Characterisation of circulating tumour cell phenotypes identifies a partial-EMT sub-population for clinical stratification of pancreatic cancer.

BACKGROUND: Limited accessibility of the tumour precludes longitudinal characterisation for therapy guidance in pancreatic ductal adenocarcinoma (PDAC). METHODS: We utilised dielectrophoresis-field flow fractionation (DEP-FFF) to isolate circulating tumour cells (CTCs) in 272 blood draws from 74 PDAC patients (41 localised, 33 metastatic) to non-invasively monitor disease progression. RESULTS: Analysis using multiplex imaging flow cytometry revealed four distinct sub-populations of CTCs: epithelial (E-CTC), mesenchymal (M-CTC), partial epithelial-mesenchymal transition (pEMT-CTC) and stem cell-like (SC-CTC). Overall, CTC detection rate was 76.8% (209/272 draws) and total CTC counts did not correlate with any clinicopathological variables. However, the proportion of pEMT-CTCs (prop-pEMT) was correlated with advanced disease, worse progression-free and overall survival in all patients, and earlier recurrence after resection. CONCLUSION: Our results underscore the importance of immunophenotyping and quantifying specific CTC sub-populations in PDAC.

Circulating Nucleic Acids Are Associated With Outcomes of Patients With Pancreatic Cancer.

BACKGROUND & AIMS: We aimed to investigate the clinical utility of circulating tumor cell DNA (ctDNA) and exosome DNA (exoDNA) in pancreatic cancer. METHODS: We collected liquid biopsy samples from 194 patients undergoing treatment for localized or metastatic pancreatic adenocarcinoma from April 7, 2015, through October 13, 2017 (425 blood samples collected before [baseline] and during therapy). Additional liquid biopsy samples were collected from 37 disease control individuals. Droplet digital polymerase chain reaction was used to determine KRAS mutant allele fraction (MAF) from ctDNA and exoDNA purified from plasma. For the longitudinal analysis, we analyzed exoDNA and ctDNA in 123 serial blood samples from 34 patients. We performed analysis including Cox regression, Fisher exact test, and Bayesian inference to associate KRAS MAFs in exoDNA and ctDNA with prognostic and predictive outcomes. RESULTS: In the 34 patients with potentially resectable tumors, an increase in exoDNA level after neoadjuvant therapy was significantly associated with disease progression (P = .003), whereas ctDNA did not show correlations with outcomes. Concordance rates of KRAS mutations present in surgically resected tissue and detected in liquid biopsy samples were greater than 95%. On univariate analysis, patients with metastases and detectable ctDNA at baseline status had significantly shorter times of progression-free survival (PFS) (hazard ratio [HR] for death, 1.8; 95% CI, 1.1-3.0; P = .019), and overall survival (OS) (HR, 2.8; 95% CI, 1.4-5.7; P = .0045) compared with patients without detectable ctDNA. On multivariate analysis, MAFs ≥5% in exoDNA were a significant predictor of PFS (HR, 2.28; 95% CI, 1.18-4.40; P = .014) and OS (HR, 3.46; 95% CI, 1.40-8.50; P = .007). A multianalyte approach showed detection of both ctDNA and exoDNA MAFs ≥5% at baseline status to be a significant predictor of OS (HR, 7.73, 95% CI, 2.61-22.91, P = .00002) on multivariate analysis. In the longitudinal analysis, an MAF peak above 1% in exoDNA was significantly associated with radiologic progression (P = .0003). CONCLUSIONS: In a prospective cohort of pancreatic cancer patients, we show how longitudinal monitoring using liquid biopsy samples through exoDNA and ctDNA provides both predictive and prognostic information relevant to therapeutic stratification.

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-Specific Transcriptome and Molecular Subtype.

Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predicted consensus molecular subtypes in patients with metastatic colorectal cancer. Analysis of plasma evRNA also enabled monitoring of changes in transcriptomic subtype under treatment selection pressure and identification of molecular pathways associated with recurrence. This approach also revealed expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of using transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to the identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling. SIGNIFICANCE: The development of an approach to interrogate molecular subtypes, cancer-associated pathways, and differentially expressed genes through RNA sequencing of plasma extracellular vesicles lays the foundation for liquid biopsy-based longitudinal monitoring of patient tumor transcriptomes.

Significance of Distinct Liquid Biopsy Compartments in Evaluating Somatic Mutations for Targeted Therapy Selection in Cancer of Unknown Primary.

PURPOSE: Cancer of unknown primary (CUP) accounts for 2-5% of all cancer diagnoses, wherein standard investigations fail to reveal the original tumor site. Basket trials allocate targeted therapeutics based on actionable somatic mutations, independent of tumor entity. These trials, however, mostly rely on variants identified in tissue biopsies. Since liquid biopsies (LB) represent the overall tumor genomic landscape, they may provide an ideal diagnostic source in CUP patients. To identify the most informative liquid biopsy compartment, we compared the utility of genomic variant analysis for therapy stratification in two LB compartments (circulating cell-free (cf) and extracellular vesicle (ev) DNA). METHODS: CfDNA and evDNA from 23 CUP patients were analyzed using a targeted gene panel covering 151 genes. Identified genetic variants were interpreted regarding diagnostic and therapeutic relevance using the MetaKB knowledgebase. RESULTS: LB revealed a total of 22 somatic mutations in evDNA and/or cfDNA in 11/23 patients. Out of the 22 identified somatic variants, 14 are classified as Tier I druggable somatic variants. Comparison of variants identified in evDNA and cfDNA revealed an overlap of 58% of somatic variants in both LB compartments, whereas over 40% of variants were only found in one or the other compartment. CONCLUSION: We observed substantial overlap between somatic variants identified in evDNA and cfDNA of CUP patients. Nonetheless, interrogation of both LB compartments can potentially increase the rate of druggable alterations, stressing the significance of liquid biopsies for possible primary-independent basket and umbrella trial inclusion.

Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution.

Heterogeneity is a hallmark of cancer. The advent of single-cell technologies has helped uncover heterogeneity in a high-throughput manner in different cancers across varied contexts. Here we apply single-cell sequencing technologies to reveal inherent heterogeneity in assumptively monoclonal pancreatic cancer (PDAC) cell lines and patient-derived organoids (PDOs). Our findings reveal a high degree of both genomic and transcriptomic polyclonality in monolayer PDAC cell lines, custodial variation induced by growing apparently identical cell lines in different laboratories, and transcriptomic shifts in transitioning from 2D to 3D spheroid growth models. Our findings also call into question the validity of widely available immortalized, non-transformed pancreatic lines as contemporaneous "control" lines in experiments. We confirm these findings using a variety of independent assays, including but not limited to whole exome sequencing, single-cell copy number variation sequencing (scCNVseq), single-nuclei assay for transposase-accessible chromatin with sequencing, fluorescence in-situ hybridization, and single-cell RNA sequencing (scRNAseq). We map scRNA expression data to unique genomic clones identified by orthogonally-gathered scCNVseq data of these same PDAC cell lines. Further, while PDOs are known to reflect the cognate in vivo biology of the parental tumor, we identify transcriptomic shifts during ex vivo passage that might hamper their predictive abilities over time. The impact of these findings on rigor and reproducibility of experimental data generated using established preclinical PDAC models between and across laboratories is uncertain, but a matter of concern.

Elucidation of Tumor-Stromal Heterogeneity and the Ligand-Receptor Interactome by Single-Cell Transcriptomics in Real-world Pancreatic Cancer Biopsies.

