Circulating tumour cell enumeration, biomarker analyses, and kinetics in patients with colorectal cancer and other GI malignancies.

Objective: Most of the work in terms of liquid biopsies in patients with solid tumors is focused on circulating tumor DNA (ctDNA). Our aim was to evaluate the feasibility of using circulating tumor cells (CTCs) in peripheral blood samples from patients with advanced or metastatic gastrointestinal (GI) cancers. Methods: In this prospective study, blood samples were collected from each patient in 2 AccuCyte® blood collection tubes and each tube underwent CTC analysis performed utilizing the RareCyte® platform. The results from both tubes were averaged and a total of 150 draws were done, with 281 unique reported results. The cadence of sampling was based on convenience sampling and piggybacked onto days of actual clinical follow-ups and treatment visits. The CTC results were correlated with patient- and tumor-related variables. Results: Data from a total of 59 unique patients were included in this study. Patients had a median age of 58 years, with males representing 69% of the study population. More than 57% had received treatment prior to taking blood samples. The type of GI malignancy varied, with more than half the patients having colorectal cancer (CRC, 54%) followed by esophageal/gastric cancer (17%). The least common cancer was cholangiocarcinoma (9%). The greatest number of CTCs were found in patients with colorectal cancer (Mean: 15.8 per 7.5 ml; Median: 7.5 per 7.5 ml). In comparison, patients with pancreatic cancer (PC) had considerably fewer CTCs (Mean: 4.2 per 7.5 ml; Median: 3 per 7.5 ml). Additionally, we found that patients receiving treatment had significantly fewer CTCs than patients who were not receiving treatment (Median 2.7 versus 0.7). CTC numbers showed noteworthy disparities between patients with responding/stable disease in comparison to those with untreated/progressive disease (Median of 2.7 versus 0). When CTCs were present, biomarker analyses of the four markers human epidermal growth factor receptor 2 (HER2)/programmed death-ligand 1 (PD-L1)/Kiel 67 (Ki-67)/epidermal growth factor receptor (EGFR) was feasible. Single cell sequencing confirmed the tumor of origin. Conclusion: Our study is one of the first prospective real-time studies evaluating CTCs in patients with GI malignancies. While ctDNA-based analyses are more common in clinical trials and practice, CTC analysis provides complementary information from a liquid biopsy perspective that is of value and worthy of continued research.

Accurate isolation and detection of circulating tumor cells using enrichment-free multiparametric high resolution imaging.

Introduction: The reliable and accurate detection of rare circulating tumor cells (CTCs) from cancer patient blood samples promises advantages in both research and clinical applications. Numerous CTC detection methods have been explored that rely on either the physical properties of CTCs such as density, size, charge, and/or their antigen expression profiles. Multiple factors can influence CTC recovery including blood processing method and time to processing. This study aimed to examine the accuracy and sensitivity of an enrichment-free method of isolating leukocytes (AccuCyte® system) followed by immunofluorescence staining and high-resolution imaging (CyteFinder® instrument) to detect CTCs. Method: Healthy human blood samples, spiked with cancer cells from cancer cell lines, as well as blood samples obtained from 4 subjects diagnosed with cancer (2 pancreatic, 1 thyroid, and 1 small cell lung) were processed using the AccuCyte-CyteFinder system to assess recovery rate, accuracy, and reliability over a range of processing times. Results: The AccuCyte-CyteFinder system was highly accurate (95.0%) at identifying cancer cells in spiked-in samples (in 7.5 mL of blood), even at low spiked-in numbers of 5 cells with high sensitivity (90%). The AccuCyte-CyteFinder recovery rate (90.9%) was significantly higher compared to recovery rates obtained by density gradient centrifugation (20.0%) and red blood cell lysis (52.0%). Reliable and comparable recovery was observed in spiked-in samples and in clinical blood samples processed up to 72 hours post-collection. Reviewer analysis of images from spiked-in and clinical samples resulted in high concordance (R-squared value of 0.998 and 0.984 respectively). Discussion: The AccuCyte-CyteFinder system is as an accurate, sensitive, and clinically practical method to detect and enumerate cancer cells. This system addresses some of the practical logistical challenges in incorporating CTCs as part of routine clinical care. This could facilitate the clinical use of CTCs in guiding precision, personalized medicine.

