Search Results - EGA European Genome-Phenome Archive

The Immune Microenvironment, Genome–Wide Copy Number Aberrations and Survival in Mesothelioma

IntroductionResults of recent clinical studies of immune checkpoint inhibitors in malignant pleural mesothelioma (MPM) have dampened initial enthusiasm. However, the immune environment and targets of these treatments such as program cell death protein 1 (PD-1) and its ligand PD-L1 have not been well characterised in MPM. Using a large cohort of patients, we investigated PD-L1 expression, immune infiltrates and genome-wide copy number status and correlated them to clinicopathological features.Patients and methodsTissue microarrays were constructed and stained with PD-L1(clone E1L3N, CST), CD4, CD8 and FOXP3 antibodies. PD-L1 positivity was defined as ≥5% membranous staining regardless of intensity and PD-L1+hi as ≥50%. Genomic DNA from a representative subset of 113 patients was used for genome-wide copy number analysis. The percent genome alteration (PGA) was computed as a proxy for genomic instability, and statistical analyses were used to relate copy number aberrations (CNA) to other variables.ResultsAmongst 329 patients evaluated, PD-L1+ was detected in 130/311 (41.7%), but PD-L1+hi was only seen in 30/311 (9.6%). PD-L1+ correlated with non–epithelioid histology and increased infiltration with CD4+, CD8+ and FOXP3+ lymphocytes. PD-L1+hi expression correlated with worse prognosis (HR = 2.37; 95%CI= 1.57-3.56; P < 0.001) on univariate analysis, but not in multivariate analysis. Higher PGA was associated with epithelioid histology and poorer survival (HR = 1.59; 95%CI= 1.01-2.5; P = 0.04), but not PD-L1 expression.ConclusionPD-L1 expression was associated with non-epithelioid MPM, poor clinical outcome and increased immunological infiltrates. Increased genomic instability did not correlate with PD-L1 expression, but was associated with poorer survival.

Study EGAS00001002323

Whole exome sequencing of cell-free DNA reveals temporo-spatial heterogeneity and identifies treatment-resistant clones in neuroblastoma

Background: Neuroblastoma (NB) displays important clinical and genetic heterogeneity, with emergence of new mutations at tumor progression. Patients and Methods: To study clonal evolution during treatment and follow-up, an innovative method based on circulating cell-free DNA (cfDNA) analysis by whole exome sequencing (WES) paired with target sequencing was realized in sequential liquid biopsy samples of 19 NB patients. Results: WES of the primary tumor and cfDNA at diagnosis showed overlap of Single Nucleotide Variants (SNVs) and Copy Number Alterations (CNAs), with 41% and 93% of all detected alterations common to the primary NB and cfDNA. CfDNA WES at a second time point indicated a mean of 22 new SNVs for patients with progressive disease. Relapse-specific alterations included genes of the MAPK pathway and targeted the protein kinase A signaling pathway. Deep coverage target sequencing of intermediate timepoints during treatment and follow-up identified distinct subclones. For 17 seemingly relapse-specific SNVs detected by sequencing detected these alterations in minor subclones, with relapse-emerging SNVs targeting genes of neuritogenesis and cell cycle. Furthermore a persisting, resistant clone with concomitant disappearance of other clones was identified by a mutation in the ubiquitin protein ligase HERC2. Conclusion: Modelisation of mutated allele fractions in cfDNA indicated distinct patterns of clonal evolution, with either a minor, treatment-resistant clone expanding to a major clone at relapse, or minor clones collaborating towards tumor progression. Identification of treatment-resistant clones will enable development of more efficient treatment strategies.cfDNA WES at relapse but not tumor or cfDNA WES at diagnosis, deep coverage target.

