Biomarkers for Lung Cancer Screening and Detection

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

Background

The proper management of suspicious radiologic findings is crucial to optimize the effectiveness of low-dose computed tomography (LDCT) lung cancer screening trials. In the BioMILD study, we evaluated the utility of combining a plasma 24-microRNA signature classifier (MSC) and LDCT to define the individual risk and personalize screening strategies. Here we aim to assess the utility of repeated MSC testing during annual screening rounds in 1024 participants with suspicious LDCT findings.

Methods

The primary outcome was two-year lung cancer incidence in relation to MSC test results, reported as relative risk (RR) with 95% confidence interval (CI). Lung cancer incidence and mortality were estimated using extended Cox models for time-dependent covariates, yielding the respective hazard ratios (HR). Clinicaltrials.gov ID: NCT02247453.

Findings

With a median follow-up of 8.5 years, the full study set included 1403 indeterminate LDCT (CTind) and 584 positive LDCT (CT+) results. A lung cancer RR increase in MSC+ compared to MSC- participants was observed in both the CTind (RR: 2.5; 95% CI: 1.4-4.32) and CT+ (RR: 2.6; 95% CI: 1.81-3.74) groups and was maintained when considering stage I or resectable tumors only. A 98% negative predictive value in CTind/MSC- and a 30% positive predictive value in CT+/MSC+ lesions were recorded. At seven years' follow-up, MSC+ participants had a cumulative HR of 4.4 (95% CI: 3.0-6.4) for lung cancer incidence and of 8.1 (95% CI: 2.7-24.5) for lung cancer mortality.

Interpretation

Our study shows that MSC can be reliably performed during LDCT screening rounds to increase the accuracy of lung cancer risk and mortality prediction and supports its clinical utility in the management of LDCT findings of uncertain malignancy.

Funding

Italian Association for Cancer Research; Italian Ministry of Health; Horizon2020; National Cancer Institute (NCI); Gensignia LifeScience.

The Role of Biomarkers in Lung Cancer Screening

BACKGROUND

Lung Cancer Screening (LCS) is an evolving field with variations in its implementation in various countries. There are only scarce data from National LCS programs.

AIM

We aim to provide an up-to-date overview of the current evidence regarding the use of biomarkers in LCS.

MATERIALS AND METHODS

A multidisciplinary Task Force experts' panel collaborated and conducted a systematic literature search, followed by screening, review and synthesis of available evidence.

RESULTS

Biomarkers in LCS could be used to improve risk stratification in high-risk participants, improve clarification regarding indeterminate lung nodules and avoid overdiagnosis in suspicious lung findings. Currently, there seem to be promising biomarkers (blood/serum/breath) that have been studied in various trials; however, there is still a lack of solid evidence in clinical validation that would pave the way for their integration into LCS programs.

CONCLUSIONS

Biomarkers are the next logical step in improving the LCS pathway and its efficiency by playing an adjuvant role in a minimally invasive way. National LCS programs and pilot studies should integrate biomarkers to validate their accuracy in real-life LCS participants.

miR-122 and miR-21 are Stable Components of miRNA Signatures of Early Lung Cancer after Validation in Three Independent Cohorts

Several panels of circulating miRNAs have been reported as potential biomarkers of early lung cancer, yet the overlap of components between different panels is limited, and the universality of proposed biomarkers has been minimal across proposed panels. To assess the stability of the diagnostic potential of plasma miRNA signature of early lung cancer among different cohorts, a panel of 24 miRNAs tested in the frame of one lung cancer screening study (MOLTEST-2013, Poland) was validated with material collected in the frame of two other screening studies (MOLTEST-BIS, Poland; and SMAC, Italy) using the same standardized analytical platform (the miRCURY LNA miRNA PCR assay). On analysis of selected miRNAs, two associated with lung cancer development, miR-122 and miR-21, repetitively differentiated healthy participants from individuals with lung cancer. Additionally, miR-144 differentiated controls from cases specifically in subcohorts with adenocarcinoma. Other tested miRNAs did not overlap in the three cohorts. Classification models based on neither a single miRNA nor multicomponent miRNA panels (24-mer and 7-mer) showed classification performance sufficient for a standalone diagnostic biomarker (AUC, 75%, 71%, and 53% in MOLTEST-2013, SMAC, and MOLTEST-BIS, respectively, in the 7-mer model). The performance of classification in the MOLTEST-BIS cohort with the lowest contribution of adenocarcinomas was increased when only this cancer type was considered (AUC, 60% in 7-mer model).

