Abstract 3655
Background
Lung cancer is the most common cause of cancer-related mortality worldwide. Early diagnosis and surgery may be one of the most important strategy for the treatment of lung cancer patients. However, the procedure of lung cancer diagnosis from initial suspicion to final confirmation is not efficient due to low sensitivity of current diagnostic methods and difficulties involved in tumor tissue biopsy in lung cancer compared to other cancer types. Therefore, we investigated the feasibility of liquid biopsy using circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) analysis for the better diagnosis of lung cancer.
Methods
In this study, we blindly analyzed both CTCs and ctDNA in the blood samples derived from 109 patients including histology-proven and clinically suspicious lung cancer patients to test the sensitivity of liquid biopsy methods. CTC analysis was done by CytoGen’s liquid biopsy platform, in which viable CTCs were isolated by size-based filtration with gravity and validated by immunostaining of EpCAM or CK, excluding CD45 positive cells and enumerated by CytoGen’s cell imaging software. Lung cancer diagnosis was predicted by a cut-off, 2 ≥ CTC in 5 ml peripheral blood. For ctDNA analysis, EDGC F-Can platform was used to analyze single nucleotide variations of very low variant allele frequencies by utilizing unique molecular indexes and a novel read error correction algorithm. For comparison, we also analyzed the levels of conventional tumor markers (CEA, cyfra21-1 and NSE) in the patient cohort.
Results
Compared to the diagnostic sensitivities of conventional tumor markers (CEA 29%; cyfra21-1 41%; NSE 39%), both assays of CTCs and ctDNA showed higher diagnostic sensitivity in predicting primary lung cancer (CTCs 67%; ctDNA 83%). When the assays of CTCs and ctDNA were combined for the diagnosis, the sensitivity was increased up to 98%.
Conclusions
Collectively, this study suggests that combined CTCs and ctDNA assay would be useful for the diagnosis of primary lung cancer.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Cytogen, Inc., EDGC, Inc., Department of Medicine, Samsung Medical Center
Funding
Has not received any funding
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
2436 - Development and Validation of an RNA-Seq Assay for Gene Fusions Detection in Formalin-Fixed Paraffin-Embedded Samples
Presenter: Hua Dong
Session: Poster Display session 3
Resources:
Abstract
5271 - A Pilot Study to Implement an Artificial Intelligence (AI) System for Gastrointestinal Cancer Clinical Trial Matching
Presenter: Zhaohui Jin
Session: Poster Display session 3
Resources:
Abstract
4787 - A Blinded Comparison of Patient Treatments to Therapeutic Options Presented by an Artificial Intelligence-based Clinical Decision-support system
Presenter: Suthida Suwanvecho
Session: Poster Display session 3
Resources:
Abstract
5744 - OncOS: scalable and accurate next-generation sequencing analytics for precision oncology and personalized patient care
Presenter: Joe Thompson
Session: Poster Display session 3
Resources:
Abstract
3752 - The association between wearable device physical activity metrics and performance status in oncology: a systematic review
Presenter: Milan Kos
Session: Poster Display session 3
Resources:
Abstract
5820 - SomaticNET: neural network evaluation of somatic mutations in cancer
Presenter: Geoffroy Dubourg-Felonneau
Session: Poster Display session 3
Resources:
Abstract
4771 - Is there a role for Next-generation sequencing (NGS) profiling on metastatic non-colorectal gastrointestinal carcinomas (MNCGIC) in developing countries? A single center experience.
Presenter: Mauricio Ribeiro
Session: Poster Display session 3
Resources:
Abstract
1209 - Metastatic Cancer Whole-Exome Sequencing in daily practice
Presenter: Manon Réda
Session: Poster Display session 3
Resources:
Abstract
5702 - Genomic-Guided Individualized Precision Therapy in Refractory Metastatic Solid Tumor Patients with Extensively Poor Performance Status: A Chinese single institutional prospective observational real-world study
Presenter: Haitao Wang
Session: Poster Display session 3
Resources:
Abstract
4021 - Prospective pathological experience with research biopsies in the context of clinical trials at Vall d’Hebron Institute of Oncology
Presenter: Paolo Nuciforo
Session: Poster Display session 3
Resources:
Abstract