HE4 and CA125 serum biomarker monitoring in women with epithelial ovarian cancer.

BACKGROUND: CA125 is the gold standard serum biomarker for monitoring patients with epithelial ovarian cancer (EOC). Human epididymal protein 4 (HE4) is a novel serum biomarker for EOC patients. OBJECTIVE: The objective of this trial was to examine the utility of measuring serum HE4 levels for monitoring EOC patients and to compare HE4 performance parameters to serum CA125. METHODS: A retrospective trial using residual longitudinal serum samples drawn during treatment and monitoring from EOC patients. Serum CA125 and HE4 levels were analyzed at each time point, and a velocity of change was calculated and correlated with clinical status. The null hypothesis was that HE4 is inferior to CA125, and this was tested using concordance and two-sided Fisher's exact testing. McNemar's test was used to assess the overall agreement of the two assays with the clinical status. RESULTS: A total of 129 patients with 272 separate clinical periods and 1739 events (serum samples) were evaluated. Using a 25% change in serum biomarker levels to indicate change in disease status, the accuracy and NPV determined for HE4 versus CA125 were 81.8% versus 82.6% (p = 0.846) and 87.4% versus 89.7% (p = 0.082), respectively. Concordance comparison of HE4 accuracy / CA125 accuracy was 0.990, indicating HE4 was not inferior to CA125 (McNemar's test p-value = 0.522). Performing a velocity of change analysis, the accuracy and NPV determined for HE4 versus CA125 were 78.3% versus 78.6% (p = 0.995) and 74.9% versus 76.3% (p = 0.815), respectively. Concordance comparison of HE4 velocity accuracy / CA125 velocity accuracy was 0.996, again indicating HE4 was not inferior to CA125 (McNemar's test p-value = 0.884). The combination of HE4 and CA125 velocity changes showed a similar accuracy of 81.3% (p = 0.797 compared to HE4 and CA125 alone) and NPV of 81.1% (p≥0.172 compared to HE4 and CA125 alone), and an increased sensitivity of 70.5% (p≤0.070 compared to HE4 and CA125 alone). CONCLUSION: HE4 is equivalent to CA125 for monitoring of EOC patients. The combination of CA125 and HE4 velocities is superior to either marker alone.

Analysis of serum HE4 levels in various histologic subtypes of epithelial ovarian cancer and other malignant tumors.

BACKGROUND: The measurement of serum HE4 levels has emerged as a sensitive and specific biomarker for epithelial ovarian cancers (EOCs). However, serum levels in women diagnosed with various histologic subtypes of EOC and in women with metastatic non-ovarian primary malignancies have not been widely reported. OBJECTIVE: The goal of this study was to identify how serum HE4 levels vary in women diagnosed with different histologic subtypes of EOC and non-ovarian malignancies. METHODS: Data from six prospective pelvic mass clinical trials was combined and an evaluation of serum HE4 levels in women diagnosed with a malignancy was performed. For all patients, serum was obtained prior to surgery and final pathology, including primary tumor site, histologic subtype, grade and stage, were recorded. The mean, median, standard deviation, maximum, and minimum HE4 levels were determined for each group. RESULTS: A total of 984 patients were included in this study, with the average patient age being 60 years old. There were 230 premenopausal and 754 postmenopausal patients. Serum HE4 levels were elevated (≥70.0 pMol) in 85%of EOCs, 40%of LMP tumors, 21%of non-EOCs (germ cell tumors), 25%of cervical cancers, and 47%of non-gynecologic metastatic cancers. Analysis of histologic subtypes revealed 90%(n = 391) of serous, 85%(n = 73) of endometrioid, 45%(n = 42) of mucinous, 86%(n = 51) of mixed tumors, and 69%(n = 36) of clear cell tumors had elevated serum HE4 levels. CONCLUSIONS: Serum HE4 levels are most often elevated in women with high grade serous and endometrioid EOCs, and though serum elevations are seen more often with advanced stage disease, HE4 is also often elevated in early stage disease and lower grade tumors.

Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival.

