Integrated extracellular microRNA profiling for ovarian cancer screening

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Abstract

A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9–10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer.

Abstract

Screening methods for early detection of ovarian cancer is technically difficult. Here, the authors investigated circulating microRNA in human blood serum and developed a model using 10 microRNAs to discern between ovarian cancer and being ovarian tumors, solid tumors, and non-cancer patients.

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Cancer Statistics, 2017.

Rebecca Siegel, Kimberly D Miller, Ahmedin Jemal (2017)

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data were collected by the National Center for Health Statistics. In 2017, 1,688,780 new cancer cases and 600,920 cancer deaths are projected to occur in the United States. For all sites combined, the cancer incidence rate is 20% higher in men than in women, while the cancer death rate is 40% higher. However, sex disparities vary by cancer type. For example, thyroid cancer incidence rates are 3-fold higher in women than in men (21 vs 7 per 100,000 population), despite equivalent death rates (0.5 per 100,000 population), largely reflecting sex differences in the "epidemic of diagnosis." Over the past decade of available data, the overall cancer incidence rate (2004-2013) was stable in women and declined by approximately 2% annually in men, while the cancer death rate (2005-2014) declined by about 1.5% annually in both men and women. From 1991 to 2014, the overall cancer death rate dropped 25%, translating to approximately 2,143,200 fewer cancer deaths than would have been expected if death rates had remained at their peak. Although the cancer death rate was 15% higher in blacks than in whites in 2014, increasing access to care as a result of the Patient Protection and Affordable Care Act may expedite the narrowing racial gap; from 2010 to 2015, the proportion of blacks who were uninsured halved, from 21% to 11%, as it did for Hispanics (31% to 16%). Gains in coverage for traditionally underserved Americans will facilitate the broader application of existing cancer control knowledge across every segment of the population. CA Cancer J Clin 2017;67:7-30. © 2017 American Cancer Society.

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Integrated Genomic Analyses of Ovarian Carcinoma

Nikolaus Schultz (2012)

Summary The Cancer Genome Atlas (TCGA) project has analyzed mRNA expression, miRNA expression, promoter methylation, and DNA copy number in 489 high-grade serous ovarian adenocarcinomas (HGS-OvCa) and the DNA sequences of exons from coding genes in 316 of these tumors. These results show that HGS-OvCa is characterized by TP53 mutations in almost all tumors (96%); low prevalence but statistically recurrent somatic mutations in 9 additional genes including NF1, BRCA1, BRCA2, RB1, and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three miRNA subtypes, four promoter methylation subtypes, a transcriptional signature associated with survival duration and shed new light on the impact on survival of tumors with BRCA1/2 and CCNE1 aberrations. Pathway analyses suggested that homologous recombination is defective in about half of tumors, and that Notch and FOXM1 signaling are involved in serous ovarian cancer pathophysiology.

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MicroRNA biogenesis: coordinated cropping and dicing.

V Kim (2005)

The recent discovery of microRNAs (miRNAs) took many by surprise because of their unorthodox features and widespread functions. These tiny, approximately 22-nucleotide, RNAs control several pathways including developmental timing, haematopoiesis, organogenesis, apoptosis, cell proliferation and possibly even tumorigenesis. Among the most pressing questions regarding this unusual class of regulatory miRNA-encoding genes is how miRNAs are produced in cells and how the genes themselves are controlled by various regulatory networks.

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Author and article information

Contributors

Takahiro Ochiya: tochiya@ncc.go.jp

Journal

Journal ID (nlm-ta): Nat Commun

Journal ID (iso-abbrev): Nat Commun

Title: Nature Communications

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2041-1723

Publication date (Electronic): 17 October 2018

Publication date PMC-release: 17 October 2018

Publication date Collection: 2018

Volume: 9

Electronic Location Identifier: 4319

Affiliations

[1 ]ISNI 0000 0001 2168 5385, GRID grid.272242.3, Division of Molecular and Cellular Medicine, , National Cancer Center Research Institute, ; 05-01-01 Tsukiji, Chuo-ku, Tokyo, 104-0045 Japan

[2 ]ISNI 0000 0001 0943 978X, GRID grid.27476.30, Department of Obstetrics and Gynecology, , Nagoya University Graduate School of Medicine, ; 65 Tsuruma-cho, Showa-ku, Nagoya, 466-8550 Japan

[3 ]ISNI 0000 0001 2168 5385, GRID grid.272242.3, Department of Gynecology, , National Cancer Center Hospital, ; 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045 Japan

[4 ]ISNI 0000 0001 0658 2898, GRID grid.452701.5, New Frontiers Research Institute, Toray Industries, ; 6-10-1 Tebiro, Kamakura city, Kanagawa 248-0036 Japan

[5 ]Division of Bioinformatics, Dynacom Co., Ltd., World Business Garden E25, 2-6-1 Nakase, Mihama-ku, Chiba city, Chiba 261-7125 Japan

[6 ]ISNI 0000 0004 1791 9005, GRID grid.419257.c, Medical Genome Center, , National Center for Geriatrics and Gerontology, ; 7-430 Morioka-cho, Obu, Aichi 474-8511 Japan

[7 ]ISNI 0000 0001 2168 5385, GRID grid.272242.3, Department of Clinical Genomics, Fundamental Innovative Oncology Core, , National Cancer Center Research Institute, ; Tokyo, 104-0045 Japan

[8 ]ISNI 0000 0001 2168 5385, GRID grid.272242.3, Department of Gastrointestinal Medical Oncology, , National Cancer Center Hospital, ; 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045 Japan

Author information

Juntaro Matsuzaki http://orcid.org/0000-0002-3204-5049

Ken Kato http://orcid.org/0000-0002-1733-5072

Tomoyasu Kato http://orcid.org/0000-0001-9561-1522

Article

Publisher ID: 6434

DOI: 10.1038/s41467-018-06434-4

PMC ID: 6192980

PubMed ID: 30333487

SO-VID: eea0a839-6cb0-45c1-aacf-6b2f86cc00ea

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 11 December 2017

Date accepted : 28 August 2018

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Integrated extracellular microRNA profiling for ovarian cancer screening

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Cancer Metabolism

Most cited references 30

Cancer Statistics, 2017.

Integrated Genomic Analyses of Ovarian Carcinoma

MicroRNA biogenesis: coordinated cropping and dicing.

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Cited by 134

Most referenced authors 726