Study EGAS00001002705

Integrative genomic analysis reveals cancer-associated mutations at diagnosis of CML in patients with high risk disease

Genomic events associated with poor outcome in chronic myeloid leukemia (CML) are poorly understood. We performed whole exome sequencing, copy number variation and/or RNA-Seq for 65 patients to discover mutations at diagnosis and blast crisis (BC). Forty-six chronic phase patients with the extremes of outcome were studied at diagnosis. Cancer gene variants were detected in 15/27 patients (56%) with subsequent BC or poor outcome and in 3/19 optimal responders (16%), P=.007. Frequently mutated genes at diagnosis were ASXL1, IKZF1 and RUNX1. The methyltransferase SETD1B was a novel recurrently mutated gene. A novel class of variant associated with the Philadelphia translocation was detected at diagnosis in 11/46 patients (24%) comprising fusions and/or rearrangement of genes on the translocated chromosomes, with evidence of fragmentation, inversion and imperfect sequence reassembly. These were more frequent at diagnosis in patients with poor outcome: 9/27 (33%) versus 2/19 optimal responders (11%), P=.07. Thirty-nine patients were tested at BC and all had cancer gene variants, including ABL1 kinase domain mutations in 58%. However, ABL1 mutations co-occurred with other mutated cancer genes in 89% of cases, and these predated ABL1 mutations in 62% of evaluable patients. Gene fusions not associated with the Philadelphia translocation occurred in 42% of patients at BC and commonly involved fusion partners that were known cancer genes (78%). Genomic analysis revealed numerous relevant variants at diagnosis in patients with poor outcome and all patients at BC. Future refined biomarker testing of specific variants will likely provide prognostic information to facilitate a risk-adapted therapeutic approach.

Study EGAS00001003071

Comparison of capture-based method for transcriptome profiling of formalin-fixed paraffin embedded tumor samples

Background: The need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. Methods: Transcriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. Results: The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions that were initially identified in FF-TruSeq. Conclusion: All exome capture-based methods had comparable performance and concordance with FF-TruSeq. By enabling the interrogation of FFPE tumor samples, our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

Study EGAS00001005255

Are children born after medical assisted reproduction at greater risk of having an increased de novo mutation rate?

Introduction: De novo mutations (DNMs) play a prominent role in sporadic disorders with reduced fitness such as infertility and intellectual disability. Advanced paternal age is known to increase disease risk in offspring by increasing the number of DNMs in their genome. Less is known about the effect of assisted reproduction techniques (ART) on the number of DNMs in offspring. With the on-going trend of delayed parenthood more children are now born both from older fathers and through ART. Materials and Methods: We investigated 49 trios (mother, father and child) and 2 quartets (mother, father and 2 siblings) divided into children born after spontaneous conception (n=18); born after in vitro fertilisation (IVF) (n=17) and born after intracytoplasmic sperm injection combined with testicular sperm extraction (ICSI-TESE) (n=18). Groups further divided by paternal age, young (<35) or old (>45 years of age at conception). Whole-genome sequencing was performed twice to independently detect and validate all DNMs in children. Results: A clear paternal age effect was observed, with 70 DNMs detected on average in children born to young fathers and 94 DNMs in those born to older fathers (p = 0.001). No significant differences were observed between different methods of conception (p = 1) with paternal age affecting all methods equally. Conclusions: Paternal age, not method of conception, had a major effect on the observed number of DNMs in offspring. Given the role DNMs in disease risk, this negative result is good news for IVF and ICSI-TESE born children, if replicated in larger cohorts.

