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• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Study EGAS00001001184

• miRNA expression in response to LPS stimulus in macrophages

  Our lab is currently using macrophages as a model system for understanding how genetic variation modulates the response to external environmental stimulus. We want to extend this beyond regular polyadenylated RNA to small RNAs such as miRNAs. This project would cover the costs of a pilot to study miRNA response to LPS stimulus, and will be performed as part of a rotation project in the lab. We will require a small number of miRNA libraries and a single lane of MiSeq

  Dataset EGAD00001002196

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• Sequencing_the_exome_of_12_early_sporadic_human_colorectal_cancers__CRC_

  In the project we sequenced the exomes of tumour from patients with germline mutations in APC i.e. FAP patients. The aim of the study was to determine the load of mutations acquired during the early staged of tumour development in these patients with the aim of determining the rate mutation acquisition.

  Study EGAS00001000358

• ARAF Mutations Confer Resistance to RAF Dimer Inhibitor Belvarafenib in NRAS- and BRAF- Mutant Melanoma

  Belvarafenib, a potent and selective RAF dimer (type II) inhibitor, exhibits clinical activity in BRAFV600E- and NRAS-mutant melanoma patients. Here, we report the first-in-human phase I study investigating maximum tolerated dose, assessing safety and preliminary efficacy of belvarafenib in BRAF- and RAS-mutated advanced solid tumors (NCT02405065, NCT03118817). Through generation of belvarafenib resistant NRAS- mutant melanoma cells and analysis of circulating tumor DNA from patients treated with belvarafenib, we identified novel recurrent mutations in ARAF within the kinase domain. ARAF mutants conferred resistance to belvarafenib in both a dimer- and kinase activity- dependent manner. Belvarafenib induced ARAF mutant dimers, and dimers containing mutant ARAF were active in the presence of inhibitor. ARAF mutations may serve as a general resistance mechanism for RAF dimer inhibitors as the mutants exhibit reduced sensitivity to a panel of type II RAF inhibitors. The combination of RAF plus MEK inhibition may be used to delay ARAF-driven resistance and suggests a rational combination for clinical use. Taken together, our findings reveal specific and compensatory functions for the ARAF isoform and implicate ARAF mutations as a driver of resistance to RAF dimer inhibitors.

  Study EGAS00001005086

• H3Africa - Genomic and Environmental Risk Factors for Cardiometabolic Disease in Africans

  The long-term vision of the AWI-Gen Collaborative Centre (CC) is to build sustainable capacity in Africa for research that leads to an understanding of the interplay between genetic, epigenetic and environmental risk factors for obesity and related cardiometabolic diseases (CMD) in sub-Saharan Africa. The CC will be consolidated under the auspices of the University of the Witwatersrand (Wits) and the International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries (INDEPTH). It will capitalize on the unique strengths of existing longitudinal cohorts, including the urban Soweto and rural Agincourt studies in South Africa (Wits based), and the well established INDEPTH demographic health and surveillance centers in Kenya, Ghana, Burkina Faso and South Africa. The centers offer established infrastructure, trained fieldworkers, long-standing community engagement, and detailed longitudinal phenotypic data, focusing on obesity and cardiometabolic health. Key strengths are harmonized phenotyping across sites, building on strong existing cohorts, and representation of the geographic and social variability of African populations. We aim to: 1. Build sustainable infrastructure (biobanks and laboratories) and capabilities (well characterized population cohorts, genotyping and bioinformatics) for genomic research on the African continent; 2. Understand the genomic architecture of sub-Saharan populations from west, east and south Africa to guide genomic studies (genome sequencing and high throughput SNP and CNV arrays using unrelated individuals and family trios to improve the accuracy of haplotype analyses) and; 3. Investigate the independent and synergistic genomic contributions to body fat distribution (BMI, hip/waist circumference, subcutaneous and visceral fat) in these populations considering the relevant environmental and social contexts (rural/urban communities, quickly transitioning obesity prevalence, differential HIV, TB, and malaria infection histories). We will investigate the effect of obesity and fat distribution on the risk for CMD in the longitudinal cohorts.

