MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening

Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities

Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.

Emerging role of miR-320a in lung cancer: a comprehensive review

A specialized biomarker(s) for lung cancer is imperative owing to its high mortality. Continuing our earlier work demonstrating the role of miR-320a as a tumor suppressor, here we discuss the most recent updates on miR-320a in lung cancer pathogenesis. We found that miR-320a modulates levels of diverse cancer-associated molecules and signaling pathways, and is also involved in modulating the immune microenvironment of lung cancer during its pathogenesis. We also discuss how miR-320a encapsulated in exosomes inhibits invasive phenotypes of lung cancer. Therefore, based on the multimodal role of miR-320a in lung cancer development and progression, we believe that miR-320a may be utilized as a potential diagnostic/prognostic marker and therapeutic target for lung cancer patients.

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.

Micro-RNAs Predict Response to Systemic Treatments in Metastatic Renal Cell Carcinoma Patients: Results from a Systematic Review of the Literature

Locally advanced or metastatic renal cell carcinomas (mRCCs) account for up to 15% of all kidney cancer diagnoses. Systemic therapies (with or without surgery) represent gold standard treatments, mostly based on tyrosine kinase inhibitors in association with immunotherapy. We provide an overview of the current knowledge of miRNAs as predictors of treatment resistance. A systematic review of the literature was carried out in January 2022 following the PICO methodology. Overall, we included seven studies—four testing plasmatic miRNAs, two exosomal miRNAs, and one urinary miRNA. A total of 789 patients were included (354 for plasmatic miRNAs, 366 for urinary miRNAs, and 69 for exosomal miRNAs). Several miRNAs were tested within the included studies, but six plasmatic (miR9-5-p¸ miR-192, miR193-3p, miR-501-3p¸ miR-221, miR-376b-3p) one urinary (miR-30a-5p), and three exosomal (miR-35-5p, miR-301a-3p, miR-1293) were associated with resistance to systemic treatments or treatment failure in mRCC patients. Results showed a fair accuracy of these biomarkers in predicting treatment resistance and overall survival. However, to date, the biomarkers tested have not been validated and their clinical uses are not recommended. Nevertheless, the literature results are encouraging; future large clinical trials are warranted to validate the effectiveness of these tools in clinical decision-making.

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

Simple Summary

In this paper, the authors show that artificial intelligence (AI) and machine learning (ML) are useful approaches to integrate multifactorial data and helpful for personalized prediction. In detail, compared to PD-L1 for advanced non-small cell lung cancer (NSCLC), ML tools predicted better responder (R) and non-responder (NR) patients to immunotherapy (IO). It was also able to indirectly foresee OS and PFS of R and NR patients. Given the high incidence of NSCLC, and the absence of reliable biomarkers to predict the response to IO other than PD-L1, the authors believe this research may be of great interest to anyone involved in thoracic oncology. Furthermore, given the growing interest from the scientific community in AI and ML, the authors believe that this manuscript could represent a fascinating topic to anyone who needs to exploit the enormous potential of these tools in the treatment of cancer.

Abstract

(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.

miR-519d-3p suppresses tumorigenicity and metastasis by inhibiting Bcl-w and HIF-1α in NSCLC

Bcl-w, a member of the Bcl-2 family, is highly expressed in various solid tumor, including lung cancer, suggesting that it is involved in cancer cell survival and carcinogenesis. Solid cancer-induced hypoxia has been reported to increase angiogenesis, growth factor, gene instability, invasion, and metastasis. Despite many studies on the treatment of non-small cell lung cancer (NSCLC) with a high incidence rate, the survival rate of patients has not improved because the cancer cells acquired resistance to treatment. This study investigated the correlation between Bcl-w expression and hypoxia in tumor malignancy of NSCLC. Meanwhile, microRNAs (miRNAs) are involved in a variety of key signaling mechanisms associated with hypoxia. Therefore, we discovered miR-519d-3p, which inhibits the expression of Bcl-w and hypoxia-inducing factor (HIF)-1α, and found that it reduces hypoxia-induced tumorigenesis. Spearman's correlation analysis showed that the expression levels of miR-519d-3p and Bcl-w/HIF-1α were negatively correlated, respectively. This showed that miR-519d-3p can be used as a diagnostic biomarker and target therapy for NSCLC.

