| Background&Purpose:Esophageal cancer (EC) is the eighth most common cancer and6th leading cause of cancer mortality globally. An estimated482,300new EC cases and406,800deaths occurred in2008worldwide. Incidence rates vary internationally by nearly16-fold, with the highest rates in Southern and Eastern Africa and Eastern Asia and the lowest in Western and Middle Africa and Central America in both males and females. EC is3to4times more common among males than females. Its incidence has increased rapidly in Western countries during the past half century. The Chaoshan area of Guangdong Province in China has a high incidence of EC (>100/100,000)[4]. The death toll caused by EC in China accounts for more than70%of all EC deaths worldwide.The overall survival rate remains low; only3-10%of diagnosed patients survive for5years. In contrast, the survival rate increases to90%in patients diagnosed with Stage I disease (T1N0M0) who undergo surgical resection. Therefore, early diagnosis and treatment are vital. At present, the clinical diagnosis mainly depends on radiology and endoscopic biopsy. However, these tests are expensive, invasive, or cause discomfort to patients, and most patients are in a late stage of the disease when accurate diagnosis is attained. Therefore, it is necessary to identify a biomarker of early-stage EC.Several studies have demonstrated that aberrant expression of miRNAs is closely related to the pathogenesis and development of cancer, and miRNAs possess discriminatory power as cancer biomarkers. Several studies have reported that miRNAs are aberrantly expressed in cancer tissue and plasma in patients with EC. However, miRNA expression in the saliva of patients with EC has not yet been reported. Due to the extensive blood supply in salivary glands, saliva is considered to be a terminal product of blood circulation, and molecules that are present in plasma are also present in saliva. Hence, saliva is believed to mirror systemic health and reflect conditions such as cancers, infectious diseases, cardiovascular diseases, etc.. Tissue, plasma, and saliva miRNAs share similar expression profiles. This study comprised two phases:the discovery and validation phases. In the discovery phase, six miRNAs that were dysregulated most significantly in whole saliva of patients with EC by Agilent microarray analysis were selected as targets. In the validation phase, the expression levels of the six target miRNAs were validated by RT-qPCR using both whole saliva and saliva supernatant samples.Method:1. Sample size estimationIn the discovery phase, according to the Agilent microarray results, the sensitivity of miR-144for EC was85.7%. The formula for sample size estimation was as follows: n=uα/2P (1-P)/δ2In this formula, n is the number needed, uα/2is the test level, a is the cutoff value of two-tailed normal distribution, P is the expected value of sensitivity, and8is the permissible error.According to the ability to attain the sample size for our study, we chose the values a=0.05(uα/2=1.96), δ=0.11, and the values were substituted into the formula. The result was n=1.962×0.857×(1-0.857)/0.152≈38.9=39. That is, in the validation phase of this study, the minimum number of cases needed for the EC group was39, and39cases were chosen. According to the ability to attain the sample size for our study, we assumed the ratio of cases in the EC group to that in the healthy group to be2:1.19cases in healthy group were chosen. 2.Subject selection46whole saliva and46saliva supernatant samples from46patients with EC and22whole saliva and22saliva supernatant samples from age-, gender-, and ethnically-matched healthy individuals were obtained from Guangdong General Hospital between July,2011and January,2012. Patient histopathology results were confirmed by endoscopic biopsy, and the EC patients had no concomitant organic, systemic, or oral diseases, such as hepatitis, diabetes mellitus, etc, that could influence EC marker expression levels. Cancer staging was based on the UICC/TMN staging system. Stages I, II, and III were based on the histopathology results after surgical resection. Stage IV was based on histopathology results of puncture biopsy of metastatic nodes or PET-CT results. This study was