A Gene Expression Classifier from Whole Blood Distinguishes Benign from Malignant Lung Nodules Detected by Low-Dose CT.

Low-dose CT (LDCT) is widely accepted as the preferred method for detecting pulmonary nodules. However, the determination of whether a nodule is benign or malignant involves either repeated scans or invasive procedures that sample the lung tissue. Noninvasive methods to assess these nodules are needed to reduce unnecessary invasive tests.

Comparative functional genomics of adaptation to muscular disuse in hibernating mammals.

Hibernation is an energy-saving adaptation that involves a profound suppression of physical activity that can continue for 6-8 months in highly seasonal environments. While immobility and disuse generate muscle loss in most mammalian species, in contrast, hibernating bears and ground squirrels demonstrate limited muscle atrophy over the prolonged periods of physical inactivity during winter, suggesting that hibernating mammals have adaptive mechanisms to prevent disuse muscle atrophy. To identify common transcriptional programmes that underlie molecular mechanisms preventing muscle loss, we conducted a large-scale gene expression screen in hind limb muscles comparing hibernating and summer-active black bears and arctic ground squirrels using custom 9600 probe cDNA microarrays.

The peripheral immune response and lung cancer prognosis.

Attempts to refine and improve outcome predictions using tumor gene expression have been recently reported. We show that peripheral blood mononuclear cell (PBMC)-associated gene signatures can predict outcome in non-small cell lung carcinoma patients independent of demographic data or TNM staging, and that this information may persist after tumor resection.

Peripheral immune cell gene expression predicts survival of patients with non-small cell lung cancer.

Prediction of cancer recurrence in patients with non-small cell lung cancer (NSCLC) currently relies on the assessment of clinical characteristics including age, tumor stage, and smoking history. A better prediction of early stage cancer patients with poorer survival and late stage patients with better survival is needed to design patient-tailored treatment protocols. We analyzed gene expression in RNA from peripheral blood mononuclear cells (PBMC) of NSCLC patients to identify signatures predictive of overall patient survival.

Genome-wide maps of circulating miRNA biomarkers for ulcerative colitis.

Inflammatory Bowel Disease--comprised of Crohn's Disease and Ulcerative Colitis (UC)--is a complex, multi-factorial inflammatory disorder of the gastrointestinal tract. In this study we have explored the utility of naturally occurring circulating miRNAs as potential blood-based biomarkers for non-invasive prediction of UC incidences. Whole genome maps of circulating miRNAs in micro-vesicles, Peripheral Blood Mononuclear Cells and platelets have been constructed from a cohort of 20 UC patients and 20 normal individuals.

Preservation of bone mass and structure in hibernating black bears (Ursus americanus) through elevated expression of anabolic genes.

Physical inactivity reduces mechanical load on the skeleton, which leads to losses of bone mass and strength in non-hibernating mammalian species. Although bears are largely inactive during hibernation, they show no loss in bone mass and strength. To obtain insight into molecular mechanisms preventing disuse bone loss, we conducted a large-scale screen of transcriptional changes in trabecular bone comparing winter hibernating and summer non-hibernating black bears using a custom 12,800 probe cDNA microarray.

Resection of non-small cell lung cancers reverses tumor-induced gene expression changes in the peripheral immune system.

Purpose: To characterize the interactions of non-small cell lung cancer (NSCLC) tumors with the immune system at the level of mRNA and microRNA (miRNA) expression and to define expression signatures that characterize the presence of a malignant tumor versus a nonmalignant nodule.

Experimental Design: We have examined the changes of both mRNA and miRNA expression levels in peripheral blood mononuclear cells (PBMC) between paired samples collected from NSCLC patients before and after tumor removal using Illumina gene expression arrays.

Results: We found that malignant tumor removal significantly changes expression of more than 3,000 protein-coding genes, especially genes in pathways associated with suppression of the innate immune response, including natural killer cell signaling and apoptosis-associated ceramide signaling.

Modulation of gene expression in heart and liver of hibernating black bears (Ursus americanus).

Background: Hibernation is an adaptive strategy to survive in highly seasonal or unpredictable environments. The molecular and genetic basis of hibernation physiology in mammals has only recently been studied using large scale genomic approaches. We analyzed gene expression in the American black bear, Ursus americanus, using a custom 12,800 cDNA probe microarray to detect differences in expression that occur in heart and liver during winter hibernation in comparison to summer active animals.

Sp100 as a potent tumor suppressor: accelerated senescence and rapid malignant transformation of human fibroblasts through modulation of an embryonic stem cell program.

Identifying the functions of proteins, which associate with specific subnuclear structures, is critical to understanding eukaryotic nuclear dynamics. Sp100 is a prototypical protein of ND10/PML nuclear bodies, which colocalizes with Daxx and the proto-oncogenic PML. Sp100 isoforms contain SAND, PHD, Bromo, and HMG domains and are highly sumoylated, all characteristics suggestive of a role in chromatin-mediated gene regulation.

Gene expression profiles in peripheral blood mononuclear cells can distinguish patients with non-small cell lung cancer from patients with nonmalignant lung disease.

