Bioinformatic analysis of the effects and mechanisms of decitabine and cytarabine on acute myeloid leukemia

Epigenetically upregulating TROP2 and SLFN11 enhances therapeutic efficacy of TROP2 antibody drug conjugate sacitizumab govitecan

TROP2 antibody drug conjugates (ADCs) are under active development. We seek to determine whether we can enhance activity of TROP2 ADCs by increasing TROP2 expression. In metaplastic breast cancers (MpBC), there is limited expression of TROP2, and downregulating transcription factor ZEB1 upregulates E-cad and TROP2, thus sensitizing cancers to TROP2 ADC sacituzumab govitecan (SG). Demethylating agent decitabine decreases DNA methyltransferase expression and TROP2 promoter methylation and subsequently increases TROP2 expression. Decitabine treatment as well as overexpression of TROP2 significantly enhance SG antitumor activity. Decitabine also increases SLFN11, a biomarker of topoisomerase 1 inhibitor (TOP1) sensitivity and is synergistic with SG which has a TOP1 payload, in TROP2-expressing SLFN11-low BC cells. In conclusion, TROP2 and SLFN11 expression can be epigenetically modulated and the combination of demethylating agent decitabine with TROP2 ADCs may represent a novel therapeutic approach for tumors with low TROP2 or SLFN11 expression.

Decitabine combined with RDHAP regimen in relapsed/refractory diffuse large B cell lymphoma

BACKGROUND

There is an urgent need for effective treatment of patients with relapsed/refractory diffuse large B-cell lymphoma (R/R-DLBCL). This trial investigated the efficacy of decitabine in combination with rituximab, cisplatin, cytarabine, dexamethasone (RDHAP) in R/R-DLBCL.

METHODS

56 patients were divided into two groups (decitabine-RDHAP group. n = 35; RDHAP group, n = 21). The primary endpoints were the overall response rate (ORR) and duration of remission (DOR). Secondary objectives were toxicity, progression-free survival (PFS), and overall survival (OS).

RESULTS

The ORR was 40% and 33% for decitabine-RDHAP and RDHAP groups, respectively, with no difference between the groups. The DOR for the decitabine-RDHAP regimen was higher than that for the RDHAP regimen (p = 0.044). After a median follow-up of 12.0 months, the median PFS and OS were 7.0 and 17.0 months for in the decitabine-RDHAP group and 5.0 and 9.0 months in the RDHAP group with no significant differences between the two groups (p = 0.47, 0.17). The incidence of adverse events was not significantly different between groups.

CONCLUSION

The decitabine-RDHAP regimen is effective and well tolerated, and is a promising salvage regimen for R/R-DLBCL.

Expression and prognostic potential of GPX1 in human cancers based on data mining

BACKGROUND

Glutathione peroxidase-1 (GPX1) is a member of the GPX family, which considered an enzyme that interacts with oxidative stress. GPX1 differential expression is closely correlated with carcinogenesis and disease progression. In this study, we used bioinformatics analysis to investigate GPX1 expression level and explore the prognostic information in different human cancers.

METHODS

Expression was analyzed via the Oncomine database and Gene Expression Profiling Interactive Analysis tool, and potential prognostic analysis was evaluated using the UALCAN, GEPIA, and DriverDBv3 databases. Then, the UALCAN database was used to find the promoter methylation of GPX1 in defied cancer types. While GPX1 related functional networks were found within the GeneMANIA interactive tool and Cytoscape software. Moreover, Metascape online website was used to analyze Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways.

RESULTS

We found that GPX1 was commonly overexpressed in most human cancers. High expression of GPX1 could lead to poor outcomes in Brain Lower Grade Glioma, while GPX1 over expression was correlated with better prognosis in Kidney renal papillary cell carcinoma (KIPP). High GPX1 expression was marginally associated with poor prognosis in acute myeloid leukemia (AML). Gene regulation network suggested that GPX1 mainly involved in pathways including the glutathione metabolism, ferroptosis, TP53 regulates metabolic genes, reactive oxygen species (ROS) metabolic process, and several other signaling pathways.

CONCLUSIONS

Our findings revealed that GPX1 showed significant expression differences among cancers and served as a prognostic biomarker for defined cancer types. The data mining effectively revealed useful information about GPX1 expression, prognostic values, and potential functional networks in cancers, thus providing researchers with an available way to further explore the mechanism underlying carcinogenesis of genes of interest in different cancers.