Cellular Heterogeneity During Mouse Pancreatic Ductal Adenocarcinoma Progression at Single-Cell Resolution
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Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution Abdel Nasser Hosein, … , Udit Verma, Rolf A. Brekken JCI Insight. 2019. https://doi.org/10.1172/jci.insight.129212. Research In-Press Preview Gastroenterology Oncology Pancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death with limited therapeutic options available. This highlights the need for improved understanding of the biology of PDA progression, a highly complex and dynamic process featuring changes in cancer cells and stromal cells. A comprehensive characterization of PDA cancer cell and stromal cell heterogeneity during disease progression is lacking. In this study, we aimed to profile cell populations and understand their phenotypic changes during PDA progression. To that end, we employed single-cell RNA sequencing technology to agnostically profile cell heterogeneity during different stages of PDA progression in genetically engineered mouse models. Our data indicate that an epithelial-to-mesenchymal transition of cancer cells accompanies tumor progression in addition to distinct populations of macrophages with increasing inflammatory features. We also noted the existence of three distinct molecular subtypes of fibroblasts in the normal mouse pancreas, which ultimately gave rise to two distinct populations of fibroblasts in advanced PDA, supporting recent reports on intratumoral fibroblast heterogeneity. Our data also suggest that cancer cells and fibroblasts may be dynamically regulated by epigenetic mechanisms. This study systematically describes the landscape of cellular heterogeneity during the progression of PDA and has the potential to act as a resource in the development of therapeutic strategies against specific cell populations of the disease. Find the latest version: https://jci.me/129212/pdf 1 Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at 2 single-cell resolution 3 4 Abdel Nasser Hosein1,2,3, Huocong Huang1, Zhaoning Wang4, Kamalpreet Parmar5, Wenting 5 Du1, Jonathan Huang3, Anirban Maitra3,6, Eric Olson4, Udit Verma2, Rolf A. Brekken1,7,8 6 7 1. Hamon Center for Therapeutic Oncology Research, Division of Surgical Oncology, 8 Department of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, 9 USA. 10 2. Department of Internal Medicine – Division of Hematology & Oncology, University of Texas 11 Southwestern Medical Center, Dallas, Texas, USA. 12 3. Department of Translational Molecular Pathology, University of Texas MD Anderson 13 Cancer Center, Houston, TX, USA. 14 4. Department of Molecular Biology, University of Texas Southwestern Medical Center, 15 Dallas, Texas, USA. 16 5. Department of Pathology, University of Texas Southwestern Medical Center, Dallas, 17 Texas, USA. 18 6. Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 19 USA. 20 7. Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, 21 Texas, USA. 22 8. Department of Surgery – Division of Surgical Oncology, University of Texas Southwestern 23 Medical Center, Dallas, Texas, USA. 24 25 Short title: scRNA-seq of PDA GEMMs 26 27 Corresponding author 28 Rolf A. Brekken, PhD 29 Hamon Center for Therapeutic Oncology Research 30 University of Texas Southwestern Medical Center 31 6000 Harry Hines Blvd. 32 Dallas, TX 75390-8593 33 Tel: 214.648.5151; Fax: 214.648.4940 34 [email protected] 35 36 1 37 Disclosures 38 AM has received royalties from Cosmos Wisdom Biotechnology for a biomarker assay related to 39 early detection of pancreatic cancer. All other authors have no conflicts of interest to report. 40 Funding 41 This work was supported by NIH grants R01 CA192381 and U54 CA210181 Project 2 to RAB, 42 the Effie Marie Cain Fellowship to RAB, the H. Ray and Paula Calvert Pancreatic Cancer 43 Research Fund to UV, NIH grants U01 CA200468, U01 CA196403, R01 CA218004, R01 44 CA204969, P01 CA117696, to AM and grants from the NIH and Welch Foundation to EO. Z.W. 45 was supported by a predoctoral fellowship from the American Heart Association and the Harry 46 S. Moss Heart Trust (19PRE34380436). 