Label-free DIA-NN enabled RIME (DIANNeR) reveals glucocorticoid receptor interaction networks in breast, bladder, and blood across normaluntransformed cells, cancer cell lines, and PDXs

Abstract

Understanding how transcription factors execute tissue-specific programmes requires defining their protein interaction networks in physiologically relevant contexts. However, profiling normal untransformed cells presents fundamental challenges due to intrinsically limited input material. To meet this challenge we integrated data-independent acquisition (DIA), ion mobility separation, and library-free analysis to achieve a 2-fold increase in detection without loss in enrichment. Applied to the glucocorticoid receptor (GR), a ubiquitously expressed nuclear receptor driving pleiotropic responses to standard-of-care anti-inflammatory therapeutics, DIANNeR (DIA-NN enabled RIME) resolves distinct, context-dependent networks across breast, ureter and blood in normal and transformed contexts. Key findings include: detection of a HOXA5-GR interaction in normal epithelium which was undetected in malignant models; an epithelial-restricted SMARCD3-GR interaction with prognostic relevance; and a FOXP3-BCL11B-GR network in primary CD4+ T cell populations undetected by data dependant acquisition (DDA). By defining normal GR tissue interactomes, DIANNeR provides the essential comparator for interpreting network rewiring that drives disease.