Evidence map›Paper›PMID 39433650›Full record

ArticleGenes & genomics2025

Machine learning identification of NK cell immune characteristics in hepatocellular carcinoma based on single-cell sequencing and bulk RNA sequencing.

Fang Liu, Baohua Mei, Jianfeng Xu, Yong Zou, Gang Luo, Haiyu Liu

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Article in Genes & genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Fang LiuDepartment of Hepatobiliary Surgery, Jiujiang First People's Hospital, 48 Taling South Road, Jiujiang City, 332000, Jiangxi Province, China. 13879246993@163.com.ORCID 0009-0000-2695-8581
Baohua MeiDepartment of Hepatobiliary Surgery, Jiujiang First People's Hospital, 48 Taling South Road, Jiujiang City, 332000, Jiangxi Province, China.
Jianfeng XuDepartment of Hepatobiliary Surgery, Jiujiang First People's Hospital, 48 Taling South Road, Jiujiang City, 332000, Jiangxi Province, China.
Yong ZouDepartment of Hepatobiliary Surgery, Jiujiang First People's Hospital, 48 Taling South Road, Jiujiang City, 332000, Jiangxi Province, China.
Gang LuoDepartment of Hepatobiliary Surgery, Jiujiang First People's Hospital, 48 Taling South Road, Jiujiang City, 332000, Jiangxi Province, China.
Haiyu LiuCollege of Chinese Medicine, Jiangxi University of Chinese Medicine, Nanchang, 330004, Jiangxi, China.

Funding

Jiangxi Provincial Department of Education science and technology research key project GJJ20210
6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenvironment and mechanisms remain elusive. Single-cell sequencing allows for the exploration of immune characteristics within tumor at the cellular level. However, current knowledge regarding the roles of different immune cell populations in liver cancer progression is limited.

objectiveThe main objective of this study is to identify molecular markers with NK cell immune characteristics in hepatocellular carcinoma using various machine learning methods based on Single-Cell Sequencing and Bulk RNA Sequencing.

methodsWe collected samples from eight normal liver tissues and eight HCC tumor tissues and performed single-cell RNA sequencing for immune cell clustering and expression profile analysis. Using various bioinformatic approaches, we investigated the immune phenotype associated with natural killer (NK) cells expressing high CD7 level. In addition, we verified the role of CD7 in the growth of HCC after NK cell and HCC cells cocultured by RT-qPCR, MTS and Flow cytometer experiments. Finally, we constructed a machine learning model to develop a prognostic prediction system for HCC based on NK cell-related genes.

resultsThrough single-cell typing, we found that the proportions of hepatocytes and NK cells were significantly elevated in the tumor samples. Moreover, we found that the expression of CD7 was high in HCC and correlated with prognosis. More importantly, Overexpression of CD7 in NK cells significantly inhibited the activity of MHCC97 cells and increased the number of apoptosis of HCC cells (p < 0.05). Furthermore, we observed that NK cells with high CD7 expression were associated with an activated immune phenotype.

conclusionOur study found that CD7 is an important biomarker for assessing immune status and predicting survival of HCC patients; hence, it is a potential target for immune therapy against HCC.

Indexed as

Carcinoma, HepatocellularKiller Cells, NaturalLiver NeoplasmsMachine LearningBiomarkers, TumorCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisSequence Analysis, RNASingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorHepatocellular carcinomaImmune phenotypeMachine learningNK cellsSingle-cell RNA sequencing

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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.