Evidence map›Paper›PMID 41402579›Full record

ArticleNPJ precision oncology2025

Quantitative profiling of intratumor immune heterogeneity identifies loss of immune diversity as a hallmark of cancer progression.

Qiqi Lu, Jiangti Luo, Chia-Hao Tung, Xiaosheng Wang, Zhongming Zhao

Abstract read
In one paragraph

Article in NPJ precision oncology, 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. Article
  2. Review
  3. Article
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  5. Review
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

5 authors.

Qiqi Lu *Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Jiangti Luo *Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Chia-Hao TungCenter for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Xiaosheng WangCenter for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA. xiaosheng.wang@uth.tmc.edu.
Zhongming ZhaoCenter for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA. zhongming.zhao@uth.tmc.edu.

Funding

Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
NIH HHS R01LM012806NLM NIH HHS R01 LM012806
6 · The paper itself

Abstract

Immunological intratumor heterogeneity (ImTH) describes the variability in the types, spatial distribution, and functional states of immune cells within tumors. While evidence suggests that ImTH influences tumor progression and therapeutic response, few studies have provided a quantitative characterization of ImTH. Here, we present Scoring Immunological Intratumor Heterogeneity (ScImTH), a novel algorithm that quantifies ImTH by calculating the Shannon entropy of immune cell type proportions within the tumor microenvironment. Using bulk, single-cell, and spatial transcriptomic datasets, we show that reduced ScImTH scores are associated with unfavorable survival outcomes, tumor progression-related molecular and phenotypic features, immunosuppressive states, and resistance to immunotherapy across multiple cancer types. Compared with existing measures of tumor immunity, such as immune score and B-cell receptor diversity, the ScImTH score demonstrated stronger and more consistent associations with clinicopathological features. Notably, the ScImTH score outperformed established biomarkers, including tumor mutational burden and PD-L1 expression, in predicting immunotherapy response. These findings highlight the clinical potential of the ScImTH score as a biomarker for cancer prognosis and immunotherapy stratification. More broadly, our results support the hypothesis that loss of immune diversity is a hallmark of tumor progression.

Identifiers

PMID41402579
PMCPMC12820210

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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.