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• Whole exome sequencing of germline DNA was performed and subsequent polymorphisms in genes known and putatively involved in the innate immune response to fungi were identified

  Disease can be conceptualized as the result of interactions between infecting microbe and holobiont, the combination of a host and its microbial communities. It is likely that genomic variation in the host, infecting microbe, and commensal microbiota are key determinants of infectious disease clinical outcomes. However, until recently, simultaneous, multiomic investigation of infecting microbe and holobiont components has rarely been explored. Herein, we characterized the infecting microbe, host, micro- and mycobiomes leading up to infection onset in a leukemia patient that developed invasive mucormycosis. We discovered that the patient was infected with a strain of the recently described Mucor velutinosus species which we determined was hypervirulent in a Drosophila challenge model and has a predisposition for skin dissemination. After completing the infecting M. velutinosus genome and genomes from four other Mucor species, comparative pathogenomics was performed and assisted in identifying 66 M. velutinosus-specific putatively secreted proteins, including multiple novel secreted aspartyl proteinases which may contribute to the unique clinical presentation of skin dissemination. Whole exome sequencing of the patient revealed multiple non-synonymous polymorphisms in genes critical to control of fungal proliferation, such as TLR6 and PTX3. Moreover, the patient had a non-synonymous polymorphism in the NOD2 gene and a missense mutation in FUT2, which have been linked to microbial dysbiosis and microbiome diversity maintenance during physiologic stress, respectively. In concert with host genetic polymorphism data, the micro- and mycobiome analyses revealed that the infection developed amid a dysbiotic microbiome with low α-diversity, dominated by staphylococci. Additionally, longitudinal mycobiome data showed that M. velutinosus DNA was detectable in oral samples preceding disease onset. Our genome-level study of the host-infecting microbe-commensal triad extends the concept of personalized genomic medicine to the holobiont-infecting microbe interface thereby offering novel opportunities for using synergistic genetic methods to increase understanding of infectious diseases pathogenesis and clinical outcomes.

  Study EGAS00001001542

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• ctDNA to predict risk of progression and death after trifluridin/tipiracil therapy

  Background. Late-line treatment in metastatic colorectal cancer (mCRC) can improve the prognosis. However, not every patient has a benefit and may experience severe side effects. Thus, predictive/prognostic biomarkers are urgently needed. Despite many promising results, the role of circulating tumor DNA (ctDNA) analysis in trifluridin/tipiracil (FTD/TPI) treated mCRC patients is so far still elusive. Study design. This prospective non-interventional translational biomarker phase II study enrolled 30 metastatic CRC patients treated with FTD/TPI. The primary study aim was to identify a molecular biomarker to predict overall survival (OS) benefit upon FTD/TPI treatment. Methods. mCRC patients (60% male, 40% female) with FTD/TPI therapy were included. Molecular profiling in cell-free DNA from plasma was performed prior to treatment and on average 4, 8 and 12 weeks after FTD/TPI initiation. Tumor levels were assessed as the highest variant allele frequency (hVAF) and correlated with OS. Uni- and multivariate analyses for survival were performed with clinical variables. Multivariate analyses for survival and treatment efficacy were adjusted to age, gender and ECOG performance status. Results. Compared to previous data, our disease control rate of 30% was lower with a median OS of 8.1 months and a median PFS of 3.2 months. At baseline (BL) and the first two follow-ups (FU), a hVAF cut-off of 7.5% was most discriminative (BL HR 0.39 95% CI 0.16 - 0.98 P=0.0212, FU1 HR 0.30 95% CI 0.12 -0.77 P=0.0021, FU2 HR 0.23 95% CI 0.08-0.70 P=0.0004) whereas at the last follow-up the stratification was most pronounced at a 15% cut-off. An elevated hVAF trajectory over time was associated with a higher risk of death. Conclusion. ctDNA is detectable in a high proportion of mCRC patients. Changes in ctDNA levels are associated with survival among FTD/TPI therapy and may identify patients who benefit most from treatment in these late-stage disease.

  Study EGAS00001006883

• Osteosarcoma_X10

  This is a continuation of the osteosarcoma work we have undertaken.

