A Multi-Center Clinical Study to Harvest and Characterize Circulating Tumor Cells from Patients with Metastatic Breast Cancer Using the Parsortix® PC1 System.

Circulating tumor cells (CTCs) captured from the blood of cancer patients may serve as a surrogate source of tumor material that can be obtained via a venipuncture (also known as a liquid biopsy) and used to better understand tumor characteristics. However, the only FDA-cleared CTC assay has been limited to the enumeration of surface marker-defined cells and not further characterization of the CTCs. In this study, we tested the ability of a semi-automated device capable of capturing and harvesting CTCs from peripheral blood based on cell size and deformability, agnostic of cell-surface markers (the Parsortix® PC1 System), to yield CTCs for evaluation by downstream techniques commonly available in clinical laboratories. The data generated from this study were used to support a De Novo request (DEN200062) for the classification of this device, which the FDA recently granted. As part of a multicenter clinical trial, peripheral blood samples from 216 patients with metastatic breast cancer (MBC) and 205 healthy volunteers were subjected to CTC enrichment. A board-certified pathologist enumerated the CTCs from each participant by cytologic evaluation of Wright-Giemsa-stained slides. As proof of principle, cells harvested from a concurrent parallel sample provided by each participant were evaluated using one of three additional evaluation techniques: molecular profiling by qRT-PCR, RNA sequencing, or cytogenetic analysis of HER2 amplification by FISH. The study demonstrated that the Parsortix® PC1 System can effectively capture and harvest CTCs from the peripheral blood of MBC patients and that the harvested cells can be evaluated using orthogonal methodologies such as gene expression and/or Fluorescence In Situ Hybridization (FISH).

Stacking Machine Learning Algorithms for Biomarker-Based Preoperative Diagnosis of a Pelvic Mass.

OBJECTIVE: To identify the most predictive parameters of ovarian malignancy and develop a machine learning (ML) based algorithm to preoperatively distinguish between a benign and malignant pelvic mass. METHODS: Retrospective study of 70 predictive parameters collected from 140 women with a pelvic mass. The women were split into a 3:1 "training" to "testing" dataset. Feature selection was performed using Gini impurity through an embedded random forest model and principal component analysis. Nine unique ML classifiers were assessed across a variety of model-specific hyperparameters using 25 bootstrap resamples of the training data. Model predictions were then combined into an ensemble stack by LASSO regression. The final ensemble stack and individual classifiers were then applied to the testing dataset to assess model performance. RESULTS: Feature selection identified HE4, CA125, and transferrin as three predictive parameters of malignancy. Assessment of the ensemble stack on the testing dataset outperformed all individual ML classifiers in predicting malignancy. The ensemble stack demonstrated an accuracy of 97.1%, a receiver operating characteristic (ROC) area under the curve (AUC) of 0.951, and a sensitivity of 93.3% with a specificity of 100%. CONCLUSIONS: Combining the measurement of three distinct biomarkers with the stacking of multiple ML classifiers into an ensemble can provide valuable preoperative diagnostic predictions for patients with a pelvic mass.

Volatile organic compounds at two oil and natural gas production well pads in Colorado and Texas using passive samplers.

