1,409
Views
42
CrossRef citations to date
0
Altmetric
Reports

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data

ORCID Icon, , ORCID Icon, , , , , , , , , , , ORCID Icon, , , , , ORCID Icon, & ORCID Icon show all
Pages 1810-1823 | Received 15 May 2017, Accepted 25 Jul 2017, Published online: 22 Sep 2017

References

  • Kumar D, Bansal G, Narang A, Basak T, Abas T, Dash D. Integrating transcriptome and proteome profiling: Strategies and applications. Proteomics. 2016;6:2533-44. PMID:27343053. doi:10.1002/pmic.201600140
  • Zhavoronkov A, Cantor CR. Methods for structuring scientific knowledge from many areas related to aging research. PLoS One. 2011;6:e22597. doi:10.1371/journal.pone.0022597. PMID:21799912
  • Buzdin AA, Zhavoronkov AA, Korzinkin MB, Roumiantsev SA, Aliper AM, Venkova LS, Smirnov PY, Borisov NM. The OncoFinder algorithm for minimizing the errors introduced by the high-throughput methods of transcriptome analysis. Front Mol Biosc. 2014;1:8. PMID:25988149. doi:10.3389/fmolb.2014.00008
  • MAQC Consortium. The MicroArray Quality Control (MAQC) project shows inter- and intra-platform reproducibility of gene expression measurements. Nat Biotechnol. 2006;24:1151-61. PMID:16964229
  • Zhang L, Zhang J, Yang G, Wu D, Jiang L, Wen Z, Li M. Investigating the concordance of Gene Ontology terms reveals the intra- and inter-platform reproducibility of enrichment analysis. BMC Bioinformatics. 2013;14:143. doi:10.1186/1471-2105-14-143. PMID:23627640
  • Diederich M, Cerella C. Non-canonical programmed cell death mechanisms triggered by natural compounds. Semin Cancer Biol. 2016;S1044-579X:30021-29. PMID:27262793. doi:10.1016/j.semcancer.2016.06.001
  • Zhavoronkov A, Buzdin AA, Garazha AV, Borisov NM, Moskalev AA. Signaling pathway cloud regulation for in silico screening and ranking of the potential geroprotective drugs. Front Genet. 2014;5:49. doi:10.3389/fgene.2014.00049. PMID:24624136
  • Kholodenko BN, Demin OV, Moehren G, Hoek JB. Quantification of short term signaling by the epidermal growth factor receptor. J Biol Chem 1999;274:30169-81. PMID:10514507. doi:10.1074/jbc.274.42.30169
  • Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100:57-70. doi:10.1016/S0092-8674(00)81683-9. PMID:10647931
  • Croft D, Mundo AF, Haw R, Milacic M, Weiser J, Wu G, Caudy M, Garapati P, Gillespie M, Kamdar MR et al. The Reactome pathway knowledge base. Nucleic Acids Res. 2014;42:D472-77. doi:10.1093/nar/gkt1102. PMID:24243840
  • Nakaya A, Katayama T, Itoh M, Hiranuka K, Kawashima S, Moriya Y, Okuda S, Tanaka M, Tokimatsu T, Yamanishi Y et al. KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters. Nucleic Acids Res. 2013;41:D353-57, doi:10.1093/nar/gks1239. PMID:23193276
  • Borisov NM, Terekhanova NV, Aliper AM, Venkova LS, Smirnov PY, Roumiantsev S, Korzinkin MB, Zhavoronkov AA, Buzdin AA. Signaling pathways activation profiles make better markers of cancer than expression of individual genes. Oncotarget. 2014;5:10198-205. doi:10.18632/oncotarget.2358. PMID:25415353
  • Lezhnina K, Kovalchuk O, Zhavoronkov AA, Korzinkin MB, Zabolotneva AA, Shegay PV, Sokov DG, Gaifullin NM, Rusakov IG, Aliper AM. Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways. Oncotarget. 2014;5:9022-32. doi:10.18632/oncotarget.2493. PMID:25296972
  • Zhu Q, Izumchenko E, Aliper AM, Makarev E, Paz K, Buzdin AA, Zhavoronkov AA, Sidransky D. Pathway activation strength is a novel independent prognostic biomarker for cetuximab sensitivity in colorectal cancer patients. Hum Genome Var. 2015;2:15009. doi:10.1038/hgv.2015.9. PMID:27081524
  • Venkova L, Aliper A, Suntsova M, Kholodenko R, Shepelin D, Borisov N, Malakhova G., Vasilov R, Roumiantsev S, Zhavoronkov A, Buzdin A. Oncotarget. 2015;6:27227-32728. doi:10.18632/oncotarget.4507. PMID:26317900
