ArticleGenomics, proteomics & bioinformatics2019
Multi-omics Analysis of Primary Cell Culture Models Reveals Genetic and Epigenetic Basis of Intratumoral Phenotypic Diversity.
Article in Genomics, proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
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- Liver biopsy in the modern era: from traditional techniques to artificial intelligence and multi-omics integration.Frontiers in medicine · 2025Review
- Comprehensive analysis and immune landscape of chemokines- and chemokine receptors-based signature in hepatocellular carcinoma.Frontiers in immunology · 2023Article
- Multi-omics analysis based on 3D-bioprinted models innovates therapeutic target discovery of osteosarcoma.Bioactive materials · 2022Article
- Artificial intelligence for the prevention and clinical management of hepatocellular carcinoma.Journal of hepatology · 2022Review
- A 3D-printed scaffold-based osteosarcoma model allows to investigate tumor phenotypes and pathogenesis in an in vitro bone-mimicking niche.Materials today. Bio · 2022Article
- Article
- The Role of Epigenetics in the Progression of Clear Cell Renal Cell Carcinoma and the Basis for Future Epigenetic Treatments.Cancers · 2021Review
- Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine.Biomedicines · 2021Review
- Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma.Cancer management and research · 2021Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Uncovering the functionally essential variations related to tumorigenesis and tumor progression from cancer genomics data is still challenging due to the genetic diversity among patients, and extensive inter- and intra-tumoral heterogeneity at different levels of gene expression regulation, including but not limited to the genomic, epigenomic, and transcriptional levels. To minimize the impact of germline genetic heterogeneities, in this study, we establish multiple primary cultures from the primary and recurrent tumors of a single patient with hepatocellular carcinoma (HCC). Multi-omics sequencing was performed for these cultures that encompass the diversity of tumor cells from the same patient. Variations in the genome sequence, epigenetic modification, and gene expression are used to infer the phylogenetic relationships of these cell cultures. We find the discrepancy among the relationships revealed by single nucleotide variations (SNVs) and transcriptional/epigenomic profiles from the cell cultures. We fail to find overlap between sample-specific mutated genes and differentially expressed genes (DEGs), suggesting that most of the heterogeneous SNVs among tumor stages or lineages of the patient are functionally insignificant. Moreover, copy number alterations (CNAs) and DNA methylation variation within gene bodies, rather than promoters, are significantly correlated with gene expression variability among these cell cultures. Pathway analysis of CNA/DNA methylation-related genes indicates that a single cell clone from the recurrent tumor exhibits distinct cellular characteristics and tumorigenicity, and such an observation is further confirmed by cellular experiments both in vitro and in vivo. Our systematic analysis reveals that CNAs and epigenomic changes, rather than SNVs, are more likely to contribute to the phenotypic diversity among subpopulations in the tumor. These findings suggest that new therapeutic strategies targeting gene dosage and epigenetic modification should be considered in personalized cancer medicine. This culture model may be applied to the further identification of plausible determinants of cancer metastasis and relapse.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.