BACKGROUND: Although enumeration of circulating tumor cells (CTCs) has shown some clinical value, the pool of CTCs contains a mixture of cells that contains additional information that can be extracted. The authors subclassified CTCs by shape features focusing on nuclear size and related this with clinical information.METHODS: A total of 148 blood samples were obtained from 57 patients with prostate cancer across the spectrum of metastatic states: no metastasis, nonvisceral metastasis, and visceral metastasis. CTCs captured and enumerated on NanoVelcro Chips (CytoLumina, Los Angeles, Calif) were subjected to pathologic review including nuclear size. The distribution of nuclear size was analyzed using a Gaussian mixture model. Correlations were made between CTC subpopulations and metastatic status.RESULTS: Statistical modeling of nuclear size distribution revealed 3 distinct subpopulations: large nuclear CTCs, small nuclear CTCs, and very small nuclear CTCs (vsnCTCs). Small nuclear CTCs and vsnCTC identified those patients with metastatic disease. However, vsnCTC counts alone were found to be elevated in patients with visceral metastases when compared with those without (0.36 ± 0.69 vs 1.95 ± 3.77 cells/mL blood; P<.001). Serial enumeration studies suggested the emergence of vsnCTCs occurred before the detection of visceral metastases.CONCLUSIONS: There are morphologic subsets of CTCs that can be identified by fundamental pathologic approaches, such as nuclear size measurement. The results of this observational study strongly suggest that CTCs contain relevant information regarding disease status. In particular, the detection of vsnCTCs was found to be correlated with the presence of visceral metastases and should be formally explored as a putative blood‐borne biomarker to identify patients at risk of developing this clinical evolution of prostate cancer. Cancer 2015;121:3240–3251. © 2015 American Cancer Society.

A comparison of isolated circulating tumor cells and tissue biopsies using whole-genome sequencing in prostate cancer

In recent years, new therapeutic options have become available for prostate cancer (PC) patients, generating an urgent need for better biomarkers to guide the choice of therapy and monitor treatment response. Liquid biopsies, including circulating tumor cells (CTCs), circulating nucleic acids, and exosomes, have been developed as minimally invasive assays allowing oncologists to monitor PC patients with real-time cellular or molecular information. While CTC counts remain the most extensively validated prognostic biomarker to monitor treatment response, recent advances demonstrate that CTC morphology and androgen receptor characterization can provide additional information to guide the choice of treatment. Characterization of cell-free DNA (cfDNA) is another rapidly emerging field with novel technologies capable of monitoring the evolution of treatment relevant alterations such as those in DNA damage repair genes for poly (ADP-ribose) polymerase (PARP) inhibition. In addition, several new liquid biopsy fields are emerging, including the characterization of heterogeneity, CTC RNA sequencing, the culture and xenografting of CTCs, and the characterization of extracellular vesicles (EVs) and circulating microRNAs. This review describes the clinical utilization of liquid biopsies in the management of PC patients and emerging liquid biopsy technologies with the potential to advance personalized cancer therapy.

Integrating liquid biopsies of circulating tumor cells (CTCs) and cell-free DNA (cfDNA) with other minimally invasive measures may yield more comprehensive disease profiles. We evaluated the feasibility of concurrent cellular and molecular analysis of CTCs and cfDNA combined with radiomic analysis of CT scans from patients with metastatic castration-resistant PC (mCRPC). CTCs from 22 patients were enumerated, stained for PC-relevant markers, and clustered based on morphometric and immunofluorescent features using machine learning. DNA from single CTCs, matched cfDNA, and buffy coats was sequenced using a targeted amplicon cancer hotspot panel. Radiomic analysis was performed on bone metastases identified on CT scans from the same patients. CTCs were detected in 77% of patients and clustered reproducibly. cfDNA sequencing had high sensitivity (98.8%) for germline variants compared to WBC. Shared and unique somatic variants in PC-related genes were detected in cfDNA in 45% of patients (MAF > 0.1%) and in CTCs in 92% of patients (MAF > 10%). Radiomic analysis identified a signature that strongly correlated with CTC count and plasma cfDNA level. Integration of cellular, molecular, and radiomic data in a multi-parametric approach is feasible, yielding complementary profiles that may enable more comprehensive non-invasive disease modeling and prediction.