Circulating mir-320a promotes immunosuppressive macrophages M2 phenotype associated with lung cancer risk.

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.

Baseline and Postoperative C-reactive Protein Levels Predict Long-Term Survival After Lung Metastasectomy.

BACKGROUND: Blood level of C-reactive protein (CRP) at diagnosis is a well-know prognostic bio-marker in different primary tumors, but its role has not been investigated in resectable lung metastases. The aim of our study is to assess the predictive value of baseline (CRP0) and 3rd postoperative day (CRP3) levels on long-term survival of patients undergoing lung metastasectomy. METHODS: A total of 846 consecutive patients underwent the first pulmonary resection for lung metastases between January 2003 and December 2015, including 611 (72%) single surgical procedures, 235 (28%) multiple metastasectomies, 501 (59%) epithelial primary tumors, 276 (33%) sarcomas, 66 (8%) melanomas, 286 (33.8%) with 0 risk factors (CRP0 ≤ 2 and CRP3 ≤ 84 mg/L) and 560 (66.2%) with ≥ 1 risk factor (CRP0 > 2 and/or CRP3 > 84 mg/L). RESULTS: Cumulative 5-year survival was 57% in patients with low CRP (0 risk factors) versus 43% in high CRP (≥ 1 risk factor, p < 0.0002), 62% versus 50% respectively for epithelial tumors (p < 0.0140), and 51% versus 34% for sarcomas (p < 0.0111). Multivariable Cox analysis confirmed a mortality hazard ratio of 2.5 at 1-year and 1.5 at 5-years in patients with high CRP. CONCLUSIONS: Baseline and postoperative CRP levels predict survival of patients with resectable lung metastases. These data provide a rationale for prospective clinical trials testing the efficacy of anti-inflammatory or immune-modulating agents as "adjuvant" therapy after lung metastasectomy, in patients with elevated pre- and/or postoperative CRP levels.

[Lung cancer screening in high-risk subjects: early detection with LDCT and risk stratification using miRNA-based blood test]. / Screening per il tumore polmonare in soggetti ad alto rischio: diagnosi precoce con TC spirale associata a stratificazione del rischio con miRNA circolanti.

Lung cancer still remains a high mortality disease in the face of developments in diagnostic and therapeutic methods that occurred in the last 20 years. The analysis of the experiences from the first studies - in which chest X-ray (CXR) was adopted, associated or not with sputum cytology - has failed to show a reduction in lung cancer specific mortality. Subsequent screening studies that have introduced the use of low-dose computed tomography (LDCT) have revealed a large number of early-stage lung cancers, thus potentially curable; however, this has not allowed us to demonstrate a decrease in lung cancer-specific mortality. With the results of the American study National Lung ScreeningTrial (NLST), published in 2011, for the first time a lung cancer-specific mortality reduction by 20% thanks to the use of LDCT compared to RXT, was highlighted. However, a false discovery rate of 96.4% was also described with an overdiagnosis that can be up to 78.9% for bronchioalveolar lung cancer. Due to the high sensitivity of LDCT, able to identify a non-calcified pulmonary nodule in one subject on two, it becomes necessary to avail instruments to more accurately identify suspicious nodules. Until some time ago, the possible use of lung tumour markers was not viable in view of the poor organ specificity. The study and development was, then, pushed to organ- and tissue-specific markers such as microRNA (miRNA), noncoding RNA sequences involved in many processes and expression of oncogenic activity of the microenvironment. The use of biomarkers such as circulating miRNA implemented in LDCT screening has highlighted a reduction of 5 times for the rate of false positives, going from 19.4% to 3.7%, with a sensitivity of 87%, a specificity of 81%, and a negative predictive value of 99%. The need to appropriately use the available resources commensurate with the disease to treat will push more and more towards the implementation of LDCT biomarkers based screenings, stable and easily reproducible, as circulating miRNAs, obviating to problems such as false positives, unnecessary procedures of invasive surgery for benign lesions, and optimizing the cost benefit ratios.The development of new specific biomarkers appears to offer new promising prospects.

MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer.

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.

Assessment of circulating microRNAs in plasma of lung cancer patients.

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.

Blood microRNA testing in participants with suspicious low-dose CT findings: follow-up of the BioMILD lung cancer screening trial.

