Circulating Tumor Cells Gene Expression Research Articles

Programmed Death Ligand 1 Expression in Circulating Tumor Cells as a Predictor and Monitor of Response to Atezolizumab plus Bevacizumab Treatment in Patients with Hepatocellular Carcinoma.

There remains no reliable biomarker of therapeutic efficacy in hepatocellular carcinoma (HCC) for the PD-L1 inhibitor atezolizumab and bevacizumab (Atezo/Bev). Circulating tumor cells (CTCs) enable the serial collection of living tumor cells. Pre-treatment and serial CTC gene expression changes and tumor histology were evaluated to identify predictors of response to Atezo/Bev. Peripheral blood from 22 patients with HCC treated with Atezo/Bev and 24 patients treated with lenvatinib was serially collected. The RNA expression in CTCs was analyzed using qRT-PCR. Higher PD-L1 expression in pre-treatment CTCs was associated with response and improved prognosis with Atezo/Bev treatment, but not with lenvatinib. There was no correlation between PD-L1 expression in CTCs and that in liver tumor biopsy specimens scored using imaging software. Furthermore, PD-L1 RNA expression in CTCs was dynamically altered by Atezo/Bev, decreasing during effective response and increasing upon progression. CTC-derived RNA collected during Atezo/Bev indicates that patients with higher PD-L1 expression in CTCs at baseline were 3.9 times more responsive to treatment. Therefore, PD-L1 RNA levels in CTCs are an accurate response predictor and may be a monitorable biomarker that changes dynamically to reflect the response during Atezo/Bev treatment.

Detecting androgen receptor (AR), AR variant 7 (AR-V7), prostate-specific membrane antigen (PSMA), and prostate-specific antigen (PSA) gene expression in CTCs and plasma exosome-derived cfRNA in patients with metastatic castration-resistant prostate cancer (mCRPC) by integrating the VTX-1 CTC isolation system with the QIAGEN AdnaTest

BackgroundTherapies for metastatic castration-resistant prostate cancer (mCRPC) include targeting the androgen receptor (AR) with androgen receptor inhibitors (ARIs) and prostate-specific membrane antigen (PSMA). Having the ability to detect AR, AR splice variant 7 (AR-V7), or PSMA in circulating tumor cells (CTCs) or circulating exosomal cell-free RNA (cfRNA) could be helpful to guide selection of the appropriate therapy for each individual patient. The Vortex Biosciences VTX-1 system is a label-free CTC isolation system that enables the detection of the expression of multiple genes in both CTCs and exosomal cfRNA from the same blood sample in patients with mCRPC. Detection of both AR-V7 and PSMA gene expression in both CTCs and cfRNA simultaneously has not yet been reported.MethodsTo characterize the combined VTX-1-AdnaDetect workflow, 22Rv1 cancer cells were spiked into blood from healthy donors and processed with the VTX-1 to mimic patient samples and assess performances (capture efficiency, purity, AR and AR-V7 expression). Then, we collected 19 blood samples from 16 patients with mCRPC and therapeutic resistance to androgen receptor inhibitors (ARIs). Plasma was separated and the plasma-depleted blood was processed further with the VTX-1 to collect CTCs. Both plasma exosomal cfRNA and CTCs were subsequently analyzed for AR, AR-V7, PSMA, and prostate-specific antigen (PSA) mRNA expression using the AdnaTest ProstateCancerPanel AR-V7 assay.ResultsAR-V7 expression could be detected in 22Rv1 cells spiked into blood from healthy volunteers as well as in CTCs and plasma-derived exosomal cfRNA from patients with mCRPC by processing blood with the VTX-1 CTC isolation system followed by the AdnaTest ProstateCancerPanel AR-V7 assay. 94.7% of patient blood samples (18/19) had detectable AR expression in either CTCs or exosomal cfRNA (16 in CTCs, 12 in cfRNA). 15.8% of the 19 patient blood samples (3/19) were found to have AR-V7-positive (AR-V7+) CTCs, one of which was also AR-V7+ in the exosomal cfRNA analysis. 42.1% of patient blood samples (8/19) were found to be PSMA positive (PSMA+): 26.3% (5/19) were PSMA+ in the CTC analysis and 31.6% (6/19) were PSMA+ in the exosomal cfRNA analysis. Of those 8 PSMA+ samples, 2 had detectable PSMA only in CTCs, and 3 had detectable PSMA only in exosomal cfRNA.ConclusionVTX-1 enables isolation of CTCs and plasma exosomes from a single blood draw and can be used for detecting AR-V7 and PSMA mRNA in both CTCs and cfRNA in patients with mCRPC and resistance to ARIs. This technology facilitates combining RNA measurements in CTCs and exosomal cfRNA for future studies to develop potentially clinically relevant cancer biomarker detection in blood.

