Genotyping by array of copy number variation in multi-regional sampling of hepatocellular carcinoma
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ABSTRACT: The purpose of the experiment is to determine purity (aberrant cell fraction), ploidy levels and copy number alterations of the samples. Several samples were taken for each of the patients. These include tumor and controls. Controls are adjacent liver tissue in most cases, and blood cells (buffy coat isolate) in some special cases.
Project description:The purpose of this experiment is to characterize the intratumor heterogeneity in liver cancer and to study the crosstalk between the immune component of the tumor and the aberrant hepatocites.
Project description:The purpose of this experiment of high-coverage DNA sequencing of 58 frequently mutated genes in hepatocellular carcinoma (HCC) is to confirm clonal distribution of the known HCC drivers in samples corresponding to multiple regions of a tumor.
Project description:We showed that nandrolone attenuated subacute, but not acute, denervation atrophy and upregulation of MAFbx. The present study explored the molecular determinants for this time-dependent effect using microarray analysis to identify genes that were differentially regulated by administration of nandrolone for 7 days beginning either concomitantly with denervation (7 days) or 29 days later (35 days) Experiment Overall Design: The analysis used gastrocnemius muscle from male Wistar-Hannover rats that had undergone left sciatic nerve transaction followed by the administration of nandrolone or vehicle beginning either on the day of surgery or 29 days thereafter. Animals had been sacrificed 7 days after starting nandrolone (Nan) or vehicle (Veh) (e.g, at days 7 or 35).
Project description:Contemporary analyses focused on a limited number of clinical and molecular features have been unable to accurately predict clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). Here we describe a novel, conceptual approach and use it to analyze clinical, computational pathology, and molecular (DNA, RNA, protein, and lipid) analyte data from 74 patients with resectable PDAC. Multiple, independent, machine learning models were developed and tested on curated singleand multi-omic feature/analyte panels to determine their ability to predict clinical outcomes in patients. The multi-omic models predicted recurrence with an accuracy and positive predictive value (PPV) of 0.90, 0.91, and survival of 0.85, 0.87, respectively, outperforming every singleomic model. In predicting survival, we defined a parsimonious model with only 589 multi-omic analytes that had an accuracy and PPV of 0.85. Our approach enables discovery of parsimonious biomarker panels with similar predictive performance to that of larger and resource consuming panels and thereby has a significant potential to democratize precision cancer medicine worldwide.
Project description:Background: Examining transcriptional regulation by existing antidepressants in key neural circuits implicated in depression, and understanding the relationship to transcriptional mechanisms of susceptibility and natural resilience, may help in the search for new therapeutics. Further, given the heterogeneity of treatment response in human populations, examining both treatment response and non-response is critical. Methods: We compared the effects of a conventional monoamine-based tricyclic antidepressant, imipramine (14 daily injections), and a rapidly acting, experimental, non-monoamine-based antidepressant, ketamine (single injection), in mice subjected to chronic social defeat stress, a validated model of depression, and used RNA-sequencing to analyze transcriptional profiles associated with susceptibility, resilience and antidepressant response and non-response in prefrontal cortex (PFC), nucleus accumbens, hippocampus, and amygdala. Results: We identified approximately equal numbers of responder and non-responder mice following ketamine or imipramine treatment. Ketamine induced more expression changes in hippocampus than other brain regions; imipramine induced more expression changes in nucleus accumbens and amygdala. Transcriptional profiles in ketamine and imipramine responders were most similar in PFC, where the least transcriptional regulation occurred for each drug. Non-response reflected both the lack of response-associated gene expression changes and unique gene regulation. In responders, both drugs reversed susceptible associated transcriptional changes as well as induced resilient associated transcription in PFC, with effects varying by drug and brain region studied. Conclusions: We generated a uniquely large resource of gene expression data in four inter-connected limbic brain regions implicated in depression and its treatment with imipramine or ketamine. Our analyses highlight the PFC as a key site of common transcriptional regulation by both antidepressant drugs and in both reversing susceptibility and inducing resilience associated molecular adaptations. In addition, we found region-specific effects of each drug suggesting both common and unique effects of imipramine versus ketamine. mRNA profiles of susceptibility to chronic social defeat stress as well as treatment response were generated across 4 separate brain regions, with a sample size of 3-5 per group.
Project description:Setleis Syndrome is a rare type of facial ectodermal dysplasia characterized by an aged leonine appearance with puckered skin about the eyes, absent eyelashes on both lids or multiple rows on the upper lids and none on the lower lids, eyebrows that slant sharply upward laterally, and a rubbery feel of the nose and chin. Some of the patients showed bilateral temporal marks superficially like forceps marks and like the lesions seen in focal facial dermal dysplasia. We have evidence that Setleis Syndrome is caused by nonsense mutations in the gene coding for the small bHLH transcription factor known as TWIST2 in Puerto Rican and Omani patients. We performed expression microarray analysis of RNA samples derived from skin fibroblasts grown from skin biopsies of Setleis Syndrome patients and normal controls in order to identify genes potentially involved in facial development and the pathogenesis of Setleis Syndrome. A total of 4 control and 4 Setleis Syndrome RNA samples were hybridized to U133 plus 2 Affymetrix 3'IVT arrays in the Mount Sinai School of Medicine Microarray Core Facility.
Project description:Analysis of gene expression between WT and iNOS defecient M1 macrophage RNA microarray was performed using RNA isolated from M1 polarized macrophages from WT and iNOS deficient mice stimulated with LPS/IFNγ for 6 hours. Total RNA was extracted using a RNeasy plus kit (QIAGEN, Valencia, CA), and the array was performed on an Illumina MouseRef-8 v2.0 expression beadchip (Illumina, USA) by the Genomics Core Facility at the Mount Sinai School of Medicine.
Project description:The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. With an extremely poor five-year survival rate of only 15%, identification of new therapeutic targets for EAC is of great importance. Here, we analyze the mutation spectra from the whole exome sequencing of 149 EAC tumors/normal pairs, 15 of which have also been subjected to whole genome sequencing. We identify a novel mutational signature in EACs defined by a high prevalence of A to C transversions at Ap*A dinucleotides. Statistical analysis of the exome data identified 26 genes that are mutated at a significant frequency. Of these 26 genes, only four (TP53, CDKN2A, SMAD4, and PIK3CA) have been previously implicated in EAC. The novel significantly mutated genes include several chromatin modifying factors and candidate contributors to EAC: SPG20, TLR4, ELMO1, and DOCK2. Notably, functional analyses of EAC-derived mutations in ELMO1 increase cellular invasion. Therefore, we suggest a new hypothesis about the potential activation of the RAC1 pathway to be a contributor to EAC tumorigenesis. The study aimed to analyze 150 primary, human esophageal adenocarcinoma samples by whole genome and whole exome sequencing (which will be deposited to dbGAP following the TCGA practice). RNA expression data was used to determine gene expression in 14 of the samples analyzed by whole genome sequencing. No normals were analyzed.
Project description:Sleep dysfunction and stress susceptibility are co-morbid complex traits, which often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multi-level organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J×A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests the interplay between sleep, stress, and neuropathology emerge from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework to interrogate the mechanisms underlying sleep, stress susceptibility, and related neuropathology. Examination of genomic and transcriptomic networks in a random subset of 100 (B6xA/J)F2 mice modeling the natural spectrum of stress susceptibility.
Project description:Human brain samples from healthy and advanced Alzheimer's diseased patients were subjected to RNA-seq analysis to monitor RNA level changes during AD progression. Human brain samples were obtained from the Mount Sinai Brain Bank; RNA was Trizol extracted, ribominus selected and submitted for high-throughput sequencing.