Cell State and Cell Type: Deconvoluting Circulating Tumor Cell Populations in Liquid Biopsies by Multi-Omics.

Bi-directional crosstalk between the tumor and the tumor microenvironment (TME) has been shown to increase the rate of tumor evolution and to play a key role in neoplastic progression, therapeutic resistance, and a patient's overall survival. Here, we set out to use a comprehensive liquid-biopsy analysis to study cancer and specific TME cells in circulation and their association with disease status. Cytokeratin+, CD45- circulating rare cells (CRCs) from nine breast and four prostate cancer patients were characterized through morphometrics, single-cell copy number analysis, and targeted multiplexed proteomics to delineate cancer cell lineage from other rare cells originating in the TME. We show that we can detect epithelial circulating tumor cells (EPI.CTC), CTCs undergoing epithelial-to-mesenchymal transition (EMT.CTC) and circulating endothelial cells (CECs) using a universal rare event detection platform (HDSCA). Longitudinal analysis of an index patient finds that CTCs are present at the time of disease progression, while CECs are predominately present at the time of stable disease. In a small cohort of prostate and breast cancer patients, we find high inter-patient and temporal intra-patient variability in the expression of tissue specific markers such as ER, HER2, AR, PSA and PSMA and EpCAM. Our study stresses the importance of the multi-omic characterization of circulating rare cells in patients with breast and prostate carcinomas, specifically highlighting overlapping and cell type defining proteo-genomic characteristics of CTCs and CECs.

Contrived Materials and a Data Set for the Evaluation of Liquid Biopsy Tests: A Blood Profiling Atlas in Cancer (BLOODPAC) Community Study.

The Blood Profiling Atlas in Cancer (BLOODPAC) Consortium is a collaborative effort involving stakeholders from the public, industry, academia, and regulatory agencies focused on developing shared best practices on liquid biopsy. This report describes the results from the JFDI (Just Freaking Do It) study, a BLOODPAC initiative to develop standards on the use of contrived materials mimicking cell-free circulating tumor DNA, to comparatively evaluate clinical laboratory testing procedures. Nine independent laboratories tested the concordance, sensitivity, and specificity of commercially available contrived materials with known variant-allele frequencies (VAFs) ranging from 0.1% to 5.0%. Each participating laboratory utilized its own proprietary evaluation procedures. The results demonstrated high levels of concordance and sensitivity at VAFs of >0.1%, but reduced concordance and sensitivity at a VAF of 0.1%; these findings were similar to those from previous studies, suggesting that commercially available contrived materials can support the evaluation of testing procedures across multiple technologies. Such materials may enable more objective comparisons of results on materials formulated in-house at each center in multicenter trials. A unique goal of the collaborative effort was to develop a data resource, the BLOODPAC Data Commons, now available to the liquid-biopsy community for further study. This resource can be used to support independent evaluations of results, data extension through data integration and new studies, and retrospective evaluation of data collection.

Multianalyte liquid biopsy to aid the diagnostic workup of breast cancer.

Breast cancer (BC) affects 1 in every 8 women in the United States and is currently the most prevalent cancer worldwide. Precise staging at diagnosis and prognosis are essential components for the clinical management of BC patients. In this study, we set out to evaluate the feasibility of the high-definition single cell (HDSCA) liquid biopsy (LBx) platform to stratify late-stage BC, early-stage BC, and normal donors using peripheral blood samples. Utilizing 5 biomarkers, we identified rare circulating events with epithelial, mesenchymal, endothelial and hematological origin. We detected a higher level of CTCs in late-stage patients, compared to the early-stage and normal donors. Additionally, we observed more tumor-associated large extracellular vesicles (LEVs) in the early-stage, compared to late-stage and the normal donor groups. Overall, we were able to detect reproducible patterns in the enumeration of rare cells and LEVs of cancer vs. normal donors and early-stage vs. late-stage BC with high accuracy, allowing for robust stratification. Our findings illustrate the feasibility of the LBx assay to provide robust detection of rare circulating events in peripheral blood draws and to stratify late-stage BC, early-stage BC, and normal donor samples.

Identification of epithelial and mesenchymal circulating tumor cells in clonal lineage of an aggressive prostate cancer case.

