Unique Features of Germline Variation in Five Egyptian Familial Breast Cancer Families Revealed by Exome Sequencing.

Genetic predisposition increases the risk of familial breast cancer. Recent studies indicate that genetic predisposition for familial breast cancer can be ethnic-specific. However, current knowledge of genetic predisposition for the disease is predominantly derived from Western populations. Using this existing information as the sole reference to judge the predisposition in non-Western populations is not adequate and can potentially lead to misdiagnosis. Efforts are required to collect genetic predisposition from non-Western populations. The Egyptian population has high genetic variations in reflecting its divergent ethnic origins, and incident rate of familial breast cancer in Egypt is also higher than the rate in many other populations. Using whole exome sequencing, we investigated genetic predisposition in five Egyptian familial breast cancer families. No pathogenic variants in BRCA1, BRCA2 and other classical breast cancer-predisposition genes were present in these five families. Comparison of the genetic variants with those in Caucasian familial breast cancer showed that variants in the Egyptian families were more variable and heterogeneous than the variants in Caucasian families. Multiple damaging variants in genes of different functional categories were identified either in a single family or shared between families. Our study demonstrates that genetic predisposition in Egyptian breast cancer families may differ from those in other disease populations, and supports a comprehensive screening of local disease families to determine the genetic predisposition in Egyptian familial breast cancer.

Serum microRNA panels as potential biomarkers for early detection of hepatocellular carcinoma on top of HCV infection.

The identification of new high-sensitivity and high-specificity markers for hepatocellular carcinoma (HCC) is essential. We aimed at identifying serum microRNAs (miRNAs) as potential biomarkers for early detection of HCC on top hepatitis C virus (HCV) infection. We investigated serum expression of 13 miRNAs in 384 patients with HCV-related chronic liver disease (192 with HCC, 96 with liver cirrhosis (LC), and 96 with chronic hepatitis C (CHC)) in addition to 96 healthy participants enrolled as a control group. The miRNA expression was performed using real-time quantitative PCR-based SYBR Green custom miRNA arrays. The area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic performance of miRNA panels for early detection of HCC. Using miRNA panel of miR-122, miR-885-5p, and miR-29b with alpha fetoprotein (AFP) provided high diagnostic accuracy (AUC = 1) for early detection of HCC in normal population while using miRNA panel of miR-122, miR-885-5p, miR-221, and miR-22 with AFP provided high diagnostic accuracy (AUC = 0.982) for early detection of HCC in LC patients. However, using miRNA panel of miR-22 and miR-199a-3p with AFP provided high diagnostic accuracy (AUC = 0.988) for early detection of HCC in CHC patients. We identified serum miRNA panels that could have a considerable clinical use in early detection of HCC in both normal population and high-risk patients.

Early detection of hepatocellular carcinoma co-occurring with hepatitis C virus infection: A mathematical model.

AIM: To develop a mathematical model for the early detection of hepatocellular carcinoma (HCC) with a panel of serum proteins in combination with α-fetoprotein (AFP). METHODS: Serum levels of interleukin (IL)-8, soluble intercellular adhesion molecule-1 (sICAM-1), soluble tumor necrosis factor receptor II (sTNF-RII), proteasome, and ß-catenin were measured in 479 subjects categorized into four groups: (1) HCC concurrent with hepatitis C virus (HCV) infection (n = 192); (2) HCV related liver cirrhosis (LC) (n = 96); (3) Chronic hepatitis C (CHC) (n = 96); and (4) Healthy controls (n = 95). The R package and different modules for binary and multi-class classifiers based on generalized linear models were used to model the data. Predictive power was used to evaluate the performance of the model. Receiver operating characteristic curve analysis over pairs of groups was used to identify the best cutoffs differentiating the different groups. RESULTS: We revealed mathematical models, based on a binary classifier, made up of a unique panel of serum proteins that improved the individual performance of AFP in discriminating HCC patients from patients with chronic liver disease either with or without cirrhosis. We discriminated the HCC group from the cirrhotic liver group using a mathematical model (-11.3 + 7.38 × Prot + 0.00108 × sICAM + 0.2574 × ß-catenin + 0.01597 × AFP) with a cutoff of 0.6552, which achieved 98.8% specificity and 89.1% sensitivity. For the discrimination of the HCC group from the CHC group, we used a mathematical model [-10.40 + 1.416 × proteasome + 0.002024 × IL + 0.004096 × sICAM-1 + (4.251 × 10(-4)) × sTNF + 0.02567 × ß-catenin + 0.02442 × AFP] with a cutoff 0.744 and achieved 96.8% specificity and 89.7% sensitivity. Additionally, we derived an algorithm, based on a binary classifier, for resolving the multi-class classification problem by using three successive mathematical model predictions of liver disease status. CONCLUSION: Our proposed mathematical model may be a useful method for the early detection of different statuses of liver disease co-occurring with HCV infection.

miR-34a: Multiple Opposing Targets and One Destiny in Hepatocellular Carcinoma.

Background and Aims: The role of miR-34a in hepatocellular carcinoma (HCC) is controversial and several unresolved issues remain, including its expression pattern and relevance to tumor etiology, tumor stage and prognosis, and finally, its impact on apoptosis. Methods: miR-34a expression was assessed in hepatitis C virus (HCV)-induced non-metastatic HCC tissues by RT-Q-PCR. Huh-7 cells were transfected with miR-34a mimics and the impact of miR-34a was examined on 84 pro-apoptotic/anti-apoptotic genes using PCR array; its net effect was tested on cell viability via MTT assay. Results: miR-34a expression was up-regulated in HCC tissues. Moreover, miR-34a induced a large set of pro-apoptotic/anti-apoptotic genes, with a net result of triggering apoptosis and repressing cell viability. Conclusions: HCC-related differential expression of miR-34a could be etiology-based or stage-specific, and low expression of miR-34a may predict poor prognosis. This study's findings also emphasize the role of miR-34a in apoptosis.

Gene expression profiling of non-hodgkin lymphomas.

BACKGROUND: Chromosomal translocations are genetic aberrations associated with specific non-Hodgkin lymphoma (NHL) subtypes. This study investigated the differential gene expression profile of Egyptian NHL cases based on a microarray approach. MATERIALS AND METHODS: The study included tissue samples from 40 NHL patients and 20 normal lymph nodes used as controls. Total RNA was extracted and used for cDNA microarray assays. The quantitative real time polymerase chain reaction was used to identify the aberrantly expressed genes in cancer. RESULTS: Significant associations of 8 up-regulated and 4 down-regulated genes with NHL were observed. Aberrant expression of a new group of genes not reported previously was apparent, including down-regulated NAG14 protein, 3 beta hydroxy-delta 5-c27 steroid oxi-reductase, oxi-glutarate dehydrogenase (lipo-amide), immunoglobulin lambda like polypeptide 3, protein kinase x linked, Hmt1, and caveolin 2 Tetra protein. The up-regulated genes were Rb binding protein 5, DKFZP586J1624 protein, protein kinase inhibitor gamma, zinc finger protein 3, choline ethanolamine phospho-transferase CEPT1, protein phosphatase, and histone deacetylase-3. CONCLUSIONS: This study revealed that new differentially expressed genes that may be markers for NHL patients and individuals who are at high risk for cancer development.