Study EGAS00001005569

Targeted Gene Panel for 171 PTCLs

Mature T-cell lymphomas, including peripheral T-cell lymphoma (PTCL) and extranodal NK/T-cell lymphoma (NKTL), represent a heterogeneous group of non-Hodgkin lymphomas with dismal outcomes and limited treatment options. To determine the extent of involvement of the JAK/STAT pathway in this malignancy, we performed targeted capture sequencing of 188 genes in this pathway in 171 PTCL and NKTL cases. A total of 272 nonsynonymous somatic mutations in 101 genes were identified in 73% of the samples, including 258 single-nucleotide variants and 14 insertions or deletions. Recurrent mutations were most frequently located in STAT3 and TP53 (15%), followed by JAK3 and JAK1 (6%) and SOCS1 (4%). A high prevalence of STAT3 mutation (21%) was observed specifically in NKTL. Novel STAT3 mutations (p.D427H, E616G, p.E616K, and p.E696K) were shown to increase STAT3 phosphorylation and transcriptional activity of STAT3 in the absence of cytokine, in which p.E616K induced programmed cell death-ligand 1 (PD-L1) expression by robust binding of activated STAT3 to the PD-L1 gene promoter. Consistent with these findings, PD-L1 was overexpressed in NKTL cell lines harboring hotspot STAT3 mutations, and similar findings were observed by the overexpression of p.E616K and p.E616G in the STAT3 wild-type NKTL cell line. Conversely, STAT3 silencing and inhibition decreased PD-L1 expression in STAT3 mutant NKTL cell lines. In NKTL tumors, STAT3 activation correlated significantly with PD-L1 expression. We demonstrated that STAT3 activation confers high PD-L1 expression, which may promote tumor immune evasion. The combination of PD-1/PD-L1 antibodies and STAT3 inhibitors might be a promising therapeutic approach for NKTL, and possibly PTCL.

Study EGAS00001002740

The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort

The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort and biobank that we established. To date, approximately 28,000 participants have enrolled in the study, with over 13,000 having completed their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing AI-based predictive models for disease onset and progression. A unique feature of the HPP is its deep and longitudinal profiling that includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests, continuous glucose and sleep monitoring, imaging modalities and molecular profiling of the transcriptome, genetics, gut, vaginal and oral microbiome, metabolome and immune system. For several of these modalities, the HPP is the first or largest cohort of its kind. Our analyses of this data provide novel insights into the variation of phenotypes with age and ethnicity, highlighting the importance of having ethnically diverse cohorts and the need for establishing age-dependent norms. We demonstrate how the HPP can be used to unravel personalized molecular signatures of disease by comparison to patient-specific and disease-specific matched healthy controls. Leveraging the extensive dietary and lifestyle HPP data, we systematically identify associations between lifestyle factors and health outcomes. Finally, we present a multi-modal foundation AI model that is trained using self-supervised learning on diet and CGM data and outperforms existing methods in predicting future onset of disease. We extend this AI framework to integrate all data modalities of each subject as a continuous sequence of diverse medical events, creating a digital twin that can simulate interventions and predict health trajectories and outcomes.

Study EGAS00001008040

Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

Epithelial ovarian carcinoma of all subtypes has one of the worst outcomes of any human cancer. To improve our understanding of underlying biology and therapeutic possibilities in this disease, we performed whole genome sequencing, methylation, and expression analyses of a comprehensive set of 47 ovarian cancer cell lines representing different histologic tumor subtypes. Given the challenges of genomic analyses in tumors without matched normal samples, we developed novel approaches for detection of somatic alterations and used these to identify sequence, copy number, and rearrangement changes and integrated these with genome-wide epigenetic and expression alterations. Ovarian cancer cell lines had molecular changes in genes involved in cell cycle, PI3K, RAS, BRCA, chromatin regulating, and p53 pathways, and displayed global mutation and methylation changes similar to primary ovarian carcinoma. We identified alterations not previously implicated in ovarian cancer including amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and members of the TGF beta receptor pathway, including TGFBR2, SMAD3 and SMAD4, in-frame rearrangements of YAP1-MAML2 and IKZF2-ERBB4, and fusions involving MET, NF1, FBXW7 and CCND1. Integrating cell line alterations with dose-response data using three targeted therapies revealed novel molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, those with MYC amplifications to PARP inhibitor BMN673, and SMAD4 alterations to MEK inhibitor MEK162. Genome-wide analyses revealed intrachromosomal rearrangements as an improved measure of sensitivity to PARP inhibition compared to the homologous recombination defect (HRD) score. This study provides a comprehensive resource of molecular information for ovarian cancer cell line models and a pharmacogenomic platform for developing rational cancer therapeutic strategies.

