A Pilot Proteogenomic Study with Data Integration Identifies MCT1 and GLUT1 as Prognostic Markers in Lung Adenocarcinoma
暂无分享,去创建一个
Bin Fang | Keiryn L. Bennett | John M. Koomen | Steven A. Eschrich | Eric B. Haura | K. Bennett | S. Eschrich | A. Müller | E. Haura | E. Welsh | J. Koomen | B. Fang | K. Parapatics | Paul A. Stewart | Katja Parapatics | Eric A. Welsh | André C. Müller | Haoyun Cao | P. Stewart | Haoyun Cao | Katja Parapatics
[1] L. Cantley,et al. Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation , 2009, Science.
[2] W. Oyen,et al. Glucose Metabolism in NSCLC Is Histology-Specific and Diverges the Prognostic Potential of 18FDG-PET for Adenocarcinoma and Squamous Cell Carcinoma , 2014, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.
[3] Amy-Joan L Ham,et al. Sample preparation and digestion for proteomic analyses using spin filters , 2005, Proteomics.
[4] Steven J. M. Jones,et al. Comprehensive molecular profiling of lung adenocarcinoma , 2014, Nature.
[5] J. Miyoshi,et al. Increased susceptibility to spontaneous lung cancer in mice lacking LIM‐domain only 7 , 2009, Cancer science.
[6] Edward L. Huttlin,et al. Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses. , 2012, Analytical chemistry.
[7] R. Weinshilboum,et al. Role of the glutathione metabolic pathway in lung cancer treatment and prognosis: a review. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[8] Brandon M. Malone,et al. The Proteogenomic Mapping Tool , 2011, BMC Bioinformatics.
[9] Steven Eschrich,et al. Libaffy: software for processing Affymetrix(R) GeneChip(R) data , 2007, Bioinform..
[10] Z. Duan,et al. Aberrant Signaling Pathways in Squamous Cell Lung Carcinoma , 2011, Cancer informatics.
[11] Andrew R. Jones,et al. ProteomeXchange provides globally co-ordinated proteomics data submission and dissemination , 2014, Nature Biotechnology.
[12] P. Massion,et al. In-depth Proteomic Analysis of Nonsmall Cell Lung Cancer to Discover Molecular Targets and Candidate Biomarkers* , 2012, Molecular & Cellular Proteomics.
[13] M. Moran,et al. Proteomic profiles of human lung adeno and squamous cell carcinoma using super‐SILAC and label‐free quantification approaches , 2014, Proteomics.
[14] Benjamin M. Bolstad,et al. affy - analysis of Affymetrix GeneChip data at the probe level , 2004, Bioinform..
[15] David A. Fenstermacher,et al. Tissue-specific RMA models to incrementally normalize Affymetrix GeneChip data , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[16] Jean YH Yang,et al. Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.
[17] Andrey Tovchigrechko,et al. PGP: parallel prokaryotic proteogenomics pipeline for MPI clusters, high-throughput batch clusters and multicore workstations , 2014, Bioinform..
[18] M. Mann,et al. Parts per Million Mass Accuracy on an Orbitrap Mass Spectrometer via Lock Mass Injection into a C-trap*S , 2005, Molecular & Cellular Proteomics.
[19] Mark A. Hall,et al. Blocking lactate export by inhibiting the Myc target MCT1 Disables glycolysis and glutathione synthesis. , 2014, Cancer research.
[20] L. Paz-Ares,et al. Proteomic biomarkers in lung cancer , 2013, Clinical and Translational Oncology.
[21] Rafael Rosell,et al. Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer , 2011, International journal of cancer.
[22] Yixue Li,et al. Identification of gene fusions from human lung cancer mass spectrometry data , 2013, BMC Genomics.
[23] R. Branca,et al. Quantitative accuracy in mass spectrometry based proteomics of complex samples: the impact of labeling and precursor interference. , 2014, Journal of proteomics.
[24] Paul D. Smith,et al. Activity of the Monocarboxylate Transporter 1 Inhibitor AZD3965 in Small Cell Lung Cancer , 2013, Clinical Cancer Research.
[25] A. Nesvizhskii. Proteogenomics: concepts, applications and computational strategies , 2014, Nature Methods.
[26] Steven J. M. Jones,et al. Comprehensive genomic characterization of squamous cell lung cancers , 2012, Nature.
[27] Zlatko Trajanoski,et al. Proteomic analysis of human cataract aqueous humour: Comparison of one-dimensional gel LCMS with two-dimensional LCMS of unlabelled and iTRAQ®-labelled specimens. , 2011, Journal of proteomics.
[28] Philip Wenig,et al. OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data , 2010, BMC Bioinformatics.
[29] Alexey I Nesvizhskii,et al. Interpretation of Shotgun Proteomic Data , 2005, Molecular & Cellular Proteomics.
[30] Hyung-Ryong Kim,et al. Lysyl oxidase-like-1 enhances lung metastasis when lactate accumulation and monocarboxylate transporter expression are involved. , 2011, Oncology letters.
