Hila Benjamin

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.

Accurate Classification of Non–Small Cell Lung Carcinoma Using a Novel MicroRNA-Based Approach

Purpose: Advances in targeted lung cancer therapy now demand accurate classification of non–small cell lung cancer (NSCLC). MicroRNAs (miRNA) are recently discovered short, noncoding genes that play essential roles in tissue differentiation during normal development and tumorigenesis. For example, hsa-miR-205 is a miRNA that is highly expressed in lung squamous cell carcinomas (SqCC) but not in lung adenocarcinomas. The differential expression of miRNAs could be exploited to distinguish these tumor types. Experimental Design: One hundred and two resected NSCLCs were classified as SqCC or adenocarcinoma based on their histologic features and immunohistochemical profiles. Corresponding preoperative biopsies/aspirates that had been originally diagnosed as poorly differentiated NSCLCs were available for 21 cases. A quantitative reverse transcription-PCR diagnostic assay that measures the expression level of hsa-miR-205 was used to classify the carcinomas as SqCC or adenocarcinoma based solely on expression levels. The two sets of diagnoses were compared. Results: Using standard pathologic methods of classification (i.e., microscopy and immunohistochemistry), 52 resected lung carcinomas were classified as SqCCs and 50 as adenocarcinomas. There was 100% concordance between the diagnoses established by conventional and miRNA-based methods. MiRNA profiling also correctly classified 20 of the 21 preoperative biopsy specimens. Conclusions: MiRNA profiling is a highly reliable strategy for classifying NSCLCs. Indeed, classification is consistently accurate even in small biopsies/aspirates of poorly differentiated tumors. Confirmation of its reliability across the full range of tumor grades and specimen types represents an important step toward broad application. Clin Cancer Res; 16(2); 610–9

Discovery of microRNAs and other small RNAs in solid tumors

MicroRNAs (miRNAs) are ∼22-nt long, non-coding RNAs that regulate gene silencing. It is known that many human miRNAs are deregulated in numerous types of tumors. Here we report the sequencing of small RNAs (17–25 nt) from 23 breast, bladder, colon and lung tumor samples using high throughput sequencing. We identified 49 novel miRNA and miR-sized small RNAs. We further validated the expression of 10 novel small RNAs in 31 different types of blood, normal and tumor tissue samples using two independent platforms, namely microarray and RT–PCR. Some of the novel sequences show a large difference in expression between tumor and tumor-adjacent tissues, between different tumor stages, or between different tumor types. We also report the identification of novel small RNA classes in human: highly expressed small RNA derived from Y-RNA and endogenous siRNA. Finally, we identified dozens of new miRNA sequence variants that demonstrate the existence of miRNA-related SNP or post-transcriptional modifications. Our work extends the current knowledge of the tumor small RNA transcriptome and provides novel candidates for molecular biomarkers and drug targets.

Comprehensive Gene and microRNA Expression Profiling Reveals a Role for microRNAs in Human Liver Development

Background and Aims microRNAs (miRNAs) are small noncoding RNAs that regulate cognate mRNAs post-transcriptionally. miRNAs have been implicated in regulating gene expression in embryonic developmental processes, including proliferation and differentiation. The liver is a multifunctional organ, which undergoes rapid changes during the developmental period and relies on tightly-regulated gene expression. Little is known regarding the complex expression patterns of both mRNAs and miRNAs during the early stages of human liver development, and the role of miRNAs in the regulation of this process has not been studied. The aim of this work was to study the impact of miRNAs on gene expression during early human liver development. Methods Global gene and miRNA expression were profiled in adult and in 9–12w human embryonic livers, using high-density microarrays and quantitative RT-PCR. Results Embryonic liver samples exhibited a gene expression profile that differentiated upon progression in the developmental process, and revealed multiple regulated genes. miRNA expression profiling revealed four major expression patterns that correlated with the known function of regulated miRNAs. Comparison of the expression of the most regulated miRNAs to that of their putative targets using a novel algorithm revealed a significant anti-correlation for several miRNAs, and identified the most active miRNAs in embryonic and in adult liver. Furthermore, our algorithm facilitated the identification of TGFβ-R1 as a novel target gene of let-7. Conclusions Our results uncover multiple regulated miRNAs and genes throughout human liver development, and our algorithm assists in identification of novel miRNA targets with potential roles in liver development.

Accurate Molecular Classification of Renal Tumors Using MicroRNA Expression

Subtypes of renal tumors have different genetic backgrounds, prognoses, and responses to surgical and medical treatment, and their differential diagnosis is a frequent challenge for pathologists. New biomarkers can help improve the diagnosis and hence the management of renal cancer patients. We extracted RNA from 71 formalin-fixed paraffin-embedded (FFPE) renal tumor samples and measured expression of more than 900 microRNAs using custom microarrays. Clustering revealed similarity in microRNA expression between oncocytoma and chromophobe subtypes as well as between conventional (clear-cell) and papillary tumors. By basing a classification algorithm on this structure, we followed inherent biological correlations and could achieve accurate classification using few microRNAs markers. We defined a two-step decision-tree classifier that uses expression levels of six microRNAs: the first step uses expression levels of hsa-miR-210 and hsa-miR-221 to distinguish between the two pairs of subtypes; the second step uses either hsa-miR-200c with hsa-miR-139-5p to identify oncocytoma from chromophobe, or hsa-miR-31 with hsa-miR-126 to identify conventional from papillary tumors. The classifier was tested on an independent set of FFPE tumor samples from 54 additional patients, and identified correctly 93% of the cases. Validation on qRT-PCR platform demonstrated high correlation with microarray results and accurate classification. MicroRNA expression profiling is a very effective molecular bioassay for classification of renal tumors and can offer a quantitative standardized complement to current methods of tumor classification.

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.

Novel microRNA-based assay demonstrates 92% agreement with diagnosis based on clinicopathologic and management data in a cohort of patients with carcinoma of unknown primary

BackgroundCancer of unknown or uncertain primary 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 RNA molecules that are tissue-specific, with a great potential to be excellent biomarkers.MethodsIn this study we tested the performance of a microRNA-based assay in formalin-fixed paraffin-embedded samples from 84 CUP patients.ResultsThe microRNA based assay agreed with the clinical diagnosis at presentation in 70% of patients; it agreed with the clinical diagnosis obtained after patient management, taking into account response and outcome data, in 89% of patients; it agreed with the final clinical diagnosis reached with supplemental immunohistochemical stains in 92% of patients, indicating a 22% improvement in agreement from diagnosis at presentation to the final clinical diagnosis. In 18 patients the assay disagreed with the presentation diagnosis and was in agreement with the final clinical diagnosis, which may have resulted in the administration of more effective chemotherapy. In three out of four discordant cases in which supplemental IHC was performed, the IHC results validated the assay’s molecular diagnosis.ConclusionsThis novel microRNA-based assay shows high accuracy in identifying the final clinical diagnosis in a real life CUP patient cohort and could be a useful tool to facilitate administration of optimal therapy.