Early Lung Cancer Screening Research Articles

Perfluorosulfonic acid polymer based eATRP for ultrasensitive detection of CYFRA21-1 DNA.

The sensitive detection of biomarker cytokeratin fragment antigen 21-1 (CYFRA21-1) is crucial for early diagnosis and screening of non-small cell lung cancer (NSCLC). In this work, an electrochemical biosensor based on Nafion-initiated eATRP has been built for ultrasensitive detection of CYFRA21-1 DNA for the first time. Specifically, peptide nucleic acid (PNA) probes are immobilized onto a gold electrode surface and then hybridized with target DNA to form PNA/DNA heteroduplexes for the subsequent attachment of Nafion by the identified carboxyl-Zr4+-phosphoric acid chemistry. Finally, polymer chains are obtained by linking the monomer of ferrocenylmethyl methacrylate to the PNA/MCH/DNA/Zr4+/Nafion probes via eATRP. Under optimized steady-state conditions, the sensor offers a wide current response for CYFRA21-1 DNA from 10-11 to 10-16 M with a detection limit of 6.42 × 10-17 M. The proposed method of using Nafion as the eATRP initiator exhibits high sensitivity, reproducibility and stability and is a promising strategy for early diagnosis of NSCLC.

Pulmonary nodule detection method based on convolutional neural network

A method was proposed to detect pulmonary nodules in low-dose computed tomography (CT) images by two-dimensional convolutional neural network under the condition of fine image preprocessing. Firstly, CT image preprocessing was carried out by image clipping, normalization and other algorithms. Then the positive samples were expanded to balance the number of positive and negative samples in convolutional neural network. Finally, the model with the best performance was obtained by training two-dimensional convolutional neural network and constantly optimizing network parameters. The model was evaluated in Lung Nodule Analysis 2016(LUNA16) dataset by means of five-fold cross validation, and each group's average model experiment results were obtained with the final accuracy of 92.3%, sensitivity of 92.1% and specificity of 92.6%.Compared with other existing automatic detection and classification methods for pulmonary nodules, all indexes were improved. Subsequently, the model perturbation experiment was carried out on this basis. The experimental results showed that the model is stable and has certain anti-interference ability, which could effectively identify pulmonary nodules and provide auxiliary diagnostic advice for early screening of lung cancer.

Clinicopathological characteristics and prognosis of lung cancer in young patients aged 30 years and younger.

Lung cancer is one of the most common malignant tumors in the world and mainly occurs in elderly patients, but rarely in young patients. The purpose of this retrospective study was to examine the clinicopathological features and prognosis of lung cancer patients aged 30 years and younger. Patients aged 30 years and younger with lung cancer admitted to our center from November 2013 to October 2018 were retrospectively identified. Data included sex, age, smoking history, family history of cancer, high resolution computed tomography results, size and location of tumors, histology of tumors, lymph node status, stage of tumors, treatment methods and prognosis of patients. The patient group included more females (56.3%) than males (43.7%) among lung cancer patients aged 30 and younger. Some patients had a history of tobacco inhalation and family cancer (17.5% and 22.3%, respectively). The most common tumors were in the left lower lobe (27.2%). Nearly half (49.5%) of the patients had pathological adenocarcinomas and 59.3% of the patients were showed early clinical stage and had no lymph node metastasis. All patients received surgical treatment; 47.1% received lobectomy and only 17.9% received adjuvant therapy such as radiotherapy, chemotherapy or targeted therapy after operation. Only seven (7.4%) of the successful follow-up patients died. Local recurrence occurred in two cases and distant metastasis in six cases. The main clinicopathological type of lung cancer in young lung cancer patients aged 30 years and younger is adenocarcinoma, and most cases were at the early stage. Surgical treatment based on lobectomy is still the main treatment method and the prognosis of these patients is very good. Early screening of lung cancer should be actively promoted for young people.