  • Artemov A, Aliper A, Korzinkin, M, Lezhnina K, Jellen L, Zhukov N, Roumiantsev S, Gaifullin N, Zhavoronkov A, Borisov N, Buzdin A. A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation. Oncotarget. 2015;6:29347-56. doi:10.18632/oncotarget.5119. PMID:26320181
  • Khatri P, Sirota M, Butte AJ. Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol. 2012;8:e1002375. doi:10.1371/journal.pcbi.1002375. PMID:22383865
  • Buzdin AA, Zhavoronkov AA, Korzinkin MB, Venkova LS, Zenin AA, Smirnov PY, Borisov NM. Oncofinder, a new method for the analysis of intracellular signaling pathway activation using transcriptomic data. Front Genet. 2014;5:55. doi:10.3389/fgene.2014.00055. PMID:24723936
  • Gao, S, Wang X. TAPPA: topological analysis of pathway phenotype association. Bioinformatics. 2007;23:3100-02. doi:10.1093/bioinformatics/btm460. PMID:17890270
  • Ibrahim MA, Jassim S, Cawthorne MA, Langlands K. A topology-based score for pathway enrichment. J Comput Biol. 2012;19:563-73. doi:10.1089/cmb.2011.0182. PMID:22468678
  • Draghici S, Khatri P, Tarca AL, Amin K, Done A, Voichita C, Georgescu C, Romero R. A systems biology approach for pathway level analysis. Genome Res. 2007;17:1537-45. doi:10.1101/gr.6202607. PMID:17785539
  • Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, Kim CJ, Kusanovic JP, Romero R. A novel signaling pathway impact analysis. Bioinformatics. 2009;25:75-82. doi:10.1093/bioinformatics/btn577. PMID:18990722
  • Shabalin AA, Tjelmeland H, Fan C, Perou CM, Nobel AB. Merging two gene-expression studies via cross-platform normalization. Bioinformatics. 2008;24:1154-60. doi:10.1093/bioinformatics/btn083. PMID:18325927
  • Makarev E, Izumchenko E, Aihara F, Wysocki PT, Zhu Q, Buzdin A, Sidransky D, Zhavo-ronkov A, Atala A. Common pathway signature in lung and liver fibrosis. Cell Cycle. 2016;15:1667-73. doi:10.1080/15384101.2016.1152435. PMID:27267766
  • Artcibasova AV, Korzinkin MB, Sorokin MI, Shegay PV, Zhavoronkov AA, Gaifullin N Alekseev BY, Vorobyev NV, Kuzmin DV, Kaprin АD, et al. MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways. Cell Cycle. 2016;15:689-98. doi:10.1080/15384101.2016.1147633. PMID:27027999
  • Alexandrova E, Nassa G, Corleone G, Buzdin A., Aliper AM, Terekhanova N, Shepelin D, Zhavoronkov A, Tamm M, Milanesi L, et al. Large-scale profiling of signaling pathways reveals an asthma specific signature in bronchial smooth muscle cells. Oncotarget. 2016;7:25150-61. doi:10.18632/oncotarget.7209. PMID:26863634
  • Lebedev TD, Spirin PV, Suntsova MV, Ivanova AV, Buzdin AA, Prokofjeva MM, Rub-tsov PM, Prassolov VS. Receptor tyrosine kinase KIT may regulate expression of genes involved in spontaneous regression of neuroblastoma. Mol Biol (Mosk). 2015;49:1052-1055. doi:10.7868/S0026898415060154. PMID:26710790
  • Lazar C, Meganck S, Taminau J, Steenhoff D, Coletta A, Molter C, Weiss-Solís DY, Duque R, Bersini H, Nowé A. Batch effect removal methods for microarray gene expression data integration: a survey. Brief Bioinform. 2013;14:469-90. doi:10.1093/bib/bbs037. PMID:22851511
  • Risso D, Schwartz K, Sherlock G, Dudoit S. GC-content normalization for RNA-Seq data. BMC Bioinformatics. 2011;12:480. doi:10.1186/1471-2105-12-480. PMID:22177264
  • Karlsson J, Holmquist Mengelbier L, Ciornei CD, Naranjo A, O'Sullivan MJ, Gisselsson D. Clear cell sarcoma of the kidney demonstrates an embryonic signature indicative of a primitive nephrogenic origin. Genes Chromosomes Cancer. 2014;53:381-91. doi:10.1002/gcc.22149. PMID:24488803
  • Van Delft J, Gaj S, Lienhard J, Albrecht MW, Kirpiy A, Brauers K, Claes-sen S, Lizarraga D, Lehrach H, Herwig R, Kleinjans J. RNA-seq provides new insights in the transcriptome responses induced by the carcinogen benzo[a]pyrene. Toxicological sciences. 2012;130:427-39. doi:10.1093/toxsci/kfs250. PMID:22889811