Longitudinal Circulating Levels of miR-23b-3p, miR-126-3p and lncRNA GAS5 in HCC Patients Treated with Sorafenib

Human hepatocellular carcinoma (HCC) is the most frequent primary tumor of the liver and the third cause of cancer-related deaths. The multikinase inhibitor sorafenib is a systemic drug for unresectable HCC. The identification of molecular biomarkers for the early diagnosis of HCC and responsiveness to treatment are needed. In this work, we performed an exploratory study to investigate the longitudinal levels of cell-free long ncRNA GAS5 and microRNAs miR-126-3p and -23b-3p in a cohort of 7 patients during the period of treatment with sorafenib. We used qPCR to measure the amounts of GAS5 and miR-126-3p and droplet digital PCR (ddPCR) to measure the levels of miR-23b-3p. Patients treated with sorafenib displayed variable levels of GAS5, miR-126-3p and miR-23b-3p at different time-points of follow-up. miR-23b-3p was further measured by ddPCR in 37 healthy individuals and 25 untreated HCC patients. The amount of miR-23b-3p in the plasma of untreated HCC patients was significantly downregulated if compared to healthy individuals. The ROC curve analysis underlined its diagnostic relevance. In conclusion, our results highlight a potential clinical significance of circulating miR-23b-3p and an exploratory observation on the longitudinal plasmatic levels of GAS5, miR-126-3p and miR-23b-3p during sorafenib treatment.

The Role of Liquid Biopsy in Early Diagnosis of Lung Cancer

Liquid biopsy is an emerging technology with a potential role in the screening and early detection of lung cancer. Several liquid biopsy-derived biomarkers have been identified and are currently under ongoing investigation. In this article, we review the available data on the use of circulating biomarkers for the early detection of lung cancer, focusing on the circulating tumor cells, circulating cell-free DNA, circulating micro-RNAs, tumor-derived exosomes, and tumor-educated platelets, providing an overview of future potential applicability in the clinical practice. While several biomarkers have shown exciting results, diagnostic performance and clinical applicability is still limited. The combination of different biomarkers, as well as their combination with other diagnostic tools show great promise, although further research is still required to define and validate the role of liquid biopsies in clinical practice.

Evidence that dysplasia related microRNAs in Barrett's esophagus target PD-L1 expression and contribute to the development of esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) is the cancer arising from the esophagus, which frequently develop from Barrett's esophagus (BE). Extracellular vesicles (EVs), particularly exosomes, are nanosized vesicles of endosomal origin released from various types of cells that have been implicated in cancers. However, the significance of circulating exosomes during the progression of BE to EAC remains unknown. Sera exosmal microRNAs were profiled from 13 EAC and 12BE patients compared to 12 healthy controls. We found a substantial dysregulation of exosomal miRNA levels in BE compared to healthy control, and identified a unique signature of 24 up regulated and 14 down regulated miRNAs. Further validation showed exosomal miR-196a, -26b, -21, and -143 expression was significantly higher in BE and continued to have higher levels in EAC compared to healthy controls; while sera exosomal miR-378, -210, -205, and -200c-3p were significantly lower expressed in BE patients compared to compared to controls. Further, miR-378, -210, -205, and -200c-3p continue to have even lower levels in EAC patients compared to BE. Interestingly, sera expression levels of exosomal miR-15a, -16, and -193a-3p were significantly down regulated in BE PD-L1(+) patients; Sera exosomal miR-15a, -15b, -16, and -193a-3p expression levels in EAC PD-L1(+) patients were significantly lower (all p < 0.01) when compared to EAC PD-L1(-) patients. More importantly, the BE-EAC group had longitudinally decreased exosomal expression levels of miR-15a, -15b, -16, and -193a-3p from BE status to their EAC progression. In conclusion, distinct microRNA expression patterns were demonstrated in circulating exosomes from Barrett's esophagus and esophageal adenocarcinoma; Furthermore exosomal microRNAs potentially targeting PD-L1 mRNA were down regulated in PD-L1 (+) BE and EAC patients.