approved by the Institutional Review Board and Ethics Committee at Guangdong General Hospital. All participants were provided written consent for their information to be stored in the hospital database and used for research.3.Saliva collectionSubjects were asked to refrain from eating, drinking, smoking, and oral hygiene procedures for at least2hours before the collection. To stimulate glandular salivary flow, subjects received a2%citric acid solution for application to the bilateral posterior lateral surfaces of the tongue with a cotton swab for5s every30s. The citric acid stimulation continued at30-second intervals during the entire collection procedure. Up to5mL of saliva from each subject was collected in a50-mL centrifuge tube. A total of2mL of saliva was removed from the tube as a whole saliva sample. The remaining3mL of saliva samples was centrifuged to spin down exfoliated cells, and the supernatant was transferred into microcentrifuge tubes followed by a second centrifugation to completely remove cellular components as saliva supernatant samples. Samples were stored at-80℃until use. The procedure mentioned above must be finished within2h. 4.Agilent microarray in discovery phaseBecause this is the first research on salivary microRNAs for the detection of EC in the world, we just chose10cases to perform microarray. Seven whole saliva samples from the EC group and3from the healthy group were selected randomly. The pathology of all seven patients with EC was squamous cell carcinoma; one was stage Ⅰ, one stage Ⅱ,3stage Ⅲ, and two stage IV. A total of923mature miRNA sequences were assembled and integrated into our miRNA microarray design. Raw data were normalized by Quantile algorithm, Gene Spring Software11.0(Agilent technologies, Santa Clara, CA, US).6miRNAs were selected as targets, and their expression levels were validated by RT-qPCR in the validation phase. The selection method was as follows:the gTotalGeneSignal value in the Agilent microarray amounted to the expression level of each miRNA. Therefore, for identical miRNAs, bar charts were drawn according to the gTotalGeneSignal value of each miRNA. We selected five miRNAs:miR-144, miR-lOb*, miR-451, miR-486-5p, and miR-634, the values of which tended to be much higher or lower in the EC group than in the healthy group and which also are closely associated with development of deseases. Meanwhile, several studies have reported that miR-21is aberrantly expressed in cancer tissue and plasma from patients with EC. The gTotalGeneSignal value of miR-21did not show this tendency, but was also selected as a target.5. Validation phaseThe expression levels of the6selected miRNAs were validated by RT-qPCR using both the58whole saliva samples and the58saliva supernatant samples from39patients with EC and19healthy controls. The mirVana PARIS Kit (Ambion, USA)was used to isolate total RNA from1mL of whole saliva or saliva supernatant, according to the manufacturer’s protocol. Finally, RNA was eluted in30μL of preheated nuclease-free water (95℃) and stored at-80℃until use. After the reverse transcription reaction, quantitative PCR was run on a Biorad CFX962.1(Biorad Biosystems). At the end of the PCR cycles, melting curve analysis was performed to validate generation of the expected PCR product. Each sample was analyzed in triplicate. All Ct values were<36. The expression levels of each target miRNA were normalized to that of miR-16. All expression levels were calculated utilizing the2-ΔΔCt method. Briefly:samplei ΔCt target miR=sample’Ct target miR-sampleiCtmiR-16; sample1ΔΔCt target miR=sample1Ct target miR-the mean value of ΔCt target miR of the healthy group.6.Statistical analysisExpression levels of miRNAs and ages were compared using the Mann-Whitney U test or the Kruskall-Wallis H test. Genders were compared using the X2test. A multivariate logistic regression model was established for the4risk factors:smoking, alcohol intake, drinking or eating at hot temperatures, and Chaoshanese nationality. The odds ratios (ORs) of the4risk factors were calculated by forward LR. Each OR was compared using the X2test. Receiver-operating characteristics (ROC) curves were used to evaluate the discriminatory power of each miRNA for differentiation of