  Study EGAS00001002167

• Neuroblastoma sequencing data

  This study shares tumor and normal DNA for a patient with neuroblastoma

  Study EGAS00001005602

• Whole-Genome Sequencing of a Healthy Aging Cohort.

  Whole-Genome Sequencing of a Healthy Aging Cohort.

  Dataset EGAD00001003941

• Poly A transcriptom sequencing of mutifocal hepatocellular carcinoma

  Poly A transcriptome sequence of mutifocal hepatocelular carcinoma

  Dataset EGAD00001003231

• Liquid biopsy for molecular characterization of diffuse large B-cell lymphoma and early assessment of minimal residual disease

  Circulating tumor DNA (ctDNA) allows genotyping and minimal residual disease (MRD) detection in lymphomas. Using a NGS approach (Euroclonality-NDC), we evaluated clinical and prognostic value of ctDNA in a series of R-CHOP-treated DLBCL patients at baseline (n=68) and after 2-cycles (n=59), monitored by metabolic imaging (PET/CT). A molecular marker was identified in 61/68 (90%) ctDNA samples at diagnosis. Pre-treatment high ctDNA levels significantly correlated with elevated LDH, advanced stage, high risk IPI and a trend to shorter 2-year PFS. Valuable NGS data after 2-cycles of treatment were obtained in 44 cases, and 38 achieved major molecular response (MMR; 2.5-log drop in ctDNA). PFS curves displayed statistically significant differences among those achieving MMR vs. those not achieving MMR (2yr PFS of 76% vs. 0%, p<0.001). Similarly, more than 66% reduction in SUVmax by PET/CT identified two subgroups with different prognosis (2yr PFS of 83% vs. 38%; p<0.001). Combining both approaches MMR and SUVmax reduction, a better stratification was observed (2yr PFS of 84% vs. 17% vs. 0%, p<0.001). Euroclonality-NDC panel allows the detection of a molecular marker in the ctDNA in 90% of DLBCL. ctDNA reduction at 2 cycles and its combination with interim PET results improves patient prognosis stratification.

  Study EGAS50000000215

• North Carolina Clinical Genomic Evaluation by NextGen Exome Sequencing (NCGENES)

  North Carolina Clinical Genomic Evaluation by Next-generation Exome Sequencing This study is part of a larger consortium project investigating the validity and best use of next-generation sequencing (in particular, whole exome sequencing, or WES) in clinical care. Participants are patients who were either seen in the UNC Cancer and Adult Genetics Clinic or referred to the study by their physician. They will be approached by their physician or a genetic counselor for recruitment. Once enrolled, a clinical geneticist or genetic counselor will obtain consent and collect blood samples to be analyzed using WES. Results may include information related to a diagnosis and incidental information. Medically actionable incidental findings will be CLIA-certified and returned to participants in a routine genetic counseling session, along with diagnostic findings. Eligible adult participants will be randomized to have the opportunity to choose to get certain types of non-medically actionable incidental findings, as well. Their decisions will be investigated, as will psychosocial and behavioral responses to sequencing and receiving sequencing information. This is a longitudinal, mixed methods study (i.e., multiple assessments pre- and post-return of results, with both quantitative and qualitative methods used to gather data). Because only the quantitative component of the study uses randomization, only measures and procedures associated with that component are included here. The third study release includes data of additional n=189 subjects.

  Study phs000827

• Epigenomics of Human CD8 T cell Differentiation and Aging

  The efficacy of the adaptive immune response declines dramatically with age, but the cell-intrinsic mechanisms driving the changes characteristic of immune aging in humans remain poorly understood. One hallmark of immune aging is the loss of self-renewing naive cells and the accumulation of differentiated but dysfunctional cells within the CD8 T cell compartment. Using ATAC-seq, we first inferred the transcription factor binding activities that maintain the naive and central and effector memory CD8 T cell states in young adults. Integrating our results with RNA-seq, we determined that BATF, ETS1, Eomes, and Sp1 govern transcription networks associated with specific CD8 T cell subset properties, including activation and proliferative potential. Extending our analysis to aged humans, we found that the differences between memory and naive CD8 T cells were largely preserved across age, but that naive and central memory cells from older individuals exhibited a shift toward a more differentiated pattern of chromatin openness. Additionally, aged naive cells displayed a loss in chromatin openness at gene promoters, a phenomenon that appears to be due largely to a loss in binding by NRF1, leading to a marked drop-off in the ability of the naive cell to initiate transcription of mitochondrial genes. Our findings identify BATF- and NRF1-driven gene regulation as targets for delaying CD8 T cell aging and restoring T cell function.