A deep learning model predicts the presence of diverse cancer types using circulating tumor cells

Circulating tumor cells (CTCs) are cancer cells that detach from the primary tumor and intravasate into the bloodstream. Thus, non-invasive liquid biopsies are being used to analyze CTC-expressed genes to identify potential cancer biomarkers. In this regard, several studies have used gene expression changes in blood to predict the presence of CTC and, consequently, cancer. However, the CTC mRNA data has not been used to develop a generic approach that indicates the presence of multiple cancer types. In this study, we developed such a generic approach. Briefly, we designed two computational workflows, one using the raw mRNA data and deep learning (DL) and the other exploiting five hub gene ranking algorithms (Degree, Maximum Neighborhood Component, Betweenness Centrality, Closeness Centrality, and Stress Centrality) with machine learning (ML). Both workflows aim to determine the top genes that best distinguish cancer types based on the CTC mRNA data. We demonstrate that our automated, robust DL framework (DNNraw) more accurately indicates the presence of multiple cancer types using the CTC gene expression data than multiple ML approaches. The DL approach achieved average precision of 0.9652, recall of 0.9640, f1-score of 0.9638 and overall accuracy of 0.9640. Furthermore, since we designed multiple approaches, we also provide a bioinformatics analysis of the gene commonly identified as top-ranked by the different methods. To our knowledge, this is the first study wherein a generic approach has been developed to predict the presence of multiple cancer types using raw CTC mRNA data, as opposed to other models that require a feature selection step.

Circulating tumor cells (CTCs) and hTERT gene expression in CTCs for radiotherapy effect with lung cancer

BackgroundCirculating tumor cells (CTCs) are important biological indicators of the lung cancer prognosis, and CTC counting and typing may provide helpful biological information for the diagnosis and treatment of lung cancer.MethodsThe CTC count in blood before and after radiotherapy was detected by the CanPatrol™ CTC analysis system, and the CTC subtypes and the expression of hTERT before and after radiotherapy were detected by multiple in situ hybridization. The CTC count was calculated as the number of cells per 5 mL of blood.ResultsThe CTC positivity rate in patients with tumors before radiotherapy was 98.44%. Epithelial–mesenchymal CTCs (EMCTCs) were more common in patients with lung adenocarcinoma and squamous carcinoma than in patients with small cell lung cancer (P = 0.027). The total CTCs (TCTCs), EMCTCs, and mesenchymal CTCs (MCTCs) counts were significantly higher in patients with TNM stage III and IV tumors (P < 0.001, P = 0.005, and P < 0.001, respectively). The TCTCs and MCTCs counts were significantly higher in patients with an ECOG score of > 1 (P = 0.022 and P = 0.024, respectively). The TCTCs and EMCTCs counts before and after radiotherapy affected the overall response rate (ORR) (P < 0.05). TCTCs and ECTCs with positive hTERT expression were associated with the ORR of radiotherapy (P = 0.002 and P = 0.038, respectively), as were TCTCs with high hTERT expression (P = 0.012). ECOG score (P = 0.006) and post-radiation TCTCs count (P = 0.011) were independent factors for progression-free survival (PFS) and TNM stage (P = 0.054) and pre-radiation EMCTCs count (P = 0.009) were independent factors of overall survival (OS).ConclusionThis study showed a high rate of positive CTC detection in patients with lung cancer, and the number, subtype, and hTERT-positive expression of CTCs were closely related to patients’ ORR, PFS, and OS with radiotherapy. EMCTCs, hTERT-positive expression of CTCs are expected to be important biological indicators for predicting radiotherapy efficacy and the prognosis in patients with lung cancer. These results may be useful in improving disease stratification for future clinical trials and may help in clinical decision-making.

Abstract 3370: Liquid biopsy approaches to determine tumor cell heterogeneity in advanced prostate cancer

Abstract Aggressive variants of prostate cancer (AVPC) emerge from prostate adenocarcinoma following enduring therapeutic pressure. They grow independent of the androgen receptor, progress rapidly and can show traits of neuroendocrine (NE) differentiation. As progression to AVPC is not well detected by prostate specific antigen monitoring, new biomarkers are urgently needed. The aim of this study is to evaluate the detection of circulating tumor cells (CTCs) in combination with gene expression analysis of NE genes to identify AVPC patients with neuroendocrine traits. Blood samples were collected from patients suffering from AVPC (n=78, including 25 patients with histological evidence of NEPC) as well as from patients with hormone-sensitive prostate cancer (HSPC) as controls (n=12) at the University Medical Center Hamburg-Eppendorf. CTC counts were determined by CellSearch analysis. In parallel, CTCs were immuno-magnetically enriched using the AdnaTest and bulk gene expression of prostate-specific and NE genes was analyzed by semi-quantitative PCR. From a subset of patients, CTCs were additionally enriched by Parsortix to compare gene expression of CTCs with EpCAM-based or size-based CTC enrichment. Using CellSearch analysis, CTCs were found in 88.9 % of AVPC patients. CTC counts ranged between 0 – 20,000 CTCs/7.5 ml of blood with a median of 32 CTCs/7.5 ml. Similarly, 81.8 % of NEPC patients were positive for CTCs with a median count of 35 CTCs/7.5 ml (range 0-13,000). In contrast, CTCs were found in only 50 % of HSPC patients at lower concentrations (median count of 0.5 CTCs/7.5 ml, range 0-34). CTC counts were significantly elevated in AVPC and NEPC patients compared to HSPC (p = 0.002, p = 0.012), but no significant differences were found between AVPC and NEPC samples.In 93.8 % of AVPC samples, CTCs expressed prostate-specific genes such as KLK3 or PSMA. At least one of the NE transcripts was detected in 37.5 % of AVPC patients. In CTCs from NEPC patients, the positivity for prostate markers was significantly reduced to 66.6 % (p = 0.01) and the positivity for NE markers was increased to 61.1 %. A random Forrest model trained on all analyzed transcripts allowed for a distinction of HSPC and NEPC with an AUC of 79.5 %. Comparison of CTC enrichment strategies in a subset of 13 patients showed similar NE marker detection by size-based enrichment (53.8 % NE-positive) compared to the AdnaTest (61.5 % NE-positive). AVPC and NEPC patients show a high CTC burden that will allow subsequent molecular analyses, and CTC counts allowed a distinction between blood samples from HSPC and NEPC patients. Gene expression analysis revealed a high degree of inter-patient heterogeneity for neuroendocrine-specific transcripts with a reduction of prostate markers in NEPC patients. Future molecular characterization and longitudinal monitoring of CTCs will shed more light on the evolution of AVPC and NEPC. Citation Format: Lina Merkens, Sarah Greimeier, Sabine Riethdorf, Klaus Pantel, Gunhild von Amsberg, Stefan Werner. Liquid biopsy approaches to determine tumor cell heterogeneity in advanced prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3370.