The diagnostic performance of micro-RNA and metabolites in lung cancer: A meta-analysis

BACKGROUND

The diagnosis of lung cancer is based on the microscopic exam of tissue or liquid. During the recent decade, many biomarkers have been pointed to have a potential diagnostic role. These biomarkers may be assessed in blood, pleural effusion or sputum and they could avoid biopsies or other risky procedures. The authors aimed to assess the diagnostic performances of biomarkers focusing on micro-RNA and metabolites.

METHODS

This meta-analysis was conducted under the PRISMA guidelines during a nine-year-period (2013-2022). the Meta-Disc software 5.4 (free version) was used. Q test and I2 statistics were carried out to explore the heterogeneity among studies. Meta-regression was performed in case of significant heterogeneity. Publication bias was assessed using the funnel plot test and the Egger's test (free version JASP).

RESULTS

According to our inclusion criteria, 165 studies from 79 articles were included. The pooled SEN, SPE and dOR accounted, respectively, for 0.76, 0.79 and 13.927. The AUC was estimated to 0.859 suggesting a good diagnostic accuracy. The heterogeneity in the pooled SEN and SPE was statistically significant. The meta-regression analysis focusing on the technique used, the sample, the number of biomarkers, the biomarker subtype, the tumor stage and the ethnicity revealed the biomarker number (p  =  0.009) and the tumor stage (p  =  0.0241) as potential sources of heterogeneity.

CONCLUSION

Even if this meta-analysis highlighted the potential diagnostic utility of biomarkers, more prospective studies should be performed, especially to assess the biomarkers' diagnostic potential in early-stage lung cancers.

Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies

Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum metabolome is a promising source of auxiliary biomarkers that could help enhance the precision of lung cancer diagnosis in CT-based screening. Thus, we aimed to verify whether the combination of these two techniques, which provides local/morphological and systemic/molecular features of disease at the same time, increases the performance of lung cancer classification models. The collected cohort consists of 1086 patients with radiomic and 246 patients with serum metabolomic evaluations. Different machine learning techniques, i.e., random forest and logistic regression were applied for each omics. Next, model predictions were combined with various integration methods to create a final model. The best single omics models were characterized by an AUC of 83% in radiomics and 60% in serum metabolomics. The model integration only slightly increased the performance of the combined model (AUC equal to 85%), which was not statistically significant. We concluded that radiomics itself has a good ability to discriminate lung cancer from benign lesions. However, additional research is needed to test whether its combination with other molecular assessments would further improve the diagnosis of screening-detected lung nodules.

Serum-based biomarkers associated with lung cancer risk and cause-specific mortality in the German randomized Lung Cancer Screening Intervention (LUSI) trial

Background

Lung cancer (LC) screening can be optimized using individuals' estimated risks of having a detectable lung tumor, as well as of mortality risk by competing causes, to guide decisions on screening eligibility, ideal screening intervals and stopping ages. Besides age, sex and smoking history, blood-based biomarkers may be used to improve the assessment of LC risk and risk of mortality by competing causes.

Methods

In the German randomized Lung Screening Intervention Trial (LUSI), we measured growth/differentiation factor-15 (GDF-15), interleukin-6 (IL-6), C-reactive protein (CRP) and N-terminal pro-brain natriuretic protein (NT-proBNP), in blood serum samples collected at start of the trial. Participants in the computed tomography (CT)-screening arm also had a pulmonary function test. Regression models were used to examine these markers as predictors for impaired lung function, LC risk and mortality due to LC or other causes, independently of age, sex and smoking history.

Results

Our models showed increases in LC risk among participants with elevated serum levels of GDF-15 [odds ratio (OR)Q4-Q1 =2.47, 95% confidence interval (CI): 1.49-4.26], IL-6 [ORQ4-Q1 =2.36 (1.43-4.00)] and CRP [ORQ4-Q1 =1.81 (1.08-2.75)]. Likewise, proportional hazards models showed increased risks for LC-related mortality, hazard ratio (HR)Q4-Q1 of 4.63 (95% CI: 2.13-10.07) for GDF-15, 3.56 (1.72-7.37) for IL-6 and 2.34 (1.24-4.39) for CRP. All four markers were associated with increased risk of mortality by causes other than LC, with strongest associations for GDF-15 [HRQ4-Q1 =3.04 (2.09-4.43)] and IL-6 [HRQ4-Q1 =2.98 (2.08-4.28)]. Significant associations were also observed between IL-6, CRP, GDF-15 and impaired pulmonary function [chronic obstructive pulmonary disease (COPD), preserved ratio impaired spirometry (PRISm)]. Multi-marker models identified GDF-15 and IL-6 as joint risk predictors for risk of LC diagnosis, without further discrimination by CRP or NT-proBNP. A model based on age, sex, smoking-related variables, GFD-15 and IL-6 provided moderately strong discrimination for prediction of LC diagnoses within 9 years after blood sampling [area under the curve (AUC) =74.3% (57.3-90.2%)], compared to 67.0% (49.3-84.8%) for a model without biomarkers. For mortality by competing causes, a model including biomarkers resulted in an AUC of 76.2% (66.6-85.3%)], compared to 70.0% (60.9-77.9%) a model including age, sex and smoking variables.

