Danit Lebanony

Serum MicroRNAs Are Promising Novel Biomarkers

Background Circulating 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 Results After 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 Significance Considering 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 accurately identify cancer tissue origin

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.

Diagnostic Assay Based on hsa-miR-205 Expression Distinguishes Squamous From Nonsquamous Non–Small-Cell Lung Carcinoma

PURPOSE Recent advances in treatment of lung cancer require greater accuracy in the subclassification of non-small-cell lung cancer (NSCLC). Targeted therapies which inhibit tumor angiogenesis pose higher risk for adverse response in cases of squamous cell carcinoma. Interobserver variability and the lack of specific, standardized assays limit the current abilities to adequately stratify patients for such treatments. In this study, we set out to identify specific microRNA biomarkers for the identification of squamous cell carcinoma, and to use such markers for the development of a standardized assay. PATIENTS AND METHODS High-throughput microarray was used to measure microRNA expression levels in 122 adenocarcinoma and squamous NSCLC samples. A quantitative real-time polymerase chain reaction (qRT-PCR) platform was used to verify findings in an independent set of 20 NSCLC formalin-fixed, paraffin-embedded (FFPE) samples, and to develop a diagnostic assay using an additional set of 27 NSCLC FFPE samples. The assay was validated using an independent blinded cohort consisting of 79 NSCLC FFPE samples. RESULTS We identified hsa-miR-205 as a highly specific marker for squamous cell lung carcinoma. A microRNA-based qRT-PCR assay that measures expression of hsa-miR-205 reached sensitivity of 96% and specificity of 90% in the identification of squamous cell lung carcinomas in an independent blinded validation set. CONCLUSION 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.

Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

Identification of the tissue of origin of a tumor is vital to its management. Previous studies showed tissue-specific 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.

A Diagnostic Assay Based on MicroRNA Expression Accurately Identifies Malignant Pleural Mesothelioma

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 hsa-miR-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.

Differential diagnosis of hepatocellular carcinoma from metastatic tumors in the liver using microRNA expression

Distinguishing hepatocellular carcinoma from metastatic tumors in the liver is of great practical importance, with significant therapeutic and prognostic implications. This differential diagnosis can be difficult because metastatic cancers in the liver, especially adenocarcinomas, may mimic the morphology and immunoexpression of hepatocellular carcinoma. Biomarkers that are specifically expressed in either hepatocellular carcinoma or metastatic adenocarcinoma can therefore be useful diagnostic tools. To find such biomarkers, we studied microRNA expression in 144 tumor samples using custom microarrays. Hsa-miR-141 and hsa-miR-200c, microRNAs that promote epithelial phenotypes, had significantly higher levels in non-hepatic epithelial tumors. In contrast, endothelial-associated hsa-miR-126 showed higher expression levels in hepatocellular carcinomas. Combinations of these microRNAs accurately identified primary hepatocellular carcinoma from metastatic adenocarcinoma in the liver. These findings were validated using quantitative real-time PCR to measure microRNA expression in additional samples. Thus, the tissue-specific expression patterns of microRNAs make them useful biomarkers for the diagnosis of liver malignancies.

Multicentre validation of a microRNA-based assay for diagnosing indeterminate thyroid nodules utilising fine needle aspirate smears

Aims The 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. Methods A 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. Results Test 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%). Conclusions A 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.

Abstract 816: A novel microRNA-based test demonstrates 92% accuracy in the classification of metastatic tumors from patients diagnosed with carcinoma of unknown primary .