  Study EGAS00001002482

• Investigating the Role of Neddylation in the Repair of Topoisomerase I-Mediated DNA Damage in Colorectal Cancer

  Colorectal cancer is one of the most lethal cancers worldwide. First-line chemotherapy for metastatic CRC (mCRC) entails a combination of irinotecan with 5-fluorouracil and leucovorin (FOLFIRI). Irinotecan is a prodrug that is converted within the cell to its active metabolite SN38, a potent TOP1 inhibitor. TOP1 relieves DNA torsional strain arising from DNA metabolism by cleaving one strand of the DNA duplex and forming an enzyme-DNA covalent intermediate that can be trapped by inhibitors. The resulting TOP1 DNA-protein crosslinks (TOP1-DPCs) interfere with replication and transcription and induce cell death if left unrepaired. I have established the role of the ubiquitin-proteasome pathway in TOP1-DPC repair, but it remains unknown how ubiquitylation is activated. One possibility is that collision between advancing replication forks and the DPCs triggers a specific ubiquitin ligase to target DPCs for degradation. The DDB1-CUL4 (Cullin 4)-RBX1 (CRL4) ubiquitin ligase complex performs a salient role in both replication and DNA repair upon its activation by auto-NEDD8 modification (neddylation), but it is unknown whether it plays a role for TOP1-DPC repair. We plan to define the role of neddylation for TOP1-DPC repair during replication and examine irinotecan plus pevonedistat (PEV), a NEDD8-activating enzyme inhibitor in multiple clinical trials, in CRC patient-derived preclinical models including 3D organoids. The three in-house organoids, from which samples have been submitted to dbGaP, were sequenced as a means of verifying their identity as colon cancer organoids, to allow us to investigate the combination of TOP1 inhibitors and PEV and the molecular mechanisms underlying this drug combination in these organoids.

  Study phs003257

• Neoantigen-Targeted CD8+ T-Cell Responses 1 With PD-1 Blockade Therapy

  Background: The primary target of T-cell responses induced against cancer cells are peptides derived from non-synonymous mutations presented by HLA (neoantigens). However, the large diversity of HLA alleles and restricted availability of clinical samples have limited the study of the specificity and the evolution over time of the neoantigen-specific T cell responses induced after treatment with immune checkpoint blockade (ICB) immunotherapy. Methods: We applied a newly developed neoepitope-specific T cell isolation technology to perform a longitudinal landscape analysis of the neoepitope-specific T cells in peripheral blood and tumor from 11 patients with metastatic melanoma; 7 with response and 4 with no response to ICB. Briefly, first using computational prediction, the putative neoantigens in each patient were ranked based on affinity for the patient's HLA and expression levels. Then hundreds of barcoded capture reagents consisting of the patient HLA class I subtypes loaded with the corresponding predicted neoantigen were made and used to isolate neoepitope-specific T cells. Once isolated, the TCRs and the barcodes were sequenced. Finally, the tumor reactivity of the isolated neoepitope-specific TCRs (neoTCRs) was assessed upon co-culture of autologous melanoma cell lines from each patient with primary human T cells expressing the neoTCRs generated using a CRISPR-based non-viral gene editing to replace the endogenous TCRs. Results: The tumor mutation burden ranged between 3507 and 177 for patients with response to therapy and 977 to 31 for patients without response to therapy. We screened a median of 172 predicted neoantigen-HLA per patient across their 6 HLA molecules and isolated neoTCRs in all 11 patients. The number of mutations targeted ranged between 13 and 1. We assessed the neoTCR-tumor reactivity in samples from 3 patients with response and 3 patients without response. 39 of the 62 neoTCRs demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Multiple T cell clonotypes recognized a limited number of mutations in 7 patients with response (median of 41 different neoTCR clonotypes per patient), and the T cell specificities were recurrently detected in the blood and the tumor over time. Samples from 4 patients without response to therapy also demonstrated neoepitope-specific T cell responses in blood and tumor to a similarly restricted number of mutations, but lacked TCR polyclonality (median 6.5 neoTCR clonotypes per patient) and were not recurrently detected in sequential samples. Conclusion: Effective ICB therapy is associated with polyclonal neoepitope-specific T-cell responses in the tumor and blood that recognize a limited number of immunodominant mutations and are recurrently detected over time.