patients and controls. The correlation of each miRNA expression level between whole saliva and saliva supernatant was analyzed by Spearman’s correlation test. The differences in the discriminatory powers of target miRNAs were compared with the method of Delong using the MedCalc12.2.1software. Other statistical analyses were performed with the SPSS software, version13.0(SPSS, Inc., Chicago, IL). A value of<0.05was considered to indicate statistical significance.Results:1. Whole saliva profileTen whole saliva samples (7from patients with EC and3from healthy controls) were evaluated by Agilent microarray. A total of923mature miRNA sequences were assembled and integrated into our miRNA microarray design. A total of461miRNAs were detected in whole saliva (the probe signal value of these miRNAs was present in at least one sample). Of these461miRNAs,452were detected in EC samples and391in healthy control samples. A total of232miRNAs were detected in all10samples. A total of261miRNAs were detected in all7EC samples, and243miRNAs in all3 control samples. Twenty-five miRNAs showed significant differences in expression between the EC group and the healthy group.6miRNAs (miR-144, miR-10b*, miR-21, miR-451, miR-486-5p, and miR-634) were subjected to validation of their expression levels by RT-qPCR.2.Diagnostic value of whole saliva and saliva supernatant miRNAs for ECSix miRNAs (miR-10b*, miR-144, miR-21, miR-451, miR-486-5p, and miR-634) were identified as targets by Agilent microarray. After validation by RT-qPCR, miR-10b*, miR-144, and miR-451in whole saliva and miR-10b*, miR-144, miR-21, and miR-451in saliva supernatant were significantly upregulated in patients, with sensitivities of89.7,92.3,84.6,79.5,43.6,89.7, and51.3%and specificities of57.9,47.4,57.9%,57.9,89.5,47.4, and84.2%, respectively.3.Comparison of AUCsTo accurately compare different AUCs, we used the method of Delong with the MedCalc software, version12.2.1.3whole saliva and4saliva supernatant miRNAs were able to detect EC. miR-10b*, miR-144, and miR-451could detect EC using both whole saliva and saliva supernatant. The AUCs indicated no significant differences among whole saliva miR-10b*and saliva supernatant miR-10b*, whole saliva miR-144and saliva supernatant miR-144, and whole saliva miR-451and saliva supernatant miR-451(p=0.3413,0.7050, and0.6867, respectively). The discriminatory powers of the same miRNAs in whole saliva and saliva supernatant were not significantly different. Furthermore, the AUCs of the3whole saliva miRNAs (miR-10b*, miR-144, and miR-451) that could detect EC were compared between two miRNAs. The results also showed no significant differences [p=0.2356(miR-lOb*vs. miR-144),0.8959(miR-lOb*vs. miR-451), and0.3248(miR-144vs. miR-451)]. Finally, the AUCs of the4saliva supernatant miRNAs (miR-10b*, miR-144, miR-21, and miR-451) that could detect EC were compared between two miRNAs. The results also showed no significant differences\p=0.8251(miR-lOb*vs. miR-21),0.7699(miR-10b*vs. miR-451),0.7102(miR-10b*vs. miR-144),0.6079(miR-21vs. miR-451),0.8729(miR-21vs. miR-144), and0.3529(miR-144vs miR-451)]. In conclusion, the discriminatory powers of all miRNAs in both whole saliva and saliva supernatant were similar.4.Correlation between whole saliva and saliva supernatant expression levelsWhole saliva and saliva supernatant samples were collected from each subject. According to the above results, miR-10b*, miR-144, and miR-451were significantly upregulated in both whole saliva and saliva supernatant in the EC group. Spearman’s correlation test was used to evaluate correlations of the expression levels of these3miRNAs between whole saliva and saliva supernatant. The expression levels of these3miRNAs in whole saliva and saliva supernatant showed significant correlations[p=0.000(miR-10b*),0.035(miR-144), and0.003(miR-451)].Conclusions:We found distinctive miRNAs for esophageal cancer in both whole saliva and saliva supernatant. These miRNAs possess discriminatory power for detection of esophageal cancer. Because saliva collection is noninvasive and convenient, salivary miRNAs show great promise as biomarkers for detection of esophageal cancer in areas at high risk. |
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