  Study phs001187

• Integrated Metabolic Profiling and Gene Expression Analysis Reveals Therapeutic Modalities in Breast Cancer

  In this study, we performed metabolite profiling and RNA-sequencing on human breast cancer tumors and normal breast tissue samples, including triple negative breast cancer (TNBC), estrogen receptor positive breast cancer (ER+) and paired normal samples, and patient-derived xenografts (PDX) samples. Here, we report two distinctive groups defined by metabolites; a TNBC-HIGH group that shows high levels of pyrimidine pathway metabolites and biosynthetic enzymes, and an ER-HIGH group that shows high levels of fatty acid and arginine biosynthesis intermediates. We identify different metabolic enrichment profiles between cell lines grown in vitro vs. in vivo; cell lines grown in vivo recapitulate patient tumors metabolic profiles. Further, we identify a subset of genes that strongly correlates with the TNBC-HIGH metabolic profile using integrated metabolic and gene expression profiling, which strongly predicts patient prognosis when tested on larger human datasets. As a proof-of-principle, when we target TNBC-HIGH metabolic dysregulation with a pyrimidine biosynthesis inhibitor (Brequinar), and/or a glutaminase inhibitor (CB-839), we observe therapeutic efficacy and decreased tumor growth in representative TNBC cell lines, murine p53-null mammary tumors, and in vivo patient-derived xenografts (PDXs) upon multi-agent drug treatment. This study highlights potential new therapeutic opportunities in breast cancers guided by a genomic biomarker, which could prove impactful for breast cancers that rapidly proliferate.

  Study phs002396

• Genetic Markers of Caries Risk in Diverse Underserved Children: CIDR

  The study Predicting Caries Risk In Underserved Children, From Toddlers To The School-age Years In Primary Healthcare Settings, is a renewal of an initial project designed to develop a dental caries risk tool for use in primary medical and dental healthcare settings to identify high dental caries risk children, expanding from the toddler (1-4 years old, referred to as Stage 1 grant) to the school-age years (6-9 years old, referred to as Stage 2 grant); and to determine the relationships between dental caries risk profiles and dental caries disease patterns. 1326 children, 12 +/- 3 months of age, and their primary caregivers, were enrolled in the study. This cohort represents a diverse population, including ethnic and racial minorities and low socio-economic status groups. There are a total of six in-person visits (at child age 1, 2.5, 4, 6.5, 8 and 9.5 years), and at each one the primary caregiver (PCG) completes a dental caries risk questionnaire, and the child receives a detailed dental caries examination. Saliva samples were collected during the age 8 visit (2019-2020) from 1,059 racially and ethnically diverse individuals (543 children and 516 PCGs) for the purposes of human genetic testing, to study the genetics of dental caries experience of children and their primary caregivers.

  Study phs003280

• MSK SPECTRUM - SPatiotemporal Evolution of Cancer Traced Using Multimodalities

  MSK SPECTRUM is a multi-modal, interdisciplinary prospective study of spatiotemporal determinants of high-grade serous ovarian cancer (HGSOC) evolution, treatment and response. Accounting for ~80% of ovarian cancers, HGSOC is the most lethal gynecological malignancy and is a cancer of major unmet clinical need. Challenges in disease management relate to several unresolved questions about disease biology and diagnostic modalities. Prospective longitudinal collection of tissues and blood from laparoscopic biopsies and debulking surgeries enable multi-modal molecular measurements. The program brings together formidable expertise at Memorial Sloan Kettering Cancer Center (MSKCC) across the disciplines of high-resolution genomics and computer science, radiology and radiomics, surgery, tissue banking and sample preparation, medical oncology, immuno-oncology and high-resolution tissue profiling to generate a comprehensive and integrative dataset that will allow us to address the following major aims: i) characterize malignant and immune diversity at diagnosis, ii) survey the co-evolution of malignant cells and the immune response, and iii) stratify patients on standard-of-care and investigational compounds based on their genomic and transcriptomic signatures and changes to relevant genes (TP53, CCNE1, BRCA1/2, CDK12). The goal is to create a framework to utilize integrated multi-modal data as a route to advanced diagnostics and to ultimately establish a proof-of-concept for integrated diagnostics.