Study EGAS00001002998

Whole exome sequencing of small cell neuroendocrine cancer of the cervix

In order to improve treatment selection for high grade neuroendocrine carcinomas of the cervix (NECC), we performed a comparative genomic analysis between this rare tumor type and other cervical cancer types, as well as extra-cervical neuroendocrine small cell carcinomas of the lung and bladder. We performed whole exome sequencing on fresh-frozen tissue from 15 NECCs and matched normal tissue. We then identified mutations and copy number variants using standard analysis pipelines. Published mutation tables from cervical cancers and extra-cervical small cell carcinomas were used for comparative analysis. Descriptive statistical methods were used and a two-sided threshold of P < .05 was used for significance. In the NECC cohort, we detected a median of 1.7 somatic mutations per megabase (range 1.0-20.9). PIK3CA p.E545K mutations were the most frequency observed oncogenic mutation (4/15 tumors, 27%). Activating MAPK pathway mutations in KRAS (p.G12D) and GNAS (p.R201C) co-occurred in two tumors (13%). In total we identified PI3-kinase or MAPK pathway activating mutations in 67% of NECC. When compared to NECC, lung and bladder small cell carcinomas exhibited a statistically significant higher rate of coding mutations (P < .001 for lung; P = .001 for bladder). Mutation of TP53 was uncommon in NECC (13%) and was more frequent in both lung (103 of 110 tumors [94%], P < .001) and bladder (18 of 19 tumors [95%], P < .001) small cell carcinoma. These comparative genomics data suggest that NECC may be genetically more similar to common cervical cancer subtypes than to extra-cervical small cell neuroendocrine carcinomas of the lung and bladder. These results may have implications for the selection of cytotoxic and targeted therapy regimens for this rare disease.

Study EGAS00001003142

RNA-seq as a tool for evaluating human embryo competence

The majority of embryos that are created through IVF do not implant. One possibility for this inefficiency is an incomplete understanding of the molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to develop a foundational dataset for identifying candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

Study EGAS00001003667

Altered oligodendrocyte heterogeneity in Multiple sclerosis revealed by single nuclei RNA sequencing

This study is currently hosted by the European Nucleotide Archive. To access the data contained within the Study please follow the link below: https://www.ebi.ac.uk/ena/browser/view/PRJEB39323 Oligodendrocyte (OL) pathology is increasingly implicated in neurodegenerative diseases, as they are involved in metabolic support of axons and functional cross-talk with other brain cells. Rodent OLs are heterogeneous, with developmental and biological differences, but the extent of heterogeneity in the normal human brain and its contribution to any changes to disease remains unknown. Here we performed single nuclei RNA-sequencing (snRNA-seq) from white matter (WM) areas of post mortem human brain both in control (Ctr) and multiple sclerosis (MS) patients. We identified several sub-clusters of oligodendroglia in the Ctr human WM, some similar to those in mouse, and defined new markers for these cell states. Strikingly, some of these sub-clusters were under-represented in MS tissue, while others were more prevalent than in controls. We found a lack of OL precursor cells (OPCs) and an OL subcluster in an intermediate stage of differentiation in MS lesions and in normal appearing white matter (NAWM), suggesting either depletion by the disease or by a regenerative response. The differences in mature OL sub-clusters indicate different functional states of OLs in MS tissue and, as this is similar in NAWM to lesions, that MS is a more diffuse brain disease than the focal demyelinating lesions suggest. We were also able to identify new putative markers of different MS lesion subtypes. Our findings of an altered heterogeneity of oligodendroglia in MS may have an important contribution to our understanding of disease progression and may alter therapeutic approaches to MS.

