Abstract LB-103: Landscape of somatic ERBB2 Mutations: Findings from AACR GENIE and comparison to ongoing ERBB2 mutant basket study

Background: AACR GENIE is an international data-sharing project that aggregates clinical-grade cancer genomic data. As a demonstration of utility, we evaluated the landscape of ERBB2 mutations in the first 18,486 patients included in this registry and compared it to the first 100 patients enrolled in an ongoing international Phase 2 SUMMIT ‘basket’ study of the pan-HER inhibitor neratinib in ERBB2 mutant solid tumors (NCT01953926). Results: ERBB2 mutations were identified in 2.8% (519/18,486) of patients in the GENIE cohort and observed at all participating centers. In total, there were 482 missense, 66 indels, 19 truncating mutations, and 14 structural variants. A total of 263 unique missense mutations were observed including 12 at previously identified hotspots which accounted for 69.2% of all missense mutations. 35 unique cancer types were represented. The tumor types with the highest proportion of ERBB2 mutations were bladder (12.8%, 82/641), breast (3.9%, 87/2230), colorectal (3.3%, 70/2102), and NSCLC (3%, 90/3006). Among patients with copy number data available (91%) 11% had concurrent ERBB2 amplification, most often in breast cancer. The most frequently observed alterations in ERBB2, adjusted for differing exon coverage between panels, was S310F/Y in 0.46% of the GENIE cohort (12.6% of samples with ERBB2 alterations), Y772_A775dup in 0.21% (6.9%), R678Q in 0.17% (4.5%), L755S in 0.16% (5.2%), V777L in 0.12% (3.8%), and V842I in 0.09% (3.1%). The distribution of specific ERBB2 variants differed significantly by tumor type with exon 20 insertions being most common in NSCLC (44.4%, 40/90), L755S (18.9%, 11/92) in breast, S310F/Y (26.9%, 28/104) in bladder, and V842I (13.9%, 10/72) in colorectal cancer. Structural variants included intragenic deletions (n=4) and fusions involving various partners including GRB7 (n=2), and one each of C1orf87, PPIL6, HEXIM2, THRA, ASIC2, BCA3, WIPF2. The frequencies of ERBB2 mutant cancer types observed in the GENIE cohort were generally comparable to those enrolled to the neratinib basket study including NSCLC (17 vs 22%, respectively), breast (16.4 vs 24%), bladder (15.5 vs 14%), colorectal (13.2 vs 17%), and endometrial (4.2 vs 6%). At the variant level, S310F/Y was less prevalent in GENIE compared to the neratinib study (12.6 vs 24%) while all other mutations were generally similar including L755S (5.2 vs 9%), R678Q (4.5 vs 2%), Y772_A775dup (6.9 vs 13%), V777L (3.8 vs 9%), and V842I (3.1 vs 6%). Conclusion: GENIE confirms that a diversity of ERBB2 mutations are prevalent across a variety of tumor types in patients with advanced cancer. The genomic landscape of ERBB2 mutations was largely similar in the population based GENIE cohort and the neratinib SUMMIT study, providing the first direct evidence that basket study enrollment accurately reflects the true landscape of the target alteration.

Citation Format: Alison Schram, Helen H. Won, Fabrice Andre, Monica Arnedos, Funda Meric - Bernstam, Philippe L. Bedard, Kenna R. Shaw, Hugo Horlings, Christine Micheel, Ben Ho Park, Grace Mann, Alshad S. Lalani, Lillian Smyth, David B. Solit, Deborah Schrag, Mia A. Levy, Barrett J. Rollins, Mark Routbort, Charles L. Sawyers, Eva Lepisto, Michael F. Berger, David M. Hyman, on behalf of the AACR Project GENIE Consortium. Landscape of somatic ERBB2 Mutations: Findings from AACR GENIE and comparison to ongoing ERBB2 mutant basket study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-103. doi:10.1158/1538-7445.AM2017-LB-103

Quantitative proteomic analysis in breast cancer

Much progress has recently been made in the genomic and transcriptional characterization of tumors. However, historically the characterization of cells at the protein level has suffered limitations in reproducibility, scalability and robustness. Recent technological advances have made it possible to accurately and reproducibly portray the global levels and active states of cellular proteins. Protein microarrays examine the native post-translational conformations of proteins including activated phosphorylated states, in a comprehensive high-throughput mode, and can map activated pathways and networks of proteins inside the cells. The reverse-phase protein microarray (RPPA) offers a unique opportunity to study signal transduction networks in small biological samples such as human biopsy material and can provide critical information for therapeutic decision-making and the monitoring of patients for targeted molecular medicine. By providing the key missing link to the story generated from genomic and gene expression characterization efforts, functional proteomics offer the promise of a comprehensive understanding of cancer. Several initial successes in breast cancer are showing that such information is clinically relevant.