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PDF file - 981KB, Representative Immunohistochemistry for CHD7 Expression in Primary Tumor Tissue (S1). Network Analysis via MetaCore ExPlain Process Network Analysis for genes involved in CHK1, CDC25A, AURKB, PLK1, HUS1 pathway (S2). CHD7 Knockdown Causes Gemcitabine Sensitization (S3). Mice with Xenograft Tumors Showed No Significant Difference in Body Weight (S4). CHD7 Knockdown Effect on Cell Cycle (S5). Gemcitabine Does Not Significantly Change CHD7 Protein Levels in Cells (S6).

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XLS file - 675KB, Full Results of Primary Gemcitabine Sensitivity Screen (S1). Known DNA Damage Response Genes Identified as Hits in Gemcitabine Sensitivity Screen (S2). Dysregulation, Differential Expression, and Literature RNAi Cross-Reference for Known DDR Genes and Select Hits (S3). Selected Top 15% of Gemcitabine Sensitivity Genes Tested on Secondary Screen (S4).

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor outcomes with current therapies. Gemcitabine is the primary adjuvant drug used clinically, but its effectiveness is limited. In this study, our objective was to use a rationale-driven approach to identify novel biomarkers for outcome in patients with early-stage resected PDAC treated with adjuvant gemcitabine. Using a synthetic lethal screen in human PDAC cells, we identified 93 genes, including 55 genes linked to DNA damage responses (DDR), that demonstrated gemcitabine sensitization when silenced, including CHD7, which functions in chromatin remodeling. CHD7 depletion sensitized PDAC cells to gemcitabine and delayed their growth in tumor xenografts. Moreover, CHD7 silencing impaired ATR-dependent phosphorylation of CHK1 and increased DNA damage induced by gemcitabine. CHD7 was dysregulated, ranking above the 90th percentile in differential expression in a panel of PDAC clinical specimens, highlighting its potential as a biomarker. Immunohistochemical analysis of specimens from 59 patients with resected PDAC receiving adjuvant gemcitabine revealed that low CHD7 expression was associated with increased recurrence-free survival (RFS) and overall survival (OS), in univariate and multivariate analyses. Notably, CHD7 expression was not associated with RFS or OS for patients not receiving gemcitabine. Thus, low CHD7 expression was correlated selectively with gemcitabine sensitivity in this patient population. These results supported our rationale-driven strategy to exploit dysregulated DDR pathways in PDAC to identify genetic determinants of gemcitabine sensitivity, identifying CHD7 as a novel biomarker candidate to evaluate further for individualizing PDAC treatment. Cancer Res; 74(10); 2677–87. ©2014 AACR.

Mosaic variants in the PIK3CA gene, encoding the catalytic subunit of phosphoinositide 3-kinase (PI3K), produce constitutive PI3K activation, which causes PIK3CA-related overgrowth spectrum disorders. To date, fewer than 20 patients have been described with germline alterations in PIK3CA. In this study, we describe three unrelated individuals with overgrowth and germline PIK3CA variants. These variants were discovered through whole-exome sequencing and confirmed as germline by testing multiple tissue types, when available. Functional analysis using Patient 1’s fibroblast cell line and two previously reported patients’ cell lines showed increased phosphorylation of AKT during cellular starvation revealing constitutive activation of the phosphoinositide-3-kinase/protein kinase B/mechanistic target of rapamycin (PI3K/AKT/mTOR) pathway. Alternatively, stimulation of the cells by fetal bovine serum produced a reduced response, indicating an activated status of the PI3K complex reducing the pathway response to further external stimulation. Additional studies utilizing Biolog Phenotype Microarray technology indicated reduced energy production when cells were exposed to growth factors stimulating the PI3K/AKT/mTOR pathway, confirming the trend observed in the AKT phosphorylation test after stimulation. Furthermore, treatment with inhibitors of the PI3K/AKT/mTOR pathway rescued the normal energy response in the patients’ cells. Collectively, these data demonstrate that disease-causing germline PIK3CA variants have a functional consequence, similar to mosaic variants in the PI3K/AKT/mTOR pathway.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterized by challenges in social communication as well as repetitive or restrictive behaviors. Many genetic associations with ASD have been identified, but most associations occur in a fraction of the ASD population. Here, we searched for eQTL-associated DNA variants with significantly different allele distributions between ASD-affected and control. Thirty significant DNA variants associated with 174 tissue-specific eQTLs from ASD individuals in the SPARK project were identified. Several significant variants fell within brain-specific regulatory regions or had been associated with a significant change in gene expression in the brain. These eQTLs are a new class of biomarkers that could control the myriad of brain and non-brain phenotypic traits seen in ASD-affected individuals.

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that poses several challenges in terms of clinical diagnosis and investigation of molecular etiology. The lack of knowledge on the pathogenic mechanisms underlying ASD has hampered the clinical trials that so far have tried to target ASD behavioral symptoms. In order to improve our understanding of the molecular abnormalities associated with ASD, a deeper and more extensive genetic profiling of targeted individuals with ASD was needed. Methods: The recent availability of new and more powerful sequencing technologies (third-generation sequencing) has allowed to develop novel strategies for characterization of comprehensive genetic profiles of individuals with ASD. In particular, this review will describe integrated approaches based on the combination of various omics technologies that will lead to a better stratification of targeted cohorts for the design of clinical trials in ASD. Results: In order to analyze the big data collected by assays such as whole genome, epigenome, transcriptome, and proteome, it is critical to develop an efficient computational infrastructure. Machine learning models are instrumental to identify non-linear relationships between the omics technologies and therefore establish a functional informative network among the different data sources. Conclusion: The potential advantage provided by these new integrated omics-based strategies is to better characterize the genetic background of ASD cohorts, identify novel molecular targets for drug development, and ultimately offer a more personalized approach in the design of clinical trials for ASD.