BACKGROUND: Circulating tumour cells (CTCs) in blood associate with overall survival (OS) of cancer patients, but they are detected in extremely low numbers. Large tumour-derived extracellular vesicles (tdEVs) in castration-resistant prostate cancer (CRPC) patients are present at around 20 times higher frequencies than CTCs and have equivalent prognostic power. In this study, we explored the presence of tdEVs in other cancers and their association with OS. METHODS: The open-source ACCEPT software was used to automatically enumerate tdEVs in digitally stored CellSearch® images obtained from previously reported CTC studies evaluating OS in 190 CRPC, 450 metastatic colorectal cancer (mCRC), 179 metastatic breast cancer (MBC) and 137 non-small cell lung cancer (NSCLC) patients before the initiation of a new treatment. RESULTS: Presence of unfavourable CTCs and tdEVs is predictive of OS, with respective hazard ratios (HRs) of 2.4 and 2.2 in CRPC, 2.7 and 2.2 in MBC, 2.3 and 1.9 in mCRC and 2.0 and 2.4 in NSCLC, respectively. CONCLUSIONS: tdEVs have equivalent prognostic value as CTCs in the investigated metastatic cancers. CRPC, mCRC, and MBC (but not NSCLC) patients with favourable CTC counts can be further prognostically stratified using tdEVs. Our data suggest that tdEVs could be used in clinical decision-making.

Multiple biomarker algorithms to predict epithelial ovarian cancer in women with a pelvic mass: Can additional makers improve performance?

INTRODUCTION: Management of a woman with a pelvic mass is complicated by difficulty in discriminating malignant from benign disease. Many serum biomarkers have been examined to determine their sensitivity for detecting malignancy. This study was designed to evaluate if the addition of biomarkers to HE4 and CA125, as used in the Risk of Malignancy Algorithm (ROMA), can improve the detection of EOC. METHODS: This was an IRB approved, prospective clinical trial examining serum obtained from women diagnosed with a pelvic mass who subsequently underwent surgery. Serum biomarker levels for CA125, HE4, YKL-40, transthyretin, ApoA1, Beta-2-microglobulin, transferrin, and LPA were measured. Logistic regression analysis was performed for various marker combinations, ROC curves were generated, and the area under the curves (AUCs) were determined. RESULTS: A total of 184 patients met inclusion criteria with a median age of 56 years (Range 20-91). Final pathology revealed there were 103 (56.0%) benign tumors, 4 (2.2%) LMP tumors, 61 EOC (33.1%), 2 (1.1%) non-EOC ovarian cancers, 6 (3.3%) gynecologic cancers with metastasis to the ovary and 8 (4.3%) non-gynecologic cancers with metastasis to the ovary. The combination of HE4 and CA125 (i.e. ROMA) achieved an AUC of 91.2% (95% CI: 86.0-96.4) for the detection of EOC vs benign disease. The combination of CA125, HE4, YKL-40, transthyretin, ApoA1, Beta 2 microglobulin, transferrin, LPA and menopausal status achieved the highest AUC of 94.6% (95% CI: 90.1-99.2) but this combination was not significantly better than the HE4 and CA125 combination alone (p = 0.078). CONCLUSIONS: The addition of select further serum biomarkers to HE4 and CA125 does not add to the performance of the dual marker combination for the detection of ovarian cancer.

PBOV1 as a potential biomarker for more advanced prostate cancer based on protein and digital histomorphometric analysis.

BACKGROUND: There are few tissue-based biomarkers that can accurately predict prostate cancer (PCa) progression and aggressiveness. We sought to evaluate the clinical utility of prostate and breast overexpressed 1 (PBOV1) as a potential PCa biomarker. METHODS: Patient tumor samples were designated by Grade Groups using the 2014 Gleason grading system. Primary radical prostatectomy tumors were obtained from 48 patients and evaluated for PBOV1 levels using Western blot analysis in matched cancer and benign cancer-adjacent regions. Immunohistochemical evaluation of PBOV1 was subsequently performed in 80 cancer and 80 benign cancer-adjacent patient samples across two tissue microarrays (TMAs) to verify protein levels in epithelial tissue and to assess correlation between PBOV1 proteins and nuclear architectural changes in PCa cells. Digital histomorphometric analysis was used to track 22 parameters that characterized nuclear changes in PBOV1-stained cells. Using a training and test set for validation, multivariate logistic regression (MLR) models were used to identify significant nuclear parameters that distinguish Grade Group 3 and above PCa from Grade Group 1 and 2 PCa regions. RESULTS: PBOV1 protein levels were increased in tumors from Grade Group 3 and above (GS 4 + 3 and ≥ 8) regions versus Grade Groups 1 and 2 (GS 3 + 3 and 3 + 4) regions (P = 0.005) as assessed by densitometry of immunoblots. Additionally, by immunoblotting, PBOV1 protein levels differed significantly between Grade Group 2 (GS 3 + 4) and Grade Group 3 (GS 4 + 3) PCa samples (P = 0.028). In the immunohistochemical analysis, measures of PBOV1 staining intensity strongly correlated with nuclear alterations in cancer cells. An MLR model retaining eight parameters describing PBOV1 staining intensity and nuclear architecture discriminated Grade Group 3 and above PCa from Grade Group 1 and 2 PCa and benign cancer-adjacent regions with a ROC-AUC of 0.90 and 0.80, respectively, in training and test sets. CONCLUSIONS: Our study demonstrates that the PBOV1 protein could be used to discriminate Grade Group 3 and above PCa. Additionally, the PBOV1 protein could be involved in modulating changes to the nuclear architecture of PCa cells. Confirmatory studies are warranted in an independent population for further validation.

