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1.
Cancer Cell ; 42(2): 225-237.e5, 2024 02 12.
Artigo em Inglês | MEDLINE | ID: mdl-38278149

RESUMO

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy.


Assuntos
Ácidos Nucleicos Livres , Neoplasias Pulmonares , Carcinoma de Pequenas Células do Pulmão , Humanos , Carcinoma de Pequenas Células do Pulmão/genética , Carcinoma de Pequenas Células do Pulmão/patologia , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Metilação de DNA , Ácidos Nucleicos Livres/genética , Epigênese Genética , Biomarcadores Tumorais/genética
2.
Eur Respir J ; 57(1)2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33122336

RESUMO

AIM: Lung cancer screening reduces mortality. We aim to validate the performance of Lung EpiCheck, a six-marker panel methylation-based plasma test, in the detection of lung cancer in European and Chinese samples. METHODS: A case-control European training set (n=102 lung cancer cases, n=265 controls) was used to define the panel and algorithm. Two cut-offs were selected, low cut-off (LCO) for high sensitivity and high cut-off (HCO) for high specificity. The performance was validated in case-control European and Chinese validation sets (cases/controls 179/137 and 30/15, respectively). RESULTS: The European and Chinese validation sets achieved AUCs of 0.882 and 0.899, respectively. The sensitivities/specificities with LCO were 87.2%/64.2% and 76.7%/93.3%, and with HCO they were 74.3%/90.5% and 56.7%/100.0%, respectively. Stage I nonsmall cell lung cancer (NSCLC) sensitivity in European and Chinese samples with LCO was 78.4% and 70.0% and with HCO was 62.2% and 30.0%, respectively. Small cell lung cancer (SCLC) was represented only in the European set and sensitivities with LCO and HCO were 100.0% and 93.3%, respectively. In multivariable analyses of the European validation set, the assay's ability to predict lung cancer was independent of established risk factors (age, smoking, COPD), and overall AUC was 0.942. CONCLUSIONS: Lung EpiCheck demonstrated strong performance in lung cancer prediction in case-control European and Chinese samples, detecting high proportions of early-stage NSCLC and SCLC and significantly improving predictive accuracy when added to established risk factors. Prospective studies are required to confirm these findings. Utilising such a simple and inexpensive blood test has the potential to improve compliance and broaden access to screening for at-risk populations.


Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Biomarcadores Tumorais , China , Detecção Precoce de Câncer , Humanos , Pulmão , Neoplasias Pulmonares/diagnóstico , Metilação , Estudos Prospectivos
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