Background: As early and appropriate care of severe septic patients is associated with better outcome, understanding of the very first events in the disease process is needed. Pan-genomic analyses offer an interesting opportunity to study global genomic response within the very first hours after sepsis.The objective of this study was to investigate the systemic genomic response in severe intensive care unit (ICU) patients and determine whether patterns of gene expression could be associated with clinical severity evaluated by the severity score.Methods: Twenty-eight ICU patients were enrolled at the onset of septic shock. Blood samples were collected within 30 min and 24 and 48 h after shock and genomic response was evaluated using microarrays. The genome-wide expression pattern of blood leukocytes was sequentially compared to healthy volunteers and after stratification based on Simplified Acute Physiology Score II (SAPSII) score to identify potential mechanisms of dysregulation.Results: Septic shock induces a global reprogramming of the whole leukocyte transcriptome affecting multiple functions and pathways (>71% of the whole genome was modified). Most altered pathways were not significantly different between SAPSII-high and SAPSII-low groups of patients. However, the magnitude and the duration of these alterations were different between these two groups. Importantly, we observed that the more severe patients did not exhibit the strongest modulation. This indicates that some regulation mechanisms leading to recovery seem to take place at the early stage.Conclusions: In conclusion, both pro- and anti-inflammatory processes, measured at the transcriptomic level, are induced within the very first hours after septic shock. Interestingly, the more severe patients did not exhibit the strongest modulation. This highlights that not only the responses mechanisms by themselves but mainly their early and appropriate regulation are crucial for patient recovery. This reinforces the idea that an immediate and tailored aggressive care of patients, aimed at restoring an appropriately regulated immune response, may have a beneficial impact on the outcome.

Lipopolysaccharide (LPS) is ubiquitous in the environment. Inhalation of LPS has been implicated in the pathogenesis and/or severity of several lung diseases, including pneumonia, chronic obstructive pulmonary disease and asthma. Alveolar macrophages are the main resident leukocytes exposed to inhaled antigens. To obtain insight into which innate immune pathways become activated within human alveolar macrophages upon exposure to LPS in vivo, we conducted a study in eight healthy humans, in which we instilled sterile saline into a lung segment by bronchoscope, followed by instillation of LPS into the contralateral lung. Six hours later, a bilateral bronchoalveolar lavage was performed and whole-genome transcriptional profiling was done on purified alveolar macrophages, comparing cells exposed to saline or LPS from the same individuals. LPS induced differential expression of 2,932 genes in alveolar macrophages; 1,520 genes were upregulated, whereas 1,440 genes were downregulated. A total of 26 biological functions were overrepresented in LPS-exposed macrophages; 44 canonical pathways affected by LPS were identified, among which the genes associated with the role of pattern recognition receptors in recognition of bacteria and viruses represented the top pathway. Other pathways included cellular immune response, signaling by tumor necrosis factor (receptor) family members, cytokine signaling and glucocorticoid receptor signaling. These results reveal for the first time a large number of functional pathways influenced by the biologically relevant challenge provided by LPS administered into the airways. These data can assist in identifying novel targets for therapeutic intervention in pulmonary diseases associated with LPS exposure, including pneumonia, asthma and chronic obstructive pulmonary disease.

BACKGROUND:The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals.METHODOLOGY/PRINCIPAL FINDINGS:Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients.CONCLUSIONS:In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

Background: One of the most thoroughly studied systems in relation to its prognostic relevance in patients with breast cancer, is the plasminogen activation system that comprises of, among others, the urokinase Plasminogen Activator (uPA) and its main inhibitor, the Plasminogen Activator Inhibitor-1 (PAI-1). In this study, we investigated the prognostic value of uPA and PAI-1 at the mRNA level in lymph node- and hormone receptor-positive breast cancer.Methods: The study included a retrospective series of 87 patients with hormone-receptor positive and axillary lymph node- positive breast cancer. All patients received radiotherapy, adjuvant anthracycline-based chemotherapy and five years of tamoxifen treatment. The median patient age was 54 and the median follow-up time was 79 months. Distant relapse occurred in 30 patients and 22 patients died from breast cancer during follow-up. We investigated the prognostic value of uPA and PAI-1 at the mRNA level as measured by real-time quantitative RT-PCR.Results: uPA and PAI-1 gene expression was not found to be correlated with any of the established clinical and pathological factors. Metastasis-free Survival (MFS) and Breast Cancer specific Survival (BCS) were significantly shorter in patients expressing high levels of PAI-1 mRNA ( p < 0.0001; p < 0.0001; respectively). In Cox multivariate analysis, the level of PAI-1 mRNA appeared to be the strongest prognostic factor for MFS ( Hazard Ratio (HR) = 10.12; p = 0.0002) and for BCS ( HR = 13.17; p = 0.0003). Furthermore, uPA gene expression was not significantly associated neither with MFS ( p = 0.41) nor with BCS ( p = 0.19). In a Cox-multivariate regression analysis, uPA expression did not demonstrate significant independent prognostic value.Conclusion: These findings indicate that high PAI-1 mRNA expression represents a strong and independent unfavorable prognostic factor for the development of metastases and for breast cancer specific survival in a population of hormone receptor- and lymph node- positive breast cancer patients.