Study EGAS00001003412

A molecular cell atlas of the human lung from single cell RNA sequencing

Although single cell RNA sequencing studies have begun providing compendia of cell expression profiles, it has proven more difficult to systematically identify and localize all molecular cell types in individual organs to create a full molecular cell atlas. Here we describe droplet- and plate-based single cell RNA sequencing applied to ~75,000 human lung and blood cells, combined with a multi-pronged cell annotation approach, which have allowed us to define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 of 45 previously known cell types or subtypes and 14 new ones. This comprehensive molecular atlas elucidates the biochemical functions of lung cell types and the cell-selective transcription factors and optimal markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signaling interactions including sources and targets of chemokines in immune cell trafficking and expression changes on lung homing; and identifies the cell types directly affected by lung disease genes and respiratory viruses. Comparison to mouse identified 17 molecular types that appear to have been gained or lost during lung evolution and others whose expression profiles have been substantially altered, revealing extensive plasticity of cell types and cell-type-specific gene expression during organ evolution including expression switches between cell types. This atlas provides the molecular foundation for investigating how lung cell identities, functions, and interactions are achieved in development and tissue engineering and altered in disease and evolution.

Study EGAS00001004344

We evaluate the potential for routine WGS using ONT by sequencing the well-characterised reference sample NA12878 and the genome of an individual with ataxia-pancytopenia syndrome accompanied by severe immune dysregulation.

Whole-genome sequencing (WGS) is becoming widely used in clinical medicine in diagnostic contexts and to inform treatment choice. While current sequencing technologies have been extremely successful, their reliance on short read lengths necessarily involves some limitations: accurately assaying certain genomic regions and classes of variation can be problematic. Recent advances in throughput and cost have made WGS using the Oxford Nanopore Technologies (ONT) MinION long-read single-molecule sequencer a potential solution to these challenges. Here we evaluate the potential for routine WGS using ONT by sequencing the well-characterised reference sample NA12878 and the genome of an individual with ataxia-pancytopenia syndrome accompanied by severe immune dysregulation, to 82× and 30× respectively. For NA12878, we evaluated single-nucleotide variant (SNV) calls based on data from multiple base-calling algorithms. We demonstrate that phasing metrics from a novel, reference panel-free, long-read-based method can improve variant-calling performance from otherwise modest levels, resulting in a false discovery rate of 7.1% and false negative rate of 8.5%; remaining errors are concentrated near homopolymers and in regions of reduced sequencing coverage. In the clinical sample, we are able to identify and directly phase two non-synonymous de novo variants in SAMD9L, (OMIM #159550) inferring that they both lie on a common paternal haplotype by overlap with parental genotypes at nearby common variants. This work demonstrates that methodological innovation can substantially reduce variant-calling error rates in ONT data, and that with on-going improvements in throughput, base-calling and dedicated long-read-based SNV-calling methodology, ONT offers promise as an option for clinical WGS.

Study EGAS00001003469

Persistence of circulating tumor DNA in breast cancer patients during neoadjuvant treatment is a significant predictor of poor tumor response

Purpose:Accurate assessment of response during neoadjuvant systemic treatment (NST) poses a major clinical challenge. Therefore, a minimally-invasive assessment of tumor response based on cell-free circulating tumor DNA (ctDNA) may be beneficial to guide treatment decisions.Experimental Design: We profiled 93 genes in tissue from 193 early breast cancer patients. Patient-specific assays were designed to track ctDNA during NST from 145 patients with available plasma. ctDNA presence and levels were correlated with complete pathological response (pCR) and residual cancer burden (RCB) as well as with clinicopathologic characteristics of the tumor to identify potential proxies for ctDNA release. Moreover, we tested the predictive value of driver events identified in the tumor.Results:At baseline, ctDNA could be detected in 63/145 (43.4%) patients and persisted in 25/63 (39.7%) patients at mid-therapy (MT) and 15/63 (23.8%) patients at the end of treatment. ctDNA detection at MT was significantly associated with higher RCB (OR 0.062, 95% CI 0.01-0.48, P=0.0077). Out of 31 patients with detectable ctDNA at MT, 30 patients (96.8%) were non-responders (RCB II, n=8; RCB III, n=22) and only one patient responded to the treatment (RCB I). Considering all 145 patients with baseline (BL) plasma, none of the patients with RCB 0 and only 6.7% of patients with RCB I had ctDNA detectable at MT, while 30.6% and 29.6% of patients with RCB II/III, respectively, had a positive ctDNA result. Conclusion:Overall, our results demonstrate that the detection and persistence of ctDNA at mid-therapy may have the potential to negatively predict response to neoadjuvant treatment and identify patients who will not achieve pCR or be classified with RCB II/III.

