Evidence map›Paper›PMID 41708895›Full record

Trial reportNature cancer2026

Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition in metastatic TNBC.

Noah F Greenwald, Iris Nederlof, Cameron Sowers, Daisy Yi Ding, Seongyeol Park, Alex Kong, Kathleen E Houlahan, Sricharan Reddy Varra, Manon de Graaf, Veerle Geurts and 28 more

Abstract readAdaptive Clinical TrialClinical Trial, Phase II
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Nature cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  7. An update on spatial proteomics.Nature methods · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

38 authors.

Noah F Greenwald *Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-7836-4379
Iris Nederlof *Division of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0001-7608-6515
Cameron SowersDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Daisy Yi DingDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
Seongyeol ParkStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-9236-5853
Alex KongDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Kathleen E HoulahanStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-2273-2099
Sricharan Reddy VarraDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0009-0000-5757-6818
Manon de GraafDivision of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
Veerle GeurtsDivision of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
Candace C LiuDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Jolene S RanekDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-0701-0565
Leonie VoorwerkDivision of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
Michiel de MaakerMolecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
Adam KagelDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Erin McCaffreyDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Aziz KhanStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-6459-6224
Christine Yiwen YehDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-4217-8555
Christine Camacho FullawayDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-4924-591X
Zumana KhairDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Brennan G SimonCancer Biology Program, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-7255-2766
Yunhao BaiDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Hadeesha PiyadasaDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Tyler RisomDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Alea DelmastroDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-7959-3165
Felix J HartmannDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-4174-2276
Lise MangianteStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-8309-0950
Cristina Sotomayor-VivasStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-8228-477X
Sean C BendallDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1341-2453
Ton N SchumacherDivision of Molecular Oncology & Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0003-0517-8804
Zhicheng MaStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
Marc BosseDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-4912-8059
Marc J van de VijverDepartment of Pathology, University of Amsterdam, Amsterdam, the Netherlands.
Robert TibshiraniDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
Hugo M HorlingsDepartment of Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0003-4782-8828
Christina CurtisDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA. cncurtis@stanford.edu.ORCID http://orcid.org/0000-0003-0166-3802
Marleen KokDivision of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. m.kok@nki.nl.ORCID http://orcid.org/0000-0001-9043-9815
Michael AngeloDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA. mangelo0@stanford.edu.ORCID http://orcid.org/0000-0003-1531-5067

Funding

The Bone Marrow Multi-modal Imaging CoreU54HL165445 · NHLBI · STANFORD UNIVERSITY · PI ANGELO, ROBERT MICHAEL, BENDALL, SEAN CURTIS · 2022 to 2025
$5.9M
A robust platform for multiplexed, subcellular proteomic imaging in human tissueUH3CA246633 · NCI · STANFORD UNIVERSITY · PI ANGELO, ROBERT MICHAEL, BENDALL, SEAN CURTIS · 2019 to 2021
$1.8M
Comprehensive profiling of the tumor microenvironment to predict patient response to immunotherapyF99CA264307 · NCI · STANFORD UNIVERSITY · PI GREENWALD, NOAH · 2021 to 2022
$79k
Predicting response to anti-PD-1 therapy in triple negative breast cancer by comprehensive profiling of the tumor microenvironmentF31CA246880 · NCI · STANFORD UNIVERSITY · PI GREENWALD, NOAH · 2020 to 2021
$53k
NCI NIH HHS F31 CA246880NCI NIH HHS F99 CA264307NCI NIH HHS UH3 CA246633NHLBI NIH HHS U54 HL165445
6 · The paper itself

Abstract

Immune checkpoint inhibition (ICI) benefits only a subset of patients with metastatic triple-negative breast cancer and determinants of response remain unclear. We assembled a longitudinal cohort of 103 female patients from the phase 2 TONIC trial, with samples spanning primary tumors, pretreatment metastases and on-treatment metastases during nivolumab therapy. We profiled 37 proteins in 270 tumors using highly multiplexed imaging and developed SpaceCat, an open-source pipeline that extracts more than 800 imaging features per sample, including cell density, diversity, spatial interactions and functional marker expression. Metastatic but not primary tumors contained features predictive of outcome. Spatial metrics such as immune diversity and T cell infiltration at tumor borders were most informative, while ratios of T cells to cancer cells and PDL1 on myeloid cells were also associated with response. Multivariate models stratified patients with the highest performance on treatment (area under the curve = 0.90). Bulk RNA-seq confirmed the predictive value of on-treatment samples. These findings highlight the value of longitudinal profiling to resolve evolving tumor microenvironment dynamics driving ICI response.

Indexed as

Immune Checkpoint InhibitorsTriple Negative Breast NeoplasmsTumor MicroenvironmentBiomarkers, TumorFemaleHumansLongitudinal StudiesLymphocytes, Tumor-InfiltratingNeoplasm MetastasisNivolumabT-LymphocytesBiomarkers, TumorImmune Checkpoint InhibitorsNivolumab

Identifiers

PMID41708895
PMCPMC13262111

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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.