Epigenomic Blood-Based Early Detection of Pancreatic Cancer Employing Cell-Free DNA.

BACKGROUND & AIMS: Early detection of pancreatic cancer (PaC) can drastically improve survival rates. Approximately 25% of subjects with PaC have type 2 diabetes diagnosed within 3 years prior to the PaC diagnosis, suggesting that subjects with type 2 diabetes are at high risk of occult PaC. We have developed an early-detection PaC test, based on changes in 5-hydroxymethylcytosine (5hmC) signals in cell-free DNA from plasma. METHODS: Blood was collected from 132 subjects with PaC and 528 noncancer subjects to generate epigenomic and genomic feature sets yielding a predictive PaC signal algorithm. The algorithm was validated in a blinded cohort composed of 102 subjects with PaC, 2048 noncancer subjects, and 1524 subjects with non-PaCs. RESULTS: 5hmC differential profiling and additional genomic features enabled the development of a machine learning algorithm capable of distinguishing subjects with PaC from noncancer subjects with high specificity and sensitivity. The algorithm was validated with a sensitivity for early-stage (stage I/II) PaC of 68.3% (95% confidence interval [CI], 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%). CONCLUSIONS: The PaC detection test showed robust early-stage detection of PaC signal in the studied cohorts with varying type 2 diabetes status. This assay merits further clinical validation for the early detection of PaC in high-risk individuals.

Enrichment-Free Single-Cell Detection and Morphogenomic Profiling of Myeloma Patient Samples to Delineate Circulating Rare Plasma Cell Clones.

Multiple myeloma is an incurable malignancy that initiates from a bone marrow resident clonal plasma cell and acquires successive mutational changes and genomic alterations, eventually resulting in tumor burden accumulation and end-organ damage. It has been recently recognized that myeloma secondary genomic events result in extensive sub-clonal heterogeneity both in localized bone marrow areas and circulating peripheral blood plasma cells. Rare genomic subclones, including myeloma initiating cells, could be the drivers of disease progression and recurrence. Additionally, evaluation of rare myeloma cells in blood for disease monitoring has numerous advantages over invasive bone marrow biopsies. To this end, an unbiased method for detecting rare cells and delineating their genomic makeup enables disease detection and monitoring in conditions with low abundant cancer cells. In this study, we applied an enrichment-free four-plex (CD138, CD56, CD45, DAPI) immunofluorescence assay and single-cell DNA sequencing for morphogenomic characterization of plasma cells to detect and delineate common and rare plasma cells and discriminate between normal and malignant plasma cells in paired blood and bone marrow aspirates from five patients with newly diagnosed myeloma (N = 4) and monoclonal gammopathy of undetermined significance (n = 1). Morphological analysis confirms CD138+CD56+ cells in the peripheral blood carry genomic alterations that are clonally identical to those in the bone marrow. A subset of altered CD138+CD56- cells are also found in the peripheral blood consistent with the known variability in CD56 expression as a marker of plasma cell malignancy. Bone marrow tumor clinical cytogenetics is highly correlated with the single-cell copy number alterations of the liquid biopsy rare cells. A subset of rare cells harbors genetic alterations not detected by standard clinical diagnostic methods of random localized bone marrow biopsies. This enrichment-free morphogenomic approach detects and characterizes rare cell populations derived from the liquid biopsies that are consistent with clinical diagnosis and have the potential to extend our understanding of subclonality at the single-cell level in this disease. Assay validation in larger patient cohorts has the potential to offer liquid biopsy for disease monitoring with similar or improved disease detection as traditional blind bone marrow biopsies.

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.

Circulating tumor cells as a response monitor in stage IV non-small cell lung cancer.

