BACKGROUND: Biphenotypic hepatocellular carcinoma-cholangiocarcinoma (HCC-CC) is an uncommon primary liver neoplasm. Due to limitations in radiologic imaging for the diagnosis of this condition, biopsy is a common method for diagnosis, which is invasive and holds potential complications. To identify alternative means for obtaining the diagnosis and assessing the prognosis of this condition, we evaluated biomarkers for biphenotypic HCC-CC using a genetic database. METHODS: To evaluate the genetic associations with each variable we utilized GeneCards(®), The Human Gene Compendium (http://www.genecards.org). The results of our search were entered into the Pathway Interaction Database from the National Cancer Institute (PID-NCI) (http://pid.nci.nih.gov), to generate a biomolecule interaction map. RESULTS: The results of our query yielded 690 genes for HCC, 98 genes for CC and 50 genes for HCC-CC. Genes depicted in this analysis demonstrate the role of hormonal regulation, embryonic development, cell surface adhesion, cytokeratin stability, mucin production, metalloproteinase regulation, Ras signaling, metabolism and apoptosis. Examples of previously described markers included hepatocyte growth factor (HGF), mesenchymal epithelial transition (MET) and Kirsten rat sarcoma viral oncogene homolog (KRAS). Novel markers included phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA), GPC3, choline kinase alpha (CHKA), prostaglandin-endoperoxide synthase 2 (PTGS2), telomerase reverse transcriptase (TERT), myeloid cell leukemia 1 (MCL1) and N-acetyltransferase 2 (NAT2). CONCLUSIONS: GeneCards is a useful research tool in the genetic analysis of low frequency malignancies. Utilizing this tool we identified several biomarkers are methods for diagnosing HCC-CC. Finally, utilizing these methods, HCC-CC was found to be predominantly a subtype of CC.
BACKGROUND:Biphenotypic hepatocellular carcinoma-cholangiocarcinoma (HCC-CC) is an uncommon primary liver neoplasm. Due to limitations in radiologic imaging for the diagnosis of this condition, biopsy is a common method for diagnosis, which is invasive and holds potential complications. To identify alternative means for obtaining the diagnosis and assessing the prognosis of this condition, we evaluated biomarkers for biphenotypic HCC-CC using a genetic database. METHODS: To evaluate the genetic associations with each variable we utilized GeneCards(®), The Human Gene Compendium (http://www.genecards.org). The results of our search were entered into the Pathway Interaction Database from the National Cancer Institute (PID-NCI) (http://pid.nci.nih.gov), to generate a biomolecule interaction map. RESULTS: The results of our query yielded 690 genes for HCC, 98 genes for CC and 50 genes for HCC-CC. Genes depicted in this analysis demonstrate the role of hormonal regulation, embryonic development, cell surface adhesion, cytokeratin stability, mucin production, metalloproteinase regulation, Ras signaling, metabolism and apoptosis. Examples of previously described markers included hepatocyte growth factor (HGF), mesenchymal epithelial transition (MET) and Kirsten ratsarcoma viral oncogene homolog (KRAS). Novel markers included phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA), GPC3, choline kinase alpha (CHKA), prostaglandin-endoperoxide synthase 2 (PTGS2), telomerase reverse transcriptase (TERT), myeloid cell leukemia 1 (MCL1) and N-acetyltransferase 2 (NAT2). CONCLUSIONS: GeneCards is a useful research tool in the genetic analysis of low frequency malignancies. Utilizing this tool we identified several biomarkers are methods for diagnosing HCC-CC. Finally, utilizing these methods, HCC-CC was found to be predominantly a subtype of CC.
Authors: Kathryn J Fowler; Arman Sheybani; Rex A Parker; Sean Doherty; Elizabeth M Brunt; William C Chapman; Christine O Menias Journal: AJR Am J Roentgenol Date: 2013-08 Impact factor: 3.959
Authors: Hana Park; Ki Hong Choi; Sae-Byeol Choi; Jong Won Choi; Do Young Kim; Sang Hoon Ahn; Kyung Sik Kim; Jin Sub Choi; Kwang-Hyub Han; Chae Yoon Chon; Jun Yong Park Journal: Yonsei Med J Date: 2011-09 Impact factor: 2.759