Evidence map›Paper›PMID 38414027›Full record

ArticleJournal of translational medicine2024

Integrative single-cell transcriptomic analyses reveal the cellular ontological and functional heterogeneities of primary and metastatic liver tumors.

Menghui Gui, Shilin Huang, Shizhou Li, Yuying Chen, Furong Cheng, Yulin Liu, Ji-Ao Wang, Yuting Wang, Rui Guo, Yiming Lu and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.8field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 18 citations in OpenAlex.

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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

12 authors at 6 institutions in 1 country.

Menghui GuiSchool of Public Health, Nanjing Medical University, Nanjing, 211166, People's Republic of China.
Shilin HuangDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, People's Republic of China.
Shizhou LiDepartment of Medical Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, People's Republic of China.
Yuying ChenHengyang Medical College, University of South China, Hengyang, 421001, People's Republic of China.
Furong ChengInstitute of Life Science and Green Development, College of Life Sciences, Hebei University, Baoding, 071002, People's Republic of China.
Yulin LiuMudanjiang Medical College, Mudanjiang, 157011, People's Republic of China.
Ji-Ao WangInstitute of Life Science and Green Development, College of Life Sciences, Hebei University, Baoding, 071002, People's Republic of China.
Yuting WangCollege of Chemistry & Environmental Science, Hebei University, Baoding, 071002, People's Republic of China.
Rui GuoInstitute of Life Science and Green Development, College of Life Sciences, Hebei University, Baoding, 071002, People's Republic of China.
Yiming LuState Key Laboratory of Medical Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, People's Republic of China.
Pengbo CaoState Key Laboratory of Medical Proteomics, National Center for Protein Sciences at Beijing, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, People's Republic of China. birchcpb@163.com.
Gangqiao ZhouSchool of Public Health, Nanjing Medical University, Nanjing, 211166, People's Republic of China. zhougq114@126.com.
Hebei University · CNBeijing Proteome Research Center · CNGuangxi Medical University · CNNanjing Medical University · CNMudanjiang Medical University · CNUniversity of South China · CN

Funding

National Key Research and Development Plan of China 2022YFC2504703National Natural Science Foundation of China 82002573National Natural Science Foundation of China 82172707
6 · The paper itself

Abstract

backgroundThe global cellular landscape of the tumor microenvironment (TME) combining primary and metastatic liver tumors has not been comprehensively characterized.

methodsBased on the scRNA-seq and spatial transcriptomic data of non-tumor liver tissues (NTs), primary liver tumors (PTs) and metastatic liver tumors (MTs), we performed the tissue preference, trajectory reconstruction, transcription factor activity inference, cell-cell interaction and cellular deconvolution analyses to construct a comprehensive cellular landscape of liver tumors.

resultsOur analyses depicted the heterogeneous cellular ecosystems in NTs, PTs and MTs. The activated memory B cells and effector T cells were shown to gradually shift to inhibitory B cells, regulatory or exhausted T cells in liver tumors, especially in MTs. Among them, we characterized a unique group of TCF7+ CD8+ memory T cells specifically enriched in MTs that could differentiate into exhausted T cells likely driven by the p38 MAPK signaling. With regard to myeloid cells, the liver-resident macrophages and inflammatory monocyte/macrophages were markedly replaced by tumor-associated macrophages (TAMs), with TREM2+ and UBE2C+ TAMs enriched in PTs, while SPP1+ and WDR45B+ TAMs in MTs. We further showed that the newly identified WDR45B+ TAMs exhibit an M2-like polarization and are associated with adverse prognosis in patients with liver metastases. Additionally, we addressed that endothelial cells display higher immune tolerance and angiogenesis capacity, and provided evidence for the source of the mesenchymal transformation of fibroblasts in tumors. Finally, the malignant hepatocytes and fibroblasts were prioritized as the pivotal cell populations in shaping the microenvironments of PTs and MTs, respectively. Notably, validation analyses by using spatial or bulk transcriptomic data in clinical cohorts concordantly emphasized the clinical significance of these findings.

conclusionsThis study defines the ontological and functional heterogeneities in cellular ecosystems of primary and metastatic liver tumors, providing a foundation for future investigation of the underlying cellular mechanisms.

Indexed as

Endothelial CellsLiver NeoplasmsEcosystemGene Expression ProfilingHumansTumor MicroenvironmentFunctional heterogeneityMetastatic liver tumorsOntological heterogeneityPrimary liver tumorsSingle-cell RNA sequencingTumor microenvironment

Identifiers

PMID38414027
PMCPMC10898050
OpenAlexW4392197036

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.