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.
Circulating tumor DNA (ctDNA) is now widely investigated as a biomarker in translational and clinical research (1). However, despite the growing field of clinical applications, the biology of ctDNA remains unclear. In trying to learn about the origins of ctDNA, nature provides us with very few clues. One of the important accessible parameters is the size of those DNA fragments. In addition, a well-informed model of these sizes and biases can help design more efficient and accurate diagnostic methods. In PNAS, Jiang et al. take an important step in that direction (2).
11028 Background: MicroRNAs are a novel class of non-coding, regulatory RNA genes which are involved in oncogenesis and show remarkable tissue-specificity. Their potential for tumor classification suggests they may be applied for identifying tissue-origin of cancers of unknown primary (CUP), a major clinical problem accounting for 3%∼5% of new cancer cases. We have developed a platform for the discovery and development of microRNA-based diagnostic tests. Here we report on the application of this platform for developing a microRNA signature that successfully identifies the tissue origin of primary as well as metastatic tumors. Methods: We developed protocols for extraction of high-quality RNA that retain the microRNA fraction from FFPE archival tissue samples. A microarray platform was used for high-throughput measurement of microRNA expression levels in tumor samples, and a highly specific qRT-PCR platform was used to validate biomarkers. Results: MicroRNA expression profiles were measured in 205 primary and 131 metastatic tumor samples representing 22 distinct tumor types and origins. Samples were divided into a training set (3/4) and a blinded test set (1/4). We developed a transparent classification approach based on 48 microRNAs, each linked to specific differential diagnosis roles. In an independent test of the 83 blinded samples, two-thirds of the samples were classified with high-confidence with an overall accuracy of 89%. Classification accuracy reached 100% for most tissue classes, including for the metastatic tumors. We further validated the significance of these microRNA biomarkers by qRT-PCR using 65 new blinded test samples. Conclusions: We developed a potent and highly accurate microRNA-based algorithm for identifying tissue origin of tumors. The high tissue specificity of microRNAs permits the identification of tumor origin of metastases and primary tumors, based on a small number of microRNAs, and can be used as a new tool in molecular diagnostics of cancer and in particular for identifying tumor origin in CUP. Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Expert Testimony Other Remuneration Rosetta Genomics Ltd Rosetta Genomics Ltd
<div>Abstract<p>The factors responsible for the low detection rate of cell-free tumor DNA (ctDNA) in the plasma of patients with glioblastoma (GBM) are currently unknown. In this study, we measured circulating nucleic acids in patient-derived orthotopically implanted xenograft (PDOX) models of GBM (<i>n</i> = 64) and show that tumor size and cell proliferation, but not the integrity of the blood–brain barrier or cell death, affect the release of ctDNA in treatment-naïve GBM PDOX. Analysis of fragment length profiles by shallow genome-wide sequencing (<0.2× coverage) of host (rat) and tumor (human) circulating DNA identified a peak at 145 bp in the human DNA fragments, indicating a difference in the origin or processing of the ctDNA. The concentration of ctDNA correlated with cell death only after treatment with temozolomide and radiotherapy. Digital PCR detection of plasma tumor mitochondrial DNA (tmtDNA), an alternative to detection of nuclear ctDNA, improved plasma DNA detection rate (82% vs. 24%) and allowed detection in cerebrospinal fluid and urine. Mitochondrial mutations are prevalent across all cancers and can be detected with high sensitivity, at low cost, and without prior knowledge of tumor mutations via capture-panel sequencing. Coupled with the observation that mitochondrial copy number increases in glioma, these data suggest analyzing tmtDNA as a more sensitive method to detect and monitor tumor burden in cancer, specifically in GBM, where current methods have largely failed.</p>Significance:<p>These findings show that detection of tumor mitochondrial DNA is more sensitive than circulating tumor DNA analysis to detect and monitor tumor burden in patient-derived orthotopic xenografts of glioblastoma.</p></div>
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