Single Circulating-Tumor-Cell-Targeted Sequencing to Identify Somatic Variants in Liquid Biopsies in Non-Small-Cell Lung Cancer Patients.

Non-small-cell lung cancer (NSCLC) accounts for most cancer-related deaths worldwide. Liquid biopsy by a blood draw to detect circulating tumor cells (CTCs) is a tool for molecular profiling of cancer using single-cell and next-generation sequencing (NGS) technologies. The aim of the study was to identify somatic variants in single CTCs isolated from NSCLC patients by targeted NGS. Thirty-one subjects (20 NSCLC patients, 11 smokers without cancer) were enrolled for blood draws (7.5 mL). CTCs were identified by immunofluorescence, individually retrieved, and DNA-extracted. Targeted NGS was performed to detect somatic variants (single-nucleotide variants (SNVs) and insertions/deletions (Indels)) across 65 oncogenes and tumor suppressor genes. Cancer-associated variants were classified using OncoKB database. NSCLC patients had significantly higher CTC counts than control smokers (p = 0.0132; Mann-Whitney test). Analyzing 23 CTCs and 13 white blood cells across seven patients revealed a total of 644 somatic variants that occurred in all CTCs within the same subject, ranging from 1 to 137 per patient. The highest number of variants detected in ≥1 CTC within a patient was 441. A total of 18/65 (27.7%) genes were highly mutated. Mutations with oncogenic impact were identified in functional domains of seven oncogenes/tumor suppressor genes (NF1, PTCH1, TP53, SMARCB1, SMAD4, KRAS, and ERBB2). Single CTC-targeted NGS detects heterogeneous and shared mutational signatures within and between NSCLC patients. CTC single-cell genomics have potential for integration in NSCLC precision oncology.

Liquid Biopsy Assessment of Circulating Tumor Cell PD-L1 and IRF-1 Expression in Patients with Advanced Solid Tumors Receiving Immune Checkpoint Inhibitor.

BACKGROUND: Reliable biomarkers that can be serially monitored to predict treatment response to immune checkpoint inhibitors (ICIs) are still an unmet need. Here, we present a multiplex immunofluorescence (IF) assay that simultaneously detects circulating tumor cells (CTCs) and assesses CTC expression of programmed death ligand-1 (PD-L1) and interferon regulatory factor 1 (IRF-1) as a candidate biomarker related to ICI use. OBJECTIVE: To assess the potential of CTC PD-L1 and IRF-1 expression as candidate biomarkers for patients with advanced epithelial solid tumors receiving ICIs. PATIENTS AND METHODS: We tested the IF CTC assay in a pilot study of 28 patients with advanced solid tumors who were starting ICI. Blood for CTC evaluation was obtained prior to starting ICI, after a single cycle of therapy, and at the time of radiographic assessment or treatment discontinuation. RESULTS: At baseline, patients with 0-1 CTCs had longer progression-free survival (PFS) compared to patients with ≥ 2 CTCs (4.3 vs 1.3 months, p = 0.01). The presence of any PD-L1+ CTCs after a single dose of ICI portended shorter PFS compared to patients with no CTCs or PD-L1- CTCs (1.2 vs 4.2 months, p = 0.02); the presence of any PD-L1+ or IRF-1+ CTCs at time of imaging assessment or treatment discontinuation also was associated with shorter PFS (1.9 vs 5.5 months, p < 0.01; 1.6 vs 4.7 months, p = 0.05). CTC PD-L1 and IRF-1 expression did not correlate with tumor tissue PD-L1 or IRF-1 expression. Strong IRF-1 expression in tumor tissue was associated with durable (≥ 1 year) radiographic response (p = 0.02). CONCLUSIONS: Based on these results, CTC PD-L1 and IRF-1 expression is of interest in identifying ICI resistance and warrants further study.

Beyond Circulating Tumor Cell Enumeration: Cell-Based Liquid Biopsy to Assess Protein Biomarkers and Cancer Genomics Using the RareCyte® Platform.