  Study phs002857

• Nala TAS-LRS PGx Study

  Pharmacogenomics (PGx) testing improves medication safety and efficacy by identifying genetic variants that affect drug response. However, current technologies often fail to resolve complex loci, detect structural variants, or phase alleles accurately. Here, we present an end-to-end PGx workflow based on Targeted Adaptive Sampling-Long Read Sequencing (TAS-LRS), integrating a streamlined laboratory protocol with a bioinformatics pipeline that includes a novel CYP2D6 caller. Using 1,000 ng of DNA and three-sample multiplexing on a single PromethION flow cell, the assay achieves consistent on-target (25x) and off-target (3x) coverage, enabling accurate, haplotype-resolved testing of 35 pharmacogenes alongside genome-wide genotyping from off-target reads. We further developed the workflow into a clinically ready service and validated its performance across 17 reference and clinical samples. The assay demonstrated high concordance for small variants (99.9%) and structural variants (>95%), with phased diplotypes and metabolizer phenotypes reaching 97.7% and 98.0% concordance, respectively. Improved calls were observed in 12 genes due to enhanced genotyping, phasing, or novel allele detection. In addition, off-target reads supported accurate genome-wide imputation, comparable to short-read sequencing and superior to microarrays. These results establish the feasibility of long-read sequencing for clinical PGx testing and position TAS-LRS as a scalable solution combining both targeted and genome-wide utility.

  Study EGAS50000001116

• INSPIRE - Investigator-initiated Phase 2 Study of Pembrolizumab Immunological Response in Metastatic Solid Tumors

  Whole exome and RNA sequencing source data for: Clouthier, D.L., Lien, S.C., Yang, S.Y.C. et al. An interim report on the investigator-initiated phase 2 study of pembrolizumab immunological response evaluation (INSPIRE). j. immunotherapy cancer 7, 72 (2019). https://doi.org/10.1186/s40425-019-0541-0 Bratman S*, Yang SYC*, Iafolla MAJ, Liu Z, Hansen AR, Bedard P, Lheureux S, Spreafico A, Razak AA, Shchegrova S, Louie M, Billings P, Zimmerman B, Sethi H, Aleshi A, Torti D, Marsh K, Eagles J, Cirlan I, Hanna Y, Clouthier D, Lien SC, Ohashi PS, Xu W, Siu LL, Pugh TJ. Personalized circulating tumor DNA analysis as a predictive biomarker in solid tumor patients treated with pembrolizumab. Nature Cancer. 2020:1:873-881. https://doi.org/10.1038/s43018- 020-0096-5. Yang SYC, Lien SC, Wang BX, Clouthier DL, Hanna Y, Cirlan I, Zhu K, Bruce JP, El Ghamrasni S, Iafallo MAJ, Oliva M, Hansen AR, Spreafico A, Bedard PL, Lheureux S, Razak A, Speers V, Berman HK, Aleshin A, Haibe-Kains B, Brooks DG, McGaha TL, Butler MO, Bratman SV, Ohashi PS, Siu LL, and Pugh TJ. Pan-cancer analysis of longitudinal metastatic tumors reveals genomic alterations and immune landscape dynamics associated with pembrolizumab sensitivity. Nature Comm 2021:12, 5137. https://doi.org/10.1038/s41467-021-25432-7