  • Xu X, Zhang Y, Williams J, Antoniou E, McCombie WR, Wu S, Zhu W, Davidson NO, De-noya P, Li E. Parallel comparison of Illumina RNA-Seq and Affymetrix microarray platforms on transcriptomic profiles generated from 5-aza-deoxy-cytidine treated HT-29 colon cancer cells and simulated datasets. BMC Bioinformatics. 2013;14:S1. doi:10.1186/1471-2105-14-S9-S1. PMID:23902433
  • Kim SC, Jung Y, Park J, Cho S, Seo C, Kim J, Kim P, Park J, Seo J, Kim J, et al. A high-dimensional, deep-sequencing study of lung adenocarcinoma in female never-smokers. PLoS One. 2013;8:e55596. doi:10.1371/journal.pone.0055596. PMID:23405175
  • Yang W, Ramachandran A, You S, Jeong H, Morley S, Mulone MD, Log-vinenko T, Kim J, Hwang D, Freeman MR, Adam RM. Integration of proteomic and transcriptomic profiles identifies a novel PDGF-MYC network in human smooth muscle cells. Cell Commun Signal. 2014;12:44. doi:10.1186/s12964-014-0044-z. PMID:25080971
  • Cabezas-Wallscheid N, Klimmeck D, Hansson J, Lipka DB, Reyes A, Wang Q, Weich-enhan D, Lier A, von Paleske L, Renders S, et al. Identification of regulatory networks in HSCs and their immediate progeny via integrated proteome, transcriptome, and DNA methylome analysis. Cell Stem Cell. 2014;15:507-22. doi:10.1016/j.stem.2014.07.005
  • Hara Y, Kawasaki N, Hirano K, Hashimoto Y, Adachi J, Watanabe S, Tomonaga T. Quantitative proteomic analysis of cultured skin fibroblast cells derived from patients with triglyceride deposit cardiomyovasculopathy. Orphanet J Rare Dis. 2013;8:197. doi:10.1186/1750-1172-8-197. PMID: 24360150
  • Warnat P, Eils R, Brors B. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes. BMC Bioinformatics. 2005;6:265. doi: 10.1186/1471-2105-6-265. PMID:16271137
  • Hsu MJ, Chang YC, Hsueh HM. Biomarker selection for medical diagnosis using the partial area under the ROC curve. BMC Res Notes. 2014;7:25. doi:10.1186/1756-0500-7-25. PMID:24410929
  • Chalaya T, Gogvadze E, Buzdin A, Kovalskaya E, Sverdlov ED. Improving specificity of DNA hybridization-based methods. Nucleic Acids Res. 2004;32:e130. doi:10.1093/nar/gnh125. PMID:15371554
  • Shugay M, Britanova OV, Merzlyak EM, Turchaninova MA, Mamedov Z, Tuganbaev TR, Bo-lotin DA, Staroverov DB, Putintseva EV, Plevova K, et al. Towards error-free profiling of immune repertoires. Nat Methods. 2014;11:653-655. doi:10.1038/nmeth.2960. PMID:24793455
  • Aiello D, Casadonte F, Terracciano R, Damiano R, Savino R, Sindona G, Napoli A. Targeted proteomic approach in prostatic tissue: a panel of potential biomarkers for cancer detection. Oncoscience. 2016;3:220-41. doi:10.18632/oncoscience.313. PMID:27713912
  • Borras C, Abdelaziz KM, Gambini J, Serna E, Inglés M, de la Fuente M, Garcia I, Matheu A, Sanchís P, Belenguer A, Errigo A, Avellana JA, Barettino A, Lloret-Fernández C, Flames N, Pes G, Rodriguez-Mañas L, Viña J. Human exceptional longevity: transcriptome from centenarians is distinct from septuagenarians and reveals a role of Bcl-xL in successful aging. Aging (Albany NY). 2016;8:3185-208. doi:10.18632/aging.101078. PMID:27794564
  • Demetrashvili N, Kron K, Pethe V, Bapat B, Briollais L. How to deal with batch effect in sequential microarray experiments? Mol Inform. 2010;29:387-393. doi:10.1002/minf.200900019. PMID:27463194
  • Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455:1061-68. doi:10.1038/nature07385. PMID:18772890
  • Jones P, Côté RG, Martens L, Quinn AF, Taylor CF, Derache W, Hermjakob H, Apweiler R. PRIDE: a public repository of protein and peptide identifications for the proteomics community. Nucleic Acids Res. 2006;34:D659-63. doi:10.1093/nar/gkj138. PMID:16381953
  • Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003;19:185-193. PMID:12538238. doi:10.1093/bioinformatics/19.2.185.
