Using circulating tumor DNA analysis to depict genomic profiles and predict survival outcomes in patients with small-cell lung cancer.
Sub-category:
Small Cell Lung Cancer
Category:
Lung Cancer — Non-Small Cell Local-Regional/Small
Cell/Other Thoracic Cancers
Meeting:
2017 ASCO Annual Meeting
Abstract No:
8567
Poster Board Number:
Poster Session (Board #303)
Citation:
J Clin Oncol 35, 2017 (suppl; abstr 8567)
Author(s): Jinghui Wang, Jingying Nong, Yuhua Gong, Shuai Sun, Yuting Yi, Yan-Fang Guan, LingYang, Hongyan Jia, Shucai Zhang, Xuefeng Xia, Xin Yi, Zhongxing X. Liao; Department of Medical Oncology, Beijing Chest Hospital, Capital Medicine University, Beijing Tuberculosis and Thoracic
Tumor Research Institute, Beijing, China; Geneplus-Beijing, Beijing, China; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
Abstract Disclosures
Abstract
Background
Small-cell lung cancer (SCLC) accounts for approximately 15% of lung cancers. Most patients have extensive-stage disease with widespread metastases and poor survival. Understanding the molecular mutation profile of each SCLC patient would allow precision treatment and improved clinical outcome. However, tumor tissues from surgery are not available for most SCLC patients and biopsy specimens are often have limited quantities. Several studies have provided evidence
of circulating tumor DNA (ctDNA) in detecting somatic variants of multiple solid tumors. This study evaluated utility of ctDNA to depict genomic profiles and predict survival outcomes in SCLC patients.
Methods
22 Plasma samples were obtained before initial treatment from 22 patients with SCLC enrolled between 2012 and 2016. Targeted-capture deep sequencing was performed to identify somatic variants in 465 cancer-related genes. Genomic mutation profiles were described and the clinical implications were further analyzed.
Results
Tumor DNA can be detected in all 22 plasma samples collected from patients with SCLC. In total,340 variants were identified, and the mean and median mutation rate were 6.3 and 6.6 per Mb.TP53 and RB1 are the most frequently mutated genes, detected in 90.9% (20/22) and 59.1(13/22)patients,respectively. Further analysis showed that high ctDNA fraction in cell-free DNA(cfDNA) was associated with heavy tumor burden (R = 0.7, p = 0.0017). Moreover, patients with
high ctDNA fractions (ctDNA fraction > = 18.3%) had poor progression free survival (PFS) (HR,17.2; p = 0.0019). The median PFS of patients with high versus low ctDNA fractions was 5.2months (95% CI 4.6 to 5.8 months) versus 10.0 months (95% CI 9.3 to 10.7 months), respectively.
Conclusions
In this study, ctDNA analysis offers a promising way to depict the molecular profile in patients with SCLC. Moreover, these findings highlight the potential clinical utility of ctDNA to predicate clinical outcome in SCLC.