P1.11-27 Computed Tomography Screening for Early Lung Cancer, COPD and Cardiovascular Disease in Shanghai: Rationale and Design of a Population-Based Comparative Study

P1.11-27 Computed Tomography Screening for Early Lung Cancer, COPD and Cardiovascular Disease in Shanghai: Rationale and Design of a Population-Based Comparative Study

Application of sputum cell DNA ploidy quantitative analysis technique in early non-invasive screening of lung cancer

Objective To investigate the application value of sputum cell DNA ploidy quantitative analysis technique in early non-invasive screening of lung cancer. Methods The clinical data of 84 patients with lung cancer (lung cancer group) and 84 patients with benign lung disease (lung benign disease group) who were admitted to the Second Affiliated Hospital of Xuzhou Medical University from April 2016 to May 2017 were retrospectively analyzed, and 80 healthy subjects were selected as the control group. The sputum samples of all subjects were collected, and 55 corresponding lavage fluid samples in the lung cancer group were also collected. A fully automated cell tumor screening analysis system was used to make DNA ploidy quantitative analysis in all specimens, and the results were compared with sputum smear and liquid-based thin-layer cytology results. Results The positive detection rates of routine smear, liquid-based thin-layer cytology and DNA ploidy quantitative analysis in lung cancer group were 4.76% (4/84), 29.76% (25/84) and 45.24% (38/84). The positive detection rate of liquid-based thin-layer cytology and DNA ploidy quantitative analysis was higher than that of routine smear, and the differences were statistically significant (χ 2 = 18.38, P 0.05). Conclusions DNA ploidy quantitative analysis technique of sputum cells can directly reflect the malignant transformation of early lung cancer patients compared with traditional smear method and liquid-based thin-layer technology. Its positive detection rate is higher than that of the conventional detection method, which can be used as a valuable reference index for early screening of lung cancer. Key words: Lung neoplasms; Sputum; DNA ploidy; Diagnosis

Early lung cancer screening using double normalization-based multi-aggregation (DNMA) and Delphi methods with hesitant fuzzy information

Withthedevelopmentofeconomyandtheimprovementofpeople'slivingstandard, health has become one of the most important things that people pay attention to. Lung cancer, as one of the most serious malignant tumors threatening people's health, has a high mortality rate and a low cure rate for the reason that the early symptoms of it are not obvious. Usually, when a patient is found to have lung cancer, s/he is already at the middle or even the advanced stage. The early screening of lung cancer is of great significance for the effective treatment of lung cancer. The lung cancer screening process can be seen as a multi-criteria decision making problem. However, the nature of making a right decision for lung cancer screening is unstructured and complex since there are many factors that may affect such decisions. Furthermore, these factors are usually vague and difficult to evaluate precisely and numerically. The hesitant fuzzy set is a powerful tool to deal with uncertain and ambiguous information and has better applicability in quantifying such information. This study establishes a framework that uses the double normalization-based multi-aggregation method to solve the lung cancer screening problem. The critical factors for lung cancer screening are obtained by the fuzzy Delphi method. We adopt an illustrative example that is related to the lung cancer screening in a hospital of China to demonstrate the effectiveness of the proposed model. Furthermore, a comparison analysis is provided to verify the stability of the proposed method.

Abstract 3329: Lung cancer screening initiative and identification of novel blood biomarkers for early detection of lung cancer

Abstract In lung cancer, 81% of patients detected are late-stage, since early-stage patients are generally asymptomatic. Winnebago County has a 14% higher mortality rate for lung cancer when compared to the national rate; hence, to improve early detection of lung cancer in the Winnebago County, we implemented low-dose computed tomography (LDCT) screening. Currently, LDCT is used to detect lung cancer at early-stages, and the CDC has proposed new guidelines for early screening of lung cancer in individuals between 55-77 years of age with a 30 pack/year smoking history. Using circulating DNA from lung cancer patients and examining changes in methylation patterns in genes that are expressed in lung cancer patients can be used for early detection. Epidermal growth factor receptor (EGFR) is shown to be expressed in lung cancer patients’ serum in all stages; hence, it can be used as a potential biomarker for early detection. To improve early detection of lung cancer in the Winnebago County, we educated physicians/smokers about LDCT screenings to promote early detection of lung cancer. We evaluated the number of LDCTs performed and recorded the number of lung cancer cases detected in the Winnebago County between June 2015 to October 2017. To explore EGFR as a promising biomarker, plasma was separated from whole blood and collected. Circulating DNA was extracted with the MagMax cell-free circulating kit and bisulfite converted. Identification of percent methylation patterns in the EGFR promoter region in CpG islands was obtained after next generation sequencing (NGS) followed by bioinformatics analysis. In our study, 1,116 LDCT screenings occurred in the Winnebago County. Lung cancer was diagnosed in 19 patients, out of which 11 patients (57.8%) were early-stage patients. We detected 45.4% of patients screened that were present with nodules compared to 24.2% of patients in the National Lung Cancer Screening Trial. We observed that 1.70% of patients referred for LDCT screening were diagnosed with lung cancer, compared to 0.87% of patients in the National Lung Cancer Screening Trial. This may be due to the higher incidence of smoking in Winnebago County (18%) compared to the nation (15.5%). Our screening study had 96.3% false positives, which is comparable (96.4%) to the results obtained in the National Lung Cancer Screening Trial. Using NGS, methylation in the promoter region of EGFR was studied using degenerate EGFR primers. In the promoter region of EGFR, our analysis showed that there are regions of hypermethylation (68-86%) in three CpG islands in sequences at the beginning of the promoter (8-241 bases). However, there was hypomethylation (6-21%) at four CpG island further downstream (375-689 bases from the beginning of the promoter). Currently we are studying the methylation patterns in normal subjects to determine whether these regions which could be used as predictive biomarkers for early detection. Citation Format: Adijan Kuckovic, Joseph Berei, Shylendra Sreenivasappa, Joseph Ross, Sandra Martell, Connie Vitali, William Schulz, Neelu Puri. Lung cancer screening initiative and identification of novel blood biomarkers for early detection of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3329.

