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Aim: To investigate the clinicopathological factors affecting the mSHOX2/mPTGER4 assay performance and its application in lung cancer detection in Chinese population. Materials & methods: A total of 455 subjects were recruited in this case–control study (302 untreated lung cancer patients, 153 normal subjects). Blood samples were collected before therapy and the mSHOX2/mPTGER4 level was measured with Epi proLung assay. Results: The mSHOX2/mPTGER4 sensitivity was 75.6% at 84.8% specificity. Both markers showed stage-dependent sensitivity. mSHOX2 was more sensitive to small-cell lung cancer and mPTGER4 was more sensitive to poorly differentiated lung cancer. Sensitivity increased with age but was not affected by sex. The mPRGER4/ mSHOX2 sensitivity was significantly higher than that of protein markers. Conclusion: The mSHOX2/ mPTGER4 assay showed some values with more limitations in lung cancer early detection.

Lung cancer is a devastating disease affecting hundreds of thousands of patients in Europe. Despite recent advances in treatment, its prognosis remains poor. This is mainly attributed to the late stages that diagnoses are usually established at, consequently excluding curative treatment options. During the 2019 European Respiratory Society International Congress in Madrid, Spain, lung cancer experts presented the most recent aspects of lung cancer early detection with low-dose computed tomography., Key thoracic oncology highlights from #ERSCongress Madrid 2019 https://bit.ly/3dQZtv7

Simple Summary Lung cancer is the leading cause of cancer death worldwide. Detecting lung malignancies promptly is essential for any anticancer treatment to reduce mortality and morbidity, especially in high-risk individuals. The use of liquid biopsy to detect circulating biomarkers such as RNA, microRNA, DNA, proteins, autoantibodies in the blood, as well as circulating tumor cells (CTCs), can substantially change the way we manage lung cancer patients by improving disease stratification using intrinsic molecular characteristics, identification of therapeutic targets and monitoring molecular residual disease. Here, we made an update on recent developments in liquid biopsy-based biomarkers for lung cancer early diagnosis, and we propose guidelines for an accurate study design, execution, and data interpretation for biomarker development. Abstract Lung cancer burden is increasing, with 2 million deaths/year worldwide. Current limitations in early detection impede lung cancer diagnosis when the disease is still localized and thus more curable by surgery or multimodality treatment. Liquid biopsy is emerging as an important tool for lung cancer early detection and for monitoring therapy response. Here, we reviewed recent advances in liquid biopsy for early diagnosis of lung cancer. We summarized DNA- or RNA-based biomarkers, proteins, autoantibodies circulating in the blood, as well as circulating tumor cells (CTCs), and compared the most promising studies in terms of biomarkers prediction performance. While we observed an overall good performance for the proposed biomarkers, we noticed some critical aspects which may complicate the successful translation of these biomarkers into the clinical setting. We, therefore, proposed a roadmap for successful development of lung cancer biomarkers during the discovery, prioritization, and clinical validation phase. The integration of innovative minimally invasive biomarkers in screening programs is highly demanded to augment lung cancer early detection.