The Parsortix™ Cell Separation System-A versatile liquid biopsy platform.

Cancer cells from solid tumors can enter the circulatory system and survive to subsequently form distant metastases. The CellSearch® system (Menarini-Silicon Biosystems, Huntingdon Valley, PA) was the first, FDA-cleared system that provided a reliable tool for the investigation of circulating tumor cells (CTCs), which have been shown to be strongly associated with poor survival and therapy failure. Since that time, a number of new technologies have been introduced to improve CTC detection and/or isolation for further characterization. The continued and growing interest in the "liquid biopsy" field has spurred the development of numerous different CTC technologies. However, selecting the most appropriate CTC platform for individual applications can be challenging. No consensus has yet been reached in the community regarding which liquid biopsy technology is optimal. Here, we introduce the Parsortix™ Cell Separation System (ANGLE North America, Inc., King of Prussia, PA), a microfluidic based technology that captures rare cells based on size and deformability, offers reproducibly high capture efficiency, and produces highly enriched, viable (viability dependent on preservative used) CTCs that are amenable to a multitude of downstream analyses, including the isolation and interrogation of single cells. © 2018 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Validation of a Commercial Assay and Decision Support Tool for Routine Paclitaxel Therapeutic Drug Monitoring (TDM).

BACKGROUND: The value of therapeutic drug monitoring (TDM) for paclitaxel (PTX) was recently demonstrated in the largest TDM trial ever conducted in oncology. The trial demonstrated significant reduction in neuropathy when using TDM. Dose adjustment for PTX was based on time above a threshold concentration (Tc>0.05). Tc>0.05 must be calculated with a pharmacokinetic model and complex nonlinear mixed-effects software. The use of the software and chromatographic methods to measure PTX requires specialized expertise. User-friendly methods to quantitate PTX and calculate Tc>0.05 could simplify the introduction of TDM into routine clinical practice. METHODS: The immunoassay (MyPaclitaxel) was used to quantitate PTX in samples from the clinical trial; the results were used to calculate Tc>0.05 using a stand-alone computer program with a simple, friendly graphical user interface for nonlinear mixed-effects pharmacokinetic calculations (MyCare Drug Exposure Calculator). The resulting dose recommendations from the calculated Tc>0.05 were compared with those using liquid chromatography-ultraviolet detection and NONMEM to examine the efficacy of the simpler tools for TDM. RESULTS: There was a good agreement between the immunoassay and liquid chromatography-ultraviolet detection: Passing-Bablok regression slope was 1.045 and intercept was -6.00, R was 0.9757, and mean bias was -1.77 ng/mL (-2.07 nmol/L). Dosing recommendations were identical for 70% of the cycles and within 10% for 89% of the samples. All Tc>0.05 values were at the same or adjacent medical decision points. CONCLUSIONS: MyPaclitaxel assay and MyCare Drug Exposure Calculator are convenient, user-friendly tools that may be suitable for routine TDM of PTX in clinical care.

Combining clinical assessment and the Risk of Ovarian Malignancy Algorithm for the prediction of ovarian cancer.