Conclusions

Serum GDF-15 and IL-6 may be useful indicators for estimating risks for LC and competing mortality among long-term smokers participating in LC screening, to optimize LC screening strategies.

Conducting polymer composite-based biosensing materials for the diagnosis of lung cancer: A review

The development of a simple and fast cancer detection method is crucial since early diagnosis is a key factor in increasing survival rates for lung cancer patients. Among several diagnosis methods, the electrochemical sensor is the most promising one due to its outstanding performance, portability, real-time analysis, robustness, amenability, and cost-effectiveness. Conducting polymer (CP) composites have been frequently used to fabricate a robust sensor device, owing to their excellent physical and electrochemical properties as well as biocompatibility with nontoxic effects on the biological system. This review brings up a brief overview of the importance of electrochemical biosensors for the early detection of lung cancer, with a detailed discussion on the design and development of CP composite materials for biosensor applications. The review covers the electrochemical sensing of numerous lung cancer markers employing composite electrodes based on the conducting polyterthiophene, poly(3,4-ethylenedioxythiophene), polyaniline, polypyrrole, molecularly imprinted polymers, and others. In addition, a hybrid of the electrochemical biosensors and other techniques was highlighted. The outlook was also briefly discussed for the development of CP composite-based electrochemical biosensors for POC diagnostic devices.

Liquid Biopsy as an Adjunct to Lung Screening Imaging

Current lung cancer screening protocols use low-dose computed tomography scans in selected high-risk individuals. Unfortunately, utilization is low, and the rate of false-positive screens is high. Peripheral biomarkers carry meaningful promise in diagnosing and monitoring cancer with added potential advantages reducing invasive procedures and improving turnaround time. Herein, the use of such blood-based assays is considered as an adjunct to further utilization and accuracy of lung cancer screening.

Circulating proteome for pulmonary nodule malignancy

BACKGROUND

Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules.

METHODS

Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated.

RESULTS

We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001).

CONCLUSIONS

Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.

Early detection of lung cancer using artificial intelligence-enhanced optical nanosensing of chromatin alterations in field carcinogenesis

Supranucleosomal chromatin structure, including chromatin domain conformation, is involved in the regulation of gene expression and its dysregulation has been associated with carcinogenesis. Prior studies have shown that cells in the buccal mucosa carry a molecular signature of lung cancer among the cigarette-smoking population, the phenomenon known as field carcinogenesis or field of injury. Thus, we hypothesized that chromatin structural changes in buccal mucosa can be predictive of lung cancer. However, the small size of the chromatin chain (approximately 20 nm) folded into chromatin packing domains, themselves typically below 300 nm in diameter, preclude the detection of alterations in intradomain chromatin conformation using diffraction-limited optical microscopy. In this study, we developed an optical spectroscopic statistical nanosensing technique to detect chromatin packing domain changes in buccal mucosa as a lung cancer biomarker: chromatin-sensitive partial wave spectroscopic microscopy (csPWS). Artificial intelligence (AI) was applied to csPWS measurements of chromatin alterations to enhance diagnostic performance. Our AI-enhanced buccal csPWS nanocytology of 179 patients at two clinical sites distinguished Stage-I lung cancer versus cancer-free controls with an area under the ROC curve (AUC) of 0.92 ± 0.06 for Site 1 (in-state location) and 0.82 ± 0.11 for Site 2 (out-of-state location).

ERS International Congress 2022: highlights from the Thoracic Oncology Assembly

Thoracic malignancies are associated with a substantial public health burden. Lung cancer is the leading cause of cancer-related mortality worldwide, with significant impact on patients' quality of life. Following 2 years of virtual European Respiratory Society (ERS) Congresses due to the COVID-19 pandemic, the 2022 hybrid ERS Congress in Barcelona, Spain allowed peers from all over the world to meet again and present their work. Thoracic oncology experts presented best practices and latest developments in lung cancer screening, lung cancer diagnosis and management. Early lung cancer diagnosis, subsequent pros and cons of aggressive management, identification and management of systemic treatments' side-effects, and the application of artificial intelligence and biomarkers across all aspects of the thoracic oncology pathway were among the areas that triggered specific interest and will be summarised here.

