Accurate prostate cancer detection based on enrichment and characterization of prostate cancer specific circulating tumor cells

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood

INTRODUCTION

We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood.

MATERIALS AND METHODS

We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47).

RESULTS

A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%.

CONCLUSION

A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

Liquid Biopsy for Detection of Pancreaticobiliary Cancers by Functional Enrichment and Immunofluorescent Profiling of Circulating Tumor Cells and Their Clusters

Circulating tumor cells (CTCs) have historically been used for prognostication in oncology. We evaluate the performance of liquid biopsy CTC assay as a diagnostic tool in suspected pancreaticobiliary cancers (PBC). The assay utilizes functional enrichment of CTCs followed by immunofluorescent profiling of organ-specific markers. The performance of the assay was first evaluated in a multicentric case-control study of blood samples from 360 participants, including 188 PBC cases (pre-biopsy samples) and 172 healthy individuals. A subsequent prospective observational study included pre-biopsy blood samples from 88 individuals with suspicion of PBC and no prior diagnosis of cancer. CTCs were harvested using a unique functional enrichment method and used for immunofluorescent profiling for CA19.9, Maspin, EpCAM, CK, and CD45, blinded to the tissue histopathological diagnosis. TruBlood® malignant or non-malignant predictions were compared with tissue diagnoses to establish sensitivity and specificity. The test had 95.9% overall sensitivity (95% CI: 86.0-99.5%) and 92.3% specificity (95% CI: 79.13% to 98.38%) to differentiate PBC (n = 49) from benign conditions (n = 39). The high accuracy of the CTC-based TruBlood test demonstrates its potential clinical application as a diagnostic tool to assist the effective detection of PBC when tissue sampling is unviable or inconclusive.

Profiling of circulating glial cells for accurate blood-based diagnosis of glial malignancies

Here, we describe a blood test for the detection of glial malignancies (GLI-M) based on the identification of circulating glial cells (CGCs). The test is highly specific for GLI-M and can detect multiple grades (II-IV) and subtypes including gliomas, astrocytomas, oligodendrogliomas, oligoastrocytomas and glioblastomas, irrespective of gender and age. Analytical validation of the test was performed as per Clinical and Laboratory Standards Institute (CLSI) guidelines. Real-world performance characteristics of the test were evaluated in four clinical (observational) studies. The test has high analytical sensitivity (95%), specificity (100%) and precision (coefficient of variation [CV] = 13.7% for repeatability and CV = 23.5% for within laboratory precision, both at the detection threshold) and is not prone to interference from common drugs and serum factors. The ability of the test to detect and differentiate GLI-M from non-malignant brain tumours (NBT), brain metastases from primary epithelial malignancies (EPI-M) and healthy individual donors (HD) was evaluated in four clinical cohorts. Across these clinical studies, the test showed 99.35% sensitivity (95% confidence interval [CI]: 96.44%-99.98%) and 100% specificity (95% CI: 99.37%-100%). The performance characteristics of this test support its clinical utility for diagnostic triaging of individuals presenting with intracranial space-occupying lesions (ICSOL).

Multi-Cancer Early Detection: The New Frontier in Cancer Early Detection

The new generation of cancer early detection tests holds remarkable promise for revolutionizing and changing the paradigm of cancer early detection. Dozens of cancer early detection tests are being developed and evaluated. Some are already commercialized and available for use, most as a complement to and not in place of existing recommended cancer screening tests. This review evaluates existing single- and multi-cancer early detection tests (MCEDs), discussing their performance characteristics including sensitivity, specificity, positive and negative predictive values, and accuracy. It also critically looks at the potential harms that could result from these tests, including false positive and negative results, the risk of overdiagnosis and overtreatment, psychological and economic harms, and the risk of widening cancer inequities. We also review the large-scale, population-based studies that are being launched in the United States and United Kingdom to determine the impact of MCEDs on clinically relevant outcomes and implications for current practice.