The course of 187 individuals ages 3–21 years with Autistic Disorder was traced through a period of 20 years (enrollment: 1995–1998, follow up: 2014–2019). Specific genetic and environmental causes were identified in only a minority. Intellectual disability coexisted in 84%. Few became independent with 99% living at home with relatives, in disability group homes or in residential facilities. Seven individuals (3.7%) attained postsecondary education, two receiving baccalaureate degrees, two receiving associate degrees, and three receiving certificates from college disability programs. It may be anticipated that the long term outcome for individuals currently diagnosed with Autism Spectrum Disorder (ASD) will be substantially better than for individuals with Autistic Disorder in this cohort.

Uterine cancer is the fourth most common cancer among women, projected to affect 66,000 US women in 2021. Uterine cancer often arises in the inner lining of the uterus, known as the endometrium, but can present as several different types of cancer, including endometrioid cancer, serous adenocarcinoma, and uterine carcinosarcoma. Previous studies have analyzed the genetic changes between normal and cancerous uterine tissue to identify specific genes of interest, including TP53 and PTEN. Here we used Gaussian Mixture Models to build condition-specific gene coexpression networks for endometrial cancer, uterine carcinosarcoma, and normal uterine tissue. We then incorporated uterine regulatory edges and investigated potential coregulation relationships. These networks were further validated using differential expression analysis, functional enrichment, and a statistical analysis comparing the expression of transcription factors and their target genes across cancerous and normal uterine samples. These networks allow for a more comprehensive look into the biological networks and pathways affected in uterine cancer compared with previous singular gene analyses. We hope this study can be incorporated into existing knowledge surrounding the genetics of uterine cancer and soon become clinical biomarkers as a tool for better prognosis and treatment.

Background Lung cancer is the leading cause of cancer death in both men and women. The most common lung cancer subtype is non-small cell lung carcinoma (NSCLC) comprising about 85% of all cases. NSCLC can be further divided into three subtypes: adenocarcinoma (LUAD), squamous cell carcinoma (LUSC), and large cell lung carcinoma. Specific genetic mutations and epigenetic aberrations play an important role in the developmental transition to a specific tumor subtype. The elucidation of normal lung versus lung tumor gene expression patterns and regulatory targets yields biomarker systems that discriminate lung phenotypes (i.e., biomarkers) and provide a foundation for the discovery of normal and aberrant gene regulatory mechanisms. Results We built condition-specific gene co-expression networks (csGCNs) for normal lung, LUAD, and LUSC conditions. Then, we integrated normal lung tissue-specific gene regulatory networks (tsGRNs) to elucidate control-target biomarker systems for normal and cancerous lung tissue. We characterized co-expressed gene edges, possibly under common regulatory control, for relevance in lung cancer. Conclusions Our approach demonstrates the ability to elucidate csGCN:tsGRN merged biomarker systems based on gene expression correlation and regulation. The biomarker systems we describe can be used to classify and further describe lung specimens. Our approach is generalizable and can be used to discover and interpret complex gene expression patterns for any condition or species.

Kosaki overgrowth syndrome is a recently described syndrome characterized by distinctive facial features, brain white matter lesions, and developmental delay. Germline activating heterozygous PDGFRB mutations have been reported in this condition. Systemic connective tissue-type findings have been described in some individuals. We describe a 19-year-old Caucasian female with a history of hydrocephalus, Dandy-Walker malformation, cervical spine arachnoid cyst, progressive scoliosis, and overgrowth. Her physical exam included distinctive craniofacial dysmorphism, as well as soft and hyperextensible skin. Cardiovascular imaging during adolescence revealed saccular aneurysms in both coronary artery systems and subtle tortuosity of the cervical vertebral arteries. Exome sequencing trio analysis identified a de novo previously reported pathogenic variant in PDGFRB, c.1696T>C (p.[Trp566Arg]). Further functional studies included platelet-derived growth factor cellular metabolic pathway activity that confirmed the variant causes a constitutive activation of the PI3K-AKT pathway. This is the first report to characterize the activating nature of this PDGFRB variant. We also highlight the connective tissue findings seen in Kosaki overgrowth syndrome and recommend baseline echocardiographic evaluation in all individuals with this condition with particular emphasis on coronary arteries.

Background: The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a large number of patient-derived xenograft (PDX) models from a diverse set of rare cancers. These models have been genomically characterized using whole-exome sequencing (WES) and RNAseq. The resource provides a unique opportunity to explore the genomic features of rare tumor models in NCI PDMR and to understand the oncogenic processes in pre-clinical models to identify biomarkers associated with therapeutic responses. Methods: Genomic characterization was done in 4-6 PDX samples across multiple passages and lineages from each model. As the samples exhibited a high level of genomic stability within each model, consensus mutation and copy number variation (CNV), microsatellite instability (MSI), genomic loss of heterozygosity (LOH), homologous recombination deficiency score (scarHRD), and mutational signature data were generated from WES. Fusions were identified from RNASeq data using Star-Fusion and FusionInspector. Gene set enrichment analysis was conducted from the gene expression data obtained from RNAseq. Results: 1) 233 PDX models have been developed and characterized from more than 45 different rare malignancies. Most frequent cancer types are different sarcomas (n=63), head & neck squamous cell carcinoma (n=61), and malignant fibrous histiocytoma (MFH) (n=11); 2) TP53 was the most frequently altered gene, mutated in 51% of models, followed by NOTCH1 (16%) and PIK3CA (11%). In terms of CNVs, ovarian epithelial cancer (OVT) showed relatively high chromosomal instability, while uterine endometrioid carcinoma (UEC) and synovial sarcoma (SYNS) had low instability; 3) MSI-H was observed in only 7 models. Esophageal adenocarcinoma (ESCA), OVT, and cervical squamous cell carcinoma (CESC) had high scarHRD and genomic LOH scores, while both scores were low in UEC and anal squamous cell carcinoma (ANSC). COSMIC v2 mutational signature 3 is significantly associated with a high scarHRD score (p-value < 0.01, Wilcoxon rank-sum test); 4) Characteristic fusions were observed in certain sarcoma models: SS18-SSX1 and ASPSCR1-TFE3 fusions were observed in SYNS and alveolar soft part sarcoma (ASPS) models respectively. EWSR1-FLI1 fusion was present in 2 out of 3 Ewing sarcoma (ES) models. 5) Gene set enrichment analysis from RNASeq data showed that epithelial-mesenchymal transition score could accurately distinguish carcinoma from sarcoma models, confirming the divergent gene expression programs. Conclusion: Comprehensive genomic characterization of NCI PDMR models generated from rare cancers solves an unmet need in the community. It will serve as a valuable resource for translational researchers interested in pre-clinical drug development and discovery. Citation Format: Li Chen, Rini Pauly, Ting-Chia Chang, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna Lee Fong, Amanda Peach, Shahanawaz Jiwani, Nastaran Neishaboori, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Corinne Camalier, Thomas Forbes, Michelle Gottholm-Ahalt, John Carter, Suzanne Borgel, Chelsea McGlynn, Candace Mallow, Emily Delaney, Tiffanie Miner, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Genomic characterization of PDX models from rare cancer patients in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 80.