Plasma protein biomarkers for early prediction of lung cancer

BACKGROUND

Individual plasma proteins have been identified as minimally invasive biomarkers for lung cancer diagnosis with potential utility in early detection. Plasma proteomes provide insight into contributing biological factors; we investigated their potential for future lung cancer prediction.

METHODS

The Olink® Explore-3072 platform quantitated 2941 proteins in 496 Liverpool Lung Project plasma samples, including 131 cases taken 1-10 years prior to diagnosis, 237 controls, and 90 subjects at multiple times. 1112 proteins significantly associated with haemolysis were excluded. Feature selection with bootstrapping identified differentially expressed proteins, subsequently modelled for lung cancer prediction and validated in UK Biobank data.

FINDINGS

For samples 1-3 years pre-diagnosis, 240 proteins were significantly different in cases; for 1-5 year samples, 117 of these and 150 further proteins were identified, mapping to significantly different pathways. Four machine learning algorithms gave median AUCs of 0.76-0.90 and 0.73-0.83 for the 1-3 year and 1-5 year proteins respectively. External validation gave AUCs of 0.75 (1-3 year) and 0.69 (1-5 year), with AUC 0.7 up to 12 years prior to diagnosis. The models were independent of age, smoking duration, cancer histology and the presence of COPD.

INTERPRETATION

The plasma proteome provides biomarkers which may be used to identify those at greatest risk of lung cancer. The proteins and the pathways are different when lung cancer is more imminent, indicating that both biomarkers of inherent risk and biomarkers associated with presence of early lung cancer may be identified.

FUNDING

Janssen Pharmaceuticals Research Collaboration Award; Roy Castle Lung Cancer Foundation.

The use of biomarkers in the diagnosis of lung cancer

Using a simple 10 to 20 milliliters of blood sample in order to make the diagnosis of lung cancer is the dream of every patient and practitioner. In fact, even if tissue samples or bronchial liquid represent the gold standard for microscopic diagnosis, using less invasive procedures represented the aim of many researches published in the literature. The utility of biomarkers has been widely reported in screening context, mainly in association to low dose CT-scan, or in therapeutic context in order to highlight therapeutic targets or to change treatment in a context of resistance to target therapies. The use of biomarkers in a diagnostic context has been recently highlighted in the literature. The authors aimed to present a general review of different biomarkers that could be used in the diagnosis of lung cancer.

circPTN Promotes the Progression of Non-Small Cell Lung Cancer through Upregulation of E2F2 by Sponging miR-432-5p

Background

Non-small cell lung cancer (NSCLC) is one of the most prevalent cancers, accounting for around 80% of total lung cancer cases worldwide. Exploring the function and mechanism of circRNAs could provide insights into the diagnosis and treatment for NSCLC.

Methods

In this study, we collected tumor tissues and adjacent normal tissues from NSCLC patients to detect the expression level of circPTN and analyzed the association of its expression level with the clinicopathological parameter of NSCLC patients. Moreover, the functional engagement of circPTN in NSCLC cells was examined by cell counting kit-8 (CCK-8) cell proliferation assay, transwell migration and invasion assays, and tube formation assay. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting (WB) analysis were used to detect gene and protein expression, respectively. The molecular targets of cicrPTN were predicted using starBase online resources, which was validated by RNA immunoprecipitation (RIP) and dual-luciferase reporter assay.

Results

Compared with adjacent normal tissues, there was a remarkable increase of the circPTN levels in NSCLC tissues. A high level of circPTN expression was associated with more lymph node metastasis (LNM) and advanced TNM stages. Functionally, circPTN knockdown inhibited the proliferation, migration, and invasion and tube formation ability of NSCLC cells. We further demonstrated that circPTN regulated the malignant phenotype of NSCLC cells through targeting the miR-432-5p/E2F2 axis.

Conclusion

Together, our results suggest that circPTN, which is upregulated in NSCLC tissues, could serve as a prognostic marker for NSCLC patients. circPTN regulates the malignant progression of NSCLC cells through targeting the miR-432-5p/E2F2 axis, which may be employed as a potential strategy for the management of NSCLC.

