Research Papers:
Does molecular profiling of tumors using the Caris molecular intelligence platform improve outcomes for cancer patients?
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Abstract
Philip Carter1, Costi Alifrangis2, Biancastella Cereser1, Pramodh Chandrasinghe1,3, Lisa Del Bel Belluz1, Thomas Herzog4,5, Joel Levitan1, Nina Moderau1, Lee Schwartzberg6, Neha Tabassum1, Jinrui Wen1, Jonathan Krell1 and Justin Stebbing1
1Department of Surgery and Cancer, Imperial College, London, UK
2Department of Oncology, University College Hospital, London, UK
3Department of Surgery, University of Kelaniya, Kelaniya, Sri Lanka
4Department of Obstetrics and Gynecology, University of Cincinnati, Cincinnati, USA
5University of Cincinnati Cancer Institute, University of Cincinnati, Cincinnati, USA
6WEST Cancer Center, The University of Tennessee, Memphis, USA
Correspondence to:
Philip Carter, email: [email protected]
Keywords: tumor molecular profiling; cancer treatment
Received: July 29, 2017 Accepted: November 15, 2017 Published: January 16, 2018
ABSTRACT
We evaluated the effect of tailoring treatments based on predictions informed by tumor molecular profiles across a range of cancers, using data from Caris Life Sciences. These included breast carcinoma, colorectal adenocarcinoma, female genital tract malignancy, lung non-small cell lung cancer, neuroendocrine tumors, ovarian surface epithelial carcinomas, and urinary tract cancers.
Molecular profiles using mostly immunohistochemistry (IHC) and DNA sequencing for tumors from 841 patients had been previously used to recommend treatments; some physicians followed the suggestions completely while some did not. This information was assessed to find out if the outcome was better for the patients where their received drugs matched recommendations.
The IHC biomarker for the progesterone receptor and for the androgen receptor were found to be most prognostic for survival overall. The IHC biomarkers for P-glycoprotein (PGP), tyrosine-protein kinase Met (cMET) and the DNA excision repair protein ERCC1 were also shown to be significant predictors of outcome. Patients whose treatments matched those predicted to be of benefit survived for an average of 512 days, compared to 468 days for those that did not (P = 0.0684). In the matched treatment group, 34% of patients were deceased at the completion of monitoring, whereas this was 47% in the unmatched group (P = 0.0001).
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