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BACKGROUND:Peripheral blood transcriptome profiling is a potentially important tool for disease detection. We utilize this technique in a case-control study to identify candidate transcriptomic biomarkers able to differentiate women with breast lesions from normal controls. METHODS:Whole blood samples were collected from 50 women with high-risk breast lesions, 57 with breast cancers and 44 controls (151 samples). Blood gene expression profiling was carried out using microarray hybridization. We identified blood gene expression signatures using AdaBoost, and constructed a predictive model differentiating breast lesions from controls. Model performance was then characterized by AUC sensitivity, specificity and accuracy. Biomarker biological processes and functions were analyzed for clues to the pathogenesis of breast lesions. RESULTS:Ten gene biomarkers were identified (YWHAQ, BCLAF1, WSB1, PBX2, DDIT4, LUC7L3, FKBP1A, APP, HERC2P2, FAM126B). A ten-gene panel predictive model showed discriminatory power in the test set (sensitivity: 100%, specificity: 84.2%, accuracy: 93.5%, AUC: 0.99). These biomarkers were involved in apoptosis, TGF-beta signaling, adaptive immune system regulation, gene transcription and post-transcriptional protein modification. CONCLUSION:A promising method for the detection of breast lesions is reported. This study also sheds light on breast cancer/immune system interactions, providing clues to new targets for breast cancer immune therapy.

PURPOSE: Prostate cancer is a bimodal disease with aggressive and indolent forms. Current prostate-specific-antigen testing and digital rectal examination screening provide ambiguous results leading to both under-and over-treatment. Accurate, consistent diagnosis is crucial to risk-stratify patients and facilitate clinical decision making as to treatment versus active surveillance. Diagnosis is currently achieved by needle biopsy, a painful procedure. Thus, there is a clinical need for a minimally-invasive test to determine prostate cancer aggressiveness. A blood sample to predict Gleason score, which is known to reflect aggressiveness of the cancer, could serve as such a test. MATERIALS AND METHODS: Blood mRNA was isolated from North American and Malaysian prostate cancer patients/controls. Microarray analysis was conducted utilizing the Affymetrix U133 plus 2·0 platform. Expression profiles from 255 patients/controls generated 85 candidate biomarkers. Following quantitative real-time PCR (qRT-PCR) analysis, ten disease-associated biomarkers remained for paired statistical analysis and normalization. RESULTS: Microarray analysis was conducted to identify 85 genes differentially expressed between aggressive prostate cancer (Gleason score ≥8) and controls. Expression of these genes was qRT-PCR verified. Statistical analysis yielded a final seven-gene panel evaluated as six gene-ratio duplexes. This molecular signature predicted as aggressive (ie, Gleason score ≥8) 55% of G6 samples, 49% of G7(3+4), 79% of G7(4+3) and 83% of G8-10, while rejecting 98% of controls. CONCLUSION: In this study, we have developed a novel, blood-based biomarker panel which can be used as the basis of a simple blood test to identify men with aggressive prostate cancer and thereby reduce the overdiagnosis and overtreatment that currently results from diagnosis using PSA alone. We discuss possible clinical uses of the panel to identify men more likely to benefit from biopsy and immediate therapy versus those more suited to an "active surveillance" strategy.

Background: Blood has advantages over tissue samples as a diagnostic tool, and blood mRNA transcriptomics is an exciting research field. To realize the full potential of blood transcriptomic investigations requires improved methods for gene expression measurement and data interpretation able to detect biological signatures within the "noisy" variability of whole blood. Methods: We demonstrate collection tube bias compensation during the process of identifying a liver cancer-specific gene signature. The candidate probe set list of liver cancer was filtered, based on previous repeatability performance obtained from technical replicates. We built a prediction model using differential pairs to reduce the impact of confounding factors. We compared prediction performance on an independent test set against prediction on an alternative model derived by Weka. The method was applied to an independent set of 157 blood samples collected in PAXgene tubes. Results: The model discriminated liver cancer equally well in both EDTA and PAXgene collected samples, whereas the Weka-derived model (using default settings) was not able to compensate for collection tube bias. Cross-validation results show our procedure predicted membership of each sample within the disease groups and healthy controls. Conclusion: Our versatile method for blood transcriptomic investigation overcomes several limitations hampering research in blood-based gene tests. [ABSTRACT FROM AUTHOR]

