Transcriptome classification of HCC is related to gene alterations and to new therapeutic targets

By Sandrine Boyault, D. Rickman, A. de Reyniès, C. Balabaud, S. Rebouissou, E. Jeannot, Aurélie Hérault, J. Saric, J. Belghiti, D. Franco and 3 more. Hepatology, 2007

1,163 citations recorded by the source corpus.

Subfields: Genetics, Hepatology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b5e3c7488b1efaa46f8c828843bc2e1ca27027aa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. humAn cArcinogens
2. Iarc Monographs
3. peRsonAl hAbIts
4. Stacey Gabriel
5. S. Friedman

In Hepatology

1. J. Llovet
2. Jordi Bruix1 , 2
3. Riccardo Lencioni
4. V. Mazzaferro
5. Andrew X. Zhu
6. Peter R. Galle
7. T. de Baère
8. Yujin Hoshida

In Molecular Biology

1. Yujin Hoshida
2. Jean-Philippe Brunet
3. Yanqin Zuo
4. Matthew Meyerson
5. Kumardeep Chaudhary
6. L. Yao
7. Yitian Wang
8. L. Ye

Citations in the corpus

• iArc monogrAphs on the evAluAtion oF cArcinogenic risks to humAns (2012, background): “A recent study compared the transcriptome-genotype-phenotype of more than 50 HCCs, and could identify specific patterns for HBV-associated HCCs (Boyault et al., 2007).”
• Wnt/β-catenin signalling: function, biological mechanisms, and therapeutic opportunities (2022, background): “In hepatocellular carcinoma, CTNNB1-activating mutations [28% (34/ 123) to 40% (18/45)] are the most significant genetic changes in the Wnt/β-catenin pathway.(228,229) In medulloblastomas, CTNNB1 is a common mutation (15/125, 12%).”
• EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. (2012, background): “From the biological standpoint, different tumoral classes have been characterized including a Wnt subclass, a proliferation class (with two subclasses: S1-TGF-beta and S2-EpCAM positive) and an inflammation class [77,137,174,175].”
• Histological subtypes of hepatocellular carcinoma are related to gene mutations and molecular tumour classification. (2017, methodology): “Transcriptomic classification of HCC samples was performed in 265 cases using a combination of 16 genes, as previously described.(11) In addition, the expression of the following genes was investigated in a subset of 186 tumours: ALB, AFP, APOB, CYP1A1, CYP1A2, CYP3A4, CYP2E1, CYP2C9, HNF4A, HNF1A (”
• MicroRNA profiling in hepatocellular tumors is associated with clinical features and oncogene/tumor suppressor gene mutations (2008, methodology): “In each tumor, several oncogenic pathways are deregulated (2) and different subtypes of tumors are defined according to genetic and transcriptomic based classification (7, 8).”
• Deep Learning based multi-omics integration robustly predicts survival in liver cancer (2017, methodology): “As a result, some molecular subtypes showed converging and similar survival profiles, making them redundant subtypes in terms of survival differences (16).”
• EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. (2012, background): “From the biological standpoint, different tumoral classes have been characterized including a Wnt subclass, a proliferation class (with two subclasses: S1-TGF-beta and S2-EpCAM positive) and an inflammation class [77,137,174,175].”
• Focal Gains of Vascular Endothelial Growth Factor A and Molecular Classification of Hepatocellular Carcinoma (2008, methodology): “Combined annotations from marker gene lists, mutation analyses, and immunohistochemistry could associate three of five gene expression classes with previously described signaling pathway alterations (4, 5, 7).”
• Integrative Transcriptome Analysis Reveals Common Molecular Subclasses of Human Hepatocellular Carcinoma (2009, methodology): “An AFP-AKT association has been previously observed (10, 26), and we see here that this association is being driven primarily by S2 tumors.”