Transcriptomics

Dataset Information

0

Gene expression data from precision cut tumor slices from head and neck or mesothelioma tumors


ABSTRACT: As cancer immunotherapy and precision medicine dynamically evolve, there is greater need for pre-clinical models that can better replicate the intact tumor and its complex tumor microenvironment (TME). Precision-cut tumor slices (PCTS) have recently emerged as an ex vivo human tumor model, offering the opportunity to study individual patient responses to targeted therapies, including immunotherapies. However, little is known about the physiologic status of PCTS and how they can be utilized in view of the intra-tumoral heterogeneity. In this study, we generated PCTS from head and neck cancers (HNC) and mesotheliomas (Meso) and studied their viability in culture, the extent of variability in serial PCTS, and whether tumor immune response can be measured following PCTS T cell activation. We also undertook transcriptomic analyses to understand the changes that occur in the timeframe between PCTS generation and up to 72hr in culture. Our findings suggest that PCTS viability can be tumor-specific and culture conditions-dependent, but an overall viability of up to 72 hrs was observed. Tumor heterogeneity is present and can skew findings if appropriate experimental design and multiple control PCTS are not considered. Activation of endogenous T cells and measurement of immune responses is possible, however, our transcriptomic analyses showed major changes occurring during the first 24hr culture period of PCTS, involving genes related to wound healing, extracellular matrix, hypoxia, and IFNγ-dependent pathways. Our data suggest the PCTS model may be especially useful for studies involving exogenous immune therapies, such as adoptive cell therapy, rather than for the study of the effects of therapy on endogenous immune systems.

ORGANISM(S): Homo sapiens

PROVIDER: GSE250038 | GEO | 2024/05/22

REPOSITORIES: GEO

Dataset's files

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

Similar Datasets

2023-03-10 | PXD030571 | Pride
2022-01-21 | GSE194095 | GEO
2022-06-28 | GSE206828 | GEO
2013-09-06 | GSE47581 | GEO
2013-09-06 | E-GEOD-47581 | biostudies-arrayexpress
2014-10-01 | E-GEOD-58600 | biostudies-arrayexpress
| PRJNA392769 | ENA
| PRJNA392770 | ENA
2024-01-20 | E-MTAB-13677 | biostudies-arrayexpress
| PRJNA666613 | ENA