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Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment.

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment naive. We uncovered recurrent expression programs across malignant cells and fibroblasts, including a newly identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities with distinct contributions from malignant, fibroblast and immune subtypes: classical, squamoid-basaloid and treatment enriched. Our refined molecular and cellular taxonomy can provide a framework for stratification in clinical trials and serve as a roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.

SUBMITTER: Hwang WL

PROVIDER: S-EPMC10290535 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment.

Hwang William L WL Jagadeesh Karthik A KA Guo Jimmy A JA Hoffman Hannah I HI Yadollahpour Payman P Reeves Jason W JW Mohan Rahul R Drokhlyansky Eugene E Van Wittenberghe Nicholas N Ashenberg Orr O Farhi Samouil L SL Schapiro Denis D Divakar Prajan P Miller Eric E Zollinger Daniel R DR Eng George G Schenkel Jason M JM Su Jennifer J Shiau Carina C Yu Patrick P Freed-Pastor William A WA Abbondanza Domenic D Mehta Arnav A Gould Joshua J Lambden Conner C Porter Caroline B M CBM Tsankov Alexander A Dionne Danielle D Waldman Julia J Cuoco Michael S MS Nguyen Lan L Delorey Toni T Phillips Devan D Barth Jaimie L JL Kem Marina M Rodrigues Clifton C Ciprani Debora D Roldan Jorge J Zelga Piotr P Jorgji Vjola V Chen Jonathan H JH Ely Zackery Z Zhao Daniel D Fuhrman Kit K Fropf Robin R Beechem Joseph M JM Loeffler Jay S JS Ryan David P DP Weekes Colin D CD Ferrone Cristina R CR Qadan Motaz M Aryee Martin J MJ Jain Rakesh K RK Neuberg Donna S DS Wo Jennifer Y JY Hong Theodore S TS Xavier Ramnik R Aguirre Andrew J AJ Rozenblatt-Rosen Orit O Mino-Kenudson Mari M Castillo Carlos Fernandez-Del CF Liss Andrew S AS Ting David T DT Jacks Tyler T Regev Aviv A

Nature genetics 20220728 8

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either receive ...[more]

PMID: 35902743

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Project description:BackgroundSingle-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts.MethodsWe obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library.ResultsFirst, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo.ConclusionsIn summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo.

Dataset Information

Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment.

Publications

Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment.

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