  • McCall MN, Bolstad BM, Irizarry RA. Frozen robust multiarray analysis (fRMA). Biostatistics. 2010, 11:242-53. doi:10.1093/biostatistics/kxp059. PMID:20097884
  • Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106. doi:10.1186/gb-2010-11-10-r106. PMID:20979621
  • Huang H, Lu X, Liu Y, Haaland P, Marron JS. R/DWD: distance-weighted discrimination for classification, visualization and batch adjustment. Bioinformatics. 2012;28:1182-83. doi:10.1093/bioinformatics/bts096. PMID:22368246
  • Deshwar, A.G., Morris, Q. (2014) PLIDA: cross-platform gene expression normalization using perturbed topic models. Bioinformatics, 30, 956-61, 10.1093/bioinformatics/btt574. PMID:24123674
  • Spirin PV, Lebedev TD, Orlova NN, Gornostaeva AS, Prokofjeva MM, Nikitenko NA, Dmit-riev SE, Buzdin AA, Borisov NM, Aliper AM, et al. Silencing AML1-ETO gene expression leads to simultaneous activation of both pro-apoptotic and proliferation signaling. Leukemia. 2014;28:2222-8. doi:10.1038/leu.2014.130. PMID:24727677
  • Birtwistle MR, Hatakeyama M, Yumoto N, Ogunnaike BA, Hoek JB, Kholodenko BN. Ligand-dependent responses of the ErbB signaling network: experimental and modeling analyses. Mol Syst Biol. 2007;3:144. doi:10.1038/msb4100188. PMID:18004277
  • Borisov N, Aksamitiene E, Kiyatkin A, Legewie S, Berkhout J, Maiwald T, Kaimach-nikov NP, Timmer J, Hoek, JB, Kholodenko B.N. Systems-level interactions between insulin-EGF networks amplify mitogenic signaling. Mol Syst Biol. 2009;5:256. doi:10.1038/msb.2009.19. PMID:19357636
  • Kuzmina NB, Borisov NM. Handling complex rule-based models of mitogenic cell signaling (On the example of ERK activation upon EGF stimulation). Intl Proc Chem Biol Envir Engng. 2011;5:76-82. doi:10.7763/ipcbee.2011.v5.17
  • Even Sh. Graph Algorithms. Ed. by G. Even. Cambridge, UK: Cambridge University Press; 2011. ISBN-13: 978-0521736534. ISBN-10: 0521736536
  • Culhane AC, Thioulouse J, Perrière G, Higgins DG. MADE4: an R package for multivariate analysis of gene expression data. Bioinformatics. 2005;21:2789-90. doi:10.1093/bioinformatics/bti394. PMID:15797915
  • Scales M, Jäger R, Migliorini G, Houlston RS, Henrion MY. VisPIG–a web tool for producing multi-region, multi-track, multi-scale plots of genetic data. PLoS One. 2014;9:e107497. doi:10.1371/journal.pone.0107497. PMID:25208325
  • Rudy J, Valafar F. Empirical comparison of cross-platform normalization methods for gene expression data. BMC Bioinformatics. 2011;12:46. doi:10.1186/1471-2105-12-467. PMID:21291543

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.