Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Comprehensive analysis of potential immunotherapy genomic biomarkers in 1,000 Chinese patients with cancer

Shunchang Jiao, Yuansheng Zang, Chun Dai, Xiaoman Xu, Xin Cai, Guan Wang, Jinwang Wei, Angela Wu, Wending Sun, Qiang Xu
doi: https://doi.org/10.1101/366062
Shunchang Jiao
1Department of Medical Oncology, Chinese PLA General Hospital, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yuansheng Zang
2Department of Oncology, Shanghai Changzheng Hospital, Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chun Dai
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiaoman Xu
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xin Cai
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Guan Wang
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jinwang Wei
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Angela Wu
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wending Sun
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Qiang Xu
3GenomiCare Biotechnology Co. Ltd., Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: Qiang.Xu@genomicarebio.com
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Background Tumor mutation burden (TMB), DNA mismatch repair deficiency (dMMR), microsatellite instability (MSI), and PD-L1 amplification (PD-L1 AMP) may predict the efficacy of PD-1/PD-L1 blockade. In this study, we aimed to characterize the distributions of these biomarkers in over 1,000 Chinese patients with cancer.

Methods TMB, MSI, dMMR, and PD-L1 AMP were determined based on whole-exome sequencing of tumor/blood samples from > 1,000 Chinese patients with cancer.

Results Incidence rates among 953 Chinese patients with cancer showing high TMB (TMB-H), high MSI (MSI-H), dMMR and PD-L1 AMP were 35%, 4%, 0.53% and 3.79%, respectively. We found higher rates of TMB-H among hepatocellular carcinoma, breast cancer, and esophageal cancer patients than was reported for The Cancer Genome Atlas data. Lung cancer patients with EGFR mutations had significantly lower TMB values than those with wild-type EGFR, and increased TMB was significantly associated with dMMR in colorectal cancer (CRC). The frequency of tumors with MSI-H was highest in CRC (14%) and gastric cancer (4%). PD-L1 AMP occurred most frequently in lung squamous cell carcinoma (14.3%) and HER2-positive breast cancer (8.8%). Most MSI-H and dMMR cases exhibited TMB-H, but the overlap among the other biomarkers was low.

Conclusion While MSI and dMMR are associated with higher mutational loads, correlations between TMB-H and other biomarkers, between MSI-H and dMMR, and between PD-L1 AMP and other biomarkers were low, indicating different underlying causes of the four biomarkers. Thus, it is recommended that all four biomarkers be assessed for certain cancers before administration of PD-1/PD-L1 blockade treatment.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted July 12, 2018.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Comprehensive analysis of potential immunotherapy genomic biomarkers in 1,000 Chinese patients with cancer
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Comprehensive analysis of potential immunotherapy genomic biomarkers in 1,000 Chinese patients with cancer
Shunchang Jiao, Yuansheng Zang, Chun Dai, Xiaoman Xu, Xin Cai, Guan Wang, Jinwang Wei, Angela Wu, Wending Sun, Qiang Xu
bioRxiv 366062; doi: https://doi.org/10.1101/366062
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Comprehensive analysis of potential immunotherapy genomic biomarkers in 1,000 Chinese patients with cancer
Shunchang Jiao, Yuansheng Zang, Chun Dai, Xiaoman Xu, Xin Cai, Guan Wang, Jinwang Wei, Angela Wu, Wending Sun, Qiang Xu
bioRxiv 366062; doi: https://doi.org/10.1101/366062

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Cancer Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3602)
  • Biochemistry (7570)
  • Bioengineering (5524)
  • Bioinformatics (20792)
  • Biophysics (10329)
  • Cancer Biology (7984)
  • Cell Biology (11640)
  • Clinical Trials (138)
  • Developmental Biology (6603)
  • Ecology (10202)
  • Epidemiology (2065)
  • Evolutionary Biology (13617)
  • Genetics (9541)
  • Genomics (12847)
  • Immunology (7921)
  • Microbiology (19541)
  • Molecular Biology (7658)
  • Neuroscience (42097)
  • Paleontology (308)
  • Pathology (1258)
  • Pharmacology and Toxicology (2202)
  • Physiology (3267)
  • Plant Biology (7041)
  • Scientific Communication and Education (1294)
  • Synthetic Biology (1951)
  • Systems Biology (5426)
  • Zoology (1117)