Esraa M. Hashem

K6. Circular binary segmentation modeling of array CGH data on hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor derived from hepatocytes that belong to primary malignant epithelial tumors of the liver. The outcome of HCC patients still remains dismal due to the difficulty in detecting the disease at its early stage. We propose a new approach aiming to identify new biomarkers for early diagnosis of HCC. Genomic DNA copy number alterations (CNAs) are associated with complex diseases like HCC. Array-based Comparative Genomic Hybridization (a-CGH) is a technique used to identify copy number changes in genomic DNA. We use a statistical model based on a circular binary segmentation (CBS) algorithm. Our approach makes use of a median absolute deviation model to separate outliers from their surrounding segments. We tested 35 samples of HCC patients on specific chromosome regions, then applied CBS algorithm to detect genomic DNA alternations in copy number. Our results show that a gain of 1q was detected in 63% and a gain of 20q was detected in 26% of HCC cases. Also, a loss of 4q was detected in 3%, a loss of 13q was detected in 29%, loss in 16q was detected in 9%, and loss of 17q was detected in 3% of HCC cases.

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

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.

Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC) Using Whole Genome SNP Array

cancer represents one of the greatest medical causes of mortality. The majority of Hepatocellular carcinoma arises from the accumulation of genetic abnormalities, and possibly induced by exterior etiological factors especially HCV and HBV infections. There is a need for new tools to analysis the large sum of data to present relevant genetic changes that may be critical for both understanding how cancers develop and determining how they could ultimately be treated. Gene expression profiling may lead to new biomarkers that may help develop diagnostic accuracy for detecting Hepatocellular carcinoma. In this work, statistical technique (discrete stationary wavelet transform) for detection of copy number alternations to analysis high-density single-nucleotide polymorphism array of 30 cell lines on specific chromosomes, which are frequently detected in Hepatocellular carcinoma have been proposed. The results demonstrate the feasibility of whole-genome fine mapping of copy number alternations via high-density single-nucleotide polymorphism genotyping, Results revealed that a novel altered chromosomal region is discovered; region amplification (4q22.1) have been detected in 22 out of 30-Hepatocellular carcinoma cell lines (73%). This region strike, AFF1 and DSPP, tumor suppressor genes. This finding has not previously reported to be involved in liver carcinogenesis; it can be used to discover a new HCC biomarker, which helps in a better understanding of hepatocellular carcinoma.