OBJECTIVES: ACOG guidelines for the evaluation of women with a pelvic mass employ a combination of physical exam, imaging, and CA125 to guide physicians in the triage of women to gynecologic oncologists. We studied the use of ROMA with clinical assessment for cancer risk assessment in women with a pelvic mass. METHODS: This was a prospective, multicenter trial evaluating women with a pelvic mass who had an initial clinical risk assessment (ICRA) performed by a generalist. ROMA scores were calculated and sensitivity, specificity, PPV and NPV were determined for ICRA and ICRA+ROMA. RESULTS: A total of 461 women were entered into the study. There were 375 benign tumors, 48 EOC, 18 LMP tumors and 20 non-ovarian malignancies. For detection of ovarian cancer alone, ICRA had a sensitivity of 85.4%, a specificity of 84.3%, and a NPV of 97.8%. Adding ROMA to ICRA produced a significant improvement of 8.4% in sensitivity, achieving a sensitivity of 93.8% with a specificity of 67.2% and a NPV of 98.8%. Examination of all malignancies (ovarian & non-ovarian) provided a sensitivity of 89.7% for ROMA+ICRA in comparison to 77.9% for ICRA alone, a significant increase in sensitivity of 11.8%. The NPV also significantly increased from 95.5% to 97.3%. Overall, ROMA detected 13 additional malignancies missed by ICRA. CONCLUSIONS: Adjunctive use of ROMA with clinical assessment improves the stratification of women with a pelvic mass into low and high risk groups for ovarian cancer. The combination is particularly effective in ruling out malignant disease.

Analytical performance of the FDA-cleared Parsortix® PC1 system.

Introduction: The Parsortix® PC1 system, Food and Drug Administration (FDA) cleared for use in metastatic breast cancer (MBC) patients, is an epitope-independent microfluidic device for the capture and harvest of circulating tumor cells from whole blood based on cell size and deformability. This report details the analytical characterization of linearity, detection limit, precision, and reproducibility for this device. Methods: System performance was determined using K2-EDTA blood samples collected from self-declared healthy female volunteers (HVs) and MBC patients spiked with prelabeled cultured breast cancer cell lines (SKBR3, MCF7, or Hs578T). Samples were processed on Parsortix® PC1 systems and captured cells were harvested and enumerated. Results: The system captured and harvested live SKBR3, MCF7, and Hs578T cells and fixed SKBR3 cells linearly between 2 and ~100 cells, with average harvest rates of 69%, 73%, 79%, and 90%, respectively. To harvest ≥1 cell ≥95% of the time, the system required 3, 5 or 4 live SKBR3, MCF7 or Hs578T cells, respectively. Average harvest rates from precision studies using 5, 10, and ~50 live cells spiked into blood for each cell line ranged from 63.5% to 76.2%, with repeatability and reproducibility percent coefficient of variation (%CV) estimates ranging from 12.3% to 32.4% and 13.3% to 34.1%, respectively. Average harvest rates using ~20 fixed SKBR3 cells spiked into HV and MBC patient blood samples were 75.0% ± 16.1% (%CV = 22.3%) and 68.4% ± 14.3% (%CV = 21.1%), respectively. Conclusions: These evaluations demonstrate the Parsortix® PC1 system linearly and reproducibly harvests tumor cells from blood over a range of 1 to ~100 cells.

Human epididymis protein 4 offers superior specificity in the differentiation of benign and malignant adnexal masses in premenopausal women.

OBJECTIVE: We sought to assess the ability of human epididymis protein 4 (HE4) and CA-125 to distinguish among benign, borderline, and malignant pelvic masses in premenopausal women. STUDY DESIGN: We conducted a subset analysis of data from a prospective clinical trial that enrolled women undergoing surgery for an adnexal mass. Diagnostic performance of CA-125 and HE4 for epithelial ovarian cancer (EOC) detection in premenopausal women was determined. RESULTS: Of 229 premenopausal patients, 195 (85%) had benign masses, 18 (8%) had EOC, and 16 (7%) had borderline ovarian tumor. The sensitivity of CA-125 and HE4 for EOC detection was 83.3% and 88.9%, respectively. The specificity of CA-125 and HE4 was 59.5% and 91.8%, respectively. A normal HE4 level ruled out invasive cancer in 98% of women with an elevated CA-125. CONCLUSION: HE4 offers superior specificity compared to CA-125 for the differentiation of benign and malignant adnexal masses in premenopausal women.

Nuclear roundness variance predicts prostate cancer progression, metastasis, and death: A prospective evaluation with up to 25 years of follow-up after radical prostatectomy.

