Evidence map›Paper›PMID 40220297›Full record

ArticleCell reports2025

Quantitatively defined stromal B cell aggregates are associated with response to checkpoint inhibitors in unresectable melanoma.

James W Smithy, Xiyu Peng, Fiona D Ehrich, Andrea P Moy, Mohammad Yosofvand, Colleen Maher, Nathaniel Aleynick, Rami Vanguri, Mingqiang Zhuang, Jasme Lee and 7 more

Abstract read
In one paragraph

Article in Cell reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Association of Circulating T Cell and Tumor Microenvironment Profiles with Immune Checkpoint Blockade Outcomes in Sarcoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  4. Review
  5. Article
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

17 authors.

James W SmithyDepartment of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. Electronic address: smithyj@mskcc.org.
Xiyu PengDepartment of Statistics, Texas A&M University, College Station, TX, USA.
Fiona D EhrichDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Andrea P MoyDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Mohammad YosofvandDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Colleen MaherDepartment of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Nathaniel AleynickDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Rami VanguriDepartment of Medicine, NYU Grossman School of Medicine, New York, NY, USA.
Mingqiang ZhuangDepartment of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Jasme LeeDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
MaryLena BleileDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Yanyun LiBristol Myers Squibb, Princeton, NJ, USA.
Michael A PostowDepartment of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA.
Katherine S PanageasDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Travis J HollmannBristol Myers Squibb, Princeton, NJ, USA.
Margaret K CallahanDepartment of Medicine, University of Connecticut School of Medicine, Farmington, CT, USA.
Ronglai ShenDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Multiplex immunofluorescence (mIF) is a promising tool for immunotherapy biomarker discovery in melanoma and other solid tumors. mIF captures detailed phenotypic information of immune cells in the tumor microenvironment, as well as spatial data that can reveal biologically relevant interactions among cell types. Given the complexity of mIF data, the development of automated analysis pipelines is crucial for advancing biomarker discovery. In pre-treatment melanoma samples from 50 patients treated with immune checkpoint inhibitors (ICIs), a higher stromal B cell percentage is associated with the clinical benefit of ICI therapy. The automatic detection of B cell aggregates with DBSCAN, a novel application of a computer-aided machine learning algorithm, demonstrates the potential for enhanced accuracy compared to pathologist assessment of lymphoid aggregates. TCF1

Indexed as

B-LymphocytesImmune Checkpoint InhibitorsMelanomaStromal CellsFemaleHumansImmunotherapyLymphocyte Activation Gene 3 ProteinTumor MicroenvironmentImmune Checkpoint InhibitorsLymphocyte Activation Gene 3 ProteinCP: Cancerimmune checkpoint inhibitorsmelanomamultiplex immunofluorescencespatial analysistertiary lymphoid structures

Identifiers

PMID40220297
PMCPMC12166967

What OpenQuestion holds

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Registered trials

None linked

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.