Abstract
Our goal in these analyses was to use genomic features from a test set of primary breast tumors to build an integrated transcriptome landscape model that makes relevant hypothetical predictions about the biological and/or clinical behavior of HER2-positive breast cancer. We interrogated RNA-Seq data from benign breast lesions, ER+, triple negative, and HER2-positive tumors to identify 685 differentially expressed genes, 102 alternatively spliced genes, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were associated with the HER2-positive tumors in our survey panel. These features were integrated into a transcriptome landscape model that identified 12 highly interconnected genomic modules, each of which represents a cellular processes pathway that appears to define the genomic architecture of the HER2-positive tumors in our test set. The generality of the model was confirmed by the observation that several key pathways were enriched in HER2-positive TCGA breast tumors. The ability of this model to make relevant predictions about the biology of breast cancer cells was established by the observation that integrin signaling was linked to lapatinib sensitivity in vitro and strongly associated with risk of relapse in the NCCTG N9831 adjuvant trastuzumab clinical trial dataset. Additional modules from the HER2 transcriptome model, including ubiquitin-mediated proteolysis, TGF-beta signaling, RHO-family GTPase signaling, and M-phase progression, were linked to response to lapatinib and paclitaxel in vitro and/or risk of relapse in the N9831 dataset. These data indicate that an integrated transcriptome landscape model derived from a test set of HER2-positive breast tumors has potential for predicting outcome and for identifying novel potential therapeutic strategies for this breast cancer subtype.
Highlights
15% of all invasive breast tumors, at presentation, overexpress the EGFR family member HER2 [1,2,3]
Sequence alignment data are summarized in Table S2; but, briefly, percent aligned reads ranged from 73-86%, with GeneCountReadStart aligned ranging from 22M to 68M read pairs per sample. (Note that for paired end sequencing, total aligned 50nt tags is equal to twice the number of read pairs.) Mode normalization of gene counts was carried out as described previously [25]
The first of these was that we could integrate multiple genomic features from RNA sequence (RNA-Seq) data to model the genomic architecture of a test set of HER2-positive tumors
Summary
15% of all invasive breast tumors, at presentation, overexpress the EGFR family member HER2 [1,2,3]. The initial targeted trials were done with the humanized HER2 monoclonal antibody trastuzumab (Herceptin®), first in the metastatic and in the adjuvant setting [5,6,7,8,9,10,11,12] Such targeted therapy in the adjuvant setting has resulted in a dramatic increase in survival of patients with HER2 breast cancer, as first firmly established by clinical trials such as NCCTG N9831 and NSABP B31 [13], which have helped define the standard of care for such patients. Additional trials have been carried out (or are in progress) using other HER2 monoclonal antibodies (pertuzumab, trastuzumab-emtansine) as well as small molecule receptor tyrosine kinase inhibitors (lapatinib) that target HER2 signaling activity
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