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• H3Africa - An integrated approach to the identification of genetic determinants of susceptibility to trypanosomiasis

  The objective of the TrypanoGEN project is to discover genetic variants associated with different responses to sleeping sickness infection. The project was designed in two phases:Phase 1) Variant discovery; 222 samples were sequenced to approximately 10X coverage on an Illumina 2500 with 2x150bp reads, at the University of Liverpool Center for Genomic Research. In addition, 77 samples from Cameroon and Zambia were sequenced to approximately 30X Coverage at Baylor College of Medicine. The sequenced reads were mapped onto the 1000 genomes project human_g1k_v37_decoy reference genome using BWA. The SNP calling on all the samples was done using the genome analysis tool kit GATK v3.4. Samples were selected from seven populations where Trypanosomiasis is endemic: Nilo-Saharan speakers from North-West Uganda and Niger-Congo speakers from South-East Uganda, DRC, Ivory Coast, Guinea, Cameroon and Zambia. The samples included 182 controls, 97 cases, 17 latent infections and 3 suspect cases. Phase 2) Variants discovered in Phase 1 will be used in the development of the H3Africa SNP chip. This chip will then be used in a GWAS study to identify variants associated with trypanosomiasis.

  Study EGAS00001002602

• Genetic Epidemiology Network of Salt Sensitivity (GenSalt)

  The GenSalt study is aimed at identifying novel genes which interact with the effect of dietary sodium and potassium intake or cold pressor on blood pressure.

  Study phs000784

• Pilot_experiment_on_functional_genomics_in_osteoarthritis_RNA

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of transcription (RNASeq) The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data.

  Study EGAS00001001203

• Clonal Evolution of Pre-Leukemic Hematopoietic Stem Cells Precedes Human Acute Myeloid Leukemia

  Acute myeloid leukemia is an aggressive clonal malignancy of the bone marrow that is the direct result of sequential acquisition of mutations in a single lineage of cells. In this study, we investigate a model in which this mutational acquisition occurs serially in long-lived self-renewing hematopoietic stem cells eventually resulting in frank acute myeloid leukemia. Coding mutations in multiple AML patients were identified using exome sequencing followed by sanger sequencing validation. The level of these mutations was then assessed in residual hematopoietic stem cells from each patient using targeted deep sequencing. These population-level estimates of mutant allele burden were then validated in single cell assays targeted to the identified mutations. This allowed for determination of the order of acquisition of the mutations that preceded the development of the leukemia. The results of this study identify pre-leukemic hematopoietic stem cell clones that could contribute to patient relapse and outcome.

  Study phs000549

• Pharmacogenomic Interactions in Glioblastoma Cell Line Models

  Glioblastoma (GBM) is a lethal disease without effective treatments. To advance toward effective therapeutic approaches that are biomarker-driven, there is a need for new targeted agents and to develop accurate preclinical models that encompass its cellular and molecular diversity. Historical cell line models poorly represent molecular diversity of GBMs, so we developed a living tissue bank encompassing 103 patient-derived GBM cell lines (PDGCLs) as a platform for preclinical pharmacogenomic investigation at scale. Thirty-four PDGCLs were submitted to a comprehensive molecular characterization of copy number alterations and mutations using whole exome sequencing (WES) and gene expression (microarrays), and tested against a panel of 390 small molecules at sixteen different duplicated concentrations. After integrating and systematically correlating molecular alterations with drug sensitivities, we yielded 8,083,140 pharmacogenomic interactions, and discovered novel drug and biomarker combinations which help to prioritize highly effective novel candidate treatments in GBM. Our findings demonstrate the utility of deep characterization of large numbers of models from a single disease to detect complex predictors of compound sensitivity, and indicate novel therapeutic approaches for a large fraction of patients with GBM.

  Study phs001793

• Mechanism and targeted therapy of Vemurafenib-Resistant Hairy-Cell Leukemia

  The discovery of the BRAF V600E mutation in almost all cases of hairy-cell leukemia has led to the widespread adoption of the BRAF inhibitor vemurafenib for treatment of chemotherapy-resistant cases. Impressive responses are reported; however, acquired resistance is common. Whilst diverse mechanisms of vemurafenib resistance have been elucidated in melanoma, the basis of resistance in HCL is unclear. Here we apply whole genome and deep targeted sequencing to investigate resistance mechanisms and potential therapeutic strategies in a patient with aquired resistance to vemurafenib.

