Increased expression of RUNX3 inhibits normal human myeloid development

SF3B1 mutations provide genetic vulnerability to copper ionophores in human acute myeloid leukemia

In a phenotypical screen of 56 acute myeloid leukemia (AML) patient samples and using a library of 10,000 compounds, we identified a hit with increased sensitivity toward SF3B1-mutated and adverse risk AMLs. Through structure-activity relationship studies, this hit was optimized into a potent, specific, and nongenotoxic molecule called UM4118. We demonstrated that UM4118 acts as a copper ionophore that initiates a mitochondrial-based noncanonical form of cell death known as cuproptosis. CRISPR-Cas9 loss-of-function screen further revealed that iron-sulfur cluster (ISC) deficiency enhances copper-mediated cell death. Specifically, we found that loss of the mitochondrial ISC transporter ABCB7 is synthetic lethal to UM4118. ABCB7 is misspliced and down-regulated in SF3B1-mutated leukemia, creating a vulnerability to copper ionophores. Accordingly, ABCB7 overexpression partially rescued SF3B1-mutated cells to copper overload. Together, our work provides mechanistic insights that link ISC deficiency to cuproptosis, as exemplified by the high sensitivity of SF3B1-mutated AMLs. We thus propose SF3B1 mutations as a biomarker for future copper ionophore-based therapies.

Integrated analysis and validation reveal CYTH4 as a potential prognostic biomarker in acute myeloid leukemia

Acute myeloid leukemia (AML) is a clonal hematological malignancy with high mortality rates. The identification of novel markers is urgent for AML. Cytohesins are a subfamily of guanine nucleotide exchange factors activating the ADP-ribosylation factor family GTPases. While the important roles of cytohesins have been reported in various cancers, their function in AML remains unclear. The present study aimed to explore the prognostic impact of cytohesin-4 (CYTH4) and the underlying molecular functions. RNA sequencing and AML clinical data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases to investigate gene expression and survival. Using the R software, differentially expressed genes were identified between the high- and the low-CYTH4 group. Functional enrichment analysis was conducted by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analyses. The CIBERSORTx tool was used to explore the proportions of different immune cell types. The molecular function of CYTH4 was also validated in vitro by examining cell growth, cell cycle, apoptosis and colony-forming ability. CYTH4 was significantly upregulated in AML compared with other cancers and normal tissues. High CYTH4 expression was associated with high white blood count (P=0.004) and higher risk status (P<0.001). Patients with high CYTH4 expression had poor overall survival (OS; HR=2.19; 95% CI, 1.40-3.44; P=0.0006; high vs. low) and event-free survival (EFS; HR=2.32; 95% CI, 1.43-3.75; P=0.0006; high vs. low), and these patients could benefit from transplantation (HR=0.29; 95% CI, 0.18-0.47; P<0.0001; transplantation vs. chemotherapy). Multivariate analysis showed that high CYTH4 expression was independently associated with inferior OS (HR=2.49; 95% CI, 1.28-4.83; P=0.007) and EFS (HR=2.56; 95% CI, 1.48-4.42; P=0.001). Functional analysis showed that CYTH4 was involved in immunoregulation. In vitro validation showed knockdown of CYTH4 adversely affected cell growth and induced cell apoptosis, while overexpression of CYTH4 enhanced cell growth. Taken together, CYTH4 is expressed at high levels in AML and can potentially function as a prognostic biomarker.

Immune determinants of CAR-T cell expansion in solid tumor patients receiving GD2 CAR-T cell therapy

Chimeric antigen receptor T cells (CAR-Ts) have remarkable efficacy in liquid tumors, but limited responses in solid tumors. We conducted a Phase I trial (NCT02107963) of GD2 CAR-Ts (GD2-CAR.OX40.28.z.iC9), demonstrating feasibility and safety of administration in children and young adults with osteosarcoma and neuroblastoma. Since CAR-T efficacy requires adequate CAR-T expansion, patients were grouped into good or poor expanders across dose levels. Patient samples were evaluated by multi-dimensional proteomic, transcriptomic, and epigenetic analyses. T cell assessments identified naive T cells in pre-treatment apheresis associated with good expansion, and exhausted T cells in CAR-T products with poor expansion. Myeloid cell assessment identified CXCR3+ monocytes in pre-treatment apheresis associated with good expansion. Longitudinal analysis of post-treatment samples identified increased CXCR3- classical monocytes in all groups as CAR-T numbers waned. Together, our data uncover mediators of CAR-T biology and correlates of expansion that could be utilized to advance immunotherapies for solid tumor patients.

