Xi Chen

BACKGROUND: Detection of pancreatic cancer (PaC), particularly at early stages, remains a great challenge owing to lack of specific biomarkers. We sought to identify a PaC-specific serum microRNA (miRNA) expression profile and test its specificity and sensitivity as a biomarker in the diagnosis and prognosis of PaC. METHODS: We obtained serum samples from 197 PaC cases and 158 age- and sex-matched cancer-free controls. We screened the differentially expressed serum miRNAs with Illumina sequencing by synthesis technology using pooled serum samples followed by RT-qPCR validation of a large number of samples arranged in multiple stages. We used risk score analysis to evaluate the diagnostic value of the serum miRNA profiling system. To assess the serum miRNA-based biomarker accuracy in predicting PaC, we performed additional double-blind testing in 77 PaC cases and 52 controls and diagnostic classification in 55 cases with clinically suspected PaC. RESULTS: After the selection and validation process, 7 miRNAs displayed significantly different expression levels in PaC compared with controls. This 7 miRNA-based biomarker had high sensitivity and specificity for distinguishing various stages of PaC from cancer-free controls and also accurately discriminated PaC patients from chronic pancreatitis (CP) patients. Among the 7 miRNAs, miR-21 levels in serum were significantly associated with overall PaC survival. The diagnostic accuracy rate of the 7-miRNA profile was 83.6% in correctly classifying 55 cases with clinically suspected PaC. CONCLUSIONS: These data demonstrate that the 7 miRNA-based biomarker can serve as a novel noninvasive approach for PaC diagnosis and prognosis.

It has been demonstrated that there are abundant stable microRNAs (miRNAs) in plasma/serum, which can be detected and are potentially disease specific. However, the lack of suitable endogenous controls for serum miRNA detection is the restriction for the widely usage of this kind of biomarkers and for the between-laboratory comparison of the findings. We first systematically screened for endogenous control miRNAs (ECMs) by testing 10 pooling samples (using both Solexa sequencing and TaqMan low density array) and 50 individual samples (using quantitative reverse transcription-PCR) of different cancer traits and healthy controls. Then we assessed serum miRNAs used as potential biomarkers for breast cancer risk prediction based on a two-stage case-control analysis, including 48 breast cancer patients and 48 controls for the discovery stage and 76 breast cancer patients and 76 controls for validation. We identified two candidate ECMs (miRNA-191 and miRNA-484). Normalized by the two ECMs, we found four miRNAs (miR-16, miR-25, miR-222 and miR-324-3p) that were consistently differentially expressed between breast cancer cases and controls. The area under the receiver operating characteristic curve is 0.954 for the four-miRNA signature in the discovery stage (sensitivity = 0.917 and specificity = 0.896) and 0.928 in the validation stage (sensitivity = 0.921 and specificity = 0.934). In conclusion, the four-miRNA signature from serum may serve as a non-invasive prediction biomarker for breast cancer. Furthermore, we proposed the combination of miRNA-484 and miRNA-191 as endogenous control for serum miRNA detection, at least for most common cancers.

Alzheimer's disease (AD) is the most common type of dementia, and promptly diagnosis of AD is crucial for delaying the development of disease and improving patient quality of life. However, AD detection, particularly in the early stages, remains a substantial challenge due to the lack of specific biomarkers. The present study was undertaken to identify and validate the potential of circulating miRNAs as novel biomarkers for AD. Solexa sequencing was employed to screen the expression profile of serum miRNAs in AD and controls. RT-qPCR was used to confirm the altered miRNAs at the individual level. Moreover, candidate miRNAs were examined in the serum samples of patients with mild cognitive impairment (MCI) and vascular dementia (VD). The results showed that four miRNAs (miR-31, miR-93, miR-143, and miR-146a) were markedly decreased in AD patients' serum compared with controls. Receiver operating characteristic curve analysis demonstrated that this panel of four miRNAs could be used as potential biomarker for AD. Furthermore, miR-93, and miR-146a were significantly elevated in MCI compared with controls, and the panel of miR-31, miR-93 and miR-146a can be used to discriminate AD from VD. We established a panel of four serum miRNAs as a novel noninvasive biomarker for AD diagnosis.