47 48 Abbreviations 49 ADM, acinar-to-ductal metaplasia 50 BET, bromodomain and extraterminal 51 CAF, cancer-associated fibroblast 52 FB, fibroblast population 53 GEM, gel bead in emulsion 54 GEMM, genetically engineered mouse model 55 GO, gene ontology 56 PDA, pancreatic ductal adenocarcinoma 57 PSC, pancreatic stellate cell 58 scRNA-seq, single-cell RNA sequencing 59 UMI, unique molecular identifiers 60 2 61 Abstract: 62 Pancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death with limited 63 therapeutic options available. This highlights the need for improved understanding of the biology 64 of PDA progression, a highly complex and dynamic process featuring changes in cancer cells 65 and stromal cells. A comprehensive characterization of PDA cancer cell and stromal cell 66 heterogeneity during disease progression is lacking. In this study, we aimed to profile cell 67 populations and understand their phenotypic changes during PDA progression. To that end, we 68 employed single-cell RNA sequencing technology to agnostically profile cell heterogeneity 69 during different stages of PDA progression in genetically engineered mouse models. Our data 70 indicate that an epithelial-to-mesenchymal transition of cancer cells accompanies tumor 71 progression in addition to distinct populations of macrophages with increasing inflammatory 72 features. We also noted the existence of three distinct molecular subtypes of fibroblasts in the 73 normal mouse pancreas, which ultimately gave rise to two distinct populations of fibroblasts in 74 advanced PDA, supporting recent reports on intratumoral fibroblast heterogeneity. Our data also 75 suggest that cancer cells and fibroblasts may be dynamically regulated by epigenetic 76 mechanisms. This study systematically describes the landscape of cellular heterogeneity during 77 the progression of PDA and has the potential to act as a resource in the development of 78 therapeutic strategies against specific cell populations of the disease. 79 80 Key words: single-cell RNA sequencing; pancreatic cancer; cellular heterogeneity; fibroblasts; 81 macrophages 82 3 83 Introduction 84 Pancreatic ductal adenocarcinoma (PDA) carries the highest mortality rate of all major 85 malignancies in industrialized countries, with a 5-year survival of 8.5%. Patients are faced with 86 limited treatment options that achieve poor durable response rates, highlighting the need for an 87 improved understanding of PDA disease biology [1]. PDA progression is a complex and 88 dynamic process that requires interaction between cancer cells and stromal cells [2]. It is 89 characterized by the formation of a unique microenvironment consisting of heterogeneous 90 stromal cell populations that include fibroblasts, macrophages, lymphocytes, and endothelial 91 cells. These stromal compartments are critical in driving PDA biology [3]. 92 93 The dynamic phenotypic changes in different cell populations during PDA progression is not 94 fully understood. Gene expression profiling of bulk tissues provides a limited picture of the 95 cellular complexity of the heterogeneous cell populations in PDA. In contrast, single-cell RNA 96 sequencing (scRNA-seq) has the potential to enable gene expression profiling at the level of the 97 individual cell [4] and provides a powerful tool to understand the cellular heterogeneity of PDA. 98 We applied scRNA-seq to investigate gene expression changes of cancer cells and stromal 99 cells during PDA progression in genetically engineered mouse models (GEMMs). This unbiased 100 approach provided evidence of considerable intratumoral cellular heterogeneity, including 101 molecular insights into epithelial and mesenchymal populations of cancer cells and distinct 102 molecular subtypes of macrophages and cancer-associated fibroblasts (CAFs). These data will 103 provide a resource for future studies aimed at further characterizing and targeting specific cell 104 populations in PDA. 105 106 Results 107 Cellular heterogeneity during PDA progression 108 We sought to determine the composition of single cells during the progression of PDA GEMMs. 109 Normal mouse pancreas, 40-day-old KIC [5] (KrasLSL-G12D/+; Ink4aflox/flox; Ptf1aCre/+) mouse 110 pancreas, termed “early KIC” (with the early lesion initially confirmed by ultrasound; 111 Supplementary Fig. 1), and 60-day-old KIC pancreas, termed “late KIC” (Fig. 1A) were freshly 112 isolated and enzymatically digested followed by single-cell cDNA library generation using the 113 10x Genomics platform [6]. Libraries were subsequently sequenced at a depth of more than 105 114 reads per cell. We performed stringent filtering, normalization, and graph-based clustering, 115 which identified distinct cell populations in the normal pancreas and both stages of PDA. 116 4 117 In the normal mouse pancreas, 2354 cells were sequenced and classified into appropriate cell 118 types based on the gene expression of known markers: acinar cells, islet & ductal cells 119 (Supplementary figure 2), macrophages, T cells, and B cells, as well as three distinct 120 populations of fibroblasts (Fig. 1B and E) were noted. In the early KIC lesion (3524 cells 121 sequenced), the emergence of an expanded ductal population was observed (9.9% of cells), 122 expressing known ductal markers such as Krt18 and Sox9 [7] and displaying early neoplastic 123 changes