JAK-STAT inhibitor as a potential therapeutic opportunity in AML patients resistant to cytarabine and epigenetic therapy.
Govind BabuPadmaparna ChaudhuriManoj RajappaManjusha BiswasBipinesh SansarChethan RajegowdaAneesha RadhakrishnanJayshree AdvaniBiplab TewaryPadhma RadhakrishnanSaravanan ThiyagarajanAditi ChatterjeeRam Shankar UpadhayayaPradip K MajumderPublished in: Cancer biology & therapy (2020)
The prognosis of AML is generally poor, with 5-year survival rate of 25%. There has been substantial progress in identification of new therapeutic targets, along with approval of at least three targeted therapies for AML in recent years. Nevertheless, treatment has largely remained unchanged over couple of decades, with ~40% patients not achieving remission. AML is a highly heterogenous disease and there is a need for a preclinical platform to understand the heterogeneity and tumor microenvironment that can guide therapy selection. In this study, we employed an ex vivo tumor explant model to study tumor microenvironment and to select a treatment course for AML patients. Our data reveal dysregulation of DNA methyltransferase (DNMT) and histone deacetylase (HDAC) in a subset of AML patients. Based on this observation, epigenetic modulators azacitidine and panobinostat alone and in combination, were evaluated as treatment regimens in cytarabine refractory tumors. More than 50% of the treated samples showed response to the combination therapy. In order to explore alternate treatment modalities for tumors refractory to these epigenetic modulators, TCGA data analysis was done which revealed increased expression and hypomethylation of IFNGR1/2, suggesting activation of JAK/STAT pathway in AML. This was further interrogated ex vivo, with p-STAT3 expression in patients' samples. Fedratinib, a JAK/STAT inhibitor was evaluated and 78% tumor efficacy response was achieved. Taken together, our data indicate that ex vivo platform derived from patient samples is capable in guiding optimal therapy selection for various classes of drugs including identification of novel targeted therapies.
Keyphrases
- acute myeloid leukemia
- end stage renal disease
- ejection fraction
- newly diagnosed
- combination therapy
- chronic kidney disease
- data analysis
- peritoneal dialysis
- gene expression
- dna methylation
- prognostic factors
- allogeneic hematopoietic stem cell transplantation
- histone deacetylase
- high dose
- low dose
- small molecule
- patient reported outcomes
- high throughput
- acute lymphoblastic leukemia
- bone marrow
- systemic lupus erythematosus
- big data
- cell free
- artificial intelligence