Evidence map›Paper›PMID 39341903›Full record

ArticleCommunications biology2024

Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments.

Victor G Wang, Zichao Liu, Jan Martinek, Ali Foroughi Pour, Jie Zhou, Hannah Boruchov, Kelly Ray, Karolina Palucka, Jeffrey H Chuang

Abstract read
In one paragraph

Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Victor G Wang *The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Zichao Liu *The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.ORCID 0000-0002-3156-5114
Jan Martinek *The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Ali Foroughi PourThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Jie ZhouThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Hannah BoruchovThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Kelly RayThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Karolina PaluckaThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Jeffrey H ChuangThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA. jeff.chuang@jax.org.ORCID 0000-0002-3298-2358

Funding

Shared Resource ManagementP30CA034196 · NCI · JACKSON LABORATORY · PI William Carl Skarnes · 1985 to 2026
$61.9M
(PQ3) Cellular and Molecular Mechanisms Driving Myeloid Compartment Variation in Human Triple Negative Breast CancerR01CA219880 · NCI · JACKSON LABORATORY · PI PALUCKA, ANNA KAROLINA · 2017 to 2021
$3.4M
Quantitative Computational Methods to Accurately Measure Tumor Heterogeneity in Solid Tumors to Inform Development of Evolution-based Treatment StrategiesR01CA230031 · NCI · JACKSON LABORATORY · PI CHUANG, JEFFREY HSU-MIN · 2018 to 2022
$2.6M
Towards True Precision Oncology: Validation of a Comprehensively Humanized, Autologous Mouse ModelR01CA204115 · NCI · WASHINGTON UNIVERSITY · PI FIELDS, RYAN C, FLAVELL, RICHARD A · 2017 to 2019
$1.8M
Humanized mouse models to dissect in vivo the interplay between melanoma and the immune systemR01CA195712 · NCI · JACKSON LABORATORY · PI FLAVELL, RICHARD A, PALUCKA, ANNA KAROLINA · 2015 to 2017
$1.3M
Dissection of Tumor Evolution Using Patient-Derived XenograftsR21CA191848 · NCI · JACKSON LABORATORY · PI CHUANG, JEFFREY HSU-MIN · 2015 to 2016
$531k
NCI NIH HHS P30 CA034196NCI NIH HHS R01 CA195712NCI NIH HHS R01 CA204115NCI NIH HHS R01 CA219880NCI NIH HHS R01 CA230031NCI NIH HHS R21 CA191848U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) P30CA034196U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) R01CA204115U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) R01CA230031
6 · The paper itself

Abstract

The tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then verify CISA's applicability across data modalities with melanoma histocytometry whole slide images, revealing that T-cell:macrophage synapse formation correlates with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types.

Indexed as

Immunological SynapsesMelanomaT-LymphocytesTumor MicroenvironmentBreast NeoplasmsCell CommunicationComputational BiologyFemaleHumans

Identifiers

PMID39341903
PMCPMC11438971

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.