Lisa F. Newcomb

A Mouse to Human Search for Plasma Proteome Changes Associated with Pancreatic Tumor Development

Background The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease. Here, we sought to exploit the merits of a well-characterized GEM model of pancreatic cancer to determine whether proteomics technologies allow identification of protein changes associated with tumor development and whether such changes are relevant to human pancreatic cancer. Methods and Findings Plasma was sampled from mice at early and advanced stages of tumor development and from matched controls. Using a proteomic approach based on extensive protein fractionation, we confidently identified 1,442 proteins that were distributed across seven orders of magnitude of abundance in plasma. Analysis of proteins chosen on the basis of increased levels in plasma from tumor-bearing mice and corroborating protein or RNA expression in tissue documented concordance in the blood from 30 newly diagnosed patients with pancreatic cancer relative to 30 control specimens. A panel of five proteins selected on the basis of their increased level at an early stage of tumor development in the mouse was tested in a blinded study in 26 humans from the CARET (Carotene and Retinol Efficacy Trial) cohort. The panel discriminated pancreatic cancer cases from matched controls in blood specimens obtained between 7 and 13 mo prior to the development of symptoms and clinical diagnosis of pancreatic cancer. Conclusions Our findings indicate that GEM models of cancer, in combination with in-depth proteomic analysis, provide a useful strategy to identify candidate markers applicable to human cancer with potential utility for early detection.

Urinary TMPRSS2:ERG and PCA3 in an Active Surveillance Cohort: Results from a Baseline Analysis in the Canary Prostate Active Surveillance Study

Purpose: Active surveillance is used to manage low-risk prostate cancer. Both PCA3 and TMPRSS2:ERG are promising biomarkers that may be associated with aggressive disease. This study examines the correlation of these biomarkers with higher cancer volume and grade determined at the time of biopsy in an active surveillance cohort. Experimental Design: Urine was collected after digital rectal examination prospectively as part of the multi-institutional Canary Prostate Active Surveillance Study (PASS). PCA3 and TMPRSS2:ERG levels were analyzed in urine collected at study entry. Biomarker scores were correlated to clinical and pathologic variables. Results: In 387 men, both PCA3 and TMPRSS2:ERG scores were significantly associated with higher volume disease. For a negative repeat biopsy, and 1% to 10%, 11% to 33%, 34% or more positive cores, median PCA3, and TMPRSS2:ERG scores increased incrementally (P < 0.005). Both PCA3 and TMPRSS2:ERG scores were also significantly associated with the presence of high-grade disease. For a negative repeat biopsy, Gleason 6 and Gleason ≥7 cancers, the median PCA3, and TMPRSS2:ERG scores also increased incrementally (P = 0.02 and P = 0.001, respectively). Using the marker scores as continuous variables, the ORs for a biopsy in which cancer was detected versus a negative repeat biopsy (ref) on modeling was 1.41 (95% CI: 1.07–1.85), P = 0.01 for PCA3 and 1.28 (95% CI: 1.10–1.49), P = 0.001 for TMPRSS2:ERG. Conclusions: For men on active surveillance, both PCA3 and TMPRSS2:ERG seem to stratify the risk of having aggressive cancer as defined by tumor volume or Gleason score. Clin Cancer Res; 19(9); 2442–50. ©2013 AACR.

The potential impact of reproducibility of Gleason grading in men with early stage prostate cancer managed by active surveillance: a multi-institutional study.