Phenotypic Plasticity in Circulating Tumor Cells Is Associated with Poor Response to Therapy in Metastatic Breast Cancer Patients.

Circulating tumor cells (CTCs) are indicators of metastatic spread and progression. In a longitudinal, single-center trial of patients with metastatic breast cancer starting a new line of treatment, a microcavity array was used to enrich CTCs from 184 patients at up to 9 timepoints at 3-month intervals. CTCs were analyzed in parallel samples from the same blood draw by imaging and by gene expression profiling to capture CTC phenotypic plasticity. Enumeration of CTCs by image analysis relying primarily on epithelial markers from samples obtained before therapy or at 3-month follow-up identified the patients at the highest risk of progression. CTC counts decreased with therapy, and progressors had higher CTC counts than non-progressors. CTC count was prognostic primarily at the start of therapy in univariate and multivariate analyses but had less prognostic utility at 6 months to 1 year later. In contrast, gene expression, including both epithelial and mesenchymal markers, identified high-risk patients after 6-9 months of treatment, and progressors had a shift towards mesenchymal CTC gene expression on therapy. Cross-sectional analysis showed higher CTC-related gene expression in progressors 6-15 months after baseline. Furthermore, patients with higher CTC counts and CTC gene expression experienced more progression events. Longitudinal time-dependent multivariate analysis indicated that CTC count, triple-negative status, and CTC expression of FGFR1 significantly correlated with inferior progression-free survival while CTC count and triple-negative status correlated with inferior overall survival. This highlights the utility of protein-agnostic CTC enrichment and multimodality analysis to capture the heterogeneity of CTCs.

Signatures of Breast Cancer Progression in the Blood: What Could Be Learned from Circulating Tumor Cell Transcriptomes.

Gene expression profiling has revolutionized our understanding of cancer biology, showing an unprecedented ability to impact patient management especially in breast cancer. The vast majority of breast cancer gene expression signatures derive from the analysis of the tumor bulk, an experimental approach that limits the possibility to dissect breast cancer heterogeneity thoroughly and might miss the message hidden in biologically and clinically relevant cell populations. During disease progression or upon selective pressures, cancer cells undergo continuous transcriptional changes, which inevitably affect tumor heterogeneity, response to therapy and tendency to disseminate. Therefore, metastasis-associated signatures and transcriptome-wide gene expression measurement at single-cell resolution hold great promise for the future of breast cancer clinical care. Seen from this perspective, transcriptomics of circulating tumor cells (CTCs) represent an attractive opportunity to bridge the knowledge gap and develop novel biomarkers. This review summarizes the current state-of-the-science on CTC gene expression analysis in breast cancer, addresses technical and clinical issues related to the application of CTC-derived signatures, and discusses potential research directions.

Circulating tumor cell gene expression and plasma AR gene copy number as biomarkers for castration-resistant prostate cancer patients treated with cabazitaxel

BackgroundCabazitaxel improves overall survival (OS) in metastatic castration-resistant prostate cancer (mCRPC) patients progressing after docetaxel. In this prospective study, we evaluated the prognostic role of CTC gene expression on cabazitaxel-treated patients and its association with plasma androgen receptor (AR) copy number (CN).MethodsPatients receiving cabazitaxel 20 or 25 mg/sqm for mCRPC were enrolled. Digital PCR was performed to assess plasma AR CN status. CTC enrichment was assessed using the AdnaTest EMT-2/StemCell kit. CTC expression analyses were performed for 17 genes. Data are expressed as hazard ratio (HR) or odds ratio (OR) and 95% CI.ResultsSeventy-four patients were fully evaluable. CTC expression of AR-V7 (HR=2.52, 1.24–5.12, p=0.011), AKR1C3 (HR=2.01, 1.06–3.81, p=0.031), AR (HR=2.70, 1.46–5.01, p=0.002), EPCAM (HR=3.75, 2.10–6.71, p< 0.0001), PSMA (HR=2.09, 1.19–3.66, p=0.01), MDK (HR=3.35, 1.83–6.13, p< 0.0001), and HPRT1 (HR=2.46, 1.44–4.18, p=0.0009) was significantly associated with OS. ALDH1 (OR=5.50, 0.97–31.22, p=0.05), AR (OR=8.71, 2.32–32.25, p=0.001), EPCAM (OR=7.26, 1.47–35.73, p=0.015), PSMA (OR=3.86, 1.10–13.50, p=0.035), MDK (OR=6.84, 1.87–24.98, p=0.004), and HPRT1 (OR=7.41, 1.82–30.19, p=0.005) expression was associated with early PD. AR CN status was significantly correlated with AR-V7 (p=0.05), EPCAM (p=0.02), and MDK (p=0.002) expression. In multivariable model, EPCAM and HPRT1 CTC expression, plasma AR CN gain, ECOG PS=2, and liver metastases and PSA were independently associated with poorer OS. In patients treated with cabazitaxel 20 mg/sqm, median OS was shorter in AR-V7 positive than negative patients (6.6 versus 14 months, HR=3.46, 1.47–8.17], p=0.004).ConclusionsBaseline CTC biomarkers may be prognosticators for cabazitaxel-treated mCRPC patients. Cabazitaxel at lower (20 mg/sqm) dose was associated with poorer outcomes in AR-V7 positive patients compared to AR-V7 negative patients in a post hoc subgroup analysis.Trial registrationClinicaltrials.govNCT03381326. Retrospectively registered on 18 December 2017.