Computed Tomography Screening for Early Lung Cancer, COPD and Cardiovascular Disease in Shanghai, China

Computed Tomography Screening for Early Lung Cancer, COPD and Cardiovascular Disease in Shanghai, China

Screening for Early Lung Cancer, Chronic Obstructive Pulmonary Disease, and Cardiovascular Disease (the Big-3) Using Low-dose Chest Computed Tomography: Current Evidence and Technical Considerations.

Lung cancer, chronic obstructive pulmonary disease, and cardiovascular disease are highly prevalent in the general population and expected to cause most deaths by 2050. For these "Big-3," treatment might cure, delay, or stop the progression of disease at a very early stage. Lung nodule growth rate (a biomarker for lung cancer), emphysema/air trapping (a biomarker for chronic obstructive pulmonary disease), and coronary artery calcification (a biomarker for cardiovascular disease) are imaging biomarkers of early stages of the Big-3 that can be acquired with low-dose computed tomography (CT). We hypothesize that a (combined) low-dose CT examination for detection of all 3 diseases may significantly improve the cost-effectiveness of screening in the future. We review the current evidence of the imaging biomarkers for the detection of the Big-3 diseases and present the potential health economic potential of Big-3 screening. Furthermore, we review the low-dose CT protocols to acquire these biomarkers and describe the technical considerations when combining the CT protocols for the different biomarkers.

Five-year lung cancer mortality risk analysis and topography in Xuan Wei: a spatiotemporal correlation analysis

BackgroundIn Xuan Wei, China, the lung cancer mortality rate is rising significantly more than that of the nation overall. However, it remains unclear 1) if improved diagnosis can just partially explain this observation and how other local risk factors may be correlated with the lung cancer mortality rate and 2) how the lung cancer mortality rates differ within Xuan Wei and how these spatiotemporal patterns are linked with local risk factors. To increase etiological knowledge, this study evaluated the spatial and temporal distributions of the health effects (the lung cancer mortality rates) from 2011 to 2015.MethodsFour steps of spatial analysis were applied, as follows: 1) hotspot analysis to determine the geographical patterns of lung cancer mortality, 2) spatially-weighted sum to identify areas with higher health risks, 3) bivariate statistical analysis to assess the overall correlation between coal mines and lung cancer mortality, and 4) geographically-weighted regression to test for correlations among different towns within Xuan Wei.ResultsWomen had higher lung cancer mortality rates than those in men, with an increasing trend in both sexes over time. The incidence rates in Laibin Town were the highest in Xuan Wei every year. Over the 5-year study period, the lung cancer mortality was increasingly concentrated in Laibin, Shuanglong, and Longchang, where the smoky coal mines are most concentrated. The population-level health risks from the coal mine in Xuan Wei were mapped and divided into five types of risk areas (Type I – Type IV). Correlation analysis revealed that there was no significant correlation between lung cancer mortality as a whole and coal mine distribution during the 5-year study period. However, the geographically-weighted regression revealed a stronger correlation in medium (Type III) and second-lowest (Type IV) health risks.ConclusionsXuan Wei lung cancer mortality has increased continuously since the third national retrospective surveys on the causes of death by the Ministry of Health of the People’s Republic of China (2004–2005), especially for local women and residents over 35 years of age. Geographically, lung cancer in Xuan Wei showed unique spatiotemporal clustering. The local lung cancer mortality was significantly correlated with the smoky coal mine geographically. Some specific towns (Laibin, Shuanglong, and Longchang) within Xuan Wei manifested high correlations between lung cancer mortality and coal mines. The effects of coal mines on lung cancer mortality rates also spread geographically outward from these areas. Public health concern regarding lung cancer in Xuan Wei should prioritize higher-risk towns surrounded by smoking coal mines. Intervention strategies for particular toxic coal types require further studies on their chemical characteristics and mechanisms of carcinogenesis. Additional studies are also warranted to systematically examine the local environmental health risks related to coal industries and combustion air pollution and eventually to conduct early screening of lung cancer for local people who are more exposed to smoky coal in high-risk areas.

