Abstract P6-04-14: Integrating whole genome sequencing data with RNAseq, pathway analysis, and quantitative proteomics to determine prognosis after standard adjuvant treatment with trastuzumab and chemotherapy in primary breast cancer patients (2016)

Abstract Background: Despite improvements in the treatment of HER2+ breast cancer (BC), almost all patients (pts) progress in the metastatic setting. Three examples of resistance mechanisms are: PI3K mutations, lack of ADCC, or low expression of HER2. We recently showed that among 237 pts who had HER2 amplifications, 49% had normal or low levels of HER2 RNA. In addition, quantification of HER2 protein by selected reaction monitoring mass spectrometry (SRM-MS) accurately predicted HER2 expression status compared with IHC (3+)/ISH (≥2.0). Here we report a comprehensive panomic approach that integrates whole genome sequencing (WGS), RNASeq, quantitative proteomics, and pathway analysis to determine associations between tumor molecular profiles and prognosis among HER2+ pts. Methods: Matched tumor-normal samples (FFPE tumors and blood) were obtained from 58 pts with HER2+ BC who had received standard adjuvant chemotherapy and trastuzumab. Pts were divided into 2 groups: those who had no recurrence after 5 years and those who had developed metastases. The HER2 status of each pt was previously determined using IHC/FISH. Samples underwent WGS and RNASeq according to NantOmics CLIA-approved assay specifications. WGS data were processed using Contraster; RNASeq data confirmed the presence of gene mutations and was used to identify mutational and transcript abundance. PARADIGM was used to reveal associations between gene mutations and pathway levels. SRM-MS was used for proteomics analysis of a panel of 53 proteins. Tumor areas from FFPE tissue sections were analyzed after laser microdissection. Absolute protein quantitation was accomplished through simultaneous detection of endogenous target and synthetic labeled heavy peptide identical to analytical targets. Genetic alterations in germline and tumor DNA were compared in pts with vs without recurrence. Results: There was no statistically significant difference in the mean concentration of HER2 in the tumors of pts with vs without recurrence: 2.34 fmol/µL vs 2.56 fmol/µL. Other analyzed proteins did not appear to be associated with recurrence; however, expected correlations between pt and tumor characteristics and protein expression were found. With regard to clinically relevant mutations, we found one germline BRCA2 mutation in a pt with no family history of this mutation. The most commonly found somatic mutations were in TP53 (11 pts), AMBRA1 (11 pts), MORC4 (10 pts), SETD2 (8 pts), CDC27 (6 pts), BCLAF1 (5 pts), ZNF479 (4 pts) , PIK3CA (3 pts), PIK3R1 (3 pts), RUNX1 (3 pts), and GATA3 (3 pts). Conclusion: Whereas HER2 expression status was predictive of OS and PFS in pts treated with trastuzumab (Nuciforo et al. Mol Onc. 2015), in this small exploratory study of HER2+ BC pts, HER2 expression status was not predictive of recurrence. To better understand the molecular mechanisms driving recurrence beyond HER2 status alone, genomic sequencing may define a signature of recurrence after anti-HER2 therapy. Citation Format: Benz SC, Rabizadeh S, Cecchi F, Beckman MW, Brucker SY, Hartmann A, Golovato J, Hembrough T, Janni W, Rack B, Sanborn JZ, Schneeweiss A, Vaske CJ, Soon-Shiong P, Fasching PA. Integrating whole genome sequencing data with RNAseq, pathway analysis, and quantitative proteomics to determine prognosis after standard adjuvant treatment with trastuzumab and chemotherapy in primary breast cancer patients. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-04-14.