Focus on 16p13.3 Locus in colon cancer

Background : With one million new cases of colorectal cancer (CRC) diagnosed annually in the world, CRC is the third most commonly diagnosed cancer in the Western world. Patients with stage I-III CRC can be cured with surgery but are at risk for recurrence. Colorectal cancer is characterized by the presence of chromosomal deletions and gains. Large genomic profiling studies have however not been conducted in this disease. The number of a specific genetic aberration in a tumour sample could correlate with recurrence-free survival or overall survival, possibly leading to its use as biomarker for therapeutic decisions. At this point there are not sufficient markers for prediction of disease recurrence in colorectal cancer, which can be used in the clinic to discriminate between stage II patients who will benefit from adjuvant chemotherapy. For instance, the benefit of adjuvant chemotherapy has been most clearly demonstrated in stage III disease with an approximately 30 percent relative reduction in the risk of disease recurrence. The benefits of adjuvant chemotherapy in stage II disease are less certain, the risk for relapse is much smaller in the overall group and the specific patients at risk are hard to identify. Materials and Methods : In this study, array-comparative genomic hybridization analysis (array-CGH) was applied to study high-resolution DNA copy number alterations in 93 colon carcinoma samples. These genomic data were combined with parameters like KRAS mutation status, microsatellite status and clinicopathological characteristics. Results : Both large and small chromosomal losses and gains were identified in our sample cohort. Recurrent gains were found for chromosome 1q, 7, 8q, 13 and 20 and losses were mostly found for 1p, 4, 8p, 14, 15, 17p, 18, 21 and 22. Data analysis demonstrated that loss of chromosome 4 is linked to a worse prognosis in our patients series. Besides these alterations, two interesting small regions of overlap were identified, which could be associated with disease recurrence. Gain of the 16p13.3 locus (including the RNA binding protein, fox-1 homolog gene, RBFOX1) was linked with a worse recurrence-free survival in our patient cohort. On the other hand, loss of RBFOX1 was only found in patients without disease recurrence. Most interestingly, above mentioned characteristics were also found in stage II patients, for whom there is a high medical need for the identification of new prognostic biomarkers. Conclusions : In conclusion, copy number variation of the 16p13.3 locus seems to be an important parameter for prediction of disease recurrence in colon cancer

The microRNA body map : dissecting microRNA function through integrative genomics

While a growing body of evidence implicates regulatory miRNA modules in various aspects of human disease and development, insights into specific miRNA function remain limited. Here, we present an innovative approach to elucidate tissue-specific miRNA functions that goes beyond miRNA target prediction and expression correlation. This approach is based on a multi-level integration of corresponding miRNA and mRNA gene expression levels, miRNA target prediction, transcription factor target prediction and mechanistic models of gene network regulation. Predicted miRNA functions were either validated experimentally or compared to published data. The predicted miRNA functions are accessible in the miRNA bodymap, an interactive online compendium and mining tool of high-dimensional newly generated and published miRNA expression profiles. The miRNA bodymap enables prioritization of candidate miRNAs based on their expression pattern or functional annotation across tissue or disease subgroup. The miRNA bodymap project provides users with a single one-stop data-mining solution and has great potential to become a community resource

Focal DNA copy number changes in neuroblastoma target MYCN regulated genes

Neuroblastoma is an embryonic tumor arising from immature sympathetic nervous system cells. Recurrent genomic alterations include MYCN and ALK amplification as well as recurrent patterns of gains and losses of whole or large partial chromosome segments. A recent whole genome sequencing effort yielded no frequently recurring mutations in genes other than those affecting ALK. However, the study further stresses the importance of DNA copy number alterations in this disease, in particular for genes implicated in neuritogenesis. Here we provide additional evidence for the importance of focal DNA copy number gains and losses, which are predominantly observed in MYCN amplified tumors. A focal 5 kb gain encompassing the MYCN regulated miR-17,92 cluster as sole gene was detected in a neuroblastoma cell line and further analyses of the array CGH data set demonstrated enrichment for other MYCN target genes in focal gains and amplifications. Next we applied an integrated genomics analysis to prioritize MYCN down regulated genes mediated by MYCN driven miRNAs within regions of focal heterozygous or homozygous deletion. We identified RGS5, a negative regulator of G-protein signaling implicated in vascular normalization, invasion and metastasis, targeted by a focal homozygous deletion, as a new MYCN target gene, down regulated through MYCN activated miRNAs. In addition, we expand the miR-17,92 regulatory network controlling TGFß signaling in neuroblastoma with the ring finger protein 11 encoding gene RNF11, which was previously shown to be targeted by the miR-17,92 member miR-19b. Taken together, our data indicate that focal DNA copy number imbalances in neuroblastoma (1) target genes that are implicated in MYCN signaling, possibly selected to reinforce MYCN oncogene addiction and (2) serve as a resource for identifying new molecular targets for treatment

Performance and Diagnostic Value of Genome-Wide Noninvasive Prenatal Testing in Multiple Gestations.

