Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine.

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

Low-Coverage Whole Genome Sequencing Using Laser Capture Microscopy with Combined Digital Droplet PCR: An Effective Tool to Study Copy Number and Kras Mutations in Early Lung Adenocarcinoma Development.

Defining detailed genomic characterization of early tumor progression is critical to identifying key regulators and pathways in carcinogenesis as potentially druggable targets. In human lung cancer, work to characterize early cancer development has mainly focused on squamous cancer, as the earliest lesions are more proximal in the airways and often accessible by repeated bronchoscopy. Adenocarcinomas are typically located distally in the lung, limiting accessibility for biopsy of pre-malignant and early stages. Mouse lung cancer models recapitulate many human genomic features and provide a model for tumorigenesis with pre-malignant atypical adenomatous hyperplasia and in situ adenocarcinomas often developing contemporaneously within the same animal. Here, we combined tissue characterization and collection by laser capture microscopy (LCM) with digital droplet PCR (ddPCR) and low-coverage whole genome sequencing (LC-WGS). ddPCR can be used to identify specific missense mutations in Kras (Kirsten rat sarcoma viral oncogene homolog, here focused on Kras Q61) and estimate the percentage of mutation predominance. LC-WGS is a cost-effective method to infer localized copy number alterations (CNAs) across the genome using low-input DNA. Combining these methods, the histological stage of lung cancer can be correlated with appearance of Kras mutations and CNAs. The utility of this approach is adaptable to other mouse models of human cancer.

Glucocorticoid Receptor ChIP-Seq Identifies PLCD1 as a KLF15 Target that Represses Airway Smooth Muscle Hypertrophy.

Glucocorticoids exert important therapeutic effects on airway smooth muscle (ASM), yet few direct targets of glucocorticoid signaling in ASM have been definitively identified. Here, we show that the transcription factor, Krüppel-like factor 15 (KLF15), is directly induced by glucocorticoids in primary human ASM, and that KLF15 represses ASM hypertrophy. We integrated transcriptome data from KLF15 overexpression with genome-wide analysis of RNA polymerase (RNAP) II and glucocorticoid receptor (GR) occupancy to identify phospholipase C delta 1 as both a KLF15-regulated gene and a novel repressor of ASM hypertrophy. Our chromatin immunoprecipitation sequencing data also allowed us to establish numerous direct transcriptional targets of GR in ASM. Genes with inducible GR occupancy and putative antiinflammatory properties included IRS2, APPL2, RAMP1, and MFGE8. Surprisingly, we also observed GR occupancy in the absence of supplemental ligand, including robust GR binding peaks within the IL11 and LIF loci. Detection of antibody-GR complexes at these areas was abrogated by dexamethasone treatment in association with reduced RNA polymerase II occupancy, suggesting that noncanonical pathways contribute to cytokine repression by glucocorticoids in ASM. Through defining GR interactions with chromatin on a genome-wide basis in ASM, our data also provide an important resource for future studies of GR in this therapeutically relevant cell type.

Cistrome-based Cooperation between Airway Epithelial Glucocorticoid Receptor and NF-κB Orchestrates Anti-inflammatory Effects.

Antagonism of pro-inflammatory transcription factors by monomeric glucocorticoid receptor (GR) has long been viewed as central to glucocorticoid (GC) efficacy. However, the mechanisms and targets through which GCs exert therapeutic effects in diseases such as asthma remain incompletely understood. We previously defined a surprising cooperative interaction between GR and NF-κB that enhanced expression of A20 (TNFAIP3), a potent inhibitor of NF-κB. Here we extend this observation to establish that A20 is required for maximal cytokine repression by GCs. To ascertain the global extent of GR and NF-κB cooperation, we determined genome-wide occupancy of GR, the p65 subunit of NF-κB, and RNA polymerase II in airway epithelial cells treated with dexamethasone, TNF, or both using chromatin immunoprecipitation followed by deep sequencing. We found that GR recruits p65 to dimeric GR binding sites across the genome and discovered additional regulatory elements in which GR-p65 cooperation augments gene expression. GR targets regulated by this mechanism include key anti-inflammatory and injury response genes such as SERPINA1, which encodes α1 antitrypsin, and FOXP4, an inhibitor of mucus production. Although dexamethasone treatment reduced RNA polymerase II occupancy of TNF targets such as IL8 and TNFAIP2, we were unable to correlate specific binding sequences for GR or occupancy patterns with repressive effects on transcription. Our results suggest that cooperative anti-inflammatory gene regulation by GR and p65 contributes to GC efficacy, whereas tethering interactions between GR and p65 are not universally required for GC-based gene repression.

