Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
Abstract 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 stra...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-02-01
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| Series: | Cancer Cell International |
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| Online Access: | https://doi.org/10.1186/s12935-021-02430-9 |
| _version_ | 1798022567615791104 |
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| author | Nan Zhao Yanhui Zhang Runfen Cheng Danfang Zhang Fan Li Yuhong Guo Zhiqiang Qiu Xueyi Dong Xinchao Ban Baocun Sun Xiulan Zhao |
| author_facet | Nan Zhao Yanhui Zhang Runfen Cheng Danfang Zhang Fan Li Yuhong Guo Zhiqiang Qiu Xueyi Dong Xinchao Ban Baocun Sun Xiulan Zhao |
| author_sort | Nan Zhao |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-11T17:32:02Z |
| format | Article |
| id | doaj.art-327e4d53d57f42e8baf85e057bdc95ec |
| institution | Directory Open Access Journal |
| issn | 1475-2867 |
| language | English |
| last_indexed | 2024-04-11T17:32:02Z |
| publishDate | 2022-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Cancer Cell International |
| spelling | doaj.art-327e4d53d57f42e8baf85e057bdc95ec2022-12-22T04:11:58ZengBMCCancer Cell International1475-28672022-02-0122111810.1186/s12935-021-02430-9Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survivalNan Zhao0Yanhui Zhang1Runfen Cheng2Danfang Zhang3Fan Li4Yuhong Guo5Zhiqiang Qiu6Xueyi Dong7Xinchao Ban8Baocun Sun9Xiulan Zhao10Department of Pathology, Tianjin Medical UniversityDepartment of Pathology, Cancer Hospital of Tianjin Medical UniversityDepartment of Pathology, Cancer Hospital of Tianjin Medical UniversityDepartment of Pathology, Tianjin Medical UniversityDepartment of Pathology, Tianjin Medical UniversityDepartment of Pathology, Cancer Hospital of Tianjin Medical UniversityDepartment of Pathology, Cancer Hospital of Tianjin Medical UniversityDepartment of Pathology, Tianjin Medical UniversityDepartment of Pathology, Tianjin Medical UniversityDepartment of Pathology, Tianjin Medical UniversityDepartment of Pathology, Tianjin Medical UniversityAbstract 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.https://doi.org/10.1186/s12935-021-02430-9Hepatocellular carcinoma (HCC)HeterogeneitySpatial transcriptomics (ST)Satellite nodulesGene signature |
| spellingShingle | Nan Zhao Yanhui Zhang Runfen Cheng Danfang Zhang Fan Li Yuhong Guo Zhiqiang Qiu Xueyi Dong Xinchao Ban Baocun Sun Xiulan Zhao Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival Cancer Cell International Hepatocellular carcinoma (HCC) Heterogeneity Spatial transcriptomics (ST) Satellite nodules Gene signature |
| 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 | Hepatocellular carcinoma (HCC) Heterogeneity Spatial transcriptomics (ST) Satellite nodules Gene signature |
| url | https://doi.org/10.1186/s12935-021-02430-9 |
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