OBJECTIVE: To evaluate the accuracy and diagnostic value of genome-wide noninvasive prenatal testing (NIPT) for the detection of fetal aneuploidies in multiple gestations, with a focus on dichorionic-diamniotic twin pregnancies. METHODS: We performed a retrospective cohort study including data from pregnant women with a twin or higher-order gestation who underwent genome-wide NIPT at one of the eight Belgian genetic centers between November 1, 2013, and March 1, 2020. Chorionicity and amnionicity were determined by ultrasonography. Follow-up invasive testing was carried out in the event of positive NIPT results. Sensitivity and specificity were calculated for the detection of trisomy 21, 18, and 13 in the dichorionic-diamniotic twin cohort. RESULTS: Unique NIPT analyses were performed for 4,150 pregnant women with a multiple gestation and an additional 767 with vanishing gestations. The failure rate in multiple gestations excluding vanishing gestations ranged from 0% to 11.7% among the different genetic centers. Overall, the failure rate was 4.8%, which could be reduced to 1.2% after single resampling. There were no common fetal trisomies detected among the 86 monochorionic-monoamniotic and 25 triplet cases. Two monochorionic-diamniotic twins had an NIPT result indicative of a trisomy 21, which was confirmed in both fetuses. Among 2,716 dichorionic-diamniotic twin gestations, a sensitivity of 100% (95% CI 74.12-100%) and a specificity of 100% (95% CI 99.86-100%) was reached for trisomy 21 (n=12). For trisomy 18 (n=3), the respective values were 75% (95% CI 30.06-95.44%) sensitivity and 100% (95% CI 99.86-100%) specificity, and for trisomy 13 (n=2), 100% (95% CI 20.65-100%) sensitivity and 99.96% (95% CI 99.79-99.99%) specificity. In the vanishing gestation group, 28 NIPT results were positive for trisomy 21, 18, or 13, with only five confirmed trisomies. CONCLUSION: Genome-wide NIPT performed accurately for detection of aneuploidy in dichorionic-diamniotic twin gestations

Cancer Gene Prioritization for Targeted Resequencing Using FitSNP Scores

Background: Although the throughput of next generation sequencing is increasing and at the same time the cost is substantially reduced, for the majority of laboratories whole genome sequencing of large cohorts of cancer samples is still not feasible. In addition, the low number of genomes that are being sequenced is often problematic for the downstream interpretation of the significance of the variants. Targeted resequencing can partially circumvent this problem; by focusing on a limited number of candidate cancer genes to sequence, more samples can be included in the screening, hence resulting in substantial improvement of the statistical power. In this study, a successful strategy for prioritizing candidate genes for targeted resequencing of cancer genomes is presented. Results: Four prioritization strategies were evaluated on six different cancer types: genes were ranked using these strategies, and the positive predictive value (PPV) or mutation rate within the top-ranked genes was compared to the baseline mutation rate in each tumor type. Successful strategies generate gene lists in which the top is enriched for known mutated genes, as evidenced by an increase in PPV. A clear example of such an improvement is seen in colon cancer, where the PPV is increased by 2.3 fold compared to the baseline level when 100 top fitSNP genes are sequenced. Conclusions: A gene prioritization strategy based on the fitSNP scores appears to be most successful in identifying mutate

Integrated and cross-species omics analyses identify the DNA damage response pathway as an important vulnerable pathway in aggressive neuroblastoma tumors

Introduction: The past decade several high throughput technologies have been developed that allow to profile cancer cells at global omics level. The big datasets generated on these new platforms can significantly help in generating a comprehensive view and understanding of the tumor biology and subsequently fuels studies on the development and implementation of new molecular targeted therapies. For neuroblastoma, a childhood tumor of the developing sympathetic nervous system, new insights on targetable driver genes are currently limited. Methods: We studied neuroblastoma oncogenesis through analysis of big omics datasets using different bio-informatics tools. Available datasets include transcriptomic and genomic profiles of large sets of human and mouse neuroblastoma tumors and cell lines. Using those data (1) we performed dynamic gene expression analysis during tumor initiation and formation in a MYCN driven mouse model, (2) designed and tested an embryonic stem cell (ESC) signature and (3) integrated DNA copy number and m(i)RNA expression data using the Conexic tool in order to identify new driver genes. Results: Most interestingly, these independent 3 data-mining approaches lead to the identification of a converging theme that can be attributed to tumor aggressiveness and which can serve as an important novel target for therapy, i.e. the DNA damage response pathway. First, master regulator analysis of genes involved in MYCN driven neuroblastoma formation identified the transcription factor FOXM1, an important DNA damage regulator. Second, analysis of a m(i)RNA expression ESC signature in data of more than 200 neuroblastoma tumors allowed us to mark a subgroup of neuroblastoma tumors with increased stem cell capabilities which matched with the most agressive subset of neuroblastoma tumors. Remarkably, the top list of coding genes that correlate with the ESC signature was dominated by genes implicated in DNA damage response, including the FOXM1 gene. Third, driver gene identification in aggressive neuroblastoma tumors using the Conexic tool pointed at 2 DNA repair genes that are both known to be regulated by FOXM1. Conclusions: Based on these data, we hypothesize that FOXM1 plays an important central role in the MYC(N) induced DNA damage response and predict that FOXM1 and its downstream DNA repair genes impact on chemotherapy resistance. Currently, we are testing the effect of treatment with a FOXM1 inhibitor on neuroblastoma chemo-resistance

The number of mutated genes in relation to a certain number of top-ranked genes.

<p>Mutation plots showing the amount of genes that need to be sequenced (y-axis) in order to find a certain number of mutated genes (depicted on the x-axis), for the six different tumor types. A: colon cancer; B: pancreas cancer; C: breast cancer; D: ovarian cancer: E: glioblastoma; F: medulloblastoma.</p

Overview of the publically available tumor data sets, used in this study.

*<p> <i>one sample was excluded from this study due to a hypermutated profile caused by chemotherapeutic treatment.</i></p><p> <i>CN: copy number; GE: gene expression.</i></p

PPV plot of the fitSNP strategy for the combined tumor entities.

<p>A PPV plot for the fitSNP strategy, performed on the mutation data of all combined tumor entities, in function of different prioritization value cut-offs.</p