TGen and HonorHealth investigators suggest this granular analysis could lead to better treatments for pancreatic cancer patients
Led by the Translational Genomics Research Institute (TGen), an affiliate of City of Hope, and by HonorHealth Research and Innovation Institute, an international team of researchers have described in detail the individual cells that comprise the pancreatic cancer microenvironment, a critical step in devising new treatment options for patients with this aggressive and difficult-to-treat disease.
Researchers used a relatively new technique known as single-cell sequencing to genetically identify cell types, and subtypes, that occur in pancreatic tumors, and identify the various cells in the tumor’s stroma, a substance surrounding the tumor that can hide the cancer from the body’s immune system.
While single-cell transcriptomics has been used previously to study the cellular composition of primary tumor tissues of pancreatic ductal adenocarcinoma (PDAC), this study also used the technology to profile individual cells from dissociated primary tumors and biopsies of metastatic tissues, those cancerous lesions that have spread throughout the body from the primary tumor.
This study was carried out in collaboration with investigators from Samsung Medical Center and City of Hope, a world-renowned independent research and treatment center for cancer, diabetes and other life-threatening diseases. Primary tumors and core needle biopsies of metastatic lesions from PDAC patients were sequenced using the Chromium single cell RNA-Seq platform.
“Single-cell transcriptome analysis can offer important clinical insights on individual cell subpopulations and provide clues for developing novel therapeutic strategies for both targeted therapies and immunotherapies,” said Haiyong Han, Ph.D., a professor in TGen’s Molecular Medicine Division and head of the institute’s Pancreatic Cancer Research Laboratory.
“Understanding the diversity and complexity of the PDAC tumor and stromal compartments in individual tumors may help identify unique intervention points and potentially inform treatment and maintenance strategies for patients with advanced disease,” said Dr. Han, the study’s senior author.
Distinct cell types and subtypes were identified in the analysis, including tumor cells, endothelial cells, cancer associated fibroblasts, and immune cells, and the expression levels of various genes in the individual cell populations correlated with patient clinical outcomes.
“Working with our partners and colleagues by utilizing the technology of singe cell sequencing, we can continue to learn more about the biology of pancreas cancer. These insights may potentially help us determine more treatment options for our patients,” said Erkut Borazanci, M.D., M.S., a medical oncologist and physician-investigator at HonorHealth Research and Innovation Institute, a clinical associate professor at TGen, and one of the paper’s authors.
Pancreatic cancer is an aggressive disease that carries a high mortality rate. It is the third-leading cause of cancer death in the U.S., following lung and colorectal cancers. In 2020, the five-year survival rate for pancreatic cancer is only about 10%, though that represents progress from the dismal 6% rate in 2014.
Next, researchers plan to use more advanced single-cell spatial transcriptomics analysis to further investigate the cellular relationships related to survival rates using real-time methods. Broader use of this technology could potentially guide the search for new agents to treat pancreatic cancer.
Source – Translational Genomics Research Institute
Lin W, Noel P, Borazanci EH et al. (2020) Single-cell transcriptome analysis of tumor and stromal compartments of pancreatic ductal adenocarcinoma primary tumors and metastatic lesions. Genome Med 12, 80. [article]
TGen and HonorHealth investigators suggest this granular analysis could lead to better treatments for pancreatic cancer patients
Led by the Translational Genomics Research Institute (TGen), an affiliate of City of Hope, and by HonorHealth Research and Innovation Institute, an international team of researchers have described in detail the individual cells that comprise the pancreatic cancer microenvironment, a critical step in devising new treatment options for patients with this aggressive and difficult-to-treat disease.
Researchers used a relatively new technique known as single-cell sequencing to genetically identify cell types, and subtypes, that occur in pancreatic tumors, and identify the various cells in the tumor’s stroma, a substance surrounding the tumor that can hide the cancer from the body’s immune system.
While single-cell transcriptomics has been used previously to study the cellular composition of primary tumor tissues of pancreatic ductal adenocarcinoma (PDAC), this study also used the technology to profile individual cells from dissociated primary tumors and biopsies of metastatic tissues, those cancerous lesions that have spread throughout the body from the primary tumor.
This study was carried out in collaboration with investigators from Samsung Medical Center and City of Hope, a world-renowned independent research and treatment center for cancer, diabetes and other life-threatening diseases. Primary tumors and core needle biopsies of metastatic lesions from PDAC patients were sequenced using the Chromium single cell RNA-Seq platform.