Little is known about the complexity and plasticity of circulating tumor cell (CTC) biology in different compartments of the fluid microenvironment during tumor metastasis. Here we integrated phenomics, genomics, and targeted proteomics to characterize CTC phenotypic and genotypic heterogeneity in paired peripheral blood (PB) and bone marrow aspirate (BMA) from a metastatic prostate cancer patient following the rapid disease progression, using the High-Definition Single Cell Assay 3.0 (HDSCA3.0). Uniquely, we identified a subgroup of genetically clonal CTCs that acquired a mesenchymal-like state and its presence was significantly associated with one subclone that emerged along the clonal lineage. Higher CTC abundance and phenotypic diversity were observed in the BMA than PB and differences in genomic alterations were also identified between the two compartments demonstrating spatial heterogeneity. Single cell copy number profiling further detected clonal heterogeneity within clusters of CTCs (also known as microemboli or aggregates) as well as phenotypic variations by targeted proteomics. Overall, these results identify epithelial and mesenchymal CTCs in the clonal lineage of an aggressive prostate cancer case and also demonstrate a single cell multi-omic approach to deconvolute the heterogeneity and association of CTC phenotype and genotype in multi-medium liquid biopsies of metastatic prostate cancer.

Platelet-Coated Circulating Tumor Cells Are a Predictive Biomarker in Patients with Metastatic Castrate-Resistant Prostate Cancer.

Metastatic castration-resistant prostate cancer (mCRPC) includes a subset of patients with particularly unfavorable prognosis characterized by combined defects in at least two of three tumor suppressor genes: PTEN, RB1, and TP53 as aggressive variant prostate cancer molecular signature (AVPC-MS). We aimed to identify circulating tumor cells (CTC) signatures that could inform treatment decisions of patients with mCRPC with cabazitaxel-carboplatin combination therapy versus cabazitaxel alone. Liquid biopsy samples were collected prospectively from 79 patients for retrospective analysis. CTCs were detected, classified, enumerated through a computational pipeline followed by manual curation, and subjected to single-cell genome-wide copy-number profiling for AVPC-MS detection. On the basis of immunofluorescence intensities, detected rare cells were classified into 8 rare-cell groups. Further morphologic characterization categorized CTC subtypes from 4 cytokeratin-positive rare-cell groups, utilizing presence of mesenchymal features and platelet attachment. Of 79 cases, 77 (97.5%) had CTCs, 24 (30.4%) were positive for platelet-coated CTCs (pc.CTCs) and 25 (38.5%) of 65 sequenced patients exhibited AVPC-MS in CTCs. Survival analysis indicated that the presence of pc.CTCs identified the subset of patients who were AVPC-MS-positive with the worst prognosis and minimal benefit from combination therapy. In AVPC-MS-negative patients, its presence showed significant survival improvement from combination therapy. Our findings suggest the presence of pc.CTCs as a predictive biomarker to further stratify AVPC subsets with the worst prognosis and the most significant benefit of additional platinum therapy. IMPLICATIONS: HDSCA3.0 can be performed with rare cell detection, categorization, and genomic characterization for pc.CTC identification and AVPC-MS detection as a potential predictive biomarker of mCRPC.

BloodPAC Data Commons for Liquid Biopsy Data.

PURPOSE: The Blood Profiling Atlas in Cancer (BloodPAC) Data Commons (BPDC) is being developed and is operated by the public-private BloodPAC Consortium to support the liquid biopsy community. It is an interoperable data commons with the ultimate aim of serving as a recognized source of valid scientific evidence for liquid biopsy assays for industry, academia, and standards and regulatory stakeholders. METHODS: The BPDC is implemented using the open source Gen3 data commons platform (https://gen3.org). In particular, the BPDC Data Exploration Portal, BPDC Data Submission Portal, the BPDC Workspace Hub, and the BloodPAC application programming interface (API) were all automatically generated from the BloodPAC Data Model using the Gen3 data commons platform. BPDC uses Gen3's implementation of the data commons framework services so that it can interoperate through secure, compliant APIs with other data commons using data commons framework service, such as National Cancer Institute's Cancer Research Data Commons. RESULTS: The BPDC contains 57 studies and projects spanning more than 4,100 cases. This amounts to 5,700 aliquots (blood plasma, serum, or a contrived sample) that have been subjected to a liquid biopsy assay, quantified, and then contributed by members of the BloodPAC Consortium. In all, there are more than 31,000 files in the commons as of December 2020. We describe the BPDC, the data it manages, the process that the BloodPAC Consortium used to develop it, and some of the applications that have been developed using its API. CONCLUSION: The BPDC has been the data platform used by BloodPAC during the past 4 years to manage the data for the consortium and to provide workspaces for its working groups.