  Study EGAS00001003280

• Mutational Landscape of Grey Zone Lymphoma

  The mutational landscape of grey zone lymphoma (GZL) has not yet been established and differences to related entities are mostly unknown. Here, we studied coding sequence mutations of 50 EBV-negative GZL and 20 polymorphic EBV-positive DLBCL NOS (poly-EBV-L) in comparison to classical Hodgkin lymphoma (cHL), primary mediastinal B cell lymphoma (PMBCL), and diffuse large B cell lymphoma (DLBCL). Paired exomes of 21 GZL and 7 poly-EBV-L cases were analyzed as a discovery cohort followed by targeted sequencing of 217 genes in an extension cohort of 29 GZL and 13 poly-EBV-L cases. GZL cases with thymic niche involvement displayed a mutation profile closely resembling cHL and PMBCL, with SOCS1 (45%), B2M (45%), TNFAIP3 (35%), GNA13 (35%) and NFKBIA (29%) being the most recurrently mutated genes. In contrast, GZL cases without thymic niche involvement (N=18) had a significantly distinct pattern, enriched in mutations related to apoptosis defects (TP53 (39%), BCL2 (28%), BIRC6 (22%)) and depleted in GNA13, XPO1 or NFKB signaling pathway mutations (TNFAIP3, NFKBIE, IKBKB, NFKBIA). Poly-EBV-L cases presented a distinct mutational profile including STAT3, PRKDC mutations and a significantly lower coding-mutation load in comparison to EBV-negative GZL. Our study highlights characteristic mutational patterns in GZL associated with presentation in the thymic niche suggesting a common cell of origin and disease evolution with related anterior mediastinal lymphomas.

  Study EGAS00001004482

• Prebiotic inulin-type fructans induce specific changes in the human gut microbiota

  ObjectiveContrary to the long-standing prerequisite of inducing selective (i.e. bifidogenic) effects, recent findings suggest that prebiotic interventions lead to ecosystem-wide microbiota shifts. Yet, a comprehensive characterization of this process is still lacking. Here, we apply 16S rDNA microbiota profiling and matching (GC-MS) metabolomics to assess the consequences of inulin fermentation both on the composition of the colon bacterial ecosystem and fecal metabolites profiles.DesignFecal samples collected during a double blind, randomized, cross-over intervention study (NCT02548247) set up to assess the effect of inulin consumption on stool frequency in healthy adults with mild constipation were analyzed. Fecal microbiota composition and metabolite profiles were linked to the study’s clinical outcome as well as to quality-of-life measurements recorded.ResultsWhile fecal metabolite profiles were not significantly altered by inulin consumption, our analyses did detect a modest effect on global microbiota composition. At the same time, specific inulin-induced changes in relative abundances of Anaerostipes, Bilophila, and Bifidobacterium were identified. The observed decrease in Bilophila abundances following inulin consumption was associated with both softer stools and a favorable change in constipation-specific quality of life measures.ConclusionsEcosystem-wide analysis of the effect of a dietary intervention with prebiotic inulin-type fructans on the colon microbiota revealed that this effect is specifically associated to three genera, one of which (Bilophila) representing a promising novel target for mechanistic research.

  Study EGAS00001002173

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p&lt;0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005584

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p&lt;0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005586

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p&lt;0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005587

• Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

  Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

  Study EGAS00001006331

• Childhood Cancer Survivor Study (CCSS)

