Single-Cell RNA-Seq Reveals Dynamic Change in Tumor Microenvironment During Pancreatic Ductal Adenocarcinoma Malignant Progression

2020 ◽  
Author(s):  
Kai Chen ◽  
Qi Wang ◽  
Mingzhe Li ◽  
Huahu Guo ◽  
Weikang Liu ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Dynamic Change ◽  
Malignant Progression ◽  
Ductal Adenocarcinoma ◽  
Rna Seq

scholarly journals Author Correction: Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma

Cell Research ◽  
2019 ◽  
Vol 29 (9) ◽  
pp. 777-777
Author(s):  
Junya Peng ◽  
Bao-Fa Sun ◽  
Chuan-Yuan Chen ◽  
Jia-Yi Zhou ◽  
Yu-Sheng Chen ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Malignant Progression ◽  
Ductal Adenocarcinoma ◽  
Rna Seq

scholarly journals Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma

Cell Research ◽  
2019 ◽  
Vol 29 (9) ◽  
pp. 725-738 ◽  
Author(s):  
Junya Peng ◽  
Bao-Fa Sun ◽  
Chuan-Yuan Chen ◽  
Jia-Yi Zhou ◽  
Yu-Sheng Chen ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Malignant Progression ◽  
Ductal Adenocarcinoma ◽  
Rna Seq

scholarly journals Deciphering the Prognostic Implications of the Components and Signatures in the Immune Microenvironment of Pancreatic Ductal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Rong Tang ◽  
Xiaomeng Liu ◽  
Chen Liang ◽  
Jie Hua ◽  
Jin Xu ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cd8 T Cells ◽  
Nkt Cells ◽  
Ductal Adenocarcinoma ◽  
Hematopoietic Stem ◽  
Single Cell Sequencing ◽  
Prognostic Implications

Background: The treatment modalities for pancreatic ductal adenocarcinoma (PDAC) are limited and unsatisfactory. Although many novel drugs targeting the tumor microenvironment, such as immune checkpoint inhibitors, have shown promising efficacy for some tumors, few of them significantly prolong the survival of patients with PDAC due to insufficient knowledge on the tumor microenvironment.Methods: A single-cell RNA sequencing (scRNA-seq) dataset and seven PDAC cohorts with complete clinical and bulk sequencing data were collected for bioinformatics analysis. The relative proportions of each cell type were estimated using the gene set variation analysis (GSVA) algorithm based on the signatures identified by scRNA-seq or previous literature.Results: A meta-analysis of 883 PDAC patients showed that neutrophils are associated with worse overall survival (OS) for PDAC, while CD8+ T cells, CD4+ T cells, and B cells are related to prolonged OS for PDAC, with marginal statistical significance. Seventeen cell categories were identified by clustering analysis based on single-cell sequencing. Among them, CD8+ T cells and NKT cells were universally exhausted by expressing exhaustion-associated molecular markers. Interestingly, signatures of CD8+ T cells and NKT cells predicted prolonged OS for PDAC only in the presence of “targets” for pyroptosis and ferroptosis induction. Moreover, a specific state of T cells with overexpression of ribosome-related proteins was associated with a good prognosis. In addition, the hematopoietic stem cell (HSC)-like signature predicted prolonged OS in PDAC. Weighted gene co-expression network analysis identified 5 hub genes whose downregulation may mediate the observed survival benefits of the HSC-like signature. Moreover, trajectory analysis revealed that myeloid cells evolutionarily consisted of 7 states, and antigen-presenting molecules and complement-associated genes were lost along the pseudotime flow. Consensus clustering based on the differentially expressed genes between two states harboring the longest pseudotime span identified two PDAC groups with prognostic differences, and more infiltrated immune cells and activated immune signatures may account for the survival benefits.Conclusion: This study systematically investigated the prognostic implications of the components of the PDAC tumor microenvironment by integrating single-cell sequencing and bulk sequencing, and future studies are expected to develop novel targeted agents for PDAC treatment.

