSION CDGnet provides results in a number of easily accessible and usable forms, separating targeted cancer therapies into categories in an evidence-based manner that incorporates biologic pathway information.


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