The plasma peptides of breast versus ovarian cancer.

BACKGROUND: There is a need to demonstrate a proof of principle that proteomics has the capacity to analyze plasma from breast cancer versus other diseases and controls in a multisite clinical trial design. The peptides or proteins that show a high observation frequency, and/or precursor intensity, specific to breast cancer plasma might be discovered by comparison to other diseases and matched controls. The endogenous tryptic peptides of breast cancer plasma were compared to ovarian cancer, female normal, sepsis, heart attack, Alzheimer's and multiple sclerosis along with the institution-matched normal and control samples collected directly onto ice. METHODS: Endogenous tryptic peptides were extracted from individual breast cancer and control EDTA plasma samples in a step gradient of acetonitrile, and collected over preparative C18 for LC-ESI-MS/MS with a set of LTQ XL linear quadrupole ion traps working together in parallel to randomly and independently sample clinical populations. The MS/MS spectra were fit to fully tryptic peptides or phosphopeptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The observation frequency was subsequently tested by Chi Square analysis. The log10 precursor intensity was compared by ANOVA in the R statistical system. RESULTS: Peptides and/or phosphopeptides of common plasma proteins such as APOE, C4A, C4B, C3, APOA1, APOC2, APOC4, ITIH3 and ITIH4 showed increased observation frequency and/or precursor intensity in breast cancer. Many cellular proteins also showed large changes in frequency by Chi Square (χ2 > 100, p < 0.0001) in the breast cancer samples such as CPEB1, LTBP4, HIF-1A, IGHE, RAB44, NEFM, C19orf82, SLC35B1, 1D12A, C8orf34, HIF1A, OCLN, EYA1, HLA-DRB1, LARS, PTPDC1, WWC1, ZNF562, PTMA, MGAT1, NDUFA1, NOGOC, OR1E1, OR1E2, CFI, HSA12, GCSH, ELTD1, TBX15, NR2C2, FLJ00045, PDLIM1, GALNT9, ASH2L, PPFIBP1, LRRC4B, SLCO3A1, BHMT2, CS, FAM188B2, LGALS7, SAT2, SFRS8, SLC22A12, WNT9B, SLC2A4, ZNF101, WT1, CCDC47, ERLIN1, SPFH1, EID2, THOC1, DDX47, MREG, PTPRE, EMILIN1, DKFZp779G1236 and MAP3K8 among others. The protein gene symbols with large Chi Square values were significantly enriched in proteins that showed a complex set of previously established functional and structural relationships by STRING analysis. An increase in mean precursor intensity of peptides was observed for QSER1 as well as SLC35B1, IQCJ-SCHIP1, MREG, BHMT2, LGALS7, THOC1, ANXA4, DHDDS, SAT2, PTMA and FYCO1 among others. In contrast, the QSER1 peptide QPKVKAEPPPK was apparently specific to ovarian cancer. CONCLUSION: There was striking agreement between the breast cancer plasma peptides and proteins discovered by LC-ESI-MS/MS with previous biomarkers from tumors, cells lines or body fluids by genetic or biochemical methods. The results indicate that variation in plasma peptides from breast cancer versus ovarian cancer may be directly discovered by LC-ESI-MS/MS that will be a powerful tool for clinical research. It may be possible to use a battery of sensitive and robust linear quadrupole ion traps for random and independent sampling of plasma from a multisite clinical trial.

The plasma peptidome.

