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Purpose: Pancreatic ductal adenocarcinoma (PDAC) is associated with a poor prognosis. Multianalyte signatures, including liquid biopsy and traditional clinical variables, have shown promise for improving prognostication in other solid tumors but have not yet been rigorously assessed for PDAC., Materials and Methods: We performed a prospective cohort study of patients with newly diagnosed locally advanced pancreatic cancer (LAPC) or metastatic PDAC (mPDAC) who were planned to undergo systemic therapy. We collected peripheral blood before systemic therapy and assessed circulating tumor cells (CTCs), cell-free DNA concentration (cfDNA), and circulating tumor KRAS (ctKRAS)-variant allele fraction (VAF). Association of variables with overall survival (OS) was assessed in univariate and multivariate survival analysis, and comparisons were made between models containing liquid biopsy variables combined with traditional clinical prognostic variables versus models containing traditional clinical prognostic variables alone., Results: One hundred four patients, 40 with LAPC and 64 with mPDAC, were enrolled. CTCs, cfDNA concentration, and ctKRAS VAF were all significantly higher in patients with mPDAC than patients with LAPC. ctKRAS VAF (cube root; 0.05 unit increments; hazard ratio, 1.11; 95% CI, 1.03 to 1.21; P = .01), and CTCs ≥ 1/mL (hazard ratio, 2.22; 95% CI, 1.34 to 3.69; P = .002) were significantly associated with worse OS in multivariate analysis while cfDNA concentration was not. A model selected by backward selection containing traditional clinical variables plus liquid biopsy variables had better discrimination of OS compared with a model containing traditional clinical variables alone (optimism-corrected Harrell's C-statistic 0.725 v 0.681)., Conclusion: A multianalyte prognostic signature containing CTCs, ctKRAS, and cfDNA concentration outperformed a model containing traditional clinical variables alone suggesting that CTCs, ctKRAS, and cfDNA provide prognostic information complementary to traditional clinical variables in advanced PDAC.

Background: Precision medicine approaches for managing patients with metastatic castrate-resistant prostate cancer (mCRPC) are lacking. Non-invasive approaches for molecular monitoring of disease are urgently needed, especially for patients suffering from bone metastases for whom tissue biopsy is challenging. Here we utilized baseline blood samples to identify mCRPC patients most likely to benefit from abiraterone plus prednisone (AAP) or enzalutamide., Methods: Baseline blood samples were collected for circulating tumor cell (CTC) enumeration and qPCR-based gene expression analysis from 51 men with mCRPC beginning treatment with abiraterone or enzalutamide., Results: Of 51 patients (median age 68 years [51-82]), 22 received AAP (abiraterone 1000 mg/day plus prednisone 10 mg/day) and 29 received enzalutamide (160 mg/day). The cohort was randomly divided into training (n = 37) and test (n = 14) sets. Baseline clinical variables (Gleason score, PSA, testosterone, and hemoglobin), CTC count, and qPCR-based gene expression data for 141 genes/isoforms in CTC-enriched blood were analyzed with respect to overall survival (OS). Genes with expression most associated with OS included MSLN, ARG2, FGF8, KLK3, ESRP2, NPR3, CCND1, and WNT5A. Using a Cox-elastic net model for our test set, the 8-gene expression signature had a c-index of 0.87 (95% CI [0.80, 0.94]) and was more strongly associated with OS than clinical variables or CTC count alone, or a combination of the three variables. For patients with a low-risk vs. high-risk gene expression signature, median OS was not reached vs. 18 months, respectively (HR 5.32 [1.91-14.80], p = 0.001). For the subset of 41 patients for whom progression-free survival (PFS) data was available, the median PFS for patients with a low-risk vs high-risk gene expression signature was 20 vs. 5 months, respectively (HR 2.95 [1.46-5.98], p = 0.003)., Conclusions: If validated in a larger prospective study, this test may predict patients most likely to benefit from second-generation antiandrogen therapy.