Background: Early stages of lung cancer have a better prognosis than later stages. The accuracy of current lung cancer early detection methods is relatively poor. We firstly try to use circRNAs of platelets enable blood-based early detection of lung cancer. Methods: We did a three-stage study that included healthy controls, benign lung nodule, and patients with diagnosed lung cancer from two hospitals in China. We used High-throughput Illumina sequencing analysis to profile circRNAs expression in the 8 patients with lung cancer and 8 non-cancer controls (including healthy controls and benign lung nodule patients). Using a training cohort of patients with lung cancer and non-cancer controls, we built a circRNAs classifier to detect lung cancer. Then, the classifiers’ ability was validated in two independent cohorts of patients and non-cancer controls. We used the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) to evaluate diagnostic performance. Findings: Between Aug 1, 2018, and September 31, 2019, we recruited 88 participants to the training cohort, and 694 and 605 participants to the two independent validation cohorts. A signature comprising 23 circRNAs was identified by RNA-Seq analysis in the discovery stage. Then, four circRNAs (CD274, TIMP1, FLNA, ITGA2B) was found to have the possibility to serve as biomarkers for LC detection in the training stage by qRT-PCR. These selected four circRNAs from platelets was identified and subsequently assessed in the two independent validation cohorts. The area under the curve (AUC) for the five circRNAs from platelets (Pcs) were 0.975 in the validation cohort. In the following blinded test including the platelets from benign pulmonary nodule, LC patients and LC patients after surgery, Pcs correctly discriminated the patients with 90.6% sensitivity and 96.3% specificity. Interpretation: CircRNAs from platelets are very promising biomarkers for early stages of lung cancer diagnosis with very high sensitivity and specificity. This novel technology could serve as a Non-invasive, highly accurate diagnostic tool for lung nodule carriers that difficult to distinguish malignance from benign ones. Funding Statement: This work was supported by grants from National Natural Science Foundation of China (81572262), Jiangsu Province’s Key provincial Talents Program (ZDRCA2016028), 333 high class Talented Man Project (BRA2016516) and The Natural Science Foundation of the Jiangsu Higher Education Institution of China (18KJB320006). Declaration of Interests: None declared. Ethics Approval Statement: The study was approved by institutional ethics committee in each study center.

The early detection of lung cancer continues to be a major clinical challenge. Using whole-transcriptome next-generation sequencing to analyze lung tumor and the matched noncancerous tissues, we previously identified 54 lung cancer-associated microRNAs (miRNAs). The objective of this study was to investigate whether the miRNAs could be used as plasma biomarkers for lung cancer. We determined expressions of the lung tumor-miRNAs in plasma of a development cohort of 180 subjects by using reverse transcription PCR to develop biomarkers. The development cohort included 92 lung cancer patients and 88 cancer-free smokers. We validated the biomarkers in a validation cohort of 64 individuals comprising 34 lung cancer patients and 30 cancer-free smokers. Of the 54 miRNAs, 30 displayed a significant different expression level in plasma of the lung cancer patients vs. cancer-free controls (all P < 0.05). A plasma miRNA signature (miRs-126, 145, 210, and 205-5p) with the best prediction was developed, producing 91.5% sensitivity and 96.2% specificity for lung cancer detection. Diagnostic performance of the plasma miRNA signature had no association with stage and histological type of lung tumor, and patients’ age, sex, and ethnicity (all p > 0.05). The plasma miRNA signature was reproducibly confirmed in the validation cohort. The plasma miRNA signature may provide a blood-based assay for diagnosing lung cancer at the early stage, and thereby reduce the associated mortality and cost.

Introduction Low-dose computed tomography (LDCT) is used for screening for lung cancer (LC) in high-risk patients in the United States. The definition of high risk and the impact of frequent false-positive results of low-dose computed tomography remains a challenge. DNA methylation biomarkers are valuable noninvasive diagnostic tools for cancer detection. This study reports on the evaluation of methylation markers in plasma DNA for LC detection and discrimination of malignant from nonmalignant lung disease. Methods Circulating DNA was extracted from 3.5-mL plasma samples, treated with bisulfite using a commercially available kit, purified, and assayed by real-time polymerase chain reaction for assessment of DNA methylation of short stature homeobox 2 gene ( SHOX2 ), prostaglandin E receptor 4 gene ( PTGER4 ), and forkhead box L2 gene ( FOXL2 ). In three independent case-control studies these assays were evaluated and optimized. The resultant assay, a triplex polymerase chain reaction combining SHOX2 , PTGER4 , and the reference gene actin, beta gene ( ACTB ), was validated using plasma from patients with and without malignant disease. Results A panel of SHOX2 and PTGER4 provided promising results in three independent case-control studies examining a total of 330 plasma specimens (area under the receiver operating characteristic curve = 91%–98%). A validation study with 172 patient samples demonstrated significant discriminatory performance in distinguishing patients with LC from subjects without malignancy (area under the curve = 0.88). At a fixed specificity of 90%, sensitivity for LC was 67%; at a fixed sensitivity of 90%, specificity was 73%. Conclusions Measurement of SHOX2 and PTGER4 methylation in plasma DNA allowed detection of LC and differentiation of nonmalignant diseases. Development of a diagnostic test based on this panel may provide clinical utility in combination with current imaging techniques to improve LC risk stratification.