615P Circulating tumor cells (CTC) gene expression and plasma androgen receptor (AR) copy number (CN) in cabazitaxel-treated metastatic castration-resistant prostate cancer (mCRPC)

Cabazitaxel showed overall survival (OS) benefit for mCRPC patients (pts) progressing after docetaxel. In a prospective study (NCT03381326), we evaluated the role of CTC gene expression of cabazitaxel-treated pts and its association with plasma AR CN.

Prognostic Significance of Gene Expression and DNA Methylation Markers in Circulating Tumor Cells and Paired Plasma Derived Exosomes in Metastatic Castration Resistant Prostate Cancer

Simple Summary“Liquid biopsy”, based on the analysis of circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA), provides non-invasive real-time monitoring of tumor evolution and therapeutic efficacy. We performed for the first time a direct comparison study on gene expression and DNA methylation markers in CTCs and paired plasma-derived exosomes and evaluated their prognostic significance in metastatic castration resistant prostate cancer. Our results revealed for the first time a significantly higher positivity of all markers in EpCAM-positive CTCs compared to plasma-derived exosomes. We report that in EpCAM-positive CTCs, CK-19, PSMA, TWIST1 expression and GSTP1 methylation are significantly correlated with worse overall survival (OS), while in exosomes, CK-8 expression and GSTP1 and RASSF1A methylation status were significantly correlated with a lower OS. We also enumerated CTC and tumor-derived extracellular vesicles (tdEVs) using CellSearch (CS) and found a correlation between the CTC and tumor-derived extracellular vesicles (tdEVs) enumeration values.Liquid biopsy, based on the analysis of circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA), provides non-invasive real-time monitoring of tumor evolution and therapeutic efficacy. We performed for the first time a direct comparison study on gene expression and DNA methylation markers in CTCs and paired plasma-derived exosomes and evaluated their prognostic significance in metastatic castration resistant prostate cancer. This prospective liquid biopsy (LB) study was based on a group of 62 metastatic castration resistant prostate cancer (mCRPC) patients and 10 healthy donors (HD) as controls. Identical blood draws were used to: (a) enumerate CTC and tumor-derived extracellular vesicles (tdEVs) using CellSearch (CS) and (b) analyze CTCs and paired plasma-derived exosomes at the gene expression and DNA methylation level. CTCs were enumerated using CellSearch in 57/62 patients, with values ranging from 5 to 854 cells/7.5 mL PB. Our results revealed for the first time a significantly higher positivity of gene expression markers (CK-8, CK-18, TWIST1, PSMA, AR-FL, AR-V7, AR-567 and PD-L1 mRNA) in EpCAM-positive CTCs compared to plasma-derived exosomes. GSTP1, RASSF1A and SCHLAFEN were methylated both in CTC and exosomes. In CTCs, Kaplan–Meier analysis revealed that CK-19 (p = 0.009), PSMA (p = 0.001), TWIST1 (p = 0.001) expression and GSTP1 (p = 0.001) methylation were correlated with OS, while in exosomes GSTP1 (p = 0.007) and RASSF1A (p = 0.001) methylation was correlated with OS. Our direct comparison study of CTCs and exosomes at gene expression and DNA methylation level, revealed for the first time a significantly higher positivity in EpCAM-positive CTCs compared to plasma-derived exosomes. Future perspective of this study should be the evaluation of clinical utility of molecular biomarkers in CTCs and exosomes on independent multicentric cohorts with mCRPC patients.

Abstract B40: Analytical validation and initial clinical utility of multianalyte transcriptomic biomarker profiling of circulating tumor cells using automated exclusion-based sample preparation technology