Background: Colonoscopy is widely regarded to be the gold standard for colorectal cancer (CRC) detection. Recent studies, however, suggest that the effectiveness of colonoscopy is mostly confined to tumors on the left side of the colon (descending, sigmoid, rectum), and that the technology has poor tumor detection for right-sided (cecum, ascending, transverse) lesions. A minimally invasive test that can detect both left-sided and right-sided lesions could increase the effectiveness of screening colonoscopy by revealing the potential presence of neoplasms in the right-sided "blind spot". Methods: We previously reported on a seven-gene, blood-based biomarker panel that effectively stratifies a patient's risk of having CRC. For the current study, we assessed the effectiveness of the seven-gene panel for the detection of left- and right-sided CRC lesions. Results were evaluated for 314 patients with CRC (left-sided: TNM I, 65; TNM II, 57; TNM III, 60; TNM IV, 17; unknown, 9. right-sided: TNM I, 28; TNM II, 29; TNM III, 38; TNM IV, 12; unknown, 1 and including two samples with both left and right lesions) and 328 control samples. Blood samples were obtained prior to clinical staging and therapy. Most CRC subjects had localized disease (stages I and II, 58%); regional (stage III) and systemic (stage IV) disease represented 32% and 9%, respectively, of the study population. Results: The panel detected left-sided (74%, 154/208) and right-sided (85%, 92/108) lesions with an overall sensitivity of 78% (215/316) at a specificity of 66% (215/328). Treatable cancer (stages I to III) was detected with left-sided lesion sensitivity of 76% (138/182) and right-sided sensitivity of 84% (80/95). Conclusion: This seven-gene biomarker panel detected right-sided CRC lesions across all cancer stages with a sensitivity that is at least equal to that for left-sided lesions. This study supports the use of this panel as the basis for a patient-friendly, blood-based test that can be easily incorporated into a routine physical examination in advance of colonoscopy to provide a convenient companion diagnostic and a pre-screening alert, ultimately leading to enhanced CRC screening effectiveness. [ABSTRACT FROM AUTHOR]

Background: Treatment protocols for nasopharyngeal carcinoma (NPC) developed in the past decade have significantly improved patient survival. In most NPC patients, however, the disease is diagnosed at late stages, and for some patients treatment response is less than optimal. This investigation has two aims: to identify a blood-based gene-expression signature that differentiates NPC from other medical conditions and from controls and to identify a biomarker signature that correlates with NPC treatment response. Methods: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n = 28) of a pre-intervention case cohort of patients whom we followed post-treatment. Results: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 090). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment. Conclusion: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy. [ABSTRACT FROM AUTHOR]

Gene expression signatures in blood correlate with specific diseases. Such signatures may serve as valuable diagnostic and prognostic tools in disease management. Blood gene expression signatures associated with heart failure may be applied to predict prognosis, monitor disease progression, and optimize treatment. Blood gene expression profiles were generated for 71 subjects with heart failure and 15 controls without heart failure, using the Affymetrix GeneChip U133Plus2.0. Survival analysis identified 197 "mortality genes" that were significantly associated with patient outcome. Functional categorization showed that genes associated with T cell receptor signaling were most significantly overpresented. Cluster analysis of these T cell receptor signaling genes significantly categorized heart failure patients into three risk groups (P = 0.031) that were distinct from the three risk groups categorized by New York Heart Association (NYHA) Classification (P = 0.0002). By combining the analysis of clinical assessment (NYHA class) with T cell receptor signaling gene expression, we proposed a model that demonstrated an even greater differentiation of patients at risk (P = 0.0001). In this discovery study, we identified blood expression signatures associated with heart failure patient outcomes. Characterization of these mortality genes helped identify a set of T cell receptor signaling genes that may be of utility in predicting survival of heart failure patients. These data raise the possibility of prospectively risk stratifying patients with heart failure by integrating blood gene expression signatures with current clinical assessment. [ABSTRACT FROM AUTHOR]

