miR-Test: a blood test for lung cancer early detection

Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey

With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.

Reactivation of Multiple Fetal miRNAs in Lung Adenocarcinoma

MicroRNAs (miRNAs) play vital roles in the regulation of normal developmental pathways. However, cancer cells can co-opt these miRNAs, and the pathways that they regulate, to drive pro-tumourigenic phenotypes. Characterization of the miRNA transcriptomes of fetal organs is essential for identifying these oncofetal miRNAs, but it has been limited by fetal sample availability. As oncofetal miRNAs are absent from healthy adult lungs, they represent ideal targets for developing diagnostic and therapeutic strategies. We conducted small RNA sequencing of a rare collection of 25 human fetal lung (FL) samples and compared them to two independent cohorts (n = 140, n = 427), each comprised of adult non-neoplastic lung (ANL) and lung adenocarcinoma (LUAD) samples. We identified 13 oncofetal miRNAs that were expressed in FL and LUAD but not in ANL. These oncofetal miRNAs are potential biomarkers for LUAD detection (AUC = 0.963). Five of these miRNAs are derived from the imprinted C14MC miRNA cluster at the 14q32 locus, which has been associated with cancer development and abnormal fetal and placental development. Additionally, we observed the pulmonary expression of 44 previously unannotated miRNAs. The sequencing of these fetal lung samples also provides a baseline resource against which aberrant samples can be compared.

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.

MicroRNA expression profiling and biomarker validation in treatment-naïve and drug resistant non-small cell lung cancer

Background

In the absence of targetable mutations or immune checkpoints, cisplatin-doublet chemotherapy remains the standard of care in non-small cell lung cancer (NSCLC). Drug resistance has however become a significant clinical challenge. Exploring a role for small non-coding microRNAs (miRNA) as biomarker candidates in cisplatin resistant (CisR) lung cancer is lacking and warrants further investigation.

Methods

miRNA expression profiling was assessed in a panel of cisplatin sensitive and resistant NSCLC cell lines and validated by qPCR. Modulation of altered miRNAs was studied using antagomiRs and pre-miRs while functional assays were used to assess cisplatin response. The translational relevance of these miRNAs as potential biomarkers was assessed in serum and matched normal and tumour lung tissues from chemo-naïve NSCLC patients, in addition to xenograft formalin-fixed paraffin-embedded (FFPE) tumours derived from cisplatin sensitive and resistant cell lines.

Results

Differential expression of a 5-miR signature (miR-30a-3p, miR-30b-5p, miR-30c-5p, miR-34a-5p, miR-4286) demonstrated their ability to distinguish between normal and tumour lung tissue and between NSCLC histologies. In squamous cell carcinoma (SqCC), tissue miRNA expression was associated with poor survival. miR-4286 showed promise as a blood-based diagnostic biomarker that could distinguish between adenocarcinoma and SqCC histologies. In a xenograft model of cisplatin resistance, using 7-9 week old female NOD/SCID mice (NOD.CB17-Prkdcscid/NCrCrl), a 5-miRNA panel showed altered expression between sensitive and resistant tumours.

Conclusions

This study identified a panel of miRNAs which may have diagnostic and prognostic potential as novel biomarkers in lung cancer and furthermore, may have a predictive role in monitoring the emergence of resistance to cisplatin.

miRNAs in lung cancer. A systematic review identifies predictive and prognostic miRNA candidates for precision medicine in lung cancer

Lung cancer (LC) is the leading cause of cancer-related death worldwide and miRNAs play a key role in LC development. To better diagnose LC and to predict drug treatment responses we evaluated 228 articles encompassing 16,697 patients and 12,582 healthy controls. Based on the criteria of ≥3 independent studies and a sensitivity and specificity of >0.8 we found blood-borne miR-20a, miR-10b, miR-150, and miR-223 to be excellent diagnostic biomarkers for non-small cell LC whereas miR-205 is specific for squamous cell carcinoma. The systematic review also revealed 38 commonly regulated miRNAs in tumor tissue and the circulation, thus enabling the prediction of histological subtypes of LC. Moreover, theranostic biomarker candidates with proven responsiveness to checkpoint inhibitor treatments were identified, notably miR-34a, miR-93, miR-106b, miR-181a, miR-193a-3p, and miR-375. Conversely, miR-103a-3p, miR-152, miR-152-3p, miR-15b, miR-16, miR-194, miR-34b, and miR-506 influence programmed cell death-ligand 1 and programmed cell death-1 receptor expression, therefore providing a rationale for the development of molecularly targeted therapies. Furthermore, miR-21, miR-25, miR-27b, miR-19b, miR-125b, miR-146a, and miR-210 predicted response to platinum-based treatments. We also highlight controversial reports on specific miRNAs. In conclusion, we report diagnostic miRNA biomarkers for in-depth clinical evaluation. Furthermore, in an effort to avoid unnecessary toxicity we propose predictive biomarkers. The biomarker candidates support personalized treatment decisions of LC patients and await their confirmation in randomized clinical trials.

Serum Exosomes and Their miRNA Load-A Potential Biomarker of Lung Cancer

Early detection of lung cancer in screening programs is a rational way to reduce mortality associated with this malignancy. Low-dose computed tomography, a diagnostic tool used in lung cancer screening, generates a relatively large number of false-positive results, and its complementation with molecular biomarkers would greatly improve the effectiveness of such programs. Several biomarkers of lung cancer based on different components of blood, including miRNA signatures, were proposed. However, only a few of them have been positively validated in the context of early cancer detection yet, which imposes a constant need for new biomarker candidates. An emerging source of cancer biomarkers are exosomes and other types of extracellular vesicles circulating in body fluids. Hence, different molecular components of serum/plasma-derived exosomes were tested and showed different levels in lung cancer patients and healthy individuals. Several studies focused on the miRNA component of these vesicles. Proposed signatures of exosome miRNA had promising diagnostic value, though none of them have yet been clinically validated. These signatures involved a few dozen miRNA species overall, including a few species that recurred in different signatures. It is worth noting that all these miRNA species have cancer-related functions and have been associated with lung cancer progression. Moreover, a few of them, including known oncomirs miR-17, miR-19, miR-21, and miR-221, appeared in multiple miRNA signatures of lung cancer based on both the whole serum/plasma and serum/plasma-derived exosomes.

