In Situ Proteomic Analysis of Human Breast Cancer Epithelial Cells Using Laser Capture Microdissection: Annotation by Protein Set Enrichment Analysis and Gene Ontology

Identification of molecular signatures that allow detection of the transition from normal breast epithelial cells to malignant invasive cells is a critical component in the development of diagnostic, therapeutic, and preventative strategies for human breast cancer. Substantial efforts have been devoted to deciphering breast cancer etiology at the genome level, but only a limited number of studies have appeared at the proteome level. In this work, we compared individual in situ proteome profiles of nonpatient matched nine noncancerous, normal breast epithelial (NBE) samples with nine estrogen receptor (ER)-positive (luminal subtype), invasive malignant breast epithelial (MBE) samples by combining laser capture microdissection (LCM) and quantitative shotgun proteomics. A total of 12,970 unique peptides were identified from the 18 samples, and 1623 proteins were selected for quantitative analysis using spectral index (SpI) as a measure of protein abundance. A total of 298 proteins were differentially expressed between NBE and MBE at 95% confidence level, and this differential expression correlated well with immunohistochemistry (IHC) results reported in the Human Protein Atlas (HPA) database. To assess pathway level patterns in the observed expression changes, we developed protein set enrichment analysis (PSEA), a modification of a well-known approach in gene expression analysis, Gene Set Enrichment Analysis (GSEA). Unlike single gene-based functional term enrichment analyses that only examines pathway overrepresentation of proteins above a given significance threshold, PSEA applies a weighted running sum statistic to the entire expression data to discover significantly enriched protein groups. Application of PSEA to the expression data in this study revealed not only well-known ER-dependent and cellular morphology-dependent protein abundance changes, but also significant alterations of downstream targets for multiple transcription factors (TFs), suggesting a role for specific gene regulatory pathways in breast tumorigenesis. A parallel GOMiner analysis revealed both confirmatory and complementary data to PSEA. The combination of the two annotation approaches yielded extensive biological feature mapping for in depth analysis of the quantitative proteomic data. Identification of molecular signatures that allow detection of the transition from normal breast epithelial cells to malignant invasive cells is a critical component in the development of diagnostic, therapeutic, and preventative strategies for human breast cancer. Substantial efforts have been devoted to deciphering breast cancer etiology at the genome level, but only a limited number of studies have appeared at the proteome level. In this work, we compared individual in situ proteome profiles of nonpatient matched nine noncancerous, normal breast epithelial (NBE) samples with nine estrogen receptor (ER)-positive (luminal subtype), invasive malignant breast epithelial (MBE) samples by combining laser capture microdissection (LCM) and quantitative shotgun proteomics. A total of 12,970 unique peptides were identified from the 18 samples, and 1623 proteins were selected for quantitative analysis using spectral index (SpI) as a measure of protein abundance. A total of 298 proteins were differentially expressed between NBE and MBE at 95% confidence level, and this differential expression correlated well with immunohistochemistry (IHC) results reported in the Human Protein Atlas (HPA) database. To assess pathway level patterns in the observed expression changes, we developed protein set enrichment analysis (PSEA), a modification of a well-known approach in gene expression analysis, Gene Set Enrichment Analysis (GSEA). Unlike single gene-based functional term enrichment analyses that only examines pathway overrepresentation of proteins above a given significance threshold, PSEA applies a weighted running sum statistic to the entire expression data to discover significantly enriched protein groups. Application of PSEA to the expression data in this study revealed not only well-known ER-dependent and cellular morphology-dependent protein abundance changes, but also significant alterations of downstream targets for multiple transcription factors (TFs), suggesting a role for specific gene regulatory pathways in breast tumorigenesis. A parallel GOMiner analysis revealed both confirmatory and complementary data to PSEA. The combination of the two annotation approaches yielded extensive biological feature mapping