BACKGROUND: Nuclear structure is often altered in cancer due to spatial rearrangements of chromatin organization via activation of oncogenes and other chromatin remodeling genes. Therefore, we evaluated the prognostic value of nuclear roundness variance (NRV) for prostate cancer (PCa) progression, metastasis and PCa-specific death free survivals in a cohort of 116 men after radical prostatectomy (RP). METHOD: NRV was calculated for each case using the variance of the nuclear roundness from approximately 150 nuclei captured at a magnification of 2,440x for each case in 1992-1993. $${\rm Nuclear}\,{\rm roundness} = {{{\rm Radius}({\rm circumference})} \over {{\rm radius}({\rm area})}} = {R \over r} = {{P/2\pi } \over {\sqrt {A/\pi } }}$$ NRV data were merged with clinical, pathologic, and follow-up data for all patients in 2009. Cox proportional hazards regression and Kaplan-Meier plots were employed to analyze the data. RESULTS: Median follow-up time after RP for all patients was 19 years (range: 1-25 years, mean: 17 years), with approximately 92% (107/116), 71% (82/116), and 47% (55/116) patients having >or=10, 15, and 20 years of follow-up, respectively. NRV was the most significant parameter for prediction of all three outcomes and its concordance-index (C-Index) increased from progression (0.7080) to metastasis (0.7332) to PCa-specific death (0.8090) free survival predictions. Of note, NRV C-Index was significantly higher compared to Gleason Score C-Index for metastasis (0.7332 vs. 0.6046; P = 0.027) and PCa-specific death (0.8090 vs. 0.6336; P = 0.004) free survival predictions. However, the difference between NRV and Gleason Score C-Indexes was not statistically significant for progression free survival prediction (0.7080 vs. 0.6463; P = 0.106). CONCLUSION: NRV is valuable nuclear structural feature that exceeds Gleason score to predict an aggressive phenotype of PCa.

Comparison of a novel multiple marker assay vs the Risk of Malignancy Index for the prediction of epithelial ovarian cancer in patients with a pelvic mass.

OBJECTIVE: We sought to compare the Risk of Malignancy Index (RMI) to the Risk of Ovarian Malignancy Algorithm (ROMA) to predict epithelial ovarian cancer (EOC) in women with a pelvic mass. STUDY DESIGN: In all, 457 women with imaging results from ultrasound, computed tomography, magnetic resonance imaging, and serum HE4 and CA125 determined prior to surgery for pelvic mass were evaluable. RMI values were determined using CA125, imaging score, and menopausal status. ROMA values were determined using HE4, CA125, and menopausal status. RESULTS: At a set specificity of 75%, ROMA had a sensitivity of 94.3% and RMI had a sensitivity of 84.6% for distinguishing benign status from EOC (P = .0029). In patients with stage I and II disease, ROMA achieved a sensitivity of 85.3% compared with 64.7% for RMI (P < .0001). CONCLUSION: The dual marker algorithm utilizing HE4 and CA125 to calculate a ROMA value achieves a significantly higher sensitivity for identifying women with EOC than does RMI.

Characterization of RNA-Binding Motif 3 (RBM3) Protein Levels and Nuclear Architecture Changes in Aggressive and Recurrent Prostate Cancer.

Background: The RNA-binding motif protein 3 (RBM3) has been shown to be up-regulated in several types of cancer, including prostate cancer (PCa), compared to normal tissues. Increased RBM3 nuclear expression has been linked to improved clinical outcomes. Aims: Given that RBM3 has been hypothesized to play a role in critical nuclear functions such as chromatin remodeling, DNA damage response, and other post-transcriptional processes, we sought to: (1) quantify RBM3 protein levels in archival PCa samples; (2) develop a nuclear morphometric model to determine if measures of RBM3 protein levels and nuclear features could be used to predict disease aggressiveness and biochemical recurrence. Methods & Results: This study utilized two tissue microarrays (TMAs) stained for RBM3 that included 80 total cases of PCa stratified by Gleason score. A software-mediated image processing algorithm identified RBM3-positive cancerous nuclei in the TMA samples and calculated twenty-two features quantifying RBM3 expression and nuclear architecture. Multivariate logistic regression (MLR) modeling was performed to determine if RBM3 levels and nuclear structural changes could predict PCa aggressiveness and biochemical recurrence (BCR). Leave-one-out cross validation (LOOCV) was used to provide insight on how the predictive capabilities of the feature set might behave with respect to an independent patient cohort to address issues such as model overfitting. RBM3 expression was found to be significantly downregulated in highly aggressive GS ≥ 8 PCa samples compared to other Gleason scores (P < 0.0001) and significantly down-regulated in recurrent PCa samples compared to non-recurrent samples (P = 0.0377). An eleven-feature nuclear morphometric MLR model accurately identified aggressive PCa, yielding a receiver operating characteristic area under the curve (ROC-AUC) of 0.90 (P < 0.0001) in the raw data set and 0.77 (95% CI: 0.83-0.97) for LOOCV testing. The same eleven-feature model was then used to predict recurrence, yielding a ROC-AUC of 0.92 (P = 0.0004) in the raw data set and 0.76 (95% CI: 0.64-0.87) for LOOCV testing. Conclusions: The RBM3 biomarker alone is a strong prognostic marker for the prediction of aggressive PCa and biochemical recurrence. Further, RBM3 appears to be down-regulated in aggressive and recurrent tumors.