BACKGROUND: Monitoring circulating tumor cells (CTC) has been shown to be prognostic in most solid malignancies. There is no CTC assay in clinical use for lung cancer therapy monitoring due to inconclusive clinical utility data. Limited data has been published outside of the standard CTC enumerations, regarding clinical significance of phenotypic heterogeneity of CTCs in late stage NSCLC and its ability to correlate with treatment outcomes. METHODS: In 81 patients with stage IV NSCLC, multiple timepoints for CTC analysis were collected after initiation of treatment across 139 lines of therapy using single cell high definition diagnostic pathology imaging of all nucleated cells from 362 peripheral blood samples as a liquid biopsy. RESULTS: We analyzed the subset of 25 patients with complete time series data, totaling 117 blood samples, to determine the significance of HD-CTC kinetics during the initiation of treatment. These kinetics follow three distinct patterns: an increase in HD-CTCs with therapy (mean + 118.40 HD-CTCs/mL), unchanged HD-CTCs numbers (stable; mean 0.54 HD-CTCs/mL), and a decrease in HD-CTCs numbers (mean - 81.40 HD-CTCs/mL). Patients with an increasing CTC count during the first 3 months post initiation of new treatment had a better PFS and OS compared to the other groups. There was weak correlation between the absolute number of HD-CTCs at a single time point of therapy and patient outcomes (OS p value = 0.0754). In the whole cohort of 81 patients, HD-CTCs were detected in 51 (63%) patients at initiation of therapy with a median of 2.20 (range 0-509.20) and a mean of 26.21 HD-CTCs/mL (± 15.64). CONCLUSIONS: CTCs are identifiable in most patients with stage IV NSCLC. While absolute HD-CTC counts do not correlate with prognosis, the changes in CTC counts were predictive of survival in patients with metastatic lung cancer receiving chemotherapy. The level and dynamics of CTCs indicate very different biological and pharmacological phenomena at different stages of disease and timepoints of treatment, highlighting the complex role of CTCs in cancer research and clinical management.

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.

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.

A genome sequencing program for novel undiagnosed diseases.

PURPOSE: The Scripps Idiopathic Diseases of Man (IDIOM) study aims to discover novel gene-disease relationships and provide molecular genetic diagnosis and treatment guidance for individuals with novel diseases using genome sequencing integrated with clinical assessment and multidisciplinary case review. Here we describe the operational protocol and initial results of the IDIOM study. METHODS: A total of 121 cases underwent first-tier review by the principal investigators to determine whether the primary inclusion criteria were satisfied, 59 (48.8%) underwent second-tier review by our clinician-scientist review panel, and 17 patients (14.0%) and their family members were enrolled. RESULTS: 60% of cases resulted in a plausible molecular diagnosis, and 18% of cases resulted in a confirmed molecular diagnosis. Two of three confirmed cases led to the identification of novel gene-disease relationships. In the third confirmed case a previously described but unrecognized disease was revealed. In all three confirmed cases a new clinical management strategy was initiated based on the genetic findings. CONCLUSION: Genome sequencing provides tangible clinical benefit for individuals with idiopathic genetic disease, not only in the context of molecular genetic diagnosis of known rare conditions but also in cases where prior clinical information regarding a new genetic disorder is lacking.

A physical sciences network characterization of circulating tumor cell aggregate transport.

Circulating tumor cells (CTC) have been implicated in the hematogenous spread of cancer. To investigate the fluid phase of cancer from a physical sciences perspective, the multi-institutional Physical Sciences-Oncology Center (PS-OC) Network performed multidisciplinary biophysical studies of single CTC and CTC aggregates from a patient with breast cancer. CTCs, ranging from single cells to aggregates comprised of 2-5 cells, were isolated using the high-definition CTC assay and biophysically profiled using quantitative phase microscopy. Single CTCs and aggregates were then modeled in an in vitro system comprised of multiple breast cancer cell lines and microfluidic devices used to model E-selectin mediated rolling in the vasculature. Using a numerical model coupling elastic collisions between red blood cells and CTCs, the dependence of CTC vascular margination on single CTCs and CTC aggregate morphology and stiffness was interrogated. These results provide a multifaceted characterization of single CTC and CTC aggregate dynamics in the vasculature and illustrate a framework to integrate clinical, biophysical, and mathematical approaches to enhance our understanding of the fluid phase of cancer.

Limited genomic heterogeneity of circulating melanoma cells in advanced stage patients.

