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.circulating biomarkers | risk prediction | miRNA ratios D espite recent advances in the management of resected lung cancer and the use of molecular targeted agents in specific clinical settings, the cure rate of non-small-cell lung cancer (NSCLC) remains low due to drug-refractory recurrent and metastatic disease.Early detection studies using chest X-rays (1) and, more recently, spiral-computed tomography (CT; refs. 2 and 3), have reported a significant increase in the number of lung cancer diagnoses, without apparent major decrease in advanced cancers or reduction of mortality in smokers (4). A recent press release (http://www.cancer.gov) reporting the findings of the largest randomized trial comparing spiral-CT to chest X-rays showed a 6.9% reduction in all-cause mortality (−20.3% lung cancer mortality), but a full report of the results of this trial is not yet available. A likely explanation of the limited impact of CT screening on mortality is that perhaps not all aggressive lung tumors arise from identifiable slow-growing precursors, suggesting a possible paradigm shift in our understanding of the natural history of lung cancer (5, 6). In this respect, the identification of biologic and molecular features of indolent and aggressive disease would be critical to define clinically useful predictors of high-risk lesions. microRNAs (miRNAs) are small RNA molecules with regulatory function and marked tissue specificity that can modulate multiple targets belonging to several pathways. They are fr...

Hyperprogression (HP), a paradoxical boost in tumor growth, was described in a subset of patients treated with immune checkpoint inhibitors (ICI). Neither clinicopathologic features nor biological mechanisms associated with HP have been identified. Among 187 patients with non-small cell lung cancer (NSCLC) treated with ICI at our institute, cases with HP were identified according to clinical and radiologic criteria. Baseline histologic samples from patients treated with ICI were evaluated by IHC for myeloid and lymphoid markers. T-cell-deficient mice, injected with human lung cancer cells and patient-derived xenografts (PDX) belonging to specific mutational subsets, were assessed for tumor growth after treatment with antibodies against mouse and human programmed death receptor-1 (PD-1). The immune microenvironment was evaluated by flow cytometry and IHC. Among 187 patients, 152 were evaluable for clinical response. We identified four categories: 32 cases were defined as responders (21%), 42 patients with stable disease (27.7%), 39 cases were defined as progressors (25.7%), and 39 patients with HP (25.7%). Pretreatment tissue samples from all patients with HP showed tumor infiltration by M2-like CD163CD33PD-L1 clustered epithelioid macrophages. Enrichment by tumor-associated macrophages (TAM) was observed, even in tumor nodules from immunodeficient mice injected with human lung cancer cells and with PDXs. In these models, tumor growth was enhanced by treatment with anti-PD-1 but not anti-PD-1 F(ab) fragments. These results suggest a crucial role of TAM reprogramming, upon Fc receptor engagement by ICI, eventually inducing HP and provide clues on a distinctive immunophenotype potentially able to predict HP.

A B S T R A C T PurposeRecent 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 MethodsPlasma samples from 939 participants, including 69 patients with lung cancer and 870 disease-free individuals (n ϭ 652, LDCT arm; n ϭ 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. ResultsThe 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 ( 1 2 ϭ 49.53; P Ͻ .001). ConclusionThis 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.

Background The National Lung Screening Trial showed that lung cancer (LC) screening by three annual rounds of low-dose computed tomography (LDCT) reduces LC mortality. We evaluated the benefit of prolonged LDCT screening beyond 5 years, and its impact on overall and LC specific mortality at 10 years. Design The Multicentric Italian Lung Detection (MILD) trial prospectively randomized 4099 participants, to a screening arm ( n = 2376), with further randomization to annual ( n = 1190) or biennial ( n = 1186) LDCT for a median period of 6 years, or control arm ( n = 1723) without intervention. Between 2005 and 2018, 39 293 person-years of follow-up were accumulated. The primary outcomes were 10-year overall and LC specific mortality. Landmark analysis was used to test the long-term effect of LC screening, beyond 5 years by exclusion of LCs and deaths that occurred in the first 5 years. Results The LDCT arm showed a 39% reduced risk of LC mortality at 10 years [hazard ratio (HR) 0.61; 95% confidence interval (CI) 0.39–0.95], compared with control arm, and a 20% reduction of overall mortality (HR 0.80; 95% CI 0.62–1.03). LDCT benefit improved beyond the 5th year of screening, with a 58% reduced risk of LC mortality (HR 0.42; 95% CI 0.22–0.79), and 32% reduction of overall mortality (HR 0.68; 95% CI 0.49–0.94). Conclusions The MILD trial provides additional evidence that prolonged screening beyond 5 years can enhance the benefit of early detection and achieve a greater overall and LC mortality reduction compared with NLST trial. ClinicalTrials.gov identifier NCT02837809.

The present review is an update of the research and development efforts regarding the use of molecular biomarkers in the lung cancer screening setting. The two main unmet clinical needs, namely, the refinement of risk to improve the selection of individuals undergoing screening and the characterization of undetermined nodules found during the computed tomography-based screening process are the object of the biomarkers described in the present review. We first propose some principles to optimize lung cancer biomarker discovery projects. Then, we summarize the discovery and developmental status of currently promising molecular candidates, such as autoantibodies, complement fragments, microRNAs, circulating tumor DNA, DNA methylation, blood protein profiling, or RNA airway or nasal signatures. We also mention other emerging biomarkers or new technologies to follow, such as exhaled breath biomarkers, metabolomics, sputum cell imaging, genetic predisposition studies, and the integration of nextgeneration sequencing into study of circulating DNA. We also underline the importance of integrating different