A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass.

INTRODUCTION: Patients diagnosed with epithelial ovarian cancer (EOC) have improved outcomes when cared for at centers experienced in the management of EOC. The objective of this trial was to validate a predictive model to assess the risk for EOC in women with a pelvic mass. METHODS: Women diagnosed with a pelvic mass and scheduled to have surgery were enrolled on a multicenter prospective study. Preoperative serum levels of HE4 and CA125 were measured. Separate logistic regression algorithms for premenopausal and postmenopausal women were utilized to categorize patients into low and high risk groups for EOC. RESULTS: Twelve sites enrolled 531 evaluable patients with 352 benign tumors, 129 EOC, 22 LMP tumors, 6 non EOC and 22 non ovarian cancers. The postmenopausal group contained 150 benign cases of which 112 were classified as low risk giving a specificity of 75.0% (95% CI 66.9-81.4), and 111 EOC and 6 LMP tumors of which 108 were classified as high risk giving a sensitivity of 92.3% (95% CI=85.9-96.4). The premenopausal group had 202 benign cases of which 151 were classified as low risk providing a specificity of 74.8% (95% CI=68.2-80.6), and 18 EOC and 16 LMP tumors of which 26 were classified as high risk, providing a sensitivity of 76.5% (95% CI=58.8-89.3). CONCLUSION: An algorithm utilizing HE4 and CA125 successfully classified patients into high and low risk groups with 93.8% of EOC correctly classified as high risk. This model can be used to effectively triage patients to centers of excellence.

Circulating tumor cells predict survival benefit from treatment in metastatic castration-resistant prostate cancer.

PURPOSE: A method for enumerating circulating tumor cells (CTC) has received regulatory clearance. The primary objective of this prospective study was to establish the relationship between posttreatment CTC count and overall survival (OS) in castration-resistant prostate cancer (CRPC). Secondary objectives included determining the prognostic utility of CTC measurement before initiating therapy, and the relationship of CTC to prostate-specific antigen (PSA) changes and OS at these and other time points. EXPERIMENTAL DESIGN: Blood was drawn from CRPC patients with progressive disease starting a new line of chemotherapy before treatment and monthly thereafter. Patients were stratified into predetermined Favorable or Unfavorable groups (<5 and > or =5 CTC/7.5mL). RESULTS: Two hundred thirty-one of 276 enrolled patients (84%) were evaluable. Patients with Unfavorable pretreatment CTC (57%) had shorter OS (median OS, 11.5 versus 21.7 months; Cox hazard ratio, 3.3; P < 0.0001). Unfavorable posttreatment CTC counts also predicted shorter OS at 2 to 5, 6 to 8, 9 to 12, and 13 to 20 weeks (median OS, 6.7-9.5 versus 19.6-20.7 months; Cox hazard ratio, 3.6-6.5; P < 0.0001). CTC counts predicted OS better than PSA decrement algorithms at all time points; area under the receiver operator curve for CTC was 81% to 87% and 58% to 68% for 30% PSA reduction (P = 0.0218). Prognosis for patients with (a) Unfavorable baseline CTC who converted to Favorable CTC improved (6.8 to 21.3 months); (b) Favorable baseline CTC who converted to Unfavorable worsened (>26 to 9.3 months). CONCLUSIONS: CTC are the most accurate and independent predictor of OS in CRPC. These data led to Food and Drug Administration clearance of this assay for the evaluation of CRPC.

