한빛사 논문
Han-Byoel Lee1,2,3, Sae Byul Lee4, Minsu Kim5, Sunyoung Kwon6,7, Jeonghee Jo8, Jinkyoung Kim9, Hee Jin Lee10, Han-Suk Ryu11, Jong Won Lee4, Chungyeul Kim9, Jaehwan Jeong12, Hyoki Kim12, Dong-Young Noh1,3, In-Ae Park11, Sei-Hyun Ahn4, Sun Kim5, Sungroh Yoon6,8, Aeree Kim9, Wonshik Han1,2,3
1Department of Surgery, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
2Biomedical Research Institute, Seoul National University Hospital, Seoul 03080, Republic of Korea
3Cancer Research Institute, Seoul National University, Seoul 03080, Republic of Korea
4Department of Surgery, Asan Medical Center, Seoul 05505, Republic of Korea
5Bioinformatics Institute, Seoul National University, Seoul 08826, Republic of Korea
6Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea
7School of Biomedical Convergence Engineering, College of Information and Biomedical Engineering, Pusan National University, Yangsan 50612, Republic of Korea
8Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Republic of Korea
9Department of Pathology, Korea University Guro Hospital, Seoul 08308; Republic of Korea
10Department of Pathology, Asan Medical Center, Seoul 05505; Republic of Korea
11Department of Pathology, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
12 Celemics Inc., Seoul 08506, Republic of Korea
Corresponding Author: Wonshik Han, MD, Ph.D
Department of Surgery, Seoul National University Hospital, Cancer Research Institute, Seoul National University, Biomedical Research Institute, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
Abstract
Purpose: Multigene assays provide useful prognostic information regarding hormone receptor (HR)-positive breast cancer. Next-generation sequencing (NGS)-based platforms have numerous advantages including reproducibility and adaptability in local laboratories. This study aimed to develop and validate an NGS-based multigene assay to predict the distant recurrence risk.
Experimental Design: In total, 179 genes including 30 reference genes highly correlated with the 21-gene recurrence score (RS) algorithm were selected from public databases. Targeted RNA-seq was performed using 250 and 93 archived breast cancer samples with a known RS in the training and verification sets, respectively, to develop the algorithm and NGS-Prognostic Score (NGS-PS). The assay was validated in 413 independent samples with long-term follow-up data on distant metastasis.
Results: In the verification set, the NGS-PS and 21-gene RS displayed 91.4% concurrence (85/93 samples). In the validation cohort of 413 samples, area under the receiver operating characteristic curve plotted using NGS-PS values classified for distant recurrence was 0.76. The best NGS-PS cutoff value predicting distant metastasis was 20. Furthermore, 269 and 144 patients were classified as low- and high-risk patients in accordance with the cut-off. Five- and 10-year estimates of distant metastasis-free survival (DMFS) for low- vs. high-risk groups were 97.0% vs. 77.8% and 93.2% vs. 64.4%, respectively. The age-related hazard ratio for distant recurrence without chemotherapy was 9.73 (95% CI 3.59-26.40) and 3.19 (95% CI 1.40-7.29) for patients aged ≤50 and >50 years, respectively.
Conclusions: The newly developed and validated NGS-based multigene assay can predict the distant recurrence risk in ER-positive, HER2-negative breast cancer.
논문정보
TOP52020년 후보
관련 링크
연구자 키워드
관련분야 연구자보기
소속기관 논문보기
관련분야 논문보기
해당논문 저자보기