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Liquid biopsy for lung cancer early detection.

ABSTRACT: 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.

SUBMITTER: Santarpia M

PROVIDER: S-EPMC5945693 | biostudies-other | 2018 Apr

REPOSITORIES: biostudies-other

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Liquid biopsy for lung cancer early detection.

Santarpia Mariacarmela M Liguori Alessia A D'Aveni Alessandro A Karachaliou Niki N Gonzalez-Cao Maria M Daffinà Maria Grazia MG Lazzari Chiara C Altavilla Giuseppe G Rosell Rafael R

Journal of thoracic disease 20180401 Suppl 7

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-r ...[more]

PMID: 29780635

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Project description:Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic feature for detecting the presence of cancer and determining its origin. The purpose of this study was to evaluate the diagnostic performance of methylation-sensitive restriction enzyme digestion followed by sequencing (MRE-Seq) using cfDNA, and to investigate the cancer signal origin (CSO) of the cancer using a deep neural network (DNN) analyses for liquid biopsy of colorectal and lung cancer. We developed a selective MRE-Seq method with DNN learning-based prediction model using demethylated-sequence-depth patterns from 63,266 CpG sites using SacII enzyme digestion. A total of 191 patients with stage I-IV cancers (95 lung cancers and 96 colorectal cancers) and 126 noncancer participants were enrolled in this study. Our study showed an area under the receiver operating characteristic curve (AUC) of 0.978 with a sensitivity of 78.1% for colorectal cancer, and an AUC of 0.956 with a sensitivity of 66.3% for lung cancer, both at a specificity of 99.2%. For colorectal cancer, sensitivities for stages I-IV ranged from 76.2 to 83.3% while for lung cancer, sensitivities for stages I-IV ranged from 44.4 to 78.9%, both again at a specificity of 99.2%. The CSO model's true-positive rates were 94.4% and 89.9% for colorectal and lung cancers, respectively. The MRE-Seq was found to be a useful method for detecting global hypomethylation patterns in liquid biopsy samples and accurately diagnosing colorectal and lung cancers, as well as determining CSO of the cancer using DNN analysis.Trial registration: This trial was registered at ClinicalTrials.gov (registration number: NCT04253509) for lung cancer on 5 February 2020, https://clinicaltrials.gov/ct2/show/NCT04253509 . Colorectal cancer samples were retrospectively registered at CRIS (Clinical Research Information Service, registration number: KCT0008037) on 23 December 2022, https://cris.nih.go.kr , https://who.init/ictrp . Healthy control samples were retrospectively registered.

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Liquid biopsy for lung cancer early detection.

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Liquid biopsy for lung cancer early detection.

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