Long-term assessment of prostate cancer progression free survival: evaluation of pathological parameters, nuclear shape and molecular biomarkers of pathogenesis.

BACKGROUND: Molecular pathways of proliferation, angiogenesis, neuroendocrine differentiation, apoptosis and alterations in nuclear structure of cancer epithelial cells are important in the pathogenesis of prostate cancer (PCa). Therefore, we evaluated the prognostic value of these parameters in 105 clinically localized PCa tumors with long-term follow-up after radical prostatectomy for progression-free survival (PFS). METHOD: Nuclear roundness variance (NRV) was calculated for tumor nuclei using the graphic tracing DynaCELL system. Immunohistochemistry assessed expression of Ki67, PCNA (proliferation), Chromogranin A (neuroendocrine differentiation), CD31 (angiogenesis), BCL2 (apoptosis), and Her-2/neu (oncogene) in the tumors. Cox proportional hazards regression, Spearman's rank correlation, and Kaplan-Meier plots were employed to analyze the data. RESULTS: Gleason score, focal vs. non-focal extra-prostatic extension, organ confined status, NRV, Her-2/neu, CD-31 and Ki67 were univariately significant predictors of PFS. NRV was the most significant prognostic indicator with the highest concordance index (0.7) for PFS. Gleason score, NRV and Her-2/neu were multivariately significant and yielded a concordance index of 0.77. CONCLUSION: Her-2/neu oncogene and NRV were shown to be significant in the prediction of PFS. The assessment of alterations in nuclear structure using NRV proved to be the most significant factor in the prediction of PFS. Integration of image analysis-based NRV and molecular biomarkers with pathologic parameters should be considered for validation in the prediction of PFS.

Prediction of prostate-specific antigen recurrence in men with long-term follow-up postprostatectomy using quantitative nuclear morphometry.

BACKGROUND: Nuclear morphometric signatures can be calculated using nuclear size, shape, DNA content, and chromatin texture descriptors [nuclear morphometric descriptor (NMD)]. We evaluated the use of a patient-specific quantitative nuclear grade (QNG) alone and in combination with routine pathologic features to predict biochemical [prostate-specific antigen (PSA)] recurrence-free survival in patients with prostate cancer. METHODS: The National Cancer Institute Cooperative Prostate Cancer Tissue Resource (NCI-CPCTR) tissue microarray was prepared from radical prostatectomy cases treated in 1991 to 1992. We assessed 112 cases (72 nonrecurrences and 40 PSA recurrences) with long-term follow-up. Images of Feulgen DNA-stained nuclei were captured and the NMDs were calculated using the AutoCyte system. Multivariate logistic regression was used to calculate QNG and pathology-based solutions for prediction of PSA recurrence. Kaplan-Meier survival curves and predictive probability graphs were generated. RESULTS: A QNG signature using the variance of 14 NMDs yielded an area under the receiver operator characteristic curve (AUC-ROC) of 80% with a sensitivity, specificity, and accuracy of 75% at a predictive probability threshold of > or =0.39. A pathology model using the pathologic stage and Gleason score yielded an AUC-ROC of 67% with a sensitivity, specificity, and accuracy of 70%, 50%, and 57%, respectively, at a predictive probability threshold of > or =0.35. Combining QNG, pathologic stage, and Gleason score yielded a model with an AUC-ROC of 81% with a sensitivity, specificity, and accuracy of 75%, 78%, and 77%, respectively, at a predictive probability threshold of > or =0.34. CONCLUSIONS: PSA recurrence is more accurately predicted using the QNG signature compared with routine pathology information alone. Inclusion of a morphometry signature, routine pathology, and new biomarkers should improve the prognostic value of information collected at surgery.

Utility of a novel serum tumor biomarker HE4 in patients with endometrioid adenocarcinoma of the uterus.

