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miRNAs play a central role in the complex signaling network of cancer cells with the tumor microenvironment. Little is known on the origin of circulating miRNAs and their relationship with the tumor microenvironment in lung cancer. Here, we focused on the cellular source and relative contribution of different cell types to circulating miRNAs composing our risk classifier of lung cancer using in vitro/in vivo models and clinical samples. A cell-type specific expression pattern and topography of several miRNAs such as mir-145 in fibroblasts, mir-126 in endothelial cells, mir-133a in skeletal muscle cells was observed in normal and lung cancer tissues. Granulocytes and platelets are the major contributors of miRNAs release in blood. miRNAs modulation observed in plasma of lung cancer subjects was consistent with de-regulation of the same miRNAs observed during immunosuppressive conversion of immune cells. In particular, activated neutrophils showed a miRNA profile mirroring that observed in plasma of lung cancer subjects. Interestingly mir-320a secreted by neutrophils of high-risk heavy-smokers promoted an M2-like protumorigenic phenotype through downregulation of STAT4 when shuttled into macrophages. These findings suggest a multifactorial and nonepithelial cell-autonomous origin of circulating miRNAs associated with risk of lung cancer and that circulating miRNAs may act in paracrine signaling with causative role in lung carcinogenesis and immunosuppression., (© 2018 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

The development of a minimally invasive test, such as liquid biopsy, for early lung cancer detection in its preclinical phase is crucial to improve the outcome of this deadly disease. MicroRNAs (miRNAs) are tissue specific, small, non-coding RNAs regulating gene expression, which may act as extracellular messengers of biological signals derived from the cross-talk between the tumor and its surrounding microenvironment. They could thus represent ideal candidates for early detection of lung cancer. In this work, a methodological workflow for the prospective validation of a circulating miRNA test using custom made microfluidic cards and quantitative Real-Time PCR in plasma samples of volunteers enrolled in a lung cancer screening trial is proposed. In addition, since the release of hemolysis-related miRNAs and more general technical issues may affect the analysis, the quality control steps included in the standard operating procedures are also presented. The protocol is reproducible and gives reliable quantitative results; however, when using large clinical series, both pre-analytical and analytical features should be cautiously evaluated.

Digital PCR (dPCR) is an innovative approach for detection and quantification of nucleic acid that offers an alternative method to conventional real-time quantitative PCR for absolute quantification. dPCR is a highly precise and sensitive technique that does not require a standard reference, making it a suitable method for the detection of microRNAs. The potential of these small noncoding RNA as biomarkers is on the rise, especially due to their presence in body fluids, making them easily accessible. Nevertheless, the problem of lack of consensus regarding an optimal method for miRNAs normalization compromises their use. Here, we describe an innovative method for the absolute quantification of miRNAs across different types of biological samples using a chip-based platform, the QuantStudio 3D digital PCR.

Background: Research efforts for the management of cancer, in particular for lung cancer, are directed to identify new strategies for its early detection. MicroRNAs (miRNAs) are a new promising class of circulating biomarkers for cancer detection, but lack of consensus on data normalization methods has affected the diagnostic potential of circulating miRNAs. There is a growing interest in techniques that allow an absolute quantification of miRNAs which could be useful for early diagnosis. Recently, digital PCR, mainly based on droplets generation, emerged as an affordable technology for precise and absolute quantification of nucleic acids., Results: In this work, we described a new interesting approach for profiling circulating miRNAs in plasma samples using a chip-based platform, the QuantStudio 3D digital PCR. The proposed method was validated using synthethic oligonucleotide at serial dilutions in plasma samples of lung cancer patients and in lung tissues and cell lines., Conclusion: Given its reproducibility and reliability, our approach could be potentially applied for the identification and quantification of miRNAs in other biological samples such as circulating exosomes or protein complexes. As chip-digital PCR becomes more established, it would be a robust tool for quantitative assessment of miRNA copy number for diagnosis of lung cancer and other diseases.

