Sun-Wha Im1, Jeesoo Chae2, Se Song Jang2, Jaeyong Choi2, Jihui Yun2, Soojin Cha1,3, Nak-Jung Kwon4, Yoon Kyung Jeon5,6, Yoohwa Hwang7,8, Miso Kim6,9, Tae Min Kim6,9, Dong-Wan Kim6,9, Jong-Il Kim10,11,12, Young Tae Kim13,14,15. 1. Genomic Medicine Institute, Medical Research Center, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. 2. Department of Biomedical Science, Seoul National University Graduate School, Seoul, Republic of Korea. 3. Samsung Medical Center, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea. 4. Macrogen Inc., Seoul, Republic of Korea. 5. Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea. 6. Seoul National University Cancer Research Institute, Seoul, Republic of Korea. 7. Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. 8. Department of Thoracic and Cardiovascular Surgery, Seoul National University Bundang Hospital, Seongnamsi, Gyeonggido, Republic of Korea. 9. Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea. 10. Genomic Medicine Institute, Medical Research Center, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. jongil@snu.ac.kr. 11. Department of Biomedical Science, Seoul National University Graduate School, Seoul, Republic of Korea. jongil@snu.ac.kr. 12. Seoul National University Cancer Research Institute, Seoul, Republic of Korea. jongil@snu.ac.kr. 13. Genomic Medicine Institute, Medical Research Center, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. ytkim@snu.ac.kr. 14. Seoul National University Cancer Research Institute, Seoul, Republic of Korea. ytkim@snu.ac.kr. 15. Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. ytkim@snu.ac.kr.
Abstract
BACKGROUND: The increase in genetic alterations targeted by specific chemotherapy in lung cancer has led to the need for universal use of more comprehensive genetic testing, which has highlighted the development of a lung cancer diagnostic panel using next-generation sequencing. OBJECTIVE: We developed a hybridization capture-based massively parallel sequencing assay named Friendly, Integrated, Research-based, Smart and Trustworthy (FIRST)-lung cancer panel (LCP), and evaluated its performance. METHODS: FIRST-LCP comprises 64 lung cancer-related genes to test for various kinds of genetic alterations including single nucleotide variations (SNVs), insertions and deletions (indels), copy number variations (CNVs), and structural variations. To assess the performance of FIRST-LCP, we compiled test sets using HapMap samples or tumor cell lines with disclosed genetic information, and also tested our clinical lung cancer samples whose genetic alterations were known by conventional methods. RESULTS: FIRST-LCP accomplished high sensitivity (99.4%) and specificity (100%) of the detection of SNVs. High precision was also achieved, with intra- or inter-run concordance rate of 0.99, respectively. FIRST-LCP detected indels and CNVs close to the expected allele frequency and magnitude, respectively. Tests with samples from lung cancer patients also identified all SNVs, indels and fusions. CONCLUSION: Based on the current state of the art, continuous application of the panel design and analysis pipeline following up-to-date knowledge could ensure precision medicine for lung cancer patients.
BACKGROUND: The increase in genetic alterations targeted by specific chemotherapy in lung cancer has led to the need for universal use of more comprehensive genetic testing, which has highlighted the development of a lung cancer diagnostic panel using next-generation sequencing. OBJECTIVE: We developed a hybridization capture-based massively parallel sequencing assay named Friendly, Integrated, Research-based, Smart and Trustworthy (FIRST)-lung cancer panel (LCP), and evaluated its performance. METHODS: FIRST-LCP comprises 64 lung cancer-related genes to test for various kinds of genetic alterations including single nucleotide variations (SNVs), insertions and deletions (indels), copy number variations (CNVs), and structural variations. To assess the performance of FIRST-LCP, we compiled test sets using HapMap samples or tumor cell lines with disclosed genetic information, and also tested our clinical lung cancer samples whose genetic alterations were known by conventional methods. RESULTS: FIRST-LCP accomplished high sensitivity (99.4%) and specificity (100%) of the detection of SNVs. High precision was also achieved, with intra- or inter-run concordance rate of 0.99, respectively. FIRST-LCP detected indels and CNVs close to the expected allele frequency and magnitude, respectively. Tests with samples from lung cancerpatients also identified all SNVs, indels and fusions. CONCLUSION: Based on the current state of the art, continuous application of the panel design and analysis pipeline following up-to-date knowledge could ensure precision medicine for lung cancerpatients.
Entities:
Keywords:
Cancer panel; Lung; Neoplasms; Next-generation sequencing