While lung cancer is the leading cause of cancer death in the US, we have a limited understanding of the earliest molecular events preceding the onset of disease. Prior work has demonstrated that cigarette smoke creates a molecular “field of injury” throughout the airway epithelium and that there are distinct alterations in the airway transcriptome among smokers who have lung cancer. Molecular characterization of this airway “field of injury” in current and former smokers with premalignant lesions (PMLs) could provide novel insights into the earliest molecular events associated with lung carcinogenesis and identify relatively accessible biomarkers to guide lung cancer detection and early intervention. Using mRNA sequencing (mRNA-Seq), we profiled 82 cytologically normal bronchial airway epithelial cells collected during autofluorescence bronchoscopy from high-risk smokers with and without bronchial PMLs, 75 of which were used in downstream analyses. We identified 280 genes differentially expressed in the “field of injury” between subjects with (n=50) and without (n=25) PMLs (FDR<0.002), 81 of which were up-regulated in subjects with PMLs. Oxidative phosphorylation (OXPHOS), the electron transport chain (ETC), and mitochondrial protein transport pathways were strongly enriched among these up-regulated genes (FDR<0.05). We next demonstrated that OXPHOS activation is shared between the “field” and the PMLs with increased oxygen consumption and increased staining for mitochondrial markers in biopsies of PMLs from patients as well as an animal model of lung squamous cell carcinoma (SCC) premalignancy. The 280-gene signature also has a significant concordant relationship to gene expression changes identified in PMLs adjacent to lung SCC tumors, in lung SCC tumors, and in the cytologically normal airway of individuals with lung cancer (FDR<0.05). These findings suggest that these expression changes are reflective of early cancer-associated changes occurring throughout the respiratory tract, and that pathways such as OXPHOS may be targets for chemoprevention. We subsequently developed an airway gene expression biomarker that predicts the presence of PMLs (AUC=0.92, n=17 samples in test set) and show that changes in the biomarker score are associated with progression and regression of PMLs in an independent cohort (AUC=0.75, n=51 samples). The biomarker results indicate that molecular alterations in the field of injury are dynamic with progression or regression of PMLs, suggesting that these changes may be leveraged to stratify high-risk smokers with progressive disease into early intervention trials and monitor disease progression or recurrence. Overall design: 82 mRNA-Seq samples from 25 smokers without PMLs, 50 smokers with PMLs, and 7 smokers with metaplasia.
Detecting the Presence and Progression of Premalignant Lung Lesions via Airway Gene Expression.
No sample metadata fields
View SamplesWhile lung cancer is the leading cause of cancer death in the US, we have a limited understanding of the earliest molecular events preceding the onset of disease. Prior work has demonstrated that cigarette smoke creates a molecular “field of injury” throughout the airway epithelium and that there are distinct alterations in the airway transcriptome among smokers who have lung cancer. Molecular characterization of this airway “field of injury” in current and former smokers with premalignant lesions (PMLs) could provide novel insights into the earliest molecular events associated with lung carcinogenesis and identify relatively accessible biomarkers to guide lung cancer detection and early intervention. Using mRNA sequencing (mRNA-Seq), we profiled cytologically normal bronchial airway epithelial cells collected during autofluorescence bronchoscopy from high-risk smokers (n=75) with and without bronchial PMLs. We identified 280 genes differentially expressed in the “field of injury” between subjects with (n=50) and without (n=25) PMLs (FDR<0.002), 81 of which were up-regulated in subjects with PMLs. Oxidative phosphorylation (OXPHOS), the electron transport chain (ETC), and mitochondrial protein transport pathways were strongly enriched among these up-regulated genes (FDR<0.05). We next demonstrated that OXPHOS activation is shared between the “field” and the PMLs with increased oxygen consumption and increased staining for mitochondrial markers in biopsies of PMLs from patients as well as an animal model of lung squamous cell carcinoma (SCC) premalignancy. The 280-gene signature also has a significant concordant relationship to gene expression changes identified in PMLs adjacent to lung SCC tumors, in lung SCC tumors, and in the cytologically normal airway of individuals with lung cancer (FDR<0.05). These findings suggest that these expression changes are reflective of early cancer-associated changes occurring throughout the respiratory tract, and that pathways such as OXPHOS may be targets for chemoprevention. We subsequently developed an airway gene expression biomarker that predicts the presence of PMLs (AUC=0.92, n=17 samples in test set) and show that changes in the biomarker score are associated with progression and regression of PMLs in an independent cohort (AUC=0.75, n=51 samples). The biomarker results indicate that molecular alterations in the field of injury are dynamic with progression or regression of PMLs, suggesting that these changes may be leveraged to stratify high-risk smokers with progressive disease into early intervention trials and monitor disease progression or recurrence. Overall design: 51 mRNA-Seq samples from 23 subjects obtained via bronchscopy (18 subjects with 2 procedures, 5 subjects with 3 procedures).