Background: The proper management of suspicious radiologic findings is crucial to optimize the effectiveness of low-dose computed tomography (LDCT) lung cancer screening trials. In the BioMILD study, we evaluated the utility of combining a plasma 24-microRNA signature classifier (MSC) and LDCT to define the individual risk and personalize screening strategies. Here we aim to assess the utility of repeated MSC testing during annual screening rounds in 1024 participants with suspicious LDCT findings. Methods: The primary outcome was two-year lung cancer incidence in relation to MSC test results, reported as relative risk (RR) with 95% confidence interval (CI). Lung cancer incidence and mortality were estimated using extended Cox models for time-dependent covariates, yielding the respective hazard ratios (HR). Clinicaltrials.gov ID: NCT02247453. Findings: With a median follow-up of 8.5 years, the full study set included 1403 indeterminate LDCT (CTind) and 584 positive LDCT (CT+) results. A lung cancer RR increase in MSC+ compared to MSC- participants was observed in both the CTind (RR: 2.5; 95% CI: 1.4-4.32) and CT+ (RR: 2.6; 95% CI: 1.81-3.74) groups and was maintained when considering stage I or resectable tumors only. A 98% negative predictive value in CTind/MSC- and a 30% positive predictive value in CT+/MSC+ lesions were recorded. At seven years' follow-up, MSC+ participants had a cumulative HR of 4.4 (95% CI: 3.0-6.4) for lung cancer incidence and of 8.1 (95% CI: 2.7-24.5) for lung cancer mortality. Interpretation: Our study shows that MSC can be reliably performed during LDCT screening rounds to increase the accuracy of lung cancer risk and mortality prediction and supports its clinical utility in the management of LDCT findings of uncertain malignancy. Funding: Italian Association for Cancer Research; Italian Ministry of Health; Horizon2020; National Cancer Institute (NCI); Gensignia LifeScience.

Detection of (pre)cancerous colorectal lesions in Lynch syndrome patients by microsatellite instability liquid biopsy.

Lynch syndrome (LS) is an inherited condition characterized by an increased risk of developing cancer, in particular colorectal cancer (CRC). Microsatellite instability (MSI) is the main feature of (pre)cancerous lesions occurring in LS patients. Close endoscopic surveillance is the only option available to reduce CRC morbidity and mortality. However, it may fail to intercept interval cancers and patients' compliance to such an invasive procedure may decrease over the years. The development of a minimally invasive test able to detect (pre)cancerous colorectal lesions, could thus help tailor surveillance programs in LS patients. Taking advantage of an endoscopic surveillance program, we retrospectively assessed the instability of five microsatellites (BAT26, BAT25, NR24, NR21, and Mono27) in liquid biopsies collected at baseline and possibly at two further endoscopic rounds. For this purpose, we tested a new multiplex drop-off digital polymerase chain reaction (dPCR) assay, reaching mutant allele frequencies (MAFs) as low as 0.01%. Overall, 78 plasma samples at the three time-points from 18 patients with baseline (pre)cancerous lesions and 18 controls were available for molecular analysis. At baseline, the MAFs of BAT26, BAT25 and NR24 were significantly higher in samples of patients with lesions but did not differ with respect to the grade of dysplasia or any other clinico-pathological characteristics. When all markers were combined to determine MSI in blood, this test was able to discriminate lesion-bearing patients with an AUC of 0.80 (95%CI: 0.66; 0.94).

Development of a Molecular Blood-Based Immune Signature Classifier as Biomarker for Risks Assessment in Lung Cancer Screening.

BACKGROUND: Low-dose CT (LDCT) screening trials have shown that lung cancer early detection saves lives. However, a better stratification of the screening population is still needed. In this respect, we generated and prospectively validated a plasma miRNA signature classifier (MSC) able to categorize screening participants according to lung cancer risk. Here, we aimed to deeply characterize the peripheral immune profile and develop a diagnostic immune signature classifier to further implement blood testing in lung cancer screening. METHODS: Peripheral blood mononuclear cell (PBMC) samples collected from 20 patients with LDCT-detected lung cancer and 20 matched cancer-free screening volunteers were analyzed by flow cytometry using multiplex panels characterizing both lymphoid and myeloid immune subsets. Data were validated in PBMC from 40 patients with lung cancer and 40 matched controls and in a lung cancer specificity set including 27 subjects with suspicious lung nodules. A qPCR-based gene expression signature was generated resembling selected immune subsets. RESULTS: Monocytic myeloid-derived suppressor cell (MDSC), polymorphonuclear MDSC, intermediate monocytes and CD8+PD-1+ T cells distinguished patients with lung cancer from controls with AUCs values of 0.94/0.72/0.88 in the training, validation, and lung cancer specificity set, respectively. AUCs raised up to 1.00/0.84/0.92 in subgroup analysis considering only MSC-negative subjects. A 14-immune genes expression signature distinguished patients from controls with AUC values of 0.76 in the validation set and 0.83 in MSC-negative subjects. CONCLUSIONS: An immune-based classifier can enhance the accuracy of blood testing, thus supporting the contribution of systemic immunity to lung carcinogenesis. IMPACT: Implementing LDCT screening trials with minimally invasive blood tests could help reduce unnecessary procedures and optimize cost-effectiveness.