Purpose: Recent screening trial results indicate that low-dose computed tomography (LDCT) reduces lung cancer mortality in high-risk patients. However, high false-positive rates, costs, and potential harms highlight the need for complementary biomarkers. The diagnostic performance of a noninvasive plasma microRNA signature classifier (MSC) was retrospectively evaluated in samples prospectively collected from smokers within the randomized Multicenter Italian Lung Detection (MILD) trial., Patients and Methods: Plasma samples from 939 participants, including 69 patients with lung cancer and 870 disease-free individuals (n = 652, LDCT arm; n = 287, observation arm) were analyzed by using a quantitative reverse transcriptase polymerase chain reaction-based assay for MSC. Diagnostic performance of MSC was evaluated in a blinded validation study that used prespecified risk groups., Results: The diagnostic performance of MSC for lung cancer detection was 87% for sensitivity and 81% for specificity across both arms, and 88% and 80%, respectively, in the LDCT arm. For all patients, MSC had a negative predictive value of 99% and 99.86% for detection and death as a result of disease, respectively. LDCT had sensitivity of 79% and specificity of 81% with a false-positive rate of 19.4%. Diagnostic performance of MSC was confirmed by time dependency analysis. Combination of both MSC and LDCT resulted in a five-fold reduction of LDCT false-positive rate to 3.7%. MSC risk groups were significantly associated with survival (χ1(2) = 49.53; P < .001)., Conclusion: This large validation study indicates that MSC has predictive, diagnostic, and prognostic value and could reduce the false-positive rate of LDCT, thus improving the efficacy of lung cancer screening.

Lung cancer is the most common cause of cancer deaths worldwide and numerous ongoing research efforts are directed to identify new strategies for its early detection. The development of non-invasive blood-based biomarkers for cancer detection in its preclinical phases is crucial to improve the outcome of this deadly disease. MicroRNAs (miRNAs) are a new promising class of circulating biomarkers for cancer detection and prognosis definition, but lack of consensus on data normalization methods for circulating miRNAs and the critical issue of haemolysis, has affected the identification of circulating miRNAs with diagnostic potential. We describe here an interesting approach for profiling circulating miRNAs in plasma samples based on the evaluation of reciprocal miRNA levels measured by quantitative Real-Time PCR. By monitoring changes of plasma miRNA-ratios, it is possible to assess the deregulation of tumor-related miRNAs and identify signatures with diagnostic and prognostic value. In addition, to avoid bias due to the release of miRNAs from blood cells, a miRNA-ratios signature distinguishing haemolyzed samples was identified. The method described was validated in plasma samples of lung cancer patients, but given its reproducibility and reliability, could be potentially applied for the identification of diagnostic circulating miRNAs in other diseases.

The efficacy of computed tomography (CT) screening for early lung cancer detection in heavy smokers is currently being tested by a number of randomized trials. Critical issues remain the frequency of unnecessary treatments and impact on mortality, indicating the need for biomarkers of aggressive disease. We explored microRNA (miRNA) expression profiles of lung tumors, normal lung tissues and plasma samples from cases with variable prognosis identified in a completed spiral-CT screening trial with extensive follow-up. miRNA expression patterns significantly distinguished: (i) tumors from normal lung tissues, (ii) tumor histology and growth rate, (iii) clinical outcome, and (iv) year of lung cancer CT detection. Interestingly, miRNA profiles in normal lung tissues also displayed remarkable associations with clinical features, suggesting the influence of a permissive microenvironment for tumor development. miRNA expression analyses in plasma samples collected 1-2 y before the onset of disease, at the time of CT detection and in disease-free smokers enrolled in the screening trial, resulted in the generation of miRNA signatures with strong predictive, diagnostic, and prognostic potential (area under the ROC curve ≥ 0.85). These signatures were validated in an independent cohort from a second randomized spiral-CT trial. These results indicate a role for miRNAs in lung tissues and plasma as molecular predictors of lung cancer development and aggressiveness and have theoretical and clinical implication for lung cancer management.