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Abstract 1377: Improved ctDNA detection in early stage non-small-cell lung cancer

Authors :
Katrin Heider
Jonathan C. Wan
Davina Gale
Florent C. Mouliere
Wendi Qian
Angels Kateb
Gail Doughton
Nicola Ramenatte
Ruth Tysoe
Christopher G. Smith
Doris M. Rassl
Susan Harden
Robert C. Rintoul
Charles Massie
Nitzan Rosenfeld
Source :
Cancer Research. 79:1377-1377
Publication Year :
2019
Publisher :
American Association for Cancer Research (AACR), 2019.

Abstract

Overall survival of non-small-cell lung cancer (NSCLC) patients remains poor as patients are frequently diagnosed at a late stage. The evaluation of circulating tumour DNA (ctDNA) has been shown to offer a non-invasive method for detection of cancer. However, detection rates of ctDNA in patients with early stage cancers, including NSCLC, have been limited due to sampling and sensitivity issues. We developed a novel algorithm for INtegration of VAriant Reads (INVAR), which uses sequencing data across hundreds to thousands of tumour-mutated loci to detect ctDNA in plasma samples at high sensitivity. We applied this to a cohort of stage I-III NSCLC patients recruited in the LUCID study. LUCID is a prospective and observational study of 100 stage I-IIIB NSCLC who are planning to undergo radical treatment (surgery or radiotherapy +/- chemotherapy) with curative intent. Plasma samples were collected before and after treatment with curative intent. We analysed a total of 50 patients using patient specific-sequencing panels and detected ctDNA in 78% of cases before treatment, at ctDNA fractions as low as 1.7x10-5. For 17 of those patients staging information was available. Here, we detected ctDNA in 50% of stage I patients (split evenly between stages IA and B) and 100% of stage II and III patients. We also applied INVAR to whole exome and shallow whole genome sequencing data from plasma samples, and showed that this algorithm can be used to detect low ctDNA fractions in such data. Our findings highlight an opportunity to improve ctDNA detection in early stage NSCLC by using patient specific sequencing information. Additionally, our algorithm has the potential to aid in longitudinal cancer monitoring and is applicable to a variety of sequencing data types. We aim to apply this approach to serial samples obtained through the LUCID study to investigate its application in the treatment management. Citation Format: Katrin Heider, Jonathan C. Wan, Davina Gale, Florent C. Mouliere, Wendi Qian, Angels Kateb, Gail Doughton, Nicola Ramenatte, Ruth Tysoe, Christopher G. Smith, Doris M. Rassl, Susan Harden, Robert C. Rintoul, Charles Massie, Nitzan Rosenfeld. Improved ctDNA detection in early stage non-small-cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1377.

Subjects

Subjects :
Cancer Research
Oncology

Details

ISSN :
15387445 and 00085472
Volume :
79
Database :
OpenAIRE
Journal :
Cancer Research
Accession number :
edsair.doi...........65a57ecb9dcee921f88c489f1447be0d
Full Text :
https://doi.org/10.1158/1538-7445.am2019-1377