Dimeric-(-)-epigallocatechin-3-gallate inhibits the proliferation of lung cancer cells by inhibiting the EGFR signaling pathway

Non-small cell lung cancer (NSCLC) is one of the most general malignant tumors. The overexpression of epidermal growth factor receptor (EGFR) is a common marker in NSCLC, and it plays an important role in the proliferation, invasion, and metastasis of cancer cells. At present, drugs developed with EGFR as a target suffer from drug resistance, so it is necessary to study new compounds for the treatment of NSCLC. The active substance in green tea is EGCG, which has anti-cancer effects. In this study, we synthesized dimeric-(-)-epigallocatechin-3-gallate (prodelphinidin B-4-3,3‴-di-O-gallate, PBOG), and explored the effect of PBOG on lung cancer cells. PBOG can inhibit the proliferation and migration of NCI-H1975 cells, promote cell apoptosis, and inhibit cell cycle progression. In addition, PBOG can bind to the EGFR ectodomain protein and change the secondary structure of the protein. At the same time, PBOG decreases the expression of EGFR and downstream protein phosphorylation. Animal experiments confirmed that PBOG can inhibit tumor growth by inhibiting EGFR phosphorylation. Collectively, our study results show that PBOG may induce a decrease in intracellular phosphorylated EGFR expression by binding to the EGFR ectodomain protein, thereby inducing apoptosis and inhibiting cell cycle progression, thus providing a new strategy to treat lung cancer.

NEIL3 Mediates Lung Cancer Progression and Modulates PI3K/AKT/mTOR Signaling: A Potential Therapeutic Target

Background. Nei endonuclease VIII-like 3 (NEIL3) is widely involved in pathophysiological processes of the body; however, its role in lung cancer has not been conclusively determined. Objective. This study is aimed at exploring the role of NEIL3 in lung cancer. Methods. The public data used in this study were downloaded from The Cancer Genome Atlas (TCGA) database. “Limma” in R was used for the analysis of differentially expressed genes. Clinical correlations and prognostic analyses were performed using the survival package in R. The proliferative abilities of lung cancer cells were evaluated by the CCK8 and colony formation assays while their invasive and migration abilities were assessed by the transwell and wound healing assays. Quantitative real-time PCR (qRT-PCR) and western blot analyses were utilized to detect RNA and protein levels. Biological differences between groups were determined by gene set enrichment analysis (GSEA). Tumor Immune Dysfunction and Exclusion (TIDE) as well as Genomics of Drug Sensitivity in Cancer (GDSC) was used for immunotherapeutic and chemotherapeutic sensitivity analyses. Results. NEIL3 was upregulated in NSCLC tissues and cell lines, implying that it is involved in lung cancer initiation and progression. Clinical correlation and prognostic analyses showed that NEIL3 was associated with worse clinical features (stage and T and N classifications) and poor prognostic outcomes. In vitro, NEIL3 significantly enhanced NSCLC proliferation, invasion, and migration. GSEA indicated that NEIL3 might be involved in PI3K/AKT/mTOR, G2/M checkpoints, and E2F target pathways. Inhibition of NEIL3 suppressed cyclinD1 and p-AKT protein levels; however, it had no effects on AKT levels, indicating that NEIL3 can partially activate the PI3K/AKT/mTOR signaling pathway. The predicted result of TIDE indicated that immunotherapeutic nonresponders had elevated NEIL3 levels. Moreover, there was a positive correlation between NEIL3 levels and chemosensitivity to cisplatin and paclitaxel. Conclusion. In general, NEIL3 mediates NSCLC progression and affects sensitivity to immunotherapy and chemotherapy; therefore, it is a potential molecular target for treatment.

Clinical Implications of Circulating Circular RNAs in Lung Cancer

Circular RNAs (circRNAs) are single-stranded RNAs with a covalently closed-loop structure that increases their stability; thus, they are more advantageous to use as liquid biopsy markers than linear RNAs. circRNAs are thought to be generated by back-splicing of pre-mRNA transcripts, which can be facilitated by reverse complementary sequences in the flanking introns and trans-acting factors, such as splicing regulatory factors and RNA-binding factors. circRNAs function as miRNA sponges, interact with target proteins, regulate the stability and translatability of other mRNAs, regulate gene expression, and produce microproteins. circRNAs are also found in the body fluids of cancer patients, including plasma, saliva, urine, and cerebrospinal fluid, and these “circulating circRNAs” can be used as cancer biomarkers. In lung cancer, some circulating circRNAs have been reported to regulate cancer progression and drug resistance. Circulating circRNAs have significant diagnostic value and are associated with the prognosis of lung cancer patients. Owing to their functional versatility, heightened stability, and practical applicability, circulating circRNAs represent promising biomarkers for lung cancer diagnosis, prognosis, and treatment monitoring.

