-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
-
Cosmetic Ingredient
- Water Treatment Chemical
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
Pancreatic intraepithelial neoplasia (PanIN) is a pre-malignancy of pancreatic ductal adenocarcinoma (PDAC) diagnosed from formalin-fixed and paraffin-embedded (FFPE) specimens, limiting single-cell-based studies
.
On July 16, 2022, a preprint article entitled "Spatial transcriptomics of FFPE pancreatic intraepithelial neoplasias reveals cellular and molecular alterations of progression to pancreatic ductal carcinoma" was published on bioRxiv by combining single-cell transcriptome data with 10x Visium FFPE spatial transcriptome data were combined to develop a new protocol for spatial transcriptome analysis of FFPE samples, supplemented by two new transfer learning methods
.
The first is to assign cell types to ST sites and integrate transcriptional signatures, showing that PanINs are surrounded by subtypes of PDAC cancer-associated fibroblasts (CAFs), including rare antigen-presenting CAFs
.
The second, integrating ST PanIN data with PDAC scRNA-seq data, identified a shift between inflammatory and proliferative signals as PanINs progressed to PDAC
.
This study is the first to identify similar CAF populations and associated molecular changes in PanINs that may be early mediators of precancerous transformation to PDAC
.
This integrated experimental and computational approach provides the means to develop models of PDAC development and progression by integrating imaging, ST, and scRNA-seq datasets
.
.
On July 16, 2022, a preprint article entitled "Spatial transcriptomics of FFPE pancreatic intraepithelial neoplasias reveals cellular and molecular alterations of progression to pancreatic ductal carcinoma" was published on bioRxiv by combining single-cell transcriptome data with 10x Visium FFPE spatial transcriptome data were combined to develop a new protocol for spatial transcriptome analysis of FFPE samples, supplemented by two new transfer learning methods
.
The first is to assign cell types to ST sites and integrate transcriptional signatures, showing that PanINs are surrounded by subtypes of PDAC cancer-associated fibroblasts (CAFs), including rare antigen-presenting CAFs
.
The second, integrating ST PanIN data with PDAC scRNA-seq data, identified a shift between inflammatory and proliferative signals as PanINs progressed to PDAC
.
This study is the first to identify similar CAF populations and associated molecular changes in PanINs that may be early mediators of precancerous transformation to PDAC
.
This integrated experimental and computational approach provides the means to develop models of PDAC development and progression by integrating imaging, ST, and scRNA-seq datasets
.
The researchers in the preprint above mentioned that due to the cell viability requirements of the scRNA-seq method, the technique is currently not compatible with FFPE samples, preventing them from directly performing PanINs analysis
.
Here, I would like to share a piece of good news with you, FFPE samples can also be used as single cells! 10x Genomics recently launched a solution for single-cell transcriptome sequencing of FFPE samples.
Let's take a look at the preliminary data of the 10x test
.
A piece of invasive ductal carcinoma tissue was dissected and isolated by a combination of manual dissociation and enzymatic digestion, and then single-cell transcriptome sequencing was performed after sample fixation using 10x's single-cell fixed RNA analysis kit launched this year.
Processing the data yielded a variety of cell types, and we can see from the graph that many immune cells can be detected from this FFPE sample
.
Breast cancer is a highly heterogeneous disease.
In order to guide prognosis, TNM staging and clinicopathological indicators are often used.
Later, due to the generation of high-throughput data, polygenic prediction has become a new approach
.
Traditional methods that typically classify cancers based on their signatures based on bulk levels, now apply the signatures to each cell population in this dataset and associate each population with a PAM50 gene signature, showing that there is actually only one cell population17 associated with cancer.
Subtypes showed strong correlations, while other cell populations were associated with normal features
.
Such analyses have been performed on fresh samples before, but finding this on data from FFPE samples could allow researchers to apply it to a large number of biobank FFPE samples, unlocking more archived samples
.
The FFPE method is a standard method for the collection and preservation of surgical pathology specimens that are used by pathologists to determine the visual characteristics of disease on FFPE sections, often these samples can be linked to valuable metadata such as patient information records, medications used , and even clinical outcomes
.
The ability to observe transcriptome gene expression at single-cell resolution on these longitudinal samples will add a whole new axis of information to study disease progression, and it is believed that the launch of this single-cell solution for FFPE samples at 10x can unlock more clinical archives Samples, bring more new research discoveries! For more details, please contact us! Tel: 010-84409661, Email: marketing@emtd.
com.
cn
.
Reference article:
https://doi.
org/10.
1101/2022.
07.
16.
500312
