Analyzing cytogenetic chromosomal aberrations on fibrolamellar hepatocellular carcinoma detected by single-nucleotide polymorphs array

• Published in: Neural computing & applications Vol. 31; no. Suppl 2; pp. 817 - 824
• Main Authors: Hashem, Esraa M., Mabrouk, Mai S., Eldeib, Ayman M.
• Format: Journal Article
• Language: English
• Published: London Springer London 13.02.2019; Springer Nature B.V
• Subjects: Abnormalities; Adults; Amplification; Artificial Intelligence; Biomarkers; Children; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Deletion; Deoxyribonucleic acid; Diagnostic systems; DNA; Gene expression; Gene sequencing; Genes; Image Processing and Computer Vision; Liver; Liver cancer; Original Article; Probability and Statistics in Computer Science; Tumors; Fibrolamellar hepatocellular carcinoma; Hepatocellular carcinoma; Single-nucleotide polymorphism array
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-017-3034-4

Fibrolamellar hepatocellular carcinoma is a unique malignant liver tumor type which arises in young adults and children. It is uncommon variation subtype of hepatocellular carcinoma which remains ineffectively recorded. Learning of cytogenetic changes in fibrolamellar hepatocellular carcinoma has lagged behind the information obtained from alternate entities of hepatocellular carcinoma lately. Gene expression profiling may prompt new biomarkers that may help develop diagnostic precision for distinguishing fibrolamellar hepatocellular carcinoma. The subatomic cytogenetic approach permits positional identification of gains, amplification, and deletion of DNA sequences of the whole tumor genome, to search for recurrent and particular cytogenetic changes in human fibrolamellar hepatocellular carcinoma. In this work, 13 cell lines of fibrolamellar carcinomas and 30 hepatocellular carcinoma samples examined by a single-nucleotide polymorphs array using two techniques to give more accuracy of the results. The majority of the abnormalities found in the fibrolamellar hepatocellular carcinoma positive cases seen as gain in 1q, 4q, 6q, 7p, 8q, 17q, 20q and loss in 1p, 4p-q, 8p, 11p, 13q, 17p, 18q, 19p, and 22q. The ultimate successive were central amplification at 1q (in 54% of 13 samples), 4q (in 54% of 13 samples), 7p (in 46% of 13 samples), and deletions at 19p13 (in 28% of 13 samples). The study revealed 3 distinct structural variations highlights-related genes MDM4, PRDM5, and WHSC1, and these genes are a novel target signature that can help to predict survival of patients with detecting fibrolamellar hepatocellular carcinoma.