Integrating Single-cell and Bulk RNA Sequencing Reveals Stemness Phenotype Associated with Clinical Outcomes and Potential Immune Evasion Mechanisms in Hepatocellular Carcinoma


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Aims:Bulk and single-cell RNA sequencing data were analyzed to explore the association of stemness phenotype with dysfunctional anti-tumor immunity and its impact on clinical outcomes of primary and relapse HCC.

Background:The stemness phenotype is gradually acquired during cancer progression; however, it remains unclear the effect of stemness phenotype on recurrence and clinical outcomes in hepatocellular carcinoma (HCC).

Methods:The stemness index (mRNAsi) calculated by a one-class logistic regression algorithm in multiple HCC cohorts was defined as the stemness phenotype of the patient. Using single-cell profiling in primary or early-relapse HCC, cell stemness phenotypes were evaluated by developmental potential. Differential analysis of stemness phenotype, gene expression and interactions between primary and recurrent samples revealed the underlying immune evasion mechanisms.

Results:A strong correlation was discovered between mRNAsi and clinical outcomes in patient with HCC. The high and low mRNAsi groups had distinct tumor immune microenvironments. Cellular stemness phenotype varied by cell type. Moreover, compared with primary tumors, early-relapse tumors had increased stemness of dendritic cells and tumor cells and reduced stemness of T cells and B cells. Moreover, in relapse tumors, CD8+ T cells displayed a low stemness state, with a high exhausted state, unlike the high stemness state observed in primary HCC.

Conclusions:The comprehensive characterization of the HCC stemness phenotype provides insights into the clinical outcomes and immune escape mechanisms associated with recurrence.

Об авторах

Xiaojing Zhu

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Xing Wang

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Hao Wang

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Yanqi Xiao

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Minghui Jiang

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Minwei Wang

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Nan Zhang

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Aimin Xie

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Hongyan Yuan

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Zixin Zhang

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Jiaxing Zhang

College of Bioinformatics Science and Technology, Harbin Medical University

Email: info@benthamscience.net

Yan Xu

College of Bioinformatics Science and Technology, Harbin Medical University

Автор, ответственный за переписку.
Email: info@benthamscience.net

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