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.

Novel visualized quantitative epigenetic imprinted gene biomarkers diagnose the malignancy of ten cancer types

Background

Epigenetic alterations are involved in most cancers, but its application in cancer diagnosis is still limited. More practical and intuitive methods to detect the aberrant expressions from clinical samples using highly sensitive biomarkers are needed. In this study, we developed a novel approach in identifying, visualizing, and quantifying the biallelic and multiallelic expressions of an imprinted gene panel associated with cancer status. We evaluated the normal and aberrant expressions measured using the imprinted gene panel to formulate diagnostic models which could accurately distinguish the imprinting differences of normal and benign cases from cancerous tissues for each of the ten cancer types.

Results

The Quantitative Chromogenic Imprinted Gene In Situ Hybridization (QCIGISH) method developed from a 1013-case study which provides a visual and quantitative analysis of non-coding RNA allelic expressions identified the guanine nucleotide-binding protein, alpha-stimulating complex locus (GNAS), growth factor receptor-bound protein (GRB10), and small nuclear ribonucleoprotein polypeptide N (SNRPN) out of five tested imprinted genes as efficient epigenetic biomarkers for the early-stage detection of ten cancer types. A binary algorithm developed for cancer diagnosis showed that elevated biallelic expression (BAE), multiallelic expression (MAE), and total expression (TE) measurements for the imprinted gene panel were associated with cell carcinogenesis, with the formulated diagnostic models achieving consistently high sensitivities (91–98%) and specificities (86–98%) across the different cancer types.

Conclusions

The QCIGISH method provides an innovative way to visually assess and quantitatively analyze individual cells for cancer potential extending from hyperplasia and dysplasia until carcinoma in situ and invasion, which effectively supplements standard clinical cytologic and histopathologic diagnosis for early cancer detection. In addition, the diagnostic models developed from the BAE, MAE, and TE measurements of the imprinted gene panel GNAS, GRB10, and SNRPN could provide important predictive information which are useful in early-stage cancer detection and personalized cancer management.

Plasma Next Generation Sequencing and Droplet Digital-qPCR-Based Quantification of Circulating Cell-Free RNA for Noninvasive Early Detection of Cancer

Early detection of cancer holds high promise for reducing cancer-related mortality. Detection of circulating tumor-specific nucleic acids holds promise, but sensitivity and specificity issues remain with current technology. We studied cell-free RNA (cfRNA) in patients with non-small cell lung cancer (NSCLC; n = 56 stage IV, n = 39 stages I-III), pancreatic cancer (PDAC, n = 20 stage III), malignant melanoma (MM, n = 12 stage III-IV), urothelial bladder cancer (UBC, n = 22 stage II and IV), and 65 healthy controls by means of next generation sequencing (NGS) and real-time droplet digital PCR (RT-ddPCR). We identified 192 overlapping upregulated transcripts in NSCLC and PDAC by NGS, more than 90% of which were noncoding. Previously reported transcripts (e.g., HOTAIRM1) were identified. Plasma cfRNA transcript levels of POU6F2-AS2 discriminated NSCLC from healthy donors (AUC = 0.82 and 0.76 for stages IV and I-III, respectively) and significantly associated (p = 0.017) with the established tumor marker Cyfra 21-1. cfRNA yield and POU6F2-AS transcript abundance discriminated PDAC patients from healthy donors (AUC = 1.0). POU6F2-AS2 transcript was significantly higher in MM (p = 0.044). In summary, our findings support further validation of cfRNA detection by RT-ddPCR as a biomarker for early detection of solid cancers.