Computational Analyses of YY1 and Its Target RKIP Reveal Their Diagnostic and Prognostic Roles in Lung Cancer

Simple Summary

Lung cancer (LC) is the tumor with the highest global mortality rate. Novel personalized therapies are currently being tested (e.g., targeted inhibitors, the immune-checkpoint inhibitors), but they cannot yet prevent the very frequent relapse and generalized metastases observed in a large population of LC patients. Currently, there is an urgent need for novel reliable biomarkers for the prognosis and diagnosis of LC. Through the systematic analysis of multiple deposited expression datasets, this report aims to explore the role of the Yin-Yang 1 (YY1) transcription factor and its target the Raf Kinase Inhibitory Protein (RKIP) in LC. The computational analysis suggested the predictive diagnostic and prognostic roles for both YY1 and RKIP stimulating further studies for proving their implication as novel biomarkers, as well as therapeutically druggable targets in LC.

Abstract

Lung cancer (LC) represents a global threat, being the tumor with the highest mortality rate. Despite the introduction of novel therapies (e.g., targeted inhibitors, immune-checkpoint inhibitors), relapses are still very frequent. Accordingly, there is an urgent need for reliable predictive biomarkers and therapeutically druggable targets. Yin-Yang 1 (YY1) is a transcription factor that may work either as an oncogene or a tumor suppressor, depending on the genotype and the phenotype of the tumor. The Raf Kinase Inhibitory Protein (RKIP), is a tumor suppressor and immune enhancer often found downregulated in the majority of the examined cancers. In the present report, the role of both YY1 and RKIP in LC is thoroughly explored through the analysis of several deposited RNA and protein expression datasets. The computational analyses revealed that YY1 negatively regulates RKIP expression in LC, as corroborated by the deposited YY1-ChIP-Seq experiments and validated by their robust negative correlation. Additionally, YY1 expression is significantly higher in LC samples compared to normal matching ones, whereas RKIP expression is lower in LC and high in normal matching tissues. These observed differences, unlike many current biomarkers, bear a diagnostic significance, as proven by the ROC analyses. Finally, the survival data support the notion that both YY1 and RKIP might represent strong prognostic biomarkers. Overall, the reported findings indicate that YY1 and RKIP expression levels may play a role in LC as potential biomarkers and therapeutic targets. However, further studies will be necessary to validate the in silico results.

EF. Prognostic significance of a complement factor H autoantibody in early stage NSCLC

BACKGROUND: Biomarkers that predict which patients with early stage NSCLC will develop recurrent disease would be of clinical value. We previously discovered that an autoantibody to a complement regulatory protein, complement factor H (CFH), is associated with early stage, non-recurrent NSCLC, and hypothesized that the anti-CFH antibody inhibits metastasis. OBJECTIVES: The primary objective of this study was to evaluate the anti-CFH antibody as a prognostic marker for recurrence in stage I NSCLC. A secondary objective was to determine if changes in antibody serum level one year after resection were associated with recurrence. METHODS: Anti-CFH antibody was measured in the sera of 157 stage I NSCLC patients designated as a prognostic cohort: 61% whose cancers did not recur, and 39% whose cancers recurred following resection. Impact of anti-CFH antibody positivity on time to recurrence was assessed using a competing risk analysis. Anti-CFH antibody levels were measured before resection and one year after resection in an independent temporal cohort of 47 antibody-positive stage I NSCLC patients: 60% whose cancers did not recur and 40% whose cancers recurred following resection. The non-recurrent and recurrent groups were compared with respect to the one-year percent change in antibody level. RESULTS: In the prognostic cohort, the 60-month cumulative incidence of recurrence was 40% and 22% among antibody negative and positive patients, respectively; this difference was significant (Gray’s test, P= 0.0425). In the temporal cohort, the antibody persisted in the serum at one year post-tumor resection. The change in antibody levels over the one year period was not statistically different between the non-recurrent and recurrent groups (Wilcoxon two-sample test, P= 0.4670). CONCLUSIONS: The anti-CFH autoantibody may be a useful prognostic marker signifying non-recurrence in early stage NSCLC patients. However, change in the level of this antibody in antibody-positive patients one year after resection had no association with recurrence.

