Genetic testing and genomic analysis: A debate on ethical, social and legal issues in the Arab world with a focus on Qatar

In 2013 both Saudi Arabia and Qatar launched genome projects with the aim of providing information for better diagnosis, treatment and prevention of diseases and, ultimately to realize personalized medicine by sequencing hundred thousands samples. These population based genome activities raise a series of relevant ethical, legal and social issues general, related to the specific population structure as well as to the Islamic perspective on genomic analysis and genetic testing. To contribute to the debate, the Authors after reviewing the existing literature and taking advantage of their professional experience in the field and in the geographic area, discuss and provide their opinions. In particular, the Authors focus on the impact of consanguinity on population structure and disease frequency in the Arab world, on genetic testing and genomic analysis (i.e. technical aspects, impact, etc.) and on their regulations. A comparison between the Islamic perspective and the ethical, social and legal issues raised in other population contexts is also carried. In conclusion, this opinion article with an up-to-date contribution to the discussion on the relevance and impact of genomic analysis and genetic testing in the Arab world, might help in producing specific national guidelines on genetic testing and genomic analysis and help accelerate the implementation and roll out of genome projects in Muslim countries and more specifically in Qatar, and other countries of the Gulf

Protein Alterations in Infiltrating Ductal Carcinomas of the Breast as Detected by Nonequilibrium pH Gradient Electrophoresis and Mass Spectrometry

Improvement of breast-cancer detection through the identification of potential cancer biomarkers is considered as a promising strategy for effective assessment of the disease. The current study has used nonequilibrium pH gradient electrophoresis with subsequent analysis by mass spectrometry to identify protein alterations in invasive ductal carcinomas of the breast from Tunisian women. We have identified multiple protein alterations in tumor tissues that were picked, processed, and unambiguously assigned identities by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF). The proteins identified span a wide range of functions and are believed to have potential clinical applications as cancer biomarkers. They include glycolytic enzymes, molecular chaperones, cytoskeletal-related proteins, antioxydant enzymes, and immunologic related proteins. Among these proteins, enolase 1, phosphoglycerate kinase 1, deoxyhemoglobin, Mn-superoxyde dismutase, α-B-crystallin, HSP27, Raf kinase inhibitor protein, heterogeneous nuclear ribonucleoprotein A2/B1, cofilin 1, and peptidylprolyl isomerase A were overexpressed in tumors compared with normal tissues. In contrast, the IGHG1 protein, the complement C3 component C3c, which are two newly identified protein markers, were downregulated in IDCA tissues

Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes

Background: Mutated and non-mutated genes interact to drive cancer growth and metastasis. While research has focused on understanding the impact of mutated genes on cancer biology, understanding non-mutated genes that are essential to tumor development could lead to new therapeutic strategies. The recent advent of high-throughput whole genome sequencing being applied to many different samples has made it possible to calculate if genes are significantly non-mutated in a specific cancer patient cohort. Methods: We carried out random mutagenesis simulations of the human genome approximating the regions sequenced in the publicly available Cancer Growth Atlas Project for ovarian cancer (TCGA-OV). Simulated mutations were compared to the observed mutations in the TCGA-OV cohort and genes with the largest deviations from simulation were identified. Pathway analysis was performed on the non-mutated genes to better understand their biological function. We then compared gene expression, methylation and copy number distributions of non-mutated and mutated genes in cell lines and patient data from the TCGA-OV project. To directly test if non-mutated genes can affect cell proliferation, we carried out proof-of-concept RNAi silencing experiments of a panel of nine selected non-mutated genes in three ovarian cancer cell lines and one primary ovarian epithelial cell line. Results: We identified a set of genes that were mutated less than expected (non-mutated genes) and mutated more than expected (mutated genes). Pathway analysis revealed that non-mutated genes interact in cancer associated pathways. We found that non-mutated genes are expressed significantly more than mutated genes while also having lower methylation and higher copy number states indicating that they could be functionally important. RNAi silencing of the panel of non-mutated genes resulted in a greater significant reduction of cell viability in the cancer cell lines than in the non-cancer cell line. Finally, as a test case, silencing ANKLE2, a significantly non-mutated gene, affected the morphology, reduced migration, and increased the chemotherapeutic response of SKOV3 cells. Conclusion: We show that we can identify significantly non-mutated genes in a large ovarian cancer cohort that are well-expressed in patient and cell line data and whose RNAi-induced silencing reduces viability in three ovarian cancer cell lines. Targeting non-mutated genes that are important for tumor growth and metastasis is a promising approach to expand cancer therapeutic options.We would like to thank Weill Cornell Medicine in Qatar (WCM-Q) and the Qatar National Leadership Program (QNLP) for research support. We would also like to thank the WCM-Q Advanced Computing Division for computing time and software support. Finally, we would like to thank colleagues and reviewers for experimental support and critical discussions. This study was made possible by JSREP grant 4-011-1-003 from the Qatar National Research Fund (a member of Qatar Foundation) and the QF Leadership program. The statements made herein are solely the responsibility of the author[s]. The funders had no role in the design of the study or in the collection, analysis, and interpretation of data and in writing the manuscript.Scopu

