RUNX1 transactivates BCR-ABL1 expression in Philadelphia chromosome positive acute lymphoblastic leukemia.

The emergence of tyrosine kinase inhibitors as part of a front-line treatment has greatly improved the clinical outcome of the patients with Ph+ acute lymphoblastic leukemia (ALL). However, a portion of them still become refractory to the therapy mainly through acquiring mutations in the BCR-ABL1 gene, necessitating a novel strategy to treat tyrosine kinase inhibitor (TKI)-resistant Ph+ ALL cases. In this report, we show evidence that RUNX1 transcription factor stringently controls the expression of BCR-ABL1, which can strategically be targeted by our novel RUNX inhibitor, Chb-M'. Through a series of in vitro experiments, we identified that RUNX1 binds to the promoter of BCR and directly transactivates BCR-ABL1 expression in Ph+ ALL cell lines. These cells showed significantly reduced expression of BCR-ABL1 with suppressed proliferation upon RUNX1 knockdown. Moreover, treatment with Chb-M' consistently downregulated the expression of BCR-ABL1 in these cells and this drug was highly effective even in an imatinib-resistant Ph+ ALL cell line. In good agreement with these findings, forced expression of BCR-ABL1 in these cells conferred relative resistance to Chb-M'. In addition, in vivo experiments with the Ph+ ALL patient-derived xenograft cells showed similar results. In summary, targeting RUNX1 therapeutically in Ph+ ALL cells may lead to overcoming TKI resistance through the transcriptional regulation of BCR-ABL1. Chb-M' could be a novel drug for patients with TKI-resistant refractory Ph+ ALL.

Urine cell image recognition using a deep-learning model for an automated slide evaluation system.

OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant). PATIENTS AND METHODS: We collected 195 urine cytology slides from consecutive patients with a histologically confirmed diagnosis of urothelial cancer (between January 2016 and December 2017). Two certified cytotechnologists independently evaluated and labelled each slide; 4637 cell images with concordant diagnoses were selected, including 3128 benign cells (negative), 398 atypical cells, and 1111 cells that were malignant or suspicious for malignancy (positive). This pathologically confirmed labelled dataset was used to represent the ground truth for AI training/validation/testing. Customized CutMix (CircleCut) and Refined Data Augmentation were used for image processing. The model architecture included EfficientNet B6 and Arcface. We used 80% of the data for training and validation (4:1 ratio) and 20% for testing. Model performance was evaluated with fivefold cross-validation. A receiver-operating characteristic (ROC) analysis was used to evaluate the binary classification model. Bayesian posterior probabilities for the AI performance measure (Y) and cytotechnologist performance measure (X) were compared. RESULTS: The area under the ROC curve was 0.99 (95% confidence interval [CI] 0.98-0.99), the highest accuracy was 95% (95% CI 94-97), sensitivity was 97% (95% CI 95-99), and specificity was 95% (95% CI 93-97). The accuracy of AI surpassed the highest level of cytotechnologists for the binary classification [Pr(Y > X) = 0.95]. AI achieved >90% accuracy for all cell subtypes. In the subgroup analysis based on the clinicopathological characteristics of patients who provided the test cells, the accuracy of AI ranged between 89% and 97%. CONCLUSION: Our novel AI classification system for urine cytology successfully classified all cell subtypes with an accuracy of higher than 90%, and achieved diagnostic accuracy of malignancy superior to the highest level achieved by cytotechnologists.

Paradoxical enhancement of leukemogenesis in acute myeloid leukemia with moderately attenuated RUNX1 expressions.

Besides being a classical tumor suppressor, runt-related transcription factor 1 (RUNX1) is now widely recognized for its oncogenic role in the development of acute myeloid leukemia (AML). Here we report that this bidirectional function of RUNX1 possibly arises from the total level of RUNX family expressions. Indeed, analysis of clinical data revealed that intermediate-level gene expression of RUNX1 marked the poorest-prognostic cohort in relation to AML patients with high- or low-level RUNX1 expressions. Through a series of RUNX1 knockdown experiments with various RUNX1 attenuation potentials, we found that moderate attenuation of RUNX1 contributed to the enhanced propagation of AML cells through accelerated cell-cycle progression, whereas profound RUNX1 depletion led to cell-cycle arrest and apoptosis. In these RUNX1-silenced tumors, amounts of compensative upregulation of RUNX2 and RUNX3 expressions were roughly equivalent and created an absolute elevation of total RUNX (RUNX1 + RUNX2 + RUNX3) expression levels in RUNX1 moderately attenuated AML cells. This elevation resulted in enhanced transactivation of glutathione S-transferase α 2 (GSTA2) expression, a vital enzyme handling the catabolization of intracellular reactive oxygen species (ROS) as well as advancing the cell-cycle progressions, and thus ultimately led to the acquisition of proliferative advantage in RUNX1 moderately attenuated AML cells. Besides, treatment with ethacrynic acid, which is known for its GSTA inhibiting property, actually prolonged the survival of AML mice in vivo. Collectively, our findings indicate that moderately attenuated RUNX1 expressions paradoxically enhance leukemogenesis in AML cells through intracellular environmental change via GSTA2, which could be a novel therapeutic target in antileukemia strategy.

Genetic regulation of the RUNX transcription factor family has antitumor effects.

Runt-related transcription factor 1 (RUNX1) is generally considered to function as a tumor suppressor in the development of leukemia, but a growing body of evidence suggests that it has pro-oncogenic properties in acute myeloid leukemia (AML). Here we have demonstrated that the antileukemic effect mediated by RUNX1 depletion is highly dependent on a functional p53-mediated cell death pathway. Increased expression of other RUNX family members, including RUNX2 and RUNX3, compensated for the antitumor effect elicited by RUNX1 silencing, and simultaneous attenuation of all RUNX family members as a cluster led to a much stronger antitumor effect relative to suppression of individual RUNX members. Switching off the RUNX cluster using alkylating agent-conjugated pyrrole-imidazole (PI) polyamides, which were designed to specifically bind to consensus RUNX-binding sequences, was highly effective against AML cells and against several poor-prognosis solid tumors in a xenograft mouse model of AML without notable adverse events. Taken together, these results identify a crucial role for the RUNX cluster in the maintenance and progression of cancer cells and suggest that modulation of the RUNX cluster using the PI polyamide gene-switch technology is a potential strategy to control malignancies.