Five-year survival rates of ovarian cancer will be over 90%, if the cancer is found at an early localized stage. However, from the American Cancer Society’s data, only 20% of ovarian cancers are early diagnosed because there are often no obvious symptoms, until the disease has spread. Therefore, ovarian cancer is still the leading cause of death among gynecological cancers. Identification of novel biomarkers for early diagnosis could significantly improve clinical outcomes of ovarian cancer.

Recent studies have suggested that blood micro RNAs might serve as novel noninvasive biomarkers for ovarian cancer diagnosis. Blood samples are more easily accessible than solid organs, such as ovaries [1]. MicroRNA is a class of small (about 22 nucleotide long) noncoding RNAs. These small molecules negatively regulate the translation of messenger RNAs (mRNA) to target proteins by base pairing. Aberrant microRNA expressions were observed in many cancer types, including ovarian cancer, suggesting micro RNAs could be involved in the pathogenesis of cancer. Rosenfeld et al. [2] demonstrated that cancer-related micro RNAs is tissue-specific, which could identify the origin of cancer. Another important feature of micro RNAs is their biological stability [3]. Micro RNAs are still stable, even in formalinfixed, paraffin-embedded (FFPE) tissue samples. These features make blood micro RNAs particularly attractive as biomarkers for cancer diagnosis.

Recent advances in whole-genome RNA profiling techniques, such as expression microarray enable us to comprehensibly detect expression levels of micro RNAs on a genome-wide scale. A variety of blood micro RNAs differentially expressed in one specific types of cancer patients have been identified. The human disease miRNome project [4,5] (http://genetrail.bioinf.uni-sb.de/wholemirnomeproject/) is a good example. Häusler et al. [5] applied the microarray technique to determine microRNA expression levels in blood cells from 24 ovarian cancer patients and 15 healthy controls. 147 significantly differentially expressed micro RNAs were identified using the unpaired t-test at P

Human serum also contains a large amount of stable micro RNAs [6]. Some studies were performed to test whether the microRNAs directly from serum could have potential to diagnose ovarian cancer. Lodes et al. [7] analyzed genome-wide serum microRNA expression profiles of ovarian, prostate, colon, breast and lung cancer patients, and healthy controls using oligo nucleotide microarrays. It was shown that one milliliter of human serum was enough for microRNA expression level detection, without the PCR amplification. Hierarchical clustering of serum microRNA expression pattern could well separate cancer patients from normal controls. In another example, Resnick et al. [8] applied the TaqMan Array Human MicroRNA Panel, a type of realtime PCR-based microarray, to detect the expression levels of serum micro RNA from 28 ovarian cancer patients and 15 healthy controls. Statistical analysis and RT-PCR validations showed that eight micro RNAs were significantly differentially expressed between patients and healthy controls. Five micro RNAs, mir-21, 29a, 92, 93 and 126 were up-regulated and three micro RNAs, mir-99b, 155 and 127 were downregulated in cancer patients, compared to controls. Most of these eight micro RNAs have been proved to be oncomirs, micro RNAs with a role in cancer. The two projects showed that biologically meaningful microRNA expression patterns existed in the serum from ovarian cancer patients.

Conclusions and Prospective

There is an increasing interest to develop novel blood micro RNA biomarkers for the noninvasive ovarian cancer diagnosis at the early stage. Many micro RNAs from blood cells or serum were shown to be associated with ovarian cancer, and these molecules could be molecular finger prints for cancer diagnosis. These results will be validated by larger patient cohort studies in the future. Positive data will pave the way for new ovarian cancer detection kits in clinical practice. On the other hand, the investigations of micro RNAs and their target genes might significantly enhance our understanding of the molecular mechanism of ovarian cancer, and identify new therapeutic strategies against the disease.