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Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a globally prevailing cancer with a low 5-year survival rate. Little is known about its intricate gene expression profile. Single-cell RNA sequencing is an indispensable tool to explore the genetic characteristics of HCC at a more detailed level. In this study, we p...

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Autores principales: Dong, Xiao, Wang, Fan, Liu, Chuan, Ling, Jing, Jia, Xuebing, Shen, Feifei, Yang, Ning, Zhu, Sibo, Zhong, Lin, Li, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814056/
https://www.ncbi.nlm.nih.gov/pubmed/33462196
http://dx.doi.org/10.1038/s41420-021-00403-5
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author Dong, Xiao
Wang, Fan
Liu, Chuan
Ling, Jing
Jia, Xuebing
Shen, Feifei
Yang, Ning
Zhu, Sibo
Zhong, Lin
Li, Qi
author_facet Dong, Xiao
Wang, Fan
Liu, Chuan
Ling, Jing
Jia, Xuebing
Shen, Feifei
Yang, Ning
Zhu, Sibo
Zhong, Lin
Li, Qi
author_sort Dong, Xiao
collection PubMed
description Hepatocellular carcinoma (HCC) is a globally prevailing cancer with a low 5-year survival rate. Little is known about its intricate gene expression profile. Single-cell RNA sequencing is an indispensable tool to explore the genetic characteristics of HCC at a more detailed level. In this study, we profiled the gene expression of single cells from human HCC tumor and para-tumor tissues using the Smart-seq 2 sequencing method. Based on differentially expressed genes, we identified heterogeneous subclones in HCC tissues, including five HCC and two hepatocyte subclones. We then carried out hub-gene co-network and functional annotations analysis followed pseudo-time analysis with regulated transcriptional factor co-networks to determine HCC cellular trajectory. We found that MLX interacting protein like (MLXIPL) was commonly upregulated in the single cells and tissues and associated with a poor survival rate in HCC. Mechanistically, MLXIPL activation is crucial for promoting cell proliferation and inhibits cell apoptosis by accelerating cell glycolysis. Taken together, our work identifies the heterogeneity of HCC subclones, and suggests MLXIPL might be a promising therapeutic target for HCC.
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spelling pubmed-78140562021-01-25 Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma Dong, Xiao Wang, Fan Liu, Chuan Ling, Jing Jia, Xuebing Shen, Feifei Yang, Ning Zhu, Sibo Zhong, Lin Li, Qi Cell Death Discov Article Hepatocellular carcinoma (HCC) is a globally prevailing cancer with a low 5-year survival rate. Little is known about its intricate gene expression profile. Single-cell RNA sequencing is an indispensable tool to explore the genetic characteristics of HCC at a more detailed level. In this study, we profiled the gene expression of single cells from human HCC tumor and para-tumor tissues using the Smart-seq 2 sequencing method. Based on differentially expressed genes, we identified heterogeneous subclones in HCC tissues, including five HCC and two hepatocyte subclones. We then carried out hub-gene co-network and functional annotations analysis followed pseudo-time analysis with regulated transcriptional factor co-networks to determine HCC cellular trajectory. We found that MLX interacting protein like (MLXIPL) was commonly upregulated in the single cells and tissues and associated with a poor survival rate in HCC. Mechanistically, MLXIPL activation is crucial for promoting cell proliferation and inhibits cell apoptosis by accelerating cell glycolysis. Taken together, our work identifies the heterogeneity of HCC subclones, and suggests MLXIPL might be a promising therapeutic target for HCC. Nature Publishing Group UK 2021-01-18 /pmc/articles/PMC7814056/ /pubmed/33462196 http://dx.doi.org/10.1038/s41420-021-00403-5 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Dong, Xiao
Wang, Fan
Liu, Chuan
Ling, Jing
Jia, Xuebing
Shen, Feifei
Yang, Ning
Zhu, Sibo
Zhong, Lin
Li, Qi
Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma
title Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma
title_full Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma
title_fullStr Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma
title_full_unstemmed Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma
title_short Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma
title_sort single-cell analysis reveals the intra-tumor heterogeneity and identifies mlxipl as a biomarker in the cellular trajectory of hepatocellular carcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814056/
https://www.ncbi.nlm.nih.gov/pubmed/33462196
http://dx.doi.org/10.1038/s41420-021-00403-5
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