Distinct cell types and subtypes were identified in the analysis, including tumor cells, endothelial cells, cancer associated fibroblasts, and immune cells, and the expression levels of various genes in the individual cell populations correlated with patient clinical outcomes.
Pancreatic cancer is an aggressive disease that carries a high mortality rate. It is the third-leading cause of cancer death in the U.S., following lung and colorectal cancers. In 2020, the five-year survival rate for pancreatic cancer is only about 10%, though that represents progress from the dismal 6% rate in 2014.
Next, researchers plan to use more advanced single-cell spatial transcriptomics analysis to further investigate the cellular relationships related to survival rates using real-time methods. Broader use of this technology could potentially guide the search for new agents to treat pancreatic cancer.
Source – Translational Genomics Research Institute
Lin W, Noel P, Borazanci EH et al. (2020) Single-cell transcriptome analysis of tumor and stromal compartments of pancreatic ductal adenocarcinoma primary tumors and metastatic lesions. Genome Med 12, 80. [article]
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TGen and HonorHealth investigators suggest this granular analysis could lead to better treatments for pancreatic cancer patients
Led by the Translational Genomics Research Institute (TGen), an affiliate of City of Hope, and by HonorHealth Research and Innovation Institute, an international team of researchers have described in detail the individual cells that comprise the pancreatic cancer microenvironment, a critical step in devising new treatment options for patients with this aggressive and difficult-to-treat disease.
Researchers used a relatively new technique known as single-cell sequencing to genetically identify cell types, and subtypes, that occur in pancreatic tumors, and identify the various cells in the tumor’s stroma, a substance surrounding the tumor that can hide the cancer from the body’s immune system.
While single-cell transcriptomics has been used previously to study the cellular composition of primary tumor tissues of pancreatic ductal adenocarcinoma (PDAC), this study also used the technology to profile individual cells from dissociated primary tumors and biopsies of metastatic tissues, those cancerous lesions that have spread throughout the body from the primary tumor.
This study was carried out in collaboration with investigators from Samsung Medical Center and City of Hope, a world-renowned independent research and treatment center for cancer, diabetes and other life-threatening diseases. Primary tumors and core needle biopsies of metastatic lesions from PDAC patients were sequenced using the Chromium single cell RNA-Seq platform.
Distinct cell types and subtypes were identified in the analysis, including tumor cells, endothelial cells, cancer associated fibroblasts, and immune cells, and the expression levels of various genes in the individual cell populations correlated with patient clinical outcomes.
Pancreatic cancer is an aggressive disease that carries a high mortality rate. It is the third-leading cause of cancer death in the U.S., following lung and colorectal cancers. In 2020, the five-year survival rate for pancreatic cancer is only about 10%, though that represents progress from the dismal 6% rate in 2014.
Next, researchers plan to use more advanced single-cell spatial transcriptomics analysis to further investigate the cellular relationships related to survival rates using real-time methods. Broader use of this technology could potentially guide the search for new agents to treat pancreatic cancer.
Source – Translational Genomics Research Institute
Lin W, Noel P, Borazanci EH et al. (2020) Single-cell transcriptome analysis of tumor and stromal compartments of pancreatic ductal adenocarcinoma primary tumors and metastatic lesions. Genome Med 12, 80. [article]
Related Posts
Benchmarking RNA sequencing for more accurate alternative splicing analysis
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Small RNA sequencing reveals regulatory roles for sdRNAs in acute myeloid leukemia
POND-seq enables non-destructive RNA sequencing in living cells
Worm’s radical transformation shows metamorphosis can change the functions of cells
New method allows scientists to follow gene activity over time in the same cells
Single-cell and single-embryo RNA sequencing
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Deep learning improves microRNA target prediction from sequence
Atlas of the brain’s striatum could guide researchers to new drug treatments
scLS – a computationally efficient differentially expressed gene detection algorithm
Spatial mapping of RNA turnover kinetics in the mouse brain
Immune cells offer insights on billion-dollar virus
SPIDER improves spatial transcriptomics data using single-cell RNA sequencing
Ultrafast and reference-free sequence discovery in single-cell data
ARCADIA combines RNA sequencing and spatial proteomics to reveal how tissue location shapes cell behavior
An end-to-end computational framework for “Record-seq” transcriptional recording data
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
ExoShorkie – predicting RNA-seq coverage of exogenous genomes in yeast by transfer learning
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
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