1. Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival
- Author
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xiulan Zhao, Runfen Cheng, Baocun Sun, Fan Li, Zhiqiang Qiu, Danfang Zhang, Yuhong Guo, Yanhui Zhang, Xueyi Dong, Nan Zhao, and Xinchao Ban
- Subjects
Cancer Research ,QH573-671 ,Spatial transcriptomics (ST) ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Computational biology ,Biology ,medicine.disease ,Satellite nodules ,Novel gene ,Transcriptome ,Oncology ,Hepatocellular carcinoma ,Genetics ,medicine ,Gene signature ,Spatial maps ,Hepatocellular carcinoma (HCC) ,Heterogeneity ,Signature (topology) ,Primary Research ,Cytology ,RC254-282 - 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.
- Published
- 2022