Aldosterone-producing adenomas (APA) are a frequent cause of secondary hypertension characterized by autonomous hypersecretion of aldosterone. However, the molecular mechanisms involved in adrenal tumorigenesis and deregulated aldosterone secretion are currently unknown. To identify putative functional genes, a transcriptional screening was performed on 8 APA and 3 normal adrenals (NA) using oligonucleotide microarrays. Data were next validated on an expanded set of samples by real-time PCR (APA, n=19; NA, n=10). The epidermal growth factor-like teratocarcinoma-derived growth factor-1 (TDGF-1) was upregulated in APA compared with NA (14.7-fold and 21.4-fold by microarray and real-time PCR, respectively). In vitro studies and Western blot analysis using the NCI H295R adrenocortical cell line showed that TDGF-1 increased Akt phosphorylation on Thr308 and Ser473, consistent with activation of phosphatidylinositol 3-kinase/Akt signaling, and also demonstrated a concomitant inactivation of the Akt substrate glycogen synthesis kinase-3beta via Ser9 phosphorylation. Furthermore, TDGF-1 mediated a 3.8+/-0.4-fold increase in aldosterone secretion (n=4) that was specifically blocked by the phosphatidylinositol 3-kinase inhibitors wortmannin (50 nmol/L) and LY294002 (20 micromol/L). Finally, TDGF-1 protected H295R cells from apoptosis induced by staurosporine, causing a decrease in caspase-3 activity, a reduction in the inactivation of poly(ADP-ribose) polymerase, and an inhibition of DNA fragmentation, detected by the TUNEL reaction and fluorescence microscopy that was blocked by LY294002. Taken together, our data suggest that TDGF-1, which is significantly upregulated in APA and mediates aldosterone hypersecretion and deregulated growth in adrenocortical cells in vitro, may represent a key player in the development and pathophysiology of primary aldosteronism. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) screening is key to CRC prevention and mortality reduction, but patient compliance with CRC screening is low. We previously reported a blood-based test for CRC that utilizes a sevengene panel of biomarkers. The test is currently utilized clinically in North America for CRC risk stratification in the average-risk North American population in order to improve screening compliance and to enhance clinical decision making. Methods: In this study, conducted in Malaysia, we evaluated the seven-gene biomarker panel validated in a North American population using blood samples collected from local patients. The panel employs quantitative RT-PCR (qRT-PCR) to analyze gene expression of the seven biomarkers (ANXA3, CLEC4D, TNFAIP6, LMNB1, PRRG4, VNN1 and IL2RB) that are differentially expressed in CRC patients as compared with controls. Blood samples from 210 patients (99 CRC and 111 controls) were collected, and total blood RNA was isolated and subjected to quantitative RT-PCR and data analysis. Results: The logistic regression analysis of seven-gene panel has an area under the curve (AUC) of 0.76 (95% confidence interval: 0.70 to 0.82), 77% specificity, 61% sensitivity and 70% accuracy, comparable to the data obtained from the North American investigation of the same biomarker panel. Conclusions: Our results independently confirm the results of the study conducted in North America and demonstrate the ability of the seven biomarker panel to discriminate CRC from controls in blood samples drawn from a Malaysian population. [ABSTRACT FROM AUTHOR]

