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Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

ABSTRACT: Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease.

SUBMITTER: Cui Zhou D

PROVIDER: S-EPMC9470535 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

Cui Zhou Daniel D Jayasinghe Reyka G RG Chen Siqi S Herndon John M JM Iglesia Michael D MD Navale Pooja P Wendl Michael C MC Caravan Wagma W Sato Kazuhito K Storrs Erik E Mo Chia-Kuei CK Liu Jingxian J Southard-Smith Austin N AN Wu Yige Y Naser Al Deen Nataly N Baer John M JM Fulton Robert S RS Wyczalkowski Matthew A MA Liu Ruiyang R Fronick Catrina C CC Fulton Lucinda A LA Shinkle Andrew A Thammavong Lisa L Zhu Houxiang H Sun Hua H Wang Liang-Bo LB Li Yize Y Zuo Chong C McMichael Joshua F JF Davies Sherri R SR Appelbaum Elizabeth L EL Robbins Keenan J KJ Chasnoff Sara E SE Yang Xiaolu X Reeb Ashley N AN Oh Clara C Serasanambati Mamatha M Lal Preet P Varghese Rajees R Mashl Jay R JR Ponce Jennifer J Terekhanova Nadezhda V NV Yao Lijun L Wang Fang F Chen Lijun L Schnaubelt Michael M Lu Rita Jui-Hsien RJ Schwarz Julie K JK Puram Sidharth V SV Kim Albert H AH Song Sheng-Kwei SK Shoghi Kooresh I KI Lau Ken S KS Ju Tao T Chen Ken K Chatterjee Deyali D Hawkins William G WG Zhang Hui H Achilefu Samuel S Chheda Milan G MG Oh Stephen T ST Gillanders William E WE Chen Feng F DeNardo David G DG Fields Ryan C RC Ding Li L

Nature genetics 20220822 9

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor popul ...[more]

PMID: 35995947

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Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly fatal, aggressive cancer due to limited response chemotherapy. The tumor microenvironment (TME) has emerged as a key player in the development of chemoresistance and in malignant progression. In this study, we hypothesized that chemotherapy response is predictable by chemotherapy-related cell types and their differentially expressed genes (DEGs).MethodsDEGs of chemoresistance cell types were identified via single cell analysis and Wilcoxon test. A chemotherapy response signature was established using a random forest model and validated with public datasets. Bulk cell fraction was analyzed using BayesPrism algorithms. Log-rank test was used to analyze survival of PDAC patients.ResultsWe found that natural killer (NK) cells, myeloid cells, and erythroid cells were highly infiltrated in chemo-resistant TME. A total of 36 chemoresistance-related DEGs of chemo-resistant cells were identified in chemo-resistant PDAC. Functional enrichment analysis showed that chemoresistance upregulated various inflammation-related pathways, including TGF-β signaling. Based on these features, we constructed a random forest model to predict the response and survival for PDAC patients, which accurately distinguished high-risk and chemoresistant patients with significantly poorer prognosis in both the training and independent validation datasets. Cox regression analysis indicated that predicted labels were an independent prognostic factor in PDAC. Moreover, deconvolution of TME confirmed higher infiltration levels of M2 macrophage and NK cells in predicted chemoresistance. When combined with chemotherapy response related tumor mutations, the model showed excellent ability in predicting chemotherapy response and survival.ConclusionsThe TME was closely associated with the chemotherapy response and prognosis of PDAC. Our TME-based random forest model predicted chemotherapy response with complementary knowledge to the response-related genetic mutations.

Project description:Cancer-associated fibroblasts (CAFs) are orchestrators of the pancreatic ductal adenocarcinoma (PDAC) microenvironment. Previously we described four CAF subtypes with specific molecular and functional features. Here, we have refined our CAF subtype signatures using RNAseq and immunostaining with the goal of defining bioinformatically the phenotypic stromal and tumor epithelial states associated with CAF diversity. We used primary CAF cultures grown from patient PDAC tumors, human data sets (in-house and public, including single-cell analyses), genetically engineered mouse PDAC tissues, and patient-derived xenografts (PDX) grown in mice. We found that CAF subtype RNAseq signatures correlated with immunostaining. Tumors rich in periostin-positive CAFs were significantly associated with shorter overall survival of patients. Periostin-positive CAFs were characterized by high proliferation and protein synthesis rates and low α-smooth muscle actin expression and were found in peri-/pre-tumoral areas. They were associated with highly cellular tumors and with macrophage infiltrates. Podoplanin-positive CAFs were associated with immune-related signatures and recruitment of dendritic cells. Importantly, we showed that the combination of periostin-positive CAFs and podoplanin-positive CAFs was associated with specific tumor microenvironment features in terms of stromal abundance and immune cell infiltrates. Podoplanin-positive CAFs identified an inflammatory CAF (iCAF)-like subset, whereas periostin-positive CAFs were not correlated with the published myofibroblastic CAF (myCAF)/iCAF classification. Taken together, these results suggest that a periostin-positive CAF is an early, activated CAF, associated with aggressive tumors, whereas a podoplanin-positive CAF is associated with an immune-related phenotype. These two subpopulations cooperate to define specific tumor microenvironment and patient prognosis and are of putative interest for future therapeutic stratification of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Dataset Information

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

Publications

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

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