Detecting the Presence and Progression of Premalignant Lung Lesions via Airway Gene Expression.
No sample metadata fields
View SamplesLung cancer is closely associated with chronic inflammation, but the mechanism underlying such inflammation has not been clearly defined. The lung is a mucosal tissue colonized by a diverse bacterial community at the steady state, and pulmonary infections commonly present in lung cancer patients are linked to clinical outcomes. Here we provide evidence that local microbiota provoke inflammation associated with lung adenocarcinoma by activating lung-resident gamma-delta T cells. Germ-free or antibiotic-treated mice were significantly protected from lung tumor initiation and progression induced by Kras mutation and p53 loss. Mechanistically, commensal bacteria stimulated My88-dependent IL-1beta and IL-23 production from myeloid cells, inducing proliferation and activation of V?6+Vd1+ ?d T cells that produced IL-17 and other effector molecules to promote inflammation and tumor cell proliferation. Our findings provide a clear link between local microbiota-immune crosstalk and lung tumorigenesis, and thereby define key cellular and molecular mediators that may serve as effective targets in lung cancer treatment and prevention. Overall design: ?dT cells were isolated from tumor-bearing lungs or spleens of KP mice. Their transcriptional profiles are compared with RNA-seq.
Commensal Microbiota Promote Lung Cancer Development via γδ T Cells.
Specimen part, Cell line, Subject
View SamplesIn this study, we initially screened over 1400 natural products for capacity to inhibit the kinetic enzyme activity of nuclear HDACs isolated from SK-MEL-3 cells. From these findings we evaluate whole transcriptome changes that occur at a 24 hour time point in SK-ME-3 cells in the presence of a known HDAC inhibitor (Trichostatin A) (1uM) or a natural product HDAC inhibitor Grapeseed Extract (120ug/ml), both tested at sub-lethal concentrations relative to untreated controls. Microarrays were acquired for mRNAs and long intergenic non-coding RNA transcripts using the GeneChip Human 2.1ST ARRAY by Affymetrix Inc
Whole-transcriptomic Profile of SK-MEL-3 Melanoma Cells Treated with the Histone Deacetylase Inhibitor: Trichostatin A.
Cell line, Treatment
View SamplesThe effects of BSE and 3-OABA on MDA-MB-231 cells were evaluated for effects on the whole transcriptome: including mRNAs and long intergenic non-coding RNA transcripts (lincRNA) using GeneChip Human Gene 2.1 ST Arrays by Affymetrix Inc.
Transcriptomic Profiling of MDA-MB-231 Cells Exposed to <i>Boswellia Serrata</i> and 3-O-Acetyl-B-Boswellic Acid; ER/UPR Mediated Programmed Cell Death.
Specimen part, Cell line, Treatment
View SamplesIn an attempt to elucidate the molecular mechanisms underlying the multiple roles of L1 in endothelium, we checked whether manipulating its expression affected the transcriptome of lECs. To this purpose, we compared the gene expression profiles of L1-overexpressing and control lECs by Affymetrix, which revealed a remarkable effect of L1 overexpression on lECs transcriptome.