for in depth analysis of the quantitative proteomic data. Breast cancer is a major health problem that each year affects the lives of millions of women worldwide. In 2008, in the United States alone, ∼180,000 women were diagnosed with invasive breast carcinoma (1Jemal A. Siegel R. Ward E. Hao Y. Xu J. Murray T. Thun M.J. Cancer statistics, 2008.CA-Cancer J. Clin. 2008; 58: 71-96Crossref PubMed Scopus (10172) Google Scholar). The use of high-throughput gene expression technologies applied to the study of human breast cancer has lead to the discovery of the “intrinsic gene signatures” that stratify human breast cancers into four subtypes that correlate remarkably well with clinically recognized breast cancer subtypes (2Sotiriou C. Wirapati P. Loi S. Harris A. Fox S. Smeds J. Nordgren H. Farmer P. Praz V. Haibe-Kains B. Desmedt C. Larsimont D. Cardoso F. Peterse H. Nuyten D. Buyse M. Van de Vijver M.J. Bergh J. Piccart M. Delorenzi M. Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis.J. Natl. Cancer Inst. 2006; 98: 262-272Crossref PubMed Scopus (1534) Google Scholar, 3Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Lønning P. Eystein Børresen-Dale A.L. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.Proc. Natl. Acad. Sci. U.S.A. 2001; 98: 10869-10874Crossref PubMed Scopus (8426) Google Scholar, 4van't Veer L.J. Dai H. van de Vijver M.J. He Y.D. Hart A.A. Mao M. Peterse H.L. van der Kooy K. Marton M.J. Witteveen A.T. Schreiber G.J. Kerkhoven R.M. Roberts C. Linsley P.S. Bernards R. Friend S.H. Gene expression profiling predicts clinical outcome of breast cancer.Nature. 2002; 415: 530-536Crossref PubMed Scopus (7697) Google Scholar, 5Ma X.J. Wang Z. Ryan P.D. Isakoff S.J. Barmettler A. Fuller A. Muir B. Mohapatra G. Salunga R. Tuggle J.T. Tran Y. Tran D. Tassin A. Amon P. Wang W. Enright E. Stecker K. Estepa-Sabal E. Smith B. Younger J. Balis U. Michaelson J. Bhan A. Habin K. Baer T.M. Brugge J. Haber D.A. Erlander M.G. Sgroi D.C. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen.Cancer Cell. 2004; 5: 607-616Abstract Full Text Full Text PDF PubMed Scopus (789) Google Scholar, 6Perou C.M. Sørlie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Rees C.A. Pollack J.R. Ross D.T. Johnsen H. Akslen L.A. Fluge O. Pergamenschikov A. Williams C. Zhu S.X. Lønning P.E. Børresen-Dale A.L. Brown P.O. Botstein D. Molecular portraits of human breast tumours.Nature. 2000; 406: 747-752Crossref PubMed Scopus (11499) Google Scholar). These subtypes include “HER2+,” “basal,” and “luminal A,” “luminal B” breast cancers. HER2+ tumors are most frequently estrogen receptor (ER)- 1The abbreviations used are:ERestrogen receptorEREestrogen response set enrichment Protein capture breast molecular signatures breast set enrichment sum discovery response protein regulatory protein 1The abbreviations used are:ERestrogen receptorEREestrogen response set enrichment Protein capture breast molecular signatures breast set enrichment sum discovery response protein regulatory protein as well as and to this The tumors are most receptor and The A and tumors the estrogen receptor and transcription breast cancers A and of human breast cancers diagnosed worldwide. In the breast cancers are with as compared with the HER2+ and tumors have a A and data that A tumors treated with alone, tumors from to L.A. A.A. C. Molecular and molecular of breast cancer: for clinical Clin. PubMed Scopus Google Scholar). in the gene of human breast the molecular basis of breast and breast cancer clinical is in is in to the well-known with gene for is the gene the and not the that are the of and of the proteomic alterations with breast cancer of human breast cancer and in breast cancer the has been to study the breast cancer proteome to the molecular of breast cancer that from breast cancer gene expression data H. Breast cancer biological Cell. Full Text Full Text PDF PubMed Scopus Google Scholar, S. S. of breast B. PubMed Scopus Google Scholar, F. D. A. of breast cancer and clinical Cell. 2006; 5: Full Text Full Text PDF PubMed Scopus Google Scholar). proteomic analyses of tumor human breast and cancer and and for of protein expression in breast cancer H. C. of breast cancer: The for and 2008; PubMed Scopus Google Scholar, V. breast cancer discovery J. 2008; PubMed Scopus Google Scholar). is to the most proteomic analysis is the the tumor analysis is given the of the breast cancer and the limited number of cells enriched from samples by laser capture microdissection (LCM) Smith P.D. Z. L.A. PubMed Scopus Google Scholar, V. A. W. G. L.A. 2006; PubMed Scopus Google Scholar). analysis lead to proteomic portraits of tumor for of X.J. S. E. Erlander M. Sgroi D.C. Gene