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• Ameloblastoma Cell Line Resource

  Ameloblastoma (AB) is an odontogenic tumor that is locally destructive to the jaw bone. Treatment entails surgical resection, but AB often recurs locally. Recent driver mutations have been identified in the MAPK and Hedgehog pathways. However, translation to molecularly-targeted therapies has been hampered by the lack of AB cell line models. The goal of our study has been to create a new AB cell line resource that reflects the spectrum of AB driver mutations. We created 6 new AB cell lines, and by targeted exome sequencing, defined their driver mutations. We showed the utility of these cell lines in preclinical studies of oncogene dependence and drug sensitivity (which includes whole transcriptome assays).

  Study phs002753

• Preclinical Modeling of Leiomyosarcoma Identifies Susceptibility to Transcriptional CDK Inhibitors through Antagonism of E2F-Driven Oncogenic Gene Expression

  Leiomyosarcoma (LMS) is a smooth muscle-derived mesenchymal cancer commonly found to have recurrent loss of tumor suppressor genes and a poorly defined oncogenic program. Empiric cytotoxic chemotherapy is the standard systemic treatment for LMS, and while more targeted and effective therapies are urgently needed, insights into therapeutic vulnerabilities in LMS have been limited by available preclinical models. We generated a panel of LMS patient-derived xenograft (PDX) models and evaluated fidelity to their tumors of origin using RNA sequencing and ultra-low passage whole-genome sequencing (ULP-WGS). Data available at dbGaP include RNA sequencing and ULP-WGS of primary tumors and early and late passages of PDX. 

  Study phs002587

• Genetic Analysis of Substance Use Disorder Using the Indiana Biobank Data

  The goal of this study is to identify genes related to substance use disorders. The study participants were selected from the Indiana Biobank. The Indiana Biobank provides centralized processing and storage of specimens that are linked to participants' electronic medical information. Cases were defined as having any type of substance use disorders by using ICD9/10 codes, including alcohol, cannabis, cocaine, opioid, nicotine, and other substances. Controls were defined as not having any type of substance use disorders. The Indiana Biobank is part of the Indiana Clinical and Translational Sciences Institute (CTSI), a state-wide research partnership among Indiana University, Purdue University, and the University of Notre Dame.

  Study phs003025

• Grady Trauma Project (GTP)

  Not everyone exposed to traumatic experience develops Posttraumatic Stress Disorder (PTSD). Genetic background is one of the predisposing risk factors causing differential outcomes of trauma exposure. A primary goal of the Grady Trauma Project (GTP) is to pinpoint and understand genetic polymorphisms that contribute to development of PTSD. Both PTSD diagnosis binary labels and PTSD severity scores are studied as target phenotypes. Also, both candidate gene studies and genome-wide association studies are performed. Besides genetic variants, other measurements that are studied as risk factors for PTSD include lifetime history of trauma and peri-traumatic response. Study participants are primarily African American, trauma-exposed populations of low socioeconomic status recruited from Grady Memorial Hospital in Atlanta.

  Study phs002046

• Genetic contributions of lupus nephritis in a multi-ethnic cohort of systemic lupus erythematosus (SLE)

  Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE) and it occurs at a much higher rate in patients that are not of European descent. The purpose of this study is to identify genetic variants contributing to the risk of LN in a multi-ethnic cohort of SLE patients. We used a comprehensive genome-wide screen and 1244 SLE patients from 5 different ethnic groups. In genome-wide gene-based and candidate SNP analyses, we found distinct genes and pathways, and established risk SNPs associated with lupus nephritis for each ethnic group. This study represents progress in elucidating the genetic underpinnings driving LN among SLE patients of different ethnic groups.

  Study phs001609

• Diabetes Multi-Omic Investigation of Drug Response (DIAMOND)

  The Diabetes Multi-omic Investigation of Drug Response (DIAMOND) cohort is a population-based cohort of individuals with type-2 diabetes (T2D) who receive their care through a large health system serving southeast Michigan and metropolitan Detroit. The cohort represents the diversity of the population from which it was created. Because of their health plan membership, participants have a rich dataset of longitudinal clinical health information related to their care. The intent of the DIAMOND study is to use genomic profiling, drug exposure information, and electronic health record (EHR) derived outcome data to identify genetic predictors of treatment response. Genome-wide genotyping was performed using the AxiomTM Precision Medicine Research Array (ThermoFisher Scientific Inc.).

  Study phs003350

• Biomarker Research for Anti EGFR Monoclonal Antibodies by Comprehensive Cancer Genomics

  The purpose of this study is to explore new biomarkers for predicting the effectiveness of an anti-epidermal growth factor receptor (anti-EGFR) antibody in patients with advanced colorectal cancer. The investigation involves analyzing the entire exome, conducting a genome-wide association study (GWAS), and analyzing copy number variations (CNVs) using single nucleotide polymorphism (SNP) arrays. Genetic material from both cancerous and non-cancerous tissues, as well as blood samples from patients who received the antibody treatment, will be used. The goal is to identify genetic mutations and SNPs associated with treatment efficacy and adverse events, and to assess the correlation between their presence and treatment effectiveness using statistical methods.

  Study JGAS000779

• Proteomic measurements in BioBank Japan

  The BioBank Japan (BBJ) is a biobank established in the Institute of Medical Science, the University of Tokyo to collect clinical information and biological materials (DNA and serum samples). It collected about 200 thousand participants of 47 diseases started in 2003 (BBJ 1st cohort), and 67 thousand participants of 38 diseases started in 2013 (BBJ 2nd cohort), both in collaboration with 12 medical centers through the MEXT and AMED's "The BioBank Japan Project." This project is aiming at further utilization of the materials, and clinical and genomic information managed by BBJ to contribute to precision medicine by storing, managing, and providing the materials and data, as well as identifying biomarkers associated with disease risk, prognosis, and drug sensitivity.

  Study JGAS000785

• CAGE analysis for non-small cell lung carcinoma

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. To achieve this goal, we performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD). The result was followed up by by immunohistochemical analysis (IHC) in an independent group.

  Study JGAS000070

• The role of gut microbiota in metabolic diseases

  Diabetes is a major disease in the elderly and is responsible for increased risk of myocardial infarction and stroke. Recently, the relationship between microbiota and diabetes has been reported in animals and humans. In this study, blood, stool, and saliva samples were collected from examinees at the University of Tokyo Health Screening Center, and 16S rRNA and metagenomic analyses were performed to determine the variation of microbiota. Furthermore, metabolome analysis and transcriptome analysis (CAGE analysis) using blood were performed to reveal changes in host metabolites and gene expression. By comparing the host- and bacteria- derived information with the metabolic parameters, we analyzed whether microbiota can be a predictor of metabolic diseases.

  Study JGAS000569