Ying Wu

Fudan University, Shanghai, Shanghai Shi, China

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Publications (8)61.29 Total impact

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    ABSTRACT: Circulating microRNAs are promising biomarkers for non-invasive testing and dynamic monitoring in cancer patients. However, no consensus exists regarding the normalization of circulating microRNAs in the quantification, making the results incomparable. We investigated global circulating microRNA profiles to identify a stable endogenous control for quantifying circulating microRNAs using 3 cohorts (n=544), including 168 control individuals (healthy subjects and those with chronic hepatitis B and cirrhosis) and 376 cancer patients (hepatocellular, colorectal, lung, esophageal, gastric, renal, prostate, and breast cancer patients). GeNorm, NormFinder, and coefficient of variability (CV) were used to select the most stable endogenous control, whereas Ingenuity Pathway Analysis (IPA) was adopted to explore its signaling pathways. Seven candidates (miR-1225-3p, miR-1228, miR-30d, miR-939, miR-940, miR-188-5p, and miR-134) from microarray analysis and 4 commonly used controls (miR-16, miR-223, let-7a, and RNU6B) from literature were subjected to real-time quantitative reverse transcription-polymerase chain reaction validation using independent cohorts. MiR-1228 (CV=5.4%) with minimum M value and S value presented as the most stable endogenous control across 8 cancer types and 3 controls. IPA showed miR-1228 to be involved extensively in metabolism-related signal pathways and organ morphology, implying that miR-1228 functions as a housekeeping gene. Functional network analysis found that "hematological system development" was on the list of the top networks that associate with miR-1228, implying that miR-1228 plays an important role in the hematological system. The results explained the steady expression of miR-1228 in the blood. In conclusion, miR-1228 is a promising stable endogenous control for quantifying circulating microRNAs in cancer patients. © 2014 Wiley Periodicals, Inc.
    International Journal of Cancer 02/2014; · 6.20 Impact Factor
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    ABSTRACT: Lung cancers are classified as squamous cell carcinoma (SQ), adenocarcinoma (AC) and small cell lung carcinoma (SCLC). SQ is the major subtype of lung cancer. Currently, there are no targeted therapies for SQ due to lack of understanding its driving oncogenes. In this study, we validated an SQ specific biomarker hsa-miR-205 in Chinese patients with lung cancer and screened its candidate target genes for further functional studies to enrich knowledge in SQ target therapies. Quantitative reverse-transcription PCR (quantitative RT-PCR) was performed on 197 macro-dissected (cancerous cells >75%) surgical lung tissues (45 SQ, 44 AC, 54 SCLC and 54 adjacent normal tissues) to validate the expression profiles of miR-205. Furthermore, the targets of this microRNA were predicted through the gateway miRecords and mapped to lung cancer-associated pathways using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. Then quantitative RT-PCR was performed on an independent cohort of 44 snap-frozen surgical lung tissues to concurrently assess the expression profiles of miR-205 and its 52 putative targeted genes. MicroRNA-205 yielded high diagnostic accuracy in discriminating SQ from AC with an area under the curve (AUC) of 0.985, and discriminating SQ from SCLC with an AUC of 0.978 in formalin-fixed paraffin-embedded (FFPE) surgical lung tissues. Predicted targets of miR-205 were associated with 52 key members of lung cancer signaling pathways. Ten target genes (ACSL1, AXIN2, CACNA2D2, FOXO3, PPP1R3A, PRKAG3, RUNX1, SMAD4, STK3 and TBL1XR1) were significantly down-regulated in SQ and had a strong negative correlation with miR-205, while one target gene (CDH3) was up-regulated in SQ and exhibited a strong positive correlation with miR-205. We confirmed the high diagnostic accuracy of miR-205 in discriminating SQ from AC and SCLC in Chinese patients. Moreover, we identified 11 significant target genes of miR-205 which could be used for further functional studies as the basis for the development of SQ targeted therapies.
