TY - JOUR
T1 - Genome wide proteomics of ERBB2 and EGFR and other oncogenic pathways in inflammatory breast cancer
AU - Zhang, Emma Yue
AU - Cristofanilli, Massimo
AU - Robertson, Fredika
AU - Reuben, James M.
AU - Mu, Zhaomei
AU - Beavis, Ronald C.
AU - Im, Hogune
AU - Snyder, Michael
AU - Hofree, Matan
AU - Ideker, Trey
AU - Omenn, Gilbert S.
AU - Fanayan, Susan
AU - Jeong, Seul Ki
AU - Paik, Young Ki
AU - Zhang, Anna Fan
AU - Wu, Shiaw Lin
AU - Hancock, William S.
PY - 2013/6/7
Y1 - 2013/6/7
N2 - In this study we selected three breast cancer cell lines (SKBR3, SUM149 and SUM190) with different oncogene expression levels involved in ERBB2 and EGFR signaling pathways as a model system for the evaluation of selective integration of subsets of transcriptomic and proteomic data. We assessed the oncogene status with reads per kilobase per million mapped reads (RPKM) values for ERBB2 (14.4, 400, and 300 for SUM149, SUM190, and SKBR3, respectively) and for EGFR (60.1, not detected, and 1.4 for the same 3 cell lines). We then used RNA-Seq data to identify those oncogenes with significant transcript levels in these cell lines (total 31) and interrogated the corresponding proteomics data sets for proteins with significant interaction values with these oncogenes. The number of observed interactors for each oncogene showed a significant range, e.g., 4.2% (JAK1) to 27.3% (MYC). The percentage is measured as a fraction of the total protein interactions in a given data set vs total interactors for that oncogene in STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 9.0) and I2D (Interologous Interaction Database, version 1.95). This approach allowed us to focus on 4 main oncogenes, ERBB2, EGFR, MYC, and GRB2, for pathway analysis. We used bioinformatics sites GeneGo, PathwayCommons and NCI receptor signaling networks to identify pathways that contained the four main oncogenes and had good coverage in the transcriptomic and proteomic data sets as well as a significant number of oncogene interactors. The four pathways identified were ERBB signaling, EGFR1 signaling, integrin outside-in signaling, and validated targets of C-MYC transcriptional activation. The greater dynamic range of the RNA-Seq values allowed the use of transcript ratios to correlate observed protein values with the relative levels of the ERBB2 and EGFR transcripts in each of the four pathways. This provided us with potential proteomic signatures for the SUM149 and 190 cell lines, growth factor receptor-bound protein 7 (GRB7), Crk-like protein (CRKL) and Catenin delta-1 (CTNND1) for ERBB signaling; caveolin 1 (CAV1), plectin (PLEC) for EGFR signaling; filamin A (FLNA) and actinin alpha1 (ACTN1) (associated with high levels of EGFR transcript) for integrin signalings; branched chain amino-acid transaminase 1 (BCAT1), carbamoyl-phosphate synthetase (CAD), nucleolin (NCL) (high levels of EGFR transcript); transferrin receptor (TFRC), metadherin (MTDH) (high levels of ERBB2 transcript) for MYC signaling; S100-A2 protein (S100A2), caveolin 1 (CAV1), Serpin B5 (SERPINB5), stratifin (SFN), PYD and CARD domain containing (PYCARD), and EPH receptor A2 (EPHA2) for PI3K signaling, p53 subpathway. Future studies of inflammatory breast cancer (IBC), from which the cell lines were derived, will be used to explore the significance of these observations.
AB - In this study we selected three breast cancer cell lines (SKBR3, SUM149 and SUM190) with different oncogene expression levels involved in ERBB2 and EGFR signaling pathways as a model system for the evaluation of selective integration of subsets of transcriptomic and proteomic data. We assessed the oncogene status with reads per kilobase per million mapped reads (RPKM) values for ERBB2 (14.4, 400, and 300 for SUM149, SUM190, and SKBR3, respectively) and for EGFR (60.1, not detected, and 1.4 for the same 3 cell lines). We then used RNA-Seq data to identify those oncogenes with significant transcript levels in these cell lines (total 31) and interrogated the corresponding proteomics data sets for proteins with significant interaction values with these oncogenes. The number of observed interactors for each oncogene showed a significant range, e.g., 4.2% (JAK1) to 27.3% (MYC). The percentage is measured as a fraction of the total protein interactions in a given data set vs total interactors for that oncogene in STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 9.0) and I2D (Interologous Interaction Database, version 1.95). This approach allowed us to focus on 4 main oncogenes, ERBB2, EGFR, MYC, and GRB2, for pathway analysis. We used bioinformatics sites GeneGo, PathwayCommons and NCI receptor signaling networks to identify pathways that contained the four main oncogenes and had good coverage in the transcriptomic and proteomic data sets as well as a significant number of oncogene interactors. The four pathways identified were ERBB signaling, EGFR1 signaling, integrin outside-in signaling, and validated targets of C-MYC transcriptional activation. The greater dynamic range of the RNA-Seq values allowed the use of transcript ratios to correlate observed protein values with the relative levels of the ERBB2 and EGFR transcripts in each of the four pathways. This provided us with potential proteomic signatures for the SUM149 and 190 cell lines, growth factor receptor-bound protein 7 (GRB7), Crk-like protein (CRKL) and Catenin delta-1 (CTNND1) for ERBB signaling; caveolin 1 (CAV1), plectin (PLEC) for EGFR signaling; filamin A (FLNA) and actinin alpha1 (ACTN1) (associated with high levels of EGFR transcript) for integrin signalings; branched chain amino-acid transaminase 1 (BCAT1), carbamoyl-phosphate synthetase (CAD), nucleolin (NCL) (high levels of EGFR transcript); transferrin receptor (TFRC), metadherin (MTDH) (high levels of ERBB2 transcript) for MYC signaling; S100-A2 protein (S100A2), caveolin 1 (CAV1), Serpin B5 (SERPINB5), stratifin (SFN), PYD and CARD domain containing (PYCARD), and EPH receptor A2 (EPHA2) for PI3K signaling, p53 subpathway. Future studies of inflammatory breast cancer (IBC), from which the cell lines were derived, will be used to explore the significance of these observations.
KW - Chromosome-centric Human Proteome Project
KW - EGFR
KW - ERBB2
KW - Inflammatory breast cancer
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U2 - 10.1021/pr4001527
DO - 10.1021/pr4001527
M3 - Article
C2 - 23647160
AN - SCOPUS:84879327240
SN - 1535-3893
VL - 12
SP - 2805
EP - 2817
JO - Journal of Proteome Research
JF - Journal of Proteome Research
IS - 6
ER -