Transcriptomics

Dataset Information

0

Deep sequencing and automated histochemistry of human tissue slice cultures improve their usability as preclinical model for cancer research


ABSTRACT: Cancer research requires models closely resembling the tumor in the patient. Human tissue cultures can overcome interspecies limitations of animal models or the loss of tissue architecture in in vitro models. However, analysis of tissue slices is often limited to histology. Here, we demonstrate that slices are also suitable for whole transcriptome sequencing and present a method for automated histochemistry of whole slices. Tumor and peritumoral tissue from a patient with glioblastoma was processed to slice cultures, which were treated with standard therapy including temozolomide and X-irradiation. Then, RNA sequencing and automated histochemistry was performed. RNA sequencing was successfully performed with a sequencing depth of 243 to 368 x 106 reads per sample. Comparing tumor and peritumoral tissue, we identified 1888 genes significantly downregulated and 2382 genes upregulated in tumor. Treatment significantly downregulated 2017 genes, whereas 1399 genes were upregulated. Pathway analysis revealed changes in the expression profile of treated glioblastoma tissue pointing towards downregulated proliferation. This was confirmed by automated analysis of whole tissue slices stained for Ki67. In conclusion, we demonstrate that RNA sequencing of tissue slices is possible and that histochemical analysis of whole tissue slices can be automated which increases the usability of this preclinical model.

ORGANISM(S): Homo sapiens

PROVIDER: GSE119102 | GEO | 2020/02/04

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2022-02-09 | GSE179649 | GEO
2015-05-13 | E-GEOD-37985 | biostudies-arrayexpress
2017-06-29 | E-MTAB-3258 | biostudies-arrayexpress
2015-05-13 | GSE37985 | GEO
2017-03-08 | E-MTAB-3239 | biostudies-arrayexpress
2016-03-10 | ST000367 | MetabolomicsWorkbench
2019-01-03 | GSE124552 | GEO
| PRJNA488101 | ENA
2020-06-16 | GSE151414 | GEO
2014-09-26 | E-GEOD-61710 | biostudies-arrayexpress