Microarray techniques hold great promise for identifying risk factors for schizophrenia (SZ) but have not yet generated widely reproducible results due to methodological differences between studies and the high risk of type 1 inferential errors. Here we established a protocol for conservative analysis and interpretation of gene expression data from the dorsolateral prefrontal cortex of SZ patients using statistical and bioinformatic methods that limit false positives. We also compared brain gene expression profiles with those from peripheral blood cells of a separate sample of SZ patients to identify disease-associated genes that generalize across tissues and populations and further substantiate the use of gene expression profiling of blood for detecting valid SZ biomarkers. Implementing this systematic approach, we: (i) discovered 177 putative SZ risk genes in brain, 28 of which map to linked chromosomal loci; (ii) delineated six biological processes and 12 molecular functions that may be particularly disrupted in the illness; (iii) identified 123 putative SZ biomarkers in blood, 6 of which (BTG1, GSK3A, HLA-DRB1, HNRPA3I SELENBP1, and SFRS1) had corresponding differential expression in brain; (iv) verified the differential expression of the strongest candidate SZ biomarker (SELENBP1) in blood; and (v) demonstrated neuronal and glial expression of SELENBP1 protein in brain. The continued application of this approach in other brain regions and populations should facilitate the discovery of highly reliable and reproducible candidate risk genes and biomarkers for SZ. The identification of valid peripheral biomarkers for SZ may ultimately facilitate early identification, intervention, and prevention efforts as well. [ABSTRACT FROM AUTHOR]

Heart failure is a major disease burden worldwide, and its incidence continues to increase as premature deaths from other cardiovascular conditions decline. Although the overall molecular portrait of this multifactorial disease remains incomplete, molecular and genetic studies have implicated, in recent decades, various pathways and genes that participate in the pathophysiology of heart failure. Here, we highlight the current understanding of the molecular and genetic basis of heart failure and show how recently developed genomic tools are providing a new perspective on this complex disease. [ABSTRACT FROM AUTHOR]

To identify genes that are differentially expressed in human esophageal squamous cell carcinoma (ESCC), we have developed a cDNA microarray representing 34?176 clones to analyse gene expression profiles in ESCC. A total of 77 genes (including 31 novel genes) were downregulated, and 15 genes (including one novel gene) were upregulated in cancer tissues compared with their normal counterparts. Immunohistochemistry and Northern blot analysis were carried out to verify the cDNA microarray results. It was revealed that genes involved in squamous cell differentiation were coordinately downregulated, including annexin I, small proline-rich proteins (SPRRs), calcium-binding S100 proteins (S100A8, S100A9), transglutaminase (TGM3), cytokeratins (KRT4, KRT13), gut-enriched Krupple-like factor (GKLF) and cystatin A. Interestingly, most of the downregulated genes encoded Ca2+-binding or -modulating proteins that constitute the cell envelope (CE). Moreover, genes associated with invasion or proliferation were upregulated, including genes such as fibronectin, secreted protein acidic and rich in cystein (SPARC), cathepsin B and KRT17. Functional analysis of the alteration in the expression of GKLF suggested that GKLF might be able to regulate the expression of SPRR1A, SPRR2A and KRT4 in ESCC. This study provides new insights into the role of squamous cell differentiation-associated genes in ESCC initiation and progression.Oncogene (2004) 23, 1291-1299. doi:10.1038/sj.onc.1207218 Published online 1 December 2003 [ABSTRACT FROM AUTHOR]

Cardiac-restricted genes play important roles in cardiovascular system. In an effort to identify such novel genes we identified a novel cardiac-specific kinase gene TNNI3K localized on 1p31.1 based on bioinformatics analyses. Sequence analysis suggested that TNNI3K is a distant family member of integrin-linked kinase. Northern blot and 76-tissue array analyses showed that TNNI3K is highly expressed in heart, but is undetectable in other tissues. Immunohistochemical analysis predominantly localized TNNI3K in the nucleus of cardiac myocytes. In vitro kinase assay showed that TNNI3K is a functional kinase. The yeast two-hybrid system showed that TNNI3K could directly interact with cardiac troponin I, results that were further confirmed by coimmunoprecipitation in vivo. Our data suggest that TNNI3K is a cardiac-specific kinase and play important roles in cardiac system. [ABSTRACT FROM AUTHOR]