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.
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.
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.
Our analysis demonstrates that the use of
biopsies from patients with PDAC paired with scRNA-seq may facilitate therapeutic prediction from limited biopsy samples.
Pancreatic ductal adenocarcinoma (PDAC) has a hypoxic, immunosuppressive stroma that contributes to its resistance to immune checkpoint blockade therapies. The hypoxia-inducible factors (HIFs) ...mediate the cellular response to hypoxia, but their role within the PDAC tumor microenvironment remains unknown.
We used a dual recombinase mouse model to delete Hif1α or Hif2α in α-smooth muscle actin–expressing cancer-associated fibroblasts (CAFs) arising within spontaneous pancreatic tumors. The effects of CAF HIF2α expression on tumor progression and composition of the tumor microenvironment were evaluated by Kaplan-Meier analysis, reverse transcription quantitative real-time polymerase chain reaction, histology, immunostaining, and by both bulk and single-cell RNA sequencing. CAF-macrophage crosstalk was modeled ex vivo using conditioned media from CAFs after treatment with hypoxia and PT2399, an HIF2 inhibitor currently in clinical trials. Syngeneic flank and orthotopic PDAC models were used to assess whether HIF2 inhibition improves response to immune checkpoint blockade.
CAF-specific deletion of Hif2α, but not Hif1α, suppressed PDAC tumor progression and growth, and improved survival of mice by 50% (n = 21–23 mice/group, Log-rank P = .0009). Deletion of CAF-HIF2 modestly reduced tumor fibrosis and significantly decreased the intratumoral recruitment of immunosuppressive M2 macrophages and regulatory T cells. Treatment with the clinical HIF2 inhibitor PT2399 significantly reduced in vitro macrophage chemotaxis and M2 polarization, and improved tumor responses to immunotherapy in both syngeneic PDAC mouse models.
Together, these data suggest that stromal HIF2 is an essential component of PDAC pathobiology and is a druggable therapeutic target that could relieve tumor microenvironment immunosuppression and enhance immune responses in this disease.
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In this study, we show that blocking the function of a protein called hypoxia-inducible factor-2 can improve the response of pancreatic cancer to immunotherapy.
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.
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.
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.
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.
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.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States. The overwhelming majority of patients (up to 85%) present with unresectable ...disease, and the 5-year survival rate stands at a dire 9%. Current chemotherapeutic regimens extend survival by only a few months, and the molecular underpinnings of treatment failure in advanced disease remain largely unknown. Recently, single-cell sequencing techniques have emerged as highly effective methods to uncover intratumoral heterogeneity across many cancer types, including PDAC. These studies, and our own unpublished data, have reiterated profound transcriptomic subclonal diversity in PDAC, which likely underlies the divergent therapeutic responses and eventual treatment failure. Using a patient-derived organoid (PDO) platform, we have characterized, on the single cell level, gene expression and regulation profiles to understand the heterogeneity and clinical utility of this model. We applied predictive RNA-seq-based algorithms (CMap) to our initial PDO profiling data to design “custom” PDO combinatorial regimens as a true precision medicine-based approach. We are in the process of validating these predictions in vitro; however, preliminary single-cell RNA (scRNA-seq) data shows treatment PDOs with CMap-predicted compounds induced dramatic transcriptomic shifts in subclones reflective of an efficacious treatment strategy. Additionally, we conducted single-nuclei ATAC sequencing (snATAC-seq) of PDOs pre- and post-treatment with CMap-predicted compounds. This data, coupled to our scRNA-seq, allowed for construction of chromatin regulatory maps, and determined alterations in chromatin accessibility and gene regulation induced by targeted combinatorial therapeutics. These findings provide meaningful insight to biological processes driven by treatment-induced chromatin accessibility, and its relationship to heterogeneous transcriptional architecture. Our data suggests that differential regulation across PDO subclones may drive responses to therapy and acquired resistance mechanisms observed in the clinic, which could be predicted and therapeutically targeted with scRNA sequencing. Thus, this work represents the importance of leveraging subclonal architecture in the preclinical space to ensure both treatment efficacy and the consideration of novel therapeutic combinations in PDAC patients.
Citation Format: Paola A. Guerrero, Anirban Maitra, Maria E. Monberg, Jaewon J Lee, Vincent Bernard-Pagan, Senthil Muthuswamy. Elucidating intratumoral heterogeneity and predicting effective combination regimens in PDAC PDOs using scRNA-seq and snATAC-seq abstract. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PO-010.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the 3rd leading cause of cancer-related deaths in the United States. This is largely due to the fact of high propensity of patients presenting at ...metastatic stages resulting from symptom ambiguity and a complete lack of general population screening programs. As the overwhelming majority of patients (85%) present with surgically unresectable disease, the 5-year survival rate is dire at only ~8%. Outside of what is known of the commonly mutated genes in PDAC, which include KRAS, TP53, SMAD4, and CDKN2A, little molecular information exists that has yielded clinical knowledge that may have an impact on survival outcomes. Therefore, a concerted clinical and research paradigm shift towards higher-resolution investigations of the genomics of PDAC is an area of highest public health significance. In our laboratory, we have leveraged single-cell sequencing approaches in both cell lines and patient-derived tissues to develop models for molecular underpinnings of PDAC and as potential tools for therapeutic stratification. First, to demonstrate the ability to model cellular heterogeneity of tumor populations, single-cell RNA and DNA sequencing was applied to widely used patient-derived PDAC cell lines. Using a bioinformatics pipeline, were able to differentiate between supposedly identical cell lines that had evolved rich subclonal architecture that may provide insight into complex in silico landscapes that naturally evolve as these cells are continuously used by laboratories. We then characterized single-cell gene expression profiles of patient-derived organoids (PDOs) to understand their heterogeneous composition and applied an in silico therapeutic drug prediction model to identify and validate combinatorial strategies targeting subpopulations. These present multiple phenotypic traits similar to that of the parental tumor including histoarchitecture, oxygen biology, epigenetic marking, and differentiation status. Orthogonal validation of predicted drugs was confirmed through a high-throughput drug screen of 764 agency-approved candidates on two PDOs. This strategy demonstrated the utility of single-cell transcriptomic profiling from PDOs in effectively identifying heterogeneous enriched pathways and molecular subtypes within cultures to predict viable treatment options using a pharmacogenomic approach.
Citation Format: Maria E. Monberg, Vincent B. Pagan, Alexander Semaan, Jaewon J. Lee, Paola A. Guerrero, Senthil K. Muthuswamy, Anirban Maitra. Single-cell profiling reveals subclonal vulnerabilities to therapy in patient-derived 2D and organoid models abstract. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr A33.
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