Genome-Wide Association Studies (GWAS) breast cancer susceptibility loci in Arabs: susceptibility and prognostic implications in Tunisians

Genome-wide Association Studies (GWAS) revealed novel genetic markers for breast cancer susceptibility. But little is known about the risk factors and molecular events associated with breast cancer in Arab Population. Therefore, we designed a broad study to investigate the susceptibility and prognostic implications of the GWAS breast cancer loci in the Tunisian population. In a cohort of 640 unrelated patients with breast cancer and 371 healthy control subjects, we characterized the variation of 9 single nucleotide polymorphisms (SNPs), namely rs1219648, rs2981582; rs8051542, rs12443621, and rs3803662; rs889312; rs3817198; rs13387042 and rs13281615. Only 5 out of 9 GWAS breast cancer loci were found to be significantly associated with breast cancer in Tunisians: The rs1219648 (G vs. A allele: OR = 1.36, P = 1 × 10(−3)) and rs2981582 (A vs. G allele: OR = 1.55, P = 3 × 10(−6)) of FGFR2 gene; the rs8051542 of the TNRC9 gene (T vs. C allele: OR = 1.40, P = 4 × 10(−4)); the rs889312 of the MAP3K1 gene (C vs. A allele: OR = 1.33, P = 3 × 10(−3)) and the rs13281615 located on 8q24 (G vs. A allele: OR = 1.21, P = 0.03). Homozygous variant genotypes of rs2981582 were strongly related to lymph node negative breast cancer (OR = 3.33, P = 6 × 10(−7)) and the minor allele of rs2981582 was associated with increased risk of ER+ tumors (OR = 1.57, P = 0.02; OR = 2.15, P = 0.001, for heterozygous and homozygous variant genotypes, respectively) and increased risk of distant metastasis development (OR = 2.30, P = 4 × 10(−3); OR = 3.57, P = 6 × 10(−5), for heterozygous and homozygous variant genotypes, respectively) in a dose dependent manner. The association for rs8051542 was stronger for high-grade SBR tumors (OR = 2.54, P = 2 × 10(−4)). GG genotype of rs13387042 on 2q35 showed a significant association with the risk of developing distant metastasis (OR = 1.94, P = 0.02). The G allele of rs1219648 in FGFR2 and the A allele of rs13387042 on 2q35 indicated a better prognosis by showing a significantly higher overall survival rates (P = 0.013 and P = 0.005, respectively). In conclusion, GWAS breast cancer FGFR2, TNRC9, MAP3K1, and 8q24 loci are associated with an increased risk of breast cancer and genetic variation in FGFR2 gene may predict the aggressiveness of breast cancer in Tunisians. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-012-2202-6) contains supplementary material, which is available to authorized users

Associations between HLA Class I alleles and the prevalence of nasopharyngeal carcinoma (NPC) among Tunisians

