Cargando…
Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics
Currently, approximately 30%–55% of the patients with non–small cell lung cancer (NSCLC) develop recurrence due to minimal residual disease (MRD) after receiving surgical resection of the tumor. This study aims to develop an ultrasensitive and affordable fragmentomic assay for MRD detection in patie...
Autores principales: | , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for Cancer Research
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10228550/ https://www.ncbi.nlm.nih.gov/pubmed/37377889 http://dx.doi.org/10.1158/2767-9764.CRC-22-0363 |
_version_ | 1785050989227671552 |
---|---|
author | Wang, Siwei Xia, Zhijun You, Jing Gu, Xiaolan Meng, Fanchen Chen, Peng Tang, Wanxiangfu Bao, Hua Zhang, Jingyuan Wu, Xue Shao, Yang Wang, Jie Zuo, Xianglin Xu, Lin Yin, Rong |
author_facet | Wang, Siwei Xia, Zhijun You, Jing Gu, Xiaolan Meng, Fanchen Chen, Peng Tang, Wanxiangfu Bao, Hua Zhang, Jingyuan Wu, Xue Shao, Yang Wang, Jie Zuo, Xianglin Xu, Lin Yin, Rong |
author_sort | Wang, Siwei |
collection | PubMed |
description | Currently, approximately 30%–55% of the patients with non–small cell lung cancer (NSCLC) develop recurrence due to minimal residual disease (MRD) after receiving surgical resection of the tumor. This study aims to develop an ultrasensitive and affordable fragmentomic assay for MRD detection in patients with NSCLC. A total of 87 patients with NSCLC, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for both whole-genome sequencing (WGS) and targeted sequencing. WGS-based cell-free DNA (cfDNA) fragment profile was used to fit regularized Cox regression models, and leave-one-out cross-validation was further used to evaluate models’ performance. The models showed excellent performances in detecting patients with a high risk of recurrence. At 7 days postsurgical, the high-risk patients detected by our model showed an increased risk of 4.6 times, while the risk increased to 8.3 times at 6 months postsurgical. These fragmentomics determined higher risk compared with the targeted sequencing–based circulating mutations both at 7 days and 6 months postsurgical. The overall sensitivity for detecting patients with recurrence reached 78.3% while using both fragmentomics and mutation results from 7 days and 6 months postsurgical, which increased from the 43.5% sensitivity by using only the circulating mutations. The fragmentomics showed great sensitivity in predicting patient recurrence compared with the traditional circulating mutation, especially after the surgery for early-stage NSCLC, therefore exhibiting great potential to guide adjuvant therapeutics. SIGNIFICANCE: The circulating tumor DNA mutation-based approach shows limited performance in MRD detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, we describe a cfDNA fragmentomics–based method in MRD detection of resectable NSCLC using WGS, and the cfDNA fragmentomics showed a great sensitivity in predicting prognosis. |
format | Online Article Text |
id | pubmed-10228550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for Cancer Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-102285502023-05-31 Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics Wang, Siwei Xia, Zhijun You, Jing Gu, Xiaolan Meng, Fanchen Chen, Peng Tang, Wanxiangfu Bao, Hua Zhang, Jingyuan Wu, Xue Shao, Yang Wang, Jie Zuo, Xianglin Xu, Lin Yin, Rong Cancer Res Commun Research Article Currently, approximately 30%–55% of the patients with non–small cell lung cancer (NSCLC) develop recurrence due to minimal residual disease (MRD) after receiving surgical resection of the tumor. This study aims to develop an ultrasensitive and affordable fragmentomic assay for MRD detection in patients with NSCLC. A total of 87 patients with NSCLC, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for both whole-genome sequencing (WGS) and targeted sequencing. WGS-based cell-free DNA (cfDNA) fragment profile was used to fit regularized Cox regression models, and leave-one-out cross-validation was further used to evaluate models’ performance. The models showed excellent performances in detecting patients with a high risk of recurrence. At 7 days postsurgical, the high-risk patients detected by our model showed an increased risk of 4.6 times, while the risk increased to 8.3 times at 6 months postsurgical. These fragmentomics determined higher risk compared with the targeted sequencing–based circulating mutations both at 7 days and 6 months postsurgical. The overall sensitivity for detecting patients with recurrence reached 78.3% while using both fragmentomics and mutation results from 7 days and 6 months postsurgical, which increased from the 43.5% sensitivity by using only the circulating mutations. The fragmentomics showed great sensitivity in predicting patient recurrence compared with the traditional circulating mutation, especially after the surgery for early-stage NSCLC, therefore exhibiting great potential to guide adjuvant therapeutics. SIGNIFICANCE: The circulating tumor DNA mutation-based approach shows limited performance in MRD detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, we describe a cfDNA fragmentomics–based method in MRD detection of resectable NSCLC using WGS, and the cfDNA fragmentomics showed a great sensitivity in predicting prognosis. American Association for Cancer Research 2023-05-30 /pmc/articles/PMC10228550/ /pubmed/37377889 http://dx.doi.org/10.1158/2767-9764.CRC-22-0363 Text en © 2023 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by/4.0/This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. |
spellingShingle | Research Article Wang, Siwei Xia, Zhijun You, Jing Gu, Xiaolan Meng, Fanchen Chen, Peng Tang, Wanxiangfu Bao, Hua Zhang, Jingyuan Wu, Xue Shao, Yang Wang, Jie Zuo, Xianglin Xu, Lin Yin, Rong Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics |
title | Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics |
title_full | Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics |
title_fullStr | Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics |
title_full_unstemmed | Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics |
title_short | Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics |
title_sort | enhanced detection of landmark minimal residual disease in lung cancer using cell-free dna fragmentomics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10228550/ https://www.ncbi.nlm.nih.gov/pubmed/37377889 http://dx.doi.org/10.1158/2767-9764.CRC-22-0363 |
work_keys_str_mv | AT wangsiwei enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT xiazhijun enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT youjing enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT guxiaolan enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT mengfanchen enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT chenpeng enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT tangwanxiangfu enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT baohua enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT zhangjingyuan enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT wuxue enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT shaoyang enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT wangjie enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT zuoxianglin enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT xulin enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics AT yinrong enhanceddetectionoflandmarkminimalresidualdiseaseinlungcancerusingcellfreednafragmentomics |