expression profiling of the tumor breast cancer Cancer PubMed Scopus Google Scholar). analyses are in the of gene expression proteomic analyses of breast are limited Sgroi D.C. H. K. K. M. S. H. A. R. D. M.J. Y. P.S. of human breast carcinoma in 2002; Google Scholar, D. Sgroi D.C. analysis of carcinoma of the breast using laser capture and 2004; PubMed Scopus Google Scholar, H. R. T. D. K. A. W. S. C. C. W. A. Breast cancer by laser capture and differential 2006; PubMed Scopus Google Scholar, A. T.M. proteome for to breast carcinoma PubMed Scopus Google Scholar, Xu D. H. J. M. R.M. proteomic in breast cancer by laser capture microdissection and 2008; PubMed Scopus Google Scholar, J. S. D.A. J.C. M. J. a by and PubMed Scopus Google Scholar). tumor at the protein level by breast tumor and cells from a breast carcinoma J. S. D.A. J.C. M. J. a by and PubMed Scopus Google and differential proteome profiles to were from tumor samples A. H. T.M. Identification of a Protein with in Breast Cell. Full Text Full Text PDF PubMed Scopus Google combination of enrichment and shotgun has the to pathways and by normal breast epithelial cells to invasive malignant epithelial and gene expression profiling of human breast cancer has for the of molecular alterations that as and (2Sotiriou C. Wirapati P. Loi S. Harris A. Fox S. Smeds J. Nordgren H. Farmer P. Praz V. Haibe-Kains B. Desmedt C. Larsimont D. Cardoso F. Peterse H. Nuyten D. Buyse M. Van de Vijver M.J. Bergh J. Piccart M. Delorenzi M. Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis.J. Natl. Cancer Inst. 2006; 98: 262-272Crossref PubMed Scopus (1534) Google Scholar, 3Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Lønning P. Eystein Børresen-Dale A.L. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.Proc. Natl. Acad. Sci. U.S.A. 2001; 98: 10869-10874Crossref PubMed Scopus (8426) Google Scholar, 4van't Veer L.J. Dai H. van de Vijver M.J. He Y.D. Hart A.A. Mao M. Peterse H.L. van der Kooy K. Marton M.J. Witteveen A.T. Schreiber G.J. Kerkhoven R.M. Roberts C. Linsley P.S. Bernards R. Friend S.H. Gene expression profiling predicts clinical outcome of breast cancer.Nature. 2002; 415: 530-536Crossref PubMed Scopus (7697) Google Scholar, K. S. J. R. A. R.M. Z. T. F. H. T. C. S. Z. K. D. A. and to breast cancer Cell. 2006; Full Text Full Text PDF PubMed Scopus Google Scholar). of proteomic patterns in normal as compared with malignant breast in a of the molecular with breast cancer the we proteomic profiling of laser capture normal breast (NBE) from nine human to malignant breast (MBE) from nine human invasive breast cancer only the limited of by a proteomic of each by using developed for analysis of samples Y. L.J. J. analysis of cells from using laser capture microdissection and PubMed Scopus Google Scholar). To the of this is the most study that proteomic signatures of normal and invasive malignant breast epithelial cells in multiple individual each the spectral index (SpI) P.S. D.A. T. index for of differential protein expression in shotgun 2008; PubMed Scopus Google used as a measure of with differentially proteins between NBE and MBE identified by a number of proteins enriched in both well-known and proteins in the of breast were to profiles of normal and in the Human Protein Atlas (HPA) E. P. A. C.A. A. J. H. P. E. A. S. K. C. S. F. M. A human protein for expression profiles Cell. 2008; Full Text Full Text PDF PubMed Scopus Google in expression profiling studies is to the number of observed molecular approaches GOMiner have been used in the analysis of proteomic profiling studies G. D.A. J. W. for and Google Scholar, H. S. M. H. M. R.M. D. E. C. D. gene for of with to studies of PubMed Scopus Google Scholar). approaches quantitative for proteins to and the level of expression enriched functional Gene set enrichment analysis developed in the gene expression as a approach for functional significance of differential expression results by into the quantitative of expression A. P. S. A. Gene set enrichment A approach for expression Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar). has been to proteome to functional in D. analysis of using proteomic profiling and enrichment the we to for the analysis of quantitative proteomic data in approach Protein Set Enrichment Analysis PSEA into the quantitative level of differential protein expression by spectral to proteins with and expression PSEA of MBE samples revealed significant expression of proteins and of proteins that are correlated with human breast cancers. protein proteins by transcription factors were suggesting a role of estrogen response in breast tumorigenesis. In we a GOMiner analysis, for differentially the