Evidence map›Paper›PMID 42342409›Full record

Trial reportJournal for immunotherapy of cancer2026

Artificial intelligence-guided analysis of the tumor microenvironment predicts response to pembrolizumab in rare tumors.

Mohamed H Derbala, Bettzy Stephen, Woochan Hwang, Chan-Young Ock, Soohyun Hwang, Joud Hajjar, Seungeun Lee, Jianling Zhou, Serdar A Gurses, Mohamed A Gouda and 12 more

Registry-linked trialAbstract readClinical Trial, Phase II
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal for immunotherapy of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02721732 (Phase II Study for the Evaluation of Efficacy of Pembrolizumab), which is not on this map. Not yet cited in PubMed.

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

NCT02721732 phase2active not recruitingnot on this map

Phase II Study for the Evaluation of Efficacy of Pembrolizumab (MK-3475) in Patients With Rare Tumors

TypeinterventionalSponsorM.D. Anderson Cancer CenterRan2016 to 2028Enrolled157ConditionsAdvanced Malignant Solid Neoplasm, Carcinoma of Unknown Primary, Metastatic Adrenal Gland Pheochromocytoma, Metastatic Kidney Medullary CarcinomaArmsLaboratory Biomarker Analysis, Pembrolizumab, Questionnaire Administration
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

22 authors.

Mohamed H DerbalaDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Bettzy StephenDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Woochan HwangLunit Inc, Gangnam-gu, Seoul, Korea (the Republic of).
Chan-Young OckLunit Inc, Gangnam-gu, Seoul, Korea (the Republic of).
Soohyun HwangLunit Inc, Gangnam-gu, Seoul, Korea (the Republic of).
Joud HajjarDivision of Immunology, Allergy and Retrovirology, Baylor College of Medicine, Houston, Texas, USA.
Seungeun LeeLunit Inc, Gangnam-gu, Seoul, Korea (the Republic of).
Jianling ZhouDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Serdar A GursesDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID http://orcid.org/0000-0002-8781-4554
Mohamed A GoudaDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Kathryn E McGonagleDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Anas AlshawaDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Lilibeth CastilloDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Abdulrazzak ZarifaDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Siqing FuDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Sarina A Piha-PaulDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID http://orcid.org/0000-0001-9455-1660
Apostolia M TsimberidouDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID http://orcid.org/0000-0003-2713-233X
Funda Meric-BernstamDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Luisa Maren Solis SotoDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Maria Gabriela RasoDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Siraj AliLunit Inc, Gangnam-gu, Seoul, Korea (the Republic of).
Aung NaingDepartment of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA anaing@mdanderson.org.ORCID http://orcid.org/0000-0002-4803-8513

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPathologic tumor response and changes in the tumor microenvironment (TME) predict outcomes to immune checkpoint inhibitors, but are understudied in rare tumors. We investigated whether artificial intelligence (AI)-powered analyses of pretreatment and on-treatment biopsies may inform treatment outcomes to pembrolizumab.

methodsWe evaluated 256 baseline and 248 on-treatment biopsies from 84 patients with rare tumors (10 cohorts) in a phase II pembrolizumab trial. Intratumoral tumor-infiltrating lymphocyte (iTIL) density and tumor content (TC) were assessed on H&E-stained slides using a deep learning-based analyzer (Lunit SCOPE IO). Baseline iTIL and changes in iTIL and TC were correlated with progression-free survival (PFS) and overall survival (OS). Multiplex immunofluorescence was performed in 27 paired samples to assess TME changes.

resultsIn the high-iTIL tumor group, a baseline iTIL of ≥60 cells/mm

conclusionAI-powered assessment of the TME before and during treatment may help inform treatment outcomes to pembrolizumab in patients with rare tumors. TRIAL REGISTRATION NUMBER: NCT02721732.

Indexed as

Antibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalArtificial IntelligenceNeoplasmsTumor MicroenvironmentAgedFemaleHumansLymphocytes, Tumor-InfiltratingMaleMiddle AgedAntibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalpembrolizumabBiomarkerImmune Checkpoint InhibitorsImmunotherapyTumor Microenvironment

Identifiers

PMID42342409
PMCPMC13295762

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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.