Evidence map›Paper›PMID 42177228›Full record

ArticleScientific reports2026

A hybrid multiscale model for predicting CAR-T therapy outcomes in solid tumors.

Mohammad R Nikmaneshi, Lance L Munn

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Mohammad R NikmaneshiEdwin L. Steele Laboratories, Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Boston, MA, 02114, USA.
Lance L MunnEdwin L. Steele Laboratories, Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Boston, MA, 02114, USA. lmunn@mgh.harvard.edu.

Funding

Vascularized tumor explants for drug testingR01CA247441 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI MUNN, LANCE L. · 2021 to 2025
$1.9M
NCI NIH HHS R01 CA247441NCI NIH HHS R01CA247441
6 · The paper itself

Abstract

T cell distribution within tumors ("tumor hotness") critically determines the success of immunotherapy. However, despite numerous strategies to enhance intratumoral T cell accumulation - such as multi-target CAR-Ts and combinatorial approaches - limited mechanistic understanding of T cell-microenvironment interactions has constrained progress. To address this, we developed a mechanistic physiological model of the 3D tumor microenvironment (TME) to evaluate CAR-T performance under environmental fluctuations and across different infusion strategies. The model integrates key vascular (rolling, firm adhesion, endothelial suppression) and interstitial (ECM density, metabolic competition, chemokine sensitivity) barriers. Our simulations reveal that collagen density and metabolic competition are dominant factors in CAR-T efficacy. Enhancing vascular rolling and firm adhesion improves infiltration but remains limited by collagen and metabolism. Endothelial suppression markedly reduces tumor hotness, while its alleviation enhances response. Systemic infusion yields higher tumor hotness than intratumoral delivery, but combined routes or reduced collagen density restore efficacy, even in dense tumors. This mechanistic framework enables rational optimization of CAR-T strategies.

Indexed as

Immunotherapy, AdoptiveNeoplasmsReceptors, Chimeric AntigenT-LymphocytesAnimalsCollagenHumansModels, BiologicalTreatment OutcomeTumor MicroenvironmentCollagenReceptors, Chimeric Antigen

Identifiers

PMID42177228
PMCPMC13424311

What OpenQuestion holds

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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.