Study EGAS00001005798

Post_Mortem_Tissue_COVID19_RNA

Single cell analysis of post mortem tissue samples from SARS-CoV2-infected patients We aim to directly identify the human cell types infected by SARS-CoV-2 and measure the cellular response to COVID19 infection across 20 different tissues from infected patient autopsies. We have examined the expression pattern of viral entry receptors across healthy human tissues to predict several candidate target cell types across the airway and heart. In addition, high prevalence of cardiac failure and abnormal renal function in COVID19 patients implicates heart and kidney involvement, but the pathogenesis of organ specific damage - whether via a direct cytopathic mechanism or an indirect inflammatory response - remains unknown . Currently, we lack confirmation of target cell types and cellular processes in infected tissues as autopsies are discouraged in most countries due to health and safety risks. Our collaborators Drs Michael Osborn and Brian Hanley (Imperial College) have outlined guidelines to perform post-mortem in COVID19 patients (Hanley et al., 2020) and have established a programme of autopsies for research to be performed in a high-risk facility at Westminster Public Mortuary. Here, we propose to identify infected cell types and aberrant molecular pathologies in this precious tissue resource using single cell and spatial genomics. We will prioritise three organ systems: the human airway, heart and the kidney. We will directly examine the cellular identities of SARS-CoV-2 infected cell types and identify the cellular responses to infection across these organs. This fundamental knowledge will help guide future treatment choices for COVID19. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001004442

A reference map of potential determinants for the human serum metabolome

The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

Study EGAS00001004512

Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. We performed multi-omic analysis including whole-exome, RNA and miRNA sequencing and quantification of 126 proteins in a series 34 LCCL coupled with a screening of 29 anti-cancer agents. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular "proliferation class" of HCC. Genomic alterations of the RAS-MAPK pathway correlated with trametinib sensitivity that was more potent than FGFR4 inhibitors in tumor cells depending on the FGF19/FGFR4 pathway. Moreover, we showed that FGF19 amplification was only functional in tumor cells that retained a hepatocyte differentiation program with expression of FGFR4, KLB and NR1H4 highlighting the complex interplay between the genomic and transcriptomic context in drug response. We also identified drugs/combination that could target efficiently the transcriptomic "progenitor subclass of HCC", as well as specific genetic contexts such as inactivating mutations in TSC1/TSC2 and TP53 associated with higher sensitivity to the mTOR inhibitor rapamycin and the AURKA inhibitor alisertib, respectively. LCCL represent relevant preclinical models for drug-biomarker discovery in HCC and enabled to identify molecular contexts linked with particular therapeutic vulnerabilities that may be useful to stratify patients in future clinical trials

Study EGAS00001003536

Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

We retrospectively collected patients (n=1047) enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017. The outcomes were duration of treatment (DOT) and overall survival (OS). Clinical features were analyzed for their influence on the treatment effect and prognosis. Next-generation sequencing (NGS) was performed to identify genetic biomarkers associated with the efficacy of pemetrexed. The median DOT was 9.1 months (95% CI: 8.5-9.8), and the median OS was 26.2 months (95% CI: 24.2-28.1). OS was positively correlated with DOT (r=0.403, P<0.001). Multivariable analysis showed that smoking status and Eastern Cooperative Oncology Group (ECOG) performance status (PS) were independently associated with DOT; smoking status, ECOG PS, targeted therapy, and EGFR/ALK/ROS1 status were independently associated with OS. NGS in 22 patients with available samples showed genes with high mutation rates were: TP53 (54.5%), EGFR (50.0%), MYC (18.2%), PIK3CA (13.6%). When grouped based on progression-free survival (PFS) reported in the PARAMOUNT study, the DOT >6.9 months set was associated with PIK3CA, ALK, BRINP3, CDKN2A, CSMD3, EPHA3, KRAS, and RB1 mutations, while ERBB2 mutation was observed only in the DOT ≤6.9 months set. This study shows that initial chemotherapy with pemetrexed is an effective regimen for advanced lung adenocarcinoma in selected Chinese patients. There is no specific genetic profile predicting the benefit of pemetrexed found by NGS. Biomarkers predicting the efficacy of pemetrexed need further exploration.