proteomic differentially expressed proteins at the 95% confidence level, GOMiner analysis unique biological as of in PSEA with the results of GOMiner analysis, we are to and targets for proteomic analysis of breast using a combination of and shotgun proteomics. To this is the most study proteome signatures from of normal and invasive malignant breast The of this study of each a measure of biological proteomic profiles 18 samples were using a shotgun biological for each to a between the significance and for proteins were to correlate well with profiles in the Human Protein that results not to breast cancer samples, but to breast cancer given the of breast cancer samples in the in multiple protein to breast epithelial were by annotation that the quantitative profiles of identified proteins with PSEA of breast not only confirmatory biological but also revealed significant of downstream targets for a number of transcription that a pathway in breast cancer GOMiner analysis with 298 differentially proteins at above the 95% confidence level complementary results to and the combination of the two approaches revealed extensive into the molecular in is to quantitative proteome and the of PSEA of proteome in biological PSEA using the as biological that are from by of differentially proteins with PSEA biological targets and studies include analysis between a reported X.J. Salunga R. Tuggle J.T. J. Enright E. P. T. M. Stecker K. H. Smith B. M. E. J. Baer T.M. Erlander M.G. Sgroi D.C. Gene expression profiles of human breast cancer Natl. Acad. Sci. U.S.A. PubMed Scopus Google and proteome lead to significant protein and into the of breast cancer In proteome profiles of normal in and breast from the normal in to breast carcinoma has been to G. Y. G. Smith of in to Breast PubMed Scopus Google Scholar). of the molecular between and malignant breast Breast cancer is a major health problem that each year affects the lives of millions of women worldwide. In 2008, in the United States alone, ∼180,000 women were diagnosed with invasive breast carcinoma (1Jemal A. Siegel R. Ward E. Hao Y. Xu J. Murray T. Thun M.J. Cancer statistics, 2008.CA-Cancer J. Clin. 2008; 58: 71-96Crossref PubMed Scopus (10172) Google Scholar). The use of high-throughput gene expression technologies applied to the study of human breast cancer has lead to the discovery of the “intrinsic gene signatures” that stratify human breast cancers into four subtypes that correlate remarkably well with clinically recognized breast cancer subtypes (2Sotiriou C. Wirapati P. Loi S. Harris A. Fox S. Smeds J. Nordgren H. Farmer P. Praz V. Haibe-Kains B. Desmedt C. Larsimont D. Cardoso F. Peterse H. Nuyten D. Buyse M. Van de Vijver M.J. Bergh J. Piccart M. Delorenzi M. Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis.J. Natl. Cancer Inst. 2006; 98: 262-272Crossref PubMed Scopus (1534) Google Scholar, 3Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Lønning P. Eystein Børresen-Dale A.L. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.Proc. Natl. Acad. Sci. U.S.A. 2001; 98: 10869-10874Crossref PubMed Scopus (8426) Google Scholar, 4van't Veer L.J. Dai H. van de Vijver M.J. He Y.D. Hart A.A. Mao M. Peterse H.L. van der Kooy K. Marton M.J. Witteveen A.T. Schreiber G.J. Kerkhoven R.M. Roberts C. Linsley P.S. Bernards R. Friend S.H. Gene expression profiling predicts clinical outcome of breast cancer.Nature. 2002; 415: 530-536Crossref PubMed Scopus (7697) Google Scholar, 5Ma X.J. Wang Z. Ryan P.D. Isakoff S.J. Barmettler A. Fuller A. Muir B. Mohapatra G. Salunga R. Tuggle J.T. Tran Y. Tran D. Tassin A. Amon P. Wang W. Enright E. Stecker K. Estepa-Sabal E. Smith B. Younger J. Balis U. Michaelson J. Bhan A. Habin K. Baer T.M. Brugge J. Haber D.A. Erlander M.G. Sgroi D.C. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen.Cancer Cell. 2004; 5: 607-616Abstract Full Text Full Text PDF PubMed Scopus (789) Google Scholar, 6Perou C.M. Sørlie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Rees C.A. Pollack J.R. Ross D.T. Johnsen H. Akslen L.A. Fluge O. Pergamenschikov A. Williams C. Zhu S.X. Lønning P.E. Børresen-Dale A.L. Brown P.O. Botstein D. Molecular portraits of human breast tumours.Nature. 