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.

BACKGROUND: Cancer 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. METHODS: In this study we tested the performance of a microRNA-based assay in formalin-fixed paraffin-embedded samples from 84 CUP patients. RESULTS: The 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. CONCLUSIONS: This 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.

Development and validation of a microRNA-based diagnostic assay for classification of renal cell carcinomas.

Renal cancers account for more than 3% of adult malignancies and cause more than 13,000 deaths per year in the US alone. The four most common types of kidney tumors include the malignant renal cell carcinomas; clear cell, papillary, chromophobe and the benign oncocytoma. These histological subtypes vary in their clinical course and prognosis, and different clinical strategies have been developed for their management. In some kidney tumor cases it can be very difficult for the pathologist to distinguish between tumor types on the basis of morphology and immunohistochemistry (IHC). In this publication we present the development and validation of a microRNA-based assay for classifying primary kidney tumors. The assay, which classifies the four main kidney tumor types, was developed based on the expression of a set of 24 microRNAs. A validation set of 201 independent samples was classified using the assay and analyzed blindly. The assay produced results for 92% of the samples with an accuracy of 95%.

A second-generation microRNA-based assay for diagnosing tumor tissue origin.

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.

Prospective gene signature study using microRNA to identify the tissue of origin in patients with carcinoma of unknown primary.

PURPOSE: Accurate identification of tissue of origin (ToO) for patients with carcinoma of unknown primary (CUP) may help customize therapy to the putative primary and thereby improve the clinical outcome. We prospectively studied the performance of a microRNA-based assay to identify the ToO in CUP patients. EXPERIMENTAL DESIGN: Formalin-fixed paraffin-embedded (FFPE) metastatic tissue from 104 patients was reviewed and 87 of these contained sufficient tumor for testing. The assay quantitates 48 microRNAs and assigns one of 25 tumor diagnoses by using a biologically motivated binary decision tree and a K-nearest neighbors (KNN). The assay predictions were compared with clinicopathologic features and, where suitable, to therapeutic response. RESULTS: Seventy-four of the 87 cases were processed successfully. The assay result was consistent or compatible with the clinicopathologic features in 84% of cases processed successfully (71% of all samples attempted). In 65 patients, pathology and immunohistochemistry (IHC) suggested a diagnosis or (more often) a differential diagnosis. Out of those, the assay was consistent or compatible with the clinicopathologic presentation in 55 (85%) cases. Of the 9 patients with noncontributory IHC, the assay provided a ToO prediction that was compatible with the clinical presentation in 7 cases. CONCLUSIONS: In this prospective study, the microRNA diagnosis was compatible with the clinicopathologic picture in the majority of cases. Comparative effectiveness research trials evaluating the added benefit of molecular profiling in appropriate CUP subsets are warranted. MicroRNA profiling may be particularly helpful in patients in whom the IHC profile of the metastasis is nondiagnostic or leaves a large differential diagnosis.

Accurate classification of metastatic brain tumors using a novel microRNA-based test.

BACKGROUND: Identification of the tissue of origin of a brain metastatic tumor is vital to its management. Carcinoma of unknown primary (CUP) is common in oncology, representing 3%-5% of all invasive malignancies. We aimed to validate a recently developed microRNA-based quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) test for identifying the tumor tissue of origin, first in a consecutive cohort of metastatic tumors of known origin and then in a cohort of CUP cases resected from the central nervous system (CNS). PATIENTS AND METHODS: One hundred two resected CNS metastatic tumors with known origin, previously classified based on the patient's clinical history and pathological data, as well as a second cohort of resected CNS tumors from 57 patients originally diagnosed as CUP were studied. A qRT-PCR diagnostic assay that measures the expression level of 48 microRNAs was used to classify the tissue of origin of these metastatic tumors. RESULTS: In this blinded study, the test predictions correctly identified the reference diagnosis of the samples of known origin, excluding samples from prostate origin, in 84% of cases. In the second CUP patient cohort, the test prediction was in agreement with the diagnosis that was later confirmed clinically or with pathological evaluation in 80% of cases. CONCLUSION: In a cohort of brain and spinal metastases, a previously developed test based on the expression of 48 microRNAs allowed accurate identification of the tumor tissue of origin in the majority of cases. The high accuracy of this test in identifying the tissue of origin of metastases of unknown primary is demonstrated for the first time and may have broad clinical application.

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.

Pro-tumorigenic effects of miR-31 loss in mesothelioma.

The human genome encodes several hundred microRNA (miRNA) genes that produce small (21-23n) single strand regulatory RNA molecules. Although abnormal expression of miRNAs has been linked to cancer progression, the mechanisms of this dysregulation are poorly understood. Malignant mesothelioma (MM) of pleura is an aggressive and highly lethal cancer resistant to conventional therapies. We and others previously linked loss of the 9p21.3 chromosome in MM with short time to tumor recurrence. In this study, we report that MM cell lines derived from patients with more aggressive disease fail to express miR-31, a microRNA recently linked with suppression of breast cancer metastases. We further demonstrate that this loss is due to homozygous deletion of the miR-31-encoding gene that resides in 9p21.3. Functional assessment of miR-31 activity revealed its ability to inhibit proliferation, migration, invasion, and clonogenicity of MM cells. Re-introduction of miR-31 suppressed the cell cycle and inhibited expression of multiple factors involved in cooperative maintenance of DNA replication and cell cycle progression, including pro-survival phosphatase PPP6C, which was previously associated with chemotherapy and radiation therapy resistance, and maintenance of chromosomal stability. PPP6C, whose mRNA is distinguished with three miR-31-binding sites in its 3'-untranslated region, was consistently down-regulated by miR-31 introduction and up-regulated in clinical MM specimens as compared with matched normal tissues. Taken together, our data suggest that tumor-suppressive propensity of miR-31 can be used for development of new therapies against mesothelioma and other cancers that show loss of the 9p21.3 chromosome.