[31] E. Richardsen,et al. Monocarboxylate Transporters 1–4 in NSCLC: MCT1 Is an Independent Prognostic Marker for Survival , 2014, PloS one.
[32] P. Boutros,et al. Onco-proteogenomics: cancer proteomics joins forces with genomics , 2014, Nature Methods.
[33] John L Cleveland,et al. Targeting lactate metabolism for cancer therapeutics. , 2013, Journal of Clinical Investigation.
[34] C. Eyers. Universal sample preparation method for proteome analysis , 2009 .
[35] Frederick Mosteller,et al. Understanding robust and exploratory data analysis , 1983 .
[36] Anders Berglund,et al. Iterative rank-order normalization of gene expression microarray data , 2013, BMC Bioinformatics.
[37] Richard D. Smith,et al. Normalization and missing value imputation for label-free LC-MS analysis , 2012, BMC Bioinformatics.
[38] A. McCullough. Comprehensive genomic characterization of squamous cell lung cancers , 2013 .
[39] H. Rodriguez,et al. Proteogenomic convergence for understanding cancer pathways and networks , 2014, Clinical Proteomics.
[40] W. Pao,et al. A Bioinformatics Workflow for Variant Peptide Detection in Shotgun Proteomics* , 2011, Molecular & Cellular Proteomics.
[41] Gennifer E. Merrihew,et al. Proteogenomic database construction driven from large scale RNA-seq data. , 2014, Journal of proteome research.
[42] G. Balendiran,et al. The role of glutathione in cancer , 2004, Cell biochemistry and function.
[43] Jürgen Cox,et al. 1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data , 2012, BMC Bioinformatics.
[44] A. Chiappori,et al. Current clinical application of genomic and proteomic profiling in non-small-cell lung cancer. , 2014, Cancer control : journal of the Moffitt Cancer Center.
[45] Holger Sültmann,et al. Global gene expression analysis reveals specific patterns of cell junctions in non-small cell lung cancer subtypes. , 2009, Lung cancer.
[46] Paul Taylor,et al. Integrated Omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact , 2014, Nature Communications.
[47] Pratik D Jagtap,et al. Multi-omic data analysis using Galaxy , 2015, Nature Biotechnology.
[48] E. Gratton,et al. Wnt signaling directs a metabolic program of glycolysis and angiogenesis in colon cancer , 2014, The EMBO journal.
[49] B. Kuster,et al. Mass-spectrometry-based draft of the human proteome , 2014, Nature.
[50] A. Sánchez-Palencia,et al. Differential immunohistochemical localization of desmosomal plaque‐related proteins in non‐small‐cell lung cancer , 2013, Histopathology.
[51] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[52] M. Mann,et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. , 2011, Journal of proteome research.
[53] R. Zahedi,et al. Proteomic insights into non-small cell lung cancer: New ideas for cancer diagnosis and therapy from a functional viewpoint , 2014 .
[54] M. Mann,et al. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification , 2008, Nature Biotechnology.
[55] Samuel Leung,et al. Optimal Immunohistochemical Markers For Distinguishing Lung Adenocarcinomas From Squamous Cell Carcinomas in Small Tumor Samples , 2010, The American journal of surgical pathology.
[56] Jan Budczies,et al. Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer , 2013, PloS one.
[57] J. Lehtiö,et al. Lung cancer proteomics, clinical and technological considerations. , 2010, Journal of proteomics.
[58] Michael Stuart,et al. Understanding Robust and Exploratory Data Analysis , 1984 .
[59] Mathias Wilhelm,et al. Global proteome analysis of the NCI-60 cell line panel. , 2013, Cell reports.
[60] M. Moran,et al. Primary tumor xenografts of human lung adeno and squamous cell carcinoma express distinct proteomic signatures. , 2011, Journal of proteome research.
[61] James E. Johnson,et al. Flexible and Accessible Workflows for Improved Proteogenomic Analysis Using the Galaxy Framework , 2014, Journal of proteome research.
[62] Jeffrey R. Whiteaker,et al. Proteogenomic characterization of human colon and rectal cancer , 2014, Nature.
[63] C. Sima,et al. Immunohistochemical algorithm for differentiation of lung adenocarcinoma and squamous cell carcinoma based on large series of whole-tissue sections with validation in small specimens , 2011, Modern Pathology.
[64] Y. Istefanopulos,et al. IEEE Engineering in Medicine and Biology Society , 2019, IEEE Transactions on Biomedical Engineering.
[65] David E. Misek,et al. Discordant Protein and mRNA Expression in Lung Adenocarcinomas * , 2002, Molecular & Cellular Proteomics.
[66] M. Mann,et al. The coming age of complete, accurate, and ubiquitous proteomes. , 2013, Molecular cell.
[67] Gary D Bader,et al. A draft map of the human proteome , 2014, Nature.