63 research outputs found

    Expression of Sirtuin 1 and 2 Is Associated with Poor Prognosis in Non-Small Cell Lung Cancer Patients

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    Sirtuin 1 (SIRT1) and sirtuin 2 (SIRT2) are NAD+-dependent protein deacetylases involved in the regulation of key cancer-associated genes. In this study we evaluated the relevance of these deacetylases in lung cancer biology

    Identification of Importin 8 (IPO8) as the most accurate reference gene for the clinicopathological analysis of lung specimens

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    <p>Abstract</p> <p>Background</p> <p>The accurate normalization of differentially expressed genes in lung cancer is essential for the identification of novel therapeutic targets and biomarkers by real time RT-PCR and microarrays. Although classical "housekeeping" genes, such as GAPDH, HPRT1, and beta-actin have been widely used in the past, their accuracy as reference genes for lung tissues has not been proven.</p> <p>Results</p> <p>We have conducted a thorough analysis of a panel of 16 candidate reference genes for lung specimens and lung cell lines. Gene expression was measured by quantitative real time RT-PCR and expression stability was analyzed with the softwares <it>GeNorm </it>and <it>NormFinder</it>, mean of |ΔCt| (= |Ct Normal-Ct tumor|) ± SEM, and correlation coefficients among genes. Systematic comparison between candidates led us to the identification of a subset of suitable reference genes for clinical samples: IPO8, ACTB, POLR2A, 18S, and PPIA. Further analysis showed that IPO8 had a very low mean of |ΔCt| (0.70 ± 0.09), with no statistically significant differences between normal and malignant samples and with excellent expression stability.</p> <p>Conclusion</p> <p>Our data show that IPO8 is the most accurate reference gene for clinical lung specimens. In addition, we demonstrate that the commonly used genes GAPDH and HPRT1 are inappropriate to normalize data derived from lung biopsies, although they are suitable as reference genes for lung cell lines. We thus propose IPO8 as a novel reference gene for lung cancer samples.</p

    Identification of importin (IPO-8) as the most accurate reference gene for the clinicopathological analysis of lung specimens

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    Abstract Background: The accurate normalization of differentially expressed genes in lung cancer is essential for the identification of novel therapeutic targets and biomarkers by real time RT-PCR and microarrays. Although classical "housekeeping" genes, such as GAPDH, HPRT1, and beta-actin have been widely used in the past, their accuracy as reference genes for lung tissues has not been proven. Results: We have conducted a thorough analysis of a panel of 16 candidate reference genes for lung specimens and lung cell lines. Gene expression was measured by quantitative real time RTPCR and expression stability was analyzed with the softwares GeNorm and NormFinder, mean of |ΔCt| (= |Ct Normal-Ct tumor|) ± SEM, and correlation coefficients among genes. Systematic comparison between candidates led us to the identification of a subset of suitable reference genes for clinical samples: IPO8, ACTB, POLR2A, 18S, and PPIA. Further analysis showed that IPO8 had a very low mean of |ΔCt| (0.70 ± 0.09), with no statistically significant differences between normal and malignant samples and with excellent expression stability. Conclusion: Our data show that IPO8 is the most accurate reference gene for clinical lung specimens. In addition, we demonstrate that the commonly used genes GAPDH and HPRT1 are inappropriate to normalize data derived from lung biopsies, although they are suitable as reference genes for lung cell lines. We thus propose IPO8 as a novel reference gene for lung cancer samples

    Development of a novel splice array platform and its application in the identification of alternative splice variants in lung cancer

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    Abstract Background Microarrays strategies, which allow for the characterization of thousands of alternative splice forms in a single test, can be applied to identify differential alternative splicing events. In this study, a novel splice array approach was developed, including the design of a high-density oligonucleotide array, a labeling procedure, and an algorithm to identify splice events. Results The array consisted of exon probes and thermodynamically balanced junction probes. Suboptimal probes were tagged and considered in the final analysis. An unbiased labeling protocol was developed using random primers. The algorithm used to distinguish changes in expression from changes in splicing was calibrated using internal non-spliced control sequences. The performance of this splice array was validated with artificial constructs for CDC6, VEGF, and PCBP4 isoforms. The platform was then applied to the analysis of differential splice forms in lung cancer samples compared to matched normal lung tissue. Overexpression of splice isoforms was identified for genes encoding CEACAM1, FHL-1, MLPH, and SUSD2. None of these splicing isoforms had been previously associated with lung cancer. Conclusions This methodology enables the detection of alternative splicing events in complex biological samples, providing a powerful tool to identify novel diagnostic and prognostic biomarkers for cancer and other pathologies

