Whole blood-derived miRNA profiles as potential new tools for ovarian cancer screening

Background:Screening is an unsolved problem for ovarian cancer (OvCA). As late detection is equivalent to poor prognosis, we analysed whether OvCA patients show diagnostically meaningful microRNA (miRNA) patterns in blood cells.Methods:Blood-borne whole miRNome profiles from 24 patients with OvCA and 15 age- and sex-matched healthy controls were biostatistically evaluated.Results:Student's t-test revealed 147 significantly deregulated miRNAs before and 4 after Benjamini–Hochberg adjustment. Although these included miRNAs already linked to OvCA (e.g., miR-16, miR-155), others had never before been connected to specific diseases. A bioinformatically calculated miRNA profile allowed for discrimination between blood samples of OvCA patients and healthy controls with an accuracy of >76%. When only cancers of the serous subtype were considered and compared with an extended control group (n=39), accuracy, specificity and sensitivity all increased to >85%.Conclusion:Our proof-of-principle study strengthens the hypothesis that neoplastic diseases generate characteristic miRNA fingerprints in blood cells. Still, the obtained OvCA-associated miRNA pattern is not yet sensitive and specific enough to permit the monitoring of disease progression or even preventive screening. Microarray-based miRNA profiling from peripheral blood could thus be combined with other markers to improve the notoriously difficult but important screening for OvCA.

[1]  Artemis G. Hatzigeorgiou,et al.  Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer , 2008, Proceedings of the National Academy of Sciences.

[2]  S. Rafii,et al.  VEGFR1-positive haematopoietic bone marrow progenitors initiate the pre-metastatic niche , 2005, Nature.

[3]  D. Pectasides,et al.  Maintenance or Consolidation Therapy in Advanced Ovarian Cancer , 2007, Oncology.

[4]  Stijn van Dongen,et al.  miRBase: tools for microRNA genomics , 2007, Nucleic Acids Res..

[5]  Martin Vingron,et al.  Variance stabilization applied to microarray data calibration and to the quantification of differential expression , 2002, ISMB.

[6]  Hans-Peter Lenhof,et al.  Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing-Remitting Disease from Healthy Controls , 2009, PloS one.

[7]  H A Risch,et al.  The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions , 2008, British Journal of Cancer.

[8]  Yariv Yogev,et al.  Serum MicroRNAs Are Promising Novel Biomarkers , 2008, PloS one.

[9]  Y. Hochberg.  A sharper Bonferroni procedure for multiple tests of significance , 1988 .

[10]  Sandra B. Munro,et al.  Detection of Cancer with Serum miRNAs on an Oligonucleotide Microarray , 2009, PloS one.

[11]  S. Fegan.  Sensitivity and specificity of multimodal and ultrasound screening for ovarian cancer, and stage distribution of detected cancers: results of the prevalence screen of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) , 2009, Journal of Family Planning and Reproductive Health Care.

[12]  Chang-Zheng Chen,et al.  MicroRNAs as oncogenes and tumor suppressors. , 2005, The New England journal of medicine.

[13]  Yadong Wang,et al.  miR2Disease: a manually curated database for microRNA deregulation in human disease , 2008, Nucleic Acids Res..

[14]  S. Leung,et al.  Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies , 2008, PLoS medicine.

[15]  Huan Yang,et al.  MicroRNA expression profiling in human ovarian cancer: miR-214 induces cell survival and cisplatin resistance by targeting PTEN. , 2008, Cancer research.

[16]  X. Chen,et al.  Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases , 2008, Cell Research.

[17]  G. Bhagat,et al.  Overexpression of interleukin-1beta induces gastric inflammation and cancer and mobilizes myeloid-derived suppressor cells in mice. , 2008, Cancer cell.

[18]  George Coukos,et al.  Specific recruitment of regulatory T cells in ovarian carcinoma fosters immune privilege and predicts reduced survival , 2004, Nature Medicine.