Abstract The efficacy of androgen receptor (AR) signaling inhibitors (ARSIs) in prostate cancer is limited by both de novo and acquired resistance. Two well-described mechanisms of resistance to ARSIs are the development of constitutively activated AR splice variants (AR-Vs) or neuroendocrine prostate cancer (NEPC). Expression of NEPC markers is traditionally evaluated in solid tumor biopsies while AR-Vs can be detected in circulating tumor cells (CTCs) and have prognostic relevance in prostate cancer. Unlike solid tumor biopsy-based detection strategies, liquid biopsies can be performed periodically over the course of treatments, enabling early identification of resistance mechanisms. To evaluate for ARSI resistance, we developed a multiplex gene expression panel of AR-Vs and NEPC markers. We evaluated potential clinical utility of this assay in CTCs captured using an exclusion-based sample preparation technology. This test was evaluated with a cohort of 46 patients, showing 39% sensitivity and 94% specificity at detecting ARSI resistance. To develop a clinical-grade liquid biopsy assay with this multiplexed gene expression panel, we utilized a high-throughput automated exclusion-based sample preparation (ESP) technology for CTC capture, mRNA extraction, and gene expression analysis using RT-qPCR. Cell lines were used to evaluate the analytical performance of the methodology, and spike-in control materials were designed to monitor the efficiency of mRNA extraction for each individual patient sample. Serial dilutions of cell lines demonstrated the sensitivity to extract and quantify mRNA at the single-cell level with high precision between evaluations performed on three different days. Increasing numbers of cells resulted in the quantification of proportionally higher amounts of both AR-Vs and NEPC markers, demonstrating the analytical accuracy of the methodology (R2 values of 0.8 and above). To monitor for RNA degradation, a grape mRNA amplicon material was designed as an internal spike-in control for daily use in testing patient samples. Healthy donor PBMCs were used to confirm primers were specific for cells of cancer origin. ESP-mRNA extraction followed by RT-qPCR demonstrates single-cell resolution for the detection of AR-V/NEPC transcriptomic expression, with high precision in evaluating actual patient samples. The high analytical performance, and the promising preliminary correlation with ARSI resistance, warrant further efforts towards implementation into clinical laboratory testing environments and testing in prospective clinical trials. Citation Format: Zachery D. Schultz, Jennifer L. Schehr, Rory M. Bade, Molly M. Morgan, Madalyn S. Gill, Hannah M. Pezzi, Jaime M. Sperger, Charlotte N. Stahlfeld, Anupama Singh, Jay W. Warrick, David J. Beebe, Joshua M. Lang. Analytical validation and initial clinical utility of multianalyte transcriptomic biomarker profiling of circulating tumor cells using automated exclusion-based sample preparation technology [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr B40.

Molecular profiling of circulating tumor cells predicts clinical outcome in head and neck squamous cell carcinoma.

The relationship between the molecular profiling of circulating tumor cells (CTCs) and clinical factors is a challenge. In this study, we performed molecular detection and characterization of CTCs in patients with head and neck squamous cell carcinoma (HNSCC). CTCs captured by microfilter were analyzed for the expression of multiple epithelial markers (EPCAM, MET, KRT19, and EGFR) by RT-qPCR. The CTCs-positive samples were further analyzed for the expression of 10 genes (PIK3CA, CCND1, SNAI1, VIM, CD44, NANOG, ALDH1A1, CD47, CD274, and PDCD1LG2). Finally, we analyzed whether the molecular profiling of CTCs was associated with clinical factors. Twenty-eight (63.6%) of the 44 HNSCC patients were positive for at least one epithelial-related gene. CTC-positivity was significantly correlated with treatment resistance (p = 0.0363), locoregional recurrence (p = 0.0151), and a shorter progression-free survival (PFS) (p = 0.0107). Moreover, the expression of MET in CTCs was associated with a shorter PFS (p = 0.0426). Notably, patients with CD274-positive CTC showed prolonged PFS (p = 0.0346) and overall survival (p = 0.0378) compared to those with CD274-negative CTC. Our results suggest that molecular profiling characterized by the gene expression of CTCs influences clinical factors in patients with HNSCC.

Prediction of recurrence and progression in patients with T1G3 bladder cancer by gene expression of circulating tumor cells

ObjectiveTo investigate the role of gene expression of circulating tumor cells (CTCs) as noninvasive prognostic markers in patients with high risk nonmuscle invasive bladder cancer. Materials and methodsWe identified all patients with TIG3 urothelial bladder cancer (UBC) at our institution since 2016.The study included 100 patients with T1G3 UBC and 50 healthy volunteers. CTCs were isolated from blood using immunomagnetic separation and gene expression was performed using 10 bladder cancer associated genes, namely; KRAS, EPCAM, CD133, CD44, mTOR, SURVIVIN, AKT, PI3K, VEGF, and TP53. Gene expression of CTCs was correlated to time to first recurrence and time to progression using Kaplan-Meier curves. ResultsThere was strong negative correlation between CTCs-positive patients and time to first recurrence and time to progression. Significant differences in expression levels of specific genes were observed that can predict recurrence and progression of T1G3 UBC. ConclusionCTCs appear to be noninvasive methods of predicting disease recurrence and progression in patients with high- risk nonmuscle invasive bladder cancer; therefore, studying their molecular profiling may improve prediction of recurrence and progression. Further studies are invited for more in-depth investigation to consolidate our initial results.

Gene Expression Alterations during Development of Castration-Resistant Prostate Cancer Are Detected in Circulating Tumor Cells.

Development of castration-resistant prostate cancer (CRPC) is associated with alterations in gene expression involved in steroidogenesis and androgen signaling. This study investigates whether gene expression changes related to CRPC development can be identified in circulating tumor cells (CTCs). Gene expression in paired CTC samples from 29 patients, before androgen deprivation therapy (ADT) and at CRPC relapse, was compared using a panel including 47 genes related to prostate cancer progression on a qPCR platform. Fourteen genes displayed significantly changed gene expression in CTCs at CRPC relapse compared to before start of ADT. The genes with increased expression at CRPC relapse were related to steroidogenesis, AR-signaling, and anti-apoptosis. In contrast, expression of prostate markers was downregulated at CRPC. We also show that midkine (MDK) expression in CTCs from metastatic hormone-sensitive prostate cancer (mHSPC) was associated to short cancer-specific survival (CSS). In conclusion, this study shows that gene expression patterns in CTCs reflect the development of CRPC, and that MDK expression levels in CTCs are prognostic for cancer-specific survival in mHSPC. This study emphasizes the role of CTCs in exploring mechanisms of therapy resistance, as well as a promising biomarker for prognostic and treatment-predictive purposes in advanced mHSPC.