2000; 406: 747-752Crossref PubMed Scopus (11499) Google Scholar). These subtypes include “HER2+,” “basal,” and “luminal A,” “luminal B” breast cancers. HER2+ tumors are most frequently estrogen receptor (ER)- 1The abbreviations used are:ERestrogen receptorEREestrogen response set enrichment Protein capture breast molecular signatures breast set enrichment sum discovery response protein regulatory protein 1The abbreviations used are:ERestrogen receptorEREestrogen response set enrichment Protein capture breast molecular signatures breast set enrichment sum discovery response protein regulatory protein as well as and to this The tumors are most receptor and The A and tumors the estrogen receptor and transcription estrogen receptor estrogen response enrichment gene gene set enrichment analysis Human Protein Atlas immunohistochemistry laser capture microdissection malignant breast the molecular signatures normal breast protein set enrichment analysis running sum statistic spectral index transcription discovery response protein regulatory protein estrogen receptor estrogen response enrichment gene gene set enrichment analysis Human Protein Atlas immunohistochemistry laser capture microdissection malignant breast the molecular signatures normal breast protein set enrichment analysis running sum statistic spectral index transcription discovery response protein regulatory protein The breast cancers A and of human breast cancers diagnosed worldwide. In the breast cancers are with as compared with the HER2+ and tumors have a A and data that A tumors treated with alone, tumors from to L.A. A.A. C. Molecular and molecular of breast cancer: for clinical Clin. PubMed Scopus Google Scholar). in the gene of human breast the molecular basis of breast and breast cancer clinical is in is in to the well-known with gene for is the gene the and not the that are the of and of the proteomic alterations with breast cancer of human breast cancer and in breast cancer the has been to study the breast cancer proteome to the molecular of breast cancer that from breast cancer gene expression data H. Breast cancer biological Cell. Full Text Full Text PDF PubMed Scopus Google Scholar, S. S. of breast B. PubMed Scopus Google Scholar, F. D. A. of breast cancer and clinical Cell. 2006; 5: Full Text Full Text PDF PubMed Scopus Google Scholar). proteomic analyses of tumor human breast and cancer and and for of protein expression in breast cancer H. C. of breast cancer: The for and 2008; PubMed Scopus Google Scholar, V. breast cancer discovery J. 2008; PubMed Scopus Google Scholar). is to the most proteomic analysis is the the tumor analysis is given the of the breast cancer and the limited number of cells enriched from samples by laser capture microdissection (LCM) Smith P.D. Z. L.A. PubMed Scopus Google Scholar, V. A. W. G. L.A. 2006; PubMed Scopus Google Scholar). analysis lead to proteomic portraits of tumor for of X.J. S. E. Erlander M. Sgroi D.C. Gene expression profiling of the tumor breast cancer Cancer PubMed Scopus Google Scholar). analyses are in the of gene expression proteomic analyses of breast are limited Sgroi D.C. H. K. K. M. S. H. A. R. D. M.J. Y. P.S. of human breast carcinoma in 2002; Google Scholar, D. Sgroi D.C. analysis of carcinoma of the breast using laser capture and 2004; PubMed Scopus Google Scholar, H. R. T. D. K. A. W. S. C. C. W. A. Breast cancer by laser capture and differential 2006; PubMed Scopus Google Scholar, A. T.M. proteome for to breast carcinoma PubMed Scopus Google Scholar, Xu D. H. J. M. R.M. proteomic in breast cancer by laser capture microdissection and 2008; PubMed Scopus Google Scholar, J. S. D.A. J.C. M. J. a by and PubMed Scopus Google Scholar). tumor at the protein level by breast tumor and cells from a breast carcinoma J. S. D.A. J.C. M. J. a by and PubMed Scopus Google and differential proteome profiles to were from tumor samples A. H. T.M. Identification of a Protein with in Breast Cell. Full Text Full Text PDF PubMed Scopus Google Scholar). The combination of enrichment and shotgun has the to pathways and by normal breast epithelial cells to invasive malignant epithelial and gene expression profiling of human breast cancer has for the of molecular alterations that as and (2Sotiriou C. Wirapati P. Loi S. Harris A. Fox S. Smeds J. Nordgren H. Farmer P. Praz V. Haibe-Kains B. Desmedt C. Larsimont D. Cardoso F. Peterse H. Nuyten D. Buyse M. Van de Vijver M.J. Bergh J. Piccart M. Delorenzi M. Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis.J. Natl. Cancer Inst. 2006; 98: 262-272Crossref PubMed Scopus (1534) Google Scholar, 3Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Lønning P. Eystein Børresen-Dale A.L. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.Proc. Natl. Acad. Sci. U.S.A. 2001; 98: 10869-10874Crossref PubMed Scopus (8426) Google Scholar, 4van't Veer L.J. Dai H. van de Vijver M.J. He Y.D. Hart A.A. Mao M. Peterse H.L. van der Kooy K. Marton M.J. Witteveen A.T. Schreiber G.J. Kerkhoven R.M. Roberts C. Linsley P.S. Bernards R. Friend S.H. Gene expression profiling predicts clinical outcome of breast cancer.Nature. 