Lessons Learned from Setting Up a Prospective, Longitudinal, Multicenter Study with Women at High Risk for Breast Cancer

Women identified with an increased risk of breast cancer due to mutations in cancer susceptibility genes or a familial history of breast cancer undergo tailored screening with the goal of detecting tumors earlier, when potential curative interventions are still possible. Ideally, screening would identify signs of carcinogenesis even before a tumor is detectable by imaging. This could be achieved by timely signaling of altered biomarker levels for precancerous processes in liquid biopsies. Currently, the Nipple Aspirate Fluid (NAF) and the Trial Early Serum Test BREAST cancer (TESTBREAST), both ongoing, prospective, multicenter studies, are investigating biomarkers in liquid biopsies to improve breast cancer screening in high-risk women. The NAF study focuses on changes over time in miRNA expression levels both in blood and NAF samples, whereas the TESTBREAST study analyzes changes in protein levels in blood samples at sequential interval timepoints. These within-subject changes are studied in relation to later occurrence of breast cancer using a nested case-control design. These longitudinal studies face their own challenges in execution, such as hindrances in logistics and in sample processing that were difficult to anticipate. This article offers insight into those challenges and concurrently aims to provide useful strategies for the set-up of similar studies.See related commentary by Sauter, p. 429.

Molecular biomarkers in early stage lung cancer

Low dose computed tomography (LDCT) screening, together with the recent advances in targeted and immunotherapies, have shown to improve non-small cell lung cancer (NSCLC) survival. Furthermore, screening has increased the number of early stage-detected tumors, allowing for surgical resection and multimodality treatments when needed. The need for improved sensitivity and specificity of NSCLC screening has led to increased interest in combining clinical and radiological data with molecular data. The development of biomarkers is poised to refine inclusion criteria for LDCT screening programs. Biomarkers may also be useful to better characterize the risk of indeterminate nodules found in the course of screening or to refine prognosis and help in the management of screening detected tumors. The clinical implications of these biomarkers are still being investigated and whether or not biomarkers will be included in further decision-making algorithms in the context of screening and early lung cancer management still needs to be determined. However, it seems clear that there is much room for improvement even in early stage lung cancer disease-free survival (DFS) rates; thus, biomarkers may be the key to refine risk-stratification and treatment of these patients. Clinicians’ capacity to register, integrate, and analyze all the available data in both high risk individuals and early stage NSCLC patients will lead to a better understanding of the disease’s mechanisms, and will have a direct impact in diagnosis, treatment, and follow up of these patients. In this review, we aim to summarize all the available data regarding the role of biomarkers in LDCT screening and early stage NSCLC from a multidisciplinary perspective. We have highlighted clinical implications, the need to combine risk stratification, clinical data, radiomics, molecular information and artificial intelligence in order to improve clinical decision-making, especially regarding early diagnostics and adjuvant therapy. We also discuss current and future perspectives for biomarker implementation in routine clinical practice.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

Non-Coding RNAs as Prognostic Biomarkers: A miRNA Signature Specific for Aggressive Early-Stage Lung Adenocarcinomas

Lung cancer burden can be reduced by adopting primary and secondary prevention strategies such as anti-smoking campaigns and low-dose CT screening for high risk subjects (aged >50 and smokers >30 packs/year). Recent CT screening trials demonstrated a stage-shift towards earlier stage lung cancer and reduction of mortality (~20%). However, a sizable fraction of patients (30–50%) with early stage disease still experience relapse and an adverse prognosis. Thus, the identification of effective prognostic biomarkers in stage I lung cancer is nowadays paramount. Here, we applied a multi-tiered approach relying on coupled RNA-seq and miRNA-seq data analysis of a large cohort of lung cancer patients (TCGA-LUAD, n = 510), which enabled us to identify prognostic miRNA signatures in stage I lung adenocarcinoma. Such signatures showed high accuracy (AUC ranging between 0.79 and 0.85) in scoring aggressive disease. Importantly, using a network-based approach we rewired miRNA-mRNA regulatory networks, identifying a minimal signature of 7 miRNAs, which was validated in a cohort of FFPE lung adenocarcinoma samples (CSS, n = 44) and controls a variety of genes overlapping with cancer relevant pathways. Our results further demonstrate the reliability of miRNA-based biomarkers for lung cancer prognostication and make a step forward to the application of miRNA biomarkers in the clinical routine.

Diagnostic and Therapeutic Implications of microRNAs in Non-Small Cell Lung Cancer

microRNAs (miRNAs), endogenous suppressors of target mRNAs, are deeply involved in every step of non-small cell lung cancer (NSCLC) development, from tumor initiation to progression and metastasis. They play roles in cell proliferation, apoptosis, angiogenesis, epithelial-to-mesenchymal transition, migration, invasion, and metastatic colonization, as well as immunosuppression. Due to their versatility, numerous attempts have been made to use miRNAs for clinical applications. miRNAs can be used as cancer subtype classifiers, diagnostic markers, drug-response predictors, prognostic markers, and therapeutic targets in NSCLC. Many challenges remain ahead of their actual clinical application; however, when achieved, the use of miRNAs in the clinic is expected to enable great progress in the diagnosis and treatment of patients with NSCLC.

Noninvasive Diagnostics for Early Detection of Lung Cancer: Challenges and Potential with a Focus on Changes in DNA Methylation

Lung cancer remains the leading cause of cancer deaths in the United States and the world. Early detection of this disease can reduce mortality, as demonstrated for low-dose computed tomography (LDCT) screening. However, there remains a need for improvements in lung cancer detection to complement LDCT screening and to increase adoption of screening. Molecular changes in the tumor, and the patient's response to the presence of the tumor, have been examined as potential biomarkers for diagnosing lung cancer. There are significant challenges to developing an effective biomarker with sufficient sensitivity and specificity for the early detection of lung cancer, particularly the detection of circulating tumor DNA, which is present in very small quantities. We will review approaches to develop biomarkers for the early detection of lung cancer, with special consideration to detection of rare tumor events, focus on the use of DNA methylation-based detection in plasma and sputum, and discuss the promise and challenges of lung cancer early detection. Plasma-based detection of lung cancer DNA methylation may provide a simple cost-effective method for the early detection of lung cancer.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Precision Prevention and Cancer Interception: The New Challenges of Liquid Biopsy

Despite major therapeutic progress, most advanced solid tumors are still incurable. Cancer interception is the active way to combat cancer onset, and development of this approach within high-risk populations seems a logical first step. Until now, strategies for the identification of high-risk subjects have been based on low-sensitivity and low-specificity assays. However, new liquid biopsy assays, "the Rosetta Stone of the new biomedicine era," with the ability to identify circulating biomarkers with unprecedented sensitivity, promise to revolutionize cancer management. This review focuses on novel liquid biopsy approaches and the applications to cancer interception. Cancer interception involves the identification of biomarkers associated with developing cancer, and includes genetic and epigenetic alterations, as well as circulating tumor cells and circulating epithelial cells in individuals at risk, and the implementation of therapeutic strategies to prevent the beginning of cancer and to stop its development. Large prospective studies are needed to confirm the potential role of liquid biopsy for early detection of precancer lesions and tumors.