  Dataset EGAD00001003923

• Mechanism and targeted therapy of Vemurafenib-Resistant Hairy-Cell Leukemia

  The discovery of the BRAF V600E mutation in almost all cases of hairy-cell leukemia has led to the widespread adoption of the BRAF inhibitor vemurafenib for treatment of chemotherapy-resistant cases. Impressive responses are reported; however, acquired resistance is common. Whilst diverse mechanisms of vemurafenib resistance have been elucidated in melanoma, the basis of resistance in HCL is unclear. Here we apply whole genome and deep targeted sequencing to investigate resistance mechanisms and potential therapeutic strategies in a patient with aquired resistance to vemurafenib.

  Dataset EGAD00001003924

• Exome sequencing of synchronous colorectal cancers

  Approximately 4% of colorectal cancer (CRC) patients have at least two simultaneous cancers in the colon. Due to the shared environment, these synchronous CRCs (SCRCs) provide a unique setting to study colorectal carcinogenesis. Understanding whether these tumors are genetically similar or distinct is essential when designing therapeutic approaches. We performed exome sequencing of 47 primary cancers and corresponding normal samples from 23 patients. Additionally, we carried out a comprehensive mutational signature analysis to assess whether tumors had undergone similar mutational processes and the first immune cell score analysis (IS) of SCRC to analyze the interplay between immune cell invasion and mutation profile in both lesions of an individual. The tumor pairs shared only few mutations, favoring different mutations in known CRC genes and signaling pathways, and displayed variation in their signature content. Two tumor pairs had discordant mismatch repair statuses. In majority of the pairs, IS varied between primaries. Differences were not explained by any clinicopathological variable or mutation burden.

  Study EGAS00001003474

• Single-cell analysis for metastatic gastric adenocarcinoma

  Intra-tumoral heterogeneity (ITH) is the fundamental property of cancer, however, the origins of ITH remain poorly understood. Here we performed single-cell RNA sequencing of peritoneal carcinomatosis (PC) from patients with advanced gastric adenocarcinoma (GAC), constructed a transcriptome map of 45,048 PC cells, profiled the transcriptome states of diverse tumor cell lineages and types, incisively explored ITH of PC tumor cells, and identified significant correlates with patient survival.

  Study EGAS00001004443

• Autoimmune-wide landscape of circulating CD4+ T cells unveils disease-specific heritability and phenotypic changes

  While CD4+ T cells are involved in autoimmunity, how they contribute to the pathogenesis is unclear due to their cellular heterogeneity. Here, to analyze the heterogeneity, we utilized decomposition-based transcriptome characterization for evaluating non-discrete subsets of CD4+ T cells in addition to canonical clustering strategies. This approach identified 12 independent transcriptional gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of the canonical clustering.

  Study JGAS000578

• A super-enhancer associated with CD47 links pro-inflammatory signaling to CD47 upregulation in breast cancer

  CD47 is a cell surface molecule that inhibits phagocytosis of cells that express it by binding to its receptor, SIRPα, on macrophages and other immune cells. CD47 is expressed at different levels in normal cells, however, in cancer cells, CD47 transcript and protein expression is aberrantly increased. Here we sought to uncover the regulators of CD47 transcription, including active enhancers that increase its aberrant expression in cancer cells, in order to reveal mechanisms by which different neoplastic cells generate this dominant 'don't eat me' signal. Enhancers are genomic regions, often referred to as "switches", that can turn on or off the transcription of target genes. Recently the discovery of super-enhancers (SEs) has given more insight into the regulatory architecture of key genes that are highly expressed in a specific cell type, during a particular developmental stage or in disease. By analyzing the CD47 regulatory genomic landscape, we discovered: i) A distinct super-enhancer (SE) is associated with CD47 upregulation in breast cancer cells ii) Disruption of CD47 SEs by using the BRD4 inhibitor JQ1 robustly reduces CD47 gene expression; and iii) The TNF-NFKB1 signaling pathway is directly involved in the regulation of CD47 by interacting with a distal downstream constituent enhancer located within a CD47-associated SE specific to breast cancer. Our results describe a novel mechanism that cancer cells have evolved to drive CD47 overexpression to escape immune surveillance.

