Evidence map›Paper›PMID 36864399›Full record

ArticleBMC cancer2023

Integrated transcriptional analysis reveals macrophage heterogeneity and macrophage-tumor cell interactions in the progression of pancreatic ductal adenocarcinoma.

Kaidi Yang, Tongxin Yang, Jian Yu, Fang Li, Xiang Zhao

Abstract read
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Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Kaidi YangDepartment of Oncology, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, 57200, Hainan Province, P.R. China. lampirl@163.com.
Tongxin YangDepartment of Oncology, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, 57200, Hainan Province, P.R. China.
Jian YuDepartment of Health Statistics, Naval Medical University, Shanghai, 200433, PR China.
Fang LiDepartment of Oncology, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, 57200, Hainan Province, P.R. China.
Xiang ZhaoDepartment of Oncology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, P. R. China. x.zhao.tmmu@outlook.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease harboring significant microenvironment heterogeneity, especially for the macrophages. Tumor-associated macrophages (TAMs) orchestrate PDAC malignancy, but their dynamics during disease progression remains poorly understood. There is a pressing need to identify the molecular mechanism underlying tumor-macrophage interactions and thus design novel therapeutic strategies.

methodsHerein, we developed an insilico computational method incorporating bulk and single-cell transcriptome profiling to characterize macrophage heterogeneity. CellPhoneDB algorithm was applied to infer macrophage-tumor interaction networks, whereas pseudotime trajectory for dissecting cell evolution and dynamics.

resultsWe demonstrated myeloid compartment was an interactive hub of tumor microenvironment (TME) essential for PDAC progression. Dimensionality reduction classified seven clusters within the myeloid cells wherein five subsets of macrophages were characterized by diverse cell states and functionality. Remarkably, tissue-resident macrophages and inflammatory monocyte were identified as potential sources of TAMs. Further, we uncovered several ligand-receptor pairs lining tumor cells and macrophages. Among them, HBEGF-CD44, HBEGF-EGFR, LGALS9-CD44, LGALS9-MET, and GRN-EGFR were correlated with worse overall survival. Notably, as in vitro experiments indicated, TAM-derived HBEGF promoted proliferation and invasion of the pancreatic cancer cell line.

conclusionTogether, our work deciphered a comprehensive single-cell atlas of the macrophage compartment of PDAC and provided novel macrophage-tumor interaction features with potential value in developing targeted immunotherapies and molecular diagnostics for predicting patient outcome.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsCell CommunicationErbB ReceptorsHumansMacrophagesTumor MicroenvironmentErbB ReceptorsMacrophage heterogeneityPancreatic ductal adenocarcinomaPrognosisSingle-cell RNA sequencingTumor-macrophage interactions

Identifiers

PMID36864399
PMCPMC9983236

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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.