Cancer genotypes prediction and associations analysis from imaging phenotypes: a survey on radiogenomics

In this paper, we present a survey on the progress of radiogenomics research, which predicts cancer genotypes from imaging phenotypes and investigates the associations between them. First, we present an overview of the popular technology modalities for obtaining diagnostic medical images. Second, we summarize recently used methodologies for radiogenomics analysis, including statistical analysis, radiomics and deep learning. And then, we give a survey on the recent research based on several types of cancers. Finally, we discuss these studies and propose possible future research directions. In conclusion, we have identified strong correlations between cancer genotypes and imaging phenotypes. In addition, with the rapid growth of medical data, deep learning models show great application potential for radiogenomics.

Circulating tumour cells as a potential biomarker for lung cancer screening: a prospective cohort study

BACKGROUND

Lung cancer screening with low-dose chest CT (LDCT) reduces the mortality of eligible individuals. Blood signatures might act as a standalone screening tool, refine the selection of patients at risk, or help to classify undetermined nodules detected on LDCT. We previously showed that circulating tumour cells (CTCs) could be detected, using the isolation by size of epithelial tumour cell technique (ISET), long before the cancer was diagnosed radiologically. We aimed to test whether CTCs could be used as a biomarker for lung cancer screening.

METHODS

We did a prospective, multicentre, cohort study in 21 French university centres. Participants had to be eligible for lung cancer screening as per National Lung Screening Trial criteria and have chronic obstructive pulmonary disease with a fixed airflow limitation defined as post-bronchodilator FEV1/FVC ratio of less than 0·7. Any cancer, other than basocellular skin carcinomas, detected within the previous 5 years was the main exclusion criterion. Participants had three screening rounds at 1-year intervals (T0 [baseline], T1, and T2), which involved LDCT, clinical examination, and a blood test for CTCs detection. Participants and investigators were masked to the results of CTC detection, and cytopathologists were masked to clinical and radiological findings. Our primary objective was to test the diagnostic performance of CTC detection using the ISET technique in lung cancer screening, compared with cancers diagnosed by final pathology, or follow up if pathology was unavailable as the gold standard. This study is registered with ClinicalTrials.gov identifier, number NCT02500693.

FINDINGS

Between Oct 30, 2015, and Feb 2, 2017, we enrolled 614 participants, predominantly men (437 [71%]), aged 65·1 years (SD 6·5), and heavy smokers (52·7 pack-years [SD 21·5]). 81 (13%) participants dropped out between baseline and T1, and 56 (11%) did between T1 and T2. Nodules were detected on 178 (29%) of 614 baseline LDCTs. 19 participants (3%) were diagnosed with a prevalent lung cancer at T0 and 19 were diagnosed with incident lung cancer (15 (3%) of 533 at T1 and four (1%) of 477 at T2). Extrapulmonary cancers were diagnosed in 27 (4%) of participants. Overall 28 (2%) of 1187 blood samples were not analysable. At baseline, the sensitivity of CTC detection for lung cancer detection was 26·3% (95% CI 11·8-48·8). ISET was unable to predict lung cancer or extrapulmonary cancer development.

INTERPRETATION

CTC detection using ISET is not suitable for lung cancer screening.

FUNDING

French Government, Conseil Départemental 06, Fondation UNICE, Fondation Aveni, Fondation de France, Ligue Contre le Cancer-Comité des Alpes-Maritimes, ARC (Canc'Air Genexposomics), Claire de Divonne-Pollner, Enca Faidhi, Basil Faidhi, Fabienne Mourou, Michel Mourou, Leonid Fridlyand, cogs4cancer, and the Fondation Masikini.

Circulating miR-16-5p, miR-92a-3p, and miR-451a in Plasma from Lung Cancer Patients: Potential Application in Early Detection and a Regulatory Role in Tumorigenesis Pathways

BACKGROUND

Micro(mi)RNAs, potent gene expression regulators associated with tumorigenesis, are stable, abundant circulating molecules, and detectable in plasma. Thus, miRNAs could potentially be useful in early lung cancer detection. We aimed to identify circulating miRNA signatures in plasma from patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), and to verify whether miRNAs regulate lung oncogenesis pathways.

METHODS

RNA isolated from 139 plasma samples (40 LUAD, 38 LUSC; 61 healthy/non-diseased individuals) were divided into discovery (38 patients; 21 controls for expression quantification using an 800-miRNA panel; Nanostring nCounter®) and validation (40 patients; 40 controls; TaqMan® RT-qPCR) cohorts. Elastic net, Maximizing-R-Square Analysis (MARSA), and C-Statistics were applied for miRNA signature identification.

RESULTS

When compared to healthy individuals, 580 of 606 deregulated miRNAs in LUAD and 221 of 226 deregulated miRNAs in LUSC had significantly increased levels. Among the 10 most significantly overexpressed miRNAs, 6 were common to patients with LUAD and LUSC. Further analysis identified three signatures composed of 12 miRNAs. Signatures included miRNAs commonly overexpressed in patient plasma. Enriched pathways included target genes modulated by three miRNAs in the C-Statistics signature: miR-16-5p, miR-92a-3p, and miR-451a.

CONCLUSIONS

The 3-miRNA signature (miR-16-5p, miR-92a-3p, miR-451a) had high specificity (100%) and sensitivity (84%) to predict cancer (LUAD and LUSC). These miRNAs are predicted to modulate genes and pathways with known roles in lung tumorigenesis, including EGFR, K-RAS, and PI3K/AKT signaling, suggesting that the 3-miRNA signature is biologically relevant in adenocarcinoma and squamous cell carcinoma of the lung.

