Warren, Sarah

Abstract Background: Understanding heterogeneity within individual breast tumors is key to the ability to predict therapeutic outcome. Molecular heterogeneity is commonly evaluated based on genomic features, including mRNA abundance, gene copy number events, and somatic mutations. The expression profile and activation state of key proteins is widely recognized as another key element in defining tumor heterogeneity. We have taken advantage of NanoString 3D Biology™ technology (for research use only) and curated nCounter Vantage 3DTM Solid Tumor Assay to interrogate a survey panel of HER2-positive breast tumors with the ultimate goal of determining key relationships between multiple genomic and proteomic profiles in individual tumors. Methods: We analyzed samples from 24 HER2+ breast cancer patients using NanoString technology to quantify the expression profile for over 25 total and phospho signaling proteins, including PI3K/MAPK/EGFR/HER2, 770 mRNA corresponding to 13 canonical cancer pathways, and 104 somatic mutations and small INDELS that are commonly associated with cancer, including 8 known PIK3CA mutations. These analyses were carried out in a matched fresh frozen and FFPE samples on the nCounter paltform. Data were analyzed by nSolver to identify genotype specific expression profiles across the 24 samples. Results: In our proof-of-concept data set, we successfully demonstrate that NanoString’s 3D biology Technology shows concordance across both FFPE and fresh frozen sample types for DNA, RNA, and protein. NanoString analysis also showed high concordance to gold-standard techniques used to assess genotype and RNA expression profiles. The combination of digital DNA, RNA, and protein data from our HER2+ breast cancer samples yielded potentially actionable data based on mapping of mutational status as the driver of key differences in protein expression and mRNA abundance of the signaling targets profiled. This work sheds new light on HER2+ breast cancer biology and the interplay between genomic and proteomic profiles while setting the stage for future studies that further probe the differences observed in this sample set. Conclusions: Simultaneous analysis of mutational status (SNV) and expression at the level of both mRNA and protein promises to enable a more detailed view of the relationship between genotype and the biological and clinical behavior of key tumor types. The NanoString Vantage 3DTM Solid Tumor platform provides a rapid, reliable, and economic means of assessing these analytes simultaneously. The application of these analytes to models that make clinically actionable predictions will require additional analyses of large sample cohorts, but such analysis is quite feasible using a variety of sample types. Acknowledgements: Supported in part by grants from the Breast Cancer Research Foundation and the 26.2 with Donna Foundation. Citation Format: Sarayna Chumsri, Daniel J. Serie, Brian M. Necela, Jennifer M. Kachergus, Bianca C. Axenfeld, Gokhan Demirkan, Gavin Meredith, P. Martin Ross, Anisha Kharkia, Erin Piazza, Afshin Mashadi-Hossein, Sarah Warren, Sarah A. McLaughlin, Joseph Beechem, Gary Geiss, E. Aubrey Thompson. Simultaneous analysis of the mutational landscape and RNA and protein expression profile of HER2-positive breast cancer using 3D BiologyTM [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 3377. doi:10.1158/1538-7445.AM2017-3377

Abstract Background: Trastuzumab (H), a monoclonal antibody against HER2, has revolutionized the treatment for HER2-positive breast cancer. Besides inhibiting downstream signaling of HER2, several studies showed that H also exerts its anti-tumor activity via immune-related mechanisms. While H is quite effective in preventing recurrence, significant numbers of patients still develop recurrence despite adjuvant H-based chemotherapy. In this study, we analyzed immune-related genes that were associated with poor outcome in N9831. Methods: NanoStringTM technology was used to quantify mRNA of immune-related genes in baseline samples from 1,280 patients in N9831. In N9831, patients in arm A were treated with chemotherapy alone (AC-T), arm B received chemotherapy followed by sequential H (AC-T-H), and arm C received H concurrently with chemotherapy (AC-TH). Cox proportional hazard ratio (HR) was used to determine the association of each immune-related gene with recurrence free survival (RFS). Different immune subset signatures, including CD45, CD8, cytotoxic-cells, and T-cells were analyzed using algorithms developed by NanoString. Results: With the median follow up of 10.6 years, we identified a total 77 genes that were associated with improved outcome in arm C. Among these 77 genes, there were 20 tumor necrosis factor (TNF)-related genes. Of those, only OX40 (TNFRSF4) and its ligand TNFSF4 have interaction p < 0.10. Interestingly, we found uneven distribution of OX40 expression in the N9831 specimens. Approximately, 9.5% of HER2-positive breast cancer expressed OX40 at distinctly low level. Low expression of OX40 was significantly associated with HR positivity (OX40 low 61% vs. OX40 high 51%, p 0.003) and larger tumor size but not patients’ age, tumor grade, and lymph node status. Low expression of OX40 was significantly associated with low mTIL-CD45, CD8, cytotoxic-cells, and T-cells immune signature scores. Tumors with low OX40 expression had significantly lower levels of CTLA4 (p 9.11e-71) and PD-L1 expressions (p 2.49e-92). Low expression of OX40 is associated with poorer outcome among patients treated with H in both sequential (HR 0.88, 95% CI 0.79-0.98, p 0.022) and concurrent arms (HR 0.86, 95%CI 0.76-0.98, p 0.027) but not in chemotherapy only arm (HR 0.9, 95%CI 0.90-1.09, p 0.8). Similar findings were observed with its ligand TNFSF4 in arm A (HR 1.02, 95%CI 0.92-1.15, p 0.68), arm B (HR 0.87, 95%CI 0.76-0.99, p 0.04), and arm C (HR 0.81, 95%CI 0.68-0.95, p 0.01). Conclusion: Our study suggests that pre-existing expression of OX40 and its ligand TNFSF4 are prognostic and may also be predictive of adjuvant H benefit. Patients with distinctly low level of OX40 had poor outcome despite adjuvant H-based adjuvant chemotherapy. Our study provides a rationale to further evaluate the strategy to increase immune activation to improve outcome in this group of patients. Citation Format: Saranya Chumsri, Daniel J. Serie, Afshin Mashadi-Hossein, Sarah Warren, Alvaro Moreno-Aspitia, Geraldo Colon-Otero, Keith L. Knutson, Edith A. Perez, E. Aubrey Thompson. Correlation of immune co-stimulatory molecule OX40 and outcome in trastuzumab treated HER2-positive breast cancer patients in the NCCTG-N9831 [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 1682. doi:10.1158/1538-7445.AM2017-1682

ABSTRACT Human immunodeficiency virus type 1 (HIV-1) infection causes apoptosis of infected CD4 T cells as well as uninfected (bystander) CD4 and CD8 T cells. It remains unknown what signals cause infected cells to die. We demonstrate that HIV-1 protease specifically cleaves procaspase 8 to create a novel fragment termed casp8p41, which independently induces apoptosis. casp8p41 is specific to HIV-1 protease-induced death but not other caspase 8-dependent death stimuli. In HIV-1-infected patients, casp8p41 is detected only in CD4 + T cells, predominantly in the CD27 + memory subset, its presence increases with increasing viral load, and it colocalizes with both infected and apoptotic cells. These data indicate that casp8p41 independently induces apoptosis and is a specific product of HIV-1 protease which may contribute to death of HIV-1-infected cells.