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291 Spatially Resolved Transcriptomics Unveils Unique T-Cell Dysfunctional States and Prognostic Gene Expression Signatures in TP53-Mutated Acute Myeloid Leukemia

Program: Oral and Poster Abstracts
Type: Oral
Session: 617. Acute Myeloid Leukemias: Biomarkers, Molecular Markers and Minimal Residual Disease in Diagnosis and Prognosis: Immunologic and Metabolic Biomarkers of Disease Control
Hematology Disease Topics & Pathways:
Acute Myeloid Malignancies, AML, Research, Biological therapies, immune mechanism, Diseases, Immunotherapy, Therapies, computational biology, Myeloid Malignancies, Biological Processes, Technology and Procedures, profiling
Saturday, December 9, 2023: 4:15 PM

Jayakumar Vadakekolathu, PhD1*, Heidi Altmann, PhD2*, Manja Wobus2*, Malte von Bonin, MD2*, Marc Schmitz, MD3,4*, Gustavo B. Baretton, MD5*, Robert Zeiser, MD6, Martin Bornhäuser, MD7,8* and Sergio Rutella, MD, PhD, FRCPath1

1John van Geest Cancer Research Centre, Nottingham Trent University, Nottingham, United Kingdom
2Department of Internal Medicine I, University Hospital, TU Dresden, Dresden, Germany
3Institute for Immunology, University Hospital, TU Dresden, Dresden, Germany
4National Center for Tumor Diseases (NCT/UCC) Dresden, TU Dresden, Dresden, Germany
5Institute for Pathology, University Hospital, TU Dresden, Dresden, Germany
6Department of Medicine I, Medical Center University of Freiburg, Freiburg, Germany
7Department of Internal Medicine 1, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany
8National Center for Tumor Diseases (NCT/UCC) Dresden, Technical University Dresden, Dresden, Germany


Somatic TP53 mutations and 17p deletions with genomic loss of TP53 occur in 8% to 10% of AML and correlate with primary induction failure, high risk of relapse, and dismal prognosis. We have previously shown that TP53 abnormalities are associated with a pro-inflammatory and immunosuppressive tumor microenvironment (TME), including high CD274 and FoxP3 expression, with dysfunctional natural killer (NK)/CD8+ T-cell states and with response to flotetuzumab, a CD123 × CD3 bispecific T-cell engager. In the current study, we explore the cellular neighborhoods of TP53-mutated (TP53-m) AML using spatially resolved transcriptomics and we employ machine learning to identify prognostic RNA signatures.


We analyzed the expression of >1,800 immune and TME genes in bone marrow (BM) formalin-fixed paraffin-embedded (FFPE) sections (5-µm) from a discovery cohort of 11 patients with chemotherapy-naïve AML (N=5 TP53-m and N=6 TP53-wt cases) using the GeoMx™ Digital Spatial Profiling (DSP) platform (Cancer Transcriptome Atlas with next generation sequencing read-out; NanoString Technologies, Seattle, WA). Imaging was performed at 20× magnification and a total of 151 circular regions of interest (ROIs) with a 300–600 µm diameter were selected (Fig. 1A). We then generated a ROI-by-gene count matrix for deconvolution and downstream pathway analysis. For each ROI, enrichment scores reflecting immune senescence/dysfunction and leukemia stemness were calculated with gene set variation analysis (GSVA), using a manually curated compendium of published gene signatures as input. We also employed public bulk and single-cell RNA-sequencing (sc-RNA-seq) AML cohorts for in silico modeling and validation.


We initially captured transcripts from ROIs of TP53-m and TP53-wt AML with varying degrees of BM infiltration with T cells (CD3 hotspots) and AML blasts, and we found that TP53-m is enriched in T cell-specific, type I/II interferon (IFN) and pro-inflammatory genes (IL1B), as well as leukemia stem cell (LSC)-related gene programs (LSC17). After dichotomizing ROIs based on a median split of CD3D RNA expression, we observed that T-celllow ROIs express higher levels of monocyte-macrophage and myeloid derived suppressor cell (MDSC)-related genes, including S100A9 and S100A8. These findings point to previously unappreciated links between BM infiltration with immune-modulatory myeloid cell types and leukemia stemness / T-cell abundance. We then tested for differential cell density in neighborhoods (regions of transcriptionally similar cells) across TP53-m and TP53-wt AML using MiloR in a sc-RNA-seq AML dataset annotated by cell type (N=42 cases, of which N=3 with TP53-m; Lasry A, et al. Nat. Cancer 2023). This orthogonal approach highlighted a significantly higher frequency (FDR <0.05) of multipotent and granulocyte-macrophage progenitor neighborhoods in TP53-m AML, alongside suppression of adaptive immune system pathways (Fig. 1B). We next inferred active receptor-ligand pairs mediating the crosstalk between T cells and leukemic blasts in the TME of TP53-m AML, and we uncovered decreased MHC class I/II-mediated signaling, curbed CD8+/CD4+ T cell-to-AML interactions and enhanced CD6/CDCP1(CD318) signaling (Fig. 1C). We also found that CD8+ and CD4+ T cells from TP53-m AML are enriched in effector memory (TEM) / terminally differentiated effector memory (TEMRA) and regulatory T-cell gene programs, respectively, compared with their cellular counterparts from TP53-wt patients (Fig. 1D). In particular, TEM cells from TP53-m AML expressed genes known to regulate T-cell dysfunctionality, foremost PRDM1, and transcription factors (ZEB2) expected to drive the differentiation of killer cell lectin-like receptor (KLR)+ exhausted T-cell states with residual cytolytic potential. Finally, we applied the least absolute shrinkage and selection operator (LASSO) statistical method for feature selection to our discovery AML dataset, and we constructed a TP53-m-related ‘spatial metagene’ that predicted poor overall survival in TCGA-LAML (N=170) and Beat-AML2 cases (N=444; Fig. 1E).


Spatial gene programs of leukemia stemness, T-cell dysfunction and immune suppression are enriched in TP53-m AML. It remains to be determined whether TP53-m AML with a pre-existing but ineffective T-cell response may be amenable to T cell-targeting immunotherapies.

Disclosures: von Bonin: Novartis: Other: Advisory Board; BMS: Other: Advisory Board; Janssen: Research Funding; Kite: Other: Advisory Board. Zeiser: MNK: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; incyte: Consultancy, Honoraria; novartis: Consultancy, Honoraria, Research Funding; Medac: Honoraria; VectivBio: Consultancy. Rutella: Wugen: Research Funding.

*signifies non-member of ASH