Treatment response and tumor evolution: lessons from an extended series of multianalyte liquid biopsies in a metastatic breast cancer patient.

Currently, clinical characterization of metastatic breast cancer is based on tissue samples taken at time of diagnosis. However, tissue biopsies are invasive and tumors are continuously evolving, which indicates the need for minimally invasive longitudinal assessment of the tumor. Blood-based liquid biopsies provide minimal invasive means for serial sampling over the course of treatment and the opportunity to adjust therapies based on molecular markers. Here, we aim to identify cellular changes that occur in breast cancer over the lifespan of an affected patient through single-cell proteomic and genomic analysis of longitudinally sampled solid and liquid biopsies. Three solid and 17 liquid biopsies from peripheral blood of an ER+/HER2- metastatic breast cancer patient collected over 4 years and eight treatment regimens were analyzed for morphology, protein expression, copy-number alterations, and single-nucleotide variations. Analysis of 563 single morphometrically similar circulating tumor cells (CTCs) and 13 cell-free DNA (cfDNA) samples along with biopsies of the primary and metastatic tumor revealed progressive genomic evolution away from the primary tumor profiles, along with changes in ER expression and the appearance of resistance mutations. Both the abundance and the genomic alterations of CTCs and cfDNA were highly correlated and consistent with genomic alterations in the tissue samples. We demonstrate that genomic evolution and acquisition of drug resistance can be detected in real time and at single-cell resolution through liquid biopsy analytes and highlight the utility of liquid biopsies to guide treatment decisions.

Use of Wearable Activity Tracker in Patients With Cancer Undergoing Chemotherapy: Toward Evaluating Risk of Unplanned Health Care Encounters.

PURPOSE: Unplanned health care encounters (UHEs) such as emergency room visits can occur commonly during cancer chemotherapy treatments. Patients at an increased risk of UHEs are typically identified by clinicians using performance status (PS) assessments based on a descriptive scale, such as the Eastern Cooperative Oncology Group (ECOG) scale. Such assessments can be bias prone, resulting in PS score disagreements between assessors. We therefore propose to evaluate PS using physical activity measurements (eg, energy expenditure) from wearable activity trackers. Specifically, we examined the feasibility of using a wristband (band) and a smartphone app for PS assessments. METHODS: We conducted an observational study on a cohort of patients with solid tumor receiving highly emetogenic chemotherapy. Patients were instructed to wear the band for a 60-day activity-tracking period. During clinic visits, we obtained ECOG scores assessed by physicians, coordinators, and patients themselves. UHEs occurring during the activity-tracking period plus a 90-day follow-up period were later compiled. We defined our primary outcome as the percentage of patients adherent to band-wear ≥ 80% of 10 am to 8 pm for ≥ 80% of the activity-tracking period. In an exploratory analysis, we computed hourly metabolic equivalent of task (MET) and counted 10 am to 8 pm hours with > 1.5 METs as nonsedentary physical activity hours. RESULTS: Forty-one patients completed the study (56.1% female; 61.0% age 40-60 years); 68% were adherent to band-wear. ECOG score disagreement between assessors ranged from 35.3% to 50.0%. In our exploratory analysis, lower average METs and nonsedentary hours, but not higher ECOG scores, were associated with higher 150-day UHEs. CONCLUSION: The use of a wearable activity tracker is generally feasible in a similar population of patients with cancer. A larger randomized controlled trial should be conducted to confirm the association between lower nonsedentary hours and higher UHEs.

Quantified Kinematics to Evaluate Patient Chemotherapy Risks in Clinic.

