Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer
Summary: Background: As a rare subtype of lung adenocarcinoma, the diagnosis of pulmonary enteric adenocarcinoma (PEAC) remains challenging due to overlapping morphologic spectrum with lung metastatic colorectal cancer (lmCRC). However, the molecular features of PEAC as a separate lung cancer entit...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-08-01
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| Series: | EBioMedicine |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352396422003462 |
| _version_ | 1818012642666610688 |
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| author | Ying Zuo Jia Zhong Hua Bai Bin Xu Zhijie Wang Weihua Li Yedan Chen Shi Jin Shuhang Wang Xin Wang Rui Wan Jiachen Xu Kailun Fei Jiefei Han Zhenlin Yang Hua Bao Yang Shao Jianming Ying Qibin Song Jianchun Duan Jie Wang |
| author_facet | Ying Zuo Jia Zhong Hua Bai Bin Xu Zhijie Wang Weihua Li Yedan Chen Shi Jin Shuhang Wang Xin Wang Rui Wan Jiachen Xu Kailun Fei Jiefei Han Zhenlin Yang Hua Bao Yang Shao Jianming Ying Qibin Song Jianchun Duan Jie Wang |
| author_sort | Ying Zuo |
| collection | DOAJ |
| description | Summary: Background: As a rare subtype of lung adenocarcinoma, the diagnosis of pulmonary enteric adenocarcinoma (PEAC) remains challenging due to overlapping morphologic spectrum with lung metastatic colorectal cancer (lmCRC). However, the molecular features of PEAC as a separate lung cancer entity are poorly understood. Methods: We performed whole-exome sequencing and targeted bisulfite sequencing of 32 PEAC and 30 lmCRC to improve differential molecular characterization of the two diseases. We used machine learning methods to select key markers and developed a diagnostic classifier. In addition, we validated the classifier in the internal test cohort and an independently recruited external validation cohort with 17 PEAC and 7 lmCRC. Findings: Our results showed that EGFR was the key driver mutation in PEAC but at a lower prevalence compared to typical lung adenocarcinomas, whereas ERBB2 and KRAS were more frequently observed in PEAC. By contrast, we observed significant enrichment of KRAS and APC mutations in lmCRC compared with PEAC. At the chromosome arm level, copy number variations in 13q, 14q, and 18p were the major chromosomal differences observed between PEAC and lmCRC. Furthermore, by comparing differentially methylated regions (DMRs), we established a neat DNA methylation-based classifier consisting of eight DMRs. This classifier correctly classified all samples in the training cohort and 95% of the samples in the internal test cohort. An external validation cohort of 24 cases recruited from multiple centers in China also reliably agreed with pathological diagnosis. Interpretation: These results provide solid evidence of PEAC-specific genomic characteristics and demonstrate the potential utility of DNA methylation markers for auxiliary diagnosis of PEAC and lmCRC. Funding: This work was supported by National key research and development project 2019YFC1315700, CAMS Key Laboratory of Translational Research on Lung Cancer (2018PT31035), and Beijing Natural Science Foundation (7222144). |
| first_indexed | 2024-04-14T06:22:48Z |
| format | Article |
| id | doaj.art-d46ee43923634659b307aef88b9060f3 |
| institution | Directory Open Access Journal |
| issn | 2352-3964 |
| language | English |
| last_indexed | 2024-04-14T06:22:48Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EBioMedicine |
| spelling | doaj.art-d46ee43923634659b307aef88b9060f32022-12-22T02:07:57ZengElsevierEBioMedicine2352-39642022-08-0182104165Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancerYing Zuo0Jia Zhong1Hua Bai2Bin Xu3Zhijie Wang4Weihua Li5Yedan Chen6Shi Jin7Shuhang Wang8Xin Wang9Rui Wan10Jiachen Xu11Kailun Fei12Jiefei Han13Zhenlin Yang14Hua Bao15Yang Shao16Jianming Ying17Qibin Song18Jianchun Duan19Jie Wang20State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaCancer center, Renmin Hospital of Wuhan University, Wuhan, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaDepartment of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaNanjing Geneseeq Technology Inc., Nanjing, ChinaNational Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, ChinaGCP Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaState Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaDepartment of Neuro-oncology, Cancer Center Beijing Tiantan Hospital, Capital Medical University, ChinaThoracic Surgery Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaNanjing Geneseeq Technology Inc., Nanjing, ChinaNanjing Geneseeq Technology Inc., Nanjing, China; School of Public Health, Nanjing Medical University, Nanjing, ChinaDepartment of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, ChinaCancer center, Renmin Hospital of Wuhan University, Wuhan, China; Corresponding author at: Qibin Song, Cancer center, Renmin Hospital of Wuhan University, 99#, Zhangzhidong Road, Wuchang district, Wuhan, Hubei Province, 430060, China.State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China; Corresponding authors at: Jie Wang & Jianchun Duan, State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Lane, Chaoyang District, Beijing, 100021, China.State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China; Corresponding authors at: Jie Wang & Jianchun Duan, State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Pan-jia-yuan South Lane, Chaoyang District, Beijing, 100021, China.Summary: Background: As a rare subtype of lung adenocarcinoma, the diagnosis of pulmonary enteric adenocarcinoma (PEAC) remains challenging due to overlapping morphologic spectrum with lung metastatic colorectal cancer (lmCRC). However, the molecular features of PEAC as a separate lung cancer entity are poorly understood. Methods: We performed whole-exome sequencing and targeted bisulfite sequencing of 32 PEAC and 30 lmCRC to improve differential molecular characterization of the two diseases. We used machine learning methods to select key markers and developed a diagnostic classifier. In addition, we validated the classifier in the internal test cohort and an independently recruited external validation cohort with 17 PEAC and 7 lmCRC. Findings: Our results showed that EGFR was the key driver mutation in PEAC but at a lower prevalence compared to typical lung adenocarcinomas, whereas ERBB2 and KRAS were more frequently observed in PEAC. By contrast, we observed significant enrichment of KRAS and APC mutations in lmCRC compared with PEAC. At the chromosome arm level, copy number variations in 13q, 14q, and 18p were the major chromosomal differences observed between PEAC and lmCRC. Furthermore, by comparing differentially methylated regions (DMRs), we established a neat DNA methylation-based classifier consisting of eight DMRs. This classifier correctly classified all samples in the training cohort and 95% of the samples in the internal test cohort. An external validation cohort of 24 cases recruited from multiple centers in China also reliably agreed with pathological diagnosis. Interpretation: These results provide solid evidence of PEAC-specific genomic characteristics and demonstrate the potential utility of DNA methylation markers for auxiliary diagnosis of PEAC and lmCRC. Funding: This work was supported by National key research and development project 2019YFC1315700, CAMS Key Laboratory of Translational Research on Lung Cancer (2018PT31035), and Beijing Natural Science Foundation (7222144).http://www.sciencedirect.com/science/article/pii/S2352396422003462Pulmonary enteric adenocarcinomaLung metastatic colorectal cancerMachine learning model |
| spellingShingle | Ying Zuo Jia Zhong Hua Bai Bin Xu Zhijie Wang Weihua Li Yedan Chen Shi Jin Shuhang Wang Xin Wang Rui Wan Jiachen Xu Kailun Fei Jiefei Han Zhenlin Yang Hua Bao Yang Shao Jianming Ying Qibin Song Jianchun Duan Jie Wang Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer EBioMedicine Pulmonary enteric adenocarcinoma Lung metastatic colorectal cancer Machine learning model |
| title | Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer |
| title_full | Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer |
| title_fullStr | Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer |
| title_full_unstemmed | Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer |
| title_short | Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer |
| title_sort | genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer |
| topic | Pulmonary enteric adenocarcinoma Lung metastatic colorectal cancer Machine learning model |
| url | http://www.sciencedirect.com/science/article/pii/S2352396422003462 |
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