Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature.


Journal

Journal for immunotherapy of cancer
ISSN: 2051-1426
Titre abrégé: J Immunother Cancer
Pays: England
ID NLM: 101620585

Informations de publication

Date de publication:
01 2022
Historique:
accepted: 01 11 2021
entrez: 12 1 2022
pubmed: 13 1 2022
medline: 17 3 2022
Statut: ppublish

Résumé

Soft-tissue sarcomas (STSs) are heterogeneous and aggressive tumors, with high metastatic risk. The immunologic constant of rejection (ICR) 20-gene signature is a signature of cytotoxic immune response. We hypothesized that ICR might improve the prognostic assessment of early-stage STS. We retrospectively applied ICR to 1455 non-metastatic STS and searched for correlations between ICR classes and clinicopathological and biological variables, including metastasis-free survival (MFS). Thirty-four per cent of tumors were classified as ICR1, 27% ICR2, 24% ICR3, and 15% ICR4. These classes were associated with patients' age, pathological type, and tumor depth, and an enrichment from ICR1 to ICR4 of quantitative/qualitative scores of immune response. ICR1 class was associated with a 59% increased risk of metastatic relapse when compared with ICR2-4 class. In multivariate analysis, ICR classification remained associated with MFS, as well as pathological type and Complexity Index in Sarcomas (CINSARC) classification, suggesting independent prognostic value. A prognostic clinicogenomic model, including the three variables, was built in a learning set (n=339) and validated in an independent set (n=339), showing greater prognostic precision than each variable alone or in doublet. Finally, connectivity mapping analysis identified drug classes potentially able to reverse the expression profile of poor-prognosis tumors, such as chemotherapy and targeted therapies. ICR signature is independently associated with postoperative MFS in early-stage STS, independently from other prognostic features, including CINSARC. We built a robust prognostic clinicogenomic model integrating ICR, CINSARC, and pathological type, and suggested differential vulnerability of each prognostic group to different systemic therapies.

Sections du résumé

BACKGROUND
Soft-tissue sarcomas (STSs) are heterogeneous and aggressive tumors, with high metastatic risk. The immunologic constant of rejection (ICR) 20-gene signature is a signature of cytotoxic immune response. We hypothesized that ICR might improve the prognostic assessment of early-stage STS.
METHODS
We retrospectively applied ICR to 1455 non-metastatic STS and searched for correlations between ICR classes and clinicopathological and biological variables, including metastasis-free survival (MFS).
RESULTS
Thirty-four per cent of tumors were classified as ICR1, 27% ICR2, 24% ICR3, and 15% ICR4. These classes were associated with patients' age, pathological type, and tumor depth, and an enrichment from ICR1 to ICR4 of quantitative/qualitative scores of immune response. ICR1 class was associated with a 59% increased risk of metastatic relapse when compared with ICR2-4 class. In multivariate analysis, ICR classification remained associated with MFS, as well as pathological type and Complexity Index in Sarcomas (CINSARC) classification, suggesting independent prognostic value. A prognostic clinicogenomic model, including the three variables, was built in a learning set (n=339) and validated in an independent set (n=339), showing greater prognostic precision than each variable alone or in doublet. Finally, connectivity mapping analysis identified drug classes potentially able to reverse the expression profile of poor-prognosis tumors, such as chemotherapy and targeted therapies.
CONCLUSION
ICR signature is independently associated with postoperative MFS in early-stage STS, independently from other prognostic features, including CINSARC. We built a robust prognostic clinicogenomic model integrating ICR, CINSARC, and pathological type, and suggested differential vulnerability of each prognostic group to different systemic therapies.

Identifiants

pubmed: 35017155
pii: jitc-2021-003687
doi: 10.1136/jitc-2021-003687
pmc: PMC8753443
pii:
doi:

Substances chimiques

Biomarkers, Tumor 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Francois Bertucci (F)

Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France bertuccif@ipc.unicancer.fr.
Department of Medical Oncology, Institut Paoli-Calmettes, Marseille, France.
French Sarcoma Group, Lyon, France.

Vincent Niziers (V)

Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.
Department of Surgery, Institut Paoli-Calmettes, Marseille, France.

Alexandre de Nonneville (A)

Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.
Department of Medical Oncology, Institut Paoli-Calmettes, Marseille, France.

Pascal Finetti (P)

Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.

Léna Mescam (L)

French Sarcoma Group, Lyon, France.
Department of Pathology, Institut Paoli-Calmettes, Marseille, France.

Olivier Mir (O)

French Sarcoma Group, Lyon, France.
Department of Medical Oncology, Gustave Roussy, Villejuif, France.

Antoine Italiano (A)

French Sarcoma Group, Lyon, France.
Department of Medical Oncology, Institut Bergonie, Bordeaux, France.

Axel Le Cesne (A)

French Sarcoma Group, Lyon, France.
Department of Medical Oncology, Gustave Roussy, Villejuif, France.

Jean-Yves Blay (JY)

French Sarcoma Group, Lyon, France.
Department of Medical Oncology, Centre Leon Berard, Lyon, France.

Michele Ceccarelli (M)

DIETI, University of Naples Federico II Faculty of Engineering, Naples, Italy.

Davide Bedognetti (D)

Cancer Research, Sidra Medicine, Doha, Qatar.
Department of Internal Medicine and Medical Specialties, University of Genova, Genova, Italy.

Daniel Birnbaum (D)

Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.

Emilie Mamessier (E)

Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.

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