SUMMARY To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSC). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease such as how different copy number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, as well as the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC.

Early detection remains the most promising approach to improve long-term survival of patients with ovarian cancer. In a five-center casecontrol study, serum proteomic expressions were analyzed on 153 patients with invasive epithelial ovarian cancer, 42 with other ovarian cancers, 166 with benign pelvic masses, and 142 healthy women. Data from patients with early stage ovarian cancer and healthy women at two centers were analyzed independently and the results cross-validated to discover potential biomarkers. The results were validated using the samples from two of the remaining centers. After protein identification, biomarkers for which an immunoassay was available were tested on samples from the fifth center, which included 41 healthy women, 41 patients with ovarian cancer, and 20 each with breast, colon, and prostate cancers. Three biomarkers were identified as follows: (a) apolipoprotein A1 (down-regulated in cancer); (b) a truncated form of transthyretin (down-regulated); and (c) a cleavage fragment of inter-␣-trypsin inhibitor heavy chain H4 (up-regulated). In independent validation to detect early stage invasive epithelial ovarian cancer from healthy controls, the sensitivity of a multivariate model combining the three biomarkers and CA125 [74% (95% CI, 52-90%)] was higher than that of CA125 alone [65% (95% CI, 43-84%)] at a matched specificity of 97% (95% CI, 89 -100%). When compared at a fixed sensitivity of 83% (95% CI, 61-95%), the specificity of the model [94% (95% CI, 85-98%)] was significantly better than that of CA125 alone [52% (95% CI, 39 -65%)]. These biomarkers demonstrated the potential to improve the detection of early stage ovarian cancer.

ContextIn men who develop an elevated serum prostate-specific antigen level (PSA) after having undergone a radical prostatectomy, the natural history of progression to distant metastases and death due to prostate cancer is unknown.Objective To characterize the time course of disease progression in men with biochemical recurrence after radical prostatectomy.Design A retrospective review of a large surgical series with median (SD) follow-up of 5.3 (3.7) years (range, 0.5-15 years) between April 1982 and April 1997.Setting An urban academic tertiary referral institution.Patients A total of 1997 men undergoing radical prostatectomy, by a single surgeon, for clinically localized prostate cancer. None received neoadjuvant therapy, and none had received adjuvant hormonal therapy prior to documented distant metastases. Main Outcome MeasuresAfter surgery, men were followed up with PSA assays and digital rectal examinations every 3 months for the first year, semiannually for the second year, and annually thereafter. A detectable serum PSA level of at least 0.2 ng/mL was evidence of biochemical recurrence. Distant metastases were diagnosed by radionuclide bone scan, chest radiograph, or other body imaging, which was performed at the time of biochemical recurrence and annually thereafter. ResultsThe actuarial metastasis-free survival for all 1997 men was 82% (95% confidence interval, 76%-88%) at 15 years after surgery. Of the 1997 men, 315 (15%) developed biochemical PSA level elevation. Eleven of these underwent early hormone therapy after the recurrence and are not included in the study. Of the remaining 304 men, 103 (34%) developed metastatic disease within the study period. The median actuarial time to metastases was 8 years from the time of PSA level elevation. In survival analysis, time to biochemical progression (PϽ.001), Gleason score (PϽ.001), and PSA doubling time (PϽ.001) were predictive of the probability and time to the development of metastatic disease. An algorithm combining these parameters was constructed to stratify men into risk groups. Once men developed metastatic disease, the median actuarial time to death was 5 years. The time interval from surgery to the appearance of metastatic disease was predictive of time until death (PϽ.02).Conclusions Several clinical parameters help predict the outcomes of men with PSA elevation after radical prostatectomy. These data may be useful in the design of clinical trials, the identification of men for enrollment into experimental protocols, and counseling men regarding the timing of administration of adjuvant therapies.Estimates are calculated at 3, 5, or 7 years from the time of the initial prostate-specific antigen (PSA) elevation (metastatic-disease free period, based on Gleason score in the surgical specimen, the time of initial biochemical recurrence (Յ2 vs Ͼ2 years), and prostrate-specific antigen doubling time (PSADT) (Ͻ10 vs Ն10 months). CI indicates confidence interval. PSA LEVEL ELEVATION AFTER PROSTATECTOMY

Clinical stage, Gleason score and serum prostate specific antigen (PSA) levels are used separately to predict pathological stage in patients with localized prostate cancer. Because the degree of tumor differentiation has a profound influence on the expression of serum PSA, serum PSA levels alone do not reflect tumor burden accurately. To overcome this obstacle we tested these 3 variables alone and in combinations as predictors of final pathological stage in 703 men with clinically localized prostate cancer at our institution. All patients were assigned a clinical stage by 1 urologist. The Gleason score was determined from preoperative needle biopsy and serum PSA levels were measured on an ambulatory basis. Final pathological stage was determined to be either organ confined, established capsular penetration, seminal vesicle involvement or lymph node involvement. Logistic regression analysis with the likelihood ratio chi-square test determined that serum PSA, Gleason score and clinical stage all predicted final pathological stage well. The results were improved with combinations of the 3 variables (serum PSA, Gleason score and clinical stage) and the combination provided the best separation. From these analyses probability plots and nomograms have been constructed to assist urologists in the preoperative prediction of final pathological stage for patients with clinically localized prostate cancer.

Adoption of targeted mass spectrometry (MS) approaches such as multiple reaction monitoring (MRM) to study biological and biomedical questions is well underway in the proteomics community. Successful application depends on the ability to generate reliable assays that uniquely and confidently identify target peptides in a sample. Unfortunately, there is a wide range of criteria being applied to say that an assay has been successfully developed. There is no consensus on what criteria are acceptable and little understanding of the impact of variable criteria on the quality of the results generated. Publications describing targeted MS assays for peptides frequently do not contain sufficient information for readers to establish confidence that the tests work as intended or to be able to apply the tests described in their own labs. Guidance must be developed so that targeted MS assays with established performance can be made widely distributed and applied by many labs worldwide. To begin to address the problems and their solutions, a workshop was held at the National Institutes of Health with representatives from the multiple communities developing and employing targeted MS assays. Participants discussed the analytical goals of their experiments From the ‡Broad Institute of MIT and Harvard, Cambridge, Massachusetts; §Eli

Highlights d Systematic identification of colon cancer-associated proteins and phosphosites d Proteomics-supported neoantigens and cancer/testis antigens in 78% of the tumors d Rb phosphorylation is an oncogenic driver and a putative target in colon cancer d Glycolysis inhibition may render MSI tumors more sensitive to checkpoint blockade

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anticoagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multi- We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches.This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in −4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.