Identification of Novel microRNA Prognostic Markers Using Cascaded Wx, a Neural Network-Based Framework, in Lung Adenocarcinoma Patients

The evolution of next-generation sequencing technology has resulted in a generation of large amounts of cancer genomic data. Therefore, increasingly complex techniques are required to appropriately analyze this data in order to determine its clinical relevance. In this study, we applied a neural network-based technique to analyze data from The Cancer Genome Atlas and extract useful microRNA (miRNA) features for predicting the prognosis of patients with lung adenocarcinomas (LUAD). Using the Cascaded Wx platform, we identified and ranked miRNAs that affected LUAD patient survival and selected the two top-ranked miRNAs (miR-374a and miR-374b) for measurement of their expression levels in patient tumor tissues and in lung cancer cells exhibiting an altered epithelial-to-mesenchymal transition (EMT) status. Analysis of miRNA expression from tumor samples revealed that high miR-374a/b expression was associated with poor patient survival rates. In lung cancer cells, the EMT signal induced miR-374a/b expression, which, in turn, promoted EMT and invasiveness. These findings demonstrated that this approach enabled effective identification and validation of prognostic miRNA markers in LUAD, suggesting its potential efficacy for clinical use.

Recommendations for Implementing Lung Cancer Screening with Low-Dose Computed Tomography in Europe

Lung cancer screening (LCS) with low-dose computed tomography (LDCT) was demonstrated in the National Lung Screening Trial (NLST) to reduce mortality from the disease. European mortality data has recently become available from the Nelson randomised controlled trial, which confirmed lung cancer mortality reductions by 26% in men and 39-61% in women. Recent studies in Europe and the USA also showed positive results in screening workers exposed to asbestos. All European experts attending the "Initiative for European Lung Screening (IELS)"-a large international group of physicians and other experts concerned with lung cancer-agreed that LDCT-LCS should be implemented in Europe. However, the economic impact of LDCT-LCS and guidelines for its effective and safe implementation still need to be formulated. To this purpose, the IELS was asked to prepare recommendations to implement LCS and examine outstanding issues. A subgroup carried out a comprehensive literature review on LDCT-LCS and presented findings at a meeting held in Milan in November 2018. The present recommendations reflect that consensus was reached.

Molecular testing on bronchial washings for the diagnosis and predictive assessment of lung cancer

Cytopathological analyses of bronchial washings (BWs) collected during fibre‐optic bronchoscopy are often inconclusive for lung cancer diagnosis. To address this issue, we assessed the suitability of conducting molecular analyses on BWs, with the aim to improve the diagnosis and outcome prediction of lung cancer. The methylation status of RASSF1A, CDH1, DLC1 and PRPH was analysed in BW samples from 91 lung cancer patients and 31 controls, using a novel two‐colour droplet digital methylation‐specific PCR (ddMSP) technique. Mutations in ALK, BRAF, EGFR, ERBB2, KRAS, MAP2K1, MET, NRAS, PIK3CA, ROS1 and TP53 and gene fusions of ALK, RET and ROS1 were also investigated, using next‐generation sequencing on 73 lung cancer patients and 14 tumour‐free individuals. Our four‐gene methylation panel had significant diagnostic power, with 97% sensitivity and 74% specificity (relative risk, 7.3; odds ratio, 6.1; 95% confidence interval, 12.7–127). In contrast, gene mutation analysis had a remarkable value for predictive, but not for diagnostic, purposes. Actionable mutations in EGFR, HER2 and ROS1 as well as in other cancer genes (KRAS, PIK3CA and TP53) were detected. Concordance with gene mutations uncovered in tumour biopsies was higher than 90%. In addition, bronchial‐washing analyses permitted complete patient coverage and the detection of additional actionable mutations. In conclusion, BWs are a useful material on which to perform molecular tests based on gene panels: aberrant gene methylation and mutation analyses could be performed as approaches accompanying current diagnostic and predictive assays during the initial workup phase. This study establishes the grounds for further prospective investigation.

Recommendations for Implementing Lung Cancer Screening with Low-Dose Computed Tomography in Europe

Lung cancer screening (LCS) with low-dose computed tomography (LDCT) was demonstrated in the National Lung Screening Trial (NLST) to reduce mortality from the disease. European mortality data has recently become available from the Nelson randomised controlled trial, which confirmed lung cancer mortality reductions by 26% in men and 39-61% in women. Recent studies in Europe and the USA also showed positive results in screening workers exposed to asbestos. All European experts attending the "Initiative for European Lung Screening (IELS)"-a large international group of physicians and other experts concerned with lung cancer-agreed that LDCT-LCS should be implemented in Europe. However, the economic impact of LDCT-LCS and guidelines for its effective and safe implementation still need to be formulated. To this purpose, the IELS was asked to prepare recommendations to implement LCS and examine outstanding issues. A subgroup carried out a comprehensive literature review on LDCT-LCS and presented findings at a meeting held in Milan in November 2018. The present recommendations reflect that consensus was reached.

Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician's Point of View

Starting from the work of Ulivi and colleagues, we aim to summarize the research area of biomarkers for early diagnosis and early stage lung cancer.

Noninvasive biomarkers for lung cancer diagnosis, where do we stand?

The 2010's saw demonstration of the power of lung cancer screening to reduce mortality. However, with implementation of lung cancer screening comes the challenge of diagnosing millions of lung nodules every year. When compared to other cancers with widespread screening strategies (breast, colorectal, cervical, prostate, and skin), obtaining a lung nodule tissue biopsy to confirm a positive screening test remains associated with higher morbidity and cost. Therefore, non-invasive diagnostic biomarkers may have a unique opportunity in lung cancer to greatly improve the management of patients at risk. This review covers recent advances in the field of liquid biomarkers and computed tomographic imaging features, with special attention to new methods for combination of biomarkers as well as the use of artificial intelligence for the discrimination of benign from malignant nodules.

MicroRNA biomarkers for chemical hazard screening identified by RNA deep sequencing analysis in mouse embryonic stem cells

We investigated the responses of microRNAs (miRNAs) using mouse embryonic stem cells (mESCs) exposed to nine chemicals (bis(2-ethylhexyl)phthalate, p-cresol, p-dichlorobenzene, phenol, pyrocatecol, chloroform, tri-n-butyl phosphate, trichloroethylene, and benzene), which are listed as "Class I Designated Chemical Substances" from the Japan Pollutant Release and Transfer Register. Using deep sequencing analysis (RNA-seq), several miRNAs were identified that show a substantial response to general chemical toxicity (i.e., to these nine chemicals considered as a group) and several miRNA biomarkers that show a substantial and specific response to benzene. The functions of the identified miRNAs were investigated in accordance with Gene Ontology terms of their predicted target genes, indicating regulation of cellular processes. We compared the results with those for the long non-coding RNAs (ncRNAs) and mRNAs reported in our previous studies in addition to previously identified miRNAs that are either up- or down-regulated in response to the benzene as stimuli. We also observed that the changes in expression of miRNAs were smaller than those for long ncRNAs and mRNAs. Taken together the current and previous results revealed that toxic chemical stimuli regulate the expression of miRNAs. We believe that the use of miRNAs, including the thus identified miRNAs, as biomarkers contribute to predicting the potential toxicity of particular chemicals or identifying human individuals that have been exposed to chemical hazards.

A miRNA-based diagnostic model predicts resectable lung cancer in humans with high accuracy

Lung cancer, the leading cause of cancer death worldwide, is most frequently detected through imaging tests. In this study, we investigated serum microRNAs (miRNAs) as a possible early screening tool for resectable lung cancer. First, we used serum samples from participants with and without lung cancer to comprehensively create 2588 miRNAs profiles; next, we established a diagnostic model based on the combined expression levels of two miRNAs (miR-1268b and miR-6075) in the discovery set (208 lung cancer patients and 208 non-cancer participants). The model displayed a sensitivity of 99% and specificity of 99% in the validation set (1358 patients and 1970 non-cancer participants) and exhibited high sensitivity regardless of histological type and pathological TNM stage of the cancer. Moreover, the diagnostic index markedly decreased after lung cancer resection. Thus, the model we developed has the potential to markedly improve screening for resectable lung cancer.

Asakura, Kadota et al. demonstrate the diagnostic potential of serum microRNAs for resectable lung cancer. Their diagnostic model based on the combined expression levels of two miRNAs predicts resectable lung cancer with 99% sensitivity, regardless of histological types and pathological stages of cancer, suggesting its promising, diagnostic utility.

Serum MicroRNA Signature as a Diagnostic and Therapeutic Marker in Patients with Psoriatic Arthritis

OBJECTIVE

MicroRNA (miRNA) are small endogenous regulatory RNA molecules that have emerged as potential therapeutic targets and biomarkers in autoimmunity. Here, we investigated serum miRNA levels in patients with psoriatic arthritis (PsA) and further assessed a serum miRNA signature in therapeutic responder versus nonresponder PsA patients.

METHODS

Serum samples were collected from healthy controls (HC; n = 20) and PsA patients (n = 31), and clinical demographics were obtained. To examine circulatory miRNA in serum from HC and PsA patients, a focused immunology miRNA panel was analyzed utilizing a miRNA Fireplex assay (FirePlex Bioworks Inc.). MiRNA expression was further assessed in responders versus nonresponders according to the European League Against Rheumatism response criteria.

RESULTS

Six miRNA (miR-221-3p, miR-130a-3p, miR-146a-5p, miR-151-5p, miR-26a-5p, and miR-21-5p) were significantly higher in PsA compared to HC (all P < 0.05), with high specificity and sensitivity determined by receiver-operating characteristic curve analysis. Analysis of responder versus nonresponders demonstrated higher baseline levels of miR-221-3p, miR-130a-3p, miR-146a-5p, miR-151-5p, and miR-26a-5p were associated with therapeutic response.

CONCLUSION

This study identified a 6-serum microRNA signature that could be attractive candidates as noninvasive markers for PsA and may help to elucidate the disease pathogenesis.

Plasma Long Non-Coding RNA RP11-438N5.3 as a Novel Biomarker for Non-Small Cell Lung Cancer

Background

Lung cancer is one of the most common malignancies around the world. The lack of early diagnosis and effective treatment strategies contributes to the poor prognosis of patients with lung cancer. Recent studies have implied the role of long non-coding RNAs (lncRNAs) in oncogenesis. The purpose of our study was to identify specific lncRNAs which were correlated with non-small cell lung cancer (NSCLC) and their potential functions.

Materials and Methods

The global plasma lncRNA profiling was performed using LncPath^TM Human Cancer Array, and 11 lncRNAs were then selected for quantitative reverse transcription PCR (qRT-PCR) validation in 138 plasma samples from 69 NSCLC patients and 69 healthy controls (HCs). A noteworthy lncRNA, RP11-438N5.3, the function of which was previously unknown, was further explored on the aspect of the correlation of its expression level with clinicopathological factors.

Results

The results revealed that plasma level of RP11-438N5.3 was significantly lower in NSCLCs than that in HCs (p <0.01). Receiver operating characteristic (ROC) analyses showed that the area under the ROC curve (AUC) for plasma RP11-438N5.3 was 0.814 (95% CI, 0.743–0.885; p<0.01). High expression of RP11-438N5.3 in plasma correlated with favorable prognosis for NSCLC patients (Hazard ratio = 2.827; 95% CI: 1.036 to 7.718; p = 0.024; Cox regression analysis). Moreover, we found that the plasma level of stromal interaction molecule 1 (STIM1) mRNA was remarkably higher in NSCLC compared with HC (p<0.01), and the AUC for STIM1 was 0.753 (95% CI, 0.673–0.833; p<0.01), RP11-438N5.3 and STIM1 were inversely correlated with each other.

Conclusion

Our results indicated that RP11-438N5.3 and STIM1 might provide a new strategy for NSCLC diagnosis. Furthermore, increased circulating RP11-438N5.3 level holds great potential in indicating a beneficial prognosis in NSCLC patients.