UNLABELLED: A pilot study was conducted in application of the U.S. Environmental Protection Agency (EPA) Methods 325A/B variant for monitoring volatile organic compounds (VOCs) near two oil and natural gas (ONG) production well pads in the Texas Barnett Shale formation and Colorado Denver-Julesburg Basin (DJB), along with a traffic-dominated site in downtown Denver, CO. As indicated in the EPA method, VOC concentrations were measured for 14-day sampling periods using passive-diffusive tube samplers with Carbopack X sorbent at fenceline perimeter and other locations. VOCs were significantly higher at the DJB well pad versus the Barnett well pad and were likely due to higher production levels at the DJB well pad during the study. Benzene and toluene were significantly higher at the DJB well pad versus downtown Denver. Except for perchloroethylene, VOCs measured at passive sampler locations (PSs) along the perimeter of the Barnett well pad were significantly higher than PSs farther away. At the DJB well pad, most VOC concentrations, except perchloroethylene, were significantly higher prior to operational changes than after these changes were made. Though limited, the results suggest passive samplers are precise (duplicate precision usually ≤10%) and that they can be useful to assess spatial gradients and operational conditions at well pad locations over time-integrated periods. IMPLICATIONS: Recently enacted EPA Methods 325A/B use passive-diffusive tube samplers to measure benzene at multiple fenceline locations at petrochemical refineries. This pilot study presents initial data demonstrating the utility of Methods 325A/B for monitoring at ONG facilities. Measurements revealed elevated concentrations reflective of production levels and spatial gradients of VOCs relative to source proximity at the Barnett well pad, as well as operational changes at the DJB well pad. Though limited, these findings indicate that Methods 325A/B can be useful in application to characterize VOCs at well pad boundaries.

p300 (histone acetyltransferase) biomarker predicts prostate cancer biochemical recurrence and correlates with changes in epithelia nuclear size and shape.

BACKGROUND: p300 impacts the transcription of several genes involved in key pathways critical to PCa progression. Therefore, we evaluated the prognostic value of p300 expression and its correlation with nuclear alterations seen in tumor cells in men with long-term follow-up after radical prostatectomy (RP). METHODS: NCI Cooperative Prostate Cancer Tissue Resource tissue microarray cores of 92 RP cases (56 non-recurrences and 36 PSA recurrences) were utilized for the study. p300 expression was assessed by quantitative immunohistochemistry and nuclear alterations in Feulgen-stained nuclei were evaluated by digital image analysis using the AutoCyte Pathology Workstation. Cox proportional hazards regression, Spearman's rank correlation, and Kaplan-Meier plots were employed to analyze the data. RESULTS: p300 expression significantly correlated with nuclear alterations seen in tumor cells; specifically with circular form factor (P = 0.012) and minimum feret (P = 0.048). p300 expression in high grade tumors (Gleason score >or=7) was significantly higher compared to low grade tumors (Gleason score <7) [17.7% versus 13.7%, respectively, P = 0.03]. TNM stage, Gleason score, and p300 expression were univariately significant in the prediction of PCa biochemical recurrence-free survival (P or=7 and p300 expression >24% showed the highest risk for PCa biochemical recurrence (P = 0.002). CONCLUSIONS: p300 expression correlates with nuclear alterations seen in tumor cells and has prognostic value in predicting long-term PCa biochemical recurrence-free survival.

Significant variations in nuclear structure occur between and within Gleason grading patterns 3, 4, and 5 determined by digital image analysis.

BACKGROUND: Alterations in nuclei structure and DNA content captured from Gleason grading patterns 3, 4 and 5 of radical prostatectomy (RP) cases were determined by a computer-assisted microscope. Quantitative Nuclear Morphometry (QNM) profiles were created to evaluate variability in nuclear structure within each of these grades. METHODS: A tissue microarray (TMA) was constructed using RP cases and the prostate cancer (PCa) TMA cores prepared from 20 GG-3, 9 GG-4, 10 GG-5 patterns, and 20 benign cancer-adjacent cases from RP archival paraffin blocks. Feulgen-stained nuclei were captured from 0.6 mm spots using the AutoCyte system. Pools of 1100 nuclei captured from each test group were used to calculate Multivariate Logistic Regression (MLR) models that generated predictive indices and predictive probabilities (PP) to make comparisons between and within each set of pooled nuclei. RESULTS: A single QNM profiles yielded areas of receiver operator characteristic curves (ROC) that distinguished differences among benign cancer-adjacent nuclei and GG-3 (ROC-AUC = 0.78); GG-4 (ROC-AUC = 0.86) and GG-5 (ROC-AUC = 0.88) with accuracies of 73%, 78% and 80% respectively. Applying PP plots generated from MLR models of GG 3, 4, and 5 nuclei clearly demonstrated marked heterogeneity within each of these three GG patterns. CONCLUSIONS: QNM signatures illustrate alterations in nuclei structure, based upon nuclear morphometry within each of these three GG patterns, and might signify potential variations in PCa disease risk of progression outcomes. In the future a modified system of Gleason grading that considers not only glandular architecture but also quantitative nuclear grade may ensure accuracy in prognosis.

