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An Anticancer Drug Cocktail of Three Kinase Inhibitors Improved Response to a Dendritic Cell-Based Cancer Vaccine.

ABSTRACT: Monocyte-derived dendritic cell (moDC)-based cancer therapies intended to elicit antitumor T-cell responses have limited efficacy in most clinical trials. However, potent and sustained antitumor activity in a limited number of patients highlights the therapeutic potential of moDCs. In vitro culture conditions used to generate moDCs can be inconsistent, and moDCs generated in vitro are less effective than natural DCs. On the basis of our study highlighting the ability for certain kinase inhibitors to enhance tumor antigenicity, we therefore screened kinase inhibitors for their ability to improve DC immunogenicity. We identified AKT inhibitor MK2206, DNA-PK inhibitor NU7441, and MEK inhibitor trametinib as the compounds most effective at modulating moDC immunogenicity. The combination of these drugs, referred to as MKNUTRA, enhanced moDC activity over treatment with individual drugs while exhibiting minimal toxicity. An evaluation of 335 activation and T-cell-suppressive surface proteins on moDCs revealed that MKNUTRA treatment more effectively matured cells and reduced the expression of tolerogenic proteins as compared with control moDCs. MKNUTRA treatment imparted to ICT107, a glioblastoma (GBM) DC-based vaccine that has completed phase II trials, an increased ability to stimulate patient-derived autologous CD8+ T cells against the brain tumor antigens IL13R?2(345-354) and TRP2(180-188) In vivo, treating ICT107 with MKNUTRA, prior to injection into mice with an established GBM tumor, reduced tumor growth kinetics. This response was associated with an increased frequency of tumor-reactive lymphocytes within tumors and in peripheral tissues. These studies broaden the application of targeted anticancer drugs and highlight their ability to increase moDC immunogenicity.

SUBMITTER: Guo J

PROVIDER: S-EPMC6726569 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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An Anticancer Drug Cocktail of Three Kinase Inhibitors Improved Response to a Dendritic Cell-Based Cancer Vaccine.

Guo Jitao J Muse Elena E Christians Allison J AJ Swanson Steven J SJ Davila Eduardo E

Cancer immunology research 20190702 9

Monocyte-derived dendritic cell (moDC)-based cancer therapies intended to elicit antitumor T-cell responses have limited efficacy in most clinical trials. However, potent and sustained antitumor activity in a limited number of patients highlights the therapeutic potential of moDCs. <i>In vitro</i> culture conditions used to generate moDCs can be inconsistent, and moDCs generated <i>in vitro</i> are less effective than natural DCs. On the basis of our study highlighting the ability for certain ki ...[more]

PMID: 31266784

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Project description:BackgroundHuman cancer cell lines are used in research to study the biology of cancer and to test cancer treatments. Recently there are already some large panels of several hundred human cancer cell lines which are characterized with genomic and pharmacological data. The ability to predict drug responses using these pharmacogenomics data can facilitate the development of precision cancer medicines. Although several methods have been developed to address the drug response prediction, there are many challenges in obtaining accurate prediction.MethodsBased on the fact that similar cell lines and similar drugs exhibit similar drug responses, we adopted a similarity-regularized matrix factorization (SRMF) method to predict anticancer drug responses of cell lines using chemical structures of drugs and baseline gene expression levels in cell lines. Specifically, chemical structural similarity of drugs and gene expression profile similarity of cell lines were considered as regularization terms, which were incorporated to the drug response matrix factorization model.ResultsWe first demonstrated the effectiveness of SRMF using a set of simulation data and compared it with two typical similarity-based methods. Furthermore, we applied it to the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets, and performance of SRMF exceeds three state-of-the-art methods. We also applied SRMF to estimate the missing drug response values in the GDSC dataset. Even though SRMF does not specifically model mutation information, it could correctly predict drug-cancer gene associations that are consistent with existing data, and identify novel drug-cancer gene associations that are not found in existing data as well. SRMF can also aid in drug repositioning. The newly predicted drug responses of GDSC dataset suggest that mTOR inhibitor rapamycin was sensitive to non-small cell lung cancer (NSCLC), and expression of AK1RC3 and HINT1 may be adjunct markers of cell line sensitivity to rapamycin.ConclusionsOur analysis showed that the proposed data integration method is able to improve the accuracy of prediction of anticancer drug responses in cell lines, and can identify consistent and novel drug-cancer gene associations compared to existing data as well as aid in drug repositioning.

Dataset Information

An Anticancer Drug Cocktail of Three Kinase Inhibitors Improved Response to a Dendritic Cell-Based Cancer Vaccine.

Publications

An Anticancer Drug Cocktail of Three Kinase Inhibitors Improved Response to a Dendritic Cell-Based Cancer Vaccine.

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