PMID- 34610532
OWN - NLM
STAT- MEDLINE
DCOM- 20211227
LR  - 20211227
IS  - 1476-928X (Electronic)
IS  - 1476-9271 (Linking)
VI  - 95
DP  - 2021 Dec
TI  - Modeling codelivery of CD73 inhibitor and dendritic cell-based vaccines in cancer 
      immunotherapy.
PG  - 107585
LID - S1476-9271(21)00155-9 [pii]
LID - 10.1016/j.compbiolchem.2021.107585 [doi]
AB  - Dendritic cells (DCs) are the dominant class of antigen-presenting cells in 
      humans; therefore, a range of DC-based approaches have been established to 
      promote an immune response against cancer cells. The efficacy of DC-based 
      immunotherapeutic approaches is markedly affected by the immunosuppressive 
      factors related to the tumor microenvironment, such as adenosine. In this paper, 
      based on immunological theories and experimental data, a hybrid model is designed 
      that offers some insights into the effects of DC-based immunotherapy combined 
      with adenosine inhibition. The model combines an individual-based model for 
      describing tumor-immune system interactions with a set of ordinary differential 
      equations for adenosine modeling. Computational simulations of the proposed model 
      clarify the conditions for the onset of a successful immune response against 
      cancer cells. Global and local sensitivity analysis of the model highlights the 
      importance of adenosine blockage for strengthening effector cells. The model is 
      used to determine the most effective suppressive mechanism caused by adenosine, 
      proper vaccination time, and the appropriate time interval between injections.
CI  - Copyright (c) 2021 Elsevier Ltd. All rights reserved.
FAU - Arabameri, Abazar
AU  - Arabameri A
AD  - Department of Electrical Engineering, University of Zanjan, Zanjan, Iran. 
      Electronic address: arabameri@znu.ac.ir.
FAU - Pourgholaminejad, Arash
AU  - Pourgholaminejad A
AD  - Department of Immunology, School of Medicine, Guilan University of Medical 
      Sciences, Rasht, Iran. Electronic address: pourgholaminejad@gums.ac.ir.
LA  - eng
PT  - Journal Article
DEP - 20210925
PL  - England
TA  - Comput Biol Chem
JT  - Computational biology and chemistry
JID - 101157394
RN  - 0 (Cancer Vaccines)
RN  - 0 (GPI-Linked Proteins)
RN  - EC 3.1.3.5 (5'-Nucleotidase)
RN  - EC 3.1.3.5 (NT5E protein, human)
SB  - IM
MH  - 5'-Nucleotidase/*immunology
MH  - Cancer Vaccines/*immunology
MH  - Computational Biology
MH  - Dendritic Cells/*immunology
MH  - GPI-Linked Proteins/immunology
MH  - Humans
MH  - *Immunotherapy
MH  - *Models, Immunological
MH  - Neoplasms/immunology/*therapy
OTO - NOTNLM
OT  - Adenosine
OT  - Hybrid model
OT  - Immune system
OT  - Individual based model
OT  - Mathematical modelling
OT  - Ordinary differential equations
OT  - Tumor
EDAT- 2021/10/06 06:00
MHDA- 2021/12/28 06:00
CRDT- 2021/10/05 20:16
PHST- 2021/02/18 00:00 [received]
PHST- 2021/07/16 00:00 [revised]
PHST- 2021/09/23 00:00 [accepted]
PHST- 2021/10/06 06:00 [pubmed]
PHST- 2021/12/28 06:00 [medline]
PHST- 2021/10/05 20:16 [entrez]
AID - S1476-9271(21)00155-9 [pii]
AID - 10.1016/j.compbiolchem.2021.107585 [doi]
PST - ppublish
SO  - Comput Biol Chem. 2021 Dec;95:107585. doi: 10.1016/j.compbiolchem.2021.107585. 
      Epub 2021 Sep 25.