Abstract 3705: Identification of frequent HER2 activating mutations in canine primary pulmonary adenocarcinoma
Bibliographic record
Abstract
Abstract Spontaneous primary canine lung cancers are aggressive malignancies that are increasingly common in dogs. They share clinicopathologic features with human lung cancers in never-smokers, but their genetic underpinnings are unknown. As never-smoker lung cancer incidence increases in humans, a need exists for improved biologic understanding and development of new models to fuel translational research. Here, we describe for the first time the detailed clinical and genetic features of primary canine lung cancers through case review and multi-platform sequencing of 90 primary canine lung tumors and cell lines. We performed multi-platform genomic profiling including whole exome sequencing (WES), amplicon panel-based sequencing of 250 regions of 51 cancer genes, and single nucleotide polymorphism (SNP) array-based analysis of tumors and matched constitutional DNA. We profiled 76 cPAC, 11 canine pulmonary adenosquamous carcinomas (cPASC) and three canine pulmonary squamous cell carcinomas (cPSCC). The median age at the time of diagnosis was 11 year old. The most common affected pure breed was the Labrador retriever (19%). Five cPACs assessed by WES displayed low mutation burden with a median of 64 somatic single nucleotide variants (SNVs), 19 somatic copy number variants (CNVs), and 1 structural variant (SV), and frequent C>T substitutions (80%) at NpCpG trinucleotides, a common mutation signature seen across human and canine cancers. Based on WES and amplicon sequencing, we discovered somatic, coding HER2 (ERRB2) point mutations in 37% of cPAC, but none in cPASC or cPSCC. Additional recurrently mutated genes in cPAC included CDKN2A/B (~40%), TP53 (~12%), K/HRAS (~7%), SMAD4 (~5%), and PTEN (~5%). In cPASC, KRAS and TP53 were the most frequently mutated genes (18% each). In cPSCC, no recurrently mutated genes were identified, but individual somatic coding mutations were found in BRAF and PTPN11. The majority (93%) of HER2 mutations were hotspot V659E, located on the transmembrane domain (TMD), and comparable to activating mutations at this same site in human cancer. We were able to detect this mutation not only in biopsied tumors, but also in the plasma of 33% (2/6) of dogs with localized V659E-positive tumors. Other somatic HER2 mutations identified were similarly located in the HER2 juxtamembrane domain and TMD including A664T and K676E. HER2 point mutations occurred in the absence of significant focal amplification (assessed by WES and SNP array) or overexpression (assessed by qRT-PCR and IHC). We also showed that HER2 mutation correlated with constitutive phosphorylation of Akt in cPAC cell lines. Furthermore, HER2 V659E-mutant lines displayed hypersensitivity to the HER2 kinase inhibitors neratinib (IC50, 23nM) and lapatinib (IC50, 168nM) relative to HER2 wild-type cell lines (IC50, >2500nM). These data bear implications for comparative understanding of HER2-mutant lung cancer across species. Citation Format: Gwendolen Lorch, Karthigayini Sivaprakasam, Victoria Zissman, Nieves Perdigones, Tania Contente-Cuomo, Alexandra Nazareno, Salvatore Facista, ShukMei Wong, Winnie Liang, Joseph M. Amann, Sara L. Sinicropi-Yao, Michael J. Koenig, Krista La Perle, Timothy G. Whitsett, Muhammed Murtaza, Jeffrey Trent, David P. Carbone, William P. Hendricks. Identification of frequent HER2 activating mutations in canine primary pulmonary adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3705.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".