PURPOSE We evaluated the reproducibility of Gleason grading as relevant to the clinical treatment of men on active surveillance. MATERIALS AND METHODS Three sets of digital images of prostatic adenocarcinoma in biopsies were reviewed and assigned Gleason scores by a total of 11 pathologists from 7 institutions. Interobserver and intra-observer reproducibility were assessed for assignment of the highest Gleason pattern (3 vs 4 or higher). We also identified 97 consecutive patients on active surveillance. Prostate biopsy glass slides from 82 of the patients were available for re-review and the frequency of carcinoma requiring the distinction of tangentially sectioned Gleason pattern 3 from 4 was determined. RESULTS Interobserver reproducibility for classic Gleason patterns was substantial (Lights κ 0.76). Interobserver reproducibility for the histological distinction of tangentially sectioned Gleason pattern 3 from Gleason pattern 4 was only fair (Lights κ 0.27). Intra-observer reproducibility ranged from 65% to 100% (mean 81.5%). Of the 82 patients on active surveillance 61 had carcinoma and 15 (24.5%) had a set of biopsies with at least 1 focus in which the distinction between tangentially sectioned Gleason pattern 3 and poorly formed pattern 4 glands had to be considered. CONCLUSIONS The reproducibility of grading classic Gleason patterns is high. However, variability in grading occurred when distinguishing between tangentially sectioned pattern 3 glands and the poorly formed gland subset of pattern 4. Developing universally accepted histological and/or molecular criteria to distinguish these patterns and subsequently characterizing their natural history would be useful when treating patients on active surveillance.

Canary Prostate Active Surveillance Study: design of a multi-institutional active surveillance cohort and biorepository.

Active surveillance is a management plan for localized prostate cancer that offers selective delayed intervention on indication of disease progression, allowing patients to delay or avoid treatment and associated side-effects. Outcomes from centers that promote active surveillance are favorable, with high rates of disease-specific survival. However, there remains a need for prognostic variables or biomarkers that distinguish with high specificity the aggressive cancers that progress on surveillance from the indolent cancers. The Canary Prostate Active Surveillance Study is a multicenter study and a biorepository that will discover and confirm biomarkers of aggressive disease as defined by histologic, prostate-specific antigen, or clinical criteria.

Plasma proteome profiling of a mouse model of breast cancer identifies a set of up-regulated proteins in common with human breast cancer cells.

We have applied an in-depth quantitative proteomic approach, combining isotopic labeling extensive intact protein separation and mass spectrometry, for high confidence identification of protein changes in plasmas from a mouse model of breast cancer. We hypothesized that a wide spectrum of proteins may be up-regulated in plasma with tumor development and that comparisons with proteins expressed in human breast cancer cell lines may identify a subset of up-regulated proteins in common with proteins expressed in breast cancer cell lines that may represent candidate biomarkers for breast cancer. Plasma from PyMT transgenic tumor-bearing mice and matched controls were obtained at two time points during tumor growth. A total of 133 proteins were found to be increased by 1.5-fold or greater at one or both time points. A comparison of this set of proteins with published findings from proteomic analysis of human breast cancer cell lines yielded 49 proteins with increased levels in mouse plasma that were identified in breast cancer cell lines. Pathway analysis comparing the subset of up-regulated proteins known to be expressed in breast cancer cell lines with other up-regulated proteins indicated a cancer related function for the former and a host-response function for the latter. We conclude that integration of proteomic findings from mouse models of breast cancer and from human breast cancer cell lines may help identify a subset of proteins released by breast cancer cells into the circulation and that occur at increased levels in breast cancer.

Precision Medicine in Active Surveillance for Prostate Cancer: Development of the Canary-Early Detection Research Network Active Surveillance Biopsy Risk Calculator.