A Cross-Comparison of High-Throughput Platforms for Circulating MicroRNA Quantification, Agreement in Risk Classification, and Biomarker Discovery in Non-Small Cell Lung Cancer.

Background: Circulating microRNAs (ct-miRs) are promising cancer biomarkers. This study focuses on platform comparison to assess performance variability, agreement in the assignment of a miR signature classifier (MSC), and concordance for the identification of cancer-associated miRs in plasma samples from non-small cell lung cancer (NSCLC) patients. Methods: A plasma cohort of 10 NSCLC patients and 10 healthy donors matched for clinical features and MSC risk level was profiled for miR expression using two sequencing-based and three quantitative reverse transcription PCR (qPCR)-based platforms. Intra- and inter-platform variations were examined by correlation and concordance analysis. The MSC risk levels were compared with those estimated using a reference method. Differentially expressed ct-miRs were identified among NSCLC patients and donors, and the diagnostic value of those dysregulated in patients was assessed by receiver operating characteristic curve analysis. The downregulation of miR-150-5p was verified by qPCR. The Cancer Genome Atlas (TCGA) lung carcinoma dataset was used for validation at the tissue level. Results: The intra-platform reproducibility was consistent, whereas the highest values of inter-platform correlations were among qPCR-based platforms. MSC classification concordance was >80% for four platforms. The dysregulation and discriminatory power of miR-150-5p and miR-210-3p were documented. Both were significantly dysregulated also on TCGA tissue-originated profiles from lung cell carcinoma in comparison with normal samples. Conclusion: Overall, our studies provide a large performance analysis between five different platforms for miR quantification, indicate the solidity of MSC classifier, and identify two noninvasive biomarkers for NSCLC.

Cytisine Therapy Improved Smoking Cessation in the Randomized Screening and Multiple Intervention on Lung Epidemics Lung Cancer Screening Trial.

INTRODUCTION: Cytisine, a partial agonist-binding nicotine acetylcholine receptor, is a promising cessation intervention. We conducted a single-center, randomized, controlled trial (RCT) in Italy to assess the efficacy and tolerability of cytisine as a smoking cessation therapy among lung cancer screening participants. METHODS: From July 2019 to March 2020, the Screening and Multiple Intervention on Lung Epidemics RCT enrolled 869 current heavy tobacco users in a low-dose computed tomography screening program, with a randomized comparison of pharmacologic intervention with cytisine plus counseling (N = 470) versus counseling alone (N = 399). The primary outcome was continuous smoking abstinence at 12 months, biochemically verified through carbon monoxide measurement. RESULTS: At the 12-month follow-up, the quit rate was 32.1% (151 participants) in the intervention arm and 7.3% (29 participants) in the control arm. The adjusted OR of continuous abstinence was 7.2 (95% confidence interval: 4.6-11.2). Self-reported adverse events occurred more frequently in the intervention arm (399 events among 196 participants) than in the control arm (230 events among 133 participants, p < 0.01). The most common adverse events were gastrointestinal symptoms, comprising abdominal swelling, gastritis, and constipation. CONCLUSIONS: The efficacy and safety observed in the Screening and Multiple Intervention on Lung Epidemics RCT indicate that cytisine, a very low-cost medication, is a useful treatment option for smoking cessation and a feasible strategy to improve low-dose computed tomography screening outcomes with a potential benefit for all-cause mortality.

MiR-486-5p Targets CD133+ Lung Cancer Stem Cells through the p85/AKT Pathway.

