Prediction Model for Gastric Cancer With DNA Mismatch Repair Deficiency.


Journal

Anticancer research
ISSN: 1791-7530
Titre abrégé: Anticancer Res
Pays: Greece
ID NLM: 8102988

Informations de publication

Date de publication:
Feb 2021
Historique:
received: 10 12 2020
revised: 22 12 2020
accepted: 11 01 2021
entrez: 31 1 2021
pubmed: 1 2 2021
medline: 7 2 2021
Statut: ppublish

Résumé

DNA mismatch repair (MMR) deficiency has received increasing attention as a biomarker of anti-PD-1 treatments of solid tumors including gastric cancer (GC). However, efficient screening has not been established. A total of 513 patients were tested for the expression of MMR proteins by immunohistochemistry to identify MMR deficient GC. Development of a prediction model was attempted using the common clinicopathological features. In total, 11% (57/513) of the patients showed loss of expression of either one or more MMR proteins (MMR protein deficiency; MMR-D). Multivariate analysis demonstrated that age (≥70 years), sex (female), tumor location (lower 1/3), depth invasion (low, T1/T2/T3), and absence of distant metastasis were significantly independent predictive factors of MMR-D GCs. The MMR-D GC probability estimated by the prediction model ranged from 0.4% to 62.2%, and the area under the curve of the receiver operating characteristics curve was 0.82 (95% confidence interval=0.75-0.87). Our prediction model can sufficiently and efficiently identify MMR-D GCs using clinical features.

Sections du résumé

BACKGROUND/AIM OBJECTIVE
DNA mismatch repair (MMR) deficiency has received increasing attention as a biomarker of anti-PD-1 treatments of solid tumors including gastric cancer (GC). However, efficient screening has not been established.
PATIENTS AND METHODS METHODS
A total of 513 patients were tested for the expression of MMR proteins by immunohistochemistry to identify MMR deficient GC. Development of a prediction model was attempted using the common clinicopathological features.
RESULTS RESULTS
In total, 11% (57/513) of the patients showed loss of expression of either one or more MMR proteins (MMR protein deficiency; MMR-D). Multivariate analysis demonstrated that age (≥70 years), sex (female), tumor location (lower 1/3), depth invasion (low, T1/T2/T3), and absence of distant metastasis were significantly independent predictive factors of MMR-D GCs. The MMR-D GC probability estimated by the prediction model ranged from 0.4% to 62.2%, and the area under the curve of the receiver operating characteristics curve was 0.82 (95% confidence interval=0.75-0.87).
CONCLUSION CONCLUSIONS
Our prediction model can sufficiently and efficiently identify MMR-D GCs using clinical features.

Identifiants

pubmed: 33517304
pii: 41/2/975
doi: 10.21873/anticanres.14851
doi:

Substances chimiques

Biomarkers, Tumor 0
DNA-Binding Proteins 0
G-T mismatch-binding protein 0
MLH1 protein, human 0
PMS2 protein, human EC 3.6.1.-
Mismatch Repair Endonuclease PMS2 EC 3.6.1.3
MutL Protein Homolog 1 EC 3.6.1.3

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

975-982

Informations de copyright

Copyright © 2021 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Auteurs

Okihide Suzuki (O)

Department of Digestive Tract and General Surgery, Saitama Medical Center, Saitama Medical University, Saitama, Japan; osuzu@saitamamed.ac.jp.

Tatsuro Yamaguchi (T)

Department of Surgery, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan.
Department of Clinical Genetics, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan.

Minoru Fukuchi (M)

Department of Digestive Tract and General Surgery, Saitama Medical Center, Saitama Medical University, Saitama, Japan.

Erito Mochiki (E)

Department of Digestive Tract and General Surgery, Saitama Medical Center, Saitama Medical University, Saitama, Japan.

Tomio Arai (T)

Department of Pathology, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan.

Kiwamu Akagi (K)

Division of Molecular Diagnosis and Cancer Prevention, Saitama Cancer Center, Saitama, Japan.

Hideyuki Ishida (H)

Department of Digestive Tract and General Surgery, Saitama Medical Center, Saitama Medical University, Saitama, Japan.

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Classifications MeSH