PURPOSE: Performance status (PS) is a key factor in oncologic decision making, but conventional scales used to measure PS vary among observers. Consumer-grade biometric sensors have previously been identified as objective alternatives to the assessment of PS. Here, we investigate how one such biometric sensor can be used during a clinic visit to identify patients who are at risk for complications, particularly unexpected hospitalizations that may delay treatment or result in low physical activity. We aim to provide a novel and objective means of predicting tolerability to chemotherapy. METHODS: Thirty-eight patients across three centers in the United States who were diagnosed with a solid tumor with plans for treatment with two cycles of highly emetogenic chemotherapy were included in this single-arm, observational prospective study. A noninvasive motion-capture system quantified patient movement from chair to table and during the get-up-and-walk test. Activity levels were recorded using a wearable sensor over a 2-month period. Changes in kinematics from two motion-capture data points pre- and post-treatment were tested for correlation with unexpected hospitalizations and physical activity levels as measured by a wearable activity sensor. RESULTS: Among 38 patients (mean age, 48.3 years; 53% female), kinematic features from chair to table were the best predictors for unexpected health care encounters (area under the curve, 0.775 ± 0.029) and physical activity (area under the curve, 0.830 ± 0.080). Chair-to-table acceleration of the nonpivoting knee (t = 3.39; P = .002) was most correlated with unexpected health care encounters. Get-up-and-walk kinematics were most correlated with physical activity, particularly the right knee acceleration (t = -2.95; P = .006) and left arm angular velocity (t = -2.4; P = .025). CONCLUSION: Chair-to-table kinematics are good predictors of unexpected hospitalizations, whereas the get-up-and-walk kinematics are good predictors of low physical activity.

Single-Cell Circulating Tumor Cell Analysis Reveals Genomic Instability as a Distinctive Feature of Aggressive Prostate Cancer.

PURPOSE: Aggressive variant prostate cancer (AVPC) represents a clinical subset distinguished by therapy resistance and poor prognosis, linked to combined losses of the tumor suppressor genes (TSG) PTEN, RB1, and TP53. Circulating tumor cells (CTC) provide a minimally invasive opportunity for identification and molecular characterization of AVPC. We aimed to evaluate the incidence and clinical significance of compound (2+)TSG losses and genomic instability in prostate cancer CTC, and to expand the set genomic biomarkers relevant to AVPC. EXPERIMENTAL DESIGN: Genomic analysis of chromosomal copy-number alterations (CNA) at single-cell resolution was performed in CTC from patients with and without AVPC before initiating chemotherapy with cabazitaxel or cabazitaxel and carboplatin. We evaluated associations between single-CTC genomics and clinical features, progression-free survival, and overall survival. RESULTS: A total of 257 individual CTC were sequenced from 47 patients (1-22 CTC/patient). Twenty patients (42.6%) had concurrent 2+TSG losses in at least one CTC in association with poor survival and increased genomic instability, inferred by high large-scale transitions scores. Higher LST in CTC were independent of CTC enumerated, clinically more indicative of aggressive behavior than co-occurring TSG losses, and molecularly associated with gains in chromosomal regions including PTK2, Myc, and NCOA2; increased androgen receptor expression; and BRCA2 loss. In 57 patients with matched cell-free tumor DNA data, CTC were more frequently detectable and evaluable for CNA analysis (in 73.7% vs. 42.1%, respectively). CONCLUSIONS: Our findings suggest that genomic instability in CTC is a hallmark of advanced prostate cancer aggressiveness, and support single-CTC sequencing as a compelling tool to noninvasively characterize cancer heterogeneity.

Preanalytical Variables for the Genomic Assessment of the Cellular and Acellular Fractions of the Liquid Biopsy in a Cohort of Breast Cancer Patients.

Liquid biopsy allows assessment of multiple analytes, providing temporal information with potential for improving understanding of cancer evolution and clinical management of patients. Although liquid biopsies are intensely investigated for prediction and response monitoring, preanalytic variables are of primary concern for clinical implementation, including categories of collection method and sample storage. Herein, an integrated high-density single-cell assay workflow for morphometric and genomic analysis of the liquid biopsy is used to characterize the effects of preanalytical variation and reproducibility of data from a breast cancer cohort. Following prior work quantifying performance of commonly used blood collection tubes, this study completes the analysis of four time points to assay (24, 48, 72, and 96 hours), demonstrating precision up to 48 hours after collection for assay sensitivity, highly reproducible rare cell enumeration, morphometric characterization, and high efficiency and capacity for single-cell genomic analysis. For the cell-free analysis, both freezing and use of fresh plasma produced similar quality and quantity of cell-free DNA for sequencing. The genomic analysis (copy number variation and single-nucleotide variation) described herein is broadly applicable to liquid biopsy platforms capable of isolating cell-free and cell-based DNA. Morphometric parameters and genomic signatures of individual circulating tumor cells were evaluated in relation to patient clinical response, providing preliminary evidence of clinical validity as a potential biomarker aiding clinical diagnostics or monitoring progression.

