Proteome and transcriptome profiles of a Her2/Neu‐driven mouse model of breast cancer

Publisher Website
Google Scholar
Abstract
Purpose : We generated extensive transcriptional and proteomic profiles from a Her2‐driven mouse model of breast cancer that closely recapitulates human breast cancer. This report makes these data publicly available in raw and processed forms, as a resource to the community. Importantly, we previously made biospecimens from this same mouse model freely available through a sample repository, so researchers can obtain samples to test biological hypotheses without the need of breeding animals and collecting biospecimens. Experimental design : Twelve datasets are available, encompassing 841 LC‐MS/MS experiments (plasma and tissues) and 255 microarray analyses of multiple tissues (thymus, spleen, liver, blood cells, and breast). Cases and controls were rigorously paired to avoid bias. Results : In total, 18 880 unique peptides were identified (PeptideProphet peptide error rate ≤1%), with 3884 and 1659 non‐redundant protein groups identified in plasma and tissue datasets, respectively. Sixty‐one of these protein groups overlapped between cancer plasma and cancer tissue. Conclusions and clinical relevance : These data are of use for advancing our understanding of cancer biology, for software and quality control tool development, investigations of analytical variation in MS/MS data, and selection of proteotypic peptides for multiple reaction monitoring‐MS. The availability of these datasets will contribute positively to clinical proteomics.
Funding Information
  • NCI/SAIC (23XS144A)
  • The Paul G. Allen Family Foundation
  • Entertainment Industry Foundation
  • EIF Women's Cancer Research Fund
  • Keck Foundation and the Canary Foundation
  • NIH National Center for Research Resources (RR018522)
  • Environmental Molecular Science Laboratory
  • Pacific Northwest National Laboratory
  • Battelle Memorial Institute for the DOE (DE-AC05-76RLO-1830)