Multi-Resolution CNN and Knowledge Transfer for Candidate Classification in Lung Nodule Detection

The automatic lung nodule detection system can facilitate the early screening of lung cancer and timely medical interventions. However, there still exist multiple nodule candidates produced by initial rough detection in this system, and how to determine authenticity is a key problem. As this work is often challenged by the radiological heterogeneity of the computed tomography scans and the variable sizes of lung nodules, we put forward a multi-resolution convolutional neural network (CNN) to extract features of various levels and resolutions from different depth layers in the network for classification of lung nodule candidates. Through the use of knowledge transfer, the method can be divided into three steps. First, we transfer knowledge from the source CNN model which has been applied to edge detection and improve the model to a new multi-resolution model which is suitable for the image classification task. Then, the knowledge is transformed from source training progress so that all of the side-output branches in the model will be considered in the calculation. Moreover, the loss function and objective equation are improved to be image-wise calculation rather than pixel-wise. Finally, samples production and data enhancement are performed to train and test a classifier tailored for classification of lung nodule candidates. The experimental results on the LUNA16 data set show that our method gets an accuracy of 0.9733, a precision of 0.9673, and an AUC of 0.9954 while being used for lung nodule candidate classification, which is higher than the scores obtained by most of the state-of-the-art approach. In addition, when the test samples with three different sizes of 26*26, 36*36, and 48*48 are used to test the multi-resolution CNN, the accuracy rate of all three experiments exceed 92.81%, which demonstrates that the proposed model is insensitive to input scales.

Care Burden Derived from the Introduction of an Early Lung Cancer Screening Program in High-Risk HIV-Infected Patients.

We describe the care burden derived from a lung cancer screening program in high-risk patients with HIV. In a well-selected group with the described criteria, one annual low-dose thoracic computed tomographic exploration can be applied to 7.2% of the patients attended (95% confidence interval: 4.2-9.6), with at least one follow-up exploration in another 1.3%, with the generation of at least 2 extra visits for explanation of the protocol and results. If smoking habit does not change over the next 2 years, another 4.3% of the patients will have met the inclusion criteria. Early detection of lung cancer with low-dose thoracic computed tomographic could be of interest in HIV-infected patients because of the increased of risk but would imply an increase in care burden that must be taken into account.

Full Dose CT Database Induced Reconstruction With Nonlocal Means Prior for Ultra-Low-Dose Lung CT: A Preliminary Study

Although Low-dose computed tomography (LDCT) is the most effective way for early lung cancer screening, it's still a challenge to further reduce radiation dose on the premise of ensuring image quality. Penalized weighted least-squares (PWLS) image reconstruction with nonlocal means (NLM) prior has shown excellent performance to improve the image quality for LDCT, especially when the nonlocal weights are calculated from previous full-dose CT (FDCT) image. However, the previous FDCT image of the same patient is not readily available, and registration between the LDCT and FDCT images must be considered because of the scanning misalignment. This paper proposed a new NLM prior model to reconstruct high quality LDCT image without image registering. In order to estimate the nonlocal weights of NLM prior, a database was trained from FDCT images of different patients, from which the patch samples similar to each target patch of the LDCT were extracted. Then the nonlocal weights were determined by the patch samples, and integrated into PWLS reconstruction with the priori information of local structures from FDCT. Experiments with 10mAs LDCT data have shown its superiority in reducing noise, streaking artifacts and preserving structure detail, indicating the potential of further dose reduction in ultra-LDCT lung screening.