Response Element Composition Governs Correlations between Binding Site Affinity and Transcription in Glucocorticoid Receptor Feed-forward Loops.

Combinatorial gene regulation through feed-forward loops (FFLs) can bestow specificity and temporal control to client gene expression; however, characteristics of binding sites that mediate these effects are not established. We previously showed that the glucocorticoid receptor (GR) and KLF15 form coherent FFLs that cooperatively induce targets such as the amino acid-metabolizing enzymes AASS and PRODH and incoherent FFLs exemplified by repression of MT2A by KLF15. Here, we demonstrate that GR and KLF15 physically interact and identify low affinity GR binding sites within glucocorticoid response elements (GREs) for PRODH and AASS that contribute to combinatorial regulation with KLF15. We used deep sequencing and electrophoretic mobility shift assays to derive in vitro GR binding affinities across sequence space. We applied these data to show that AASS GRE activity correlated (r(2) = 0.73) with predicted GR binding affinities across a 50-fold affinity range in transfection assays; however, the slope of the linear relationship more than doubled when KLF15 was expressed. Whereas activity of the MT2A GRE was even more strongly (r(2) = 0.89) correlated with GR binding site affinity, the slope of the linear relationship was sharply reduced by KLF15, consistent with incoherent FFL logic. Thus, GRE architecture and co-regulator expression together determine the functional parameters that relate GR binding site affinity to hormone-induced transcriptional responses. Utilization of specific affinity response functions and GR binding sites by FFLs may contribute to the diversity of gene expression patterns within GR-regulated transcriptomes.

Context-dependent cooperation between nuclear factor κB (NF-κB) and the glucocorticoid receptor at a TNFAIP3 intronic enhancer: a mechanism to maintain negative feedback control of inflammation.

TNF expression is elevated in asthma and other inflammatory airway diseases that are commonly treated with glucocorticoid-based therapies, but the impact of glucocorticoids on negative feedback control of TNF is not well understood. We analyzed the effect of dexamethasone, a potent synthetic glucocorticoid, on TNF-regulated gene expression in cultured airway epithelial cells. Although dexamethasone-mediated activation of the glucocorticoid receptor (GR) potently repressed expression of IL1ß, IL8, and several other pro-inflammatory TNF targets, the expression of anti-inflammatory TNF targets such as TNFAIP3 (A20) and NFKBIA was selectively spared or augmented by dexamethasone treatment. Despite divergent effects on gene expression, GR and NF-κB occupancy at the TNFAIP3 locus and GR-repressed targets was similar. A co-occupied intronic TNFAIP3 regulatory element mediated cooperative enhancement of transcription by GR and NF-κB that required the presence of a functional GR binding site (GBS). GBS exchanges between reporters for TNFAIP3 and FKBP5, a canonical GR-induced target, revealed substantial latitude in the GBS sequence requirements for GR/NF-κB cooperation, suggesting that the TNFAIP3 GBS acts primarily as a docking site in this context. Supporting this notion, a selective GR ligand with only weak agonist activity for induction of FKBP5 enabled robust GR/NF-κB cooperative induction of a mutant TNFAIP3 reporter harboring the FKBP5 GBS. Taken together, our data support a model in which the expression of anti-inflammatory targets of TNF is maintained during treatment with glucocorticoids through context-dependent cooperation between GR and NF-κB.

HLA homozygosity is associated with Non-Hodgkin lymphoma.

The "heterozygote advantage" hypothesis has been postulated regarding the role of human leukocyte antigen (HLA) in non-Hodgkin lymphoma (NHL), where homozygous loci are associated with an increased risk of disease. In this retrospective study, we analyzed the HLA homozygosity of 3789 patients with aplastic anemia (AA), acute lymphocytic leukemia (ALL), acute myeloblastic leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myeloid leukemia (CML), myelodysplastic syndrome (MDS), multiple myeloma (MM), and non-Hodgkin lymphoma (NHL) at HLA-A, B, C, DRB1 and DQB1 loci compared to 169,964 normal controls. HLA homozygosity at one or more loci was only associated with an increased risk in NHL patients (OR = 1.28, 95% CI [1.09, 1.50], p = 0.002). This association was not seen in any of the other hematologic diseases. Homozygosity at HLA-A alone, HLA-B + C only, and HLA-DRB1 + DQB1 only was also significantly associated with NHL. Finally, we observed a 17% increased risk of NHL with each additional homozygous locus (OR per locus = 1.17, 95% CI [1.08, 1.25], p trend = 2.4 × 10-5). These results suggest that reduction of HLA diversity could predispose individuals to an increased risk of developing NHL.

