PitNET tissue deconvolution: tracing normal tissue residues and immune dynamics.

ABSTRACT:

Background

Bulk RNA sequencing (RNA-seq) has substantially advanced the understanding of pituitary neuroendocrine tumors (PitNETs). However, its limited ability to resolve cellular heterogeneity - particularly in samples containing residual non-tumor pituitary cells - remains a significant challenge.

Objective

We developed and validated a tissue deconvolution framework using a reference dataset derived from single-nucleus RNA sequencing (snRNA-seq) of normal pituitary tissue, aimed at estimating cellular composition in PitNETs from bulk RNA-seq data and characterizing the tumor microenvironment (TME).

Methods

Marker-based (CIBERSORT, MuSiC) and single-cell-based (CIBERSORTx, MuSiC) deconvolution approaches were benchmarked across simulated, pseudobulk, and bulk RNA-se

SUBMITTER: Dalle Nogare M 

PROVIDER: S-EPMC12695536 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature