Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts.
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 a ∼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 eight times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational 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.
From the ‡Proteomics Center of Excellence, §Department of Chemistry, and.
Ioanna
I
Ntai
From the ‡Proteomics Center of Excellence.
Richard D
RD
LeDuc
From the ‡Proteomics Center of Excellence.
Ryan T
RT
Fellers
‖Department of Internal Medicine, Washington University School of Medicine, St Louis, MO 63110;
Petra
P
Erdmann-Gilmore
‖Department of Internal Medicine, Washington University School of Medicine, St Louis, MO 63110;
Sherri R
SR
Davies
‖Department of Internal Medicine, Washington University School of Medicine, St Louis, MO 63110;
Jeanne
J
Rumsey
From the ‡Proteomics Center of Excellence.
Bryan P
BP
Early
From the ‡Proteomics Center of Excellence, ¶Department of Molecular BiosciencesNorthwestern University, Evanston, IL 60208;
Paul M
PM
Thomas
‖Department of Internal Medicine, Washington University School of Medicine, St Louis, MO 63110;
Shunqiang
S
Li
From the ‡Proteomics Center of Excellence, ‖Department of Internal Medicine, Washington University School of Medicine, St Louis, MO 63110;
Philip D
PD
Compton
**Department of Molecular & Cellular Biology, Baylor College of Medicine, Houston, TX 77030;
Matthew J C
MJ
Ellis
‡‡Center for Health Informatics and Bioinformatics, and Department of Biochemistry and Molecular Pharmacology, New York University Medical School, New York, NY 10016;
Kelly V
KV
Ruggles
‡‡Center for Health Informatics and Bioinformatics, and Department of Biochemistry and Molecular Pharmacology, New York University Medical School, New York, NY 10016;
David
D
Fenyö
§§Office of Cancer Clinical Proteomics Research, National Cancer Institute, Bethesda, MD 20892.
Emily S
ES
Boja
§§Office of Cancer Clinical Proteomics Research, National Cancer Institute, Bethesda, MD 20892.
Henry
H
Rodriguez
‖Department of Internal Medicine, Washington University School of Medicine, St Louis, MO 63110; rtownsend@wustl.edu n-kelleher@northwestern.edu.
R Reid
RR
Townsend
From the ‡Proteomics Center of Excellence, §Department of Chemistry, and ¶Department of Molecular BiosciencesNorthwestern University, Evanston, IL 60208; rtownsend@wustl.edu n-kelleher@northwestern.edu.
Neil L
NL
Kelleher
D000818:Animals; D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism*; D002851:Chromatography, High Pressure Liquid; D005260:Female; D005838:Genotype; D064593:Heterografts / Q000378:metabolism*; D006801:Humans; D051379:Mice; D008970:Molecular Weight; D010455:Peptides / Q000235:genetics / Q000378:metabolism; D020641:Polymorphism, Single Nucleotide; D020543:Proteome / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*; D053719:Tandem Mass Spectrometry; D014183:Transplantation, Heterologous
D010455:Peptides; D020543:Proteome