Background: A PDX bladder cancer model, BL0293-F563, spontaneously metastasizes to the liver and bone, and sheds high numbers of circulating tumor cells (CTCs). This PDX model provides a unique opportunity to explore the relationships between primary tumors, CTCs, and metastases. Methods: BL0293-F563 tumors (available from the NCI Patient-Derived Models Repository [https://pdmr.cancer.gov/] and originally developed by Jackson Laboratories) were implanted into NSG mice, and primary tumors, metastatic nodules in the liver, and blood were collected at maximal allowable tumor burden. Tumor tissue was dissociated using Miltenyi Tumor Dissociation Kit with OctoDissociator, and Human CTCs were enriched from mouse blood through negative selection with anti-mouse CD45 and anti-mouse MHC-1 magnetic beads. Single cell sequencing was done using 10X Genomics 3’ gene expression assay v3.1. Data processing and analysis was done using 10X Genomics’ Cell Ranger pipeline, Seurat, and cNMF. Results: single cell RNAseq data from primary tumors, CTCs, and metastases from 9 mice were aggregated into a single dataset, and cells were classified into 17 clusters using Seurat FindNeighbors. All clusters contained cells from multiple sites (primary tumor, CTCs, metastases), but three clusters were enriched in CTCs and one cluster was composed of mostly primary tumor cells. All clusters exhibited epithelial-like gene expression signature scores, suggesting that CTC shedding was occurring without prominent epithelial-mesenchymal transition. CTC-enriched clusters showed elevated expression of RHO pathway genes, implicating ameboid-like migration in CTC shedding in this PDX model. Consistent with expected differences in oxygenation states, CTC-enriched clusters exhibited a lower hypoxia gene expression score than primary tumor and metastasis-enriched clusters. CTC-enriched clusters also showed higher expression of oxidative phosphorylation genes, suggesting metabolic differences between CTCs and cells from other sites. Additionally, two of three CTC-enriched clusters had elevated expression of mitosis-associated genes, indicating that at least some subpopulations of CTCs are actively cycling. A metastasis suppressor gene KISS1 was expressed in a subset of primary tumor cells but undetectable in CTCs, suggesting that KISS1 expression loss occurs before CTC shedding. Conclusions: Utilizing single cell gene expression profiling, we have linked the gene expression profile of CTCs to specific cell subpopulations in primary tumors and metastases. We show that CTC-enriched cell clusters appear to maintain an epithelial phenotype. Subpopulations of CTC cells exhibit enrichment of motility-associated transcripts and features of active cell cycling. Our results implicate a known metastasis suppressor gene KISS1 in CTC shedding and metastatic dissemination in this PDX model. Citation Format: Tomas Vilimas, Brandie Fullmer, Alyssa Chapman, Rini Pauly, Ting-Chia Chang, Li Chen, Biswajit Das, Chris Karlovich, Yvonne Evrard, Melinda Hollingshead, Howard Stotler, Michelle Ahalt-Gottholm, Tara Grinnage-Pulley, Mickey Williams, James H. Doroshow. Comparative single cell transcriptome profiling of primary tumors, CTCs and metastatic sites from a bladder cancer PDX model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 973.

