Evidence map›Paper›PMID 38088895›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2024

A Dysfunctional T-cell Gene Signature for Predicting Nonresponse to PD-1 Blockade in Non-small Cell Lung Cancer That Is Suitable for Routine Clinical Diagnostics.

Karlijn Hummelink, Renaud Tissier, Linda J W Bosch, Oscar Krijgsman, Michel M van den Heuvel, Willemijn S M E Theelen, Diane Damotte, François Goldwasser, Karen Leroy, Egbert F Smit and 3 more

Abstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Karlijn HummelinkDepartment of Pathology, Division of Diagnostic Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0003-4371-8904
Renaud TissierBiostatistics Unit, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0002-9665-883X
Linda J W BoschDepartment of Pathology, Division of Diagnostic Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0001-6323-9316
Oscar KrijgsmanDivision of Molecular Oncology and Immunology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0003-0825-3291
Michel M van den HeuvelDepartment of Thoracic Oncology, Division of Medical Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0002-6372-2153
Willemijn S M E TheelenDepartment of Thoracic Oncology, Division of Medical Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0001-9772-0511
Diane DamotteTeam Cancer, Immune Control and Escape, Cordeliers Research Center, UMRS 1138, Institut National de la Santé et de la Recherche Médicale (INSERM), Paris, France.ORCID 0000-0001-5355-3045
François GoldwasserUniversity Paris Cité, Paris, France.ORCID 0000-0002-7128-6128
Karen LeroyTeam Cancer, Immune Control and Escape, Cordeliers Research Center, UMRS 1138, Institut National de la Santé et de la Recherche Médicale (INSERM), Paris, France.ORCID 0000-0002-4379-0140
Egbert F SmitDepartment of Thoracic Oncology, Division of Medical Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0002-7329-6995
Gerrit A Meijer *Department of Pathology, Division of Diagnostic Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0003-0330-3130
Daniela S Thommen *Division of Molecular Oncology and Immunology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0002-7431-2854
Kim Monkhorst *Department of Pathology, Division of Diagnostic Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID 0000-0002-8690-3811

Funding

Dutch Ministry of Health, Welfare and SportKWF Kankerbestrijding (DCS)KWF Kankerbestrijding (DCS) 12046
6 · The paper itself

Abstract

purposeBecause PD-1 blockade is only effective in a minority of patients with advanced-stage non-small cell lung cancer (NSCLC), biomarkers are needed to guide treatment decisions. Tumor infiltration by PD-1T tumor-infiltrating lymphocytes (TIL), a dysfunctional TIL pool with tumor-reactive capacity, can be detected by digital quantitative IHC and has been established as a novel predictive biomarker in NSCLC. To facilitate translation of this biomarker to the clinic, we aimed to develop a robust RNA signature reflecting a tumor's PD-1T TIL status. EXPERIMENTAL

designmRNA expression analysis using the NanoString nCounter platform was performed in baseline tumor samples from 41 patients with advanced-stage NSCLC treated with nivolumab that were selected on the basis of PD-1T TIL infiltration by IHC. Samples were included as a training cohort (n = 41) to develop a predictive gene signature. This signature was independently validated in a second cohort (n = 42). Primary outcome was disease control at 12 months (DC 12 m), and secondary outcome was progression-free and overall survival.

resultsRegularized regression analysis yielded a signature using 12 out of 56 differentially expressed genes between PD-1T IHC-high tumors from patients with DC 12 m and PD-1T IHC-low tumors from patients with progressive disease (PD). In the validation cohort, 6/6 (100%) patients with DC 12 m and 23/36 (64%) with PD were correctly classified with a negative predictive value (NPV) of 100% and a positive predictive value of 32%.

conclusionsThe PD-1T mRNA signature showed a similar high sensitivity and high NPV as the digital IHC quantification of PD-1T TIL. This finding provides a straightforward approach allowing for easy implementation in a routine diagnostic clinical setting.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsB7-H1 AntigenHumansLymphocytes, Tumor-InfiltratingProgrammed Cell Death 1 ReceptorRNA, MessengerTreatment OutcomeB7-H1 AntigenProgrammed Cell Death 1 ReceptorRNA, Messenger

Identifiers

PMID38088895
PMCPMC10870113

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Registered trials

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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.