Evidence mapPaperPMID 40404206Full record

ArticleJournal for immunotherapy of cancer2025

Development and validation of a serum proteomic test for predicting patient outcomes in advanced non-small cell lung cancer treated with atezolizumab or docetaxel.

Minu K Srivastava, Wei Zou, Mark McCleland, Joanna Roder, Senait Asmellash, Patrick Norman, Lelia Net, Laura Maguire, Heinrich Roder, Robert Georgantas and 1 more

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Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Minu K SrivastavaTranslational Medicine, Genentech, South San Francisco, California, USA srivasm3@gene.com.ORCID http://orcid.org/0009-0000-3827-9180
Wei ZouDepartment of Biostatistics Oncology, Genentech, South San Francisco, California, USA.
Mark McClelandGenentech, South San Francisco, California, USA.
Joanna RoderBiodesix, Boulder, Colorado, USA.
Senait AsmellashBiodesix, Boulder, Colorado, USA.
Patrick NormanBiodesix, Boulder, Colorado, USA.
Lelia NetBiodesix, Boulder, Colorado, USA.
Laura MaguireBiodesix, Boulder, Colorado, USA.
Heinrich RoderBiodesix, Boulder, Colorado, USA.
Robert GeorgantasBiodesix, Boulder, Colorado, USA.
David S ShamesGenentech, South San Francisco, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProgrammed cell death-ligand 1 (PD-L1) expression is used in treatment decision-making for patients with advanced non-small cell lung cancer, determining if immune checkpoint inhibitors (ICI) are recommended. Patient selection for ICI treatment can be improved by incorporating the host response. We developed and carried out multiple independent validations of a blood-based test designed to stratify outcomes for patients treated with atezolizumab.

methodsA mass spectrometry-based test was developed from a cohort of patients treated with atezolizumab and validated in two clinical trials (n=269, 823) comparing atezolizumab with docetaxel. The test classifies patients as Good or Poor indicating better or worse outcomes, respectively. The prognostic and predictive power of the test was assessed and evaluated within PD-L1 subgroups. Protein enrichment methods were used to investigate the association of test classification with biological processes.

resultsApproximately 50% of patients were assigned to each classification in all three cohorts. When treated with atezolizumab, the Good subgroup had superior outcomes in all cohorts. Overall survival (OS) HR (95% CI) for Good patients in each cohort was: 0.23 (0.12 to 0.44), 0.32 (0.21 to 0.51), and 0.52 (0.41 to 0.66) and persisted in all PD-L1 subgroups. The test was predictive of differential OS and progression-free survival in one cohort, but not in the other. Enrichment techniques indicated the test was associated with acute inflammatory response, acute phase response, and complement activation.

conclusionsAspects of host immune response to disease can be assessed from the circulating proteome and provide outcome stratification for patients treated with atezolizumab. Combining this information with PD-L1 measurements improves prediction of outcomes.

Indexed as

Antibodies, Monoclonal, HumanizedBiomarkers, TumorCarcinoma, Non-Small-Cell LungDocetaxelLung NeoplasmsProteomicsAgedFemaleHumansMaleMiddle AgedPrognosisTreatment OutcomeAntibodies, Monoclonal, HumanizedatezolizumabBiomarkers, TumorDocetaxelBiomarkerImmune Checkpoint InhibitorImmunotherapyLung Cancer

Identifiers

PMID40404206
PMCPMC12096988

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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 Socratic graph.