A survey of statistical software for analysing RNA-seq data.

High-throughput RNA sequencing is rapidly emerging as a favourite method for gene expression studies. We review three software packages - edgeR, DEGseq and baySeq - from Bioconductor http://bioconductor.org for analysing RNA-sequencing data. We focus on three aspects: normalisation, statistical models and the testing employed on these methods. We also discuss the advantages and limitations of these software packages.

Alveolar macrophage gene expression is altered in the setting of alcohol use disorders.

BACKGROUND: Alcohol use disorders (AUDs) are associated with an increased susceptibility to a variety of common and devastating pulmonary diseases including community- and hospital-acquired pneumonias, as well as the acute respiratory distress syndrome (ARDS). Alveolar macrophages play an important role in preventing the development of these disorders through maintaining lung sterility and resolving lung inflammation. Although alcohol exposure has been associated with aberrant alveolar macrophage function in animal models, the clinical relevance of these observations in humans is not established. Therefore, we sought to determine the effects of AUDs on human alveolar macrophage gene expression. METHODS: Whole genome microarray analysis was performed on alveolar macrophages obtained by bronchoalveolar lavage from a test cohort of subjects with AUDs (n = 7), and controls (n = 7) who were pair-matched on age, gender, and smoking. Probe set expression differences in this cohort were validated by real-time reverse transcription-polymerase chain reaction (RT RT-PCR). Functional analysis with web-based bioinformatics tools was utilized with microarray data to assess differentially expressed candidate genes (p < 0.01) based on alcohol consumption. Alveolar macrophage mRNA samples from a second cohort of subjects with AUDs (n = 7) and controls (n = 7) were used to confirm gene expression differences related to AUDs. RESULTS: In both the test and the confirmatory cohorts, AUDs were associated with upregulation of alveolar macrophage gene expression related to apoptosis, including perforin-1, granzyme A, and CXCR4 (fusin). Pathways governing the regulation of progression through cell cycle and immune response were also affected, as was upregulation of gene expression for mitochondrial superoxide dismutase. Overall, 12 genes' expression was affected by AUDs independent of smoking. CONCLUSIONS: Alcohol use disorders are associated with unique changes in human alveolar macrophage gene expression. Novel therapies targeting alveolar macrophage gene expression in the setting of AUDs may prove to be clinically useful in limiting susceptibility for pulmonary disorders in these individuals.

Multiple pathways of mitochondrial-nuclear communication in yeast: intergenomic signaling involves ABF1 and affects a different set of genes than retrograde regulation.

Mitochondrial-nuclear communication is taking on increased importance in models of oxygen sensing, oxidative stress, aging, and disease. The deletion of the mitochondrial genome (mtDNA) and, hence, the ability to respire, affects expression of several nuclear genes through at least two different mitochondrial-nuclear communication pathways. One of the pathways, retrograde regulation, is activated by a reduction in respiration, while another, intergenomic signaling, is unaffected by respiration but requires mtDNA. Using DNA microarrays, we identify here a set of nuclear genes in Saccharomyces cerevisiae that are targets of intergenomic signaling. These nuclear genes are down-regulated in rho degrees cells that lack mtDNA but not in nuclear pet mutant rho(+)cells that possess mtDNA but lack respiration. Many of these nuclear genes encode mitochondrial proteins, implying that intergenomic signaling functions in coordinating mitochondrial and nuclear gene expression. In addition, analyses of deletion and linker scanning mutations in the promoter of the COX6 gene, a nuclear gene affected by intergenomic signaling, suggest an involvement of Abf1p transcription factor in intergenomic signaling. Together, these findings indicate that intergenomic signaling is distinct from retrograde regulation both in the nuclear genes that it regulates and in the way in which it affects their expression.

Gene expression in the brain during reovirus encephalitis.

Viral encephalitis remains a significant cause of morbidity and mortality throughout the world. We performed microarray analysis to identify genes and pathways that are differentially regulated during reovirus encephalitis and that may provide novel therapeutic targets for virus-induced diseases of the central nervous system (CNS). An increase in the expression of 130 cellular genes was found in the brains of reovirus-infected mice at early times post infection, compared to mock-infected controls. The up-regulation of these genes was consistent with activation of innate immune responses, particularly interferon signaling. At later times post infection, when significant CNS injury is present and mice exhibit signs of severe neurologic disease, many more (1374) genes were up-regulated, indicating that increased gene expression correlates with disease pathology. Virus-induced gene expression at late times post infection was again consistent with the activation of innate immune responses. However, additional significant pathways included those associated with cytokine signaling and apoptosis, both of which can contribute to CNS injury. This is the first report comparing virus-induced cellular gene and pathway regulation at early and late times following virus infection of the brain. The shift of virus-induced gene expression from innate immune responses at early times post infection to cytokine signaling and apoptosis at later times suggests a potential therapeutic strategy that preserves early protective responses whilst inhibiting later responses that contribute to pathogenesis.