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Background: Cancers of unknown primary origin (CUP) constitute 3%-5% (50,000 to 70,000 cases) of all newly diagnosed cancers per year in the United States. Including cancers of uncertain primary origin, the total number increases to 12%-15% (180,000 to 220,000 cases) of all newly diagnosed cancers per year in the United States. CUP is a major diagnostic and clinical challenge, since identifying the tissue-of-origin of metastases is crucial for selecting optimal treatment. MicroRNAs are a family of non-coding, regulatory short RNA molecules that are stable in clinical samples and are tissue-specific, consequently they have a great potential to be excellent biomarkers for cancer tissue-of-origin diagnosis. The goal of the study was to assess the performance of a microRNAs-based assay to diagnose the tissue of origin on a well annotated cohort of real CUP patients. Methods: A pre-developed microarray-based test that measures the expression of 64 microRNAs was employed to identify the tissue of origin of metastatic tumors of CUP cases. A cohort of 93 resected metastatic lesions with adequate tissue sample from 92 patients diagnosed with CUP was studied. 85 samples (84 patients) were processed successfully; eight samples failed due to inadequate RNA quality. Test results were compared with clinical presentation including imaging, pathological data (histology and IHC) and therapeutic response. Results: Overall, in 92% of the patients the assay results were fully concordant with the final clinical diagnosis based on all other clinical, pathologic and outcome data. There was a 22% improvement in agreement of the test results from the clinical Diagnosis at presentation to the final clinical Diagnosis (based on additional data gathered with patients’ treatment and follow up), which is a strong indication of the degree in which the assay facilitates the diagnostic process from early stages of patients management. Conclusions: In a cohort of metastatic lesion samples from CUP patients, a previously developed test based on the expression profile of 64 microRNAs allowed accurate identification of tissue of origin in the vast majority of the cases. The high accuracy of this test in identifying the tissue of origin of metastasis of unknown primary has been validated by this study and demonstrates its clinical utility. The high concordance of the test results to the final diagnosis of the patient demonstrates the importance of the test to yield additional data valuable for patients management at an early stage of patients journey. This predictive ability could be associated with a change of clinical management, including administration of more effective chemotherapy combinations and targeted agents, in many of the patients in this study. Citation Format: Robert Wassman, Mats Sanden, George Pentheroudakis, Anna Goussia, Eti Meiri, Katerina Stoyianni, Danit Lebanony, George Fountzilas, Karin Ashkenazi, Vassiliki Malamou-Mitsi, Nicholas Palidis. A novel microRNA-based test demonstrates 92% accuracy in the classification of metastatic tumors from patients diagnosed with carcinoma of unknown primary . [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 816. doi:10.1158/1538-7445.AM2013-816

A microRNA-based diagnostic test for kidney tumors classification.

10578 Background: Renal cancers account for more then 3% of adult malignancies and cause more than 13,000 deaths per year in the U.S. alone. The four most common types of kidney tumors include the malignant renal cell carcinomas clear cell (conventional), papillary and chromophobe as well as the benign oncocytoma. These histological subtypes vary in their clinical courses and their prognosis, and different clinical strategies have been developed for their management. In some of the kidney tumor cases it is difficult for the pathologist to distinguish between tumor types on the basis of morphology. In this work we present a microRNA-based differential diagnosis test for primary kidney tumors. METHODS Over 200 formalin-fixed paraffin-embedded (FFPE) samples of primary kidney tumors were collected and reviewed by a pathologist with special experience in uropathology. High-quality totalRNA, including the well-preserved microRNA fraction, was extracted from the FFPE samples using a proprietary protocol. Expression levels of all known and additional Rosettas proprietary microRNAs were profiled using a custom array platform. Technical validation of the array results was performed using qRT-PCR. An assay which classifies the kidney tumors was developed based on the microRNAs expression in the different tumor types. A validation set of more than 150 independent samples was analyzed blindly and classified using the developed assay. RESULTS MicroRNAs showed differential expression in the four main histological types mentioned above with high correlation between the array and the qRT-PCR platforms. A set of microRNAs was identified that allows accurate classification of kidney tumors. A diagnostic assay based on the array technology was developed and clinical validation performed using an independent, blinded sample set. CONCLUSIONS Expression levels of certain microRNAs are highly specific to subtypes of kidney tumors. These findings were the basis for the development of a standardized diagnostic assay that can be used for the classification of kidney tumors in FFPE samples from resections or biopsies.