Sara J. Cooper

Transcriptional promoters comprise one of many classes of eukaryotic transcriptional regulatory elements. Identification and characterization of these elements are vital to understanding the complex network of human gene regulation. Using full-length cDNA sequences to identify transcription start sites (TSS), we predicted more than 900 putative human transcriptional promoters in the ENCODE regions, representing a comprehensive sampling of promoters in 1% of the genome. We identified 387 fragments that function as promoters in at least one of 16 cell lines by measuring promoter activity in high-throughput transient transfection reporter assays. These positive functional results demonstrate widespread use of alternative promoters. We show a strong correlation between promoter activity and the corresponding endogenous RNA transcript levels, providing the first experimental quantitative estimate of promoter contribution to gene regulation. Finally, we identified functional regions within a randomly selected subset of 45 promoters using deletion analyses. These experiments showed that, on average, the sequence -300 to -50 bp of the TSS positively contributes to core promoter activity. Interestingly, putative negative elements were identified -1000 to -500 bp upstream of the TSS for 55% of genes tested. These data provide the largest and most comprehensive view of promoter function in the human genome.

BACKGROUND: Patients with metastatic sarcomas have poor outcomes and although the disease may be amenable to immunotherapies, information regarding the immunologic profiles of soft tissue sarcoma (STS) subtypes is limited. METHODS: The authors identified patients with the common STS subtypes: leiomyosarcoma, undifferentiated pleomorphic sarcoma (UPS), synovial sarcoma (SS), well-differentiated/dedifferentiated liposarcoma, and myxoid/round cell liposarcoma. Gene expression, immunohistochemistry for programmed cell death protein (PD-1) and programmed death-ligand 1 (PD-L1), and T-cell receptor Vβ gene sequencing were performed on formalin-fixed, paraffin-embedded tumors from 81 patients. Differences in liposarcoma subsets also were evaluated. RESULTS: UPS and leiomyosarcoma had high expression levels of genes related to antigen presentation and T-cell infiltration. UPS were found to have higher levels of PD-L1 (P≤.001) and PD-1 (P≤.05) on immunohistochemistry and had the highest T-cell infiltration based on T-cell receptor sequencing, significantly more than SS, which had the lowest (P≤.05). T-cell infiltrates in UPS also were more oligoclonal compared with SS and liposarcoma (P≤.05). A model adjusted for STS histologic subtype found that for all sarcomas, T-cell infiltration and clonality were highly correlated with PD-1 and PD-L1 expression levels (P≤.01). CONCLUSIONS: In the current study, the authors provide the most detailed overview of the immune microenvironment in sarcoma subtypes to date. UPS, which is a more highly mutated STS subtype, provokes a substantial immune response, suggesting that it may be well suited to treatment with immune checkpoint inhibitors. The SS and liposarcoma subsets are less mutated but do express immunogenic self-antigens, and therefore strategies to improve antigen presentation and T-cell infiltration may allow for successful immunotherapy in patients with these diagnoses. Cancer 2017;123:3291-304. © 2017 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

BACKGROUND: Psychiatric disorders are multigenic diseases with complex etiology that contribute significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms, suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and provide new therapeutic targets. METHODS: We performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects. We identified differentially expressed genes and validated the results in an independent cohort. Anterior cingulate cortex samples were also subjected to metabolomic analysis. ChIP-seq data were used to characterize binding of the transcription factor EGR1. RESULTS: We compared molecular signatures across the three brain regions and disorders in the transcriptomes of post-mortem human brain samples. The most significant disease-related differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down-regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down-regulation of genes specific to neurons and concordant up-regulation of genes specific to astrocytes was observed in schizophrenia and bipolar disorder patients relative to controls. Metabolomic profiling identified disruption of GABA levels in schizophrenia patients. CONCLUSIONS: We provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling.

To better understand the quantitative characteristics and structure of phenotypic diversity, we measured over 14,000 transcript, protein, metabolite, and morphological traits in 22 genetically diverse strains of Saccharomyces cerevisiae. More than 50% of all measured traits varied significantly across strains [false discovery rate (FDR) = 5%]. The structure of phenotypic correlations is complex, with 85% of all traits significantly correlated with at least one other phenotype (median = 6, maximum = 328). We show how high-dimensional molecular phenomics data sets can be leveraged to accurately predict phenotypic variation between strains, often with greater precision than afforded by DNA sequence information alone. These results provide new insights into the spectrum and structure of phenotypic diversity and the characteristics influencing the ability to accurately predict phenotypes.

BACKGROUND: Pancreatic adenocarcinoma patients have low survival rates due to late-stage diagnosis and high rates of cancer recurrence even after surgical resection. It is important to understand the molecular characteristics associated with survival differences in pancreatic adenocarcinoma tumors that may inform patient care. RESULTS: RNA sequencing was performed for 51 patient tumor tissues extracted from patients undergoing surgical resection, and expression was associated with overall survival time from diagnosis. Our analysis uncovered 323 transcripts whose expression correlates with survival time in our pancreatic patient cohort. This genomic signature was validated in an independent RNA-seq dataset of 68 additional patients from the International Cancer Genome Consortium. We demonstrate that this transcriptional profile is largely independent of markers of cellular division and present a 19-transcript predictive model built from a subset of the 323 transcripts that can distinguish patients with differing survival times across both the training and validation patient cohorts. We present evidence that a subset of the survival-associated transcripts is associated with resistance to gemcitabine treatment in vitro, and reveal that reduced expression of one of the survival-associated transcripts, Angiopoietin-like 4, impairs growth of a gemcitabine-resistant pancreatic cancer cell line. CONCLUSIONS: Gene expression patterns in pancreatic adenocarcinoma tumors can distinguish patients with differing survival outcomes after undergoing surgical resection, and the survival difference could be associated with the intrinsic gemcitabine sensitivity of primary patient tumors. Thus, these transcriptional differences may impact patient care by distinguishing patients who would benefit from a non-gemcitabine based therapy.