3035 Background: The National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) multi-arm phase II clinical trial tested tumor tissue from 5,954 patients with advanced refractory cancer to assign treatment based on the molecular profile. Molecular profiling was successful for 93% of patients. For 267 of the patients who were not enrolled because molecular profiling was not successful, plasma cfDNA was evaluated to provide insight into the potential utility of blood-based testing in a broad spectrum of histologies when tissue is not evaluable. Methods: Cell-free DNA was extracted from plasma collected from Streck blood tubes and quantitated. Libraries were constructed using ³ 15 ng cfDNA into the Illumina TruSight Oncology 500 ctDNA RUO Assay, including unique molecular identifiers and duplex barcodes for error correction. Libraries were sequenced on the NovaSeq 6000 with S4 XP flow cells. Results: Of the 267 samples, 250 samples (94%) were evaluable, representing 72 histologies, including colorectal cancer (N = 36), lung adenocarcinoma (N = 15), pancreatic adenocarcinoma (N = 14), and invasive breast carcinoma (N = 12). Of these, 231 (92%) had ³ 1 OncoKB annotated mutation, with 208 patients (83%) having putative somatic mutations detected in genes not commonly associated with clonal hematopoiesis. The most common somatic mutations were in TP53, KRAS, APC, and PIK3CA, reported in 51%, 20%, 12%, and 12% of patients respectively. A total of 109 patients (44%) had ³ 1 actionable mutation of interest (aMOI) reported that could have been used for treatment assignment in the NCI-MATCH clinical trial. After applying histology and molecular exclusions, 75 patients (30%) had ³ 1 aMOI. The most common assignable treatment arms were Z1B/Z1BX1 (palbociclib with CCND1/2/3, N = 13), Z1F (copanlisib with PIK3CA Mutations, N = 13), S1/S1X1 (trametinib with NF1 mutation, N = 12), and Z1C/Z1CX1 (palbociclib with CDK4/CDK6 Amplification and Rb Expression by IHC, N = 10). Mutations in genes commonly associated with clonal hematopoiesis (CH) were prevalent in this population. Along with the expected high frequency of DNMT3A (21% of patients) and TET2 (11%) mutations, PPM1D mutations were the highest amongst CH genes, with 61 patients (24%) having ³ 1 PPM1D mutation, likely due to the heavily pre-treated nature of these patients. Conclusions: Variants observed in the blood are consistent with what is reported in the tissue. Using liquid biopsy when tissue is not evaluable can expand the ability of patients to obtain mutation information that can inform treatment compared to using tumor tissue only. Cell-free DNA provided valuable mutation information for these patients and could have resulted in up to an additional 75 patients being eligible for treatment selection based on their mutation profile. These results indicate that blood-based screening could be a tool for future NCI-sponsored clinical studies.

BACKGROUND: Molecular profiling of childhood CNS tumors is critical for diagnosis and clinical management, yet tissue access is restricted due to sensitive neuroanatomical locations. Moreover, CNS tumors including diffuse midline glioma (DMG) exhibit mutational heterogeneity and clonal evolution, which cannot be captured by upfront diagnostic biopsy alone. To address the lack of tumor visibility, and tprovide opportunity for longitudinal sampling, we validated and optimized a commercially available deep sequencing platform for analysis of circulating tumor DNA (TSO500ctDNATM). METHODS: In a proof-of-concept study, we defined the sensitivity, specificity, and clinical relevance of our novel ctDNA platform via analysis of paired tissue, CSF, and blood from children with DMG (n=10). Paired samples were assessed for concordance and sequencing results were compared to digital droplet PCR (ddPCR) detection of prognostic H3K27M mutation. RESULTS: DMG associated mutations in genes including H3-3A, H3C2, TP53, and ACVR1 were detected in ctDNA, including in CSF samples with low (

Background Phelan-McDermid syndrome is characterized by a range of neurodevelopmental phenotypes with incomplete penetrance and variable expressivity. It is caused by a variable size and breakpoint microdeletions in the distal long arm of chromosome 22, referred to as 22q13.3 deletion syndrome, including the SHANK3 gene. Genetic defects in a growing number of neurodevelopmental genes have been shown to cause genome-wide disruptions in epigenomic profiles referred to as epi-signatures in affected individuals. Results In this study we assessed genome-wide DNA methylation profiles in a cohort of 22 individuals with Phelan-McDermid syndrome, including 11 individuals with large (2 to 5.8 Mb) 22q13.3 deletions, 10 with small deletions (SHANK3 and one mosaic case. We describe a novel genome-wide DNA methylation epi-signature in a subset of individuals with Phelan-McDermid syndrome. Conclusion We identified the critical region including the BRD1 gene as responsible for the Phelan-McDermid syndrome epi-signature. Metabolomic profiles of individuals with the DNA methylation epi-signature showed significantly different metabolomic profiles indicating evidence of two molecularly and phenotypically distinct clinical subtypes of Phelan-McDermid syndrome.

SATB2-associated syndrome (SAS) is a multisystemic disorder characterized by developmental delay often with concurrent autistic tendencies. This study aimed to characterize cellular metabolic pathways and energy metabolism from cells derived from individuals with SAS. The cellular production of NADH (nicotinamide adenine dinucleotide, reduced form) as determined by the Phenotype Mammalian MicroArrays was measured in lymphoblastoid cell lines derived from 11 subjects with a molecularly confirmed diagnosis of SAS and compared to a control population of 50 age-matched typically developing individuals. All patients were evaluated clinically by a multidisciplinary team. Eleven individuals (five in a screening cohort and six in the validation cohort, mean age 6.1 years) were recruited to the study. All individuals had developmental delay and the diagnosis of autism was previously established in five of them. Key metabolic findings included reduced NADH production in the presence of phosphorylated carbohydrates (with corresponding increased production in the presence of alternative carbon-based energy sources), increased response to certain hormones (β-estradiol in particular), and significantly reduced levels of NADH in wells containing tryptophan. The individual analysis revealed no particular differences among the SAS subjects based on molecular findings or phenotypic features. In conclusion, individuals with SAS have a common and recognizable metabolic profile. A lower capacity to utilize glucose as an energy substrate could be contributing to the neurodevelopment phenotype of SAS. The identified abnormalities offer previously unexplored insight into the potential pathophysiology of common SAS phenotypic features.