A G protein/cAMP signal cascade is required for axonal convergence into olfactory glomeruli.

The mammalian odorant receptors (ORs) comprise a large family of G protein-coupled receptors that are critical determinants of both the odorant response profile and the axonal identity of the olfactory sensory neurons in which they are expressed. Although the pathway by which ORs activate odor transduction is well established, the mechanism by which they direct axons into proper glomerular relationships remains unknown. We have developed a gain-of-function approach by using injection of retroviral vectors into the embryonic olfactory epithelium to study the ORs' contribution to axon guidance. By ectopically expressing ORs, we demonstrate that functional OR proteins induce axonal coalescence. Furthermore, ectopic expression of Galpha mutants reveals that activation of the signal transduction cascade is sufficient to cause axonal convergence into glomeruli. Analysis of Galpha subunit expression indicates that development and odorant transduction use separate transduction pathways. Last, we establish that the generation of cAMP through adenylyl cyclase 3 is necessary to establish proper axonal identity. Our data point to a model in which axonal sorting is accomplished by OR stimulation of cAMP production by coupling to Galphas.

Can prostate specific antigen derivatives and pathological parameters predict significant change in expectant management criteria for prostate cancer?

PURPOSE: A prior report established that pretreatment criteria based on clinical and biopsy pathology parameters can predict men who harbor small volume prostate cancer who might be followed expectantly. However, some of these men will exhibit disease progression with time and will need definitive therapy. To detect those in whom disease may progress, repeat prostate biopsies are performed at yearly intervals. Therefore, we determined whether biomarkers could be used to determine those in whom disease is likely to progress and thus those who require definitive therapy. MATERIALS AND METHODS: Initial and repeat biopsy information along with transrectal ultrasound measurements of gland volume, total prostate specific antigen (PSA), %free PSA (%fPSA) and total PSA velocity were evaluated in 78 men, 45 from the prior study, in whom disease was being managed expectantly. Univariate and multivariate logistic regression analyses determined variables that predicted a favorable tumor burden based on biopsy pathology status at each subsequent repeat biopsy. A Cox proportional hazards model was produced using 67 of 78 evaluable cases having adequate temporal data to predict hazard ratios for conversion from favorable to unfavorable tumor burden status. RESULTS: At time zero for 78 patients %fPSA, total PSA, and gland volume univariately and multivariately differentiated unfavorable and favorable tumor burden groups (p <0.05). The receiver operator characteristic area under the curve (ROC-AUC) was 83%. At the first followup biopsy 17 of 67 (25.4%) men converted to unfavorable tumor burden status. The %fPSA, PSA velocity and gland volume univariately distinguished these 2 groups (p <0.05) with 82% ROC-AUC. At second repeat biopsy 6 of 36 (16.7%) men converted to unfavorable tumor burden status and the ROC-AUC was 76%. Of the 14 men who had a third repeat biopsy all demonstrated favorable tumor burden status. A Cox proportional hazards model stratified the 67 of 78 men into high (48) and low risk (19) groups based on %fPSA at a 20% cutoff (p <0.01). Classification and regression tree analysis using logistic regression multivariately selected variables predicted favorable tumor burden status with an accuracy that ranged from 75% to 84% during our study. CONCLUSIONS: PSA velocity, %fPSA and gland volume information improves the prediction of men undergoing expectant management who are more likely to have small volume disease based on a 12-core biopsy interpretation within the time of our observations. %fPSA proved to be a valuable marker to stratify the 2 risk groups. Therefore, based on these factors it may be possible to consider deferment of repeat prostate biopsy until adverse results are detected. This rational approach to the management of prostate cancer in older men with small volume cancer seems to be a reasonable strategy.