    YES1 drives lung cancer growth and progression and predicts sensitivity to dasatinib

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    Rationale: The characterization of new genetic alterations is essential to assign effective personalized therapies in non–small cell lung cancer (NSCLC). Furthermore, finding stratification biomarkers is essential for successful personalized therapies. Molecular alterations of YES1, a member of the SRC (proto-oncogene tyrosine-protein kinase Src) family kinases (SFKs), can be found in a significant subset of patients with lung cancer. Objectives: To evaluate YES1 (v-YES-1 Yamaguchi sarcoma viral oncogene homolog 1) genetic alteration as a therapeutic target and predictive biomarker of response to dasatinib in NSCLC. Methods: Functional significance was evaluated by in vivo models of NSCLC and metastasis and patient-derived xenografts. The efficacy of pharmacological and genetic (CRISPR [clustered regularly interspaced short palindromic repeats]/Cas9 [CRISPR-associated protein 9]) YES1 abrogation was also evaluated. In vitro functional assays for signaling, survival, and invasion were also performed. The association between YES1 alterations and prognosis was evaluated in clinical samples. Measurements and Main Results: We demonstrated that YES1 is essential for NSCLC carcinogenesis. Furthermore, YES1 overexpression induced metastatic spread in preclinical in vivo models. YES1 genetic depletion by CRISPR/Cas9 technology significantly reduced tumor growth and metastasis. YES1 effects were mainly driven by mTOR (mammalian target of rapamycin) signaling. Interestingly, cell lines and patient-derived xenograft models with YES1 gene amplifications presented a high sensitivity to dasatinib, an SFK inhibitor, pointing out YES1 status as a stratification biomarker for dasatinib response. Moreover, high YES1 protein expression was an independent predictor for poor prognosis in patients with lung cancer. Conclusions: YES1 is a promising therapeutic target in lung cancer. Our results provide support for the clinical evaluation of dasatinib treatment in a selected subset of patients using YES1 status as predictive biomarker for therapy

    Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations

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    BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n = 73 for ADC, n = 97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P = 0.008 for ADC and P = 0.019 for SCC) and outperforms both the clinical models (P = 0.060 for ADC and P = 0.121 for SCC) and the genomic models applied separately (P = 0.350 for ADC and P = 0.269 for SCC). CONCLUSION: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on tumor DNA that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC

    Alveolar hypoxia, alveolar macrophages, and systemic inflammation

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    Diseases featuring abnormally low alveolar PO2 are frequently accompanied by systemic effects. The common presence of an underlying inflammatory component suggests that inflammation may contribute to the pathogenesis of the systemic effects of alveolar hypoxia. While the role of alveolar macrophages in the immune and defense functions of the lung has been long known, recent evidence indicates that activation of alveolar macrophages causes inflammatory disturbances in the systemic microcirculation. The purpose of this review is to describe observations in experimental animals showing that alveolar macrophages initiate a systemic inflammatory response to alveolar hypoxia. Evidence obtained in intact animals and in primary cell cultures indicate that alveolar macrophages activated by hypoxia release a mediator(s) into the circulation. This mediator activates perivascular mast cells and initiates a widespread systemic inflammation. The inflammatory cascade includes activation of the local renin-angiotensin system and results in increased leukocyte-endothelial interactions in post-capillary venules, increased microvascular levels of reactive O2 species; and extravasation of albumin. Given the known extrapulmonary responses elicited by activation of alveolar macrophages, this novel phenomenon could contribute to some of the systemic effects of conditions featuring low alveolar PO2

    Mudskipper concatenated multiple sequence alignment

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    Concatenated multiple sequence alignment of cox1-cytb-rag1 DNA sequences from 19 species of fish in Nexus file format
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