8553 Background: Lung cancer early detection improves survival, but risk-based low-dose CT screening (LDCT) only identifies a minority of patients. We implemented an ILNP in a community healthcare system, and evaluated its risks and benefits. Methods: Patients with lung lesions on routinely-performed radiologic studies were flagged by radiologists and triaged using evidence-based guidelines. We tracked demographics, clinical characteristics, procedures, complications, and health outcomes. We analyzed ILNP subjects’ eligibility for LDCT by National Lung Screening Trial (NLST), Center for Medicaid Services (CMS), NEderlands Leuvens Screening ONderzoek (NELSON), National Comprehensive Cancer Network (NCCN) Risk Groups 1 and 2 (screening recommended), NCCN Risk Group 3 (screening not currently recommended), and US Preventive Services Task Force (USPSTF) criteria from 2013 and 2020. Statistical analysis used the chi-square test and Kaplan Meier method. Results: From 2015-2020, 13,710 patients were evaluated in the ILNP program: median age, 64 years; 42% male; 65% White, 29% Black; 667 (4.9%) were diagnosed with lung cancer. Lung cancers diagnosed from ILNP were 39% adenocarcinoma / 20% Squamous Cell with clinical stage distribution 49% I, 8% II, 17% III, and 16% IV. 832 (6.1%) had invasive diagnostic testing- CT-guided biopsy (50%), bronchoscopy (30%), and/or EBUS (26%); 11% of the 832 had >1 invasive diagnostic test. The most common complications from invasive testing were pneumothorax and chest tube placement. Only 11%-20% of all ILNP patients would have been eligible for LDCT. In ILNP patients diagnosed with lung cancer, only 33% were eligible for screening by NLST criteria; the proportion increased substantially when USPSTF 2020 or NCCN Group 2 criteria were applied (Table). Compared to NLST, NCCN Group 2 criteria increased screening eligibility among cancer patients by 22% (from 33% to 55%), while only increasing screening eligibility by 6% (from 8% to 14%) in non-cancer patients. Aggregate 1-year and 3-year survival rates for lung cancer patient diagnosed through ILNP were 76% (95% CI: 73, 80) and 64% (95% CI: 59, 69). Conclusions: The ILNP identified early-stage lung cancer more frequently than most LDCT programs, with promising survival rates. The majority of subjects with lung cancer were not eligible for LDCT, we still need to optimize risk-based screening criteria. Even with new, expanded criteria for LDCT, structured ILNP is necessary to expand early detection of lung cancer.[Table: see text]

Molecularly targeted therapies and immune checkpoint inhibitors have markedly improved the therapeutic management of advanced lung cancer. However, it still remains the leading cause of cancer-related mortality worldwide, with disease stage at diagnosis representing the main prognostic factor. Detection of lung cancer at an earlier stage of disease, potentially susceptible of curative resection, can be critical to improve patients survival. Low-dose computed tomography (LDCT) screening of high-risk patients has been demonstrated to reduce mortality from lung cancer, but can be also associated with high false-positive rate, thus often resulting in unnecessary interventions for patients. Novel sensitive and specific biomarkers for identification of high-risk subjects and early detection that can be used alternatively and/or complement current routine diagnostic procedures are needed. Liquid biopsy has recently demonstrated its clinical usefulness in advanced NSCLC as a surrogate of tissue biopsy for noninvasive assessment of specific genomic alterations, thereby providing prognostic and predictive information. Different biosources from liquid biopsy, including cell free circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs), have also been widely investigated for their potential role in lung cancer diagnosis. This review will provide an overview on the circulating biomarkers being evaluated for lung cancer detection, mainly focusing on results from most recent studies, the techniques developed to perform their assessment in blood and other biologic fluids and challenges in their clinical applications.