Purpose. Circulating melanoma cells (CMCs) constitute a potentially important representation of time-resolved tumor biology in patients. To date, genomic characterization of CMCs has been limited due to the lack of a robust methodology capable of identifying them in a format suitable for downstream characterization. Here, we have developed a methodology to detect intact CMCs that enables phenotypic, morphometric and genomic analysis at the single cell level. Experimental design. Blood samples from 40 metastatic melanoma patients and 10 normal blood donors were prospectively collected. A panel of 7 chondroitin sulfate proteoglycan 4 (CSPG4)-specific monoclonal antibodies (mAbs) was used to immunocytochemically label CMCs. Detection was performed by automated digital fluorescence microscopy and multi-parametric computational analysis. Individual CMCs were captured by micromanipulation for whole genome amplification and copy number variation (CNV) analysis. Results. Based on CSPG4 expression and nuclear size, 1-250 CMCs were detected in 22 (55%) of 40 metastatic melanoma patients (0.5-371.5 CMCs ml(-1)). Morphometric analysis revealed that CMCs have a broad spectrum of morphologies and sizes but exhibit a relatively homogeneous nuclear size that was on average 1.5-fold larger than that of surrounding PBMCs. CNV analysis of single CMCs identified deletions of CDKN2A and PTEN, and amplification(s) of TERT, BRAF, KRAS and MDM2. Furthermore, novel chromosomal amplifications in chr12, 17 and 19 were also found. Conclusions. Our findings show that CSPG4 expressing CMCs can be found in the majority of advanced melanoma patients. High content analysis of this cell population may contribute to the design of effective personalized therapies in patients with melanoma.

The thrombotic potential of circulating tumor microemboli: computational modeling of circulating tumor cell-induced coagulation.

Thrombotic events can herald the diagnosis of cancer, preceding any cancer-related clinical symptoms. Patients with cancer are at a 4- to 7-fold increased risk of suffering from venous thromboembolism (VTE), with ∼7,000 patients with lung cancer presenting from VTEs. However, the physical biology underlying cancer-associated VTE remains poorly understood. Several lines of evidence suggest that the shedding of tissue factor (TF)-positive circulating tumor cells (CTCs) and microparticles from primary tumors may serve as a trigger for cancer-associated thrombosis. To investigate the potential direct and indirect roles of CTCs in VTE, we characterized thrombin generation by CTCs in an interactive numerical model coupling blood flow with advection-diffusion kinetics. Geometric measurements of CTCs isolated from the peripheral blood of a lung cancer patient prior to undergoing lobectomy formed the basis of the simulations. Singlet, doublet, and aggregate circulating tumor microemboli (CTM) were investigated in the model. Our numerical model demonstrated that CTM could potentiate occlusive events that drastically reduce blood flow and serve as a platform for the promotion of thrombin generation in flowing blood. These results provide a characterization of CTM dynamics in the vasculature and demonstrate an integrative framework combining clinical, biophysical, and mathematical approaches to enhance our understanding of CTCs and their potential direct and indirect roles in VTE formation.

Fourier-ring descriptor to characterize rare circulating cells from images generated using immunofluorescence microscopy.

We address the problem of subclassification of rare circulating cells using data driven feature selection from images of candidate circulating tumor cells from patients diagnosed with breast, prostate, or lung cancer. We determine a set of low level features which can differentiate among candidate cell types. We have implemented an image representation based on concentric Fourier rings (FRDs) which allow us to exploit size variations and morphological differences among cells while being rotationally invariant. We discuss potential clinical use in the context of treatment monitoring for cancer patients with metastatic disease.

Entropy, complexity, and Markov diagrams for random walk cancer models.

The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential.

Increased ILC2s in the eosinophilic nasal polyp endotype are associated with corticosteroid responsiveness.

Group 2 innate lymphoid cells (ILC2s) have recently been identified in human nasal polyps, but whether numbers of ILC2s differ by polyp endotype or are influenced by corticosteroid use is unknown. Here, we show that eosinophilic nasal polyps contained double the number of ILC2s vs. non-eosinophilic polyps. Polyp ILC2s were also reduced by 50% in patients treated with systemic corticosteroids. Further, using a fungal allergen challenge mouse model, we detected greatly reduced Th2 cytokine-producing and Ki-67+ proliferating lung ILC2s in mice receiving dexamethasone. Finally, ILC2 Annexin V staining revealed extensive apoptosis after corticosteroid treatment in vivo and in vitro. Thus, ILC2s are elevated in the eosinophilic nasal polyp endotype and systemic corticosteroid treatment correlated with reduced polyp ILC2s. Finally, allergen-challenged mice showed reduced ILC2s and increased ILC2 apoptosis after corticosteroid treatment suggesting that ILC2 may be responsive to corticosteroids in eosinophilic respiratory disease.