  Background and Rationale for the Childhood Cancer Survivor Study (CCSS) Over the last several decades, advances in treatments for childhood and adolescent cancer have substantially improved survival following diagnosis. These improvements gave rise to the responsibility for investigating long-term treatment-associated morbidity and mortality. Early efforts to describe late effects were largely conducted through single-institution and limited consortia studies. However, by the mid-1980s, it became increasingly clear that these approaches had inherent limitations, including small sample size, convenience sampling, incompletely characterized populations, and limited length of follow-up. To overcome these limitations, the CCSS was proposed and funded by the National Cancer Institute (NCI) as a U01 grant in 1994. Subsequently, the strengths of the CCSS, including an efficient and extensive infrastructure, plus expanding database and biorepository, were recognized and appreciated. Thus, in consultation with the NCI, the CCSS was converted to a U24 (resource grant) funding mechanism to serve the scientific community in 2000. The overarching goal of the CCSS resource is to increase the conduct of innovative and high impact research related to pediatric cancer survivorship. CCSS has been used extensively by researchers from a wide range of disciplines to address a broad spectrum of topics. Strengths of the resource include its large size, comprehensive annotation of treatment exposures, ongoing longitudinal follow-up with characterization of a wide array of participant characteristics and outcomes, and an established biorepository. Design of the Childhood Cancer Survivor Study The Childhood Cancer Survivor Study (CCSS) is a multi-institutional, multi-disciplinary collaborative research resource comprised of a retrospective hospital-based cohort of survivors of childhood cancer and a comparison sibling cohort. Eligible survivors from 31 participating institutions were diagnosed between 1970 and 1999, prior to age 21 years, with selected common pediatric cancers (leukemia, central nervous system tumors, Hodgkin lymphoma, non-Hodgkin lymphoma, kidney tumors, neuroblastoma, soft tissue sarcoma, or bone tumors). All patients who survived five years from the date of diagnosis were eligible, regardless of disease or treatment status. The baseline questionnaire was completed by 24,368 survivors and 5,039 siblings recruited to serve as a comparison group. To date, participants have completed three general follow-up surveys, as well as a number of specialized surveys on specific topics (e.g. health care, insurance, screening practices, men's and women's health issues, adolescent health, sleep and fatigue). In addition, biological samples (buccal cells, saliva and/or blood) have been collected for over 11,000 participants. Full descriptions of the design and characteristics of the CCSS have been previously published (Robison et al; Leisenring et al.), and available data and samples are described at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html. Treatment Data in the Childhood Cancer Survivor Study A key feature of CCSS is the availability of detailed treatment data, which were collected by abstraction of medical records for each individual member of the cohort. Detailed abstraction included dates of therapy, protocol information, and specific details regarding surgery, chemotherapy and radiation. Quantitative dose details were collected for 22 specific chemotherapeutic agents, including alkylating agents, anthracyclines, platinum compounds and epipodophyllotoxins. In addition to individual agent doses, algorithms have been created to calculate cumulative doses of all drugs in a specific class, such as anthracyclines (doxorubicin, daunomycin and idarubicin) or platinum agents (cisplatinum and carboplatinum). Data abstracted for surgeries included dates and both the names and corresponding International Classification of Diseases (9th revision) code. For radiation treatment data, all relevant records were sent to the Radiation Physics Center at M.D. Anderson Cancer Center for detailed abstraction and dosimetry. Initial body region dosimetry was performed for all participants, followed by more detailed dosimetry as needed for specific studies. Genomics Data in the Childhood Cancer Survivor StudyThe NCI's Division of Cancer Epidemiology and Genetics and CCSS investigators collaborated to conduct genomics studies (SNP array genotyping and whole exome sequencing) using samples from the CCSS Biorepository. Studies included all cohort participants with available DNA regardless of sex or ancestry when the genomics studies were initiated. Phenotype Data in the Childhood Cancer Survivor Study Vital status and cause of death for both participants and non-participants is determined via linkage with the National Death Index (NDI). Identification of subsequent neoplasms is based on self-report, followed by validation using medical records, or via NDI. A wide array of additional health outcomes have been ascertained via a comprehensive set of questions on the CCSS questionnaires, covering potential adverse events across a range of organ systems (hearing/vision/speech, urinary, hormonal, heart and circulatory, respiratory, digestive, brain and nervous systems). In addition to health outcomes, longitudinal data have been collected on demographics, health behaviors, family history, screening practices, insurance status, and a range of psychosocial and neurocognitive factors. A full listing of available variables and copies of the CCSS questionnaires are available at http://ccss.stjude.org. Research Areas in the Childhood Cancer Survivor Study Extensive use by the research community has resulted in over 265 published manuscripts on a wide range of topics, including associations between treatment factors and mortality, subsequent neoplasms, chronic health conditions, cardiac events, neurocognitive sequelae, psychosocial factors, fertility, and health status. Additional topics have included health behaviors, screening practices, health care access and utilization, statistical and exposure assessment methodology, and development of risk prediction models. A full listing of published manuscripts using CCSS data is available on the CCSS website at https://ccss.stjude.org/published-research/publications.html. The Childhood Cancer Survivor Study as a Resource for Investigators The CCSS is an NCI-funded resource (U24 CA55727) to promote and facilitate research among long-term survivors of cancer diagnosed during childhood and adolescence. Interested investigators are encouraged to develop research ideas and propose projects within CCSS, whether or not they are from a participating CCSS institution. The CCSS is now accepting proposals to collaborate with CCSS and NCI investigators in the use of genomics data and corresponding outcomes-related data to address innovative research questions relating to potential genetic contributions to risk for treatment-related outcomes. Any researcher, or group of researchers, qualified to conduct genetic research can submit a proposal. There are no restrictions relative to country, institution, or prior involvement in CCSS. A full description of the process for developing a proposal for genetic research in CCSS can be found at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html, along with listings of approved proposals.

