Elucidating the molecular physiopathology of acute respiratory distress syndrome in severe acute respiratory syndrome patients
ABSTRACT Acute respiratory distress syndrome (ARDS) is a severe form of acute lung injury. It is a response to various diseases of variable etiology, including SARS-CoV infection. To date, a comprehensive study of the genomic physiopathology of ARDS (and SARS) is lacking, primarily due to the difficulty of finding suitable materials to study the disease process at a tissue level (instead of blood, sputa or swaps). Hereby we attempt to provide such study by analyzing autopsy lung samples from patient who died of SARS and showed different degrees of severity of the pulmonary involvement. We performed real-time quantitative PCR analysis of 107 genes with functional roles in inflammation, coagulation, fibrosis and apoptosis; some key genes were confirmed at a protein expression level by immunohistochemistry and correlated to the degree of morphological severity present in the individual samples analyzed. Significant expression levels were identified for ANPEP (a receptor for CoV), as well as inhibition of the STAT1 pathway, IFNs production and CXCL10 (a T-cell recruiter). Other genes unassociated to date with ARDS/SARS include C1Qb, C5R1, CASP3, CASP9, CD14, CD68, FGF7, HLA-DRA, IGF1, IRF3, MALAT-1, MSR1, NFIL3, SLPI, USP33, CLC, GBP1 and TAC1. As a result, we proposed to therapeutically target some of these genes with compounds such as ANPEP inhibitors, SLPI and dexamethasone. Ultimately, this study may serve as a model for future, tissue-based analyses of fibroinflammatory conditions affecting the lung.
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ABSTRACT: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.PLoS ONE 08/2010; 5(8):e12262. DOI:10.1371/journal.pone.0012262 · 3.23 Impact Factor
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ABSTRACT: A number of aesthetically and physically distressing disorders of the skin come under the general term "cutaneous fibrosis", all sharing a common abnormal wound healing process. These disorders are often incurable and effective treatments remain to be established and, as such, they present a significant burden for patients and a therapeutic challenge for clinicians. The aim of this review is to investigate the evidence of either positive or negative associations of the human leukocyte antigen (HLA) system with various types of cutaneous fibrosis, focussing in particular on keloid scars, hypertrophic scars and scleroderma. A standard systematic literature search was performed. The strengths and limitations of studies were evaluated in terms of significance, methodology and reproducibility. There is a clear association between specific HLA alleles and predilection or protection to cutaneous fibrosis. Of these candidate HLA alleles, the class II loci seem to be the most promising in terms of a genetic biomarker, with the DQ and DR alleles having significant associations with abnormal wound healing and cutaneous fibrosis. There is strong evidence of a significant immune component in the pathogenesis of each type of fibrotic disorder explored in this review. However, the exact mechanisms remain to be elucidated, since the pathogenesis of cutaneous fibrosis and abnormal wound healing are not fully understood.Acta Dermato-Venereologica 11/2010; 90(6):563-74. DOI:10.2340/00015555-0975 · 3.03 Impact Factor
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ABSTRACT: SARS-CoV is a pathogenic coronavirus that emerged from a zoonotic reservoir, leading to global dissemination of the virus. The association SARS-CoV with aberrant cytokine, chemokine, and Interferon Stimulated Gene (ISG) responses in patients provided evidence that SARS-CoV pathogenesis is at least partially controlled by innate immune signaling. Utilizing models for SARS-CoV infection, key components of innate immune signaling pathways have been identified as protective factors against SARS-CoV disease, including STAT1 and MyD88. Gene transcription signatures unique to SARS-CoV disease states have been identified, but host factors that regulate exacerbated disease phenotypes still remain largely undetermined. SARS-CoV encodes several proteins that modulate innate immune signaling through the antagonism of the induction of Interferon and by avoidance of ISG effector functions.05/2012; 2(3):264-75. DOI:10.1016/j.coviro.2012.04.004