  Study phs001264

• Single cell RNA seq of breast cancer stem cells

  RNA sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations' mRNA will be detected. With respect to breast cancer, it has been also reported that cancer cells can sub-gropued into cancer stem cells and non-cancer stem cells. Although the mRNA expressions' difference between this two groups has been profoundly investigated, whether each group is composed by unique cell or not is yet to be elucidated. Since cancer stem cells are the thought to be the major contributor of metastasis and/or recurrence, we focused on cancer stem cells in this study. We separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. Thereafter, we sequenced mRNA of cancer stem cells in single cell resolution. From this result, we examined whether these cells can be sub-grouped or not.

  Study JGAS000305

• RB1 Gene Inactivation by Chromothripsis in Human Retinoblastoma

  Retinoblastoma is a rare childhood cancer of the developing retina. Most retinoblastomas initiate with biallelic inactivation of the RB1 gene through diverse mechanisms including point mutations, nucleotide insertions, deletions, loss of heterozygosity and promoter hypermethylation. Recently, a novel mechanism of retinoblastoma initiation was proposed. Gallie and colleagues discovered that a small proportion of retinoblastomas lack RB1 mutations and had MYCN amplification [1]. In this study, we identified recurrent chromosomal, regional and focal genomic lesions in 94 primary retinoblastomas with their matched normal DNA using SNP 6.0 chips. We also analyzed the RB1 gene mutations and compared the mechanism of RB1 inactivation to the recurrent copy number variations in the retinoblastoma genome. In addition to the previously described focal amplification of MYCN and deletions in RB1 and BCOR, we also identified recurrent focal amplification of OTX2, a transcription factor required for retinal photoreceptor development. We identified 10 retinoblastomas in our cohort that lacked RB1 point mutations or indels. We performed whole genome sequencing on those 10 tumors and their corresponding germline DNA. In one of the tumors, the RB1 gene was unaltered, the MYCN gene was amplified and RB1 protein was expressed in the nuclei of the tumor cells. In addition, several tumors had complex patterns of structural variations and we identified 3 tumors with chromothripsis at the RB1 locus. This is the first report of chromothripsis as a mechanism for RB1 gene inactivation in cancer.

  Study EGAS00001000598

• 2014_Lung_sq_WES

  Purpose Lung squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. Currently, no targeted-therapeutics are approved for treatment of this cancer, largely due to lack of systematic understanding of the molecular parthenogenesis of the disease. To identify therapeutic targets and comparatively analyze them in lung SqCC, we probed somatic alterations of Korean lung SqCC. Patients and Methods We performed massively parallel whole-exome sequencing of 104 Korean lung SqCC patients’ samples with matched normal samples. In addition, copy number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.

  Study EGAS00001002844

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• Integrated genetic and epigenetic analysis of myxofibrosarcoma

  Myxofibrosarcoma (MFS) is a common histological subtype of adult soft tissue sarcoma characterized by an infiltrative growth pattern and a high propensity for local recurrence. We underwent whole exome sequencing, RNA sequencing, and methylation analysis of MFS.

  Study EGAS00001002889

• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

  Blog discover-cancer-image-europe

• Genome wide association study on coronary heart disease in patients with familial hypercholesterolemia

  Mutations in the low-density lipoprotein receptor (LDLR) gene cause familial hypercholesterolemia (FH), a disorder characterized by coronary heart disease (CHD) at young age. We aimed to apply an extreme sampling method to enhance the statistical power to identify novel genetic risk variants for CHD in individuals with FH. We selected cases and controls with an extreme contrast in CHD risk from 17 000 FH patients from the Netherlands, whose functional LDLR mutation was unequivocally established. The genome-wide association (GWA) study was performed on 249 very young FH cases with CHD and 217 old FH controls without CHD (above 65 years for males and 70 years of age for females) using the Illumina HumanHap 550K chip. In the next stage, two independent samples (one from the Netherlands and one from Italy, Norway, Spain, and the United Kingdom) of FH patients were used as replication samples. In the initial GWA analysis we identified 29 independent single nucleotide polymorphisms (SNPs) with suggestive associations with premature CHD (p<1×10-4). We examined the association of these SNPs with CHD risk in the replication samples. After Bonferroni correction, none of the SNPs either replicated or reached genome-wide significance after combining the discovery and replication samples. Therefore, we conclude that the genetics of CHD risk in FH is complex and even applying an ‘extreme genetics’ approach we did not identify new genetic risk variants. Most likely, this method is not as effective in leveraging effect size as anticipated, and may therefore not lead to significant gains in statistical power. (NB submitten and conditionally accepted at European Journal of Human Genetics-please use abstract only for internal review until submission complete)

  Study EGAS00001000734

• PARADIGM: Combined ctDNA and serum PSA for dynamic monitoring of metastatic prostate cancer starting first-line treatment

  The prognosis of newly-diagnosed metastatic prostate cancer is highly variable. The PARADIGM prospective cohort study evaluated predictors of survival in blood collected at the start of each of the first six treatment cycles from 114 high-volume metastatic patients starting androgen deprivation therapy combined with docetaxel or an androgen receptor pathway inhibitor.

