Integrated genomic profiling and modelling for risk stratification in patients with advanced oesophagogastric adenocarcinoma

Abstract

Prognosis of patients with advanced oesophagogastric adenocarcinoma (mEGAC) is poor and molecular determinants of shorter or longer overall survivors are lacking. Our objective was to identify molecular features and develop a prognostic model by profiling the genomic features of patients with mEGAC with widely varying outcomes.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 17, 2020
Source ID
10.1136/gutjnl-2020-322707

Entities

People

  • Ahmed Abdelhakeem
  • Brian Weston
  • Dapeng Hao
  • George A. Calin
  • Guang Peng
  • Guangchun Han
  • Jaffer Ajani
  • Jeannelyn Santiano Estrella
  • Jeffrey H. Lee
  • Jianhua Zhang
  • Ju-Seog Lee
  • Kazuto Harada
  • Linghua Wang
  • Lu Chen
  • Manoop Bhutani
  • Mariela Blum Murphy
  • Matheus Sewastjanow-Silva
  • Melissa Pool Pizzi
  • Namita Shanbhag
  • Pujun Guan
  • Qiong Gan
  • Rebecca Waters
  • Ruiping Wang
  • Samir M Hanash
  • Shaojun Zhang
  • Shuangtao Zhao
  • Shumei Song
  • Sinchita Roy-chowdhuri
  • Siyuan He
  • Xingzhi Song
  • Yang Lu

Organizations

  • Center for Strategic Scientific Initiatives, National Cancer Institute
  • United States Department of Defense

Tags

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Oncology and Biomarker-Based Cancer Detection.