10.1021/pr4001527.s002
Emma Yue Zhang
Emma Yue
Zhang
Massimo Cristofanilli
Massimo
Cristofanilli
Fredika Robertson
Fredika
Robertson
James
M. Reuben
James
M.
Reuben
Zhaomei Mu
Zhaomei
Mu
Ronald C. Beavis
Ronald C.
Beavis
Hogune Im
Hogune
Im
Michael Snyder
Michael
Snyder
Matan Hofree
Matan
Hofree
Trey Ideker
Trey
Ideker
Gilbert S. Omenn
Gilbert S.
Omenn
Susan Fanayan
Susan
Fanayan
Seul-Ki Jeong
Seul-Ki
Jeong
Young-ki Paik
Young-ki
Paik
Anna
Fan Zhang
Anna
Fan
Zhang
Shiaw-Lin Wu
Shiaw-Lin
Wu
William S. Hancock
William S.
Hancock
Genome Wide Proteomics of ERBB2 and EGFR and Other
Oncogenic Pathways in Inflammatory Breast Cancer
American Chemical Society
2013
bioinformatics sites GeneGo
CRKL
p 53 subpathway
EPH
proteomic data sets
190 cell lines
PYCARD
MYC
2D
JAK
genome Wide Proteomics
ACTN
PYD
cell lines
3K
MTDH
SFN
oncogene expression levels
PI
Interologous Interaction Database
CTNND
GRB
NCL
ERBB 2
PLEC
Other Oncogenic Pathways
SUM
proteomics data sets
RPKM
SKBR
breast cancer cell lines
SERPINB
CAV
EPHA
IBC
EGFR
S 100A caveolin 1
protein
CAD
TFRC
NCI
ERBB 2 transcript
Inflammatory Breast CancerIn
FLNA
BCAT
3 cell lines
2013-06-07 00:00:00
Dataset
https://acs.figshare.com/articles/dataset/Genome_Wide_Proteomics_of_ERBB2_and_EGFR_and_Other_Oncogenic_Pathways_in_Inflammatory_Breast_Cancer/2408779
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.