  Study phs003153

• Sudden Death in the Young Case Registry

  Knowledge gaps persist about the incidence of and risk factors for sudden death in the young (SDY). The SDY Case Registry is a collaborative effort between the National Institutes of Health, the Centers for Disease Control and Prevention, and the Michigan Public Health Institute. Its goals are to: (1) describe the incidence of SDY in the United States by using population-based surveillance: (2) compile data from SDY cases to create a resource of information and DNA samples for research; (3) encourage standardized approaches to investigation, autopsy, and categorization of SDY cases; (4) develop partnerships between local, state, and federal stakeholders toward a common goal of understanding and preventing SDY; and (5) support families who have lost loved ones to SDY by providing resources on bereavement and medical evaluation of surviving family members. Built on existing Child Death Review programs and as an expansion of the Sudden Unexpected Infant Death Case Registry, the SDY Case Registry achieves its goals by identifying SDY cases, providing guidance to medical examiners/coroners in conducting comprehensive autopsies, evaluating cases through child death review and an advanced review by clinical specialists, and classifying cases according to a standardized algorithm. The SDY Case Registry also includes a process to obtain informed consent from next-of-kin to save DNA for research, banking, and, in some cases, diagnostic genetic testing. The SDY Case Registry will provide valuable incidence data and will enhance understanding of the characteristics of SDY cases to inform the development of targeted prevention efforts. For cases where informed consent has been obtained for research genomic sequencing has been performed. On these cases genomic data, phenotype information and on a limited number of cases redacted autopsy reports will be available through dbGaP.

  Study phs003221

• PAK4 inhibition improves PD-1 blockade immunotherapy

  Introduction with rationale and aims for study Immune checkpoint blockade therapies have significantly altered the current landscape of cancer treatment. However, this immunotherapy still fails more often than it succeeds. There are now evidences that the lack of tumour infiltration by immune cells is the main mechanism of primary resistance to PD‐1 blockade therapies for cancer. It has been postulated that cancer cell‐intrinsic mechanisms may actively exclude T cells from tumours, suggesting that the finding of actionable molecules that could be inhibited to increase T cell infiltration may synergize with checkpoint inhibitor immunotherapy. With the idea of finding potential drivers of immune exclusion, we performed RNA sequencing analysis of biopsies from melanoma patients and compared the transcriptomic differences of samples that where infiltrated with those that did not have immune infiltration. Methods RNAseq analysis of gene expressions on biopsies from melanoma patients treated with checkpoint blockade were analysed. We focused on the variable of "infiltration: yes or no,", e.g. tumors that were well infiltrated by immune cells with those that kept immune cells out. Sequencing revealed a list of genes whose expression differed between the infiltrated and noninfiltrated tumors. The kinase PAK4 stood out as a good candidate for inhibition treatment in the future as it was consistently enriched in the samples without immune infiltration. To test whether immunotherapy would work better if we deleted PAK4, we first knocked out PAK4, using CRISPR‐Cas9, in the ‐resistant melanoma cell line, B16. Then they injected the melanoma cells into mice and observed that PAK4 KO tumours now responded to PD‐1 blockade. In order to elucidate whether pharmacological inhibition of PAK4 could recapitulate the results observed in the B16 PAK4 KO tumours, we obtained the PAK4 inhibitor, KPT-9274, from Karyopharm Therapeutics. Indeed, inhibiting PAK4 in combination with anti‐PD‐1 immunotherapy significantly slowed the growth of the B16 melanomas more than either drug alone. Results and Conclusions Transcriptomic analysis of melanoma tumors that were well infiltrated by immune cells with those that kept immune cells out revealed a list of genes whose expression differed between the infiltrated and non-infiltrated tumours. The result suggests that p21 activated kinase 4 (PAK4) is enriched in non-responding tumour biopsies with low T cell and dendritic cell infiltration. In addition, PAK4 decreased WNT activity, a signalling pathway that has previously been involved in immune exclusion. In mouse models, genetic deletion of PAK4 increased T cell infiltration and reversed resistance to PD‐1 blockade in a CD8 T cell-dependent manner. Furthermore, combination of with the PAK4 inhibitor, KPT-9274, improved anti‐tumour responses compared to anti‐PD‐1 alone. Therefore, high PAK4 expression is correlated with low T cell and dendritic cell infiltration and lack of response to PD‐1 blockade, which could be reversed with PAK4 inhibition. The data establish a rationale for targeting this kinase with inhibitors in combination with immune checkpoint inhibitors for patients. Future work and data that we can anticipate for this study Oncogenic signalling pathways and specially the WNT signalling pathway, have been associated with lack of immune infiltration and resistance to PD‐1 blockade therapies. Here, we show that PAK4 overcome resistance to PD‐1 blockade while significantly decreases WNT signalling activity. Therefore, it constitutes the first potential druggable target that is able to reverse oncogenic driven immune cell exclusion. However, the fully mechanism whereby PAK4 sensitizes tumours to immunotherapy remains to be fully elucidated. It is necessary to address whether PAK4 inhibition overcomes resistance through WNT signalling inhibition or if other signalling pathways are involved in the observed phenotype.

  Study phs001919