[19]  D. Mutch.  Ovarian cancer: to screen or not to screen. , 2009, Obstetrics and gynecology.

[20]  Matthew Burnell,et al.  Sensitivity and specificity of multimodal and ultrasound screening for ovarian cancer, and stage distribution of detected cancers: results of the prevalence screen of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) , 2009, Journal of Family Planning and Reproductive Health Care.

[21]  C. Croce,et al.  MicroRNA signatures in human cancers , 2006, Nature Reviews Cancer.

[22]  D. Chan,et al.  Early Detection of Cancer: Immunoassays for Plasma Tumor Markers. , 2009, Expert opinion on medical diagnostics.

[23]  R. Bast,et al.  The CA 125 tumour-associated antigen: a review of the literature. , 1989, Human reproduction.

[24]  Steven J Skates,et al.  Calculation of the risk of ovarian cancer from serial CA-125 values for preclinical detection in postmenopausal women. , 2003, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[25]  Vladimir Naumovich Vapni.  The Nature of Statistical Learning Theory , 1995 .

[26]  J. Hopper,et al.  Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: a combined analysis of 22 studies. , 2003, American journal of human genetics.

[27]  Feng Bing,et al.  Identification of microRNA profiles in docetaxel-resistant human non-small cell lung carcinoma cells (SPC-A1) , 2009, Journal of cellular and molecular medicine.

[28]  L. Hartmann,et al.  Quantitation of circulating tumor cells in blood samples from ovarian and prostate cancer patients using tumor‐specific fluorescent ligands , 2008, International journal of cancer.

[29]  N V Belinskaia,et al.  [Early detection of ovarian cancer]. , 1978, Voprosy onkologii.

[30]  F. Wilcoxon.  Individual Comparisons by Ranking Methods , 1945 .

[31]  Eckart Meese,et al.  miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments , 2009, BMC Cancer.

[32]  Timothy R Church,et al.  Results From Four Rounds of Ovarian Cancer Screening in a Randomized Trial , 2009, Obstetrics and gynecology.

[33]  Sean R. Eddy,et al.  Rfam: annotating non-coding RNAs in complete genomes , 2004, Nucleic Acids Res..

[34]  Sonja Vorwerk,et al.  Microfluidic-based enzymatic on-chip labeling of miRNAs. , 2008, New biotechnology.

[35]  R. Aharonov,et al.  MicroRNAs accurately identify cancer tissue origin , 2008, Nature Biotechnology.

[36]  Y. Benjamini,et al.  Controlling the false discovery rate in behavior genetics research , 2001, Behavioural Brain Research.

[37]  Eckart Meese,et al.  High-throughput miRNA profiling of human melanoma blood samples , 2010, BMC Cancer.

[38]  D. Clarke‐Pearson,et al.  Screening for Ovarian Cancer , 2009 .

[39]  R. Bast,et al.  A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer. , 1983, The New England journal of medicine.

[40]  M. Duffy,et al.  CA125 in ovarian cancer: European Group on Tumor Markers guidelines for clinical use , 2004, International Journal of Gynecologic Cancer.

[41]  Q. Cui,et al.  An Analysis of Human MicroRNA and Disease Associations , 2008, PloS one.

[42]  Eckart Meese,et al.  A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumors , 2006, BMC Bioinformatics.

[43]  V. Bronte,et al.  Tumor‐induced tolerance and immune suppression by myeloid derived suppressor cells , 2008, Immunological reviews.

[44]  M. van Glabbeke,et al.  Predictors of response to subsequent chemotherapy in platinum pretreated ovarian cancer: a multivariate analysis of 704 patients [seecomments]. , 1997, Annals of oncology : official journal of the European Society for Medical Oncology.

[45]  V. Ambros,et al.  The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14 , 1993, Cell.

[46]  D. Vergara,et al.  An Outlook on Ovarian Cancer and Borderline Ovarian Tumors: Focus on Genomic and Proteomic Findings , 2009, Current genomics.