Noncoding RNAs and Liquid Biopsy in Lung Cancer: A Literature Review

Lung cancer represents a genetically heterogeneous disease with low survival rates. Recent data have evidenced key roles of noncoding RNAs in lung cancer initiation and progression. These functional RNA molecules that can act as both oncogenes and tumor suppressors may become future biomarkers and more efficient therapeutic targets. In the precision medicine era, circulating nucleic acids have the potential to reshape the management and prognosis of cancer patients. Detecting genomic alterations and level variations of circulating nucleic acids in liquid biopsy samples represents a noninvasive method for portraying tumor burden. Research is currently trying to validate the potential role of liquid biopsy in lung cancer screening, prognosis, monitoring of disease progression, and treatment response. However, this method requires complex detection assays, and implementation of plasma genotyping in clinical practice continues to be hindered by discrepancies that arise when compared to tissue genotyping. Understanding the genomic landscape of lung cancer is essential in order to provide useful and innovative research in the age of patient-tailored therapy. In this landscape, the noncoding RNAs play a crucial role due to their target genes that dramatically influence the tumor microenvironment and the response to therapy. This article addresses present and future possible roles of liquid biopsy in lung cancer. It also discusses how the complex role of noncoding RNAs in lung tumorigenesis could influence the management of this pathology.

Microfluidic epigenomic mapping technologies for precision medicine

Epigenomic mapping of tissue samples generates critical insights into genome-wide regulations of gene activities and expressions during normal development and disease processes. Epigenomic profiling using a low number of cells produced by patient and mouse samples presents new challenges to biotechnologists. In this review, we first discuss the rationale and premise behind profiling epigenomes for precision medicine. We then examine the existing literature on applying microfluidics to facilitate low-input and high-throughput epigenomic profiling, with emphasis on technologies enabling interfacing with next-generation sequencing. We detail assays on studies of histone modifications, DNA methylation, 3D chromatin structures and non-coding RNAs. Finally, we discuss what the future may hold in terms of method development and translational potential.

Analysis of circulating non-coding RNAs in a non-invasive and cost-effective manner

Non-coding RNAs (ncRNAs) participate in regulation of gene expression, and are highly relevant to pathological development. They are found to be stably present in diverse body fluids, including those in the circulatory system, which can be sampled non-invasively for clinical tests. Thus, circulating ncRNAs have great potential to be disease biomarkers. However, tremendous efforts are desired to discover and utilize ncRNAs as biomarkers in clinical diagnosis, calling for technological advancement in analysis of circulating ncRNAs in biospecimens. Hence, this review summarizes the recent developments in this area, highlighting the works devoted to cancer diagnosis and prognosis. Three main directions are focused: 1) Extraction and purification of ncRNAs from body fluids; 2) Quantification of the purified circulating ncRNAs; and 3) Microfluidic platforms for integration of both steps to enable point-of-care diagnostics. These technologies have laid a solid foundation to move forward the applications of circulating ncRNAs in disease diagnosis and cure.

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.

Circulating MicroRNA Biomarkers for Lung Cancer Detection in East Asian Populations

BACKGROUND

Lung cancer (LC) is the leading cause of cancer-related death in Eastern Asia. The prognosis of LC highly depends on tumor stages and early detection could substantially reduce LC mortality. Accumulating evidence suggested that circulating miRNAs in plasma or serum may have applications in early LC detection. We thus conducted a systematic literature review on the diagnostic value of miRNAs markers for LC in East Asian populations.

METHODS

PubMed and ISI Web of Knowledge were searched to retrieve relevant articles published up to 17 September 2018. Information on study design, population characteristics, investigated miRNAs and diagnostic accuracy (including sensitivity, specificity and area under the curve (AUC)) were independently extracted by two reviewers.

