Evidence map›Paper›PMID 40652419›Full record

ArticleDiscover oncology2025

Integrating bulk and single-cell RNA sequencing reveals intratumor heterogeneity phenotypes and immune infiltration in pancreatic cancer.

Li Zhao, Yao Huang, Jiang Li, Rui Xie, Kaiming Li

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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.

Li Zhao *Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yao Huang *Guangzhou University of Chinese Medicine, Guangzhou, China.
Jiang LiDepartment of Pharmacy, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Rui XieDepartment of Pharmacy, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China. 20173188@zcmu.eud.cn.
Kaiming LiDepartment of Pharmacy, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China. likaiming2016@126.com.

Funding

the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (Grant No. LYY21H300002)the Wu Jieping Medical Foundation Special Fund for Scientific Research (Grant No. 320.6750.2024-18-11)
6 · The paper itself

Abstract

backgroundAlthough the significance of intratumoral heterogeneity (ITH) has been widely acknowledged in various cancers, its role in pancreatic cancer (PC) remains underexplored and warrants further investigation.

methodsPancreatic cancer transcriptomic data were acquired from the TCGA and GEO databases. The DEPTH2 algorithm, in combination with differential expression analysis, was used to identify genes associated with intratumoral heterogeneity (ITH). We applied univariate Cox regression analysis and multiple machine learning techniques to establish a reliable prognostic model. Patients were then stratified according to their ITH scores, and differences between subgroups were examined through pathway enrichment analysis, immune cell infiltration profiling, and drug response prediction. Furthermore, we conducted subcellular localization and differential analysis of ITH using single-cell data, followed by cell-cell communication analysis to explore interaction relationships and identify key pathways.

resultsPatients exhibiting lower intratumoral heterogeneity (ITH) levels demonstrated poorer clinical outcomes. The constructed 11-gene signature successfully differentiated individuals into high- and low-risk categories with significant survival differences. Immune profiling revealed notable differences in immune cell composition between the two groups, with patients in the high ITH cohort exhibiting enhanced immune activation. Drug sensitivity analysis indicated a differential response to therapies, with high-risk patients more resistant to certain drugs. Single-cell RNA sequencing identified a greater ITH score in epithelial cells, highlighting key interactions, particularly involving Galectin signaling pathways.

conclusionOur results highlight intratumoral heterogeneity's prognostic and therapeutic relevance in pancreatic cancer, suggesting its potential utility in guiding individualized treatment approaches.

Indexed as

Drug sensitivityImmune infiltrationIntratumoral heterogeneityPancreatic cancerPrognostic model

Identifiers

PMID40652419
PMCPMC12256387

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