Advanced imaging and DNA sequencing technologies now enable the diverse biology community to routinely generate and analyze terabytes of high resolution biological data. The community is rapidly heading toward the petascale in single investigator laboratory settings. As evidence, the single NCBI SRA central DNA sequence repository contains over 45 petabytes of biological data. Given the geometric growth of this and other genomics repositories, an exabyte of mineable biological data is imminent. The challenges of effectively utilizing these datasets are enormous as they are not only large in the size but also stored in geographically distributed repositories in various repositories such as National Center for Biotechnology Information (NCBI), DNA Data Bank of Japan (DDBJ), European Bioinformatics Institute (EBI), and NASA’s GeneLab. In this work, we first systematically point out the data-management challenges of the genomics community. We then introduce Named Data Networking (NDN), a novel but well-researched Internet architecture, is capable of solving these challenges at the network layer. NDN performs all operations such as forwarding requests to data sources, content discovery, access, and retrieval using content names (that are similar to traditional filenames or filepaths) and eliminates the need for a location layer (the IP address) for data management. Utilizing NDN for genomics workflows simplifies data discovery, speeds up data retrieval using in-network caching of popular datasets, and allows the community to create infrastructure that supports operations such as creating federation of content repositories, retrieval from multiple sources, remote data subsetting, and others. Named based operations also streamlines deployment and integration of workflows with various cloud platforms. Our contributions in this work are as follows 1) we enumerate the cyberinfrastructure challenges of the genomics community that NDN can alleviate, and 2) we describe our efforts in applying NDN for a contemporary genomics workflow (GEMmaker) and quantify the improvements. The preliminary evaluation shows a sixfold speed up in data insertion into the workflow. 3) As a pilot, we have used an NDN naming scheme (agreed upon by the community and discussed in Section 4) to publish data from broadly used data repositories including the NCBI SRA. We have loaded the NDN testbed with these pre-processed genomes that can be accessed over NDN and used by anyone interested in those datasets. Finally, we discuss our continued effort in integrating NDN with cloud computing platforms, such as the Pacific Research Platform (PRP). The reader should note that the goal of this paper is to introduce NDN to the genomics community and discuss NDN’s properties that can benefit the genomics community. We do not present an extensive performance evaluation of NDN—we are working on extending and evaluating our pilot deployment and will present systematic results in a future work.

The course of 187 individuals ages 3-21 years with Autistic Disorder was traced through a period of 20 years (enrollment: 1995-1998, follow up: 2014-2019). Specific genetic and environmental causes were identified in only a minority. Intellectual disability coexisted in 84%. Few became independent with 99% living at home with relatives, in disability group homes or in residential facilities. Seven individuals (3.7%) attained postsecondary education, two receiving baccalaureate degrees, two receiving associate degrees, and three receiving certificates from college disability programs. It may be anticipated that the long term outcome for individuals currently diagnosed with Autism Spectrum Disorder (ASD) will be substantially better than for individuals with Autistic Disorder in this cohort.

Background Autism spectrum disorder (ASD) is a common neurodevelopmental disorder whose molecular mechanisms are largely unknown. Several studies have shown an association between ASD and abnormalities in the metabolism of amino acids, specifically tryptophan and branched‐chain amino acids (BCAAs). Methods Ninety‐seven patients with ASD were screened by Sanger sequencing the genes encoding the heavy (SLC3A2) and light subunits (SLC7A5 and SLC7A8) of the large amino acid transporters (LAT) 1 and 2. LAT1 and 2 are responsible for the transportation of tryptophan and BCAA across the blood–brain barrier and are expressed both in blood and brain. Functional studies were performed employing the Biolog Phenotype Microarray Mammalian (PM‐M) technology to investigate the metabolic profiling in lymphoblastoid cell lines from 43 patients with ASD and 50 controls with particular focus on the amino acid substrates of LATs. Results We detected nine likely pathogenic variants in 11 of 97 patients (11.3%): three in SLC3A2, three in SLC7A5, and three in SLC7A8. Six variants of unknown significance were detected in eight patients, two of which also carrying a likely pathogenic variant. The functional studies showed a consistently reduced utilization of tryptophan, accompanied by evidence of reduced utilization of other large aromatic amino acids (LAAs), either alone or as part of a dipeptide. Conclusion Coding variants in the LAT genes were detected in 17 of 97 patients with ASD (17.5%). Metabolic assays indicate that such abnormalities affect the utilization of certain amino acids, particularly tryptophan and other LAAs, with potential consequences on their transport across the blood barrier and their availability during brain development. Therefore, abnormalities in the LAT1 and two transporters are likely associated with an increased risk of developing ASD., Abnormalities in the metabolism of amino acids have been reported in cases with ASD. We detected 9 likely pathogenic variants in the genes encoding the subunits of the large amino acid transporters (LAT 1 and 2) in 11 of 97 patients (11.3%). Metabolic assays suggest that such variants may affect the utilization of certain amino acids, particularly tryptophan and other LAAs, with potential consequences on their transport across the blood barrier and their availability during brain development.

Background: A PDX bladder cancer model, BL0293-F563, grows large subcutaneous tumors, spontaneously metastasizes to the liver and bone, and sheds high numbers of circulating tumor cells (CTCs). This PDX model provides a unique opportunity to explore the relationships between primary tumors, CTCs and metastatic cell subpopulations. Methods: BL0293-F563 tumors (available from the NCI Patient-Derived Models Repository [https://pdmr.cancer.gov/] and originally developed by Jackson Laboratories) were implanted into NSG mice and and primary tumors, metastatic nodules in the liver, and blood were collected at maximal allowable tumor burden. Tumor tissue was dissociated using Miltenyi Tumor Dissociation Kit with OctoDissociator, and Human CTCs were enriched from whole mouse blood through negative selection with anti-mouse CD45 and anti-mouse MHC-1 magnetic beads. Single cell sequencing was done using 10X Genomics 3’ gene expression assay v3.1. Sequencing libraries were prepared using 10X Genomics Chromium and 3’ gene expression kit v3.1. Data processing and analysis was done using 10X Genomics’ Cell Ranger pipeline, Seurat, and consensus non-negative matrix factorization. Results: Using Seurat FindNeighbors, cells in the aggregated dataset were classified into 17 distinct clusters. All clusters were comprised of cells from multiple sites (primary tumor, CTCs, metastases), but three clusters were enriched in CTCs and one cluster was composed of mostly primary tumor cells. All clusters exhibited an epithelial-like gene expression signature score, suggesting that CTC shedding was occurring without prominent epithelial-mesenchymal transition. Consistent with expected differences in oxygenation states, CTC-enriched clusters exhibited a lower hypoxia gene expression score than primary tumor and metastasis-enriched clusters. CTC-enriched clusters also showed higher expression of oxidative phosphorylation genes, suggesting metabolic differences between CTCs and cells from primary tumors and metastases. Based on Human Primary Cell Atlas phenotype prediction, several clusters were associated with stem cell like phenotypes. Additionally, two of three CTC-enriched clusters had elevated expression of mitosis-associated genes, suggesting that at least some populations of CTCs are not quiescent but actively cycling. Conclusions: Utilizing single cell gene expression profiling, we have linked the gene expression profile of CTCs to specific cell subpopulations in primary tumors and metastases. We show that CTC-enriched cell clusters appear to maintain an epithelial phenotype. Subpopulations of CTC cells exhibited enrichment of stemness-associated transcripts and features of active cell cycling. Citation Format: Tomas Vilimas, Brandie Fullmer, Alyssa Chapman, Li Chen, Ting-Chia Chang, Rini Pauly, Biswajit Das, Chris Karlovich, Yvonne A. Evrard, Howard Stotler, Michelle M. Gottholm-Ahalt, Tara Grinnage-Pulley, Melinda G. Hollingshead, James H. Doroshow, P. Mickey Williams. Comparative single cell transcriptome profiling of primary tumors, CTCs and metastatic sites from a bladder cancer PDX model [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P097.