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ESR/ERS statement paper on lung cancer screening

In Europe, lung cancer ranks third among the most common cancers, remaining the biggest killer. Since the publication of the first European Society of Radiology and European Respiratory Society joint white paper on lung cancer screening (LCS) in 2015, many new findings have been published and discussions have increased considerably. Thus, this updated expert opinion represents a narrative, non-systematic review of the evidence from LCS trials and description of the current practice of LCS as well as aspects that have not received adequate attention until now. Reaching out to the potential participants (persons at high risk), optimal communication and shared decision-making will be key starting points. Furthermore, standards for infrastructure, pathways and quality assurance are pivotal, including promoting tobacco cessation, benefits and harms, overdiagnosis, quality, minimum radiation exposure, definition of management of positive screen results and incidental findings linked to respective actions as well as cost-effectiveness. This requires a multidisciplinary team with experts from pulmonology and radiology as well as thoracic oncologists, thoracic surgeons, pathologists, family doctors, patient representatives and others. The ESR and ERS agree that Europe's health systems need to adapt to allow citizens to benefit from organised pathways, rather than unsupervised initiatives, to allow early diagnosis of lung cancer and reduce the mortality rate. Now is the time to set up and conduct demonstration programmes focusing, among other points, on methodology, standardisation, tobacco cessation, education on healthy lifestyle, cost-effectiveness and a central registry.

ESR/ERS statement paper on lung cancer screening

In Europe, lung cancer ranks third among the most common cancers, remaining the biggest killer. Since the publication of the first European Society of Radiology and European Respiratory Society joint white paper on lung cancer screening (LCS) in 2015, many new findings have been published and discussions have increased considerably. Thus, this updated expert opinion represents a narrative, non-systematic review of the evidence from LCS trials and description of the current practice of LCS as well as aspects that have not received adequate attention until now. Reaching out to the potential participants (persons at high risk), optimal communication and shared decision-making will be key starting points. Furthermore, standards for infrastructure, pathways and quality assurance are pivotal, including promoting tobacco cessation, benefits and harms, overdiagnosis, quality, minimum radiation exposure, definition of management of positive screen results and incidental findings linked to respective actions as well as cost-effectiveness. This requires a multidisciplinary team with experts from pulmonology and radiology as well as thoracic oncologists, thoracic surgeons, pathologists, family doctors, patient representatives and others. The ESR and ERS agree that Europe's health systems need to adapt to allow citizens to benefit from organised pathways, rather than unsupervised initiatives, to allow early diagnosis of lung cancer and reduce the mortality rate. Now is the time to set up and conduct demonstration programmes focusing, among other points, on methodology, standardisation, tobacco cessation, education on healthy lifestyle, cost-effectiveness and a central registry.Key Points• Pulmonologists and radiologists both have key roles in the set up of multidisciplinary LCS teams with experts from many other fields.• Pulmonologists identify people eligible for LCS, reach out to family doctors, share the decision-making process and promote tobacco cessation.• Radiologists ensure appropriate image quality, minimum dose and a standardised reading/reporting algorithm, together with a clear definition of a "positive screen".• Strict algorithms define the exact management of screen-detected nodules and incidental findings.• For LCS to be (cost-)effective, it has to target a population defined by risk prediction models.

Identification of differentially expressed circulating serum microRNA for the diagnosis and prognosis of Indian non-small cell lung cancer patients

PURPOSE

Identification of noninvasive blood-based biomarkers is of utmost importance for the early diagnosis and predicting prognosis of advance stage lung cancer patients. MicroRNAs (miRNAs) has been implicated in numerous diseases, however, their role as diagnostic and prognostic biomarkers in Indian lung cancer patients has not been evaluated yet.

METHODS

For the identification of differentially expressed miRNAs in the serum of non-small cell lung cancer (NSCLC) patients, we performed small RNA sequencing. We validated the expression of 10 miRNAs in 75 NSCLC patients and 40 controls using quantitative reverse transcription polymerase chain reaction (PCR). miRNA expression was correlated with survival and therapeutic response.

RESULTS

We identified 16 differentially expressed miRNAs in the serum of NSCLC patients as compared to controls. We observed significant downregulation of miR-15a-5p, miR-320a, miR-25-3p, miR-192-5p, let-7d-5p, let-7e-5p, miR-148a-3p, and miR-92a-3p in the serum of NSCLC patients. The expression of miR-375 and miR-10b-5p was significantly downregulated in lung squamous cell carcinoma patients than controls. The expression of miR-320a, miR-25-3p, and miR-148a-3p significantly correlated with stage. None of the miRNAs were correlated with survival outcome and therapeutic response.

CONCLUSIONS

We conclude that the relative abundance of miRNAs in serum may be explored for the development of miRNA-based assays for better diagnosis and prognosis of NSCLC. Moreover, further studies are warranted to elucidate the role of some of the less explored miRNAs, such as miR-375 and miR-320a, in the pathogenesis of NSCLC.

Biomarkers in Lung Cancer

Biomarkers that focus on lung cancer risk assessment, detection, prognosis, diagnosis, and personalized treatment are in various stages of development. This article provides an overview of lung cancer biomarker development, focusing on clinical utility and highlighting 2 unmet clinical needs: selection of high-risk patients for lung cancer screening and differentiation of early lung cancer from benign pulmonary nodules. The authors highlight biomarkers under development and those lung cancer screening and nodule management biomarkers post-clinical validation. Finally, trends in lung cancer biomarker development that may improve accuracy and accelerate implementation in practice are discussed.

Using Liquid Biopsy in the Treatment of Patient with OS

Liquid biopsies encompass a number of new technologies designed to derive tumor data through the minimally invasive sampling of an accessible body fluid. These technologies remain early in their clinical development, and applications for patients with osteosarcoma are actively under investigation. In this chapter, we outline the current state of liquid biopsy technologies as they apply to cancer generally and osteosarcoma specifically, focusing on assays that detect and profile circulating tumor DNA (ctDNA), microRNAs (miRNA), and circulating tumor cells (CTCs). At present, ctDNA assays are the most mature, with multiple assays demonstrating the feasibility of detecting and quantifying ctDNA from blood samples of patients with osteosarcoma. Initial studies show that ctDNA can be detected in the majority of patients with osteosarcoma and that the detection and level of ctDNA correlates with a worse prognosis. Profiling of ctDNA can also identify specific somatic events that may have prognostic relevance, such as 8q gain in osteosarcoma. miRNAs are stable RNAs that regulate gene expression and are known to be dysregulated in cancer, and patterns of miRNA expression have been evaluated in multiple studies of patients with osteosarcoma. While studies have identified differential expression of many miRNAs in osteosarcomas compared to healthy controls, a consensus set of prognostic miRNAs has yet to be definitively validated. Recent studies have also demonstrated the feasibility of capturing CTCs in patients with osteosarcoma. The development of assays that quantify and profile CTCs for use as prognostic biomarkers or tools for biologic discovery is still in development. However, CTC technology holds incredible promise given the potential to perform multi-omic approaches in single cancer cells to understand osteosarcoma heterogeneity and tumor evolution. The next step required to move liquid biopsy technologies closer to helping patients will be wide-scale collection of patient samples from large prospective studies.