Lung cancer is one of the leading causes of cancer-related deaths. Several diagnostic strategies are available but these are frequently ineffective, either because of their cost and organizational difficulty or because of the involvement of high radiations. As recent data from spiral computerized axial tomography have shown limited sensitivity and limited impact on cancer-related fatality, several options have been proposed in order to identify biological fluid-based biomarkers.Evaluating whether proteomic analysis of alveolar fluid obtained in the form of exhaled breath condensate (EBC) can be valuable for detecting and effectively diagnosing lung cancer.Careful review of recently published papers on proteomic EBC analysis, together with experience in the authors' laboratory, allows the discussion of benefits, pitfalls and possible future development of this approach.The rapid advancements of proteomics are expected to validate EBC protein(s) as lung pathology biomarker(s). Accessibility of an early marker of lung cancer will be a great advantage for potentially early treatment by surgical procedures with limited tissue removal, possibly preceding metastasis development.

e18527 Background: The LuCED test for lung cancer early detection analyzes non-invasive sputum using the Cell-CT system that images cells in true 3D to measure the biosignatures of cancer. Morphome...

Commentary on: Humphrey LL, Deffebach M, Pappas M, et al. Screening for lung cancer with low-dose computed tomography: a systematic review to update the US Preventive Services Task Force recommendation. Ann Intern Med 2013;159:411–20.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] The US Preventative Services Task Force (USPSTF) has published their long-awaited, updated systematic review of low-dose CT (LDCT) screening for lung cancer. Last reviewed in 2004, lung cancer screening has been under intense study worldwide for the past decade. The issue of lung cancer screening is important because lung cancer is the leading cause of cancer mortality in the USA and any method that improves lung cancer early detection and diagnosis has the potential to significantly impact … [1]: {openurl}?query=rft.jtitle%253DAnn%2BIntern%2BMed%26rft.volume%253D159%26rft.spage%253D411%26rft_id%253Dinfo%253Adoi%252F10.7326%252F0003-4819-159-6-201309170-00690%26rft_id%253Dinfo%253Apmid%252F23897166%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.7326/0003-4819-159-6-201309170-00690&link_type=DOI [3]: /lookup/external-ref?access_num=23897166&link_type=MED&atom=%2Febmed%2F19%2F4%2F150.atom [4]: /lookup/external-ref?access_num=000325625900017&link_type=ISI

Background: Lung cancer remains the major cause of cancer mortality in the world. In addition to primary prevention, earlier detection and more targeted treatments, tailored on the biological characteristics of the tumor and its microenvironment, could significantly reduce morbidity and mortality for this disease. The real efficacy of lung cancer screening by spiral-computed tomography (CT) in heavy smokers is still to be defined since, in spite of a proved capacity to detect small asymptomatic nodules, the frequency of false positive CTs as well as unnecessary treatments is very high if compared to the limited mortality reductions. The development of biomarkers able to identify tumors in a pre-clinical phase and to track the different aggressiveness of lung tumors is of paramount importance. microRNAs (miRNAs) represent a recently identified class of regulatory molecules and several studies showed that miRNA are involved in lung tumor development and progression and also circulate in plasma and serum of lung cancer patients. Materials and Methods: We analyzed miRNA profiles of lung tumors, normal lung tissues and plasma samples from cases with variable prognosis identified in two independent spiral-CT screening trials where multiple plasma samples, collected from one to four years before radiological detection of the disease were available. Results: We found miRNA expression profiles associated with aggressiveness of the disease and poor survival in tumors and also in normal lung tissues of the patients, thus proving the critical influence of a smoking-related lung microenvironment on tumor progression. Specific microRNA signatures were identified in plasma samples collected up to two years before spiral-CT detection of the disease, thus able to catch the earlier biological phases of disease development. We also defined a plasma signature that discriminates subjects according to aggressiveness of their future tumors, and in particular the occurrence of early metastatic but spiral-CT invisible lung tumors or small spiral-CT detected lesions with aggressive potential. Of interest plasma miRNas involved in the signatures of lung cancer risk and of aggressive disease more closely reflected miRNAs expressed in the normal lung rather than those characterizing the tumor samples of patients, supporting the concept that normal lung microenvironment has a critical influence on tumor development and aggressiveness. Conclusion: These results open up the prospective of using plasma miRNAs as non invasive lung cancer biomarkers.