Evidence map›Paper›PMID 38737676›Full record

ArticleTranslational cancer research2024

Identification of key molecules in the formation of portal vein tumor thrombus in hepatocellular carcinoma based on single cell transcriptomics and

Man Zhang, Chenglei Su, Xiaoyu Liu, Shuqun Hu, Xianliang Yan

Abstract read
In one paragraph

Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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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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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.

Man ZhangDepartment of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.ORCID https://orcid.org/0009-0007-8361-3740
Chenglei SuDepartment of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Xiaoyu LiuDepartment of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.ORCID https://orcid.org/0009-0003-3855-7533
Shuqun HuDepartment of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Xianliang YanDepartment of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The presence of portal vein tumor thrombus (PVTT) is a significant indicator of advanced-stage hepatocellular carcinoma (HCC). Unfortunately, the prediction of PVTT occurrence remains challenging, and there is a lack of comprehensive research exploring the underlying mechanisms of PVTT formation and its association with immune infiltration. Methods: Our approach involved analyzing single-cell sequencing data, applying high dimensional weighted gene co-expression network analysis (hdWGCNA), and identifying key genes associated with PVTT development. Furthermore, we constructed competing endogenous RNA (ceRNA) networks and employed weighted gene co-expression network analysis (WGCNA), as well as three machine-learning techniques, to identify the upstream regulatory microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) of the crucial mRNAs. We employed fuzzy clustering of time series gene expression data (Mfuzz), gene set variation analysis (GSVA), and cell communication analysis to uncover significant signaling pathways involved in the activation of these important mRNAs during PVTT development. In addition, we conducted immune infiltration analysis, survival typing, and drug sensitivity analysis using The Cancer Genome Atlas (TCGA) cohort to gain insights into the two patient groups under study. Results: Through the implementation of hdWGCNA, we identified 110 genes that was closely associated with PVTT. Among these genes, Conclusions: The regulatory axis involving

Indexed as

hepatocellular carcinoma (HCC)machine learningPortal vein tumor thrombus (PVTT)single-cellTMEM165

Identifiers

PMID38737676
PMCPMC11082669

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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.