The practice of medicine has steadily employed less invasive methods to obtain information derived from the tumor to guide clinical management of patients. Liquid biopsy-the sampling of blood-is a non-invasive method for generating information previously only available from tissue biopsies of the tumor mass. Analysis of fragmented circulating tumor DNA in the plasma is clinically used to identify actionable mutations and detect residual or recurrent disease. Plasma analysis cannot, however, assess cancer phenotypes, including the expression of drug targets and protein biomarkers. Circulating tumor cells (CTCs) are intact cancer cells that have entered the blood that have the potential for distant metastasis. While enumeration of CTCs is prognostic of outcome, recently developed technology allows for the interrogation of protein biomarkers on CTCs that could be predictive of response. Furthermore, since CTCs contain intact whole cancer genomes, isolating viable CTCs detected during therapy could provide a rational approach to assessing mutational profiles of resistance. Identification, characterization and molecular analysis of CTCs together will advance the capacity of liquid biopsy to meet the requirements of twenty-first century medicine.

Safety, Feasibility, and Merits of Longitudinal Molecular Testing of Multiple Metastatic Sites to Inform mTNBC Patient Treatment in the Intensive Trial of Omics in Cancer.

PURPOSE: Patients with metastatic triple-negative breast cancer (mTNBC) have poor outcomes. The Intensive Trial of Omics in Cancer (ITOMIC) sought to determine the feasibility and potential efficacy of informing treatment decisions through multiple biopsies of mTNBC deposits longitudinally over time, accompanied by analysis using a distributed network of experts. METHODS: Thirty-one subjects were enrolled and 432 postenrollment biopsies performed (clinical and study-directed) of which 332 were study-directed. Molecular profiling included whole-genome sequencing or whole-exome sequencing, cancer-associated gene panel sequencing, RNA-sequencing, and immunohistochemistry. To afford time for analysis, subjects were initially treated with cisplatin (19 subjects), or another treatment they had not received previously. The results were discussed at a multi-institutional ITOMIC Tumor Board, and a report transmitted to the subject's oncologist who arrived at the final treatment decision in conjunction with the subject. Assistance was provided to access treatments that were predicted to be effective. RESULTS: Multiple biopsies in single settings and over time were safe, and comprehensive analysis was feasible. Two subjects were found to have lung cancer, one had carcinoma of unknown primary site, tumor samples from three subjects were estrogen receptor-positive and from two others, human epidermal growth factor receptor 2-positive. Two subjects withdrew. Thirty-four of 112 recommended treatments were accessed using approved drugs, clinical trials, and single-patient investigational new drugs. After excluding the three subjects with nonbreast cancers and the two subjects who withdrew, 22 of 26 subjects (84.6%) received at least one ITOMIC Tumor Board-recommended treatment. CONCLUSION: Further exploration of this approach in patients with mTNBC is merited.

Circulating tumor cell investigation in breast cancer patient-derived xenograft models by automated immunofluorescence staining, image acquisition, and single cell retrieval and analysis.

BACKGROUND: Breast cancer patient-derived xenograft (BC-PDX) models represent a continuous and reproducible source of circulating tumor cells (CTCs) for studying their role in tumor biology and metastasis. We have previously shown the utility of BC-PDX models in the study of CTCs by immunohistochemistry (IHC) on serial paraffin sections and manual microscopic identification of cytokeratin-positive cells, a method that is both low-throughput and labor-intensive. We therefore aimed to identify and characterize CTCs from small volume mouse blood samples and examined its practical workflow in a study of BC-PDX mice treated with chemotherapy using an automated imaging platform, the AccuCyte®-CyteFinder® system. METHODS: CTC analysis was conducted using blood from non-tumor bearing SCID/Beige mice spiked with human breast cancer cells, BC-PDX-bearing mice, and BC-PDX mice treated with vehicle or chemotherapeutic agent(s). After red blood cell lysis, nucleated cells were mixed with transfer solution, processed onto microscope slides, and stained by immunofluorescence. The CyteFinder automated scanning microscope was used to identify CTCs, defined as nucleated cells that were human cytokeratin-positive, and mouse CD45-negative. Disaggregated primary BC-PDX tumors and lung metastatic nodules were processed using the same immunostaining protocol. Collective expression of breast cancer cell surface markers (EpCAM, EGFR, and HER2) using a cocktail of target-specific antibodies was assessed. CTCs and disaggregated tumor cells were individually retrieved from slides using the CytePicker® module for sequence analysis of a BC-PDX tumor-specific PIK3CA mutation. RESULTS: The recovery rate of human cancer cells spiked into murine blood was 83 ± 12%. CTC detection was not significantly different from the IHC method. One-third of CTCs did not stain positive for cell surface markers. A PIK3CA T1035A mutation present in a BC-PDX tumor was confirmed in isolated single CTCs and cells from dissociated metastatic nodules after whole genome amplification and sequencing. CTC evaluation could be simply implemented into a preclinical PDX therapeutic study setting with substantial improvements in workflow over the IHC method. CONCLUSIONS: Analysis of small volume blood samples from BC-PDX-bearing mice using the AccuCyte-CyteFinder system allows investigation of the role of CTCs in tumor biology and metastasis independent of surface marker expression.