Study EGAS00001004546

A Multifactorial Tumor and Immune Cell Profile Determines Response to Immune Checkpoint blockade in Melanoma

The complex crosstalk between tumor and immune cells during immune checkpoint blockade mandates the development of integrated models that interpret the anti-tumor immune response and predict clinical outcome. We have integrated genome-wide sequence and structural alterations with pre and on-therapy transcriptomic and T cell repertoire features for a cohort of 64 immunotherapy-naïve melanomas treated with anti-PD1 monotherapy or combined anti-PD1 and anti-CTLA4 therapy. While tumor mutation burden (TMB) was associated with improved response to therapy, expressed mutation burden was superior to TMB in predicting outcome. An increased pre-existing T cell density differentiated responding from non-responding tumors independent of therapy. Importantly, T cell repertoire reshaping determined by T cell receptor (TCR) clonotypic regressions and expansions reflected response to therapy such that a more dynamic repertoire predicted improved clinical outcome. Through whole-transcriptome analyses, we discovered differential abundance of B cell subsets in responding tumors, which highlights the importance of the interplay between pre-existing T and B cell immunity in shaping therapeutic response. Tumor temporal trajectories during therapy revealed distinct patterns of molecular response related to expressed mutation elimination or retention that accurately interpreted clinical response. High-dimensional genomic, transcriptomic and immune repertoire data were integrated by both a machine learning and a censored regression approach, resulting in a harmonized multi-modal predictor of response to immune checkpoint blockade. B cell abundance, expressed mutation load and tumor aneuploidy were combined to identify patients at high risk for recurrence, such that high risk patients had a significantly shorter progression-free survival (HR=9.18, 95% CI: 3.14-26.85, p=3.4e-06) especially in the anti-PD1/anti-CTLA4 group (HR=20.34, 95% CI: 4.08-101.32, p=1.68e-06).

Study EGAS00001004548

Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma

Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

Study EGAS00001004564

Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

Study EGAS00001004567

Mutational Landscape and Tumor Burden Assessed by Cell-Free DNA in Diffuse Large B-Cell Lymphoma: a Population-based Study

Purpose: We analyzed the utility of cfDNA in a prospective population-based cohort to determine the mutational profile, assess tumor burden, and estimate its impact in response rate and outcome in patients with DLBCL. Experimental Design: One-hundred patients were diagnosed with DLBCL during the study period. Mutational status of 112 genes was studied in cfDNA by targeted next-generation sequencing. Paired formalin-fixed paraffin-embedded samples and volumetric PET/CT were assessed when available. Results: Appropriate cfDNA to perform the analyses was obtained in 79/100 cases. At least one mutation could be detected in 69/79 cases (87%). The sensitivity of cfDNA to detect the mutations was 68% (95% CI: 56.2-78.7). The mutational landscape found in cfDNA samples was highly consistent with that shown in the tissue and allowed genetic classification in 43% of the cases. A higher amount of ctDNA significantly correlated with clinical parameters related to tumor burden (elevated LDH and β2-microglobulin serum levels, advanced stage, and high-risk IPI) and total metabolic tumor volume assessed by PET/CT. In patients treated with curative intent, high ctDNA levels (&gt;2.5 log hGE/mL) were associated with lower complete response (65% vs. 96%, P&lt;0.004), shorter progression-free survival (65% vs. 85%, P=0.038) and overall survival (73% vs. 100%, P=0.007) at 2 years, although it did not maintain prognostic value in multivariate analyses. Conclusions: In a population-based prospective DLBCL series, cfDNA resulted an alternative source to estimate tumor burden and to determine the tumor mutational profile and genetic classification, which have prognostic implications and may contribute to a future tailored