Identification of lung cancer gene markers through kernel maximum mean discrepancy and information entropy

BACKGROUND

The early diagnosis of lung cancer has been a critical problem in clinical practice for a long time and identifying differentially expressed gene as disease marker is a promising solution. However, the most existing gene differential expression analysis (DEA) methods have two main drawbacks: First, these methods are based on fixed statistical hypotheses and not always effective; Second, these methods can not identify a certain expression level boundary when there is no obvious expression level gap between control and experiment groups.

METHODS

This paper proposed a novel approach to identify marker genes and gene expression level boundary for lung cancer. By calculating a kernel maximum mean discrepancy, our method can evaluate the expression differences between normal, normal adjacent to tumor (NAT) and tumor samples. For the potential marker genes, the expression level boundaries among different groups are defined with the information entropy method.

RESULTS

Compared with two conventional methods t-test and fold change, the top average ranked genes selected by our method can achieve better performance under all metrics in the 10-fold cross-validation. Then GO and KEGG enrichment analysis are conducted to explore the biological function of the top 100 ranked genes. At last, we choose the top 10 average ranked genes as lung cancer markers and their expression boundaries are calculated and reported.

CONCLUSION

The proposed approach is effective to identify gene markers for lung cancer diagnosis. It is not only more accurate than conventional DEA methods but also provides a reliable method to identify the gene expression level boundaries.

Liquid Biopsy in Non-Small Cell Lung Cancer: Highlights and Challenges

Non-small cell lung cancer is one leading cause of death worldwide, and patients would greatly benefit from an early diagnosis. Since targeted and immunotherapies have emerged as novel approaches for more tailored treatments, repeated assessments of the tumor biology have become pivotal to drive clinical decisions. Currently, tumor tissue biopsy is the gold standard to investigate potentially actionable biomarkers, but this procedure is invasive and may prove inadequate to represent the whole malignancy. In this regard, liquid biopsy represents a minimally invasive and more comprehensive option for early detection and investigation of this tumor. Today, cell-free DNA is the only approved circulating marker to select patients for a targeted therapy. Conversely, the other tumor-derived markers (i.e., circulating tumor cells, miRNAs, exosomes, and tumor educated platelets) are still at a pre-clinical phase, although they show promising results for their application in screening programs or as prognostic/predictive biomarkers. The main challenges for their clinical translation are the lack of reliable cutoffs and, especially for miRNAs, the great variability among the studies. Moreover, no established tool has been approved for circulating tumor cells and exosome isolation. Finally, large prospective clinical trials are mandatory to provide evidence of their clinical utility.

The biological functions and clinical applications of exosomes in lung cancer

Lung cancer remains the leading cause of cancer-related death worldwide, and the high incidence rates are worrisome. Exosomes are a class of extracellular vesicles secreted by most cells, including RNAs, proteins and lipids. Exosomes can mediate cell-to-cell communication in both physiologic and pathologic processes. Accumulated evidences show that cancer-derived exosomes aid in the recruitment and reprogramming of constituents correlated with tumor microenvironment. Furthermore, exosome-based clinical trials have been completed in advanced lung cancer patients. In this review, we discuss the roles of exosomes in a lung cancer microenvironment, such as its participation in lung cancer initiation, progression and metastasis as well as being involved in angiogenesis, epithelial-mesenchymal transition (EMT), immune escape, and drug resistance. In addition, we focus on the potential of exosomes as diagnostic and prognostic biomarkers in lung cancer, as well as the challenges faced by and advantages of exosomes as drug delivery vehicles and in exosome-based immunotherapy.

The Translational Status of Cancer Liquid Biopsies

Abstract

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research.

Lay Summary

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

Targets, pitfalls and reference materials for liquid biopsy tests in cancer diagnostics

Assessment of cell free DNA (cfDNA) and RNA (cfRNA), circulating tumor cells (CTC) and extracellular vesicles (EV) in blood or other bodily fluids can enable early cancer detection, tumor dynamics assessment, minimal residual disease detection and therapy monitoring. However, few liquid biopsy tests progress towards clinical application because results are often discordant and challenging to reproduce. Reproducibility can be enhanced by the development and implementation of standard operating procedures and reference materials to identify and correct for pre-analytical variables. In this review we elaborate on the technological considerations, pre-analytical variables and the use and availability of reference materials for the assessment of liquid biopsy targets in blood and highlight initiatives towards the standardization of liquid biopsy testing.

A Toolbox for Functional Analysis and the Systematic Identification of Diagnostic and Prognostic Gene Expression Signatures Combining Meta-Analysis and Machine Learning

The identification of biomarker signatures is important for cancer diagnosis and prognosis. However, the detection of clinical reliable signatures is influenced by limited data availability, which may restrict statistical power. Moreover, methods for integration of large sample cohorts and signature identification are limited. We present a step-by-step computational protocol for functional gene expression analysis and the identification of diagnostic and prognostic signatures by combining meta-analysis with machine learning and survival analysis. The novelty of the toolbox lies in its all-in-one functionality, generic design, and modularity. It is exemplified for lung cancer, including a comprehensive evaluation using different validation strategies. However, the protocol is not restricted to specific disease types and can therefore be used by a broad community. The accompanying R package vignette runs in ~1 h and describes the workflow in detail for use by researchers with limited bioinformatics training.

Validation of a serum 4-microRNA signature for the detection of lung cancer

BACKGROUND

Our previous studies have identified a serum-based 4-microRNA (4-miRNA) signature that may help distinguish patients with lung cancer (LC) from non-cancer controls (NCs). Here, we used an extended independent cohort of 398 subjects to further validate the diagnostic ability of this 4-miRNA signature.

METHODS

Using quantitative reverse transcription polymerase chain reaction (qRT-PCR), expression of the 4-miRNAs was assessed in a total of 398 sera that included 213 LC patients and 185 NCs. A logistic regression model using training-test sets, receiver operating characteristic (ROC) curve analysis and t-test were used to test the impact of varying expression of these miRNAs on its diagnostic accuracy for LC. The cell proliferation and colony formation affected by these miRNAs, as well as gene ontology (GO) analysis of miRNA target genes were performed.