OBJECTIVE: Tumor markers with increased sensitivity and specificity for endometrial cancer are needed to help monitor response to therapy and to detect recurrent disease. Currently, the tumor maker CA125 is utilized in this role with limited value. The objectives of this study were to examine the levels of several novel tumor markers HE4, SMRP, CA72.4 and CA125 as potential markers in patients diagnosed with endometrioid adenocarcinoma of the uterus. METHODS: Pre-operative serum samples from surgically staged patients with endometrioid adenocarcinoma of the uterus were analyzed for levels of HE4, SMRP, CA72-4 and CA125. Control samples were obtained from healthy postmenopausal women. Logistic regression models and receiver operating characteristic (ROC) curves were constructed for each tumor marker and for all combinations, with cross-validation analyses to obtain average sensitivities at set specificities of 90%, 95%, and 98%. RESULTS: Serum samples from 156 healthy subjects and 171 patients with endometrial cancer (122 stage I, 17 stage II, 26 stage III, and 6 stage IV) were analyzed. At a 95% specificity, the sensitivities for differentiating between healthy subjects and all stages of cancer were 45.5% for HE4 and 24.6% for CA125. For stage I disease, HE4 yielded a 17.1% improvement in sensitivity compared with CA125. CONCLUSION: HE4 is elevated in all stages of endometrial can100cer and is more sensitive in early-stage endometrial cancer compared to CA125. Further investigation of HE4 as a marker for early detection of recurrent endometrial cancer and monitoring response to therapy is warranted.

The use of multiple novel tumor biomarkers for the detection of ovarian carcinoma in patients with a pelvic mass.

OBJECTIVES: The CA125 tumor marker is used to help predict the presence of ovarian cancer in patients with an adnexal mass. Because elevated CA125 levels occur in many benign gynecologic conditions, we set out to identify other novel biomarkers that would increase the sensitivity and specificity of CA125. METHODS: Serum and urine samples were obtained preoperatively from women undergoing surgery for an adnexal mass. The samples were analyzed for levels of CA125, SMRP, HE4, CA72-4, activin, inhibin, osteopontin, epidermal growth factor (EGFR), and ERBB2 (Her2) and were compared to final pathology results. Logistic regression models were estimated for all markers and combinations, with cross-validation analysis performed to obtain the sensitivities at set specificities of 90%, 95%, and 98%. RESULTS: Two hundred and fifty-nine patients with adnexal masses were enrolled. Of these, 233 patients were eligible for analysis with 67 invasive epithelial ovarian cancers and 166 benign ovarian neoplasms. Mean values for all marker levels except Her2 differed significantly between patients with benign masses and cancer. As a single marker, HE4 had the highest sensitivity at 72.9% (specificity 95%). Comparatively, combined CA125 and HE4 yielded the highest sensitivity at 76.4% (specificity 95%), with additional markers adding minimally to the sensitivity of this combination. HE4 was the best single marker for Stage I disease, with no increase in sensitivity when combined with CA125 or any other marker. CONCLUSIONS: As a single tumor marker, HE4 had the highest sensitivity for detecting ovarian cancer, especially Stage I disease. Combined CA125 and HE4 is a more accurate predictor of malignancy than either alone.

Circulating tumor cells, disease progression, and survival in metastatic breast cancer.

BACKGROUND: We tested the hypothesis that the level of circulating tumor cells can predict survival in metastatic breast cancer. METHODS: In a prospective, multicenter study, we tested 177 patients with measurable metastatic breast cancer for levels of circulating tumor cells both before the patients were to start a new line of treatment and at the first follow-up visit. The progression of the disease or the response to treatment was determined with the use of standard imaging studies at the participating centers. RESULTS: Outcomes were assessed according to levels of circulating tumor cells at baseline, before the patients started a new treatment for metastatic disease. Patients in a training set with levels of circulating tumor cells equal to or higher than 5 per 7.5 ml of whole blood, as compared with the group with fewer than 5 circulating tumor cells per 7.5 ml, had a shorter median progression-free survival (2.7 months vs. 7.0 months, P<0.001) and shorter overall survival (10.1 months vs. >18 months, P<0.001). At the first follow-up visit after the initiation of therapy, this difference between the groups persisted (progression-free survival, 2.1 months vs. 7.0 months; P<0.001; overall survival, 8.2 months vs. >18 months; P<0.001), and the reduced proportion of patients (from 49 percent to 30 percent) in the group with an unfavorable prognosis suggested that there was a benefit from therapy. The multivariate Cox proportional-hazards regression showed that, of all the variables in the statistical model, the levels of circulating tumor cells at baseline and at the first follow-up visit were the most significant predictors of progression-free and overall survival. CONCLUSIONS: The number of circulating tumor cells before treatment is an independent predictor of progression-free survival and overall survival in patients with metastatic breast cancer.