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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.