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

International audienceBackground Lung cancer screening with low-dose chest CT (LDCT) reduces the mortality of eligible individuals. Bloodsignatures might act as a standalone screening tool, refine the selection of patients at risk, or help to classifyundetermined nodules detected on LDCT. We previously showed that circulating tumour cells (CTCs) could bedetected, using the isolation by size of epithelial tumour cell technique (ISET), long before the cancer was diagnosedradiologically. We aimed to test whether CTCs could be used as a biomarker for lung cancer screening.Methods We did a prospective, multicentre, cohort study in 21 French university centres. Participants had to beeligible for lung cancer screening as per National Lung Screening Trial criteria and have chronic obstructivepulmonary disease with a fixed airflow limitation defined as post-bronchodilator FEV1/FVC ratio of less than 0∙7.Any cancer, other than basocellular skin carcinomas, detected within the previous 5 years was the main exclusioncriterion. Participants had three screening rounds at 1-year intervals (T0 [baseline], T1, and T2), which involved LDCT,clinical examination, and a blood test for CTCs detection. Participants and investigators were masked to the results ofCTC detection, and cytopathologists were masked to clinical and radiological findings. Our primary objective was totest the diagnostic performance of CTC detection using the ISET technique in lung cancer screening, compared withcancers diagnosed by final pathology, or follow up if pathology was unavailable as the gold standard. This studyis registered with ClinicalTrials.gov identifier, number NCT02500693.Findings Between Oct 30, 2015, and Feb 2, 2017, we enrolled 614 participants, predominantly men (437 [71%]), aged65∙1 years (SD 6∙5), and heavy smokers (52∙7 pack-years [SD 21∙5]). 81 (13%) participants dropped out betweenbaseline and T1, and 56 (11%) did between T1 and T2. Nodules were detected on 178 (29%) of 614 baseline LDCTs.19 participants (3%) were diagnosed with a prevalent lung cancer at T0 and 19 were diagnosed with incident lungcancer (15 (3%) of 533 at T1 and four (1%) of 477 at T2). Extrapulmonary cancers were diagnosed in 27 (4%) ofparticipants. Overall 28 (2%) of 1187 blood samples were not analysable. At baseline, the sensitivity of CTC detectionfor lung cancer detection was 26∙3% (95% CI 11∙8–48∙8). ISET was unable to predict lung cancer or extrapulmonarycancer development

Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity

AbstractPatients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyze the transcriptomes of 611,398 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observe a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD AT2 cells express higher levels of genes linked directly to the efficiency of viral replication and the innate immune response. Additionally, we identify basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.</jats:p

Integrating artificial intelligence into lung cancer screening: a randomised controlled trial protocol

Introduction Lung cancer (LC) is the most common cause of cancer-related deaths worldwide. Its early detection can be achieved with a CT scan. Two large randomised trials proved the efficacy of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk populations. The decrease in specific mortality is 20%–25%.Nonetheless, implementing LCS on a large scale faces obstacles due to the low number of thoracic radiologists and CT scans available for the eligible population and the high frequency of false-positive screening results and the long period of indeterminacy of nodules that can reach up to 24 months, which is a source of prolonged anxiety and multiple costly examinations with possible side effects.Deep learning, an artificial intelligence solution has shown promising results in retrospective trials detecting lung nodules and characterising them. However, until now no prospective studies have demonstrated their importance in a real-life setting.Methods and analysis This open-label randomised controlled study focuses on LCS for patients aged 50–80 years, who smoked more than 20 pack-years, whether active or quit smoking less than 15 years ago. Its objective is to determine whether assisting a multidisciplinary team (MDT) with a 3D convolutional network-based analysis of screening chest CT scans accelerates the definitive classification of nodules into malignant or benign. 2722 patients will be included with the aim to demonstrate a 3-month reduction in the delay between lung nodule detection and its definitive classification into benign or malignant.Ethics and dissemination The sponsor of this study is the University Hospital of Nice. The study was approved for France by the ethical committee CPP (Comités de Protection des Personnes) Sud-Ouest et outre-mer III (No. 2022-A01543-40) and the Agence Nationale du Medicament et des produits de Santé (Ministry of Health) in December 2023. The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations.Trial registration number NCT05704920

Prospective Multicenter Validation of the Detection of ALK Rearrangements of Circulating Tumor Cells for Noninvasive Longitudinal Management of Patients With Advanced NSCLC

International audienceIntroduction: Patients with advanced-stage NSCLC whose tumors harbor an ALK gene rearrangement benefit from treatment with multiple ALK inhibitors (ALKi). Approximately 30% of tumor biopsy samples contain insufficient tissue for successful ALK molecular characterization. This study evaluated the added value of analyzing circulating tumor cells (CTCs) as a surrogate to ALK tissue analysis and as a function of the response to ALKi.Methods: We conducted a multicenter, prospective observational study (NCT02372448) of 203 patients with stage IIIB/IV NSCLC across nine French centers, of whom 81 were ALK positive (immunohistochemistry or fluorescence in situ hybridization [FISH]) and 122 ALK negative on paraffin-embedded tissue specimens. Blood samples were collected at baseline and at 6 and 12 weeks after ALKi initiation or at disease progression. ALK gene rearrangement was evaluated with CTCs using immunocytochemistry and FISH analysis after enrichment using a filtration method.Results: At baseline, there was a high concordance between the detection of an ALK rearrangement in the tumor tissue and in CTCs as determined by immunocytochemistry (sensitivity, 94.4%; specificity 89.4%). The performance was lower for the FISH analysis (sensitivity, 35.6%; specificity, 56.9%). No significant association between the baseline levels or the dynamic change of CTCs and overall survival (hazard ratio = 0.59, 95% confidence interval: 0.24-1.5, p = 0.244) or progression-free survival (hazard ratio = 0.84, 95% confidence interval: 0.44-1.6, p = 0.591) was observed in the patients with ALK-positive NSCLC.Conclusions: CTCs can be used as a complementary tool to a tissue biopsy for the detection of ALK rearrangements. Longitudinal analyses of CTCs revealed promise for real-time patient monitoring and improved delivery of molecularly guided therapy in this population

Efficacy and Safety of Rovalpituzumab Tesirine Compared With Topotecan as Second-Line Therapy in DLL3-High SCLC: Results From the Phase 3 TAHOE Study

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