The Liquid Biopsy for Lung Cancer: State of the Art, Limitations and Future Developments

Simple Summary

During the development and progression of lung tumors, processes such as necrosis and vascular invasion shed tumor cells or cellular components into various fluid compartments. Liquid biopsies consist of obtaining a bodily fluid, typically peripheral blood, in order to isolate and investigate these shed tumor constituents. Circulating tumor cells (CTCs) are one such constituent, which can be isolated from blood and can act as a diagnostic aid and provide valuable prognostic information. Liquid-based biopsies may also have a potential future role in lung cancer screening. Circulating tumor DNA (ctDNA) is found in small quantities in blood and, with the recent development of sensitive molecular and sequencing technologies, can be used to directly detect actionable genetic alterations or monitor for resistance mutations and guide clinical management. While potential benefits of liquid biopsies are promising, they are not without limitations. In this review, we summarize the current state and limitations of CTCs and ctDNA and possible future directions.

Abstract

Lung cancer is a leading cause of cancer-related deaths, contributing to 18.4% of cancer deaths globally. Treatment of non-small cell lung carcinoma has seen rapid progression with targeted therapies tailored to specific genetic drivers. However, identifying genetic alterations can be difficult due to lack of tissue, inaccessible tumors and the risk of complications for the patient with serial tissue sampling. The liquid biopsy provides a minimally invasive method which can obtain circulating biomarkers shed from the tumor and could be a safer alternative to tissue biopsy. While tissue biopsy remains the gold standard, liquid biopsies could be very beneficial where serial sampling is required, such as monitoring disease progression or development of resistance mutations to current targeted therapies. Liquid biopsies also have a potential role in identifying patients at risk of relapse post treatment and as a component of future lung cancer screening protocols. Rapid developments have led to multiple platforms for isolating circulating tumor cells (CTCs) and detecting circulating tumor DNA (ctDNA); however, standardization is lacking, especially in lung carcinoma. Additionally, clonal hematopoiesis of uncertain clinical significance must be taken into consideration in genetic sequencing, as it introduces the potential for false positives. Various biomarkers have been investigated in liquid biopsies; however, in this review, we will concentrate on the current use of ctDNA and CTCs, focusing on the clinical relevance, current and possible future applications and limitations of each.

The Lipid Composition of Serum-Derived Small Extracellular Vesicles in Participants of a Lung Cancer Screening Study

Simple Summary

Molecular components of extracellular vesicles present in serum are potential biomarkers of lung cancer, however, none of them have been validated in the context of an actual early detection of lung cancer. Here, we compared the lipid profiles of vesicles obtained from participants in a lung cancer screening study, including patients with screening-detected cancer and individuals with benign pulmonary nodules or without pathological changes. A few lipids whose levels were different between compared groups were detected, including ceramide Cer(42:1) upregulated in vesicles from cancer patients. Furthermore, a high heterogeneity of lipid profiles of extracellular vesicles was observed, which impaired the performance of classification models based on specific compounds.

Abstract

Molecular components of exosomes and other classes of small extracellular vesicles (sEV) present in human biofluids are potential biomarkers with possible applicability in the early detection of lung cancer. Here, we compared the lipid profiles of serum-derived sEV from three groups of lung cancer screening participants: individuals without pulmonary alterations, individuals with benign lung nodules, and patients with screening-detected lung cancer (81 individuals in each group). Extracellular vesicles and particles were purified from serum by size-exclusion chromatography, and a fraction enriched in sEV and depleted of low-density lipoproteins (LDLs) was selected (similar sized vesicles was observed in all groups: 70–100 nm). The targeted mass-spectrometry-based approach enabled the detection of 352 lipids, including 201 compounds used in quantitative analyses. A few compounds, exemplified by Cer(42:1), i.e., a ceramide whose increased plasma/serum level was reported in different pathological conditions, were upregulated in vesicles from cancer patients. On the other hand, the contribution of phosphatidylcholines with poly-unsaturated acyl chains was reduced in vesicles from lung cancer patients. Cancer-related features detected in serum-derived sEV were different than those of the corresponding whole serum. A high heterogeneity of lipid profiles of sEV was observed, which markedly impaired the performance of classification models based on specific compounds (the three-state classifiers showed an average AUC = 0.65 and 0.58 in the training and test subsets, respectively).

