ATF4 renders human T-cell acute lymphoblastic leukemia cell resistance to FGFR1 inhibitors through amino acid metabolic reprogramming.

Abnormalities of FGFR1 have been reported in multiple malignancies, suggesting FGFR1 as a potential target for precision treatment, but drug resistance remains a formidable obstacle. In this study, we explored whether FGFR1 acted a therapeutic target in human T-cell acute lymphoblastic leukemia (T-ALL) and the molecular mechanisms underlying T-ALL cell resistance to FGFR1 inhibitors. We showed that FGFR1 was significantly upregulated in human T-ALL and inversely correlated with the prognosis of patients. Knockdown of FGFR1 suppressed T-ALL growth and progression both in vitro and in vivo. However, the T-ALL cells were resistant to FGFR1 inhibitors AZD4547 and PD-166866 even though FGFR1 signaling was specifically inhibited in the early stage. Mechanistically, we found that FGFR1 inhibitors markedly increased the expression of ATF4, which was a major initiator for T-ALL resistance to FGFR1 inhibitors. We further revealed that FGFR1 inhibitors induced expression of ATF4 through enhancing chromatin accessibility combined with translational activation via the GCN2-eIF2α pathway. Subsequently, ATF4 remodeled the amino acid metabolism by stimulating the expression of multiple metabolic genes ASNS, ASS1, PHGDH and SLC1A5, maintaining the activation of mTORC1, which contributed to the drug resistance in T-ALL cells. Targeting FGFR1 and mTOR exhibited synergistically anti-leukemic efficacy. These results reveal that FGFR1 is a potential therapeutic target in human T-ALL, and ATF4-mediated amino acid metabolic reprogramming contributes to the FGFR1 inhibitor resistance. Synergistically inhibiting FGFR1 and mTOR can overcome this obstacle in T-ALL therapy.

5-Hydroxymethylcytosine profiles of cfDNA are highly predictive of R-CHOP treatment response in diffuse large B cell lymphoma patients.

BACKGROUND: Although R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) remains the standard chemotherapy regimen for diffuse large B cell lymphoma (DLBCL) patients, not all patients are responsive to the scheme, and there is no effective method to predict treatment response. METHODS: We utilized 5hmC-Seal to generate genome-wide 5hmC profiles in plasma cell-free DNA (cfDNA) from 86 DLBCL patients before they received R-CHOP chemotherapy. To investigate the correlation between 5hmC modifications and curative effectiveness, we separated patients into training (n = 56) and validation (n = 30) cohorts and developed a 5hmC-based logistic regression model from the training cohort to predict the treatment response in the validation cohort. RESULTS: In this study, we identified thirteen 5hmC markers associated with treatment response. The prediction performance of the logistic regression model, achieving 0.82 sensitivity and 0.75 specificity (AUC = 0.78), was superior to existing clinical indicators, such as LDH and stage. CONCLUSIONS: Our findings suggest that the 5hmC modifications in cfDNA at the time before R-CHOP treatment are associated with treatment response and that 5hmC-Seal may potentially serve as a clinical-applicable, minimally invasive approach to predict R-CHOP treatment response for DLBCL patients.

5-Hydroxymethylcytosine Signatures in Circulating Cell-Free DNA as Early Warning Biomarkers for COVID-19 Progression and Myocardial Injury.

Background: The symptoms of coronavirus disease 2019 (COVID-19) range from moderate to critical conditions, leading to death in some patients, and the early warning indicators of the COVID-19 progression and the occurrence of its serious complications such as myocardial injury are limited. Methods: We carried out a multi-center, prospective cohort study in three hospitals in Wuhan. Genome-wide 5-hydroxymethylcytosine (5hmC) profiles in plasma cell-free DNA (cfDNA) was used to identify risk factors for COVID-19 pneumonia and develop a machine learning model using samples from 53 healthy volunteers, 66 patients with moderate COVID-19, 99 patients with severe COVID-19, and 38 patients with critical COVID-19. Results: Our warning model demonstrated that an area under the curve (AUC) for 5hmC warning moderate patients developed into severe status was 0.81 (95% CI 0.77-0.85) and for severe patients developed into critical status was 0.92 (95% CI 0.89-0.96). We further built a warning model on patients with and without myocardial injury with the AUC of 0.89 (95% CI 0.84-0.95). Conclusion: This is the first study showing the utility of 5hmC as an accurate early warning marker for disease progression and myocardial injury in patients with COVID-19. Our results show that phosphodiesterase 4D and ten-eleven translocation 2 may be important markers in the progression of COVID-19 disease.