Patient reported outcomes can improve performance status assessment: a pilot study.

BACKGROUND: Patient performance status is routinely used in oncology to estimate physical functioning, an important factor in clinical treatment decisions and eligibility for clinical trials. However, validity and reliability data for ratings of performance status have not been optimal. This study recruited oncology patients who were about to begin emetogenic palliative or adjuvant chemotherapy for treatment of solid tumors. We employed actigraphy as the gold standard for physical activity level. Correspondences between actigraphy and oncologists' and patients' ratings of performance status were examined and compared with the correspondences of actigraphy and several patient reported outcomes (PROs). The study was designed to determine feasibility of the measurement approaches and if PROs can improve the accuracy of assessment of performance status. METHODS: Oncologists and patients made performance status ratings at visit 1. Patients wore an actigraph and entered weekly PROs on a smartphone app. Data for days 1-14 after visit 1 were analyzed. Chart reviews were conducted to tabulate all unexpected medical events across days 1-150. RESULTS: Neither oncologist nor patient ratings of performance status predicted steps/hour (actigraphy). The PROMIS® Physical Function PRO (average of Days 1, 7, 14) was associated with steps/hour at high (for men) and moderate (for women) levels; the PROMIS® Fatigue PRO predicted steps for men, but not for women. Unexpected medical events occurred in 57% of patients. Only body weight in female patients predicted events; oncologist and patient performance status ratings, steps/hour, and other PROs did not. CONCLUSIONS: PROMIS® Physical Function and Fatigue PROs show good correspondence with steps/hour making them easy, useful tools for oncologists to improve their assessment of performance status, especially for male patients. Female patients had lower levels of steps/hour than males and lower correlations among the predictors, suggesting the need for further work to improve performance status assessment in women. Assessment of pre-morbid sedentary behavior alongside current Physical Functioning and Fatigue PROs may allow for a more valid determination of disease-related activity level and performance status.

Single cell correlation analysis of liquid and solid biopsies in metastatic colorectal cancer.

As cancer care is transitioning to personalized therapies with necessary complementary or companion biomarkers there is significant interest in determining to what extent non-invasive liquid biopsies reflect the gold standard solid biopsy. We have established an approach for measuring patient-specific circulating and solid cell concordance by introducing tumor touch preparations to the High-Definition Single Cell Analysis workflow for high-resolution cytomorphometric characterization of metastatic colorectal cancer (mCRC). Subgroups of cells based on size, shape and protein expression were identified in both liquid and solid biopsies, which overall displayed high inter- and intra- patient pleomorphism at the single-cell level of analysis. Concordance of liquid and solid biopsies was patient-dependent and between 0.1-0.9. Morphometric variables displayed particularly high correlation, suggesting that circulating cells do not represent distinct subpopulations from the solid tumor. This was further substantiated by significant decrease in concentration of circulating cells after mCRC resection. Combined with the association of circulating cells with tumor burden and necrosis of hepatic lesions, our overall findings demonstrate that liquid biopsy cells can be informative biomarkers in the mCRC setting. Patient-specific level of concordance can readily be measured to establish the utility of circulating cells as biomarkers and define biosignatures for liquid biopsy assays.

A new anion exchange purification method for Cu stable isotopes in blood samples.

The isotopic composition of iron, zinc, copper, and cadmium (δ56Fe, δ66Zn, δ65Cu, and δ114Cd) are novel and promising tools to study the metabolism and homeostasis of trace metals in the human body. Serum δ65Cu has been proposed as a potential tool for diagnosis of cancer in liquid biopsy, and other metals may have similar utility. However, accurate analysis of trace metal isotopes is challenging because of the difficulties in purifying the metals from biological samples. Here we developed a simple and rapid method for sequential purification of Cu, Fe, Zn, and Cd from a single blood plasma sample. By using a combination of 11 M acetic acid and 4 M HCl in the first steps of column chemistry on AG-MP1 resin, we dramatically improve the separation of Cu from matrix elements compared to previous methods which use concentrated HCl alone. Our new method achieves full recovery of Cu, Fe, Zn, and Cd to prevent column-induced isotope fractionation effects, and effectively separates analytes from the matrix in order to reduce polyatomic interferences during isotope analysis. Our methods were verified by the analysis of isotope standards, a whole blood reference material, and a preliminary sample set including five plasma samples from healthy individuals and five plasma samples from cancer patients. This new method simplifies preparation of blood samples for metal isotope analysis, accelerating multi-isotope approaches to medical studies and contributing to our understanding of the cycling of Fe, Zn, Cu, and Cd in the human body. Graphical abstract ᅟ.

