Richard Li
Richard Li
Richard Li
Helios Scholar
School: Arizona State University
Hometown: Gilbert, Arizona
Mentor: Kevin Gosselin, Ph.D.


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Single cell RNA sequencing of pancreatic tumors

Pancreatic ductal adenocarcinoma (PDAC) is slated to be the third leading cause of cancer-related deaths in the United States this year. PDAC is characterized by a tumor microenvironment that is highly desmoplastic and plays a role in slowing conventional chemotherapy delivery. Single cell RNA sequencing (scRNA-seq) is a promising platform by which solid tumors can be dissociated into single cells and analyzed for their whole transcriptomes at single cell level. In scRNA-seq, RNA is captured and barcoded for each individual cell and the abundance of each gene transcript is determined by sequencing reads. Through scRNA-seq, cell populations within a tumor can be quantitatively determined and transcriptionally characterized. In this study, the 10x Chromium Single Cell Sequencing Controller was used for whole cell transcript labeling and library construction and sequencing. To convert raw sequencing reads data into transcript abundance data, the Cell Ranger program (10x Genomics) was used. The program Loupe (10X Genomics) was then employed to visualize the data into clusters. Cell types were then identified and signature genes for each cell type were obtained. These signature genes yielded powerful implications on unexplored functions of certain cell types. From a clinical standpoint, some of the genes identified showed strong implications of sensitivity to specific treatment options. Gene set enrichment analysis suggests pathways that are highly activated in individual cell types. Those pathways are potential driving factors of cancer progression and can be explored for therapeutic targeting. ScRNA-seq could also potentially be employed in analyzing core biopsies for treatment planning.  Future studies would focus on the analysis of more tumor samples from patients with PDAC for within and between sample comparisons to determine inter-tumor heterogeneity and the subsequent validation of the scRNA-Seq results.

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