Despite improvements in therapies and screening strategies, lung cancer prognosis still remains dismal, especially for metastatic tumors. Cancer stem cells (CSCs) are endowed with properties such as chemoresistance, dissemination, and stem-like features, that make them one of the main causes of the poor survival rate of lung cancer patients. MicroRNAs (miRNAs), small molecules regulating gene expression, have a role in lung cancer development and progression. In particular, miR-486-5p is an onco-suppressor miRNA found to be down-modulated in the tumor tissue of lung cancer patients. In this study, we investigate the role of this miRNA in CD133+ lung CSCs and evaluate the therapeutic efficacy of coated cationic lipid-nanoparticles entrapping the miR-486-5p miRNA mimic (CCL-486) using lung cancer patient-derived xenograft (PDX) models. In vitro, miR-486-5p overexpression impaired the PI3K/Akt pathway and decreased lung cancer cell viability. Moreover, miR-486-5p overexpression induced apoptosis also in CD133+ CSCs, thus affecting the in vivo tumor-initiating properties of these cells. Finally, we demonstrated that in vivo CCL-486 treatment decreased CD133+ percentage and inhibited tumor growth in PDX models. In conclusion, we provided insights on the efficacy of a novel miRNA-based compound to hit CD133+ lung CSCs, setting the basis for new combined therapeutic strategies.

Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy.

(1) Background: In advanced non-small cell lung cancer (aNSCLC), programmed death ligand 1 (PD-L1) remains the only biomarker for candidate patients to immunotherapy (IO). This study aimed at using artificial intelligence (AI) and machine learning (ML) tools to improve response and efficacy predictions in aNSCLC patients treated with IO. (2) Methods: Real world data and the blood microRNA signature classifier (MSC) were used. Patients were divided into responders (R) and non-responders (NR) to determine if the overall survival of the patients was likely to be shorter or longer than 24 months from baseline IO. (3) Results: One-hundred sixty-four out of 200 patients (i.e., only those ones with PD-L1 data available) were considered in the model, 73 (44.5%) were R and 91 (55.5%) NR. Overall, the best model was the linear regression (RL) and included 5 features. The model predicting R/NR of patients achieved accuracy ACC = 0.756, F1 score F1 = 0.722, and area under the ROC curve AUC = 0.82. LR was also the best-performing model in predicting patients with long survival (24 months OS), achieving ACC = 0.839, F1 = 0.908, and AUC = 0.87. (4) Conclusions: The results suggest that the integration of multifactorial data provided by ML techniques is a useful tool to select NSCLC patients as candidates for IO.

Circulating Fatty Acid Profile as a Biomarker for Immunotherapy in Advanced Non-Small Cell Lung Cancer.

INTRODUCTION: Lipid metabolism impacts immune cell differentiation, activation, and functions, modulating inflammatory mediators, energy homeostasis, and cell membrane composition. Despite preclinical evidence, data in humans lack concerning tumors and immunotherapy (IO). We aimed at investigating the correlations between circulating lipids and the outcome of non-small cell lung cancer (NSCLC) patients treated with IO. MATERIALS AND METHODS: We identified all patients with advanced NSCLC treated with IO at our Institution with available baseline plasma samples. Fatty acids (FAs) were analyzed through gas chromatography. Survival curves were estimated by the Kaplan-Meier method. Cox multivariate models were constructed through a stepwise procedure, with entry and exit P value set at .2. RESULTS: We identified 112 patients, mostly with performance status 1 (65.2%) and PD-L1≥1% (75.3%). Median progression-free survival (PFS) and overall survival (OS) were 2.8 and 11.0 months, respectively. Multivariable model for survival identified a positive association of circulating free (FFA) C16:0 (P .005) and esterified (EFA) C16:1 (P .030) with PFS, and a positive association of EFA C16:1 (P .001) and EFA C18:0 (P .020) with OS. EFA C16:0 was negatively associated with PFS (P .008). CONCLUSION: FFA C16:0 and FAs derived from its unsaturation (EFA C16:1) and elongation (EFA C18:0) are associated with a better outcome in NSCLC patients treated with IO. It is conceivable that the ratio among those FAs may modify membrane fluidity and receptor activity, influencing IO efficacy. These data pave the way for the investigation of lipid-modulating strategies in association with IO in NSCLC.

Timeline of SARS-CoV-2 Spread in Italy: Results from an Independent Serological Retesting.