Low-dimensional dynamical characterization of human performance of cancer patients using motion data.

BACKGROUND: Biomechanical characterization of human performance with respect to fatigue and fitness is relevant in many settings, however is usually limited to either fully qualitative assessments or invasive methods which require a significant experimental setup consisting of numerous sensors, force plates, and motion detectors. Qualitative assessments are difficult to standardize due to their intrinsic subjective nature, on the other hand, invasive methods provide reliable metrics but are not feasible for large scale applications. METHODS: Presented here is a dynamical toolset for detecting performance groups using a non-invasive system based on the Microsoft Kinect motion capture sensor, and a case study of 37 cancer patients performing two clinically monitored tasks before and after therapy regimens. Dynamical features are extracted from the motion time series data and evaluated based on their ability to i) cluster patients into coherent fitness groups using unsupervised learning algorithms and to ii) predict Eastern Cooperative Oncology Group performance status via supervised learning. FINDINGS: The unsupervised patient clustering is comparable to clustering based on physician assigned Eastern Cooperative Oncology Group status in that they both have similar concordance with change in weight before and after therapy as well as unexpected hospitalizations throughout the study. The extracted dynamical features can predict physician, coordinator, and patient Eastern Cooperative Oncology Group status with an accuracy of approximately 80%. INTERPRETATION: The non-invasive Microsoft Kinect sensor and the proposed dynamical toolset comprised of data preprocessing, feature extraction, dimensionality reduction, and machine learning offers a low-cost and general method for performance segregation and can complement existing qualitative clinical assessments.

Clonal diversity revealed by morphoproteomic and copy number profiles of single prostate cancer cells at diagnosis.

Tumor heterogeneity is prevalent in both treatment-naïve and end-stage metastatic castration-resistant prostate cancer (PCa), and may contribute to the broad range of clinical presentation, treatment response, and disease progression. To characterize molecular heterogeneity associated with de novo metastatic PCa, multiplatform single cell profiling was performed using high definition single cell analysis (HD-SCA). HD-SCA enabled morphoproteomic and morphogenomic profiling of single cells from touch preparations of tissue cores (prostate and bone marrow biopsies) as well as liquid samples (peripheral blood and bone marrow aspirate). Morphology, nuclear features, copy number alterations, and protein expression were analyzed. Tumor cells isolated from prostate tissue touch preparation (PTTP) and bone marrow touch preparation (BMTP) as well as metastatic tumor cells (MTCs) isolated from bone marrow aspirate were characterized by morphology and cytokeratin expression. Although peripheral blood was examined, circulating tumor cells were not definitively observed. Targeted proteomics of PTTP, BMTP, and MTCs revealed cell lineage and luminal prostate epithelial differentiation associated with PCa, including co-expression of EpCAM, PSA, and PSMA. Androgen receptor expression was highest in MTCs. Hallmark PCa copy number alterations, including PTEN and ETV6 deletions and NCOA2 amplification, were observed in cells within the primary tumor and bone marrow biopsy samples. Genomic landscape of MTCs revealed to be a mix of both primary and bone metastatic tissue. This multiplatform analysis of single cells reveals several clonal origins of metastatic PCa in a newly diagnosed, untreated patient with polymetastatic disease. This case demonstrates that real-time molecular profiling of cells collected through prostate and bone marrow biopsies is feasible and has the potential to elucidate the origin and evolution of metastatic tumor cells. Altogether, biological and genomic data obtained through longitudinal biopsies can be used to reveal the properties of PCa and can impact clinical management.

Multiplex protein detection on circulating tumor cells from liquid biopsies using imaging mass cytometry.

