Selected microRNAs (miRNAs) that are abnormally expressed in the serum of patients with lung cancer have recently been proposed as biomarkers of this disease. The measurement of circulating miRNAs, however, requires a highly reliable quantification method. Quantitative real-time PCR (qPCR) is the most commonly used method, but it lacks reliable endogenous reference miRNAs for normalization of results in biofluids. When used in absolute quantification, it must rely on the use of external calibrators. Droplet digital PCR (ddPCR) is a recently introduced technology that overcomes the normalization issue and may facilitate miRNA measurement. Here we compared the performance of absolute qPCR and ddPCR techniques for quantifying selected miRNAs in the serum. In the first experiment, three miRNAs, proposed in the literature as lung cancer biomarkers (miR-21, miR-126 and let-7a), were analyzed in a set of 15 human serum samples. Four independent qPCR and four independent ddPCR amplifications were done on the same samples and used to estimate the precision and correlation of miRNA measurements obtained with the two techniques. The precision of the two methods was evaluated by calculating the Coefficient of Variation (CV) of the four independent measurements obtained with each technique. The CV was similar or smaller in ddPCR than in qPCR for all miRNAs tested, and was significantly smaller for let-7a (p = 0.028). Linear regression analysis of the miRNA values obtained with qPCR and ddPCR showed strong correlation (p < 0.001). To validate the correlation obtained with the two techniques in the first experiment, in a second experiment the same miRNAs were measured in a larger cohort (70 human serum samples) by both qPCR and ddPCR. The correlation of miRNA analyses with the two methods was significant for all three miRNAs. Moreover, in our experiments the ddPCR technique had higher throughput than qPCR, at a similar cost-per-sample. Analyses of serum miRNAs performed with qPCR and ddPCR were largely concordant. Both qPCR and ddPCR can reliably be used to quantify circulating miRNAs, however, ddPCR revealed similar or greater precision and higher throughput of analysis.

Studies investigating microRNAs as potential biomarkers for cancer, immune-related diseases, or cardiac pathogenic diseases, among others, have exponentially increased in the last years. In particular, altered expression of specific miRNAs correlates with the occurrence of several diseases, making these molecules potential molecular tools for non-invasive diagnosis, prognosis, and response to therapy. Nonetheless, microRNAs are not in clinical use yet, due to inconsistencies in the literature regarding the specific miRNAs identified as biomarkers for a specific disease, which in turn can be attributed to several reasons, including lack of assay standardization and reproducibility. Technological limitations in circulating microRNAs measurement have been, to date, the biggest challenge for using these molecules in clinical settings. In this review we will discuss pre-analytical, analytical, and post-analytical challenges to address the potential technical biases and patient-related parameters that can have an influence and should be improved to translate miRNA biomarkers to the clinical stage. Moreover, we will describe the currently available methods for circulating miRNA expression profiling and measurement, underlining their advantages and potential pitfalls.

A recent body of evidence indicates an active role for stromal (mis)-regulation in the progression of neoplasias. Within this conceptual framework, genes belonging to the growing but still poorly characterized class of tumor antagonizing/malignancy suppressor genes (TAG/MSG) seem to play a crucial role in the regulation of the cross-talk between stromal and epithelial cells by controlling malignant growth in vivo without affecting any cancer-related phenotype in vitro. Here, we have functionally characterized the human RNASET2 gene, which encodes the first human member of the widespread Rh/T2/S family of extracellular RNases and was recently found to be down-regulated at the transcript level in several primary ovarian tumors or cell lines and in melanoma cell lines. Although we could not detect any activity for RNASET2 in several functional in vitro assays, a remarkable control of ovarian tumorigenesis could be detected in vivo. Moreover, the control of ovarian tumorigenesis mediated by this unique tumor suppressor gene occurs through modification of the cellular microenvironment and the induction of immunocompetent cells of the monocyte/macrophage lineage. Taken together, the data presented in this work strongly indicate RNASET2 as a previously unexplored member of the growing family of tumor-antagonizing genes.