BackgroundCirculating nucleic acids (CNAs) offer unique opportunities for early diagnosis of clinical conditions. Here we show that microRNAs, a family of small non-coding regulatory RNAs involved in human development and pathology, are present in bodily fluids and represent new effective biomarkers.Methods and ResultsAfter developing protocols for extracting and quantifying microRNAs in serum and other body fluids, the serum microRNA profiles of several healthy individuals were determined and found to be similar, validating the robustness of our methods. To address the possibility that the abundance of specific microRNAs might change during physiological or pathological conditions, serum microRNA levels in pregnant and non pregnant women were compared. In sera from pregnant women, microRNAs associated with human placenta were significantly elevated and their levels correlated with pregnancy stage.Conclusions and SignificanceConsidering the central role of microRNAs in development and disease, our results highlight the medically relevant potential of determining microRNA levels in serum and other body fluids. Thus, microRNAs are a new class of CNAs that promise to serve as useful clinical biomarkers.
MicroRNAs (miRNAs) belong to a class of noncoding, regulatory RNAs that is involved in oncogenesis and shows remarkable tissue specificity. Their potential for tumor classification suggests they may be used in identifying the tissue in which cancers of unknown primary origin arose, a major clinical problem. We measured miRNA expression levels in 400 paraffin-embedded and fresh-frozen samples from 22 different tumor tissues and metastases. We used miRNA microarray data of 253 samples to construct a transparent classifier based on 48 miRNAs. Two-thirds of samples were classified with high confidence, with accuracy >90%. In an independent blinded test-set of 83 samples, overall high-confidence accuracy reached 89%. Classification accuracy reached 100% for most tissue classes, including 131 metastatic samples. We further validated the utility of the miRNA biomarkers by quantitative RT-PCR using 65 additional blinded test samples. Our findings demonstrate the effectiveness of miRNAs as biomarkers for tracing the tissue of origin of cancers of unknown primary origin.
Hsa-miR-205 is a highly accurate marker for lung cancer of squamous histology. The standardized diagnostic assay presented here can provide highly accurate subclassification of NSCLC patients.
AimsThe distinction between benign and malignant thyroid nodules has important therapeutic implications. Our objective was to develop an assay that could classify indeterminate thyroid nodules as benign or suspicious, using routinely prepared fine needle aspirate (FNA) cytology smears.MethodsA training set of 375 FNA smears was used to develop the microRNA-based assay, which was validated using a blinded, multicentre, retrospective cohort of 201 smears. Final diagnosis of the validation samples was determined based on corresponding surgical specimens, reviewed by the contributing institute pathologist and two independent pathologists. Validation samples were from adult patients (≥18 years) with nodule size >0.5 cm, and a final diagnosis confirmed by at least one of the two blinded, independent pathologists. The developed assay, RosettaGX Reveal, differentiates benign from malignant thyroid nodules, using quantitative RT-PCR.ResultsTest performance on the 189 samples that passed quality control: negative predictive value: 91% (95% CI 84% to 96%); sensitivity: 85% (CI 74% to 93%); specificity: 72% (CI 63% to 79%). Performance for cases in which all three reviewing pathologists were in agreement regarding the final diagnosis (n=150): negative predictive value: 99% (CI 94% to 100%); sensitivity: 98% (CI 87% to 100%); specificity: 78% (CI 69% to 85%).ConclusionsA novel assay utilising microRNA expression in cytology smears was developed. The assay distinguishes benign from malignant thyroid nodules using a single FNA stained smear, and does not require fresh tissue or special collection and shipment conditions. This assay offers a valuable tool for the preoperative classification of thyroid samples with indeterminate cytology.
Identification of the tissue of origin of a tumor is vital to its management. Previous studies showed tissuespecific expression patterns of microRNA and suggested that microRNA profiling would be useful in addressing this diagnostic challenge. MicroRNAs are well preserved in formalin-fixed, paraffin-embedded (FFPE) samples, further supporting this approach. To develop a standardized assay for identification of the tissue origin of FFPE tumor samples, we used microarray data from 504 tumor samples to select a shortlist of 104 microRNA biomarker candidates. These 104 microRNAs were profiled by proprietary quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) on 356 FFPE tumor samples. A total of 48 microRNAs were chosen from this list of candidates and used to train a classifier. We developed a clinical test for the identification of the tumor tissue of origin based on a standardized protocol and defined the classification criteria. The test measures expression levels of 48 microRNAs by qRT-PCR, and predicts the tissue of origin among 25 possible classes, corresponding to 17 distinct tissues and organs. The biologically motivated classifier combines the predictions generated by a binary decision tree and K-nearest neighbors (KNN). The classifier was validated on an independent, blinded set of 204 FFPE tumor samples, including nearly 100 metastatic tumor samples. The test predictions correctly identified the reference diagnosis in 85% of the cases. In 66% of the cases the two algorithm predictions (tree and KNN) agreed on a single-tissue origin, which was identical to the reference diagnosis in 90% of cases. Thus, a qRT-PCR test based on the expression profile of 48 tissue-specific microRNAs allows accurate identification of the tumor tissue of origin.
The definitive identification of malignant pleural mesothelioma (MPM) has significant clinical implications, yet other malignancies often involve the lung pleura, confounding the diagnosis of MPM. In the absence of accurate markers, MPM can be difficult to distinguish from peripheral lung adenocarcinoma and metastatic epithelial cancers. MicroRNA expression is tissue-specific and highly informative for identifying tumor origin. We identified microRNA biomarkers for the differential diagnosis of MPM and developed a standardized microRNA-based assay. Formalin-fixed, paraffin-embedded samples of 33 MPM and 210 carcinomas were used for assay development. Using microarrays, we identified microRNAs differentially expressed between MPM and various carcinomas. Hsa-miR-193-3p was overexpressed in MPM, while hsa-miR-200c and hsamiR-192 were overexpressed in peripheral lung adenocarcinoma and carcinomas that frequently metastasize to lung pleura. We developed a standardized diagnostic assay based on the expression of these microRNAs. The assay reached a sensitivity of 100% and a specificity of 94% in a blinded validation set of 68 samples from the lung and pleura. This diagnostic assay can provide a useful tool in the differential diagnosis of MPM from other malignancies in the pleura.
MicroRNAs (miRs) play a central role in regulating gene expression and are strongly associated with cancer development. This study sought to determine if adrenocortical carcinomas can be differentiated from adenomas by their miR profiles and to correlate the findings with the histologic Weiss system for identifying malignancy in adrenocortical tumors (ACTs). Forty-six primary and 2 recurrent ACTs retrieved from the files of the pathology department of a tertiary medical center were evaluated blindly for the Weiss criteria. High-quality RNA was extracted, and miR expression was evaluated with microarrays and quantitative reverse-transcriptase polymerase chain reaction. The Weiss system defined 17 tumors as carcinomas and 29 as adenomas. On microarray analysis, over a dozen miRs were upregulated or downregulated in carcinomas compared with adenomas. Upregulation of miR-503 was the best single discriminator of malignancy. The combination of miR-34a and miR-497 underexpression discriminated carcinomas from adenomas with 100% sensitivity and 96% specificity. Statistical analysis revealed a high level of correspondence between the Weiss system and miR expression. In conclusion, miR expression can accurately identify malignant ACTs with equal efficiency to the Weiss system. miR analysis may have added value in tumors with borderline features that are difficult to interpret histopathologically.
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