Study EGAS00001004733

Circulating Tumor DNA in Checkpoint Inhibitor treated Lung Cancer

BackgroundImmune checkpoint inhibitors (ICI) are increasingly used to treat non-small cell lung cancer (NSCLC) and there is a critical need for novel predictive/prognostic biomarkers. We evaluated whether dynamics of circulating tumor (ctDNA) can identify NSCLC patients who benefit from single agent ICI.MethodsCirculating cell-free DNA (cfDNA) from 177 patients was analyzed prior ICI and at first treatment evaluation using a Commercial 77-gene panel. We performed de novo mutation calling and corrected for variants related clonal hematopoiesis. ctDNA changes were evaluated as predictors of tumor response estimated with PET/diagnostic CT and survival.ResultsMutations were detected in 159 of 174 (91.4%) analyzable patients. Most responders presented decreasing ctDNA levels, while non-responders had mixed molecular responses. Patients with a >50% molecular ctDNA decrease or no detectable ctDNA demonstrated improved PFS (5.9 versus 1.8 months; HR 0.49, 95%CI, 0.35-0.67, P < .001), and OS (18.9 versus 9.9 months; HR 0.41, 95%CI, 0.30-0.57, P < .001) compared to patients not achieving these endpoints. Clearance of mutations (and no detected ctDNA) had a similar effect (PFS HR 0.45, 95%CI, 0.32-0.61, P < .001; OS 0.37,95%CI, 0.27-0.52, P < .001) compared to patients having stable or additional mutations. After adjusting for clinical factors both >50% ctDNA decrease (HR 0.4, 95% CI, 0.3-0.6, P < .001) and clearance of mutations (HR 0.42, 95% CI, 0.3-0.6, P < .001) remained independent predictors for PFS and OS.ConclusionsctDNA testing reveals significant prognostic albeit not predictive information in ICI treated advanced NSCLC. This relevant information can be obtained with a commercial easy-to-implement ctDNA test that will facilitate extensive testing.

Study EGAS00001004847

18 Whole Exome Sequencing for Radiation Induced-Meningiomas

Purpose: Majority of pediatric cancers require the irradiation of the central nervous system (CNS), and as more patients survive into adulthood from improved oncological therapy the sequelae of brain radiation are increasing in prevalence. Radiation-induced meningiomas (RIMs), one such secondary effect, demonstrate a clinically more aggressive behaviour than sporadic meningiomas (SMs). We aimed to describe the genomic mutational landscape of RIMs.Methods: We analyzed a principal cohort of 18 RIMs, with 31 RIMs overall, from patients who received childhood radiation therapy and 30 SMs, as a comparator population. We performed a multiplatform integrative genomic analysis; including methylation, whole exome and RNA sequencing. Results: RIMs exhibited a five-fold increase in copy number alterations, commonly the loss of chromosome 1p (17/18 RIMs) and 22q (17/18 RIMs), which was significantly more than observed in sporadic meningiomas. Furthermore, RNA sequencing data revealed an NF2 gene fusion event in 35.3% of RIMs. In all 6 cases, there was a complete NF2 exon spliced into a complete exon of a reciprocal gene, suggesting that the breakpoints of genomic rearrangement are intronic. All tumours with the NF2 fusion also possessed monosomy of chromosome 22q, rendering the cells with homozygous disruption of NF2. Clinically, RIMs with the NF2 fusion exhibited ill-defined borders and a tendency to develop in anatomic frontal location. Also, targeted sequencing panel confirmed that RIMs had fewer nonsynonymous NF2 mutations (6.5% vs. 30% in SM) and absence of mutations in TRAF7, SMO, KLF4, PIK3CA and AKT1, genes traditionally involved in SMs.Conclusion: Our study demonstrates that RIMs have distinct genomic drivers of oncogenesis as compared to SMs, specifically NF2 inactivation through fusion event. Radiation therapy possibly triggers genomic structural rearrangements through error-prone repair of double-stranded DNA breaks.

Study EGAS00001002317

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