Integrated Gene Expression Score in Circulating Tumor Cells to Predict Treatment Response in Muscle-Invasive Bladder Cancer

Muscle-invasive bladder cancer (MIBC) is often managed with radical cystectomy, but select patients are eligible for bladder-sparing trimodality therapy (TMT) with contemporary bladder preservation rates ∼85% and comparable long-term survival. There is an urgent need for reliable biomarkers to optimize treatment selection and detect recurrence early. Circulating tumor cells (CTCs) in the blood have potential as non-invasive, serial “liquid biopsies” to predict and monitor therapeutic response. Prior studies of CTCs in MIBC relied on enrichment of EpCAM-expressing CTCs. The purpose of this study is to use an unbiased negative-selection, microfluidic CTC isolation approach coupled with sensitive droplet digital PCR (ddPCR) to develop and validate a CTC gene expression score (CTC-GES) to monitor response to TMT. Candidate genes were identified by differential expression analysis comparing RNA-seq data from MIBC (TCGA; n = 67) to non-neoplastic bladder (GTEX; n = 11) and leukocytes (n = 20), as well as genes correlated with molecular subtypes in MIBC. ddPCR primer/probe sets were designed for each gene and validated using bladder cancer cell lines (RT4: luminal, HT-1376: basal) spiked into healthy donor blood and processed with the microfluidic CTC-iChip. Validated genes comprised the CTC-GES panel. Blood is being collected from a discovery cohort of MIBC patients undergoing TMT (n = 7 to date) at several time points (baseline, on-treatment, two-month follow-up). CTCs were isolated using the CTC-iChip and the CTC-GES assay was applied. The GES was computed as log(∑(positive droplets/mL blood)+1). In total, eight candidate genes (PPARG, UPK1A, UPK2, KRT14, EGFR, KRT19, TMEM129, DSG2) were analytically validated and comprised the CTC-GES. The assay lower limit of detection was 3 CTCs per 10 mL blood. In the discovery cohort to date, median age was 80 yo (6 males, 1 female), and all had T2/grade 3 MIBC, except one had T3 disease. Remarkably, the assay was able to predict a recurrence after TMT more than two months prior to clinical detection. Of the 3 patients with >6 months follow-up to date, there was an increase in the GES from baseline to on-treatment in two patients who developed metastatic disease (ΔGESprog = +3.12, +1.06), while it decreased in the patient who had no radiographic/pathologic evidence of disease (ΔGESNED = -0.78). We have developed and analytically validated a novel CTC gene expression score for MIBC pts undergoing TMT. In a small discovery cohort, our preliminary data suggests this biomarker can predict cancer recurrence more than two months prior to clinical detection. In contrast to circulating tumor DNA, CTC-GES does not require interpatient customization based on prior knowledge of specific mutations. With continued refinement and substantiation, the CTC-GES has potential as a universal biomarker in MIBC to predict early failures after TMT and enable treatment modification/intensification at a lower disease burden.

Circulating Tumor Cell–Based Molecular Classifier for Predicting Resistance to Abiraterone and Enzalutamide in Metastatic Castration-Resistant Prostate Cancer

While circulating tumor cell (CTC)–based detection of AR-V7 has been demonstrated to predict patient response to second-generation androgen receptor therapies, the rarity of AR-V7 expression in metastatic castrate-resistant prostate cancer (mCRPC) suggests that other drivers of resistance exist. We sought to use a multiplex gene expression platform to interrogate CTCs and identify potential markers of resistance to abiraterone and enzalutamide. 37 patients with mCRPC initiating treatment with enzalutamide (n = 16) or abiraterone (n = 21) were prospectively enrolled for CTC collection and gene expression analysis using a panel of 89 prostate cancer–related genes. Gene expression from CTCs was correlated with PSA response and radioclinical progression-free survival (PFS) using Kaplan-Meier and Cox regression analyses. Twenty patients (54%) had detectable CTCs. At a median follow-up of 11.3 months, increased expression of the following genes was significantly associated with shorter PSA PFS and radioclinical PFS: AR, AR-V7, PSA, PSCA, TSPAN8, NKX3.1, and WNT5B. Additionally, high SPINK1 expression was associated with increased PFS. A predictive model including all eight genes gave an area under the curve (AUC) of 0.84 for PSA PFS and 0.86 for radioclinical PFS. In comparison, the AR-V7 only model resulted in AUC values of 0.65 and 0.64.These data demonstrate that clinically relevant information regarding gene expression can be obtained from whole blood using a CTC-based approach. Multigene classifiers in this setting may allow for the development of noninvasive predictive biomarkers to guide clinical management.