Early diagnosis of lung cancer followed by surgery presently is the most effective treatment for non-small cell lung cancer (NSCLC). An accurate, minimally invasive test that could detect early disease would permit timely intervention and potentially reduce mortality. Recent studies have shown that the peripheral blood can carry information related to the presence of disease, including prognostic information and information on therapeutic response.

Classification and biomarker identification using gene network modules and support vector machines.

Background: Classification using microarray datasets is usually based on a small number of samples for which tens of thousands of gene expression measurements have been obtained. The selection of the genes most significant to the classification problem is a challenging issue in high dimension data analysis and interpretation. A previous study with SVM-RCE (Recursive Cluster Elimination), suggested that classification based on groups of correlated genes sometimes exhibits better performance than classification using single genes.

Elevated expression of protein biosynthesis genes in liver and muscle of hibernating black bears (Ursus americanus).

We conducted a large-scale gene expression screen using the 3,200 cDNA probe microarray developed specifically for Ursus americanus to detect expression differences in liver and skeletal muscle that occur during winter hibernation compared with animals sampled during summer. The expression of 12 genes, including RNA binding protein motif 3 (Rbm3), that are mostly involved in protein biosynthesis, was induced during hibernation in both liver and muscle. The Gene Ontology and Gene Set Enrichment analysis consistently showed a highly significant enrichment of the protein biosynthesis category by overexpressed genes in both liver and skeletal muscle during hibernation.

Learning from positive examples when the negative class is undetermined--microRNA gene identification.

Background: The application of machine learning to classification problems that depend only on positive examples is gaining attention in the computational biology community. We and others have described the use of two-class machine learning to identify novel miRNAs. These methods require the generation of an artificial negative class.

Naïve Bayes for microRNA target predictions--machine learning for microRNA targets.

Motivation: Most computational methodologies for miRNA:mRNA target gene prediction use the seed segment of the miRNA and require cross-species sequence conservation in this region of the mRNA target. Methods that do not rely on conservation generate numbers of predictions, which are too large to validate. We describe a target prediction method (NBmiRTar) that does not require sequence conservation, using instead, machine learning by a naïve Bayes classifier.

A 10-gene classifier for distinguishing head and neck squamous cell carcinoma and lung squamous cell carcinoma.

Purpose: The risk of developing metastatic squamous cell carcinoma for patients with head and neck squamous cell carcinoma (HNSCC) is very high. Because these patients are often heavy tobacco users, they are also at risk for developing a second primary cancer, with squamous cell carcinoma of the lung (LSCC) being the most common. The distinction between a lung metastasis and a primary LSCC is currently based on certain clinical and histologic criteria, although the accuracy of this approach remains in question.

Recursive cluster elimination (RCE) for classification and feature selection from gene expression data.

Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that are important for distinguishing the different sample classes being compared, poses a challenging problem in high dimensional data analysis. We describe a new procedure for selecting significant genes as recursive cluster elimination (RCE) rather than recursive feature elimination (RFE).

Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier.

Motivation: Most computational methodologies for microRNA gene prediction utilize techniques based on sequence conservation and/or structural similarity. In this study we describe a new technique, which is applicable across several species, for predicting miRNA genes. This technique is based on machine learning, using the Naive Bayes classifier.

Detection of differential gene expression in brown adipose tissue of hibernating arctic ground squirrels with mouse microarrays.

Hibernation is an energy-saving strategy adopted by a wide range of mammals to survive highly seasonal or unpredictable environments. Arctic ground squirrels living in Alaska provide an extreme example, with 6- to 9-mo-long hibernation seasons when body temperature alternates between levels near 0 degrees C during torpor and 37 degrees C during arousal episodes. Heat production during hibernation is provided, in part, by nonshivering thermogenesis that occurs in large deposits of brown adipose tissue (BAT).

Quantitative PCR on 5 genes reliably identifies CTCL patients with 5% to 99% circulating tumor cells with 90% accuracy.

We previously identified a small number of genes using cDNA arrays that accurately diagnosed patients with Sézary Syndrome (SS), the erythrodermic and leukemic form of cutaneous T-cell lymphoma (CTCL). We now report the development of a quantitative real-time polymerase chain reaction (qRT-PCR) assay that uses expression values for just 5 of those genes: STAT4, GATA-3, PLS3, CD1D, and TRAIL. qRT-PCR data from peripheral blood mononuclear cells (PBMCs) accurately classified 88% of 17 patients with high blood tumor burden and 100% of 12 healthy controls in the training set using Fisher linear discriminant analysis (FLDA).

Infection of U937 monocytic cells with Chlamydia pneumoniae induces extensive changes in host cell gene expression.

The effect of infection with Chlamydia pneumoniae on host messenger RNA expression in human monocytic cells with complement DNA microarrays was studied. The data chronicle a cascade of transcriptional events affecting 128 genes, many of which have not previously been reported to be affected by C. pneumoniae infection.

Classification and prediction of survival in patients with the leukemic phase of cutaneous T cell lymphoma.

We have used cDNA arrays to investigate gene expression patterns in peripheral blood mononuclear cells from patients with leukemic forms of cutaneous T cell lymphoma, primarily Sezary syndrome (SS). When expression data for patients with high blood tumor burden (Sezary cells >60% of the lymphocytes) and healthy controls are compared by Student's t test, at P < 0.01, we find 385 genes to be differentially expressed.