The RareCyte® platform for next-generation analysis of circulating tumor cells.

Circulating tumor cells (CTCs) can reliably be identified in cancer patients and are associated with clinical outcome. Next-generation "liquid biopsy" technologies will expand CTC diagnostic investigation to include phenotypic characterization and single-cell molecular analysis. We describe here a rare cell analysis platform designed to comprehensively collect and identify CTCs, enable multi-parameter assessment of individual CTCs, and retrieve single cells for molecular analysis. The platform has the following four integrated components: 1) density-based separation of the CTC-containing blood fraction and sample deposition onto microscope slides; 2) automated multiparameter fluorescence staining; 3) image scanning, analysis, and review; and 4) mechanical CTC retrieval. The open platform utilizes six fluorescence channels, of which four channels are used to identify CTC and two channels are available for investigational biomarkers; a prototype assay that allows three investigational biomarker channels has been developed. Single-cell retrieval from fixed slides is compatible with whole genome amplification methods for genomic analysis. © 2018 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

RareCyte® CTC Analysis Step 1: AccuCyte® Sample Preparation for the Comprehensive Recovery of Nucleated Cells from Whole Blood.

The RareCyte platform addresses important technology limitations of current circulating tumor cell (CTC) collection methods, and expands CTC interrogation to include advanced phenotypic characterization and single-cell molecular analysis. In this respect, it represents the "next generation" of cell-based liquid biopsy technologies. In order to identify and analyze CTCs, RareCyte has developed an integrated sample preparation, imaging and individual cell retrieval process. The first step in the process, AccuCyte®, allows the separation, collection, and transfer to a slide the nucleated cell fraction of the blood that contains CTCs. Separation and collection are based on cell density-rather than size or surface molecular expression-and are performed within a closed system, without wash or lysis steps, enabling high CTC recovery. Here, we describe our technique for nucleated cell collection from a blood sample, and the spreading of these nucleated cells onto glass slides permitting immunofluorescent staining, cell identification, and individual cell picking described in subsequent chapters. In addition to collection of rare cells such as CTCs, AccuCyte also collects cells of the circulating immune system onto archivable slides as well as plasma from the same sample.

RareCyte® CTC Analysis Step 3: Using the CytePicker® Module for Individual Cell Retrieval and Subsequent Whole Genome Amplification of Circulating Tumor Cells for Genomic Analysis.

The CytePicker module built into the RareCyte CyteFinder instrument allows researchers to easily retrieve individual cells from microscope slides for genomic analyses, including array CGH, targeted sequencing, and next-generation sequencing. Here, we describe the semiautomated retrieval of CTCs from the blood processed by AccuCyte (see Chapter 13) and amplification of genomic DNA so that molecular analysis can be performed.

A Distributed Network for Intensive Longitudinal Monitoring in Metastatic Triple-Negative Breast Cancer.

