| 1. |
- Alexeyenko, Andrey, et al.
(author)
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Network enrichment analysis : extension of gene-set enrichment analysis to gene networks
- 2012
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In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 13, s. 226-
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Journal article (peer-reviewed)abstract
- Background: Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis. Results: We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study. Conclusions: The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps.
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| 2. |
- Friboulet, Luc, et al.
(author)
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Molecular Characteristics of ERCC1-Negative versus ERCC1-Positive Tumors in Resected NSCLC
- 2011
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In: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 17:17, s. 5562-5572
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Journal article (peer-reviewed)abstract
- Purpose: Excision repair cross-complementation group 1 (ERCC1) is a protein involved in repair of DNA platinum adducts and stalled DNA replication forks. We and others have previously shown the influence of ERCC1 expression upon survival rates and benefit of cisplatin-based chemotherapy in patients with resected non-small-cell lung cancer (NSCLC). However, little is known about the molecular characteristics of ERCC1-positive and ERCC1-negative tumors. Experimental Design: We took advantage of a cohort of 91 patients with resected NSCLC, for which we had matched frozen and paraffin-embedded samples to explore the comparative molecular portraits of ERCC1-positive and ERCC1-negative tumors of NSCLC. We carried out a global molecular analysis including assessment of ERCC1 expression levels by using both immunohistochemistry (IHC) and quantitative reverse transcriptase PCR (qRT-PCR), genomic instability, global gene and miRNA expression, and sequencing of selected key genes involved in lung carcinogenesis. Results: ERCC1 protein and mRNA expression were significantly correlated. However, we observed several cases with clear discrepancies. We noted that ERCC1-negative tumors had a higher rate of genomic abnormalities versus ERCC1-positive tumors. ERCC1-positive tumors seemed to share a common DNA damage response (DDR) phenotype with the overexpression of seven genes linked to DDR. The miRNA expression analysis identified miR-375 as significantly underexpressed in ERCC1-positive tumors. Conclusions: Our data show inconsistencies in ERCC1 expression between IHC and qRT-PCR readouts. Furthermore, ERCC1 status is not linked to specific mutational patterns or frequencies. Finally, ERCC1negative tumors have a high rate of genomic aberrations that could consequently influence prognosis in patients with resected NSCLC. Clin Cancer Res; 17(17); 5562-72.
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| 3. |
- Galluzzi, Lorenzo, et al.
(author)
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Prognostic Impact of Vitamin B6 Metabolism in Lung Cancer
- 2012
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In: Cell Reports. - Cambridge : Cell press. - 2211-1247. ; 2:2, s. 257-269
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Journal article (peer-reviewed)abstract
- Patients with non-small cell lung cancer (NSCLC) are routinely treated with cytotoxic agents such as cisplatin. Through a genome-wide siRNA-based screen, we identified vitamin B6 metabolism as a central regulator of cisplatin responses in vitro and in vivo. By aggravating a bioenergetic catastrophe that involves the depletion of intracellular glutathione, vitamin B6 exacerbates cisplatin-mediated DNA damage, thus sensitizing a large panel of cancer cell lines to apoptosis. Moreover, vitamin B6 sensitizes cancer cells to apoptosis induction by distinct types of physical and chemical stress, including multiple chemotherapeutics. This effect requires pyridoxal kinase (PDXK), the enzyme that generates the bioactive form of vitamin B6. In line with a general role of vitamin B6 in stress responses, low PDXK expression levels were found to be associated with poor disease outcome in two independent cohorts of patients with NSCLC. These results indicate that PDXK expression levels constitute a biomarker for risk stratification among patients with NSCLC.
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| 4. |
- Lazar, Vladimir, et al.
(author)
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Integrated molecular portrait of non-small cell lung cancers
- 2013
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In: BMC Medical Genomics. - : Springer Science and Business Media LLC. - 1755-8794. ; 6:1, s. 53-
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Journal article (peer-reviewed)abstract
- Background: Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. Methods: Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Results: At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of similar to 800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. Conclusions: Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes.
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| 5. |
- Pernemalm, Maria, et al.
(author)
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Quantitative Proteomics Profiling of Primary Lung Adenocarcinoma Tumors Reveals Functional Perturbations in Tumor Metabolism
- 2013
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 12:9, s. 3934-3943
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Journal article (peer-reviewed)abstract
- In this study, we have analyzed human primary lung adenocarcinoma tumors using global mass spectrometry to elucidate the biological mechanisms behind relapse post surgery. In total, we identified over 3000 proteins with high confidence. Supervised multivariate analysis was used to select 132 proteins separating the prognostic groups. Based on in-depth bioinformatics analysis, we hypothesized that the tumors with poor prognosis had a higher glycolytic activity and HIF activation. By measuring the bioenergetic cellular index of the tumors, we could detect a higher dependency of glycolysis among the tumors with poor prognosis. Further, we could also detect an up-regulation of HIF1 alpha mRNA expression in tumors with early relapse. Finally, we selected three proteins that were upregulated in the poor prognosis group (cathepsin D, ENO1, and VDAC1) to confirm that the proteins indeed originated from the tumor and not from a stromal or inflammatory component. Overall, these findings show how in-depth analysis of clinical material can lead to an increased understanding of the molecular mechanisms behind tumor progression.
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| 6. |
- Piovesan, Damiano, et al.
(author)
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DisProt 7.0 : a major update of the database of disordered proteins
- 2017
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In: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 45:D1, s. d219-D227
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Journal article (peer-reviewed)abstract
- The Database of Protein Disorder (DisProt, URL: www.disprot.org) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance ( primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins.
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