    Chinese medical journal 01/2014; 127(2):272-8. · 0.90 Impact Factor
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    ABSTRACT: BACKGROUND: Acute rejection (AR) of an organ transplant is a life-threatening complication. Currently, there are few diagnostic biomarkers suitable for clinical application. We aim to determine the potential of plasma microRNAs as biomarkers for AR. METHODS: Using rat orthotopic liver transplantation model and microarrays, we compared the difference in the spectrum and levels of microRNAs in both plasma and grafts between AR rats and control. AR-related plasma microRNAs were selected and validated using real-time quantification polymerase chain reaction. Plasma from AR rats with or without tacrolimus treatment was used for microRNA dynamic monitoring. To clarify the origin of AR-related plasma microRNAs, drug-induced liver damage rat model were performed and in situ hybridization was used to detect and localize the specific microRNA in allografts. RESULTS: We found that plasma miR-122, miR-192, and miR-146a was significantly up-regulated when AR occur (fold change>2; P<0.05) and the elevation could be repressed by immunosuppression. In liver injury rat model, up-regulated plasma miR-122 (fold change=22.126; P=0.002) and miR-192 (fold change=8.833; P<0.001) rather than miR-146a (fold change=1.181; P=0.594) were observed. Further study demonstrated that miR-146a was up-regulated by sixfold in microvesicles isolated from AR plasma, whereas miR-122 and miR-192 showed no distinct change. In situ hybridization revealed that the portal areas of the AR graft were brimming with lymphocytes, which showed highly intense staining for miR-146a. CONCLUSIONS: Our study provides the global fingerprint of plasma microRNAs in AR rats and suggests that plasma miR-122 and miR-192 reflect liver injury, whereas miR-146a may associate with cellular rejection.
    Transplantation 03/2013; · 3.78 Impact Factor
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    ABSTRACT: Colonoscopy remains the standard screening method for detecting colorectal cancer (CRC) at an early stage. However, many people avoid having a colonoscopy because of the fear for its potential complications. Our study aimed to identify plasma microRNAs for preliminarily screening CRC in general population, so that some unnecessary colonoscopies can be avoided. We investigated plasma microRNA expression in 3 independent cohorts including the discovery (n=80), training (n=112) and validation (n=49) phases recruited at 2 medical centers. Microarrays were used for screening 723 microRNAs in 80 plasma samples to identify candidate microRNAs. Quantitative reverse-transcriptase PCR was performed on the 161 training and validation plasma samples to evaluate the candidate microRNAs discovered from microarrays. A logistic regression model was constructed based on the training cohort and then verified by using the validation dataset. Area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic accuracy. We identified a panel of miR-409-3p, miR-7 and miR-93 that yielded high diagnostic accuracy in discriminating CRC from healthy group (AUC 0.866 and 0.897 for training and validation dataset, respectively). Moreover, the diagnostic performance of the microRNA panel persisted in non-metastasis CRC stages (Dukes' A-B, AUC 0.809 and 0.892 for training and validation dataset, respectively) and in metastasis CRC stages (Dukes' C-D, AUC 0.917 and 0.865 for training and validation dataset, respectively). In conclusion, our study reveals a plasma microRNA panel that has potential clinical value in early CRC detection and would play a critical role on preliminarily screening CRC in general population. © 2013 Wiley Periodicals, Inc.
    International Journal of Cancer 03/2013; · 6.20 Impact Factor
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    ABSTRACT: RATIONALE: Effective treatment for lung cancer requires accuracy in sub-classification of carcinoma subtypes. OBJECTIVES: To identify microRNAs in bronchial brushing specimens for discriminating small cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC) and for further differentiating squamous cell carcinoma (SQ) from adenocarcinoma (AC). METHODS: Microarrays were used to screen 723 microRNAs in laser-captured, microdissected cancer cells from 82 snap-frozen surgical lung specimens. Quantitative reverse-transcriptase PCR was performed on 153 macrodissected formalin-fixed, paraffin-embedded (FFPE) surgical lung specimens to evaluate 7 microRNA candidates discovered from microarrays. Two microRNA panels were constructed based on a training cohort (n = 85) and validated using an independent cohort (n = 68). The microRNA panels were applied as differentiators of SCLC from NSCLC and SQ from AC in 207 bronchial brushing specimens. MEASUREMENTS AND MAIN RESULTS: Two microRNA panels yielded high diagnostic accuracy in discriminating SCLC from NSCLC (miR-29a and miR-375, AUC 0.991 and 0.982 for training and validation dataset, respectively) and in differentiating SQ from AC (miR-205 and miR-34a, AUC 0.977 and 0.982 for training and validation dataset, respectively) in FFPE surgical lung specimens. Moreover, the microRNA panels accurately differentiated SCLC from NSCLC (AUC 0.947) and SQ from AC (AUC 0.962) in bronchial brushing specimens. CONCLUSION: We found 2 microRNA panels that accurately discriminated between the 3 subtypes of lung carcinoma in bronchial brushing specimens. The identified microRNA panels may have considerable clinical value in differential diagnosis and optimizing treatment strategies based on lung cancer subtypes.