The massive emergence of COVID-19 cases in the first phase of pandemic within an extremely short period of time suggest that an undetected earlier circulation of SARS-CoV-2 might have occurred. Given the importance of this evidence, an independent evaluation was recommended by the World Health Organization (WHO) to test a subset of samples selected on the level of positivity in ELISA assays (positive, low positive, negative) detected in our previous study of prepandemic samples collected in Italy. SARS-CoV-2 antibodies were blindly retested by two independent centers in 29 blood samples collected in the prepandemic period in Italy, 29 samples collected one year before and 11 COVID-19 control samples. The methodologies used included IgG-RBD/IgM-RBD ELISA assays, a qualitative micro-neutralization CPE-based assay, a multiplex IgG protein array, an ELISA IgM kit (Wantai), and a plaque-reduction neutralization test. The results suggest the presence of SARS-CoV-2 antibodies in some samples collected in the prepandemic period, with the oldest samples found to be positive for IgM by both laboratories collected on 10 October 2019 (Lombardy), 11 November 2019 (Lombardy) and 5 February 2020 (Lazio), the latter with neutralizing antibodies. The detection of IgM and/or IgG binding and neutralizing antibodies was strongly dependent on the different serological assays and thresholds employed, and they were not detected in control samples collected one year before. These findings, although gathered in a small and selected set of samples, highlight the importance of harmonizing serological assays for testing the spread of the SARS-CoV-2 virus and may contribute to a better understanding of future virus dynamics.

Unexpected detection of SARS-CoV-2 antibodies in the prepandemic period in Italy.

There are no robust data on the real onset of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and spread in the prepandemic period worldwide. We investigated the presence of SARS-CoV-2 receptor-binding domain (RBD)-specific antibodies in blood samples of 959 asymptomatic individuals enrolled in a prospective lung cancer screening trial between September 2019 and March 2020 to track the date of onset, frequency, and temporal and geographic variations across the Italian regions. SARS-CoV-2 RBD-specific antibodies were detected in 111 of 959 (11.6%) individuals, starting from September 2019 (14%), with a cluster of positive cases (>30%) in the second week of February 2020 and the highest number (53.2%) in Lombardy. This study shows an unexpected very early circulation of SARS-CoV-2 among asymptomatic individuals in Italy several months before the first patient was identified, and clarifies the onset and spread of the coronavirus disease 2019 (COVID-19) pandemic. Finding SARS-CoV-2 antibodies in asymptomatic people before the COVID-19 outbreak in Italy may reshape the history of pandemic.

LKB1 Down-Modulation by miR-17 Identifies Patients With NSCLC Having Worse Prognosis Eligible for Energy-Stress-Based Treatments.

INTRODUCTION: Preclinical models recently unveiled the vulnerability of LKB1/KRAS comutated NSCLC to metabolic stress-based treatments. Because miR-17 is a potential epigenetic regulator of LKB1, we hypothesized that wild-type LKB1 (LKB1WT) NSCLC with high miR-17 expression may be sensitive to an energetic stress condition, and eligible for metabolic frailties-based therapeutic intervention. METHODS: We took advantage of NSCLC cell lines with different combinations of KRAS mutation and LKB1 deletion and of patient-derived xenografts (PDXs) with high (LKB1WT/miR-17 high) or low (LKB1WT/miR-17 low) miR-17 expression. We evaluated LKB1 pathway impairment and apoptotic response to metformin. We retrospectively evaluated LKB1 and miR-17 expression levels in tissue specimens of patients with NSCLC and PDXs. In addition, a lung cancer series from The Cancer Genome Atlas data set was analyzed for miR-17 expression and potential correlation with clinical features. RESULTS: We identified miR-17 as an epigenetic regulator of LKB1 in NSCLC and confirmed targeting of miR-17 to LKB1 3' untranslated region by luciferase reporter assay. We found that miR-17 overexpression functionally impairs the LKB1/AMPK pathway. Metformin treatment prompted apoptosis on miR-17 overexpression only in LKB1WT cell lines, and in LKB1WT/miR-17 high PDXs. A retrospective analysis in patients with NSCLC revealed an inverse correlation between miR-17 and LKB1 expression and highlighted a prognostic role of miR-17 expression in LKB1WT patients, which was further confirmed by The Cancer Genome Atlas data analysis. CONCLUSIONS: We identified miR-17 as a mediator of LKB1 expression in NSCLC tumors. This study proposes a miR-17 expression score potentially exploitable to discriminate LKB1WT patients with NSCLC with impaired LKB1 expression and poor outcome, eligible for energy-stress-based treatments.

Improved Prognostic Prediction in Never-Smoker Lung Cancer Patients by Integration of a Systemic Inflammation Marker with Tumor Immune Contexture Analysis.

