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      Overcoming intratumoural heterogeneity for reproducible molecular risk stratification: a case study in advanced kidney cancer

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          Abstract

          Background

          Metastatic clear cell renal cell cancer (mccRCC) portends a poor prognosis and urgently requires better clinical tools for prognostication as well as for prediction of response to treatment. Considerable investment in molecular risk stratification has sought to overcome the performance ceiling encountered by methods restricted to traditional clinical parameters. However, replication of results has proven challenging, and intratumoural heterogeneity (ITH) may confound attempts at tissue-based stratification.

          Methods

          We investigated the influence of confounding ITH on the performance of a novel molecular prognostic model, enabled by pathologist-guided multiregion sampling ( n = 183) of geographically separated mccRCC cohorts from the SuMR trial (development, n = 22) and the SCOTRRCC study (validation, n = 22). Tumour protein levels quantified by reverse phase protein array (RPPA) were investigated alongside clinical variables. Regularised wrapper selection identified features for Cox multivariate analysis with overall survival as the primary endpoint.

          Results

          The optimal subset of variables in the final stratification model consisted of N-cadherin, EPCAM, Age, mTOR (NEAT). Risk groups from NEAT had a markedly different prognosis in the validation cohort (log-rank p = 7.62 × 10 −7; hazard ratio (HR) 37.9, 95% confidence interval 4.1–353.8) and 2-year survival rates (accuracy = 82%, Matthews correlation coefficient = 0.62). Comparisons with established clinico-pathological scores suggest favourable performance for NEAT (Net reclassification improvement 7.1% vs International Metastatic Database Consortium score, 25.4% vs Memorial Sloan Kettering Cancer Center score). Limitations include the relatively small cohorts and associated wide confidence intervals on predictive performance. Our multiregion sampling approach enabled investigation of NEAT validation when limiting the number of samples analysed per tumour, which significantly degraded performance. Indeed, sample selection could change risk group assignment for 64% of patients, and prognostication with one sample per patient performed only slightly better than random expectation (median logHR = 0.109). Low grade tissue was associated with 3.5-fold greater variation in predicted risk than high grade ( p = 0.044).

          Conclusions

          This case study in mccRCC quantitatively demonstrates the critical importance of tumour sampling for the success of molecular biomarker studies research where ITH is a factor. The NEAT model shows promise for mccRCC prognostication and warrants follow-up in larger cohorts. Our work evidences actionable parameters to guide sample collection (tumour coverage, size, grade) to inform the development of reproducible molecular risk stratification methods.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12916-017-0874-9) contains supplementary material, which is available to authorized users.

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          Most cited references32

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          Wrappers for feature subset selection

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            Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: results from a large, multicenter study.

            There are no robust data on prognostic factors for overall survival (OS) in patients with metastatic renal cell carcinoma (RCC) treated with vascular endothelial growth factor (VEGF) -targeted therapy. Baseline characteristics and outcomes on 645 patients with anti-VEGF therapy-naïve metastatic RCC were collected from three US and four Canadian cancer centers. Cox proportional hazards regression, followed by bootstrap validation, was used to identify independent prognostic factors for OS. The median OS for the whole cohort was 22 months (95% CI, 20.2 to 26.5 months), and the median follow-up was 24.5 months. Overall, 396, 200, and 49 patients were treated with sunitinib, sorafenib, and bevacizumab, respectively. Four of the five adverse prognostic factors according to the Memorial Sloan-Kettering Cancer Center (MSKCC) were independent predictors of short survival: hemoglobin less than the lower limit of normal (P < .0001), corrected calcium greater than the upper limit of normal (ULN; P = .0006), Karnofsky performance status less than 80% (P < .0001), and time from diagnosis to treatment of less than 1 year (P = .01). In addition, neutrophils greater than the ULN (P < .0001) and platelets greater than the ULN (P = .01) were independent adverse prognostic factors. Patients were segregated into three risk categories: the favorable-risk group (no prognostic factors; n = 133), in which median OS (mOS) was not reached and 2-year OS (2y OS) was 75%; the intermediate-risk group (one or two prognostic factors; n = 301), in which mOS was 27 months and 2y OS was 53%; and the poor-risk group (three to six prognostic factors; n = 152), in which mOS was 8.8 months and 2y OS was 7% (log-rank P < .0001). The C-index was 0.73. This model validates components of the MSKCC model with the addition of platelet and neutrophil counts and can be incorporated into patient care and into clinical trials that use VEGF-targeted agents.
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              Nuclear signalling by tumour-associated antigen EpCAM.