Simple and rapid enrichment of circulating tumor cells (CTCs) for RNAseq in metastatic castrate resistant prostate cancer (mCRPC).

e16587 Background: CTCs have the potential to reflect not only genomic alterations but also cancer-relevant transcriptomic phenotypes. However, CTC gene expression has been hampered by signal-to-noise: rare CTC-derived transcripts are drowned out by abundant leukocyte-derived RNA. To date, a few specialized labs have achieved CTC RNAseq by capturing and analyzing single cells, a laborious and expensive approach not suitable for routine analysis of numerous samples. To address this need, we developed and validated a simple, rapid method for enrichment of live CTCs for RNAseq. Methods: Blood was drawn with informed consent under an IRB-approved protocol. Prostate cancer cell line spike-in samples were used to optimize live CTC enrichment by sequential leukocyte depletion (RosetteSep, Stem Cell Technologies) and size-based enrichment (Parsortix, Angle). Cancer-specific gene expression was first measured by multiplexed prostate specific qRT-PCR and subsequently by whole transcriptome amplification (WTA, SMARTer V2, Clontech) and RNAseq. Four patient samples were similarly analyzed by enrichment and RNAseq, along with spike-in positive controls and matched unenriched buffy coat negative controls. Results: Processing “from patient to RNA” took &lt; 3 hrs. and achieved mean CTC recovery of 30% (range 28-33%) and mean leukocyte background of 100 (range 47-179), a 100,000-fold enrichment. Prostate specific genes (AR, PSA, PSMA) were consistently detected by qRT-PCR from enriched samples but not from unenriched samples. When analyzed by RNAseq, patient samples clustered with spike-in positive controls and away from matched buffy coat controls by principle component analysis and by unsupervised hierarchical clustering. Differential gene expression (enriched vs. matched buffy coat) identified prostate cancer-relevant transcripts. Conclusions: We developed a simple and efficient method for live CTC enrichment and expression profiling, applicable to large numbers of patient samples. This approach can be used serially over time to detect known cancer-specific transcripts and to discover new gene expression signatures that reflect tumor biology and inform disease management.

Prediction of metastatic castrate-resistant prostate cancer response to abiraterone or enzalutamide by a baseline blood-based CTC gene expression signature.

e16529 Background: Prostate cancer is the most common cancer in men in the U.S., with 30% 5-year overall survival (OS) for patients (pts) with metastases. To take a precision medicine approach to the management of metastatic castrate-resistant prostate cancer (mCRPC), we developed a blood circulating tumor cell (CTC)-based test to identify mCRPC pts most likely to benefit from abiraterone (abi) or enzalutamide (enza). Methods: In this multi-institution prospective study, men with mCRPC were enrolled prior to starting abi (1,000 mg/d plus prednisone 10 mg/d) or enza (160 mg/d). At baseline (BL), 12 w, and progression, blood samples were collected for CellSearch-based CTC enumeration and qPCR-based gene expression analysis. Results: 69 pts (median age 68 y [50-82]) received abi (n = 25) or enza (n = 44) and had evaluable blood samples. Consistent with prior publications, among 43 pts with BL CTC &gt; 0, clearance of detectable CTCs (BL CTCs &gt; 0 and 12 w CTCs = 0), was achieved in 24 patients (55.8%), and was associated with greater median OS (31 mo vs. 18 mo, log-rank p = 0.03). The 43 pts with BL CTC &gt; 0 were then randomly divided into training (n = 31) and validation (n = 12) sets. Baseline gene expression data for the training set was used to develop a model to predict CTC clearance, starting with a panel of 141 expressed genes/isoforms including those associated with prostate cancer. Of the models tested, random forest yielded the best performance, with respective training and validation set sensitivity of 0.7 and 1, specificity 0.75 and 0.71, AUC 0.88 and 0.91. Top genes identified include those previously associated with disease – HOXB13, ESRP2, KLK3, GRHL2, and KRT19, among others. Conclusions: A gene expression signature from a baseline blood sample with CellSearch-enriched CTCs can predict clearance of detectable CTCs in response to abi/enza with high AUC and may give insight into molecular mechanisms of response. A prospective study with a larger number of patients will be required to further validate our findings. Ultimately, this blood test has the potential to select the patients most likely to benefit from second-generation antiandrogen vs. non-hormonal systemic treatment.

Transcriptomic Profiling of Circulating Tumor Cells (CTCs) in Multiple Myeloma (MM): A New Model to Understand Disease Dissemination

