Spatial Transcriptomic Analysis of Pituitary Corticotroph Tumors Unveils Intratumor Heterogeneity.

medRxiv

Unit on Hypothalamic and Pituitary Disorders, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA.

Published: August 2023

AI Article Synopsis

  • - This study uses spatial transcriptomic (ST) analysis to explore gene expression and the location of tumor cells within corticotroph pituitary neuroendocrine tumors (PitNETs) from preserved tissue samples.
  • - Findings indicate that gene expression profiles can effectively annotate tumor tissue in agreement with pathologist assessments, and these profiles correlate with key protein markers like reticulin and Ki-67.
  • - The research uncovers intratumor heterogeneity, revealing that different cell clusters within the same tumor may have varying functions and characteristics, which could lead to new therapeutic possibilities.

Article Abstract

Spatial transcriptomic (ST) analysis of tumors provides a novel approach on studying gene expression along with the localization of tumor cells in their environment to uncover spatial interactions. Herein, we present ST analysis of corticotroph pituitary neuroendocrine tumors (PitNETs) from formalin-fixed, paraffin-embedded (FFPE) tissues. We report that the in situ annotation of tumor tissue can be inferred from the gene expression profiles and is in concordance with the annotation made by a pathologist. Furthermore, relative gene expression in the tumor corresponds to common protein staining used in the evaluation of PitNETs, such as reticulin and Ki-67 index. Finally, we identify intratumor heterogeneity; clusters within the same tumor may present with different secretory capacity and transcriptomic profiles, unveiling potential intratumor cell variability with possible therapeutic interest. Together, our results provide the first attempt to clarify the spatial cell profile in PitNETs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10473795PMC
http://dx.doi.org/10.1101/2023.08.04.23293576DOI Listing

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