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.

hsa-miR-29c* is linked to the prognosis of malignant pleural mesothelioma.

The inability to forecast outcomes for malignant mesothelioma prevents clinicians from providing aggressive multimodality therapy to the most appropriate individuals who may benefit from such an approach. We investigated whether specific microRNAs (miR) could segregate a largely surgically treated group of mesotheliomas into good or bad prognosis categories. A training set of 44 and a test set of 98 mesothelioma tumors were analyzed by a custom miR platform, along with 9 mesothelioma cell lines and 3 normal mesothelial lines. Functional implications as well as downstream targets of potential prognostic miRs were investigated. In both the training and test sets, hsa-miR-29c* 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, and the level of this miR could segregate patients with this histology into groups with differing prognosis. Increased expression of hsa-miR-29c* predicted 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 regulation of mesothelioma is mediated by hsa-miR-29c* and was shown through downregulation of DNA methyltransferases as well as upregulation of demethylating genes. A single miR has the potential to be a prognostic biomarker in mesothelioma, and validation of these findings as well as investigation of its downstream targets may give insight for potential therapies in the future.

Tumor microRNA expression patterns associated with resistance to platinum based chemotherapy and survival in ovarian cancer patients.

BACKGROUND: Ovarian cancer, the leading cause of gynecologic cancer deaths, is usually diagnosed in advanced stages. Prognosis relates to stage at diagnosis and sensitivity to platinum based chemotherapy. We aimed to assess the expression of microRNAs in ovarian tumors and identify microRNA expression patterns that are associated with outcome, response to chemotherapy and survival. METHODS: Patients, who were surgically treated for ovarian cancer between January 2000 and December 2004 were identified. Patient charts were reviewed for clinicopathologic information, follow-up and survival. Total RNA was extracted from tumor samples and microRNA expression levels were measured by microarrays. Expression levels were compared between groups of samples and statistically analyzed. RESULTS: Fifty-seven patients were identified to fit study criteria. Of them, 19 patients had stage I disease at diagnosis, and 38 patients, stage III. All patients received platinum based chemotherapy as first line treatment. 18 microRNAs were differentially expressed (p<0.05) between stage I and stage III disease. Seven microRNAs were found to be significantly differentially expressed in tumors from platinum-sensitive vs. platinum-resistant patients (p<0.05). Five microRNAs were associated with significant differences (p<0.05) in survival or recurrence-free survival. High expression of hsa-mir-27a identified a sub-group of patients with very poor prognosis. CONCLUSIONS: We have found an array of tumor specific markers that are associated with response to platinum based first line chemotherapy. Expression of some of these miRNAs also correlated closely with prognosis. This approach can potentially be used to tailor chemotherapy and further management to specific patient needs.

MiR-92b and miR-9/9* are specifically expressed in brain primary tumors and can be used to differentiate primary from metastatic brain tumors.

A recurring challenge for brain pathologists is to diagnose whether a brain malignancy is a primary tumor or a metastasis from some other tissue. The accurate diagnosis of brain malignancies is essential for selection of proper treatment. MicroRNAs are a class of small non-coding RNA species that regulate gene expression; many exhibit tissue-specific expression and are misregulated in cancer. Using microRNA expression profiling, we found that hsa-miR-92b and hsa-miR-9/hsa-miR-9* are over-expressed, specifically in brain primary tumors, as compared to primary tumors from other tissues and their metastases to the brain. By considering the expression of only these two microRNAs, it is possible to distinguish between primary and metastatic brain tumors with very high accuracy. These microRNAs thus represent excellent biomarkers for brain primary tumors. Previous reports have found that hsa-miR-92b and hsa-miR-9/hsa-miR-9* are expressed more strongly in developing neurons and brain than in adult brain. Thus, their specific over-expression in brain primary tumors supports a functional role for these microRNAs or a link between neuronal stem cells and brain tumorigenesis.

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.

Test of a statistical model for molecular recognition in biological repertoires.

A chance encounter between members of a random repertoire and a molecular target is characteristic of different biological systems, including the immune and olfactory pathways as well as combinatorial libraries. In such systems, the affinity between the target and members of the repertoire is distributed with a probability function describing the propensity of obtaining a particular affinity value. We have previously proposed a phenomenological receptor affinity distribution (RAD) formalism, which describes this probability function based on simple statistical considerations. In the present analysis, we use published data from diverse experimental systems, including phage display libraries, immunoglobulins and enzymes, to test the RAD model and to compare it to other affinity distribution formalisms. The RAD model is found to provide the best description for binding data for over eight orders of magnitude on the affinity scale, and to account for a relationship between repertoire size and the maximal obtainable affinity within different repertoires. This approach points to a potential universality of the rules that govern affinity distributions in biology.