TP53 mutation adoption of stromal-adhesion/neuronal-like programs as a driver of stress adaptation and acute myelogenous leukemia cell survival.

A Alexandra Thalberg (4University of Minnesota School of Medicine, Minneapolis, United States) J Jonathan Dan Andreadakis (Tampa General Hospital Cancer Institute, Tampa, FL) A Alexander Shkembi (2University of South Florida, College of Public Health, Tampa, United States) I Ivan Borrello (1Tampa General Hospital Cancer Institute, Tampa, United States) E Eduardo M. Sotomayor (Tampa General Hospital Cancer Institute, Tampa, FL) M Maher Albitar (1Genomic Testing Cooperative, Lake Forest, United States) L Lacey Williams (University of North Carolina, Chapel Hill, North Carolina, United States) D David Michael Swoboda (Tampa General Hospital Cancer Institute, Tampa, FL) G Gustavo Rivero (3Tampa General Hospital Cancer Institute, Tampa, United States)

Abstract

6545 Background: TP53 -mutated AML is associated with early relapse and poor survival, highlighting the need to define p53-driven transcriptional programs that may reveal targetable therapeutic vulnerabilities. Systematic deconvolution of the TP53-associated transcriptome provides a critical framework to uncover dependencies associated with drug resistance. Methods: After IRB approval, 311 AML patients were screened; 93 (30%) with available NGS were included (32 TP53-mutated, 61 TP53-wild type). Bulk transcriptome data were available for 11 TP53+ and 13 TP53-WT cases. Overall survival was analyzed using Kaplan–Meier and multivariable Cox regression. Transcriptional modules predictive of TP53+ AML were identified using Random Forest and pathway enrichment via KEGG/Reactome with confirmation by ToppGene. Public single-cell RNA-seq datasets from the MIT Single Cell Portal were queried to assess whether low TP53 expression states recapitulate bulk TP53-mutated transcriptional programs. Results: OS was 168 and 624 days (d) in TP53+ and TP53 WT cases (HR = 4.2, p = 0.02). Only CK retained independent effect for OS (HR = 0.33, 95% CI = 0.13–0.82, p = 0.014) when accounting for TP53 mut status and age. TP53 mut status imprinted a deep transcriptomic signature (AUC = 0.94). Top upregulated genes included FHL2 (p = 4.0×10−6, FDR = 0.004), HMGA2 (p = 1.4×10−3, FDR = 0.02), ARHGEF12 (p = 5.2×10−3, FDR = 0.04), RYR3 (p = 2.1×10−3, FDR = 0.03), LRRC7 (p = 7.7×10−3, FDR = 0.05), ALDH1A1 (p = 1.4×10−3, FDR = 0.02). Top downregulated genes included CSF1 (p = 4.7×10−4, FDR = 0.007), CD34 (p = 1.2×10−3, FDR = 0.01). To uncover pathway-level shifts co-opted by TP53+ AML, we contrasted pathway-level projection against TP53 WT cases. Upregulated pathways included adhesion / stromal dependence (p = 0.0004; FDR = 0.0028), neurotrophin / calcium signaling / Ca2+-coupled survival (p = 0.0006, FDR = 0.0021). However, downregulated pathways included cytokine-cytokine receptor interaction (p = 4.7×10−4, FDR = 0.007) and myeloid differentiation (p = 1.2×10−3, FDR = 0.01) [Fig. 2]. Interestingly, in lineage-resolved single-cell reference, low TP53 GE was visually colocalized with perivascular/stromal cells exhibiting high FHL2 and THY1 (CD90) expression. This data reconfirms prior data suggesting that reduced TP53 function favors niche-adapted perivascular/MSC-like reprogramming (THY1-high) that protects “resistant AML clones” (Mizuno et al., ASH 2024). Conclusions: These findings unveil that TP53+ AML co-opts leukemic blasts toward a stromal-adhesive and neuronal-like state, allowing survival under metabolic and therapeutic stress. Reversing stromal adhesive / neuronal-like rewiring may attenuate TP53 + blasts hijacking on vascular niche that maintains relapse potential.

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
Pages 6545-6545
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (9)

A

Alexandra Thalberg

4University of Minnesota School of Medicine, Minneapolis, United States

J

Jonathan Dan Andreadakis

Tampa General Hospital Cancer Institute, Tampa, FL

A

Alexander Shkembi

2University of South Florida, College of Public Health, Tampa, United States

I

Ivan Borrello

1Tampa General Hospital Cancer Institute, Tampa, United States

E

Eduardo M. Sotomayor

Tampa General Hospital Cancer Institute, Tampa, FL

M

Maher Albitar

1Genomic Testing Cooperative, Lake Forest, United States

L

Lacey Williams

University of North Carolina, Chapel Hill, North Carolina, United States

D

David Michael Swoboda

Tampa General Hospital Cancer Institute, Tampa, FL

G

Gustavo Rivero

3Tampa General Hospital Cancer Institute, Tampa, United States