Proc Amer Assoc Cancer Res, Volume 47, 2006 3603 It is now well established that early detection of breast cancer improves survival rates and increases the probability of successful treatment. To date, mammographic screening is the most reliable method to detect breast cancer in asymptomatic women. However, mammography has significant limitations: it often fails to detect very small tumors in absence of microcalcifications and is difficult to interpret with dense breast in young women. These limitations lead us to evaluate an alternative method for screening breast cancers based on the identification of a molecular signature in peripheral blood cells. ExonHit’s gene profiling technology DATAS (Differential Analysis of Transcripts with Alternative Splicing) allowed the isolation of a set of messengers and alternatively spliced mRNA sequences that were differentially expressed between the blood of healthy women and early stage breast cancer patients. A customised Affymetrix Genechip array has then been set up for the validation of those DATAS clones. Total RNA extracted from whole blood samples of 37 controls and 55 breast cancer stage I/II (i.e. train group) were amplified, labeled and hybridized on the custom array in order to identify the most significant diagnostic markers. Monoparametric and multiparametric approaches have been carried out, leading to the identification of a 54-gene signature capable of clearly distinguishing healthy women from early stage breast cancers. By applying this method to the train group, 86.5% of the controls and 92.7% of the breast cancers were correctly classified. A first, limited validation with 21 independent blood samples (5 healthy controls vs 16 early stage-breast cancers) showed that this expression profile in blood kept its diagnostic power. The confirmation of the robustness of the blood-molecular signature is underway using a larger independent cohort of 1000 patients. In parallel, blood samples of patients suffering from benign breast diseases, inflammatory diseases or other types of cancer are processed in order to evaluate the specificity of the gene signature for breast cancer. Taken together, our results show that a gene expression-based assay can be developed for the early detection of breast cancer through the use of 5ml of whole blood and that such assay will rely on transcripts very unlikely to be expressed from circulating tumor cells.

Although genetic predisposition to type 1 diabetes shows a strong association with human leukocyte antigen (HLA) class II alleles, additional genes may influence the immune process and the progression of beta cell loss. Preliminary reports suggested that IL-10 gene polymorphisms contribute to susceptibility to type 1 diabetes. We analyzed the frequencies of three main variants of the promoter region of the IL-10 gene at the positions -1082, -819, and -592 in a cohort of 358 type 1 diabetic patients representing the same regional population pattern and 519 controls from the same region using an enzyme-linked oligonucleotide sorbent assay. We did not find any statistical association in the entire cohort or after stratification for high-risk HLA-DQ alleles. However, the IL-10 -1082 polymorphism was significantly associated with GAD and IA-2 antibodies at clinical onset. Such polymorphism is known to be associated with the reduction of secreted IL-10 which may support the concept of accelerated Th-1 T-cell reactivity. In conclusion, IL-10 promoter gene variants may contribute, but to a minor extent, to disease susceptibility in juvenile type 1 diabetes and should not be included in the routine genetic screening of high-risk individuals.

Abstract In human breast cancer, estrogen receptor-α (ERα), progesterone receptor (PR) and human epidermal growth factor receptor (ERBB2) status are currently determined using different techniques. We propose to assess the mRNA expression of these three clinically relevant markers using a unique technique, real-time nucleic acid sequence-based amplification (NASBA). Gene expression of hormone receptors was analyzed and compared to the cytosolic functional protein content as determined with a ligand binding assay (LBA), while ERBB2 mRNA expression was compared to quantitative PCR and ELISA. We observed that the three markers are significantly overexpressed at the mRNA level in positive tumors, as measured by DNA- or protein-based techniques. Biostatistical analysis of the receiver operating characteristic (ROC) curve demonstrated high concordance between NASBA and LBA [area under the curve (AUC) for ROC of 0.899] and showed that ERα status could be predicted using the molecular assay with a sensitivity of 72.7% and a specificity of 93.5%. Similar results were obtained for PR (AUC ROC 0.938, sensitivity 75.3%, specificity 100%). Moreover, excellent concordance was observed between NASBA, quantitative PCR and ELISA with respect to ERBB2 (AUC ROC 0.92, sensitivity 90%, specificity 89.7%; and AUC ROC 0.98, sensitivity 100%, specificity 91.5%, respectively). These results suggest that NASBA is well suited for assessing ER, PR and ERBB2 status in breast tumor samples. This approach is rapid, highly sensitive and a standardized method that could be complementary to the existing techniques, especially for small tumors.