Experiments employing the Phenotype Mammalian Microarray (PM-M) technology were performed on lymphoblastoid cell lines (LCLs) from individuals with autism spectrum disorder (ASD) and age-matched controls. We used the custom-made PM-M plate designed to assess differential utilization of the amino acid tryptophan. Multiple parameters such as the sample size, incubation time, and cell concentration have been tested, leading to optimized protocols and minimized background noise by variable selection while controlling for false discoveries. The assay generated data based on the production of nicotinamide adenine dinucleotide (NADH) in the presence of different compounds containing tryptophan and showed clear differences between ASD and control samples.

Phelan-McDermid syndrome (PMS) is a multi-system disorder characterized by significant variability in clinical presentation. The genetic etiology is also variable with differing sizes of deletions in the chromosome 22q13 region and types of genetic abnormalities (e.g., terminal or interstitial deletions, translocations, ring chromosomes, or SHANK3 variants). Position effects have been shown to affect gene expression and function and play a role in the clinical presentation of various genetic conditions. This study employed a topologically associating domain (TAD) analysis approach to investigate position effects of chromosomal rearrangements on selected candidate genes mapped to 22q13 in 81 individuals with PMS. Data collected were correlated with clinical information from these individuals and with expression and metabolic profiles of lymphoblastoid cells from selected cases. The data confirmed TAD predictions for genes encompassed in the deletions and the clinical and molecular data indicated clear differences among individuals with different 22q13 deletion sizes. The results of the study indicate a positive correlation between deletion size and phenotype severity in PMS and provide evidence of the contribution of other genes to the clinical variability in this developmental disorder by reduced gene expression and altered metabolomics.

Autism spectrum disorder (ASD) is a common neurodevelopmental condition with a tremendous impact on society and families. The biological basis of ASD has yet to be completely understood and there are no laboratory tests for this condition. Phenotype Mammalian Microarrays (PM-Ms) can distinguish patients with ASD from typically developing (TD) individuals by differential utilization of the amino acid tryptophan. By assessing several parameters of the assay utilizing customized tryptophan-containing PM-M plates, we improved the discrimination of the test, optimized test parameters, and minimized background noise by normalization while controlling for false discoveries. This improved platform can provide the first cell-based metabolic test to validate the clinical diagnosis of ASD and possibly identify individuals at risk even before the occurrence of neuro-behavioral symptoms.

Polyamines are tightly regulated polycations that are essential for life. Loss-of-function mutations in spermine synthase (SMS), a polyamine biosynthesis enzyme, cause Snyder-Robinson syndrome (SRS), an X-linked intellectual disability syndrome; however, little is known about the neuropathogenesis of the disease. Here we show that loss of dSms in Drosophila recapitulates the pathological polyamine imbalance of SRS and causes survival defects and synaptic degeneration. SMS deficiency leads to excessive spermidine catabolism, which generates toxic metabolites that cause lysosomal defects and oxidative stress. Consequently, autophagy–lysosome flux and mitochondrial function are compromised in the Drosophila nervous system and SRS patient cells. Importantly, oxidative stress caused by loss of SMS is suppressed by genetically or pharmacologically enhanced antioxidant activity. Our findings uncover some of the mechanisms underlying the pathological consequences of abnormal polyamine metabolism in the nervous system and may provide potential therapeutic targets for treating SRS and other polyamine-associated neurological disorders. Mutations in spermine synthase lead to Snyder-Robinson syndrome, a form of intellectual disability syndrome. Here the authors develop a Drosophila model of this disease, and show that lysosomal dysfunction and oxidative stress contribute to the morphological phenotype in these flies, as well as to cellular deficits in cells derived from patients.

Histone acetylation plays a central role in gene regulation and is sensitive to the levels of metabolic intermediates. However, predicting the impact of metabolic alterations on acetylation in pathological conditions is a significant challenge. Here, we present a genome-scale network model that predicts the impact of nutritional environment and genetic alterations on histone acetylation. It identifies cell types that are sensitive to histone deacetylase inhibitors based on their metabolic state, and we validate metabolites that alter drug sensitivity. Our model provides a mechanistic framework for predicting how metabolic perturbations contribute to epigenetic changes and sensitivity to deacetylase inhibitors. Electronic supplementary material The online version of this article (10.1186/s13059-019-1661-z) contains supplementary material, which is available to authorized users.