2002; 415: 530-536Crossref PubMed Scopus (7697) Google Scholar, K. S. J. R. A. R.M. Z. T. F. H. T. C. S. Z. K. D. A. and to breast cancer Cell. 2006; Full Text Full Text PDF PubMed Scopus Google Scholar). of proteomic patterns in normal as compared with malignant breast in a of the molecular with breast cancer In the we proteomic profiling of laser capture normal breast (NBE) from nine human to malignant breast (MBE) from nine human invasive breast cancer only the limited of by a proteomic of each by using developed for analysis of samples Y. L.J. J. analysis of cells from using laser capture microdissection and PubMed Scopus Google Scholar). To the of this is the most study that proteomic signatures of normal and invasive malignant breast epithelial cells in multiple individual each the spectral index (SpI) P.S. D.A. T. index for of differential protein expression in shotgun 2008; PubMed Scopus Google used as a measure of with differentially proteins between NBE and MBE identified by a number of proteins enriched in both well-known and proteins in the of breast were to profiles of normal and in the Human Protein Atlas (HPA) E. P. A. C.A. A. J. H. P. E. A. S. K. C. S. F. M. A human protein for expression profiles Cell. 2008; Full Text Full Text PDF PubMed Scopus Google Scholar). A in expression profiling studies is to the number of observed molecular approaches GOMiner have been used in the analysis of proteomic profiling studies G. D.A. J. W. for and Google Scholar, H. S. M. H. M. R.M. D. E. C. D. gene for of with to studies of PubMed Scopus Google Scholar). approaches quantitative for proteins to and the level of expression enriched functional Gene set enrichment analysis developed in the gene expression as a approach for functional significance of differential expression results by into the quantitative of expression A. P. S. A. Gene set enrichment A approach for expression Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar). has been to proteome to functional in D. analysis of using proteomic profiling and enrichment Scholar). In the we to for the analysis of quantitative proteomic data in approach Protein Set Enrichment Analysis PSEA into the quantitative level of differential protein expression by spectral to proteins with and expression PSEA of MBE samples revealed significant expression of proteins and of proteins that are correlated with human breast cancers. protein proteins by transcription factors were suggesting a role of estrogen response in breast tumorigenesis. In we a GOMiner analysis, for differentially the proteomic differentially expressed proteins at the 95% confidence level, GOMiner analysis unique biological as of in PSEA with the results of GOMiner analysis, we are to and targets for proteomic analysis of breast using a combination of and shotgun proteomics. To this is the most study proteome signatures from of normal and invasive malignant breast The of this study of each a measure of biological proteomic profiles 18 samples were using a shotgun biological for each to a between the significance and for proteins were to correlate well with profiles in the Human Protein that results not to breast cancer samples, but to breast cancer given the of breast cancer samples in the in multiple protein to breast epithelial were by annotation that the quantitative profiles of identified proteins with PSEA of breast not only confirmatory biological but also revealed significant of downstream targets for a number of transcription that a pathway in breast cancer GOMiner analysis with 298 differentially proteins at above the 95% confidence level complementary results to and the combination of the two approaches revealed extensive into the molecular in is to quantitative proteome and the of PSEA of proteome in biological PSEA using the as biological that are from by of differentially proteins with PSEA biological targets and studies include analysis between a reported X.J. Salunga R. Tuggle J.T. J. Enright E. P. T. M. Stecker K. H. Smith B. M. E. J. Baer T.M. Erlander M.G. Sgroi D.C. Gene expression profiles of human breast cancer Natl. Acad. Sci. U.S.A. PubMed Scopus Google and proteome lead to significant protein and into the of breast cancer In proteome profiles of normal in and breast from the normal in to breast carcinoma has been to G. Y. G. Smith of in to Breast PubMed Scopus Google Scholar). of the molecular between and malignant breast proteomic analysis of breast using a combination of and shotgun proteomics. To this is the most study proteome signatures from of normal and invasive malignant breast The of this study of each a measure of biological proteomic profiles 18 samples were using a shotgun biological for each to a between the significance and for