Gene expression profiling identifies inflammation and angiogenesis as distinguishing features of canine hemangiosarcoma.

BACKGROUND: The etiology of hemangiosarcoma remains incompletely understood. Its common occurrence in dogs suggests predisposing factors favor its development in this species. These factors could represent a constellation of heritable characteristics that promote transformation events and/or facilitate the establishment of a microenvironment that is conducive for survival of malignant blood vessel-forming cells. The hypothesis for this study was that characteristic molecular features distinguish hemangiosarcoma from non-malignant endothelial cells, and that such features are informative for the etiology of this disease. METHODS: We first investigated mutations of VHL and Ras family genes that might drive hemangiosarcoma by sequencing tumor DNA and mRNA (cDNA). Protein expression was examined using immunostaining. Next, we evaluated genome-wide gene expression profiling using the Affymetrix Canine 2.0 platform as a global approach to test the hypothesis. Data were evaluated using routine bioinformatics and validation was done using quantitative real time RT-PCR. RESULTS: Each of 10 tumor and four non-tumor samples analyzed had wild type sequences for these genes. At the genome wide level, hemangiosarcoma cells clustered separately from non-malignant endothelial cells based on a robust signature that included genes involved in inflammation, angiogenesis, adhesion, invasion, metabolism, cell cycle, signaling, and patterning. This signature did not simply reflect a cancer-associated angiogenic phenotype, as it also distinguished hemangiosarcoma from non-endothelial, moderately to highly angiogenic bone marrow-derived tumors (lymphoma, leukemia, osteosarcoma). CONCLUSIONS: The data show that inflammation and angiogenesis are important processes in the pathogenesis of vascular tumors, but a definitive ontogeny of the cells that give rise to these tumors remains to be established. The data do not yet distinguish whether functional or ontogenetic plasticity creates this phenotype, although they suggest that cells which give rise to hemangiosarcoma modulate their microenvironment to promote tumor growth and survival. We propose that the frequent occurrence of canine hemangiosarcoma in defined dog breeds, as well as its similarity to homologous tumors in humans, offers unique models to solve the dilemma of stem cell plasticity and whether angiogenic endothelial cells and hematopoietic cells originate from a single cell or from distinct progenitor cells.

Statistical identification of gene association by CID in application of constructing ER regulatory network.

BACKGROUND: A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor alpha (ERalpha) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A). RESULTS: The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's t-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. CONCLUSION: CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers. AVAILABILITY: the implementation of CID in R codes can be freely downloaded from (http://homepage.ntu.edu.tw/~lyliu/BC/).

The PhenoGen informatics website: tools for analyses of complex traits.

BACKGROUND: With the advent of "omics" (e.g. genomics, transcriptomics, proteomics and phenomics), studies can produce enormous amounts of data. Managing this diverse data and integrating with other biological data are major challenges for the bioinformatics community. Comprehensive new tools are needed to store, integrate and analyze the data efficiently. DESCRIPTION: The PhenoGen Informatics website http://phenogen.uchsc.edu is a comprehensive toolbox for storing, analyzing and integrating microarray data and related genotype and phenotype data. The site is particularly suited for combining QTL and microarray data to search for "candidate" genes contributing to complex traits. In addition, the site allows, if desired by the investigators, sharing of the data. Investigators can conduct "in-silico" microarray experiments using their own and/or "shared" data. CONCLUSION: The PhenoGen website provides access to tools that can be used for high-throughput data storage, analyses and interpretation of the results. Some of the advantages of the architecture of the website are that, in the future, the present set of tools can be adapted for the analyses of any type of high-throughput "omics" data, and that access to new tools, available in the public domain or developed at PhenoGen, can be easily provided.

Identification of genes controlled by the pregnane X receptor by microarray analysis of mRNAs from pregnenolone 16alpha-carbonitrile-treated rats.