Non-Small Cell Lung Cancer in the Elderly: a Practical Approach to Screening, Diagnosis, and Treatment

Lung cancer is primarily a disease of the elderly. We summarize the literature on screening, diagnosis, and treatment of early non-small cell lung cancer in the elderly population. Lung cancer screening has resulted in a reduction in lung cancer mortality and is recommended in some patients up to 80 years old. Minimally invasive techniques, such as endobronchial ultrasound guided biopsy, have allowed for low diagnostic complications rates in elderly patients. Surgical treatment remains the standard of care; however, stereotactic body radiation therapy in non-operative candidates has similar outcomes with less morbidity. Decision to treat and choice of treatment should not be based on age alone, but should incorporate functional status, comorbid disease, and patient preference. Advances in screening, diagnostic techniques, and radiation therapies have transformed the management of early non-small cell lung cancer in the elderly. Further studies are needed incorporating larger numbers of geriatric patients in a disease that primarily affects the elderly.

Abstract 3249: Detection of early-stage malignant lung cancer using methylation signatures in circulating tumor DNA

Abstract Low-dose computed tomography (LDCT) is recommended for early lung cancer screening in high-risk populations. Small lung nodules are identified by these CT scans in up to 50% of high-risk patients. While over 50% of lung nodules less than 1 cm are benign, discriminating benign nodules from malignant nodules remains extremely challenging without an invasive lung biopsy. Taking advantage of methylation signatures in circulating tumor DNA (ctDNA), we developed a non-invasive screening assay to identify patients with malignant lung nodules from those with benign lung nodules. Methods: We first adopted Singlera's MONOD+ assay as a marker screening technology to interrogate the methylation state of over 4,000,000 CpG sites across more than 200,000 methylation haplotype blocks in the human genome from as little as 10 ng of cell-free or tissue DNA. We first processed 129 fresh frozen and FFPE tissue samples from healthy lung, benign lung nodules, and lung cancer at various stages of malignancy. We identified a preliminary set of methylation markers capable of segregating lung nodules by malignancy and invasiveness. To examine the reproducibility of these markers in plasma, we applied the same screening assay to plasma cell-free DNA from 46 healthy patients and 175 lung nodule patients with either benign or malignant nodules (most at an early stage of Ia1/Ia2). We refined the marker set by removing methylation markers that were unstable in plasma samples. We next applied Singlera's MethylTitan assay to deeply interrogate approximately 1,000 methylation haplotype blocks enriched in malignant lung nodules in plasma samples, as MethylTitan's higher conversion rate allowed us to better handle the limited amount of DNA in plasma samples. We ran the MethylTitan assay on both healthy and lung nodule plasma samples; using this method, we confirmed that tissue-derived methylation signatures could be rapidly screened in plasma samples in a high-throughput and highly sensitive manner. Results: Using the MONOD+ marker screening assay on plasma samples, we were able to utilize cell-free DNA methylation to identify early-stage malignant lung nodule patients with a sensitivity of 80.25% and a specificity of 83.08%. We were able to further improve upon these results using the MethylTitan assay, as we could more efficiently and more accurately screen the methylation markers in a large number of plasma samples. Conclusion: In summary, we have applied Singlera's MONOD+ and MethylTitan methylation assays to non-invasively identify early stage lung cancer in patients with small lung nodules. We are currently expanding this study to a much larger cohort of lung nodule patients in order to clinically validate our early lung cancer screening assay. The approach of using MONOD+ to identify markers and MethylTitan to analyze plasma samples will allow us to noninvasively screen for additional cancer types in a high-throughput clinical setting. Citation Format: Ruijun Liu, Xiaojie Li, Athurva Gore, Zi Qin, Jeff Gole, Qiye He, Rui Liu, Shun Lu. Detection of early-stage malignant lung cancer using methylation signatures in circulating tumor DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3249.

Rapid recognition of volatile organic compounds with colorimetric sensor arrays for lung cancer screening.

