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• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• Whole genome and transcriptome sequencing of a pancreatic tumor harboring a RASGRP1 gene fusion

  Whole genome and transcriptome sequencing of a pancreatic tumor harboring a RASGRP1 gene fusion

  Dataset EGAD00001005069

• Whole-exome sequencing performed on a patient with chronic myelomonocytic leukemia and B cell acute lymphoblastic leukemia

  We studied the rare case of a patient who underwent transformation of myelodysplastic syndrome to chronic myelomonocytic leukemia and B cell acute lymphoblastic leukemia. We used fluorescence-activated cell sorting and whole-exome sequencing to identify driver mutations in the various clones. This allowed us to propose a model of branching clonal evolution with a possible germline predisposition to cancer.

  Study EGAS00001005117

• INdiana GENomics: Implementing an Opportunity for the Under Served (INGENIOUS)

  The INGenious trial planed to enroll a total of 6,000 patients, with 2,000 patients assigned to a pharmacogenetic testing arm and 4,000 to a control arm who will be followed, but not tested. It is randomized between an intervention arm and one that receives no intervention in order that the genotyped group can be compared with one in which undisturbed, routine clinical care is carried out in patients taking the same drugs. Both arms will be followed for a year after being prescribed a targeted medication. Patients randomized into the intervention arm that are prescribed one or more of the 27 targeted index medication will receive pharmacogenomic testing using a custom micro-array measuring 43 Single nucleotide polymorphisms in 14 genes. The study is being conducted by the Indiana University School of Medicine and the Indiana University Institute of Personalized Medicine in collaboration with the Eskenazi and Indiana University Health Systems and will evaluate the economic and clinical outcomes associated with embedding a pharmacogenomics program in a system that serves as the primary health care safety-net in Indianapolis, Indiana. By successfully implementing a pharmacogenomics program and integrating it with the Electronic Health Record and Clinical Decision Support system, physicians will be able to optimize patient care by delivering tailored therapeutic decisions based on the patient's individual genetics.

  Study phs001701

• The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Genetics of Genetic Epidemiology of Metabolic Syndrome in an Island Population

  The major objective of this study was to conduct a systematic genetic study of metabolic traits involved in metabolic syndrome through collection and analysis of epidemiological, demographic, environmental, and relevant biological and clinical data from a relatively isolated island population of the eastern Adriatic coast of Croatia. The population was chosen for the following reasons: 1) in spite of practicing a largely traditional life style and dietary habits, high rates of obesity, arterial hypertension, dyslipidemia and related metabolic abnormalities were found in previous studies; 2) the population was established by a relatively small number of founders, predominantly of Slavic descent from the mainland during 15th to 18th century AD, a genetically homogeneous population living in a homogeneous environment; 3) sharing a common European ancestry, a relevant population for study in the context of the general US population; 4) Croatian collaborators have been conducting anthropological and genetic studies in these communities for over three decades. There were two major aims of the study: 1) to recruit ~1200 adult participants and collect blood samples together with demographic, anthropometric, environmental and clinical data from the island of Hvar; to perform biochemical tests to measure glucose, insulin, uric acid and lipid levels; 2) conduct a genome-wide association analysis of metabolic traits and phenotypes using genome-wide SNP arrays (Affymetrix Genome-Wide Human SNP Array 5.0).

  Study phs000737

• CAGE Profiling of ncRNAs in Hepatocellular Carcinoma Reveals a Strong Activation of Retroviral LTR Promoters in Virus-Induced Tumors

  The ncRNA transcriptome of human hepatocellular carcinoma (HCC) is largely unexplored. We used CAGE to characterize transcription start sites across different etiologies of human HCCs with emphasis on ncRNAs. Here we report that retroviral LTR promoters, expressed in healthy tissues such as testis and placenta but not liver, are widely activated in HCC. Despite HCC heterogeneity, a subset of LTR-derived ncRNAs were more than 10-fold up-regulated in the vast majority of samples. HCCs with a high LTR activity mostly had a viral etiology, were less differentiated and showed higher risk of recurrence. CAGE enabled us to build a promoter map for HCC, which uncovers a new layer of complexity in HCC genomics.

  Study phs000885

• Exceptional Responders Initiative

  The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

  Study phs001145

• Discordant_Monozygotic_Twins_ALS (Epigenetics)

  We conducted a multi-omics study on a monozygotic twin pair discordant for amyotrophic lateral sclerosis. Here, we submit epigenetic data from EPIC array.

  Study EGAS00001008053

• Longitudinal evaluation of circulating tumor DNA in early breast cancer receiving neoadjuvant systemic therapy using a tumor-informed assay

  This study evaluates a highly sensitive tumor-informed ctDNA assay in a real-world cohort of patients receiving neoadjuvant therapy (NAT) to assess clinical validity and explores prognostic outcomes

  Study EGAS50000000771

• BCL11B enhancer hijacking defines a subtype of lineage ambiguous stem cell leukemia

  Hijacking of primitive hematopoietic enhancers, or generation of a neo-enhancer by genomic amplification, results in deregulation of BCL11B as the defining feature of a subset of T/myeloid leukemia

  Study EGAS00001004810