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Screening-based approach to discover effective platinum-based chemotherapies for cancers with poor prognosis.

ABSTRACT: Drug combinations are extensively used to treat cancer and are often selected according to complementary mechanisms. Here, we describe a cell-based high-throughput screening assay for identification of synergistic combinations between broadly applied platinum-based chemotherapeutics and drugs from a library composed of 1280 chemically and pharmacologically diverse (mostly FDA approved) compounds. The assay was performed on chemoresistant cell lines derived from lung (A549) and pancreatic (PANC-1) carcinoma, where platinum-based combination regimens are currently applied though with limited success. The synergistic combinations identified during the screening were validated by synergy quantification using the combination index method and via high content fluorescent microscopy analysis. New promising synergistic combinations discovered using this approach include compounds currently not used as anticancer drugs, such as cisplatin or carboplatin with hycanthone and cisplatin with spironolactone in pancreatic carcinoma, and carboplatin and deferoxamine in non-small cell lung cancer. Strong synergy between cisplatin or carboplatin and topotecan in PANC-1 cells, compared to A549 cells, suggests that this combination, currently used in lung cancer treatment regimens, could be applied to pancreatic carcinoma as well. Several drugs used to treat diseases other than cancer, including pyrvinium pamoate, auranofin, terfenadine and haloprogin, showed strong cytotoxicity on their own and synergistic interactions with platinum drugs. This study demonstrates that non-obvious drug combinations that would not be selected based on complementary mechanisms can be identified via high-throughput screening.

SUBMITTER: Varbanov HP

PROVIDER: S-EPMC6350982 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Classical antiviral therapy inhibit viral proteins and are subject to resistance. To counteract this emergence, alternative strategy has been developed that target cellular factors. We hypothesized that such approach could also be useful to identify broad antivirals. Influenza A virus was used as a model for viral diversity and need for therapy against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection with different influenza A virus subtypes which could help to identify potential antiviral drugs with broad spectrum. Cellular gene expression response to infection with five different human and avian influenza viruses strains was analyzed and 300 genes were determined as differentially expressed between infected and non-infected samples. Strikingly, only a few genes were induced by infection and related to immune response. A more concise list was used to screen connectivity map, a database of drug-associated gene expression profiles, for molecules with inverse profiles than the signature of infection. We hypothesized that such compounds would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified, and six inhibited influenza viral growth in vitro. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five of the eight identified molecules, demonstrating that this strategy could help to identify broad spectrum antivirals. This is the first study showing that a gene expression based-screening can be used to identify antivirals. Such approaches could accelerate the drug discovery progress and could be extended to other pathogens. A549 (human lung epithelial cells) were infected with 5 different influenza A strains (A/New Caledonia/20/99 (H1N1), A/Moscow/10/99 (H3N2), A/Lyon/969/09 (H1N1 SOI-V), A/Turkey/582/2006 (H5N1), A/Finch/England/2051/94 (H5N2), and A/Chicken/Italy/2076/99 (H7N1)) or mock infected. Five independant replicates were done and hybridized on a different microarray. The overall design is thus composed of 5 mock samples, and 5x5 infected samples.

Project description:BackgroundAcetyl-CoA acetyltransferase 2 (ACAT2) is a lipid metabolism enzyme and rarely was researched in epithelial ovarian cancer (EOC).MethodsACAT2 expressions were confirmed in two pairs of cell lines (A2780 and A2780/DDP, OVCAR8 and OVCAR8/DDP) from Gene Expression Omnibus database by bioinformatics analysis, and in A2780 and A2780/DDP cell lines by quantitative real-time polymerase chain reaction and western blotting. Tissue samples were stained by immunohistochemistry and scored for ACAT2 expression. The relationships between ACAT2 expression and clinicopathological characteristics were analyzed by χ2 test. The prognosis of ACAT2 was analyzed by the log-rank tests and Cox regression models.ResultsACAT2 was remarkably upregulated in the above drug-resistant cell lines by mRNA (all P < 0.05) and protein expression (P = 0.026) than those in sensitive ones. Patients were classified as ACAT2-high (n = 51) and ACAT2-low (n = 26) according to immunohistochemical score. ACAT2 expression had a significantly inverse correlation with FIGO stage (P = 0.030) and chemo-response (P = 0.041). A marginal statistical significance existed in ACAT2 expression and ascites volume (P = 0.092). Univariate analysis suggested that high-expressed ACAT2 was associated with decreased platinum-free interval (PFI) (8.57 vs. 14.13 months, P = 0.044), progression-free survival (PFS) (14.12 vs. 19.79 months, P = 0.039) and overall survival (OS) (36.89 vs. 52.40 months, P = 0.044). Multivariate analysis demonstrated that ACAT2 expression (hazard ratio = 2.18, 95% confidence interval: 1.15-4.11, P = 0.017) affected OS independently, rather than PFI and PFS.ConclusionThe expression of ACAT2 in A2780/DDP and OVCAR8/DDP was higher than the corresponding A2780 and OVCAR8. High-expressed ACAT2 was associated with advanced FIGO stage, chemo-resistance, and decreased PFI, PFS and OS. It was an independent prognostic factor of OS in EOC.

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Screening-based approach to discover effective platinum-based chemotherapies for cancers with poor prognosis.

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