RESULTS

Overall, 46 studies that evaluated a total of 88 miRNA markers for LC diagnosis in East Asian populations were identified. Sixteen of the 46 studies have incorporated individual miRNA markers as panels (with 2⁻20 markers). Three promising miRNA panels with ≥90% sensitivity and ≥90% specificity were discovered, two of which were externally validated. Diagnostic performance of circulating miRNAs in East Asian populations was comparable to previously summarized performance in Western populations. Forty-four miRNAs were reported in both populations. No major differences in diagnostic performance by ethnicity of the same miRNA was observed.

CONCLUSIONS

Circulating miRNAs or miRNA panels, possibly in combination with other promising molecular markers including epigenetic and genetic markers, may be promising candidates for noninvasive LC early detection. However, large studies with samples collected prospectively in true screening settings are required to validate the promising markers or marker panels.

Circulating microRNA-21 is an early predictor of ROS-mediated damage in subjects with high risk of developing diabetes and in drug-naïve T2D

BACKGROUND

Impaired glucose tolerance (IGT) is a risk factor for the development of diabetes and related complications that ensue. Early identification of at-risk individuals might be beneficial to reduce or delay the progression of diabetes and its related complications. Recently, microRNAs emerged as potential biomarkers of diseases. The aim of the present study was to evaluate microRNA-21 as a potential biomarker for the risk of developing diabetes in adults with IGT and to investigate its downstream effects as the generation of reactive oxygen species (ROS), the induction of manganese-superoxide dismutase-2 (SOD2), and the circulating levels of 4-HNE (4-hydroxynonenal).

METHODS

To evaluate the prognostic and predictive values of plasmatic microRNA-21 in identifying metabolic derangements, we tested a selected cohort (n = 115) of subjects enrolled in the DIAPASON Study, whom were selected on ADA criteria for 2hPG. Statistical analysis was performed using ANOVA or the Kruskal-Wallis test as appropriate. ROC curves were drawn for diagnostic accuracy of the tests; positive and negative predictive values were performed, and Youden's index was used to seek the cut-off optimum truncation point. ROS, SOD2 and 4-HNE were also evaluated.

RESULTS

We observed significant upregulation of microRNA-21 in IGT and in T2D subjects, and microRNA-21 was positively correlated with glycaemic parameters. Diagnostic performance of microRNA-21 was high and accurate. We detected significant overproduction of ROS by electron paramagnetic resonance (EPR), significant accumulation of the lipid peroxidation marker 4-HNE, and defective SOD2 antioxidant response in IGT and newly diagnosed, drug-naïve T2D subjects. In addition, ROC curves demonstrated the diagnostic accuracy of markers used.

CONCLUSIONS

our data demonstrate that microRNA-21 is associated with prediabetic status and exhibits predictive value for early detection of glucose imbalances. These data could provide novel clues for miR-based biomarkers to evaluate diabetes.

Circulating miRNAs and PD-L1 Tumor Expression Are Associated with Survival in Advanced NSCLC Patients Treated with Immunotherapy: a Prospective Study

PURPOSE

Immune-checkpoint inhibitors (ICI) have improved the survival of patients with non-small cell lung cancer (NSCLC). However, only a subset of patients benefit from ICIs, and the role of PD-L1 as predictive biomarker is still debated. A plasma immune-related miRNA-signature classifier (MSC) was established in lung cancer screening settings to identify the lethal form of the disease in early stages. In this exploratory study, we tested the efficacy of the MSC as prognostic marker in patients with advanced NSCLC treated with ICIs.

EXPERIMENTAL DESIGN

The MSC risk level was prospectively assessed in a consecutive series of 140 patients with NSCLC before starting treatment with ICIs. Overall response rate (ORR), progression-free survival (PFS), and overall survival (OS) in strata of PD-L1 and MSC alone or combined were considered as endpoints. Multiple plasma samples to monitor MSC risk level during treatment were also profiled.