Volatile organic compounds (VOCs) in breath can be used as biomarkers to identify early stages of lung cancer. Herein, we report a disposable colorimetric array that has been constructed from diverse chemo-responsive colorants. Distinguishable difference maps were plotted within 4min for specifically targeted VOCs. Through the consideration of various chemical interactions with VOCs, the arrays successfully discriminate between 20 different volatile organic compounds in breath that are related to lung cancer. VOCs were identified either with the visualized difference maps or through pattern recognition with an accuracy of at least 90%. No uncertainties or errors were observed in the hierarchical cluster analysis (HCA). Finally, good reproducibility and stability of the array was achieved against changes in humidity. Generally, this work provides fundamental support for construction of simple and rapid VOC sensors. More importantly, this approach provides a hypothesis-free array method for breath testing via VOC profiling. Therefore, this small, rapid, non-invasive, inexpensive, and visualized sensor array is a powerful and promising tool for early screening of lung cancer. Graphical abstract A disposable colorimetric array has been developed with broadly chemo-responsive dyes to incorporate various chemical interactions, through which the arrays successfully discriminate 20 VOCs that are related to lung cancer via difference maps alone or chemometrics within 4min. The hydrophobic porous matrix provides good stability against changes in humidity.

Screening for early stage lung cancer and its correlation with lung nodule detection.

Currently, the most effective way of reducing lung cancer mortality is early diagnosis of lung cancer. The National Lung Screening Trial has proved the efficacy of lung cancer screening using low-dose computed tomography to reduce lung cancer mortality. However, many questions remain surrounding lung cancer screening implementation, among which include how to select the optimal risk population, the personalized screening interval based different levels of risk, methods to improve diagnostic discrimination between malignant and benign disease in detected lung nodules, and the roles of biomolecular markers in stratifying risk and in guiding the management of indeterminate nodules. This review concentrates on the latest developments of lung cancer screening and provides an overview of the main unanswered questions on lung nodule detection.

Identification and imaging of miR-155 in the early screening of lung cancer by targeted delivery of octreotide-conjugated chitosan-molecular beacon nanoparticles

Lung cancer is still the most common cancer globally. Early screening remains the key to improve the prognosis of patients. There is currently a lack of specific and sensitive methods for early screening of lung cancer. In recent years, studies have found that microRNA plays an important role in the occurrence and development of lung cancer and become a biological target in the early diagnosis of lung cancer. In this study, lung cancer cells, subcutaneous xenografts of lung cancer in nude mice, and Lox-Stop-lox K-ras G12D transgenic mice were used as models. The transgenic mice displayed the dynamic processes from normal lung tissue to atypical hyperplasia, adenomas, carcinoma in situ and lung adenocarcinoma. It was found that miR-155 and somatostatin receptor 2 (SSTR2) were expressed in all the disease stages of transgenic mice. Through molecular beacon (MB) technology and nanotechnology, chitosan-molecular beacon (CS-MB) nanoparticles and targeted octreotide (OCT) were conjugated and synthesized. The octreotide-conjugated chitosan-molecular beacon nanoparticles (CS-MB-OCT) can specifically bind to SSTR2 expressed by the lung cancer cells to achieve the goal of identification of lung cancer cells and imaging miR-155 in vivo and in vitro. Fluorescence imaging at different disease stages of lung cancer in Lox-Stop-lox K-ras G12D transgenic mice was performed, and could dynamically monitor the occurrence and development of lung cancer by different fluorescence intensity ranges. The current research, in turn, provides new idea, new method, and new technology for the early screening of lung cancer.

早期肺癌无创筛查方法的研究进展

早期肺癌无创筛查方法的研究进展

Metabolome-based biomarkers: their potential role in the early detection of lung cancer.

Lung cancer is the leading cause of cancer-related death worldwide, and a major problem affecting its mortality is the late diagnosis of the majority of cases, where treatment options are limited and overall prognosis is very bad. Currently, a low-dose computed tomography (LD-CT) screening in the high-risk group is the only available diagnostic strategy that could reduce mortality due to this malignancy. However, the LD-CT screening test suffers from a high false positive rate. Hence, complementation of LD-CT examination with blood-based biomarkers is a rational approach to increase efficacy and reduce the cost of early lung cancer screening programs. Several molecular signatures that discriminate between patients with early lung cancer and healthy individuals have been proposed in recent years, which are based on components of serum/plasma metabolome. However, none of these signatures has been validated by independent studies based on material collected during real lung cancer screening. Therefore, the validation of the real diagnostic value of these otherwise promising candidates remains a critical step in this challenging field of cancer diagnostics.