    American Journal of Respiratory and Critical Care Medicine 10/2012; · 11.04 Impact Factor
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    ABSTRACT: OBJECTIVE: It is a challenge to differentiate invasive carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissues. In this study, microRNA profiles were evaluated in the transformation of colorectal carcinogenesis to discover new molecular markers for identifying a carcinoma in colonoscopy biopsy tissues where the presence of stromal invasion cells is not detectable by microscopic analysis. METHODS: The expression of 723 human microRNAs was measured in laser capture microdissected epithelial tumours from 133 snap-frozen surgical colorectal specimens. Three well-known classification algorithms were used to derive candidate biomarkers for discriminating carcinomas from adenomas. Quantitative reverse-transcriptase PCR was then used to validate the candidates in an independent cohort of macrodissected formalin-fixed paraffin-embedded colorectal tissue samples from 91 surgical resections. The biomarkers were applied to differentiate carcinomas from high-grade intraepithelial neoplasms in 58 colonoscopy biopsy tissue samples with stromal invasion cells undetectable by microscopy. RESULTS: One classifier of 14 microRNAs was identified with a prediction accuracy of 94.1% for discriminating carcinomas from adenomas. In formalin-fixed paraffin-embedded surgical tissue samples, a combination of miR-375, miR-424 and miR-92a yielded an accuracy of 94% (AUC=0.968) in discriminating carcinomas from adenomas. This combination has been applied to differentiate carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissues with an accuracy of 89% (AUC=0.918). CONCLUSIONS: This study has found a microRNA panel that accurately discriminates carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissues. This microRNA panel has considerable clinical value in the early diagnosis and optimal surgical decision-making of colorectal cancer.
    Gut 04/2012; · 10.73 Impact Factor
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    ABSTRACT: More than 60% of patients with hepatocellular carcinoma (HCC) do not receive curative therapy as a result of late clinical presentation and diagnosis. We aimed to identify plasma microRNAs for diagnosing hepatitis B virus (HBV) -related HCC. Plasma microRNA expression was investigated with three independent cohorts including 934 participants (healthy, chronic hepatitis B, cirrhosis, and HBV-related HCC), recruited between August 2008 and June 2010. First, we used microarray to screen 723 microRNAs in 137 plasma samples for diagnosing HCC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n = 407) and then validated using an independent cohort (n = 390). Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. We identified a microRNA panel (miR-122, miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801) that provided a high diagnostic accuracy of HCC (AUC = 0.864 and 0.888 for training and validation data set, respectively). The satisfactory diagnostic performance of the microRNA panel persisted regardless of disease status (AUCs for Barcelona Clinic Liver Cancer stages 0, A, B, and C were 0.888, 0.888, 0.901, and 0.881, respectively). The microRNA panel can also differentiate HCC from healthy (AUC = 0.941), chronic hepatitis B (AUC = 0.842), and cirrhosis (AUC = 0.884), respectively. We found a plasma microRNA panel that has considerable clinical value in diagnosing early-stage HCC. Thus, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy.
    Journal of Clinical Oncology 11/2011; 29(36):4781-8. · 18.04 Impact Factor
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    ABSTRACT: Laser capture microdissection (LCM) has successfully isolated pure cell populations from tissue sections and the combination of LCM with standard genomic and proteomic methods has revolutionized molecular analysis of complex tissue. However, the quantity and quality of material recovered after LCM is often still limited for analysis by using whole genomic and proteomic approaches. To procure high quality and quantity of RNA after LCM, we optimized the procedures on tissue preparations and applied the approach for cell type-specific miRNA expression profiling in colorectal tumors. We found that the ethanol fixation of tissue sections for 2 hours had the maximum improvement of RNA quality (1.8 fold, p = 0.0014) and quantity (1.5 fold, p = 0.066). Overall, the quality (RNA integrity number, RIN) for the microdissected colorectal tissues was 5.2 +/- 1.5 (average +/- SD) for normal (n = 43), 5.7 +/- 1.1 for adenomas (n = 14) and 7.2 +/- 1.2 for carcinomas (n = 44). We then compared miRNA expression profiles of 18 colorectal tissues (6 normal, 6 adenomas and 6 carcinomas) between LCM selected epithelial cells versus stromal cells using Agilent miRNA microarrays. We identified 51 differentially expressed miRNAs (p <= 0.001) between these two cell types. We found that the miRNAs in the epithelial cells could differentiate adenomas from normal and carcinomas. However, the miRNAs in the stromal and mixed cells could not separate adenomas from normal tissues. Finally, we applied quantitative RT-PCR to cross-verify the expression patterns of 7 different miRNAs using 8 LCM-selected epithelial cells and found the excellent correlation of the fold changes between the two platforms (R = 0.996). Our study demonstrates the feasibility and potential power of discovering cell type-specific miRNA biomarkers in complex tissue using combination of LCM with genome-wide miRNA analysis.
    BMC Genomics 03/2010; 11:163. · 4.40 Impact Factor