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The serum or plasma microRNA (miRNA) molecules have been suggested as diagnostic and prognostic biomarkers, in various pathological conditions. However, these molecules are also found in different serum fractions, such as exosomes and Argonaute (Ago) protein complexes. Ago1 is the predominant Ago protein expressed in heart tissue. The objective of the study was to examine the hypothesis that Ago1‐associated miRNAs may be more relevant to cardiac disease and heart failure compared with the serum. In total, 84 miRNA molecules were screened for their expression in the whole serum, exosomes and Ago1, and Ago2 complexes. Ago1‐bound miR‐222‐3p, miR‐497‐5p and miR‐21‐5p were significantly higher, and let‐7a‐5p was significantly lower in HF patients compared with healthy controls, whereas no such difference was observed for those markers in the serum samples among the groups. A combination of these 4 miRNAs into an Ago1‐HF score provided a ROC curve with an AUC of 1, demonstrating clear discrimination between heart failure patients and healthy individuals. Ago1 fraction might be a better and more specific platform for identifying HF‐related miRNAs compared with the whole serum.

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.

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. Cancers of unknown/uncertain primary origins present major diagnostic and clinical challenges because the tumor tissue of origin is crucial for selecting optimal treatment. MicroRNAs are a family of noncoding, regulatory RNA genes involved in carcinogenesis. MicroRNAs that are highly stable in clinical samples and tissue specific serve as ideal biomarkers for cancer diagnosis. Our first-generation assay identified the tumor of origin based on 48 microRNAs measured on a quantitative real-time polymerase chain reaction platform and differentiated 25 tumor types. Methods. We present here the development and validation of a second-generation assay that identifies 42 tumor types using a custom microarray. A combination of a binary decision-tree and a k-nearest-neighbor classifier was developed to identify the tumor of origin based on the expression of 64 microRNAs. Results. Overall assay sensitivity (positive agreement), measured blindly on a validation set of 509 independent samples, was 85%. The sensitivity reached 90% for cases in which the assay reported a single answer (>80% of cases). A clinical validation study on 52 true CUP patients showed 88% concordance with the clinicopathological evaluation of the patients. Conclusion. The abilities of the assay to identify 42 tumor types with high accuracy and to maintain the same performance in samples from patients clinically diagnosed with CUP promise improved utility in the diagnosis of cancers of unknown/uncertain primary origins.

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.

Glioblastoma multiforme is a very heterogeneous tumor, highly infiltrative, angiogenic and resistant to standard therapeutic intervention. Experimental models currently used in research are mostly based on cancer cell lines, which are grown in culture for many generations and have lost many essential biological characteristics. In consequence, the xenograft tumor models derived from those cells do not maintain genomic and phenotypic characteristics present in the original tumor. It is questionable whether these artificial preclinical models can serve as reliable platforms to select the lead candidate for a novel therapeutic approach. We utilized miRNA expression patterns to evaluate the clinical relevance of some of the currently available experimental models of GBM, searching for similarities and differences in miRNA expression levels between freshly isolated tumors, patient-derived primary cells and GBM cell lines grown in culture. The study included 22 formalin-fixed paraffin-embedded (FFPE) tumors from glioblastoma resections. Those were divided into two groups of Short Term Survivors (STS, survived up to 3 months from initial diagnosis; n=12) and Long Term Survivors (LTS, survived more than 3 years from initial diagnosis; n=10).We further tested 6 patient-derived primary cells, and 5 ATCC human GBM cell lines widely used in preclinical research. Two of the cell lines included dormant and fast-growing variants previously developed in our laboratory to resemble LTS and STS phenotypes, respectively. Samples were loaded on custom microRNA (miR) arrays, including 2172 known miRNAs (miRBase 19). We found several miRNAs that were upregulated in the STS samples while others exhibited higher expression levels in the LTS samples. Both GBM cell lines and patient-derived primary cells exhibited a miRNA profile which was very different from patient samples. Brain miRNAs used as brain markers, such as hsa-miR-124-3p), show relatively low expression levels in both patient-derived primary cells and commercial cell lines but are highly expressed in tumors. We concluded that GBM experimental models must be reevaluated and pre-clinical findings derived from long-established and commonly used in vitro and in vivo models should be further validated in patient-derived models that are more suitable to evaluate the potential clinical relevance of new therapeutics. Citation Format: Paula Ofek, Nir Dromi, Noga Yerushalmi, Sharon Kredo-Russo, Rachel Grossman, Zvi Ram, Ronit Satchi-Fainaro. Patient-derived GBM tumors versus patient-derived primary cells and GBM cell lines: lessons from microRNA profiling. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr B05.