Ppm1d truncating mutations promote the development of genotoxic stress-induced AML

Hematopoietic stem cells (HSCs) ensure blood cell production during the life-time of an organism, and to do so they need to balance self-renewal, proliferation, differentiation, and migration in a steady state as well as in response to stress or injury. Importantly, aberrant proliferation of HSCs leads to hematological malignancies, and thus, tight regulation by various tumor suppressor pathways, including p53, is essential. Protein phosphatase magnesium-dependent 1 delta (PPM1D) is a negative regulator of p53 and promotes cell survival upon induction of genotoxic stress. Truncating mutations in the last exon of PPM1D lead to the production of a stable, enzymatically active protein and are commonly associated with clonal hematopoiesis. Using a transgenic mouse model, we demonstrate that truncated PPM1D reduces self-renewal of HSCs in basal conditions but promotes the development of aggressive AML after exposure to ionizing radiation. Inhibition of PPM1D suppressed the colony growth of leukemic stem and progenitor cells carrying the truncated PPM1D, and remarkably, it provided protection against irradiation-induced cell growth. Altogether, we demonstrate that truncated PPM1D affects HSC maintenance, disrupts normal hematopoiesis, and that its inhibition could be beneficial in the context of therapy-induced AML.

Exploration of common genomic signatures of systemic juvenile rheumatoid arthritis and type 1 diabetes

To explore the genetic characteristics of systemic juvenile rheumatoid arthritis (sJRA) and type 1 diabetes mellitus (T1D). The microarray data of sJRA and T1D from Gene Expression Omnibus (GEO) were analyzed. The shared differentially expressed genes (SDEGs) were identified by the Meta-analysis, and genes of extracellular proteins were identified. Then, transcription factors (TFs) and their target genes in SDEGs were obtained by comparing databases from HumanTFDB, and hTFtarget. After that, functional enrichment analyses of the previously identified gene sets were performed by metascape tool. Finally, immune infiltration was analysed by CIBERSORT. We found 175 up-regulated and 245 down-regulated SDEGs, and by constructing a TFs-targeted SDEGs network, 3 key TFs (ARID3A, NEF2, RUNX3) were screened. Functional enrichment analyses and immune infiltration results suggested not only the adaptive immune system but also the innate immune system, and signaling pathways like JAK-STAT are important in the pathogenesis of sJRA and T1D, involving biological processes such as CD4 T cell functions and neutrophil degranulation. This work suggests that innate immune abnormalities also play important roles in sJRA and T1D, CD4 T cell functions, neutrophil degranulation and the JAK-STAT pathway may be involved. The regulatory roles of ARID3A, NEF2, and RUNX3 in this network need to be further investigated.

Transcriptomic Context of RUNX3 Expression in Monocytes: A Cross-Sectional Analysis

The runt-related transcription factor 3 (RUNX3) regulates the differentiation of monocytes and their response to inflammation. However, the transcriptomic context of RUNX3 expression in blood monocytes remains poorly understood. We aim to learn about RUNX3 from its relationships within transcriptomes of bulk CD14+ cells in adults. This study used immunomagnetically sorted CD14+ cell gene expression microarray data from the Multi-Ethnic Study of Atherosclerosis (MESA, n = 1202, GSE56047) and the Correlated Expression and Disease Association Research (CEDAR, n = 281, E-MTAB-6667) cohorts. The data were preprocessed, subjected to RUNX3-focused correlation analyses and random forest modeling, followed by the gene ontology analysis. Immunity-focused differential ratio analysis with intermediary inference (DRAIMI) was used to integrate the data with protein-protein interaction network. Correlation analysis of RUNX3 expression revealed the strongest positive association for EVL (r_mean = 0.75, p_FDR-MESA = 5.37 × 10^-140, p_FDR-CEDAR = 5.52 × 10^-80), ARHGAP17 (r_mean = 0.74, p_FDR-MESA = 1.13 × 10^-169, p_FDR-CEDAR = 9.20 × 10^-59), DNMT1 (r_mean = 0.74, p_FDR-MESA = 1.10 × 10^-169, p_FDR-CEDAR = 1.67 × 10^-58), and CLEC16A (r_mean = 0.72, p_FDR-MESA = 3.51 × 10^-154, p_FDR-CEDAR = 2.27 × 10^-55), while the top negative correlates were C2ORF76 (r_mean = -0.57, p_FDR-MESA = 8.70 × 10^-94, p_FDR-CEDAR = 1.31 × 10^-25) and TBC1D7 (r_mean = -0.55, p_FDR-MESA = 1.36 × 10^-69, p_FDR-CEDAR = 7.81 × 10^-30). The RUNX3-associated transcriptome signature was involved in mRNA metabolism, signal transduction, and the organization of cytoskeleton, chromosomes, and chromatin, which may all accompany mitosis. Transcriptomic context of RUNX3 expression in monocytes hints at its relationship with cell growth, shape maintenance, and aspects of the immune response, including tyrosine kinases.