Deletions and mutations involving the Retinoic Acid Induced 1 (RAI1) gene at 17p11.2 cause Smith-Magenis syndrome (SMS). Here we report a patient with autism as the main clinical presentation, with some SMS-like features and a rare de novo RAI1 gene mutation, c.3440G > A (p.R1147Q). We functionally characterized the RAI1 p.R1147Q mutant protein. The mutation, located near the nuclear localization signal, had no effect on the subcellular localization of the mutant protein. However, similar to previously reported RAI1 missense mutations in SMS patients, the RAI1 p.R1147Q mutant protein showed a significant deficiency in activating in vivo transcription of a reporter gene driven by a BDNF (brain-derived neurotrophic factor) intronic enhancer. In addition, expression of other genes associated with neurobehavioral abnormalities and/or neurodevelopmental disorders were found to be altered in this patient. These results suggest a likely contribution of RAI1, either alone or in combination of other factors, to social behavior and reinforce the RAI1 gene as a candidate gene in patients with autistic manifestations or social behavioral abnormalities.

Polyamines are tightly regulated polycations that are essential for life. Loss-of-function mutations in spermine synthase (SMS), a polyamine biosynthesis enzyme, cause Snyder-Robinson syndrome (SRS), an X-linked intellectual disability syndrome; however, little is known about the neuropathogenesis of the disease. Here we show that loss of dSms in Drosophila recapitulates the pathological polyamine imbalance of SRS and causes survival defects and synaptic degeneration. SMS deficiency leads to excessive spermidine catabolism, which generates toxic metabolites that cause lysosomal defects and oxidative stress. Consequently, autophagy–lysosome flux and mitochondrial function are compromised in the Drosophila nervous system and SRS patient cells. Importantly, oxidative stress caused by loss of SMS is suppressed by genetically or pharmacologically enhanced antioxidant activity. Our findings uncover some of the mechanisms underlying the pathological consequences of abnormal polyamine metabolism in the nervous system and may provide potential therapeutic targets for treating SRS and other polyamine-associated neurological disorders., Mutations in spermine synthase lead to Snyder-Robinson syndrome, a form of intellectual disability syndrome. Here the authors develop a Drosophila model of this disease, and show that lysosomal dysfunction and oxidative stress contribute to the morphological phenotype in these flies, as well as to cellular deficits in cells derived from patients.

Introduction Glioblastoma with oligodendroglioma component (GBM-O) was recognized as a histologic pattern of glioblastoma (GBM) by the World Health Organization (WHO) in 2007 and is distinguished by the presence of oligodendroglioma-like differentiation. To better understand the genetic underpinnings of this morphologic entity, we performed a genome-wide, integrated copy number, mutational and transcriptomic analysis of eight (seven primary, primary secondary) cases. Results Three GBM-O samples had IDH1 (p.R132H) mutations; two of these also demonstrated 1p/19q co-deletion and had a proneural transcriptional profile, a molecular signature characteristic of oligodendroglioma. The additional IDH1 mutant tumor lacked 1p/19q co-deletion, harbored a TP53 mutation, and overall, demonstrated features most consistent with IDH mutant (secondary) GBM. Finally, five tumors were IDH wild-type (IDHwt) and had chromosome seven gains, chromosome 10 losses, and homozygous 9p deletions (CDKN2A), alterations typical of IDHwt (primary) GBM. IDHwt GBM-Os also demonstrated EGFR and PDGFRA amplifications, which correlated with classical and proneural expression subtypes, respectively. Conclusions Our findings demonstrate that GBM-O is composed of three discrete molecular subgroups with characteristic mutations, copy number alterations and gene expression patterns. Despite displaying areas that morphologically resemble oligodendroglioma, the current results indicate that morphologically defined GBM-O does not correspond to a particular genetic signature, but rather represents a collection of genetically dissimilar entities. Ancillary testing, especially for IDH and 1p/19q, should be used for determining these molecular subtypes. Electronic supplementary material The online version of this article (doi:10.1186/s40478-015-0270-7) contains supplementary material, which is available to authorized users.

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor outcomes with current therapies. Gemcitabine is the primary adjuvant drug used clinically, but its effectiveness is limited. In this study, our objective was to use a rationale-driven approach to identify novel biomarkers for outcome in patients with early-stage resected PDAC treated with adjuvant gemcitabine. Using a synthetic lethal screen in human PDAC cells, we identified 93 genes, including 55 genes linked to DNA damage responses (DDR), that demonstrated gemcitabine sensitization when silenced, including CHD7, which functions in chromatin remodeling. CHD7 depletion sensitized PDAC cells to gemcitabine and delayed their growth in tumor xenografts. Moreover, CHD7 silencing impaired ATR-dependent phosphorylation of CHK1 and increased DNA damage induced by gemcitabine. CHD7 was dysregulated, ranking above the 90th percentile in differential expression in a panel of PDAC clinical specimens, highlighting its potential as a biomarker. Immunohistochemical analysis of specimens from 59 patients with resected PDAC receiving adjuvant gemcitabine revealed that low CHD7 expression was associated with increased recurrence-free survival (RFS) and overall survival (OS), in univariate and multivariate analyses. Notably, CHD7 expression was not associated with RFS or OS for patients not receiving gemcitabine. Thus, low CHD7 expression was correlated selectively with gemcitabine sensitivity in this patient population. These results supported our rationale-driven strategy to exploit dysregulated DDR pathways in PDAC to identify genetic determinants of gemcitabine sensitivity, identifying CHD7 as a novel biomarker candidate to evaluate further for individualizing PDAC treatment. Cancer Res; 74(10); 2677–87. ©2014 AACR.