              EpCAM was found to be overexpressed on epithelial progenitors, carcinomas and cancer-initiating cells. The role of EpCAM in proliferation, and its association with cancer is poorly explained by proposed cell adhesion functions. Here we show that regulated intramembrane proteolysis activates EpCAM as a mitogenic signal transducer in vitro and in vivo. This involves shedding of its ectodomain EpEX and nuclear translocation of its intracellular domain EpICD. Cleavage of EpCAM is sequentially catalysed by TACE and presenilin-2. Pharmacological inhibition or genetic silencing of either protease impairs growth-promoting signalling by EpCAM, which is compensated for by EpICD. Released EpICD associates with FHL2, beta-catenin and Lef-1 to form a nuclear complex that contacts DNA at Lef-1 consensus sites, induces gene transcription and is oncogenic in immunodeficient mice. In patients, EpICD was found in nuclei of colon carcinoma but not of normal tissue. Nuclear signalling of EpCAM explains how EpCAM functions in cell proliferation.
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                Author and article information

                Contributors
                alex.lubbock@vanderbilt.edu
                gds35@cam.ac.uk
                Fiach.O'Mahony@ed.ac.uk
                alaird2@exseed.ed.ac.uk
                pm72@st-andrews.ac.uk
                Marie.O'Donnell@nhslothian.scot.nhs.uk
                Thomas.Powles@bartshealth.nhs.uk
                david.harrison@st-andrews.ac.uk
                ian.overton@ed.ac.uk
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                26 June 2017
                26 June 2017
                2017
                : 15
                : 118
                Affiliations
                [1 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, MRC Institute of Genetics and Molecular Medicine, , University of Edinburgh, ; Edinburgh, EH4 2XU UK
                [2 ]Scottish Collaboration On Translational Research into Renal Cell Cancer (SCOTRRCC), Scotland, UK
                [3 ]ISNI 0000 0001 0721 1626, GRID grid.11914.3c, , School of Medicine, University of St Andrews, ; St Andrews, Fife, KY16 9TF UK
                [4 ]ISNI 0000 0004 0624 9907, GRID grid.417068.c, , Department of Pathology, Western General Hospital, ; Edinburgh, EH4 2XU UK
                [5 ]ISNI 0000 0001 2171 1133, GRID grid.4868.2, Barts Cancer Institute, Experimental Cancer Medicine Centre, , Queen Mary University of London, ; London, EC1M 6BQ UK
                [6 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Usher Institute of Population Health Sciences and Informatics, , University of Edinburgh, ; Edinburgh, EH16 4UX UK
                [7 ]ISNI 0000 0001 2264 7217, GRID grid.152326.1, , Present Address: Vanderbilt University School of Medicine, Vanderbilt University, ; Nashville, Tennessee USA
                [8 ]ISNI 0000000121885934, GRID grid.5335.0, , Present Address: Academic Urology Group, University of Cambridge, ; Box 43, Addenbrooke’s Hospital, Cambridge Biomedical Campus, Hill’s Road, Cambridge, CB2 0QQ UK
                Article
                874
                10.1186/s12916-017-0874-9
                5483837
                02db58f5-469f-40e9-8960-8febde79fe3d
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 8 November 2016
                : 15 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_12018.25
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000332, Royal Society of Edinburgh;
                Award ID: Scottish Government Fellowship cofunded by Marie Curie Actions
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000582, Carnegie Trust for the Universities of Scotland;
                Award ID: 50115
                Award Recipient :
                Funded by: Institute of Genetics and Molecular Medicine Development and Translation Fund
                Funded by: FundRef http://dx.doi.org/10.13039/501100000589, Chief Scientist Office;
                Award ID: ETM37
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000289, Cancer Research UK;
                Award ID: Experimental Medicine Centre
                Award Recipient :
                Funded by: Renal Cancer Research Fund
                Funded by: Kidney Cancer Scotland
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: Clinical Training Fellowship
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000692, Royal College of Surgeons of Edinburgh;
                Award ID: Robertson Trust
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100001237, Melville Charitable Trust;
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Medicine
                cancer,tumour heterogeneity,prognostic markers,renal cell carcinoma,tumour biomarkers
                Medicine
                cancer, tumour heterogeneity, prognostic markers, renal cell carcinoma, tumour biomarkers

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