  Study EGAS50000001357

• National Cancer Institute (NCI) Genome Wide Association Study (GWAS) of Lung Cancer in Never Smokers

  A genomewide study of lung cancer in never smokers Abstract and specific aims In the United States, lung cancer incidence and mortality rates have been steadily declining over the past decade, following decline in the prevalence of tobacco smoking. However, lung cancer remains the leading cause of cancer death, killing more patients than breast, colon, and prostate cancers combined. Although tobacco smoke is the predominant risk factor for development of lung cancer, some patients develop the disease without a history of tobacco smoking. About 10 - 15% of all lung cancers occur in lilfetime never smokers. This figure will increase as the proportion of never smokers increases in the population. Even at present rates, lung cancer in never smokers, if considered a separate disease, is 6th to 8th top cause of cancer death. The growing number of never smokers in the USA and other countries emphasizes the importance of understanding the epidemiology and biology underlying lung cancer in this group. Genetic polymorphisms associated with the risk of lung cancer in never smokers are expected to overlap with those associated with the risk of lung cancer in ever smokers only partially. Epidemiological, molecular and clinical data suggest that molecular mechanisms of LC may differ in smokers and non-smokers, implying that lung cancer in never smokers is a different disease compared to the lung cancer in smokers. One can expect that there should be stronger genetic component in the control lung cancer in never smokers because effects of the genetic factors in never smokers are unmasked by the lack of tobacco smoke exposure. The genetic epidemiology of lung cancer in never smokers has not been well explored, largely because of difficulties in accruing the needed sample size for association studies. We propose a multicenter (total 14 sites from the US and Europe) genomewide association study of lung cancer in never smokers with the following specific aims: Aim 1: To identify candidate SNPs influencing risk for lung cancer in never smokers using Discovery sample. In the Discovery phase we will genotype 1256 Caucasian cases and 1365 age- and gender-matched never smoker controls using the Illumina Human660W-Quad platform. In addition, we will include in the analysis 284 cases and 175 matched controls already genotyped on the 610Quad platform. In this phase we will only include the study sites that have collected blood specimens (MDACC, Mayo Clinic, Karmanos Cancer Institute, The University of Liverpool Cancer research Centre, Institute of Cancer Research in Sutton, and Lunenfeld Research Institute in Toronto, Canada). All the samples will be sent to the independent lab for genotyping, to reduce site-specific technical artifacts. The final sample will consist of 1540 cases and 1540 controls matched by study site. Aim 2: To perform the second phase (validation) analysis of significant SNPs identified in aim 1 using an independent set of cases and controls. SNPs associated with risk at the significance level of 0.01 or below in the discovery set will be included in the replication phase. The proposed threshold guarantees an adequate power to retain SNPs with the typical effect size of 1.3. We plan to carry 6000-7000 SNPs for validation. The independent replication set will include 800 cases and 800 controls, mostly from sites that collected tissue (Mayo Clinic, Karmanos Cancer Institute, UT Southwestern) or buccal specimens (UCLA), but also blood samples (Imperial College London, University of Pennsylvana, German Cancer Research Center, Heidelberg, National Research Center for Environment and Health, Neuherberg, Carmel Medical Center, Haifa). We will then perform a joint analysis to test the significance of the SNPs identified in the first stage using a stringent critical p-value of 10-7. There will be 2340 cases and 2340 controls in the joint set. Based on our experience with GWAS in smokers and assuming that genetic component in lung cancer risk in never smokers can be higher than genetic component in smokers, we expect to identify about 5-10 candidate regions associated with lung cancer risk in never smokers. Aim 3: To identify and explore pathways associated with the risk of lung cancer in never smokers. Results of the number of studies on the molecular mechanisms and drug response suggest that lung cancer in never smokers is a different disease and different pathways will be associated with lung cancer risk in non-smokers and smokers. To identify pathways and molecular functions associated with lung cancer risk in never smokers we will apply Ingenuity and DAVID bioinformatics tools. We will use at least 300 top candidate genes identified in joint and discovery analysis. The reason why we select rather large number of candidate genes for functional annotation is two-fold: 1. Both algorithms are looking for enrichment of pathways and function by most significant genes and they produce statistically robust results only when number of genes is relatively high. 2. Despite the fact that this study will be largest possible for never smokers we still are underpowered to detect SNPs with relatively small effect size. But though those SNPs will not reach genome wide level of significance they will tend to be on the top of the list. In other words genes from the gray zone (significant on individual level and non-significant for genome wide level) are expected to be enriched by true discoveries. True discoveries are likely to be associated with limited number of pathways / functions while false positives are expected to be uniformly distributed across functions and pathways. Therefore significant clustering of the gene to a given function will suggest that that those genes are true discoveries. This is the first GWAS aiming at identifying the genetic control of susceptibility to lung cancer in Caucasian never smokers. We will combine the available resources from the multiple sites to achieve the sample size sufficient for this study. The study will identify genetic architecture of the predisposition to the lung cancer in never smokers.