BACKGROUND Men on active surveillance (AS) face repeated biopsies. Most biopsy specimens will not show disease progression or change management. Such biopsies do not contribute to patient management and are potentially morbid and costly. OBJECTIVE To use a contemporary AS prospective trial to develop a tool to predict AS biopsy outcomes. DESIGN, SETTING, AND PARTICIPANTS Biopsy samples (median: 2; range: 2-9 per patient) from 859 men participating in the Canary Prostate Active Surveillance Study and with Gleason 6 prostate cancer (median follow-up: 35.8 mo; range: 3.0-148.7 mo) were analyzed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Logistic regression was used to predict progression, defined as an increase in Gleason score from ≤6 to ≥7 or increase in percentage of cores positive for cancer from <34% to ≥34%. Fivefold internal cross-validation was performed to evaluate the area under the receiver operating characteristic curve (AUC). RESULTS AND LIMITATIONS Statistically significant risk factors for progression on biopsy were prostate-specific antigen (odds ratio [OR]: 1.045; 95% confidence interval [CI], 1.028-1.063), percentage of cores positive for cancer on most recent biopsy (OR: 1.401; 95% CI, 1.301-1.508), and history of at least one prior negative biopsy (OR: 0.524; 95% CI, 0.417-0.659). A multivariable predictive model incorporating these factors plus age and number of months since last biopsy achieved an AUC of 72.4%. CONCLUSIONS A combination of readily available clinical measures can stratify patients considering AS prostate biopsy. Risk of progression or upgrade can be estimated and incorporated into clinical practice. PATIENT SUMMARY The Canary-Early Detection Research Network Active Surveillance Biopsy Risk Calculator, an online tool, can be used to guide patient decision making regarding follow-up prostate biopsy.

A mouse plasma peptide atlas as a resource for disease proteomics

We present an in-depth analysis of mouse plasma leading to the development of a publicly available repository composed of 568 liquid chromatography-tandem mass spectrometry runs. A total of 13,779 distinct peptides have been identified with high confidence. The corresponding approximately 3,000 proteins are estimated to span a 7 logarithmic range of abundance in plasma. A major finding from this study is the identification of novel isoforms and transcript variants not previously predicted from genome analysis.

Histologic grading of prostatic adenocarcinoma can be further optimized

Histologic grading remains the gold standard for prognosis in prostate cancer, and assessment of Gleason score plays a critical role in active surveillance management. We sought to optimize the prognostic stratification of grading and developed a method of recording and studying individual architectural patterns by light microscopic evaluation that is independent of standard Gleason grade. Some of the evaluated patterns are not assessed by current Gleason grading (eg, reactive stromal response). Individual histologic patterns were correlated with recurrence-free survival in a retrospective postradical prostatectomy cohort of 1275 patients represented by the highest-grade foci of carcinoma in tissue microarrays. In univariable analysis, fibromucinous rupture with varied epithelial complexity had a significantly lower relative risk of recurrence-free survival in cases graded as 3+4=7. Cases having focal “poorly formed glands,” which could be designated as pattern 3+4=7, had lower risk than cribriform patterns with either small cribriform glands or expansile cribriform growth. In separate multivariable Cox proportional hazard analyses of both Gleason score 3+3=6 and 3+4=7 carcinomas, reactive stromal patterns were associated with worse recurrence-free survival. Decision tree models demonstrate potential regrouping of architectural patterns into categories with similar risk. In summary, we argue that Gleason score assignment by current consensus guidelines are not entirely optimized for clinical use, including active surveillance. Our data suggest that focal poorly formed gland and cribriform patterns, currently classified as Gleason pattern 4, should be in separate prognostic groups, as the latter is associated with worse outcome. Patterns with extravasated mucin are likely overgraded in a subset of cases with more complex epithelial bridges, whereas stromogenic cancers have a worse outcome than conveyed by Gleason grade alone. These findings serve as a foundation to facilitate optimization of histologic grading and strongly support incorporating reactive stroma into routine assessment.