Serum Metabolite Profiles in Participants of Lung Cancer Screening Study; Comparison of Two Independent Cohorts

Serum metabolome is a promising source of molecular biomarkers that could support early detection of lung cancer in screening programs based on low-dose computed tomography. Several panels of metabolites that differentiate lung cancer patients and healthy individuals were reported, yet none of them were validated in the population at high-risk of developing cancer. Here we analyzed serum metabolome profiles in participants of two lung cancer screening studies: MOLTEST-BIS (Poland, n = 369) and SMAC-1 (Italy, n = 93). Three groups of screening participants were included: lung cancer patients, individuals with benign pulmonary nodules, and those without any lung alterations. Concentrations of about 400 metabolites (lipids, amino acids, and biogenic amines) were measured by a mass spectrometry-based approach. We observed a reduced level of lipids, in particular cholesteryl esters, in sera of cancer patients from both studies. Despite several specific compounds showing significant differences between cancer patients and healthy controls within each study, only a few cancer-related features were common when both cohorts were compared, which included a reduced concentration of lysophosphatidylcholine LPC (18:0). Moreover, serum metabolome profiles in both noncancer groups were similar, and differences between cancer patients and both groups of healthy participants were comparable. Large heterogeneity in levels of specific metabolites was observed, both within and between cohorts, which markedly impaired the accuracy of classification models: The overall AUC values of three-state classifiers were 0.60 and 0.51 for the test (MOLTEST) and validation (SMAC) cohorts, respectively. Therefore, a hypothetical metabolite-based biomarker for early detection of lung cancer would require adjustment to lifestyle-related confounding factors that putatively affect the composition of serum metabolome.

Therapeutic potential of AMPK signaling targeting in lung cancer: Advances, challenges and future prospects

Lung cancer (LC) is a leading cause of death worldwide with high mortality and morbidity. A wide variety of risk factors are considered for LC development such as smoking, air pollution and family history. It appears that genetic and epigenetic factors are also potential players in LC development and progression. AMP-activated protein kinase (AMPK) is a signaling pathway with vital function in inducing energy balance and homeostasis. An increase in AMP:ATP and ADP:ATP ratio leads to activation of AMPK signaling by upstream mediators such as LKB1 and CamKK. Dysregulation of AMPK signaling is a common finding in different cancers, particularly LC. AMPK activation can significantly enhance LC metastasis via EMT induction. Upstream mediators such as PLAG1, IMPAD1, and TUFM can regulate AMPK-mediated metastasis. AMPK activation can promote proliferation and survival of LC cells via glycolysis induction. In suppressing LC progression, anti-tumor compounds including metformin, ginsenosides, casticin and duloxetine dually induce/inhibit AMPK signaling. This is due to double-edged sword role of AMPK signaling in LC cells. Furthermore, AMPK signaling can regulate response of LC cells to chemotherapy and radiotherapy that are discussed in the current review.

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.

Intratumoral Treatment with Chemotherapy and Immunotherapy for NSCLC with EBUS-TBNA 19G

Introduction: Immunotherapy is being used for the past five years either as first line or second line treatment with great results. Chemotherapy and radiotherapy have been also used as combination to immunotherapy to further enhance this type of treatment. Intratumoral treatment has been previously proposed as a treatment option for certain non-small cell lung cancer patients.

Patients and Methods: We recruited in total seventy four patients with non-small cell lung cancer in their second line treatment who received only chemotherapy in their first line treatment with programmed death-ligand-1 ≤ 50. Only adenocarcinoma or squamous cell carcinoma, and all negative for epidermal growth factor receptor, anaplastic lymphoma kinase, proto-oncogene tyrosine-protein kinase-1 and proto-oncogene B-Raf. Data were first examined with descriptive statistics choosing frequencies for categorical variables and histograms for the continuous ones. Twenty five received only intravenous immunotherapy and forty-nine intravenous cisplatin with immunotherapy. Data were first examined with descriptive statistics choosing frequencies for categorical variables and histograms for the continuous ones.

Results: The relationships between changes of performance status and disease progression were examined via a single correspondence analysis. The two-dimensional scores (coordinates) derived from the correspondence analysis were then regressed against the predictors to form distinct splits and nodes obtaining quantitative results. The best fit is usually achieved by lowering exhaustively the AICc criterion and looking in parallel the change of R² expecting improvements more than 5%. both types of therapy are capable of producing best ameliorative effects, when either the programmed death-ligand-1 expression or parenchymal site in joint with low pack years are present in the sampling data.

Conclusions: Intratumoral treatment combination with cisplatin plus immunotherapy indifferent of nivolumab or pembrolizumab combination is an effective choice. In specific for those with endobronchial lesions. Moreover; patients with programmed death-ligand-1 ≥ 50 had their performance status and disease progression improved over the eight month observation.

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.