Evidence map›Paper›PMID 38507505›Full record

ArticleCancer communications (London, England)2024

Conserved immuno-collagenic subtypes predict response to immune checkpoint blockade.

Jie Mei, Yun Cai, Rui Xu, Qing Li, Jiahui Chu, Zhiwen Luo, Yaying Sun, Yuxin Shi, Junying Xu, Di Li and 10 more

Abstract read
In one paragraph

Article in Cancer communications (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Beyond DNA damage: 3D tumor models and the integrin mechanobiology of radioresistance.Journal of experimental & clinical cancer research : CR · 2026
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  18. Targeting collagen to optimize cancer immunotherapy.Experimental hematology & oncology · 2025
    Review
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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

20 authors.

Jie MeiDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, P. R. China.ORCID 0000-0001-7799-8129
Yun CaiDepartments of Gynecology, Wuxi Maternal and Child Health Care Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, P. R. China.
Rui XuDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Qing LiDepartments of Oncology, Xuzhou Central Hospital, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou, Jiangsu, P. R. China.
Jiahui ChuDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Zhiwen LuoDepartment of Sports Medicine, Huashan Hospital Affiliated to Fudan University, Shanghai, P. R. China.
Yaying SunDepartment of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Yuxin ShiDepartments of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, P. R. China.
Junying XuDepartments of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, P. R. China.
Di LiShanghai Outdo Biotech Co., Ltd., National Engineering Center for Biochip, Shanghai, P. R. China.
Shuai LiangDepartments of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, P. R. China.
Ying JiangDepartments of Gynecology, Wuxi Maternity and Child Health Care Hospital, Affiliated Women's Hospital of Jiangnan University, Wuxi, Jiangsu, P. R. China.
Jiayu LiuDepartments of Gynecology, Wuxi Maternity and Child Health Care Hospital, Affiliated Women's Hospital of Jiangnan University, Wuxi, Jiangsu, P. R. China.
Zhiwen QianDepartments of Gynecology, Wuxi Maternal and Child Health Care Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, P. R. China.
Jiaofeng ZhouDepartment of Physiology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Mengyun WanDepartment of Physiology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Yunlong YangDepartment of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, P. R. China.ORCID 0000-0003-1551-9828
Yichao ZhuDepartment of Physiology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu, P. R. China.
Yan ZhangDepartments of Gynecology, Wuxi Maternal and Child Health Care Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, P. R. China.ORCID 0000-0002-7983-8396
Yongmei YinDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, P. R. China.ORCID 0000-0003-3335-369X

Funding

High-level Innovation Team of Nanjing Medical University JX102GSP201727National Key Research and Development Program of China ZDZX2017ZL-01National Natural Science Foundation of China 81972484National Natural Science Foundation of China 82073194Precision Medicine Project of Wuxi Municipal Health Commission J202106Project of Wuxi Medical Center of Nanjing Medical University WMCC202319
6 · The paper itself

Abstract

backgroundImmune checkpoint blockade (ICB) has revolutionized the treatment of various cancer types. Despite significant preclinical advancements in understanding mechanisms, identifying the molecular basis and predictive biomarkers for clinical ICB responses remains challenging. Recent evidence, both preclinical and clinical, underscores the pivotal role of the extracellular matrix (ECM) in modulating immune cell infiltration and behaviors. This study aimed to create an innovative classifier that leverages ECM characteristics to enhance the effectiveness of ICB therapy.

methodsWe analyzed transcriptomic collagen activity and immune signatures in 649 patients with cancer undergoing ICB therapy. This analysis led to the identification of three distinct immuno-collagenic subtypes predictive of ICB responses. We validated these subtypes using the transcriptome data from 9,363 cancer patients from The Cancer Genome Atlas (TCGA) dataset and 1,084 in-house samples. Additionally, novel therapeutic targets were identified based on these established immuno-collagenic subtypes.

resultsOur categorization divided tumors into three subtypes: "soft & hot" (low collagen activity and high immune infiltration), "armored & cold" (high collagen activity and low immune infiltration), and "quiescent" (low collagen activity and immune infiltration). Notably, "soft & hot" tumors exhibited the most robust response to ICB therapy across various cancer types. Mechanistically, inhibiting collagen augmented the response to ICB in preclinical models. Furthermore, these subtypes demonstrated associations with immune activity and prognostic predictive potential across multiple cancer types. Additionally, an unbiased approach identified B7 homolog 3 (B7-H3), an available drug target, as strongly expressed in "armored & cold" tumors, relating with poor prognosis.

conclusionThis study introduces histopathology-based universal immuno-collagenic subtypes capable of predicting ICB responses across diverse cancer types. These findings offer insights that could contribute to tailoring personalized immunotherapeutic strategies for patients with cancer.

Indexed as

CollagenImmune Checkpoint InhibitorsNeoplasmsAnimalsBiomarkers, TumorExtracellular MatrixFemaleHumansMicePrognosisTranscriptomeTumor MicroenvironmentBiomarkers, TumorCollagenImmune Checkpoint Inhibitorscollagen depositionimmune infiltrationimmunotherapypan‐cancertumor microenvironment

Identifiers

PMID38507505
PMCPMC11110954

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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.