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Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival

BACKGROUND: Hepatocellular carcinoma (HCC) often presents with satellite nodules, rendering current curative treatments ineffective in many patients. The heterogeneity of HCC is a major challenge in personalized medicine. The emergence of spatial transcriptomics (ST) provides a powerful strategy for...

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Autores principales: Zhao, Nan, Zhang, Yanhui, Cheng, Runfen, Zhang, Danfang, Li, Fan, Guo, Yuhong, Qiu, Zhiqiang, Dong, Xueyi, Ban, Xinchao, Sun, Baocun, Zhao, Xiulan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812006/
https://www.ncbi.nlm.nih.gov/pubmed/35109839
http://dx.doi.org/10.1186/s12935-021-02430-9
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author Zhao, Nan
Zhang, Yanhui
Cheng, Runfen
Zhang, Danfang
Li, Fan
Guo, Yuhong
Qiu, Zhiqiang
Dong, Xueyi
Ban, Xinchao
Sun, Baocun
Zhao, Xiulan
author_facet Zhao, Nan
Zhang, Yanhui
Cheng, Runfen
Zhang, Danfang
Li, Fan
Guo, Yuhong
Qiu, Zhiqiang
Dong, Xueyi
Ban, Xinchao
Sun, Baocun
Zhao, Xiulan
author_sort Zhao, Nan
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) often presents with satellite nodules, rendering current curative treatments ineffective in many patients. The heterogeneity of HCC is a major challenge in personalized medicine. The emergence of spatial transcriptomics (ST) provides a powerful strategy for delineating the complex molecular landscapes of tumours. METHODS: In this study, the heterogeneity of tissue-wide gene expression in tumour and adjacent nonneoplastic tissues using ST technology were investigated. The transcriptomes of nearly 10,820 tissue regions and identified the main gene expression clusters and their specific marker genes (differentially expressed genes, DEGs) in patients were analysed. The DEGs were analysed from two perspectives. First, two distinct gene profiles were identified to be associated with satellite nodules and conducted a more comprehensive analysis of both gene profiles. Their clinical relevance in human HCC was validated with Kaplan–Meier (KM) Plotter. Second, DEGs were screened with The Cancer Genome Atlas (TCGA) database to divide the HCC cohort into high- and low-risk groups according to Cox analysis. HCC patients from the International Cancer Genome Consortium (ICGC) cohort were used for validation. KM analysis was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS. RESULTS: Novel markers for the prediction of satellite nodules were identified and a tumour clusters-specific marker gene signature model (6 genes) for HCC prognosis was constructed. CONCLUSION: The establishment of marker gene profiles may be an important step towards an unbiased view of HCC, and the 6-gene signature can be used for prognostic prediction in HCC. This analysis will help us to clarify one of the possible sources of HCC heterogeneity and uncover pathogenic mechanisms and novel antitumour drug targets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02430-9.
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spelling pubmed-88120062022-02-03 Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival Zhao, Nan Zhang, Yanhui Cheng, Runfen Zhang, Danfang Li, Fan Guo, Yuhong Qiu, Zhiqiang Dong, Xueyi Ban, Xinchao Sun, Baocun Zhao, Xiulan Cancer Cell Int Primary Research BACKGROUND: Hepatocellular carcinoma (HCC) often presents with satellite nodules, rendering current curative treatments ineffective in many patients. The heterogeneity of HCC is a major challenge in personalized medicine. The emergence of spatial transcriptomics (ST) provides a powerful strategy for delineating the complex molecular landscapes of tumours. METHODS: In this study, the heterogeneity of tissue-wide gene expression in tumour and adjacent nonneoplastic tissues using ST technology were investigated. The transcriptomes of nearly 10,820 tissue regions and identified the main gene expression clusters and their specific marker genes (differentially expressed genes, DEGs) in patients were analysed. The DEGs were analysed from two perspectives. First, two distinct gene profiles were identified to be associated with satellite nodules and conducted a more comprehensive analysis of both gene profiles. Their clinical relevance in human HCC was validated with Kaplan–Meier (KM) Plotter. Second, DEGs were screened with The Cancer Genome Atlas (TCGA) database to divide the HCC cohort into high- and low-risk groups according to Cox analysis. HCC patients from the International Cancer Genome Consortium (ICGC) cohort were used for validation. KM analysis was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS. RESULTS: Novel markers for the prediction of satellite nodules were identified and a tumour clusters-specific marker gene signature model (6 genes) for HCC prognosis was constructed. CONCLUSION: The establishment of marker gene profiles may be an important step towards an unbiased view of HCC, and the 6-gene signature can be used for prognostic prediction in HCC. This analysis will help us to clarify one of the possible sources of HCC heterogeneity and uncover pathogenic mechanisms and novel antitumour drug targets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02430-9. BioMed Central 2022-02-02 /pmc/articles/PMC8812006/ /pubmed/35109839 http://dx.doi.org/10.1186/s12935-021-02430-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Primary Research
Zhao, Nan
Zhang, Yanhui
Cheng, Runfen
Zhang, Danfang
Li, Fan
Guo, Yuhong
Qiu, Zhiqiang
Dong, Xueyi
Ban, Xinchao
Sun, Baocun
Zhao, Xiulan
Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
title Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
title_full Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
title_fullStr Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
title_full_unstemmed Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
title_short Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
title_sort spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812006/
https://www.ncbi.nlm.nih.gov/pubmed/35109839
http://dx.doi.org/10.1186/s12935-021-02430-9
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