As the most common type of pancreatic cancer (PC), pancreatic ductal adenocarcinoma (PDAC) is characterized by high intra-tumoral heterogeneity and complexity. Recently, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to reveal complex heterogeneity in the PDAC microenvironment with unprecedented resolution. Alfa Oncology is a leading provider of pancreatic cancer (PC) research services. Here, we use scRNA-seq-based analysis to quantify cell types and states in PDAC tumors, facilitating the understanding of PDAC heterogeneity and complexity. We specialize in PC genetic/molecular research and are committed to providing reliable and flexible services for PC basic research and precision medicine.
Overview of PDAC scRNA-Seq
The development of next-generation sequencing (NGS) technology makes it possible to perform deep RNA sequencing (RNA-seq) at the single-cell level. With scRNA-seq, researchers can explore the whole transcriptome of individual cells in a tumor and determine their status with extremely high resolution. scRNA-seq studies of cancers have revealed new insights into tumor heterogeneity and different subpopulations, which are key to a detailed dissection of tumor-related mechanisms.
PDAC is characterized by high intra-tumoral heterogeneity and complexity, including not only tumor cells, but also the microenvironment in which tumor cells are constantly interacting with each other. Specifically, PDAC has a complex immune microenvironment consisting of multiple inflammatory cells, such as T cells, B cells, and macrophages. These cells are closely associated with tumorigenesis and development. In addition, a dense stroma composed mainly of proliferating cancer-associated fibroblasts (CAFs) and abundant extracellular matrixes are present in PDAC. scRNA-seq can be applied to investigate and identify diverse malignant and stromal cell types, contributing to an in-depth characterization of PDAC intra-tumor heterogeneity, the underlying mechanisms of PDAC progression, and more.
Fig. 1 The t-distributed stochastic neighbor embedding (t-SNE) plot demonstrates main cell types in PDAC. (Peng, Junya, et al., 2019)
The service offering at Alfa Oncology
Based on advanced platforms, we are proud to offer scRNA-Seq-based profiling services to help global customers to investigate cell heterogeneity in PC. Our service is highly flexible and customized. In general, our service includes a series of steps, including sample preparation, cell capture and cDNA synthesis, scRNA-seq library preparation, scRNA-seq, and bioinformatics analysis.
Workflow of Our Services
- scRNA-Seq data processing and quality control
- Cell type identification
- Gene set enrichment analysis
- Customized analysis
Our service can help researchers achieve
- Revealing heterogeneous cell composition in PDAC tissues
- Mapping of comprehensive gene expression profiles in PDAC and analysis of gene expression profile characteristics of each cell type, such as epithelial tumor cells, CAFs, immune cells, and cancer stem cells (CSCs)
- Detecting the interactions between PDAC cells and stromal microenvironment
- Characterizing the dynamics of tumor microenvironment components during PDAC progression
To date, scRNA-seq has been widely employed in the study of the pancreas and in PC. As a CRO company, Alfa Oncology is comprised of scientists, bioinformaticians, oncologists, and so on. Our team works closely and communicates actively to achieve our common goals of helping researchers and professionals understand PC biology, explore new PC therapeutics and protocols, and develop new PC biomarkers. Thank you for choosing our services. If you have any related questions, please contact us. We will answer and serve you immediately.
- Lin, Wei, et al. "Single-cell transcriptome analysis of tumor and stromal compartments of pancreatic ductal adenocarcinoma primary tumors and metastatic lesions." Genome medicine 12.1 (2020): 1-14.
- Peng, Junya, et al. "Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma." Cell research 29.9 (2019): 725-738.