Computational Image Analysis of T-Cell Infiltrates in Resectable Gastric Cancer: Association with Survival and Molecular Subtypes.


Journal

Journal of the National Cancer Institute
ISSN: 1460-2105
Titre abrégé: J Natl Cancer Inst
Pays: United States
ID NLM: 7503089

Informations de publication

Date de publication:
04 01 2021
Historique:
received: 23 12 2019
revised: 05 03 2020
accepted: 02 04 2020
pubmed: 24 4 2020
medline: 22 6 2021
entrez: 24 4 2020
Statut: ppublish

Résumé

Gastric and gastro-esophageal junction cancers (GCs) frequently recur after resection, but markers to predict recurrence risk are missing. T-cell infiltrates have been validated as prognostic markers in other cancer types, but not in GC because of methodological limitations of past studies. We aimed to define and validate the prognostic role of major T-cell subtypes in GC by objective computational quantification. Surgically resected chemotherapy-naïve GCs were split into discovery (n = 327) and validation (n = 147) cohorts. CD8 (cytotoxic), CD45RO (memory), and FOXP3 (regulatory) T-cell densities were measured through multicolor immunofluorescence and computational image analysis. Cancer-specific survival (CSS) was assessed. All statistical tests were two-sided. CD45RO-cell and FOXP3-cell densities statistically significantly predicted CSS in both cohorts. Stage, CD45RO-cell, and FOXP3-cell densities were independent predictors of CSS in multivariable analysis; mismatch repair (MMR) and Epstein-Barr virus (EBV) status were not statistically significant. Combining CD45RO-cell and FOXP3-cell densities into the Stomach Cancer Immune Score showed highly statistically significant (all P ≤ .002) CSS differences (0.9 years median CSS to not reached). T-cell infiltrates were highest in EBV-positive GCs and similar in MMR-deficient and MMR-proficient GCs. The validation of CD45RO-cell and FOXP3-cell densities as prognostic markers in GC may guide personalized follow-up or (neo)adjuvant treatment strategies. Only those 20% of GCs with the highest T-cell infiltrates showed particularly good CSS, suggesting that a small subgroup of GCs is highly immunogenic. The potential for T-cell densities to predict immunotherapy responses should be assessed. The association of high FOXP3-cell densities with longer CSS warrants studies into the biology of regulatory T cells in GC.

Sections du résumé

BACKGROUND
Gastric and gastro-esophageal junction cancers (GCs) frequently recur after resection, but markers to predict recurrence risk are missing. T-cell infiltrates have been validated as prognostic markers in other cancer types, but not in GC because of methodological limitations of past studies. We aimed to define and validate the prognostic role of major T-cell subtypes in GC by objective computational quantification.
METHODS
Surgically resected chemotherapy-naïve GCs were split into discovery (n = 327) and validation (n = 147) cohorts. CD8 (cytotoxic), CD45RO (memory), and FOXP3 (regulatory) T-cell densities were measured through multicolor immunofluorescence and computational image analysis. Cancer-specific survival (CSS) was assessed. All statistical tests were two-sided.
RESULTS
CD45RO-cell and FOXP3-cell densities statistically significantly predicted CSS in both cohorts. Stage, CD45RO-cell, and FOXP3-cell densities were independent predictors of CSS in multivariable analysis; mismatch repair (MMR) and Epstein-Barr virus (EBV) status were not statistically significant. Combining CD45RO-cell and FOXP3-cell densities into the Stomach Cancer Immune Score showed highly statistically significant (all P ≤ .002) CSS differences (0.9 years median CSS to not reached). T-cell infiltrates were highest in EBV-positive GCs and similar in MMR-deficient and MMR-proficient GCs.
CONCLUSION
The validation of CD45RO-cell and FOXP3-cell densities as prognostic markers in GC may guide personalized follow-up or (neo)adjuvant treatment strategies. Only those 20% of GCs with the highest T-cell infiltrates showed particularly good CSS, suggesting that a small subgroup of GCs is highly immunogenic. The potential for T-cell densities to predict immunotherapy responses should be assessed. The association of high FOXP3-cell densities with longer CSS warrants studies into the biology of regulatory T cells in GC.

Identifiants

pubmed: 32324860
pii: 5824301
doi: 10.1093/jnci/djaa051
pmc: PMC7781469
doi:

Substances chimiques

CD8 Antigens 0
FOXP3 protein, human 0
Forkhead Transcription Factors 0
Leukocyte Common Antigens EC 3.1.3.48

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

88-98

Subventions

Organisme : Cancer Research UK
Pays : United Kingdom

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press.

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Auteurs

Benjamin R Challoner (BR)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

Katharina von Loga (K)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.
Translational Immuno-Oncology Team, Centre for Molecular Pathology, The Royal Marsden Hospital NHS Foundation Trust and The Institute of Cancer Research, Sutton, UK.

Andrew Woolston (A)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

Beatrice Griffiths (B)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

Nanna Sivamanoharan (N)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.
Translational Immuno-Oncology Team, Centre for Molecular Pathology, The Royal Marsden Hospital NHS Foundation Trust and The Institute of Cancer Research, Sutton, UK.

Maria Semiannikova (M)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

Alice Newey (A)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

Louise J Barber (LJ)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

David Mansfield (D)

Targeted Therapy Team, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.

Lindsay C Hewitt (LC)

Department of Pathology, Maastricht University Medical Center, Limburg, The Netherlands.

Yuichi Saito (Y)

Department of Surgery, Teikyo University School of Medicine, Tokyo, Japan.

Naser Davarzani (N)

Department of Pathology, Maastricht University Medical Center, Limburg, The Netherlands.
Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.

Naureen Starling (N)

Gastrointestinal Cancer Unit, The Royal Marsden Hospital NHS Foundation Trust, London, UK.

Alan Melcher (A)

Translational Immunotherapy Team, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.

Heike I Grabsch (HI)

Department of Pathology, Maastricht University Medical Center, Limburg, The Netherlands.
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, St James's University Hospital, Leeds, UK.

Marco Gerlinger (M)

Translational Oncogenomics Laboratory, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.
Gastrointestinal Cancer Unit, The Royal Marsden Hospital NHS Foundation Trust, London, UK.

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