Evaluating the Four Kallikrein Panel of the 4Kscore for Prediction of High-grade Prostate Cancer in Men in the Canary Prostate Active Surveillance Study

BACKGROUND Diagnosis of Gleason 6 prostate cancer can leave uncertainty about the presence of undetected aggressive disease. OBJECTIVE To evaluate the utility of a four kallikrein (4K) panel in predicting the presence of high-grade cancer in men on active surveillance. DESIGN, SETTING, AND PARTICIPANTS Plasma collected before the first and subsequent surveillance biopsies was assessed for 718 men prospectively enrolled in the multi-institutional Canary PASS trial. Biopsy data were split 2:1 into training and test sets. We developed statistical models that included clinical information and either the 4Kpanel or serum prostate-specific antigen (PSA). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The endpoint was reclassification to Gleason ≥7. We used receiver operating characteristic (ROC) curve analyses and area under the curve (AUC) to assess discriminatory capacity, and decision curve analysis (DCA) to report clinical net benefit. RESULTS AND LIMITATIONS Significant predictors for reclassification were 4Kpanel (odds ratio [OR] 1.54, 95% confidence interval [CI] 1.31-1.81) or PSA (OR 2.11, 95% CI 1.53-2.91), ≥20% cores positive (OR 2.10, 95% CI 1.33-3.32), two or more prior negative biopsies (OR 0.19, 95% CI 0.04-0.85), prostate volume (OR 0.47, 95% CI 0.31-0.70), and body mass index (OR 1.09, 95% CI 1.04-1.14). ROC curve analysis comparing 4K and base models indicated that the 4Kpanel improved accuracy for predicting reclassification (AUC 0.78 vs 0.74) at the first surveillance biopsy. Both models performed comparably for prediction of reclassification at subsequent biopsies (AUC 0.75 vs 0.76). In DCA, both models showed higher net benefit compared to biopsy-all and biopsy-none strategies. Limitations include the single cohort nature of the study and the small numbers; results should be validated in another cohort before clinical use. CONCLUSIONS The 4Kpanel provided incremental value over routine clinical information in predicting high-grade cancer in the first biopsy after diagnosis. The 4Kpanel did not add predictive value to the base model at subsequent surveillance biopsies. PATIENT SUMMARY Active surveillance is a management strategy for many low-grade prostate cancers. Repeat biopsies monitor for previously undetected high-grade cancer. We show that a model with clinical variables, including a panel of four kallikreins, indicates the presence of high-grade cancer before a biopsy is performed.

Evaluation of ERG and SPINK1 by Immunohistochemical Staining and Clinicopathological Outcomes in a Multi-Institutional Radical Prostatectomy Cohort of 1067 Patients

Distinguishing between patients with early stage, screen detected prostate cancer who must be treated from those that can be safely watched has become a major issue in prostate cancer care. Identification of molecular subtypes of prostate cancer has opened the opportunity for testing whether biomarkers that characterize these subtypes can be used as biomarkers of prognosis. Two established molecular subtypes are identified by high expression of the ERG oncoprotein, due to structural DNA alterations that encode for fusion transcripts in approximately ½ of prostate cancers, and over-expression of SPINK1, which is purportedly found only in ERG-negative tumors. We used a multi-institutional prostate cancer tissue microarray constructed from radical prostatectomy samples with associated detailed clinical data and with rigorous selection of recurrent and non-recurrent cases to test the prognostic value of immunohistochemistry staining results for the ERG and SPINK1 proteins. In univariate analysis, ERG positive cases (419/1067; 39%) were associated with lower patient age, pre-operative serum PSA levels, lower Gleason scores (≤3+4=7) and improved recurrence free survival (RFS). On multivariate analysis, ERG status was not correlated with RFS, disease specific survival (DSS) or overall survival (OS). High-level SPINK1 protein expression (33/1067 cases; 3%) was associated with improved RFS on univariate and multivariate Cox regression analysis. Over-expression of either protein was not associated with clinical outcome. While expression of ERG and SPINK1 proteins was inversely correlated, it was not mutually exclusive since 3 (0.28%) cases showed high expression of both. While ERG and SPINK1 appear to identify discrete molecular subtypes of prostate cancer, only high expression of SPINK1 was associated with improved clinical outcome. However, by themselves, neither ERG nor SPINK1 appear to be useful biomarkers for prognostication of early stage prostate cancer.