Glutamine‑Driven Nucleotide Synthesis Fuels Reversible H3K27ac Changes that Confer Adaptive Resistance to EGFR Inhibitors in Lung Adenocarcinoma

Background

Multi‑omics integration has revealed metabolic subtypes linked to prognosis and therapy response in cancers such as gastric carcinoma [2]. Proteomic and metabolomic layers expose functional states invisible to genomics, while AI‑driven fusion models achieve AUCs of 0.81–0.87 for early detection and therapy prediction [4]. Spatial technologies now co‑register transcriptomics, proteomics, and metabolomics within tumor microenvironments of glioma and colorectal cancer [5][6]. Despite these advances, a mechanistic link between dynamic metabolic rewiring and reversible epigenetic modifications that underlie therapy resistance remains poorly understood [7].

Hypothesis

We hypothesize that in EGFR‑mutant lung adenocarcinoma, increased glutamine uptake fuels de novo nucleotide biosynthesis, elevating intracellular acetyl‑CoA pools that drive histone H3 lysine 27 acetylation (H3K27ac) at enhancers of drug‑tolerant persister (DTP) programs. This epigenetic state is reversible upon glutamine withdrawal or glutaminase inhibition, sensitizing cells to EGFR tyrosine‑kinase inhibitors (TKIs).

Testable Predictions

1. EGFR‑TKI‑treated lung adenocarcinoma cells that survive treatment will show a significant increase in glutamine‑derived carbons incorporated into nucleotides, measurable by ^13C‑glutamine tracing and LC‑MS metabolomics [3].
2. The same surviving cells will display heightened H3K27ac at enhancer regions of DTP‑associated genes (e.g., AXL, IGF1R) detectable by spatial CUT&Tag coupled to imaging mass cytometry [5][6].
3. Pharmacologic inhibition of glutaminase (CB‑839) or genetic knockdown of GLS will reduce acetyl‑CoA levels, decrease H3K27ac at those enhancers, and restore sensitivity to EGFR‑TKIs in vitro and patient‑derived xenografts.
4. Longitudinal spatial multi‑omics sampling from patients receiving EGFR‑TKI therapy will reveal a temporal rise in glutamine‑nitrogen enrichment in tumor regions preceding clinical resistance, which regresses after adding a glutaminase inhibitor.

Experimental Design

• Establish EGFR‑mutant NSCLC cell lines (PC9, HCC827) and treat with osimertinib to isolate persister populations.
• Perform ^13C‑glutamine tracing followed by targeted metabolomics to quantify nucleotide labeling.
• Conduct spatial CUT&Tag for H3K27ac and multiplexed ion beam imaging (MIBI) to map acetylation alongside glutaminase expression.
• Use CRISPRi to knockdown GLS and assess changes in acetyl‑CoA (enzymatic assay), H3K27ac (Western blot), and cell viability under EGFR‑TKI.
• In PDX models, administer osimertinib ± CB‑839 and collect serial biopsies for spatial multi‑omics (transcriptomics, proteomics, metabolomics) to track metabolic‑epigenetic dynamics.
• Corrogate imaging mass cytometry data with clinical outcomes (progression‑free survival) in a prospective cohort of 30 patients.

Potential Impact

If validated, this hypothesis would connect glutamine metabolism to a reversible epigenetic mechanism of resistance, providing a biomarker‑driven rationale for combining glutaminase inhibitors with EGFR‑TKIs. It would also demonstrate how longitudinal spatial multi‑omics can capture the metabolic‑epigenetic axis in real time, informing adaptive treatment strategies.

References

• Multi‑omics integration reveals metabolic subtypes in gastric cancer [2]
• Proteomics and metabolomics provide functional readouts of cancer cell state [3]
• AI‑driven multi‑omics fusion achieves AUCs 0.81–0.87 for early detection [4]
• Spatial co‑registration of transcriptomics, proteomics, metabolomics in glioma and colorectal cancer [5][6]
• Gaps in understanding therapy resistance driven by metabolic reprogramming and post‑genomic mechanisms [7]