Accelerating cancer research is expected to require new types of clinical trials. This report describes the Intensive Trial of OMics in Cancer (ITOMIC) and a participant with triple-negative breast cancer metastatic to bone, who had markedly elevated circulating tumor cells (CTCs) that were monitored 48 times over 9 months. A total of 32 researchers from 14 institutions were engaged in the patient's evaluation; 20 researchers had no prior involvement in patient care and 18 were recruited specifically for this patient. Whole-exome sequencing of 3 bone marrow samples demonstrated a novel ROS1 variant that was estimated to be present in most or all tumor cells. After an initial response to cisplatin, a hypothesis of crizotinib sensitivity was disproven. Leukapheresis followed by partial CTC enrichment allowed for the development of a differential high-throughput drug screen and demonstrated sensitivity to investigational BH3-mimetic inhibitors of BCL-2 that could not be tested in the patient because requests to the pharmaceutical sponsors were denied. The number and size of CTC clusters correlated with clinical status and eventually death. Focusing the expertise of a distributed network of investigators on an intensively monitored patient with cancer can generate high-resolution views of the natural history of cancer and suggest new opportunities for therapy. Optimization requires access to investigational drugs.

High-recovery visual identification and single-cell retrieval of circulating tumor cells for genomic analysis using a dual-technology platform integrated with automated immunofluorescence staining.

BACKGROUND: Circulating tumor cells (CTCs) are malignant cells that have migrated from solid cancers into the blood, where they are typically present in rare numbers. There is great interest in using CTCs to monitor response to therapies, to identify clinically actionable biomarkers, and to provide a non-invasive window on the molecular state of a tumor. Here we characterize the performance of the AccuCyte®--CyteFinder® system, a comprehensive, reproducible and highly sensitive platform for collecting, identifying and retrieving individual CTCs from microscopic slides for molecular analysis after automated immunofluorescence staining for epithelial markers. METHODS: All experiments employed a density-based cell separation apparatus (AccuCyte) to separate nucleated cells from the blood and transfer them to microscopic slides. After staining, the slides were imaged using a digital scanning microscope (CyteFinder). Precisely counted model CTCs (mCTCs) from four cancer cell lines were spiked into whole blood to determine recovery rates. Individual mCTCs were removed from slides using a single-cell retrieval device (CytePicker™) for whole genome amplification and subsequent analysis by PCR and Sanger sequencing, whole exome sequencing, or array-based comparative genomic hybridization. Clinical CTCs were evaluated in blood samples from patients with different cancers in comparison with the CellSearch® system. RESULTS: AccuCyte--CyteFinder presented high-resolution images that allowed identification of mCTCs by morphologic and phenotypic features. Spike-in mCTC recoveries were between 90 and 91%. More than 80% of single-digit spike-in mCTCs were identified and even a single cell in 7.5 mL could be found. Analysis of single SKBR3 mCTCs identified presence of a known TP53 mutation by both PCR and whole exome sequencing, and confirmed the reported karyotype of this cell line. Patient sample CTC counts matched or exceeded CellSearch CTC counts in a small feasibility cohort. CONCLUSION: The AccuCyte--CyteFinder system is a comprehensive and sensitive platform for identification and characterization of CTCs that has been applied to the assessment of CTCs in cancer patient samples as well as the isolation of single cells for genomic analysis. It thus enables accurate non-invasive monitoring of CTCs and evolving cancer biology for personalized, molecularly-guided cancer treatment.

Discovery and preliminary confirmation of novel early detection biomarkers for triple-negative breast cancer using preclinical plasma samples from the Women's Health Initiative observational study.

Triple-negative breast cancer is a particularly aggressive and lethal breast cancer subtype that is more likely to be interval-detected rather than screen-detected. The purpose of this study is to discover and initially validate novel early detection biomarkers for triple-negative breast cancer using preclinical samples. Plasma samples collected up to 17 months before diagnosis from 28 triple-negative cases and 28 matched controls from the Women's Health Initiative Observational Study were equally divided into a training set and a test set and interrogated by a customized antibody array. Data were available on 889 antibodies; in the training set, statistically significant differences in case versus control signals were observed for 93 (10.5 %) antibodies at p < 0.05. Of these 93 candidates, 29 were confirmed in the test set at p < 0.05. Areas under the curve for these candidates ranged from 0.58 to 0.79. With specificity set at 98 %, sensitivity ranged from 4 to 68 % with 20 candidates having a sensitivity ≥ 20 % and 6 having a sensitivity ≥ 40 %. In an analysis of KEGG gene sets, the pyrimidine metabolism gene set was upregulated in cases compared to controls (p = 0.004 in the testing set) and the JAK/Stat signaling pathway gene set was downregulated (p = 0.003 in the testing set). Numerous potential early detection biomarkers specific to triple-negative breast cancer in multiple pathways were identified. Further research is required to followup on promising candidates in larger sample sizes and to better understand their potential biologic importance as our understanding of the etiology of triple-negative breast cancer continues to grow.

