Dataset Information

Nanotechnology and Immunotherapy in Ovarian Cancer: Tracing New Landscapes.

ABSTRACT: Ovarian cancer (OC) is the seventh most common cancer in women worldwide. Standard therapeutic treatments involve debulking surgery combined with platinum-based chemotherapies. Of the patients with advanced-stage cancer who initially respond to current treatments, 50%-75% relapse. Immunotherapy-based approaches aimed at boosting antitumor immunity have recently emerged as promising tools to challenge tumor progression. Treatments with inhibitors of immune checkpoint molecules have shown impressive results in other types of tumors. However, only 15% of checkpoint inhibitors evaluated have proven successful in OC due to the immunosuppressive environment of the tumor and the transport barriers. This limits the efficacy of the existing immunotherapies. Nanotechnology-based delivery systems hold the potential to overcome such limitations. Various nanoformulations including polymeric, liposomes, and lipid-polymer hybrid nanoparticles have already been proposed to improve the biodistribution and targeting capabilities of drugs against tumor-associated immune cells, including dendritic cells and macrophages. In this review, we examine the impact of immunotherapeutic approaches that are currently under consideration for the treatment of OC. In this review, we also provide a comprehensive analysis of the existing nanoparticle-based synthetic strategies and their limitations and advantages over standard treatments. Furthermore, we discuss how the strength of the combination of nanotechnology with immunotherapy may help to overcome the current therapeutic limitations associated with their individual application and unravel a new paradigm in the treatment of this malignancy.

SUBMITTER: Corradetti B

PROVIDER: S-EPMC6806629 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Nanotechnology and Immunotherapy in Ovarian Cancer: Tracing New Landscapes.

Corradetti Bruna B Pisano Simone S Conlan Robert Steven RS Ferrari Mauro M

The Journal of pharmacology and experimental therapeutics 20190208 3

Ovarian cancer (OC) is the seventh most common cancer in women worldwide. Standard therapeutic treatments involve debulking surgery combined with platinum-based chemotherapies. Of the patients with advanced-stage cancer who initially respond to current treatments, 50%-75% relapse. Immunotherapy-based approaches aimed at boosting antitumor immunity have recently emerged as promising tools to challenge tumor progression. Treatments with inhibitors of immune checkpoint molecules have shown impressi ...[more]

PMID: 30737357

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Project description:PurposeThe current paradigm in the development of high-grade serous ovarian carcinoma (HGSC) proposes that the majority of HGSCs arise from precursor serous tubal intraepithelial carcinoma (STIC) lesions of the fallopian tube. Here we survey genome-wide methylation in HGSC precursor lesions to identify genomic regions that exhibit high-specificity differential hypermethylation for potential use as biomarkers for detecting STIC and HGSC at stages when curative intervention likely remains feasible.Experimental designWe first identified quality control criteria for performing reliable methylomic analysis of DNA-limited tubal precursor lesions with the Illumina Infinium MethylationEPIC array. We then used this platform to compare genome-wide methylation among 12 STICs with paired adjacent-normal epithelia, one p53 signature lesion and two samples of concurrent HGSC. The resulting methylomic data were analyzed by unsupervised hierarchical clustering and multidimensional analysis. Regions of high-confidence STIC-specific differential hypermethylation were identified using selective bioinformatic criteria and compared with published MethylationEPIC data from 23 HGSC tumors and 11 healthy fallopian tube mucosae.ResultsUnsupervised analysis showed that STICs largely clustered with HGSCs, but were clearly distinct from adjacent-normal fallopian tube epithelia. Forty-two genomic regions exhibited high-confidence STIC-specific differential hypermethylation, of which 17 (40.5%) directly overlapped with HGSC-specific differentially methylated regions. Methylation at these shared loci was able to completely distinguish STIC and HGSC samples from normal and adjacent-normal specimens.ConclusionsOur results suggest that most STICs are epigenetically similar to HGSCs and share regions of differential hypermethylation that warrant further evaluation for potential use as biomarkers for early detection of ovarian HGSC.See related commentary by Ishak and De Carvalho, p. 6083.

Dataset Information

Nanotechnology and Immunotherapy in Ovarian Cancer: Tracing New Landscapes.

Publications

Nanotechnology and Immunotherapy in Ovarian Cancer: Tracing New Landscapes.

Similar Datasets

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