Rapid phenotypic and genomic change in response to therapeutic pressure in prostate cancer inferred by high content analysis of single circulating tumor cells.

Timely characterization of a cancer's evolution is required to predict treatment efficacy and to detect resistance early. High content analysis of single Circulating Tumor Cells (CTCs) enables sequential characterization of genotypic, morphometric and protein expression alterations in real time over the course of cancer treatment. This concept was investigated in a patient with castrate-resistant prostate cancer progressing through both chemotherapy and targeted therapy. In this case study, we integrate across four timepoints 41 genome-wide copy number variation (CNV) profiles plus morphometric parameters and androgen receptor (AR) protein levels. Remarkably, little change was observed in response to standard chemotherapy, evidenced by the fact that a unique clone (A), exhibiting highly rearranged CNV profiles and AR+ phenotype was found circulating before and after treatment. However, clinical response and subsequent progression after targeted therapy was associated with the drastic depletion of clone A, followed by the sequential emergence of two distinct CTC sub-populations that differed in both AR genotype and expression phenotype. While AR- cells with flat or pseudo-diploid CNV profiles (clone B) were identified at the time of response, a new tumor lineage of AR+ cells (clone C) with CNV altered profiles was detected during relapse. We showed that clone C, despite phylogenetically related to clone A, possessed a unique set of somatic CNV alterations, including MYC amplification, an event linked to hormone escape. Interesting, we showed that both clones acquired AR gene amplification by deploying different evolutionary paths. Overall, these data demonstrate the timeframe of tumor evolution in response to therapy and provide a framework for the multi-scale analysis of fluid biopsies to quantify and monitor disease evolution in individual patients.

Circulating tumor microemboli diagnostics for patients with non-small-cell lung cancer.

INTRODUCTION: Circulating tumor microemboli (CTM) are potentially important cancer biomarkers, but using them for cancer detection in early-stage disease has been assay limited. We examined CTM test performance using a sensitive detection platform to identify stage I non-small-cell lung cancer (NSCLC) patients undergoing imaging evaluation. METHODS: First, we prospectively enrolled patients during 18F-FDG PET-CT imaging evaluation for lung cancer that underwent routine phlebotomy where CTM and circulating tumor cells (CTCs) were identified in blood using nuclear (DAPI), cytokeratin (CK), and CD45 immune-fluorescent antibodies followed by morphologic identification. Second, CTM and CTC data were integrated with patient (age, gender, smoking, and cancer history) and imaging (tumor diameter, location in lung, and maximum standard uptake value [SUVmax]) data to develop and test multiple logistic regression models using a case-control design in a training and test cohort followed by cross-validation in the entire group. RESULTS: We examined 104 patients with NSCLC, and the subgroup of 80 with stage I disease, and compared them to 25 patients with benign disease. Clinical and imaging data alone were moderately discriminating for all comers (Area under the Curve [AUC] = 0.77) and by stage I disease only (AUC = 0.77). However, the presence of CTM combined with clinical and imaging data was significantly discriminating for diagnostic accuracy in all NSCLC patients (AUC = 0.88, p value = 0.001) and for stage I patients alone (AUC = 0.87, p value = 0.002). CONCLUSION: CTM may add utility for lung cancer diagnosis during imaging evaluation using a sensitive detection platform.

Adrenal metastases in lung cancer: clinical implications of a mathematical model.

Adrenal gland metastases are common in lung cancer. It is well recognized that aggressive treatment of solitary adrenal metastases leads to improved outcomes but the exact nature of adrenal deposits is not well understood. Controversy exists as to the routing of cancer cells to the adrenal gland with some believing that this transmission is lymphatic, in contrast to the more generally accepted theory of hematogenous spread. Recently published mathematical modeling of cancer progression strongly supports the lymphatic theory. With that in mind, we performed a literature review to look for biological plausibility of simulation results and believe that evidence supports the contention that metastases to the adrenal gland can be routed by means of lymphatic channels. This could explain improved survival for patients in whom solitary adrenal metastases are managed aggressively with surgical or radiation modalities. We are calling for clinical trials prospectively testing this hypothesis.

Fluid phase biopsy for detection and characterization of circulating endothelial cells in myocardial infarction.