Use of a single-chain antibody library for ovarian cancer biomarker discovery.

The discovery of novel early detection biomarkers of disease could offer one of the best approaches to decrease the morbidity and mortality of ovarian and other cancers. We report on the use of a single-chain variable fragment antibody library for screening ovarian serum to find novel biomarkers for the detection of cancer. We alternately panned the library with ovarian cancer and disease-free control sera to make a sublibrary of antibodies that bind proteins differentially expressed in cancer. This sublibrary was printed on antibody microarrays that were incubated with labeled serum from multiple sets of cancer patients and controls. The antibodies that performed best at discriminating disease status were selected, and their cognate antigens were identified using a functional protein microarray. Overexpression of some of these antigens was observed in cancer serum, tumor proximal fluid, and cancer tissue via dot blot and immunohistochemical staining. Thus, our use of recombinant antibody microarrays for unbiased discovery found targets for ovarian cancer detection in multiple sample sets, supporting their further study for disease diagnosis.

Discovery and validation of ovarian cancer biomarkers utilizing high density antibody microarrays.

Here we demonstrate the utility of high-density antibody microarrays for ovarian cancer biomarker discovery. This report describes the technology and how it can be optimized for hypothesis-generating and testing experiments. Our previous results validated the high density antibody array technology platform, the current work expands on it utilizing a second generation array that we tested with a larger set of ovarian case and control serum samples. We then describe our strategies and methods for result validation, including Western immunoblots to confirm antibody specificity. By comparing and combining the current results with our previous study, we solidified the case that the markers found could be used for ovarian cancer diagnosis using this technology. These results set the stage for further validation of these potential biomarkers and the use of this technology in future biomarker discovery studies.

Use of cancer-specific yeast-secreted in vivo biotinylated recombinant antibodies for serum biomarker discovery.

BACKGROUND: Strategies to discover circulating protein markers of ovarian cancer are urgently needed. We developed a novel technology that permits us to isolate recombinant antibodies directed against the potential serum biomarkers, to facilitate the further development of affinity reagents necessary to construct diagnostic tests. METHODS: This study presents a novel discovery approach based on serum immunoprecipitation with cancer-specific in vivo biotinylated recombinant antibodies (biobodies) derived from differentially selected yeast-display scFv, and analysis of the eluted serum proteins by electrophoresis and/or mass spectrometry. RESULTS: Using this strategy we identified catabolic fragments of complement factors, EMILIN2, Von Willebrand factor and phosphatidylethanolamine-binding protein 1 (PEBP1 or RKIP) in patient sera. To our knowledge, this is the first report of a soluble form of PEBP1 in human. Independent evidence for ovarian cancer-specific expression of PEBP1 in patient sera was found by ELISA assays and antibody arrays with anti-PEBP1 antibodies. PEBP1 was detected in 29 out of 30 ascites samples and discriminated ovarian cancer sera from controls (p = 0.02). Finally, we confirmed by western blots the presence of a 21-23 kDa fragment corresponding to the expected size of PEBP1 but we also showed additional bands of 38 kDa and 50-52 kDa in various tissues and cell lines. CONCLUSION: We conclude that the novel strategy described here allows the identification of candidate biomarkers that can be variants of normally expressed proteins or that display cancer-specific post-translational modifications.

Use of high density antibody arrays to validate and discover cancer serum biomarkers.

Perhaps the greatest barrier to translation of serum biomarker discoveries is the inability to evaluate putative biomarkers in high throughput validation studies. Here we report on the development, production, and implementation of a high-density antibody microarray used to evaluate large numbers of candidate ovarian cancer serum biomarkers. The platform was shown to be useful for evaluation of individual antibodies for comparative analysis, such as with disease classification, and biomarker validation and discovery. We demonstrate its performance by showing that known tumor markers behave as expected. We also identify several promising biomarkers from a candidate list and generate hypotheses to support new discovery studies.