Literature DB >> 32591823

Histological intratumoral heterogeneity in pretreatment esophageal cancer biopsies predicts survival benefit from neoadjuvant chemotherapy: results from the UK MRC OE02 trial.

Naser Davarzani1,2, Lindsay C Hewitt1,3, Matthew D Hale3, Veerle Melotte1,4, Matthew Nankivell5, Gordon G A Hutchins3, David Cunningham6, William H Allum7, Ruth E Langley5, Shahab Jolani8, Heike I Grabsch1,3.   

Abstract

Despite the use of multimodal treatment, survival of esophageal cancer (EC) patients remains poor. One proposed explanation for the relatively poor response to cytotoxic chemotherapy is intratumor heterogeneity. The aim was to establish a statistical model to objectively measure intratumor heterogeneity of the proportion of tumor (IHPoT) and to use this newly developed method to measure IHPoT in the pretreatment biopsies from from EC patients recruited to the OE02 trial. A statistical mixed effect model (MEM) was established for estimating IHPoT based on variation in hematoxylin/eosin (HE) stained pretreatment biopsy pieces from the same individual in 218 OE02 trial patients (103 treated by chemotherapy and surgery (chemo+surgery); 115 patients treated by surgery alone). The relationship between IHPoT, prognosis, chemotherapy survival benefit, and clinicopathological variables was assessed. About 97 (44.5%) and 121 (55.5%) ECs showed high and low IHPoT, respectively. There was no significant difference in IHPoT between surgery (median [range], 0.1637 [0-3.17]) and chemo+surgery (median [range], 0.1692 [0-2.69]) patients (P = 0.43). Chemo+surgery patients with low IHPoT had a significantly longer survival than surgery patients (HR = 1.81, 95% CI: 1.20-2.75, P = 0.005). There was no survival difference between chemo+surgery and surgery patients with high IHPoT (HR = 1.15, 95% CI: 0.72-1.81, P = 0.566). This is the first study suggesting that IHPoT measured in the pretreatment biopsy can predict chemotherapy survival benefit in EC patients. IHPoT may represent a clinically useful biomarker for patient treatment stratification. Future studies should determine if pathologists can reliably estimate IHPoT.
© The Author(s) 2020. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  esophageal cancer; histological heterogeneity; neoadjuvant chemotherapy; pretreatment biopsy; proportion of tumor

Year:  2020        PMID: 32591823     DOI: 10.1093/dote/doaa058

Source DB:  PubMed          Journal:  Dis Esophagus        ISSN: 1120-8694            Impact factor:   3.429


  23 in total

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Authors:  Ariel Pribluda; Cecile C de la Cruz; Erica L Jackson
Journal:  Clin Cancer Res       Date:  2015-04-02       Impact factor: 12.531

2.  Evaluating significance in linear mixed-effects models in R.

Authors:  Steven G Luke
Journal:  Behav Res Methods       Date:  2017-08

3.  Genetic clonal diversity predicts progression to esophageal adenocarcinoma.

Authors:  Carlo C Maley; Patricia C Galipeau; Jennifer C Finley; V Jon Wongsurawat; Xiaohong Li; Carissa A Sanchez; Thomas G Paulson; Patricia L Blount; Rosa-Ana Risques; Peter S Rabinovitch; Brian J Reid
Journal:  Nat Genet       Date:  2006-03-26       Impact factor: 38.330

4.  A comprehensive survey of clonal diversity measures in Barrett's esophagus as biomarkers of progression to esophageal adenocarcinoma.

Authors:  Lauren M F Merlo; Najaf A Shah; Xiaohong Li; Patricia L Blount; Thomas L Vaughan; Brian J Reid; Carlo C Maley
Journal:  Cancer Prev Res (Phila)       Date:  2010-10-12

5.  Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma.

Authors:  Eirini Pectasides; Matthew D Stachler; Sarah Derks; Yang Liu; Steven Maron; Adam J Bass; Daniel V Catenacci; Mirazul Islam; Lindsay Alpert; Heewon Kwak; Hedy Kindler; Blase Polite; Manish R Sharma; Kenisha Allen; Emily O'Day; Samantha Lomnicki; Melissa Maranto; Rajani Kanteti; Carrie Fitzpatrick; Christopher Weber; Namrata Setia; Shu-Yuan Xiao; John Hart; Rebecca J Nagy; Kyoung-Mee Kim; Min-Gew Choi; Byung-Hoon Min; Katie S Nason; Lea O'Keefe; Masayuki Watanabe; Hideo Baba; Rick Lanman; Agoston T Agoston; David J Oh; Andrew Dunford; Aaron R Thorner; Matthew D Ducar; Bruce M Wollison; Haley A Coleman; Yuan Ji; Mitchell C Posner; Kevin Roggin; Kiran Turaga; Paul Chang; Kyle Hogarth; Uzma Siddiqui; Andres Gelrud; Gavin Ha; Samuel S Freeman; Justin Rhoades; Sarah Reed; Greg Gydush; Denisse Rotem; Jon Davison; Yu Imamura; Viktor Adalsteinsson; Jeeyun Lee
Journal:  Cancer Discov       Date:  2017-10-04       Impact factor: 39.397

6.  Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.

Authors:  Freddie Bray; Jacques Ferlay; Isabelle Soerjomataram; Rebecca L Siegel; Lindsey A Torre; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2018-09-12       Impact factor: 508.702

7.  Whole-genome sequencing provides new insights into the clonal architecture of Barrett's esophagus and esophageal adenocarcinoma.

Authors:  Caryn S Ross-Innes; Jennifer Becq; Andrew Warren; R Keira Cheetham; Helen Northen; Maria O'Donovan; Shalini Malhotra; Massimiliano di Pietro; Sergii Ivakhno; Miao He; Jamie M J Weaver; Andy G Lynch; Zoya Kingsbury; Mark Ross; Sean Humphray; David Bentley; Rebecca C Fitzgerald
Journal:  Nat Genet       Date:  2015-07-20       Impact factor: 38.330

8.  Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma.

Authors:  Jia-Jie Hao; De-Chen Lin; Huy Q Dinh; Anand Mayakonda; Yan-Yi Jiang; Chen Chang; Ye Jiang; Chen-Chen Lu; Zhi-Zhou Shi; Xin Xu; Yu Zhang; Yan Cai; Jin-Wu Wang; Qi-Min Zhan; Wen-Qiang Wei; Benjamin P Berman; Ming-Rong Wang; H Phillip Koeffler
Journal:  Nat Genet       Date:  2016-10-17       Impact factor: 38.330

9.  Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning.

Authors:  Nicolas Coudray; Paolo Santiago Ocampo; Theodore Sakellaropoulos; Navneet Narula; Matija Snuderl; David Fenyö; Andre L Moreira; Narges Razavian; Aristotelis Tsirigos
Journal:  Nat Med       Date:  2018-09-17       Impact factor: 53.440

10.  Multiple region whole-exome sequencing reveals dramatically evolving intratumor genomic heterogeneity in esophageal squamous cell carcinoma.

Authors:  W Cao; W Wu; M Yan; F Tian; C Ma; Q Zhang; X Li; P Han; Z Liu; J Gu; F G Biddle
Journal:  Oncogenesis       Date:  2015-11-30       Impact factor: 7.485

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