Endothelial deficiency of L1 reduces tumor angiogenesis and promotes vessel normalization.
Specimen part
View SamplesIn C. elegans, ablation of germline stem cells (GSCs) extends lifespan, but also increases fat accumulation and alters lipid metabolism, raising the intriguing question of how these effects might be related. Here we show that a lack of GSCs results in a broad transcriptional reprogramming, in which the conserved detoxification regulator SKN-1/Nrf increases stress resistance, proteasome activity, and longevity. SKN-1 also activates diverse lipid metabolism genes and reduces fat storage, thereby alleviating the increased fat accumulation caused by GSC absence. Surprisingly, SKN-1 is activated by signals from this fat, which appears to derive from unconsumed yolk that was produced for reproduction. We conclude that SKN-1 plays a direct role in maintaining lipid homeostasis, in which it is activated by lipids. This SKN-1 function may explain the importance of mammalian Nrf proteins in fatty liver disease, and suggests that particular endogenous or dietary lipids might promote health through SKN-1/Nrf. Overall design: Samples were prepared from ~5,000 synchronized, L1 arrested day-one adult animals cultured at 25°C. Worms were synchronized by sodium hypochlorite (bleach) treatment, as previously described (Porta-de-la-Riva et al., 2012). Bleach solution (9 mL ddH2O; 1 mL 1 N NaOH; 4 mL Clorox bleach) was freshly prepared before each experiment. Worms were bleached for 5 minutes, washed 5x in M9, and arrested at the L1 stage at 25°C in M9 containing 10 µg/mL cholesterol. Feeding RNAi was started at the L1 stage. This approach only partially reduces skn-1 function, but allows analysis of larger samples than would be feasible with skn-1 mutants, which are sterile (Bowerman et al., 1992). Because these animals were not treated with FUdR, the WT adults contained an intact germline and eggs. As is explained in the Results section, we therefore confined our analysis to genes that were overrepresented in glp-1(ts) animals, which lack eggs and most of the germline, and established a high-confidence cutoff for genes that were upregulated by GSC absence as opposed to simply being expressed specifically in somatic tissues. RNA was extracted using the same protocol for qRT-PCR samples. Purified RNA samples were DNase treated and assigned a RIN quality score using a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). Only matched samples with high RIN scores were sent for sequencing. Single read 50 bp RNA sequencing with poly(A) enrichment was performed at the Dana-Farber Cancer Institute Center for Computational Biology using a HiSeq 2000 (Illumina, San Diego, CA). FASTQ output files were aligned to the WBcel235 (Feb 2014) C. elegans reference genome using STAR (Dobin et al., 2013). These files have been deposited at the Gene Expression Omnibus (GEO) with the accession number GSE63075. Samples averaged 75% mapping of sequence reads to the reference genome. Differential expression analysis was performed using a custom R and Bioconductor RNA-seq pipeline (http://bioinf.wehi.edu.au/RNAseqCaseStudy/) (Gentleman et al., 2004; Anders et al., 2013; R Core Team, 2014). Quantification of mapped reads in the aligned SAM output files was performed using featureCounts, part of the Subread package (Liao et al., 2013, 2014). We filtered out transcripts that didn't have at least one count per million reads in at least two samples. Quantile normalization and estimation of the mean-variance relationship of the log-counts was performed by voom (Law et al., 2014). Linear model fitting, empirical Bayes analysis and differential expression analysis was then conducted using limma (Smyth, 2005). To identify genes that are upregulated in a SKN-1-dependent manner by GSC loss, we sought genes for which glp-1(ts) expression was higher than WT, and for which glp-1(ts);skn-1(-) expression was reduced relative to glp-1(ts). To test for this pattern, if