Circulating tumor cells (CTCs) carry valuable biological information. While enumeration of CTCs in peripheral blood is an FDA-approved prognostic indicator of survival in metastatic prostate and other cancers, analysis of CTC phenotypic and genomic markers is needed to identify cancer origin and elucidate pathways that can guide therapeutic selection for personalized medicine. Given the emergence of single-cell mRNA sequencing technologies, a method is needed to isolate CTCs with high sensitivity and specificity as well as compatibility with downstream genomic analysis. Flow cytometry is a powerful tool to analyze and sort single cells, but pre-enrichment is required prior to flow sorting for efficient isolation of CTCs due to the extreme low frequency of CTCs in blood (one in billions of blood cells). While current enrichment technologies often require many steps and result in poor recovery, we demonstrate a magnetic separator and acoustic microfluidic focusing chip integrated system that enriches rare cells in-line with FACS™ (fluorescent activated cell sorting) and single-cell sequencing. This system analyzes, isolates, and index sorts single cells directly into 96-well plates containing reagents for Molecular Indexing (MI) and transcriptional profiling of single cells. With an optimized workflow using the integrated enrichment-FACS system, we performed a proof-of-concept experiment with spiked prostate cancer cells in peripheral blood and achieved: (i) a rapid one-step process to isolate rare cancer cells from lysed whole blood; (ii) an average of 92% post-enrichment cancer cell recovery (R 2 = 0.9998) as compared with 55% recovery for a traditional benchtop workflow; and (iii) detection of differentially expressed genes at a single cell level that are consistent with reported cell-type dependent expression signatures for prostate cancer cells. These model system results lay the groundwork for applying our approach to human blood samples from prostate and other cancer patients, and support the enrichment-FACS system as a flexible solution for isolation and characterization of CTCs for cancer diagnosis. © 2018 International Society for Advancement of Cytometry., (© 2018 International Society for Advancement of Cytometry.)

Comprehensive molecular analysis of rare circulating tumor cells (CTCs) and cell clusters is often hampered by low throughput and purity, as well as cell loss. To address this, we developed a fully integrated platform for flow cytometry-based isolation of CTCs and clusters from blood that can be combined with whole transcriptome analysis or targeted RNA transcript quantification. Downstream molecular signature can be linked to cell phenotype through index sorting. This newly developed platform utilizes in-line magnetic particle-based leukocyte depletion, and acoustic cell focusing and washing to achieve >98% reduction of blood cells and non-cellular debris, along with >1.5 log-fold enrichment of spiked tumor cells. We could also detect 1 spiked-in tumor cell in 1 million WBCs in 4/7 replicates. Importantly, the use of a large 200μm nozzle and low sheath pressure (3.5 psi) minimized shear forces, thereby maintaining cell viability and integrity while allowing for simultaneous recovery of single cells and clusters from blood. As proof of principle, we isolated and transcriptionally characterized 63 single CTCs from a genetically engineered pancreatic cancer mouse model (n = 12 mice) and, using index sorting, were able to identify distinct epithelial and mesenchymal sub-populations based on linked single cell protein and gene expression.

The use of microtechnology for the highly selective isolation and sensitive detection of circulating tumor cells has shown enormous promise. One challenge for this technology is that the small feature sizes - which are the key to this technology's performance - can result in low sample throughput and susceptibility to clogging. Additionally, conventional molecular analysis of CTCs often requires cells to be taken off-chip for sample preparation and purification before analysis, leading to the loss of rare cells. To address these challenges, we have developed a microchip platform that combines fast, magnetic micropore based negative immunomagnetic selection (>10 mL h -1 ) with rapid on-chip in situ RNA profiling (>100× faster than conventional RNA labeling). This integrated chip can isolate both rare circulating cells and cell clusters directly from whole blood and allow individual cells to be profiled for multiple RNA cancer biomarkers, achieving sample-to-answer in less than 1 hour for 10 mL of whole blood. To demonstrate the power of this approach, we applied our device to the circulating tumor cell based diagnosis of pancreatic cancer. We used a genetically engineered lineage-labeled mouse model of pancreatic cancer (KPCY) to validate the performance of our chip. We show that in a cohort of patient samples (N = 25) that this device can detect and perform in situ RNA analysis on circulating tumor cells in patients with pancreatic cancer, even in those with extremely sparse CTCs (<1 CTC mL -1 of whole blood).

The identification of therapeutically targetable mutations in circulating tumor cells (CTCs) from cancer patient blood is increasingly used to personalize patient care. Here, we describe a novel approach for the enumeration, capture, and molecular analysis of CTCs from blood using an FDA-approved CTC enrichment and enumeration platform followed by dielectrophoretic capture and next-generation sequencing.