The Potential Advantage of Targeting Both PD-L1/PD-L2/PD-1 and IL-10-IL-10R Pathways in Acute Myeloid Leukemia.
Laura JimbuOana MesarosAlexandra NeagaAna Maria NanutCiprian Ionut TomuleasaDelia DimaIoana Corina BocsanMihnea T ZdrengheaPublished in: Pharmaceuticals (Basel, Switzerland) (2021)
Tumor cells promote the suppression of host anti-tumor type 1 T cell responses by various mechanisms, including the upregulation of surface inhibitory molecules such as programmed death ligand (PD-L)-1, and the production of immunosuppressive cytokines such as interleukin-10 (IL-10). There are over 2000 trials investigating PD-L1 and/or its receptor programmed-death 1 (PD-1) blockade in cancer, leading to the approval of PD-1 or PD-L1 inhibitors in several types of solid cancers and in hematological malignancies. The available data suggest that the molecule PD-L1 on antigen-presenting cells suppresses type 1 T cell immune responses such as cytotoxicity, and that the cytokine IL-10, in addition to downregulating immune responses, increases the expression of inhibitory molecule PD-L1. We hypothesize that the manipulation of both the co-inhibitory network (with anti-PD-L1 blocking antibodies) and suppressor network (with anti-IL-10 blocking antibodies) is an attractive immunotherapeutic intervention for acute myeloid leukemia (AML) patients ineligible for standard treatment with chemotherapy and hematopoietic stem cell transplantation, and with less severe adverse reactions. The proposed combination of these two immunotherapies represents a new approach that can be readily translated into the clinic to improve the therapeutic efficacy of AML disease treatment.
Keyphrases
- acute myeloid leukemia
- immune response
- poor prognosis
- randomized controlled trial
- end stage renal disease
- allogeneic hematopoietic stem cell transplantation
- chronic kidney disease
- primary care
- dendritic cells
- newly diagnosed
- long non coding rna
- emergency department
- machine learning
- binding protein
- inflammatory response
- drug delivery
- risk assessment
- big data
- papillary thyroid
- combination therapy
- cell death
- patient reported outcomes
- data analysis
- adverse drug
- rectal cancer