The high prevalence of nasopharyngeal cancer (NPC) in Southern Asia and Mediterranean Northern Africa suggests genetic predisposition among other factors. While Human Leukocyte Antigen (HLA) haplotypes have been conclusively associated with NPC predisposition in Asians, Northern African Maghrebians have been less intensely studied. However, low resolution serological methods identified weak positive associations with HLA-B5, B13 and B18 and a negative with HLA-B14. Using sequence based typing (SBT), we performed a direct comparison of HLA class I frequencies in a cohort of 136 Tunisian patients with NPC matched for gender, age and geographical residence to 148 normal Tunisians. The bimodal age distribution of NPC in Maghrebians was also taken into account. HLA frequencies in normal Tunisians were also compared with those of Northern Moroccan Berbers (ME) to evaluate whether the Tunisian population in this study could be considered representative of other Maghrebian populations. HLA-B14 and -Cw08 were negatively associated with NPC (odd ratio = 0.09 and 0.18 respectively, Fisher p2-value = 0.0001 and = 0.003). Moreover, positive associations were observed for HLA-B-18, -B51 (split of -B5) and -B57 (p2-value < 0.025 in all) confirming previous findings in Maghrebs. The HLA-B14/Cw*08 haplotype frequency (HF) was 0.007 in NPC patients compared to 0.057 in both Tunisian (OR = 0.12; p2-value = 0.001) and Moroccan controls. This study confirms several previous associations noted by serologic typing between HLA class I alleles and the prevalence of NPC in Maghrebians populations. In addition, we identified a putative haplotype rare in Tunisian patients with NPC that may serve as a genetic marker for further susceptibility studies

The stable traits of melanoma genetics: an alternate approach to target discovery

<p>Abstract</p> <p>Background</p> <p>The weight that gene copy number plays in transcription remains controversial; although in specific cases gene expression correlates with copy number, the relationship cannot be inferred at the global level. We hypothesized that genes steadily expressed by 15 melanoma cell lines (CMs) and their parental tissues (TMs) should be critical for oncogenesis and their expression most frequently influenced by their respective copy number.</p> <p>Results</p> <p>Functional interpretation of 3,030 transcripts concordantly expressed (Pearson's correlation coefficient p-value < 0.05) by CMs and TMs confirmed an enrichment of functions crucial to oncogenesis. Among them, 968 were expressed according to the transcriptional efficiency predicted by copy number analysis (Pearson's correlation coefficient p-value < 0.05). We named these genes, "genomic delegates" as they represent at the transcriptional level the genetic footprint of individual cancers. We then tested whether the genes could categorize 112 melanoma metastases. Two divergent phenotypes were observed: one with prevalent expression of cancer testis antigens, enhanced cyclin activity, WNT signaling, and a Th17 immune phenotype (Class A). This phenotype expressed, therefore, transcripts previously associated to more aggressive cancer. The second class (B) prevalently expressed genes associated with melanoma signaling including <it>MITF</it>, melanoma differentiation antigens, and displayed a Th1 immune phenotype associated with better prognosis and likelihood to respond to immunotherapy. An intermediate third class (C) was further identified. The three phenotypes were confirmed by unsupervised principal component analysis.</p> <p>Conclusions</p> <p>This study suggests that clinically relevant phenotypes of melanoma can be retraced to stable oncogenic properties of cancer cells linked to their genetic back bone, and offers a roadmap for uncovering novel targets for tailored anti-cancer therapy.</p

An immunologic portrait of cancer

The advent of high-throughput technology challenges the traditional histopathological classification of cancer, and proposes new taxonomies derived from global transcriptional patterns. Although most of these molecular re-classifications did not endure the test of time, they provided bulk of new information that can reframe our understanding of human cancer biology. Here, we focus on an immunologic interpretation of cancer that segregates oncogenic processes independent from their tissue derivation into at least two categories of which one bears the footprints of immune activation. Several observations describe a cancer phenotype where the expression of interferon stimulated genes and immune effector mechanisms reflect patterns commonly observed during the inflammatory response against pathogens, which leads to elimination of infected cells. As these signatures are observed in growing cancers, they are not sufficient to entirely clear the organism of neoplastic cells but they sustain, as in chronic infections, a self-perpetuating inflammatory process. Yet, several studies determined an association between this inflammatory status and a favorable natural history of the disease or a better responsiveness to cancer immune therapy. Moreover, these signatures overlap with those observed during immune-mediated cancer rejection and, more broadly, immune-mediated tissue-specific destruction in other immune pathologies. Thus, a discussion concerning this cancer phenotype is warranted as it remains unknown why it occurs in immune competent hosts. It also remains uncertain whether a genetically determined response of the host to its own cancer, the genetic makeup of the neoplastic process or a combination of both drives the inflammatory process. Here we reflect on commonalities and discrepancies among studies and on the genetic or somatic conditions that may cause this schism in cancer behavior

CrossLink: a novel method for cross-condition classification of cancer subtypes

BACKGROUND: We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. METHODS: To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. RESULTS: We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. CONCLUSIONS: A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms