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1.  Current affairs in quantitative targeted proteomics: multiple reaction monitoring–mass spectrometry 
Quantitative targeted proteomics has recently taken front stage in the proteomics community. Centered on multiple reaction monitoring–mass spectrometry (MRM–MS) methodologies, quantitative targeted proteomics is being used in the verification of global proteomics data, the discovery of lower abundance proteins, protein post-translational modifications, discrimination of select highly homologous protein isoforms and as the final step in biomarker discovery. An older methodology utilized with small molecule analysis, the proteomics community is making great technological strides to develop MRM–MS as the next method to address previously challenging issues in global proteomics experimentation, namely dynamic range, identification of post-translational modifications, sensitivity and selectivity of measurement which will undoubtedly further biomedical knowledge. This brief review will provide a general introduction of MRM–MS and highlight its novel application for targeted quantitative proteomic experimentations.
doi:10.1093/bfgp/eln056
PMCID: PMC2722263  PMID: 19279071
absolute quantification; quantitative proteomics; mass spectrometry; multiple reaction monitoring; stable isotope dilution; targeted proteomics
2.  Characterization of KRAS Rearrangements in Metastatic Prostate Cancer 
Cancer discovery  2011;1(1):35-43.
Using an integrative genomics approach called Amplification Breakpoint Ranking and Assembly (ABRA) analysis, we nominated KRAS as a gene fusion with the ubiquitin-conjugating enzyme UBE2L3 in the DU145 cell line, originally derived from prostate cancer metastasis to the brain. Interestingly, analysis of tissues revealed that 2 of 62 metastatic prostate cancers harbored aberrations at the KRAS locus. In DU145 cells, UBE2L3-KRAS produces a fusion protein, specific knock-down of which, attenuates cell invasion and xenograft growth. Ectopic expression of the UBE2L3-KRAS fusion protein exhibits transforming activity in NIH 3T3 fibroblasts and RWPE prostate epithelial cells in vitro and in vivo. In NIH 3T3 cells, UBE2L3-KRAS attenuates MEK/ERK signaling, commonly engaged by oncogenic mutant KRAS, and instead signals via AKT and p38 MAPK pathways. This is the first report of a gene fusion involving Ras family suggesting that this aberration may drive metastatic progression in a rare subset of prostate cancers.
doi:10.1158/2159-8274.CD-10-0022
PMCID: PMC3227139  PMID: 22140652
KRAS; gene fusion; prostate cancer; genomic amplification; bioinformatics
3.  Mechanistic Rationale for Inhibition of Poly(ADP-Ribose) Polymerase in ETS Gene Fusion-Positive Prostate Cancer 
Cancer cell  2011;19(5):664-678.
Summary
Recurrent fusions of ETS genes are considered driving mutations in a diverse array of cancers, including Ewing’s sarcoma, acute myeloid leukemia, and prostate cancer. We investigate the mechanisms by which ETS fusions mediate their effects, and find that the product of the predominant ETS gene fusion, TMPRSS2:ERG, interacts in a DNA-independent manner with the enzyme poly(ADP-ribose) polymerase 1 (PARP1) and the catalytic subunit of DNA protein kinase (DNA-PKcs). ETS gene-mediated transcription and cell invasion require PARP1 and DNA-PKcs expression and activity. Importantly, pharmacological inhibition of PARP1 inhibits ETS positive, but not ETS negative, prostate cancer xenograft growth. Finally, overexpression of the TMPRSS2:ERG fusion induces DNA damage, which is potentiated by PARP1 inhibition in a manner similar to that of BRCA1/2-deficiency.
doi:10.1016/j.ccr.2011.04.010
PMCID: PMC3113473  PMID: 21575865
Prostate; Rearrangement; Gene Fusion; TMPRSS2; ERG; DNA-PKcs; PARP1
4.  Abacus: A computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis 
Proteomics  2011;11(7):1340-1345.
We describe Abacus, a computational tool for extracting spectral counts from tandem mass spectrometry based proteomic datasets. The program aggregates data from multiple experiments, adjusts spectral counts to accurately account for peptides shared across multiple proteins, and performs common normalization steps. It can also output the spectral count data at the gene level, thus simplifying the integration and comparison between gene and protein expression data. Abacus is compatible with the widely used Trans-Proteomic Pipeline suite of tools and comes with a graphical user interface making it easy to interact with the program. The main aim of Abacus is to streamline the analysis of spectral count data by providing an automated, easy to use solution for extracting this information from proteomic datasets for subsequent, more sophisticated statistical analysis.
doi:10.1002/pmic.201000650
PMCID: PMC3113614  PMID: 21360675
Label free quantification; spectral counts; software; tandem mass spectrometry; protein inference; shared peptides
5.  Alternative Splice Variants, a New Class of Protein Cancer Biomarker Candidates: Findings in Pancreatic Cancer and Breast Cancer with Systems Biology Implications 
Disease markers  2010;28(4):241-251.
Alternative splicing plays an important role in protein diversity without increasing genome size. Earlier thought to be uncommon, splicing appears to affect the majority of genes. Alternative splice variants have been detected at the mRNA level in many diseases. We have designed and demonstrated a discovery pipeline for alternative splice variant (ASV) proteins from tandem MS/MS datasets. We created a modified ECgene database with entries from exhaustive three-frame translation of Ensembl transcripts and gene models from ECgene, with periodic updates. The human database has 14 million entries; the mouse database, 10 million entries. We match MS/MS findings against these potential translation products to identify and quantify known and novel ASVs. In this review, we summarize findings and systems biology implications of biomarker candidates from a mouse model of human pancreatic ductal adenocarcinoma [28] and a mouse model of human Her2/neu-induced breast cancer [27]. The same approach is being applied to human tumors, plasma, and cell line studies of other cancers.
doi:10.3233/DMA-2010-0702
PMCID: PMC3833236  PMID: 20534909
Alternative splicing; splice variants; protein isoforms; breast cancer; pancreatic cancer; mouse models; proteomics; protein interaction networks; systems biology
6.  Comparison of MS2-only, MSA, and MS2/MS3 Methodologies for Phosphopeptide Identification 
Journal of proteome research  2009;8(2):887-899.
Current mass spectrometers provide a number of alternative methodologies for producing tandem mass spectra specifically for phosphopeptide analysis. In particular, generation of MS3 spectra in a data-dependent manner upon detection of the neutral loss of a phosphoric acid in MS2 spectra is a popular technique for circumventing the problem of poor phosphopeptide backbone fragmentation. The newer Multistage Activation method provides another option. Both these strategies require additional cycle time on the instrument and therefore reduce the number of spectra that can be measured in the same amount of time. Additional informatics is often required to make most efficient use of the additional information provided by these spectra as well. This work presents a comparison of several commonly used mass spectrometry methods for the study of phosphopeptide-enriched samples: an MS2-only method, a Multistage Activation method, and an MS2/MS3 data-dependent neutral loss method. Several strategies for dealing effectively with the resulting MS3 data in the latter approach are also presented and compared. The overall goal is to infer whether any one methodology performs significantly better than another for identifying phosphopeptides. On data presented here, the Multistage Activation methodology is demonstrated to perform optimally and does not result in significant loss of unique peptide identifications.
doi:10.1021/pr800535h
PMCID: PMC2734953  PMID: 19072539
Protein phosphorylation; mass spectrometry; MS3; Multistage Activation; phosphoproteomics; bioinformatics; peptide identification; database search

Results 1-6 (6)