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Poster Discussion session - Gastrointestinal tumours, colorectal 2

2425 - Causal modeling of CALGB/SWOG 80405 (Alliance) identifies primary (1_) side-related angiogenic drivers of metastatic colorectal cancer (mCRC)

Date

21 Oct 2018

Session

Poster Discussion session - Gastrointestinal tumours, colorectal 2

Topics

Translational Research

Tumour Site

Colon and Rectal Cancer

Presenters

Rahul Das

Citation

Annals of Oncology (2018) 29 (suppl_8): viii150-viii204. 10.1093/annonc/mdy281

Authors

R.K. Das1, L. Furchtgott1, F. Ou2, D. Swanson3, B. Hayete1, B. Harms1, D. Cunha1, J. Latourelle1, D. Wuest1, I. Khalil1, C. Washburn1, K. Rich1, C.D. Blanke4, J. Meyerhardt5, D. Niedzwiecki6, A. Nixon7, E.M. O'Reilly8, F. Innocenti9, H.J. Lenz10, A. Venook11

Author affiliations

  • 1 Precision Medicine, GNS Healthcare, Inc, 02139 - Cambridge, MA/US
  • 2 Alliance Statistics And Data Center, Mayo Clinic, Rochester/US
  • 3 Oslo Centre For Biostatistics And Epidemiology, Oslo University Hospital, Oslo/NO
  • 4 Medical Oncology, Oregon Health Science University, 972393011 - Portland/US
  • 5 Medical Oncology, Dana-Farber Cancer Institute, 02215 - Boston/US
  • 6 Department Of Biostatistics And Bioinformatics, Duke University Medical Center, Durham/US
  • 7 Duke Cancer Institute, Duke University Medical Center, Durham/US
  • 8 Medical Oncology, Memorial Sloan-Kettering Cancer Center, 10065 - New York/US
  • 9 Institute For Pharmacogenomics And Individualized Therapy, University of North Carolina, 27599 - Chapel Hill/US
  • 10 Medical Oncology, University of Southern California Norris Comprehensive Cancer Center, 90033 - Los Angeles/US
  • 11 Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 94115 - San Francisco/US
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Abstract 2425

Background

Patients (pts) in 80405 w/ mCRC originating from left-sided (L) 1° tumor had superior OS and PFS vs. pts w/ right-sided (R) 1°, but the underlying biological explanation is mostly unknown. We applied causal machine learning methods to the study to discover molecular pathways linking 1° side to OS and PFS.

Methods

430 pts including 128 RAS mutant (mut) had clinical data, mut status in 10 genes, MSI status, gene expression from 816 genes by Nanostring, and consensus molecular subtypes (CMS). For this analysis, transverse included w/ R-sided tumors. Using a Bayesian causal machine learning platform, we built an ensemble of network models for OS and PFS.

Results

Bayesian networks revealed a molecular pathway downstream of 1° side and driving OS and PFS: MSI-H status, BRAF mut, and extracellular matrix remodeling and angiogenesis-related genes including EGF7A, ALOX5, VIM, MAP4K1, COL10A1, COL6A3, and COL5A2. BRAF mut and angiogenesis signature are prognostic for OS and PFS and downstream of 1° side (Table); angiogenesis signature is downstream of BRAF (OR 13.1, p < 0.001). CMS4 and RAS mut are prognostic for OS and PFS but not causally downstream of 1° side. In angiogenesis-high pts (n = 90), 1° side is no longer prognostic for OS or PFS. In angiogenesis-low pts, 1° side remains prognostic only for OS. There is a significant angiogenesis by biologic interaction for OS (p = 0.008) favoring bevacizumab in angiogenesis-high pts.Table: 458PD

R vs LOSPFS
OR (p-value)HR (95% CI)p-valueHR (95% CI)p-value
RAS1.7 (0.01)1.42 (1.14-1.77)0.0021.24 (1.00-1.54)0.048
CMS41.2 (0.5)1.68 (1.33-2.13)<0.0011.60 (1.28-2.01)<0.001
angio sig.3.9 (<0.001)1.71 (1.32-2.21)<0.0011.71 (1.34-2.19)<0.001
BRAF7.7 (<0.001)1.76 (1.28-2.40)<0.0011.57 (1.16-2.12)0.003
R vs L (all)-1.50 (1.22-1.86)<0.0011.24 (1.02-1.51)0.03
R vs l (angio +)-1.26 (0.76-2.08)0.361.15 (0.72-1.82)0.56
R vs L (angio -)-1.47 (1.15-1.88)0.0021.15 (0.91-1.44)0.23

Conclusions

Impact of 1° side on OS and PFS is associated with BRAF and angiogenesis-related pathways, consistent with the relative clinical benefit of anti-VEGF therapy in R-sided and BRAF mut pts.

Clinical trial identification

NCT00265850.

Legal entity responsible for the study

Alliance for Clinical Trials in Oncology.

Funding

U10CA180821, U10CA180882, U10CA180830, U10CA180888; Eli Lilly and Company, Genentech, Pfizer.

Editorial Acknowledgement

Disclosure

R.K. Das, L. Furchtgott, B. Hayete, B. Harms, D. Cunha, J. Latourelle, D. Wuest, I. Khalil, C. Washburn: Employee: GNS Healthcare. K. Rich: Consulting: GNS Healthcare. A. Nixon: Research funding: Seattle Genetics, Tracon Pharma, Amgen, Novartis, Genentech/Roche, Acceleron, MedPacto, Leadiant Biosciences; Consultant: Pfizer, Eli Lilly. H-J. Lenz: Advisory board, lectures: BMS, Bayer, Roche, Merck Serono, Genentech. A. Venook: Research funding: Genentech, Roche, Merck. All other authors have declared no conflicts of interest.

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