For patients with primary lung cancer, accurate determination of the tumor type significantly influences treatment decisions. However, techniques and methods for lung cancer typing lack standardization. In particular, owing to limited tumor sample amounts and the poor quality of some samples, the classification of primary lung cancers using small preoperative biopsy specimens presents a diagnostic challenge using current tools. We previously described a microRNA-based assay (miRview squamous; Rosetta Genomics Ltd., Rehovot, Israel) that accurately differentiates between squamous and nonsquamous non–small cell lung cancer. Herein, we describe the development and validation of an assay that differentiates between the four main types of lung cancer: squamous cell carcinoma, nonsquamous non–small cell lung cancer, carcinoid, and small cell carcinoma. The assay, miRview lung (Rosetta Genomics Ltd.), is based on the expression levels of eight microRNAs, measured using a sensitive quantitative RT-PCR platform. It was validated on an independent set of 451 samples, more than half of which were preoperative cytologic samples (fine-needle aspiration and bronchial brushing and washing). The assay returned a result for more than 90% of the samples with overall accuracy of 94% (95% CI, 91% to 96%), with similar performance observed in pathologic and cytologic samples. Thus, miRview lung is a simple and reliable diagnostic assay that offers an accurate and standardized classification tool for primary lung cancer using pathologic and cytologic samples.

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.

SLE is a chronic, recurrent, potentially fatal multisystem inflammatory disorder mainly affecting women. SLE patients produce antibodies to many different self-antigens. Yet, currently used serological markers for SLE are lacking in specificity and/or sensitivity. The aim of this study was to develop an improved diagnostic test by measuring and multiplexing specific autoantibody reactivities in SLE patients. Autoantibody reactivity profiles in serum samples collected from 97 SLE patients within three years of the diagnosis were compared with those of 56 healthy controls. Autoantibody profiles were determined using the ImmunArray iCHIP™ - a proprietary protein microarray technology that allows the display of antigens representing a wide range of SLE-associated biochemical pathways on a single chip. Using this novel platform, SLE patients could be differentiated from healthy subjects by a relatively small subset of auto-antigens and Epstein Barr Virus (EBV) antigens. The autoantibody reactivity profile that allowed SLE diagnosis with high sensitivity and specificity displayed differential response to known SLE-specific antigens, such as single-stranded DNA and EBV, and to several novel ones. Conclusion: An antibody profile for SLE diagnosis using a single multiplexed chip was successfully developed. This profile may differentiate between SLE patients and healthy individuals. Validation of this profile in additional patient samples is ongoing.

10575 Background: Cancer of unknown primary (CUP) constitutes 3%-5% of all newly diagnosed cancer cases. It presents a major diagnostic challenge as knowing the tumor tissue of origin (ToO) of the ...

Introduction: The current inability to forecast outcomes for malignant pleural mesothelioma prevents clinicians from providing aggressive multimodality therapy to the most appropriate individuals who may benefit from such an approach, and hence compromises their prognosis. It was previously shown that microRNAs (miRs) have a role in the cancer process, and that they can serve as biomarkers for different tumors or histological types. Here we investigated whether specific miRs could differentiate a largely surgically-treated group of mesotheliomas into good or bad prognosis categories. Methods: In a retrospective study using snap frozen, immunohistochemically-proven mesothelioma surgical specimens, we looked for miRs associated with survival and time to progression. A training set of 44 and a test set of 98 mesothelioma tumor samples were analyzed by a custom ∼900 microRNA microarray platform and verified by qRT-PCR for cross-platform validation. Patients were segregated into good or bad time to progression (greater/less than 12 months) and into good or bad survival (greater/less than 15 months). Mann-Whitney tests for good vs. bad prognosis and Kaplan-Meier analysis were used to detect prognosticator miRs. The biological effect of the identified prognostic miR was tested in 2 mesothelioma cell lines. Functional implications as well as downstream targets of the potential prognostic miR were investigated in vitro. Results: In both the training and test sets, one miR was an independent prognostic factor for time to progression as well as survival after surgical cytoreduction. The miR was expressed at higher levels in epithelial mesothelioma than in sarcomatoid cases, and the level of this miR could segregate patients with this histology into groups with differing prognosis. Thresholds set within the training set for microarray reading were fully valid in the test-set, as was the comparable threshold using qRT-PCR. Increased expression of this specific miR predicted throughout a more favorable prognosis, and overexpression of the miR in mesothelioma cell lines resulted in significantly decreased proliferation, migration, invasion, and colony formation. Moreover, major epigenetic regulatory genes, known in mesothelioma, are mediated by this miR as was demonstrated through downregulation of DNA methyltransferases as well as upregulation of demethylating genes. This suggests that a control mechanism might explain the clinical findings, supporting their validity. Conclusions: One miR has the potential to be a prognostic biomarker in mesothelioma and shows the ability to change proliferation, migration, invasion upon over-expression in mesothelioma cell lines. Further validation of these findings as well as investigation of its downstream targets may give insight for potential therapies in the future, by allowing personalized treatment for patients who are more to benefit. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4053.