  Study phs001327

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, &gt;90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age&lt;20 0.043 Age&gt;40 0.032 Age&lt;30, &#8805;20 0.251 Age&gt;30, &#8804;40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd&#39;s group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient&#39;s breast and the reference materials have the same thickness as the patient&#39;s breast, then the breast&#39;s grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson&#39;s R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be &gt;0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Genomic Diagnosis and Individualized Therapy of Highly Penetrant Genetic Diabetes

  The most common and well-known causes of diabetes are type 1 and type 2 diabetes; however, there are many other etiologies of diabetes. At least 1-2% of diabetes cases result from high penetrance single gene defects, most commonly in a gene encoding either a transcription factor involved in beta cell development and function or the enzyme glucokinase (GCK). Others have mutations in transcription factors necessary for beta cell development and function. This subset of monogenic diabetes cases is autosomal dominant and is known as "Maturity-Onset Diabetes of the Young" (MODY). Patients with type 1 diabetes are insulin dependent, meaning they lack insulin production and therefore require multiple daily injections of insulin, as well as multiple times a day blood glucose monitoring. This can be quite burdensome. Type 2 diabetes is predominantly an insulin resistance problem and can often be managed with pills initially, but there are many who also require insulin either at diagnosis or later on in their disease course. Usually, monogenic diabetes is misdiagnosed as type 1 or type 2 diabetes and thus treated suboptimally. Those with monogenic diabetes, due to a defect in a gene encoding a transcription factor, respond extremely well to a class of oral diabetes medications called sulfonylureas. Those with GCK-MODY often have a mild, stable, fasting, nonprogressive hyperglycemia for which pharmacological treatment is often not necessary. It is important to accurately diagnose our patients with the correct etiology to their diabetes for a multitude of reasons. Accurately diagnosing a patient with MODY, for example, can predict their clinical course and we can tailor treatment accordingly. If diagnosed with a transcription factor MODY, we can try switching the patient from insulin to an oral sulfonylurea, and if diagnosed with a GCK-MODY, we can consider discontinuing pharmacological treatment altogether. With specific tailoring of treatment, we would hope to improve quality of life by discontinuing perhaps multiple daily injections of insulin and glucose checking as these may not be necessary. In addition, we would hope to improve glycemic control with an eventual decreased cost to society by decreasing the complication rate of diabetes, resulting in less specialty referrals, lab tests, supplies and procedures. Further, given MODY is an autosomal dominant condition with a 50% chance of inheritance to first-degree family members, we could offer testing to asymptomatic family members which could lead to prevention and/or early diagnosis and treatment. Overall, testing for monogenic diabetes is underutilized clinically. Testing is being done in the U.K., but in the U.S. we are lagging behind. This is most predominantly due to lack of knowledge and concern over cost. In addition, it is difficult to differentiate the relatively small number of monogenic diabetes cases from the larger number with type 1 and type 2 diabetes as each of these etiologies have overlapping characteristics. In fact, many patients with monogenic diabetes are being misdiagnosed with type 1 and type 2 diabetes. There are recommendations set forth by different societies on who to consider screening for monogenic diabetes. However, these recommendations are difficult to employ clinically as they are general recommendations, there is no specific algorithm, and they are based on varying levels of evidence. The purpose of this study is to implement a personalized diabetes medicine program to enhance the identification of individuals and families affected by highly penetrant diabetes gene mutations through a combination of systematic screening and genetic testing at the University of Maryland Center for Diabetes and Endocrinology, the Baltimore VA Medical Center and additional partner centers at Geisinger Health System and Bay West Endocrinology Associates, and other UM outpatient clinics. Our hope is to develop an approach that can be eventually implemented across the United States so that we can more often uncover the correct etiology to diabetes, tailor treatment accordingly, and test asymptomatic family members.

  Study phs001771