Almost 25% of lung cancers (LCs) occur in never-smokers. LC inflammatory profile, based on plasma C-reactive protein levels (CRP), predicts mortality, independently by smoking-status. We hypothesized that: CRP could be associated with tumor immune contexture (TIC) in never-smokers and both these two parameters may improve their prognosis. Sixty-eight never-smokers LC patients with high or low CRP were selected. The programmed cell death protein 1 (PD-1) and its ligand (PD-L1), the human leukocyte antigens (HLA-DR and HLA-I), CD8, CD4, CD3, CD33, CD163, and CD68 were evaluated by immunohistochemistry on surgical samples given TIC evaluation. The classification model based on TIC scores was generated by Classification and Regression Tree analysis. Tumor mutational burden was evaluated by targeted next-generation sequencing. Exclusively high CRP (H-CRP) subset showed PD-L1 expression in 35% of LC as well as lower HLA-I and HLA-DR in their stromal cells. CD3, CD4, CD8, HLA-I, HLA-DR tumor cells staining were associated with a "low inflammatory profile" subset. CRP and LC immune profiles drive clinical outcome: 5-year survival 88% against 8% was associated with low and high-risk profiles (p < 0.0001). Clinical outcome prediction in never-smoker LC patients may be improved by both CRP and tumor immune contexture evaluation.

Integrating clinical and biological prognostic biomarkers in patients with advanced NSCLC treated with immunotherapy: the DEMo score system.

BACKGROUND: Several biomarkers have been separately described to select patients for immunotherapy (IO), but few studies integrate these markers. Di Maio, EPSILoN and the plasma microRNA signature classifier (MSC), are three different clinico, biochemical and molecular markers able to independently predict prognosis in non-small cell lung cancer (NSCLC). METHODS: Complete data such as sex, histology, ECOG-PS, stage, smoking status, presence of liver metastasis, LDH and neutrophils-to-lymphocyte ratio were collected to generate Di Maio and EPSILoN. The MSC risk level was prospectively assessed in plasma samples collected at baseline IO. The 3 markers were integrated into the DEMo score system prospectively tested in a cohort of 200 advanced NSCLC patients treated with IO. Endpoints were overall survival (OS), progression-free survival (PFS) and overall response rate (ORR). RESULTS: DEMo separated patients in 7-risk groups whose median OS had a trend ranging from 29.7 to 1.5 months (P<0.0001). When comparing patients with the lowest (n=29) and the highest (n=35) DEMo scores ORR was 45% and 3%, respectively (P<0.0001). Considering the 53 PD-L1 ≥50% patients, DEMo identified a group of 13 (25%) patients who benefit less from IO in terms of both OS (HR: 8.81; 95% CI: 2.87-20.01) and PFS (HR: 6.82; 95% CI: 2.57-18.10). Twelve out of 111 (11%) patients who most benefit from IO according to OS (HR: 0.21; 95% CI: 0.07-0.62) and PFS (HR: 0.28; 95% CI: 0.12-0.65) were identified by DEMo in the PD-L1 <50% group. CONCLUSIONS: The DEMo prognostic score system stratified NSCLC patients treated with IO better than each single marker. The proper use of DEMo according to PD-L1 could improve selection in IO regimens.

Exo-miRNAs as a New Tool for Liquid Biopsy in Lung Cancer.

Lung cancer is the predominant cause of cancer-related deaths. The high mortality rates are mainly due to the lack of diagnosis before the cancer is at a late stage. Liquid biopsy is a promising technique that could allow early diagnosis of lung cancer and better treatment selection for patients. Cell-free microRNAs have been detected in biological fluids, such as serum and plasma, and are considered interesting biomarkers for lung cancer screening and detection. Exosomes are nanovesicles of 30-150 nm and can be released by different cell types within the tumor microenvironment. Their exosomal composition reflects that of their parental cells and could be potentially useful as a biomarker for lung cancer diagnosis. This review summarizes the state-of-the-art of circulating microRNAs (miRNAs) in lung cancer, focusing on their potential use in clinical practice. Moreover, we describe the importance of exosomal miRNA cargo in lung cancer detection and their potential role during lung carcinogenesis. Finally, we discuss our experience with the analysis of circulating exosomal miRNAs in the bioMILD screening trial.

Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges.

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 next-generation sequencing into study of circulating DNA. We also underline the importance of integrating different molecular technologies together with imaging, radiomics, and artificial intelligence. We list a number of completed, ongoing, or planned trials to show the clinical utility of molecular biomarkers. Finally, we comment on future research challenges in the field of biomarkers in the context of lung cancer screening and propose a design of a trial to test the clinical utility of one or several candidate biomarkers.