Elevated levels of circulating endothelial cells (CECs) occur in response to various pathological conditions including myocardial infarction (MI). Here, we adapted a fluid phase biopsy technology platform that successfully detects circulating tumor cells in the blood of cancer patients (HD-CTC assay), to create a high-definition circulating endothelial cell (HD-CEC) assay for the detection and characterization of CECs. Peripheral blood samples were collected from 79 MI patients, 25 healthy controls and six patients undergoing vascular surgery (VS). CECs were defined by positive staining for DAPI, CD146 and von Willebrand Factor and negative staining for CD45. In addition, CECs exhibited distinct morphological features that enable differentiation from surrounding white blood cells. CECs were found both as individual cells and as aggregates. CEC numbers were higher in MI patients compared with healthy controls. VS patients had lower CEC counts when compared with MI patients but were not different from healthy controls. Both HD-CEC and CellSearch® assays could discriminate MI patients from healthy controls with comparable accuracy but the HD-CEC assay exhibited higher specificity while maintaining high sensitivity. Our HD-CEC assay may be used as a robust diagnostic biomarker in MI patients.

MicroRNA-17~92 plays a causative role in lymphomagenesis by coordinating multiple oncogenic pathways.

MicroRNAs (miRNAs) have been broadly implicated in cancer, but their exact function and mechanism in carcinogenesis remain poorly understood. Elevated miR-17~92 expression is frequently found in human cancers, mainly due to gene amplification and Myc-mediated transcriptional upregulation. Here we show that B cell-specific miR-17~92 transgenic mice developed lymphomas with high penetrance and that, conversely, Myc-driven lymphomagenesis stringently requires two intact alleles of miR-17~92. We experimentally identified miR-17~92 target genes by PAR-CLIP and validated select target genes in miR-17~92 transgenic mice. These analyses demonstrate that miR-17~92 drives lymphomagenesis by suppressing the expression of multiple negative regulators of the PI3K and NFκB pathways and by inhibiting the mitochondrial apoptosis pathway. Accordingly, miR-17~92-driven lymphoma cells exhibited constitutive activation of the PI3K and NFκB pathways and chemical inhibition of either pathway reduced tumour size and prolonged the survival of lymphoma-bearing mice. These findings establish miR-17~92 as a powerful cancer driver that coordinates the activation of multiple oncogenic pathways, and demonstrate for the first time that chemical inhibition of miRNA downstream pathways has therapeutic value in treating cancers caused by miRNA dysregulation.

An observational study of circulating tumor cells and (18)F-FDG PET uptake in patients with treatment-naive non-small cell lung cancer.

INTRODUCTION: We investigated the relationship of circulating tumor cells (CTCs) in non-small cell lung cancer (NSCLC) with tumor glucose metabolism as defined by (18)F-fluorodeoxyglucose (FDG) uptake since both have been associated with patient prognosis. MATERIALS & METHODS: We performed a retrospective screen of patients at four medical centers who underwent FDG PET-CT imaging and phlebotomy prior to a therapeutic intervention for NSCLC. We used an Epithelial Cell Adhesion Molecule (EpCAM) independent fluid biopsy based on cell morphology for CTC detection and enumeration (defined here as High Definition CTCs or "HD-CTCs"). We then correlated HD-CTCs with quantitative FDG uptake image data calibrated across centers in a cross-sectional analysis. RESULTS: We assessed seventy-one NSCLC patients whose median tumor size was 2.8 cm (interquartile range, IQR, 2.0-3.6) and median maximum standardized uptake value (SUVmax) was 7.2 (IQR 3.7-15.5). More than 2 HD-CTCs were detected in 63% of patients, whether across all stages (45 of 71) or in stage I disease (27 of 43). HD-CTCs were weakly correlated with partial volume corrected tumor SUVmax (r = 0.27, p-value = 0.03) and not correlated with tumor diameter (r = 0.07; p-value = 0.60). For a given partial volume corrected SUVmax or tumor diameter there was a wide range of detected HD-CTCs in circulation for both early and late stage disease. CONCLUSIONS: CTCs are detected frequently in early-stage NSCLC using a non-EpCAM mediated approach with a wide range noted for a given level of FDG uptake or tumor size. Integrating potentially complementary biomarkers like these with traditional patient data may eventually enhance our understanding of clinical, in vivo tumor biology in the early stages of this deadly disease.