RESULTS

Adequate tissue and plasma samples were available from 111 (79%) and 104 (75%) patients with NSCLC, respectively. MSC risk level was associated with ORR (P = 0.0009), PFS [multivariate HR = 0.31; 95% confidence interval (CI), 0.17-0.56; P = 0.0001], and OS (multivariate HR = 0.33; 95% CI, 0.18-0.59; P = 0.0002). The combination of MSC and PD-L1 stratified patients into three risk groups having 39%-18%-0% 1-year PFS (P < 0.0001) and 88%-44%-0% 1-year OS (P < 0.0001), according to the presence of 2-1-0 favorable markers. During treatment, MSC risk level decreased or remained low until tumor progression in patients with responsive or stable disease.

CONCLUSIONS

The plasma MSC test could supplement PD-L1 tumor expression to identify a subgroup of patients with advanced lung cancer with worse ORR, PFS, and OS in immunotherapy regimens.

The narrow path to organized LDCT lung cancer screening programs in Europe

A recent position statement by a group of European experts reviewed the current evidence for low-dose computed tomography (LDCT) lung cancer screening, based on the outcomes and screening performance of the published randomized trials and identified actions needed for eventual future implementation. After the National Lung Screening Trial (NLST) outcome publication, guidelines changed in USA and Canada, but there are still problems in real-world screening practice. In Europe any decision was postponed to the publication of the European randomized trial outcomes and recommendations continue to discourage screening for lung cancer in all member countries. The NELSON randomized controlled trial (RCT), the largest one in Europe, outcome results are still waited, whereas the MILD, DANTE, DLSCT and ITALUNG (all with small sample size) RCTs have published mortality and incidence data with adequate follow up. The implementation of an organized screening in Europe is conditioned by a health technology assessment process at European level. According with the European policy, confirmed in the recent European Cancer Code [2015], screening is transferred in current public-health practice according with evidence-based recommendations and based on organized, usually population-based, programs. Guidelines, standard indicators of performance, training of dedicated radiologists and professionals and a comprehensive quality assurance system is requested in European countries to implement nationally a public health screening program. Waiting the NELSON randomized trial results, key issues as modality for selection of high risk subjects and recruitment, integration of screening and smoking cessation, optimal screening regimen and related research on biomarkers should be assessed, discussed and reviewed. Informed decision making, promotion of primary prevention and integration of screening and smoking cessation are all essential components of a comprehensive risk reduction policy. The path to an Evidence-based screening practice is narrow and, in the absence of a well-established decision-making process, the risk of a spontaneous, uncontrolled use of LDCT screening or, on the other side, an oversight of the screening opportunity is high.

MicroRNAs in Smoking-Related Carcinogenesis: Biomarkers, Functions, and Therapy

Long-term heavy cigarette smoking is a well-known high-risk factor for carcinogenesis in various organs such as the head and neck, lungs, and urinary bladder. Furthermore, cigarette smoking can systemically accelerate aging, and as the result, promoting carcinogenesis via changing the host microenvironment. Various inflammatory factors, hormones, and chemical mediators induced by smoking mediate carcinoma-related molecules and induce carcinogenesis. MicroRNAs (miRNAs) are a family of short noncoding RNA molecules that bind to mRNAs and inhibit their expression. Cigarette smoke induces the expression of various miRNAs, many of which are known to function in the post-transcriptional silencing of anticancer molecules, thereby leading to smoking-induced carcinogenesis. Analysis of expression profiles of smoking-induced miRNAs can help identify biomarkers for the diagnosis and prognosis of smoking-related cancers and prediction of therapeutic responses, as well as revealing promising therapeutic targets. Here, we introduce the most recent and useful findings of miRNA analyses focused on lung cancer and urinary bladder cancer, which are strongly associated with cigarette smoking, and discuss the utility of miRNAs as clinical biomarkers.