The identification of genes with specific patterns of change (e.g. down-regulated and methylated) as phenotype drivers or samples with similar profiles for a given gene set as drivers of clinical outcome, requires the integration of several genomic data types for which an 'integrate by intersection' (IBI) approach is often applied. In this approach, results from separate analyses of each data type are intersected, which has the limitation of a smaller intersection with more data types. We introduce a new method, GISPA (Gene Integrated Set Profile Analysis) for integrated genomic analysis and its variation, SISPA (Sample Integrated Set Profile Analysis) for defining respective genes and samples with the context of similar, a priori specified molecular profiles. With GISPA, the user defines a molecular profile that is compared among several classes and obtains ranked gene sets that satisfy the profile as drivers of each class. With SISPA, the user defines a gene set that satisfies a profile and obtains sample groups of profile activity. Our results from applying GISPA to human multiple myeloma (MM) cell lines contained genes of known profiles and importance, along with several novel targets, and their further SISPA application to MM coMMpass trial data showed clinical relevance.

The innate immune system is an ancient component of host defense. Since innate immunity pathways are well conserved throughout many eukaryotes, immune genes in model animals can be used to putatively identify homologous genes in newly sequenced genomes of non-model organisms. With the initiation of the “i5k” project, which aims to sequence 5,000 insect genomes by 2016, many novel insect genomes will soon become publicly available, yet few annotation resources are currently available for insects. Thus, we developed an online tool called the Insect Innate Immunity Database (IIID) to provide an open access resource for insect immunity and comparative biology research (http://www.vanderbilt.edu/IIID). The database provides users with simple exploratory tools to search the immune repertoires of five insect models (including Nasonia), spanning three orders, for specific immunity genes or genes within a particular immunity pathway. As a proof of principle, we used an initial database with only four insect models to annotate potential immune genes in the parasitoid wasp genus Nasonia. Results specify 306 putative immune genes in the genomes of N. vitripennis and its two sister species N. giraulti and N. longicornis. Of these genes, 146 were not found in previous annotations of Nasonia immunity genes. Combining these newly identified immune genes with those in previous annotations, Nasonia possess 489 putative immunity genes, the largest immune repertoire found in insects to date. While these computational predictions need to be complemented with functional studies, the IIID database can help initiate and augment annotations of the immune system in the plethora of insect genomes that will soon become available.

SpiceRDb knowledgebase is a unique attempt to elucidate the science behind the action of spices on various disease pathways, using text mining and molecular modeling tools. These spice-remedies have been demonstrated to mediate therapeutic benefits for wide spectra of diseases ranging from multiple sclerosis to colorectal cancer. Furthermore, the docking studies identified curcumin, a component of turmeric, to be a potential disease biomarker for colorectal neoplasm. Thus, the usefulness of the SpiceRDb knowledgebase motivates us to make it available to the public community in order to benefit from the vast knowledge available about alternative medicine projects and the recent scientific evidences supporting the benefits of spice-remedies.

Background and Aim One of the major challenges of using published genomic studies of diffuse large B-cell lymphoma (DLBCL) is that the majority of these data were generated from DLBCL patients of European American descent. Genes that were differentially mutated between activated B-cell-like (ABC) and germinal center B-cell-like (GCB) DLBCL in these populations may differ from the gene mutations associated with the increased frequency of ABC DLBCL in patients of African ancestry. We have shown that African-American (AA) DLBCL patients more commonly present with the ABC subtype (Flowers ASH 2012). Winship Cancer Institute provides the ideal patient population to investigate racial differences in lymphoma at the genome level. We have identified AA half-siblings who presented as new consults in the lymphoma clinic, both with ABC DLBCL. The female sibling had progressive disease after R-CHOP therapy, while the male sibling presented with de novo DLBCL. This observation of siblings of African descent with ABC DLBCL, one of whom had already demonstrated a poor clinical outcome with standard therapy, afforded the additional unique opportunity to examine differential prognosis among AA DLBCL patients using exome sequence. Materials and Methods A tumor sample from a paraffin embedded tissue block was obtained at initial presentation from each sibling, with an additional fresh frozen lymph node obtained from the male subject. Peripheral blood samples were also obtained from each subject to assess DNA from the normal tissue. The NimbleGen SeqCap EZ v3 capture kit was used for whole exome library preparations according to established standard Illumina TruSeq protocols for FFPE samples. Exome sequencing data was generated using the 100x100 paired-end (PE) sequencing protocol for the Illumina HiSeq2000. The PE reads were mapped to Human Reference Genome NCBI36.1/hg19 using Burrow-Wheeler Aligner. VarScan 2 was used for detection of variants (germline and somatic), LOH, and copy number alterations (CNAs) using exome sequence data from the matched tumor and normal samples. Variants were further filtered according to sequencing- or alignment-related artifacts that include among other things, read position, strand bias, variant frequency, distance to 3′, homopolymer, and mapping quality, and visually confirmed by IGV. Results Among the genes with variants identified, EP300, MTOR, MYOM2, and PIK3CD, all previously reported as associated with differentiating ABC from GCB DLBCL, were shown to have germline variants in common between the siblings. A single somatic variant in the EP300 gene was shown specific to the sister. In terms of novel genetic variants, post-filtering, we identified the following possibly damaging (non-benign) germline variants: 4 genes with variants in common between siblings, 5 genes with variants specific to the brother (common to FFPE and Fresh): 19 genes with variants specific to the sister. Novel somatic variants included the following: 1 gene variant specific to the brother (common to FFPE and Fresh), 8 genes with variants specific to the sister. The novel somatic variant specific to the brother also had a reported copy loss that was brother-specific. Exploration of publicly available expression data on ABC DLBCL patients with R-CHOP regimens showed significant associations with overall survival for the genes. We are further exploring haplotype block analysis to infer variant blocks shared by the half-siblings from the common parent to integrate with these results. Conclusion We provide novel protein-altering variant results for AA half-siblings of differential prognosis that show to be promising novel markers for ABC DLBCL. The question of whether such markers are specific to AA remains yet to be investigated. Disclosures: No relevant conflicts of interest to declare.