Background. The number of CTC predicts risk of transformation in smoldering MM and survival in active MM. Growing evidence suggests that as the tumor progresses and the microenvironment becomes hypoxic, clonal plasma cells (PC) constantly invade new regions of the bone marrow (BM) through induced systemic recirculation. Of note, the frequency of CTCs is typically low and thus, it is conceivable that the dissemination of MM depends on few tumor cells with unique features that induce them to egress the BM and spread the disease through peripheral blood (PB). This hypothesis has not been yet demonstrated because the transcriptional profile of CTCs in MM has not been investigated.Aim. To identify gene regulatory networks related to MM dissemination by comparing the transcriptional profile of CTCs with patient-matched BM clonal PCs.Methods. We used FACS to isolate CTCs and BM clonal PCs of paired PB and BM samples from 34 patients: 24 newly diagnosed MM, 9 relapsed MM and 1 MGUS. Transcriptomes were analyzed using Affymetrix arrays (n =31) and the BD WTA Precise assay was used for single-cell RNA sequencing (scRNAseq, n =3). Data was analyzed using Gene Set Enrichment Analysis (GSEA) and Limma for bulk and Seurat for scRNAseq data. The prognostic value of deregulated genes (FDR <0.1 & logFC >0.5) was investigated using a Cox-regression model in the CoMMpass dataset (n =553, IA11 release). The role of specific deregulated genes was evaluated by shRNA knockdown and blocking using a monoclonal antibody (mAb).Results. Transcriptomic profiling of patient matched CTCs and BM clonal PCs revealed a high correlation in gene expression (r =0.93; p =10-16). Only 45 genes emerged as significantly deregulated in CTCs, and GSEA unveiled biological functions related to inflammatory and interferon response (e.g. CCL5), signaling by IL-6/JAK/STAT3, IL-2/STAT5 and TNF via NFKB (CD44), the epithelial mesenchymal transition (EMP3), mitotic spindle and G2M checkpoints (TOP2A), or E2F targets (BIRC5). A high correlation in gene expression was also observed by scRNAseq (r =0.9; p =10-16), with only 31 genes (e.g. MALAT1, B2M, RHOH, ENAM or DUSP5) differentially expressed (adj.p <0.01). Under the hypothesis that genes deregulated in CTCs could be markers of dissemination and therefore of a more aggressive disease, we evaluated their prognostic significance in CoMMpass, assuming that BM clonal PCs with higher expression of these genes would be enriched in tumor cells with CTC-features. Accordingly, the expression levels of 12/33 upregulated genes in CTCs from bulk RNAseq data were associated with significantly different progression free survival (PFS). In the multivariate analysis including the above mentioned 33 genes and the R-ISS, only FLNA retained independent prognostic value; patients showing higher FLNA expression (n =185/553) had a significantly inferior PFS vs the remaining cases (medians of 22 and 47 months, respectively; p <.001). Of note, patients with higher FLNA expression also displayed significantly higher mutational burden (p =.003). After confirming that genes deregulated in CTCs were clinically meaningful, we selected two genes upregulated in CTCs (FLNA and CD44) to investigate their functional role. Interestingly, knockdown of both genes in the U266 MM cell line significantly altered actin polymerization (p ≤.003) leading to reduce migration (2-fold, p ≤0.01). Furthermore, we evaluated the effect of an anti-CD44 mAb in CB17/Icr-PrKdcscid/Crl immunodeficient mice treated with clodronate to avoid potential phagocytosis. After inoculation of MM1S-GFP intravenously and MM1S-tomato subcutaneously in Matrigel, mice were left untreated (n =11) or treated with a weekly intravenous injection of anti-CD44 (n =11) for one month and monitored weekly by bioluminescence. Overall, there was a significant reduction in the plasmacytoma volume (5-fold, p <.001) and cell engraftment of circulating MM1S cells (42-fold, p =.003) in treated mice.Conclusions. This is the first study analyzing the transcriptional profile of CTCs in MM. Our results reveal that gene expression of CTCs is almost identical to that of patient-matched BM clonal PCs, except for a few genes that are involved in interferon and inflammatory response, hypoxia, cell cycle and migration. Importantly, some of these genes are related to more aggressive disease and therefore, may represent novel therapeutic targets to overcome disease dissemination. [Display omitted] DisclosuresRios:Amgen, Celgene, Janssen, and Takeda: Consultancy. Martinez-Lopez:Pfizer: Research Funding; Vivia: Honoraria; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; BMS: Research Funding; Novartis: Research Funding. Hajek:Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding. San-Miguel:Sanofi: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Novartis: Honoraria; BMS: Honoraria; Roche: Honoraria.

Abstract B071: Circulating tumor cells as liquid biopsies of skeletal metastases from prostate cancer

Abstract Background: Circulating tumor cells (CTC) are promising biomarkers in advanced prostate cancer. Since they are seeded from metastases, they may also serve as liquid biopsies for skeletal metastases that are difficult to sample. The aim of the present study was to evaluate to which extent CTCs reflect the phenotype of skeletal metastases, and thereby their potential to serve as a clinical tool in individualizing treatment of metastatic prostate cancer. Materials and Method: CTC and tissue from skeletal metastases were sampled from 22 patients (8 GnRH-naïve and 14 castration-resistant) during surgery for spinal cord compression symptoms. CTCs were sampled prior to removal of metastatic tissue, and isolated with AdnaTest ProstateCancerSelect/Detect (Qiagen). Resulting cDNA was preamplified in a multiplex reaction and analyzed for expression of 37 genes related to prostate cancer progression and metastasis with qPCR. RNA was extracted from the metastatic tissue with RNeasy Plus Universal Mini kit (Qiagen), and gene expression was assessed in the same way as for CTCs. EPCAM expression level was used as internal control to enable normalization to epithelial content (CTCs or tumor tissue) of the samples. Correlation of detected signals between matched CTC and tissue was calculated with Pearson correlations. Results: 12 of the 37 genes displayed expression patterns that were correlating in paired CTC and metastatic samples. Using this subset of genes, the metastases could be grouped similarly to when all 37 genes were included in hierarchical clustering analyses. Using a smaller subset of genes and patients, defined by gene detection frequency in CTC samples, hierarchical clustering of gene expression in CTCs could group the patients similar to when expression data from the metastases were used. In addition, a subset of genes discriminating GnRH-naïve from castration-resistant metastases could be analyzed in CTCs, where it, to a large extent, could identify the same groups of patients. Conclusion: This study shows that gene expression patterns in CTCs can reflect those of metastases. However, careful selection of the genes to include is important. In addition, insufficient detection sensitivity in CTC analyses limits the range of the genes to be analyzed with current methodology. Taken together, the results imply that CTC phenotyping is a promising tool for individualized therapy in metastatic prostate cancer. Citation Format: Andreas Josefsson, Karin Larsson, Daniel Åhs, Helena Brisby, Jan-Erik Damber, Karin Welén. Circulating tumor cells as liquid biopsies of skeletal metastases from prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr B071.