Dataset Information

Integrated bottom-up and top-down proteomics of patient-derived breast tumor xenografts

ABSTRACT:

Ntai, I., LeDuc, R.D., Fellers, R.T., et al., (2015) Molecular and Cellular Proteomics, Manuscript M114.047480

Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the peptide-to- protein inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels, and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0-30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in an approximately 60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding 8 times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain post-translational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available.

Dataset imported into MassIVE from https://cptac-data-portal.georgetown.edu/cptac/s/S028 on 08/28/19

INSTRUMENT(S): TripleTOF 5600, LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (ncbitaxon:9606) Mus Musculus (ncbitaxon:10090)

SUBMITTER: Neil L Kelleher

PROVIDER: MSV000084247 | MassIVE | Wed Aug 28 15:26:00 BST 2019

SECONDARY ACCESSION(S): PXD015909

REPOSITORIES: MassIVE

ACCESS DATA

Publications

Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts.

Ntai Ioanna I LeDuc Richard D RD Fellers Ryan T RT Erdmann-Gilmore Petra P Davies Sherri R SR Rumsey Jeanne J Early Bryan P BP Thomas Paul M PM Li Shunqiang S Compton Philip D PD Ellis Matthew J C MJ Ruggles Kelly V KV Fenyö David D Boja Emily S ES Rodriguez Henry H Townsend R Reid RR Kelleher Neil L NL

Molecular & cellular proteomics : MCP 20151026 1

PMID: 26503891

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Project description:Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: <a href="https://cptac-data-portal.georgetown.edu/cptacPublic/">https://cptac-data-portal.georgetown.edu/cptacPublic/</a> The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

Dataset Information

Integrated bottom-up and top-down proteomics of patient-derived breast tumor xenografts

Publications

Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts.

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