Molecular analysis of circulating and disseminated tumor cells (CTCs/DTCs) has great potential as a means for continuous evaluation of prognosis and treatment efficacy in near-real time through minimally invasive liquid biopsies. To realize this potential, however, methods for molecular analysis of these rare cells must be developed and validated. Here, we describe the integration of imaging mass cytometry (IMC) using metal-labeled antibodies as implemented on the Fluidigm Hyperion Imaging System into the workflow of the previously established High Definition Single Cell Analysis (HD-SCA) assay for liquid biopsies, along with methods for image analysis and signal normalization. Using liquid biopsies from a metastatic prostate cancer case, we demonstrate that IMC can extend the reach of CTC characterization to include dozens of protein biomarkers, with the potential to understand a range of biological properties that could affect therapeutic response, metastasis and immune surveillance when coupled with simultaneous phenotyping of thousands of leukocytes.

Effect of Blood Collection Tube Type and Time to Processing on the Enumeration and High-Content Characterization of Circulating Tumor Cells Using the High-Definition Single-Cell Assay.

CONTEXT: - As circulating tumor cell (CTC) assays gain clinical relevance, it is essential to address preanalytic variability and to develop standard operating procedures for sample handling in order to successfully implement genomically informed, precision health care. OBJECTIVE: - To evaluate the effects of blood collection tube (BCT) type and time-to-assay (TTA) on the enumeration and high-content characterization of CTCs by using the high-definition single-cell assay (HD-SCA). DESIGN: - Blood samples of patients with early- and advanced-stage breast cancer were collected into cell-free DNA (CfDNA), EDTA, acid-citrate-dextrose solution, and heparin BCTs. Time-to-assay was evaluated at 24 and 72 hours, representing the fastest possible and more routine domestic shipping intervals, respectively. RESULTS: - We detected the highest CTC levels and the lowest levels of negative events in CfDNA BCT at 24 hours. At 72 hours in this BCT, all CTC subpopulations were decreased with the larger effect observed in high-definition CTCs and cytokeratin-positive cells smaller than white blood cells. Overall cell retention was also optimal in CfDNA BCT at 24 hours. Whole-genome copy number variation profiles were generated from single cells isolated from all BCT types and TTAs. Cells from CfDNA BCT at 24-hour TTA exhibited the least noise. CONCLUSIONS: - Circulating tumor cells can be identified and characterized under a variety of collection, handling, and processing conditions, but the highest quality can be achieved with optimized conditions. We quantified performance differences of the HD-SCA for specific preanalytic variables that may be used as a guide to develop best practices for implementation into patient care and/or research biorepository processes.

Paired High-Content Analysis of Prostate Cancer Cells in Bone Marrow and Blood Characterizes Increased Androgen Receptor Expression in Tumor Cell Clusters.

Purpose: Recent studies demonstrate that prostate cancer clones from different metastatic sites are dynamically represented in the blood of patients over time, suggesting that the paired evaluation of tumor cells in circulation and bone marrow, the primary target for prostate cancer metastasis, may provide complementary information.Experimental Design: We adapted our single-cell high-content liquid biopsy platform to bone marrow aspirates (BMA) to concurrently identify and characterize prostate cancer cells in patients' blood and bone and thus discern features associated to tumorigenicity and dynamics of metastatic progression.Results: The incidence of tumor cells in BMAs increased as the disease advanced: 0% in biochemically recurrent (n = 52), 26% in newly diagnosed metastatic hormone-naïve (n = 26), and 39% in metastatic castration-resistant prostate cancer (mCRPC; n = 63) patients, and their number was often higher than in paired blood. Tumor cell detection in metastatic patients' BMAs was concordant but 45% more sensitive than using traditional histopathologic interpretation of core bone marrow biopsies. Tumor cell clusters were more prevalent and bigger in BMAs than in blood, expressed higher levels of the androgen receptor protein per tumor cell, and were prognostic in mCRPC. Moreover, the patterns of genomic copy number variation in single tumor cells in paired blood and BMAs showed significant inter- and intrapatient heterogeneity.Conclusions: Paired analysis of single prostate cancer cells in blood and bone shows promise for clinical application and provides complementary information. The high prevalence and prognostic significance of tumor cell clusters, particularly in BMAs, suggest that these structures are key mediators of prostate cancer's metastatic progression. Clin Cancer Res; 23(7); 1722-32. ©2016 AACR.