Evidence map›Paper›PMID 35017155›Full record

ArticleJournal for immunotherapy of cancer2022

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

Francois Bertucci, Vincent Niziers, Alexandre de Nonneville, Pascal Finetti, Léna Mescam, Olivier Mir, Antoine Italiano, Axel Le Cesne, Jean-Yves Blay, Michele Ceccarelli and 3 more

Open access · goldAbstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 40 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 7 institutions in 5 countries.

Francois BertucciLaboratory 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.
Vincent Niziers *Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.ORCID 0000-0001-9627-7335
Alexandre de Nonneville *Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.
Pascal Finetti *Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.ORCID 0000-0002-2674-3123
Léna MescamFrench Sarcoma Group, Lyon, France.
Olivier MirFrench Sarcoma Group, Lyon, France.
Antoine ItalianoFrench Sarcoma Group, Lyon, France.ORCID 0000-0002-8540-5351
Axel Le CesneFrench Sarcoma Group, Lyon, France.
Jean-Yves BlayFrench Sarcoma Group, Lyon, France.ORCID 0000-0001-7190-120X
Michele CeccarelliDIETI, University of Naples Federico II Faculty of Engineering, Naples, Italy.
Davide BedognettiCancer Research, Sidra Medicine, Doha, Qatar.
Daniel BirnbaumLaboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.
Emilie MamessierLaboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille (CRCM), Institut Paoli-Calmettes, Aix-Marseille Université, INSERM UMR1068, CNRS UMR725, Marseille, France.
Centre National de la Recherche Scientifique · FRInstitut Gustave Roussy · FRCentre Léon Bérard · FRInstitut Bergonié · FRInstitut Paoli-Calmettes · FRQatar Airways (Qatar) · QAUniversity of Naples Federico II · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSoft-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.

methodsWe 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).

resultsThirty-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.

conclusionICR 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.

Indexed as

Biomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisSarcomaBiomarkers, Tumorgene expression profilingsarcoma

Identifiers

PMID35017155
PMCPMC8753443
OpenAlexW4205297406

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.