a gene's expression change was higher in the comparison of glp-1(ts) vs. WT and lower in the comparison of glp-1(ts);skn-1(-) vs. glp-1(ts), then we calculated the minimum (in absolute value) of the t-statistics from these two comparisons, and assessed the significance of this statistic by comparing to a null distribution derived by applying this procedure to randomly generated t-statistics. We corrected for multiple testing in this and the differential expression analysis using the false discovery rate (FDR) (Benjamini and Hochberg, 1995). Heatmaps were generated using heatmap.2 in the gplots package (Warnes et al., 2014). Functional annotations and phenotypes were obtained from Wormbase build WS246. SKN-1 transcription factor binding site analysis of hits was conducted with biomaRt, GenomicFeatures, JASPAR, MotifDb, motifStack, MotIV, and Rsamtools (Sandelin et al., 2004; Durinck et al., 2005; Durinck et al., 2009; Lawrence et al., 2013; Ou et al., 2013; Mercier and Gottardo, 2014; Shannon, 2014). JASPAR analysis was performed with the SKN-1 matrix MA0547.1 using 2 kb upstream sequences obtained from Ensembl WBcel235 (Staab et al., 2013). modENCODE SKN-1::GFP ChIP-seq analysis of hits was performed using biomaRt, ChIPpeakAnno, IRanges, and multtest (Durinck et al., 2005; Durinck et al., 2009; Gerstein et al., 2010; Zhu et al., 2010; Niu et al., 2011; Lawrence et al., 2013). SKN-1::GFP ChIP-seq peaks were generated by Michael Snyder's lab. We used the peak data generated from the first 3 larval stages: L1 (modENCODE_2622; GSE25810), L2 (modENCODE_3369), and L3 (modENCODE_3838; GSE48710). Human ortholog matching was performed using Wormbase, Ensembl, and OrthoList (Shaye and Greenwald, 2011). Gene lists were evaluated for functional classification and statistical overrepresentation with Database for Annotation, Visualization and Integrated Discovery (DAVID) version 6.7 (Dennis et al., 2003).
Lipid-mediated regulation of SKN-1/Nrf in response to germ cell absence.
Cell line, Subject
View SamplesTreatments that stimulate neuronal excitability enhance motor performance after stroke.cAMP-response-element binding protein (CREB) is a transcription factor that plays a key rolein neuronal excitability. Increasing the levels of CREB with a viral vector in a small pool ofmotor neurons enhances motor recovery after stroke, while blocking CREB signaling preventsstroke recovery. Silencing CREB-transfected neurons in the peri-infarct region with thehM4di-DREADD blocks motor recovery. Reversing this inhibition allows recovery to continue,demonstrating that it is possible to turn off and on stroke recovery by manipulating theactivity of CREB-transfected neurons. CREB transfection enhances re-mapping of injuredsomatosensory and motor circuits, and induces the formation of new connections withinthese circuits. CREB is a central molecular node in the circuit responses after stroke that leadto recovery from motor deficits.
CREB controls cortical circuit plasticity and functional recovery after stroke.
Specimen part
View SamplesMutations of -catenin gene (CTNNB1) are frequent in adrenocortical adenomas (AA) and carcinomas (ACC). However, the target genes of CTNNB1 have not yet been identified in adrenocortical tumors.
Characterization of differential gene expression in adrenocortical tumors harboring beta-catenin (CTNNB1) mutations.
Specimen part
View SamplesThe aim of this study is to profile gene expression dynamics during the in vitro differentiation of embryonic stem cells into ventral motor neurons. Expression levels were profiled using Affymetrix microarrays at six timepoints during in vitro differentiation: ES cells (Day 0), embryoid bodies (Day 2), retinoid induction of neurogenesis (Day 2 +8hours of exposure to retinoic acid), neural precursors (Day 3), progenitor motor neurons (Day 4), postmitotic motor neurons (Day 7).
Ligand-dependent dynamics of retinoic acid receptor binding during early neurogenesis.
Cell line
View Samples