BACKGROUND: It may be possible to discover new diagnostic or therapeutic peptides or proteins from blood plasma using LC-ESI-MS/MS to identify, with a linear quadrupole ion trap to identify, quantify and compare the statistical distributions of peptides cleaved ex vivo from plasma samples from different clinical populations. METHODS: A systematic method for the organic fractionation of plasma peptides was applied to identify and quantify the endogenous tryptic peptides from human plasma from multiple institutions by C18 HPLC followed nano electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) with a linear quadrupole ion trap. The endogenous tryptic peptides, or tryptic phospho peptides (i.e. without exogenous digestion), were extracted in a mixture of organic solvent and water, dried and collected by preparative C18. The tryptic peptides from 6 institutions with 12 different disease and normal EDTA plasma populations, alongside ice cold controls for pre-analytical variation, were characterized by mass spectrometry. Each patient plasma was precipitated in 90% acetonitrile and the endogenous tryptic peptides extracted by a stepwise gradient of increasing water and then formic acid resulting in 10 sub-fractions. The fractionated peptides were manually collected over preparative C18 and injected for 1508 LC-ESI-MS/MS experiments analyzed in SQL Server R. RESULTS: Peptides that were cleaved in human plasma by a tryptic activity ex vivo provided convenient and sensitive access to most human proteins in plasma that show differences in the frequency or intensity of proteins observed across populations that may have clinical significance. Combination of step wise organic extraction of 200 µL of plasma with nano electrospray resulted in the confident identification and quantification ~ 14,000 gene symbols by X!TANDEM that is the largest number of blood proteins identified to date and shows that you can monitor the ex vivo proteolysis of most human proteins, including interleukins, from blood. A total of 15,968,550 MS/MS spectra ≥ E4 intensity counts were correlated by the SEQUEST and X!TANDEM algorithms to a federated library of 157,478 protein sequences that were filtered for best charge state (2+ or 3+) and peptide sequence in SQL Server resulting in 1,916,672 distinct best-fit peptide correlations for analysis with the R statistical system. SEQUEST identified some 140,054 protein accessions, or some ~ 26,000 gene symbols, proteins or loci, with at least 5 independent correlations. The X!TANDEM algorithm made at least 5 best fit correlations to more than 14,000 protein gene symbols with p-values and FDR corrected q-values of ~ 0.001 or less. Log10 peptide intensity values showed a Gaussian distribution from E8 to E4 arbitrary counts by quantile plot, and significant variation in average precursor intensity across the disease and controls treatments by ANOVA with means compared by the Tukey-Kramer test. STRING analysis of the top 2000 gene symbols showed a tight association of cellular proteins that were apparently present in the plasma as protein complexes with related cellular components, molecular functions and biological processes. CONCLUSIONS: The random and independent sampling of pre-fractionated blood peptides by LC-ESI-MS/MS with SQL Server-R analysis revealed the largest plasma proteome to date and was a practical method to quantify and compare the frequency or log10 intensity of individual proteins cleaved ex vivo across populations of plasma samples from multiple clinical locations to discover treatment-specific variation using classical statistics suitable for clinical science. It was possible to identify and quantify nearly all human proteins from EDTA plasma and compare the results of thousands of LC-ESI-MS/MS experiments from multiple clinical populations using standard database methods in SQL Server and classical statistical strategies in the R data analysis system.

Galectin-1 has potential prognostic significance and is implicated in clear cell renal cell carcinoma progression through the HIF/mTOR signaling axis.

BACKGROUND: Metastatic clear cell renal cell carcinoma (ccRCC) patients have <9% 5-year survival rate, do not respond well to targeted therapy and eventually develop resistance. A better understanding of molecular pathways of RCC metastasis is the basis for the discovery of novel prognostic markers and targeted therapies. METHODS: We investigated the biological impact of galectin-1 (Gal-1) in RCC cell lines by migration and invasion assays. Effect of Gal-1 expression on the mitogen-activated protein kinase pathway was assessed by proteome array. RESULTS: Increased expression of Gal-1 increased cell migration while knocking down Gal-1 expression by siRNA resulted in reduced cellular migration (P<0.001) and invasion (P<0.05). Gal-1 overexpression increased phosphorylation of Akt, mTOR and p70 kinase. Upon hypoxia and increased HIF-1α, Gal-1 increased in a dose-dependent manner. We also found miR-22 overexpression resulted in decreased Gal-1 and HIF-1α. Immunohistochemistry analysis showed that high Gal-1 protein expression was associated with larger size tumor (P=0.034), grades III/IV tumors (P<0.001) and shorter disease-free survival (P=0.0013). Using the Cancer Genome Atlas data set, we found that high Gal-1 mRNA expression was associated with shorter overall survival (41 vs 78 months; P<0.01). CONCLUSIONS: Our data suggest Gal-1 mediates migration and invasion through the HIF-1α-mTOR signaling axis and is a potential prognostic marker and therapeutic target.

Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer.

Loco-regional recurrence in 50% of oral squamous cell carcinoma (OSCC) patients poses major challenge for oncologists. Lack of biomarkers that can predict disease aggressiveness and recurrence risk makes the scenario more dismal. On the basis of our earlier global proteomic analyses we identified five differentially expressed proteins in OSCC. This study aimed to develop protein biomarkers-based prognostic risk prediction model for OSCC. Sub-cellular expression of five proteins, S100A7, heterogeneous nuclear ribonucleoproteinK (hnRNPK), prothymosin α (PTMA), 14-3-3ζ and 14-3-3σ was analyzed by immunohistochemistry in test set (282 Indian OSCCs and 209 normal tissues), correlated with clinic-pathological parameters and clinical outcome over 12 years to develop a risk model for prediction of recurrence-free survival. This risk classifier was externally validated in 135 Canadian OSCC and 96 normal tissues. Biomarker signature score based on PTMA, S100A7 and hnRNPK was associated with recurrence free survival of OSCC patients (hazard ratio=1.11; 95% confidence interval 1.08, 1.13, P<0.001, optimism-corrected c-statistic=0.69) independent of clinical parameters. Biomarker signature score stratified OSCC patients into high- and low-risk groups with significant difference for disease recurrence. The high-risk group had median survival 14 months, and 3-year survival rate of 30%, whereas low-risk group survival probability did not reach 50%, and had 3-year survival rate of 71%. As a powerful predictor of 3-year recurrence-free survival in OSCC patients, the newly developed biomarkers panel risk classifier will facilitate patient counseling for personalized treatment.

The Human Proteome Organization Chromosome 6 Consortium: integrating chromosome-centric and biology/disease driven strategies.

The Human Proteome Project (HPP) is designed to generate a comprehensive map of the protein-based molecular architecture of the human body, to provide a resource to help elucidate biological and molecular function, and to advance diagnosis and treatment of diseases. Within this framework, the chromosome-based HPP (C-HPP) has allocated responsibility for mapping individual chromosomes by country or region, while the biology/disease HPP (B/D-HPP) coordinates these teams in cross-functional disease-based groups. Chromosome 6 (Ch6) provides an excellent model for integration of these two tasks. This metacentric chromosome has a complement of 1002-1034 genes that code for known, novel or putative proteins. Ch6 is functionally associated with more than 120 major human diseases, many with high population prevalence, devastating clinical impact and profound societal consequences. The unique combination of genomic, proteomic, metabolomic, phenomic and health services data being drawn together within the Ch6 program has enormous potential to advance personalized medicine by promoting robust biomarkers, subunit vaccines and new drug targets. The strong liaison between the clinical and laboratory teams, and the structured framework for technology transfer and health policy decisions within Canada will increase the speed and efficacy of this transition, and the value of this translational research. BIOLOGICAL SIGNIFICANCE: Canada has been selected to play a leading role in the international Human Proteome Project, the global counterpart of the Human Genome Project designed to understand the structure and function of the human proteome in health and disease. Canada will lead an international team focusing on chromosome 6, which is functionally associated with more than 120 major human diseases, including immune and inflammatory disorders affecting the brain, skeletal system, heart and blood vessels, lungs, kidney, liver, gastrointestinal tract and endocrine system. Many of these chronic and persistent diseases have a high population prevalence, devastating clinical impact and profound societal consequences. As a result, they impose a multi-billion dollar economic burden on Canada and on all advanced societies through direct costs of patient care, the loss of health and productivity, and extensive caregiver burden. There is no definitive treatment at the present time for any of these disorders. The manuscript outlines the research which will involve a systematic assessment of all chromosome 6 genes, development of a knowledge base, and development of assays and reagents for all chromosome 6 proteins. We feel that the informatic infrastructure and MRM assays developed will place the chromosome 6 consortium in an excellent position to be a leading player in this major international research initiative. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?