PURPOSE: Precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. With molecular subtypes of PDAC gaining relevance in the context of therapeutic stratification, the ability to characterize heterogeneity of cancer-specific gene expression patterns is of great interest. In addition, understanding patterns of immune evasion within PDAC is of importance as novel immunotherapeutic strategies are developed. EXPERIMENTAL DESIGN: Single-cell RNA sequencing (scRNA-seq) is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes. RESULTS: Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast subclasses, and predicts for a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches. CONCLUSIONS: Our analysis demonstrates that the use of de novo biopsies from patients with PDAC paired with scRNA-seq may facilitate therapeutic prediction from limited biopsy samples.

Defining the Comprehensive Genomic Landscapes of Pancreatic Ductal Adenocarcinoma Using Real-World Endoscopic Aspiration Samples.

PURPOSE: Most patients with pancreatic ductal adenocarcinoma (PDAC) present with surgically unresectable cancer. As a result, endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is the most common biospecimen source available for diagnosis in treatment-naïve patients. Unfortunately, these limited samples are often not considered adequate for genomic analysis, precluding the opportunity for enrollment on precision medicine trials. EXPERIMENTAL DESIGN: Applying an epithelial cell adhesion molecule (EpCAM)-enrichment strategy, we show the feasibility of using real-world EUS-FNA for in-depth, molecular-barcoded, whole-exome sequencing (WES) and somatic copy-number alteration (SCNA) analysis in 23 patients with PDAC. RESULTS: Potentially actionable mutations were identified in >20% of patients. Further, an increased mutational burden and higher aneuploidy in WES data were associated with an adverse prognosis. To identify predictive biomarkers for first-line chemotherapy, we developed an SCNA-based complexity score that was associated with response to platinum-based regimens in this cohort. CONCLUSIONS: Collectively, these results emphasize the feasibility of real-world cytology samples for in-depth genomic characterization of PDAC and show the prognostic potential of SCNA for PDAC diagnosis.

Single-Cell Transcriptomics of Pancreatic Cancer Precursors Demonstrates Epithelial and Microenvironmental Heterogeneity as an Early Event in Neoplastic Progression.

PURPOSE: Early detection of pancreatic ductal adenocarcinoma (PDAC) remains elusive. Precursor lesions of PDAC, specifically intraductal papillary mucinous neoplasms (IPMNs), represent a bona fide pathway to invasive neoplasia, although the molecular correlates of progression remain to be fully elucidated. Single-cell transcriptomics provides a unique avenue for dissecting both the epithelial and microenvironmental heterogeneities that accompany multistep progression from noninvasive IPMNs to PDAC. EXPERIMENTAL DESIGN: Single-cell RNA sequencing was performed through droplet-based sequencing on 5,403 cells from 2 low-grade IPMNs (LGD-IPMNs), 2 high-grade IPMNs (HGD-IPMN), and 2 PDACs (all surgically resected). RESULTS: Analysis of single-cell transcriptomes revealed heterogeneous alterations within the epithelium and the tumor microenvironment during the progression of noninvasive dysplasia to invasive cancer. Although HGD-IPMNs expressed many core signaling pathways described in PDAC, LGD-IPMNs harbored subsets of single cells with a transcriptomic profile that overlapped with invasive cancer. Notably, a proinflammatory immune component was readily seen in low-grade IPMNs, composed of cytotoxic T cells, activated T-helper cells, and dendritic cells, which was progressively depleted during neoplastic progression, accompanied by infiltration of myeloid-derived suppressor cells. Finally, stromal myofibroblast populations were heterogeneous and acquired a previously described tumor-promoting and immune-evading phenotype during invasive carcinogenesis. CONCLUSIONS: This study demonstrates the ability to perform high-resolution profiling of the transcriptomic changes that occur during multistep progression of cystic PDAC precursors to cancer. Notably, single-cell analysis provides an unparalleled insight into both the epithelial and microenvironmental heterogeneities that accompany early cancer pathogenesis and might be a useful substrate to identify targets for cancer interception.See related commentary by Hernandez-Barco et al., p. 2027.