RESULTS

The levels of the 4-miRNAs were significantly higher in the serum of patients with LCs as compared to NCs. Using a logistic regression prediction model based on training and test sets analysis, we obtained the area under the curve (AUC) of 0.921 [95% confidence interval (CI), 0.876-0.966] on the test set with specificity 90.6%, sensitivity 77.9%, accuracy 84.1%, positive predictive value (PPV) 89.8% and negative predictive value (NPV) 79.5%.

CONCLUSIONS

We have verified that this serum 4-miRNA signature could provide a promising noninvasive biomarker for the prediction of LC, particularly in patients with indeterminate lung nodules on screening CT scans.

Clinical value of non-coding RNAs in cardiovascular, pulmonary, and muscle diseases

Although a majority of the mammalian genome is transcribed to RNA, mounting evidence indicates that only a minor proportion of these transcriptional products are actually translated into proteins. Since the discovery of the first non-coding RNA (ncRNA) in the 1980s, the field has gone on to recognize ncRNAs as important molecular regulators of RNA activity and protein function, knowledge of which has stimulated the expansion of a scientific field that quests to understand the role of ncRNAs in cellular physiology, tissue homeostasis, and human disease. Although our knowledge of these molecules has significantly improved over the years, we have limited understanding of their precise functions, protein interacting partners, and tissue-specific activities. Adding to this complexity, it remains unknown exactly how many ncRNAs there are in existence. The increased use of high-throughput transcriptomics techniques has rapidly expanded the list of ncRNAs, which now includes classical ncRNAs (e.g., ribosomal RNAs and transfer RNAs), microRNAs, and long ncRNAs. In addition, splicing by-products of protein-coding genes and ncRNAs, so-called circular RNAs, are now being investigated. Because there is substantial heterogeneity in the functions of ncRNAs, we have summarized the present state of knowledge regarding the functions of ncRNAs in heart, lungs, and skeletal muscle. This review highlights the pathophysiologic relevance of these ncRNAs in the context of human cardiovascular, pulmonary, and muscle diseases.

Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer

Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum.

Current and future perspectives of liquid biopsies in genomics-driven oncology

Precision oncology seeks to leverage molecular information about cancer to improve patient outcomes. Tissue biopsy samples are widely used to characterize tumours but are limited by constraints on sampling frequency and their incomplete representation of the entire tumour bulk. Now, attention is turning to minimally invasive liquid biopsies, which enable analysis of tumour components (including circulating tumour cells and circulating tumour DNA) in bodily fluids such as blood. The potential of liquid biopsies is highlighted by studies that show they can track the evolutionary dynamics and heterogeneity of tumours and can detect very early emergence of therapy resistance, residual disease and recurrence. However, the analytical validity and clinical utility of liquid biopsies must be rigorously demonstrated before this potential can be realized.

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.

[Clinical Application of Plasma miR-34b-3p and miR-302a-5p in the Diagnosis of Non-small Cell Lung Cancer]

BACKGROUND

MicroRNA is a kind of single-stranded non-coding RNA whose length is about 22 nucleotides and its abnormal expression is related to disease closely. This study is aiming to explore the relative expression of miR-34b-3p and miR-302a-5p in the plasma of non-small cell lung cancer (NSCLC) patients and its clinical value.

METHODS

The levels of miR-34b-3p and miR-302a-5p in plasma were detected by real-time polymerase chain reaction (RT-PCR) in 86 patients with NSCLC, 64 patients with pulmonary tuberculosis (PTB) and 39 healthy subjects. Analyze their value in diagnosing NSCLC by contrasting and combining carcino-embryonic antigen (CEA), neuron-specific enolase (NSE), and cytokeratin 19 fragments 21-1 (CYFRA21-1).

RESULTS

The levels of plasma miR-34b-3p and miR-302a-5p in NSCLC group were significantly higher than those in the PTB group and the healthy group (P<0.05). In patients with NSCLC, the levels of plasma miR-34b-3p was correlated with the diameter of tumor (P<0.01). When using one plasma marker to diagnose NSCLC, miR-302a-5p had the highest sensitivity (82.6%) and CEA had the highest specificity (81.6%). While combined two plasma markers, miR-34b-3p+miR-302a-5p had the highest sensitivity (80.2%) and miR-34b-3p+CEA had the highest specificity (81.4%). As detected multiple markers, miR-302a-5p+NSE+CYFRA21-1 had the highest sensitivity (81.4%) and miR-34b-3p+CEA+NSE had the highest specificity (90.3%). The combination of miR-34b-3p, miR-302a-5p and CEA obtained the highest area under the curve (AUC), which was 0.832. Logistic regression model indicated that miR-34b-3p was independent risk factor for NSCLC compared to control groups.

CONCLUSIONS

Plasma miR-34b-3p and miR-302a-5p could be used as biological markers for the diagnosis of NSCLC.

Predicting Postoperative Liver Dysfunction Based on Blood-Derived MicroRNA Signatures

There is an urgent need for an easily assessable preoperative test to predict postoperative liver function recovery and thereby determine the optimal time point of liver resection, specifically as current markers are often expensive, time consuming, and invasive. Emerging evidence suggests that microRNA (miRNA) signatures represent potent diagnostic, prognostic, and treatment-response biomarkers for several diseases. Using next-generation sequencing as an unbiased systematic approach, 554 miRNAs were detected in preoperative plasma of 21 patients suffering from postoperative liver dysfunction (LD) after liver resection and 27 matched controls. Subsequently, we identified a miRNA signature-consisting of miRNAs 151a-5p, 192-5p, and 122-5p-that highly correlated with patients developing postoperative LD after liver resection. The predictive potential for postoperative LD was subsequently confirmed using real-time PCR in an independent validation cohort of 98 patients. Ultimately, a regression model of the two miRNA ratios 151a-5p to 192-5p and 122-5p to 151a-5p was found to reliably predict postoperative LD, severe morbidity, prolonged intensive care unit and hospital stays, and even mortality before an operation with a remarkable accuracy, thereby outperforming established markers of postoperative LD. Ultimately, we documented that miRNA ratios closely followed liver function recovery after partial hepatectomy. Conclusion: Our data demonstrate the clinical utility of an miRNA-based biomarker to support the selection of patients undergoing partial hepatectomy. The dynamical changes during liver function recovery indicate a possible role in individualized patient treatment. Thereby, our data might help to tailor surgical strategies to the specific risk profile of patients.