Multimodal deep learning to predict prognosis in adult and pediatric brain tumors

BACKGROUND

The introduction of deep learning in both imaging and genomics has significantly advanced the analysis of biomedical data. For complex diseases such as cancer, different data modalities may reveal different disease characteristics, and the integration of imaging with genomic data has the potential to unravel additional information than when using these data sources in isolation. Here, we propose a DL framework that combines these two modalities with the aim to predict brain tumor prognosis.

METHODS

Using two separate glioma cohorts of 783 adults and 305 pediatric patients we developed a DL framework that can fuse histopathology images with gene expression profiles. Three strategies for data fusion were implemented and compared: early, late, and joint fusion. Additional validation of the adult glioma models was done on an independent cohort of 97 adult patients.

RESULTS

Here we show that the developed multimodal data models achieve better prediction results compared to the single data models, but also lead to the identification of more relevant biological pathways. When testing our adult models on a third brain tumor dataset, we show our multimodal framework is able to generalize and performs better on new data from different cohorts. Leveraging the concept of transfer learning, we demonstrate how our pediatric multimodal models can be used to predict prognosis for two more rare (less available samples) pediatric brain tumors.

CONCLUSIONS

Our study illustrates that a multimodal data fusion approach can be successfully implemented and customized to model clinical outcome of adult and pediatric brain tumors.

Genetics and Epigenetics in Neoplasms with Plasmacytoid Dendritic Cells

Simple Summary

Differential diagnosis between Blastic pDC Neoplasm (BPDCN) and Acute Myeloid Leukemia with pDC expansion (pDC-AML) is particularly challenging, and genomic features can help in diagnosis. This review aims at clarifying recent data on genomics features because the past five years have generated a large amount of original data regarding pDC neoplasms. The genetic landscape of BPDCN is now well-defined, with important updates concerning MYC/MYC rearrangements, but also epigenetic defects and novel concepts in oncogenic and immune pathways. Concerning pDC-AML, they now appear to exhibit an original mutation landscape, especially with RUNX1 mutations, which is of interest for diagnostic criteria and for therapeutic purposes. We highlight here these two different profiles, which contribute to differential diagnosis between BPDCN and pDC-AML. This point is particularly important for the study of different therapeutic strategies between BPDCN and AML.

Abstract

Plasmacytoid Dendritic Cells (pDC) are type I interferon (IFN)-producing cells that play a key role in immune responses. Two major types of neoplastic counterparts for pDC are now discriminated: Blastic pDC Neoplasm (BPDCN) and Mature pDC Proliferation (MPDCP), associated with myeloid neoplasm. Two types of MPDCP are now better described: Chronic MyeloMonocytic Leukemia with pDC expansion (pDC-CMML) and Acute Myeloid Leukemia with pDC expansion (pDC-AML). Differential diagnosis between pDC-AML and BPDCN is particularly challenging, and genomic features can help for diagnosis. Here, we systematically review the cytogenetic, molecular, and transcriptional characteristics of BPDCN and pDC-AML. BPDCN are characterized by frequent complex karyotypes with recurrent MYB/MYC rearrangements as well as recurrent deletions involving ETV6, IKZF1, RB1, and TP53 loci. Epigenetic and splicing pathways are also particularly mutated, while original processes are dysregulated, such as NF-kB, TCF4, BCL2, and IFN pathways; neutrophil-specific receptors; and cholinergic signaling. In contrast, cytogenetic abnormalities are limited in pDC-AML and are quite similar to other AML. Interestingly, RUNX1 is the most frequently mutated gene (70% of cases). These typical genomic features are of potential interest for diagnosis, and also from a prognostic or therapeutic perspective.