Mammalian liver contains a pregnane X receptor (PXR, NR1I2), which binds drugs and other xenobiotics, and stimulates (or suppresses) expression of numerous genes involved in the metabolic elimination of foreign compounds and some toxic endogenous substances. In the present study, we used microarray analysis to identify genes whose expression in rat liver was significantly altered by pregnenolone 16alpha-carbonitrile (PCN) treatment. PCN is a synthetic steroid that induces cytochrome P4503A expression and is hepatoprotective by increasing resistance to subsequent stressful insults. Significant induction was seen for 138 genes while expression of 82 genes was significantly repressed. We found induction of genes known to be induced by PCN, such as enzymes involved in drug metabolism and transport. In addition, many genes were differentially expressed whose functions concerned intracellular metabolism, transport of essential small molecules, cell cycle, and redox balance. Our results support the idea that the domain of PXR-controlled gene networks may be even more extensive than currently thought and may extend to functions apart from xenobiotic metabolism.

Clinical implications of growth hormone-secreting tumor subtypes.

Growth hormone (GH) pituitary tumors are almost always benign adenomas, yet are associated with significant morbidity and mortality. Surgical and medical responses of GH tumors are often incomplete, and therefore predictors of residual or recurrent disease are needed. Clinical features, including patient gender, age or size of adenoma, have proven to be unreliable predictors of recurrence. Differing clinical behavior between the two GH tumor subtypes, sparsely granulated (SG) versus densely granulated (DG), has been reported, but has not been used routinely in clinical management. SG tumors are more common in younger patients (<50 years), and are usually larger tumors. SG tumors have been reported to be less responsive to somatostatin analogs (SSA) than DG tumors. The mechanisms underlying these potential differences in tumor behavior, however, are poorly defined. Subsets (up to 50 %) of DG adenomas harbor a gsp mutation that can activate cAMP that provides a theoretical intracellular target for somatostatin therapy. In contrast, some SG tumors have reduced somatostatin receptor expression and mutations in the extracellular domain of the GH receptor that may contribute to SSA resistance. While DG versus SG growth hormone adenomas are readily distinguished by immunohistochemistry, other less common GH adenoma variants still require electron microscopy (EM) for confident subclassification. Whether these less common variants possess unique clinical features is unknown. Research is needed to identify clinically relevant biomarkers of GH pituitary tumors that predict risk of recurrence and response to medical therapy.

Pregnancy amelioration of arthritis in SKG mice corresponds with alterations in serum amyloid A3 levels.

OBJECTIVES: Pregnancy leads to rheumatoid arthritis remission in humans. The objective of this study was to determine if the SKG mouse could serve as a model for pregnancy-associated inflammatory arthritis amelioration. In addition, the maternal peripheral blood mononuclear cell (PBMC) transcriptome was assessed to define a biomarker associated with remission. METHODS: Cohorts of zymosan-treated pregnant SKG mice and controls were monitored for arthritis progression. Microarray analysis evaluated alterations in gene expression in maternal PBMCs at embryonic day 14.5 (E14.5) between arthritic and pregnancy-remitted mice. A selected target, serum amyloid A3 (SAA3), was further investigated using quantitative reverse transcriptase PCR (qRT-PCR) and an enzyme-linked immunosorbent assay (ELISA). RESULTS: Pregnancy resulted in complete or partial remission in the majority of the zymosan-treated SKG mice. Twenty-seven transcripts were differentially expressed in the PBMCs between arthritic and pregnancy-remitted mice. Expression and plasma SAA3 levels decreased with pregnancy-induced arthritis amelioration and plasma SAA3 levels correlated with arthritis severity. CONCLUSIONS: These results establish the SKG mouse as a model system to study pregnancy-induced amelioration of arthritis. These studies also establish SAA3 as a biomarker of arthritis amelioration in SKG mice. This model can be used to elucidate the molecular and cellular mechanisms underlying the impact of pregnancy on the maternal immune system that results in arthritis amelioration.

Significant downregulation of platelet gene expression in metastatic lung cancer.

Platelets play a major role in the metastatic dissemination of tumor cells in vivo . Recent evidence reveals megakaryocyte-derived platelet pre-mRNA is spliced to mRNA and then translated into functional proteins in response to external stimulation. Employing a human lung cancer model, we hypothesized a subset of megakaryocyte/platelet genes exists that are significantly over or underexpressed in metastasis compared with noncancer. Microarray analysis employing platelet mRNA followed by unsupervised hierarchical clustering revealed an expression profile that includes decreased expression of 197 of the 200 platelet genes with the most altered expression (p < 1.0 × 10(-4)). Among the 608 splicing events identified between the metastasis and negative control groups, 33 highly variable genes were identified with between 3 and 13 splicing events each. In conclusion, this preliminary study reveals a platelet-based gene expression signature that differentiates metastatic lung cancer from negative controls on the basis of decreased expression of 197 of the 200 genes with the most altered expression levels. Further study may yield a prognostic tool for future metastasis among subsets of early stage lung cancer patients.