Single-nucleus RNA-seq of frozen archival primary pancreatic ductal adenocarcinoma uncovers multi-compartment intratumoral heterogeneity associated with neoadjuvant treatment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 4633-4633
Author(s):  
William L. Hwang ◽  
Karthik Jagadeesh ◽  
Jimmy Guo ◽  
Hannah I. Hoffman ◽  
Orr Ashenberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Neoadjuvant Treatment ◽  
Intratumoral Heterogeneity ◽  
Ductal Adenocarcinoma ◽  
Type I ◽  
Malignant Cells ◽  
Rna Seq ◽  
Single Nucleus

4633 Background: Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease and existing molecular subtypes do not inform clinical decisions. Previously identified bulk transcriptomic subtypes of PDAC were often unintentionally driven by “contaminating” stroma. RNA extraction from pancreatic tissue is difficult and prior single-cell RNA-seq efforts have been limited by suboptimal dissociation/RNA quality and poor performance in the setting of neoadjuvant treatment. We developed a robust single-nucleus RNA-seq (sNuc-seq) technique compatible with frozen archival PDAC specimens. Methods: Single nuclei suspensions were extracted from frozen primary PDAC specimens (n = 27) derived from patients with (borderline)-resectable PDAC who underwent surgical resection with or without neoadjuvant chemoradiotherapy (CRT). Approximately 170,000 nuclei were processed with the 10x Genomics Single Cell 3’ v3 pipeline and gene expression libraries were sequenced (Illumina HiSeq X). Results: Distinct nuclei clusters with gene expression profiles/inferred copy number variation analysis consistent with neoplastic, acinar, ductal, fibroblast, endothelial, endocrine, lymphocyte, and myeloid populations were identified with proportions similar to corresponding multiplexed ion beam imaging. Non-negative matrix factorization revealed intra-tumoral heterogeneity shared across patients. Neoplastic cells featured eight distinct transcriptional topics characterized by developmental (epithelial, mesenchymal, endoderm progenitor, neural progenitor) and environmental (anabolic, catabolic, cycling, hypoxic) programs. CAFs exhibited four different transcriptional topics (activated/desmoplastic, myofibroblast, neurogenic, osteochondral). Differential gene expression and gene set enrichment analyses demonstrated that CRT was associated with an enrichment in myogenic programs in CAFs, activation pathways in immune cells, and type I/II interferons in malignant cells. CRT was also associated with a depletion in developmental programs within malignant cells. Conclusions: We uncovered significant intratumoral heterogeneity and treatment-associated differences in the malignant, fibroblast, and immune compartments of PDAC using sNuc-seq. Deconvolution of clinically-annotated bulk RNA-seq cohorts and characterization of intercellular interactions with receptor-ligand analysis and spatial transcriptomics are ongoing.

scholarly journals Autophagy Regulatory Genes MET and RIPK2 Play a Prognostic Role in Pancreatic Ductal Adenocarcinoma: A Bioinformatic Analysis Based on GEO and TCGA

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xingyu Li ◽  
Zhiqiang Li ◽  
Hongwei Zhu ◽  
Xiao Yu
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Differentially Expressed Genes ◽  
Clinical Application ◽  
Regulatory Genes ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Ductal Adenocarcinoma ◽  
Rna Seq

Pancreatic ductal adenocarcinoma is a common malignant tumor with a poor prognosis. Autophagy activity changes in both cancer cells and microenvironment and affects the progression of pancreatic ductal adenocarcinoma. The purpose of this study was to predict the prognostic autophagy regulatory genes and their role in the regulation of autophagy in pancreatic ductal adenocarcinoma. We draw conclusions based on gene expression data from different platforms: GSE62165 and GSE85916 from the array platform, TCGA from the bulk RNA-seq platform, and GSE111672 from the single-cell RNA-seq platform. At first, we detected differentially expressed genes in pancreatic ductal adenocarcinoma compared with normal pancreatic tissue based on GSE62165. Then, we screened prognostic genes based on GSE85916 and TCGA. Furthermore, we constructed a risk signature composed of the prognostic differentially expressed genes. Finally, we predicted the probable role of these genes in regulating autophagy and the types of cell expressing these genes. According to our screening criteria, there were only two genes: MET and RIPK2, selected into the development of the risk signature. However, evaluated by log-rank tests, receiver operating characteristic curves, and calibration curves, the risk signature was worth considering its clinical application because of good sensitivity, specificity, and stability. Besides, we predicted that both MET and RIPK2 promote autophagy in pancreatic ductal adenocarcinoma by gene set enrichment analysis. Analysis of single-cell RNA-seq data from GSE111672 revealed that both MET and RIPK2 were expressed in cancer cells while RIPK2 was also expressed in monocytes and neutrophils. After comprehensive analysis, we found that both MET and RIPK2 are related to the prognosis of pancreatic ductal adenocarcinoma and provided some associated clues for clinical application and basic experiment research.

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