  Study phs000634

• Using human induced pluripotent stem cells (iPSC) and iPSC-derived neurons to explore cellular phenotypes associated with schizophrenia.

  Schizophrenia and major mental illness are common devastating conditions. Whilst partially effective treatments are available, none are disease-modifying. Notwithstanding important insights provided by animal models there is a need for novel models of mental illness to develop more effective therapies. A study of sporadic schizophrenia-derived human induced pluripotent stem cells (hiPS) has demonstrated a neuronal phenotype representing a powerful proof of concept of in vitro disease modeling, even for diseases with complex causation such as schizophrenia. These techniques have been used here to examine the behaviour of neural stem cells and neurons derived from fibroblasts from subjects carrying NDE1 copy number variations (CNVs) associated with increased risk of major mental illness. Using hiPS from individuals with and without disease-associated CNVs we have investigated how disease risk is conferred at a cellular and molecular level through detailed comparative studies of neural progenitor proliferation, neuronal morphology, physiology, cytoskeletal organization, synaptic function, glutamate (NMDA) receptor expression and also RNA sequencing and proteomic studies of these patient-derived cells.

  Study EGAS00001002895

• Hematopoietic Tet2 inactivation enhances the response to checkpoint blockade immunotherapy

  Somatic mutations inactivating TET2 are among the most common drivers of clonal hematopoiesis (CH). While TET2 inactivation is associated with monocyte-derived inflammation and improved chimeric antigen-receptor-T cell function, its impact on immunotherapy response is unknown. In murine models, hematopoietic Tet2 mutation enhanced the immune checkpoint blockade (ICB) response via the combined presence of phagocytes, CD4 and CD8 T cells. This effect was lost with myeloid- or T-cell restricted Tet2 inactivation, or in mice with 20% Tet2-mutant hematopoiesis. Mechanistically, in Tet2-mutant tumor-infiltrating leukocytes (TILs), ICB preferentially restricted cell states linked to tumor progression while inducing anti-tumor states. Tet2-mutant monocytes activated costimulatory programs, while Tet2-mutant T cells showed enhanced T cell memory signatures, alongside decreased exhaustion and regulatory phenotypes. This murine data was clinically relevant, since tumors from colorectal cancer and melanoma patients with TET2 driver mutation-CH (TET2-CH) showed enhanced immune infiltration, inflammation, and T cell activation. In melanoma patients treated with ICB, TET2-CH was associated with 6-fold greater odds of clinical benefit. Collectively, we demonstrate that hematopoietic Tet2 inactivation primes leukocytes for anti-tumor states associated with immunotherapy response and provides a potential biomarker for personalized therapy.

  Study EGAS50000001191

• Target sequencing of 27 cancer-predisposing genes in Japanese colorectal cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000346

• Target sequencing of 27 cancer-predisposing genes in Japanese pancreatic cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000327

• Spatial concordance of DNA methylation classification in diffuse glioma

  Background: Intratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence. Methods: We used neuronavigation to acquire 133 image-guided and spatially-separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast enhanced T1 weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a three-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites. Results: Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account. Conclusion: Our results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists.

  Study EGAS00001005434