Hee-Jin Jang1,2,3, Hyun-Sung Lee1,2,4,5, Bryan M Burt4, Geon Kook Lee5, Kyong-Ah Yoon5,6, Yun-Yong Park2, Bo Hwa Sohn2, Sang Bae Kim2, Moon Soo Kim1, Jong Mog Lee1, Jungnam Joo7, Sang Cheol Kim8, Ju Sik Yun9, Kook Joo Na9, Yoon-La Choi10, Jong-Lyul Park11, Seon-Young Kim11, Yong Sun Lee12, Leng Han13,14, Han Liang13, Duncan Mak15, Jared K Burks15, Jae Ill Zo16, David J Sugarbaker4, Young Mog Shim16, Ju-Seog Lee2. 1. Center for Lung Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Gyeonggi, Republic of Korea. 2. Division of Cancer Medicine, Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 3. Department of Molecular Oncology, The Graduate School of Medicine, Seoul National University, Seoul, Republic of Korea. 4. Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, USA. 5. Lung Cancer Branch, Research Institute and Hospital, National Cancer Center, Goyang, Gyeonggi, Republic of Korea. 6. College of Veterinary Medicine, Konkuk University, Seoul, Republic of Korea. 7. Biometric Research Branch, Research Institute and Hospital, National Cancer Center, Goyang, Gyeonggi, Republic of Korea. 8. Department of Biomedical Informatics, Center for Genome Science, National Institute of Health, KCDC, Choongchung-Buk-do, Republic of Korea. 9. Lung and Esophageal Cancer Clinic, Department of Thoracic and Cardiovascular Surgery, Chonnam National University Hwasun Hospital, Hwasun, Jeollanamdo, Republic of Korea. 10. Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 11. Department of Functional Genomics, University of Science and Technology, Medical Genomics Research Center, KRIBB, Daejeon, Republic of Korea. 12. Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch, Galveston, Texas, USA. 13. Division of Quantitative Sciences, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 14. Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston McGovern Medical School, Houston, Texas, USA. 15. Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 16. Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Abstract
OBJECTIVE: Oesophageal squamous cell carcinoma (ESCC) is a heterogeneous disease with variable outcomes that are challenging to predict. A better understanding of the biology of ESCC recurrence is needed to improve patient care. Our goal was to identify small non-coding RNAs (sncRNAs) that could predict the likelihood of recurrence after surgical resection and to uncover potential molecular mechanisms that dictate clinical heterogeneity. DESIGN: We developed a robust prediction model for recurrence based on the analysis of the expression profile data of sncRNAs from 108 fresh frozen ESCC specimens as a discovery set and assessment of the associations between sncRNAs and recurrence-free survival (RFS). We also evaluated the mechanistic and therapeutic implications of sncRNA obtained through integrated analysis from multiple datasets. RESULTS: We developed a risk assessment score (RAS) for recurrence with three sncRNAs (microRNA (miR)-223, miR-1269a and nc886) whose expression was significantly associated with RFS in the discovery cohort (n=108). RAS was validated in an independent cohort of 512 patients. In multivariable analysis, RAS was an independent predictor of recurrence (HR, 2.27; 95% CI, 1.26 to 4.09; p=0.007). This signature implies the expression of ΔNp63 and multiple alterations of driver genes like PIK3CA. We suggested therapeutic potentials of immune checkpoint inhibitors in low-risk patients, and Polo-like kinase inhibitors, mammalian target of rapamycin (mTOR) inhibitors, and histone deacetylase inhibitors in high-risk patients. CONCLUSION: We developed an easy-to-use prognostic model with three sncRNAs as robust prognostic markers for postoperative recurrence of ESCC. We anticipate that such a stratified and systematic, tumour-specific biological approach will potentially contribute to significant improvement in ESCC treatment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
OBJECTIVE:Oesophageal squamous cell carcinoma (ESCC) is a heterogeneous disease with variable outcomes that are challenging to predict. A better understanding of the biology of ESCC recurrence is needed to improve patient care. Our goal was to identify small non-coding RNAs (sncRNAs) that could predict the likelihood of recurrence after surgical resection and to uncover potential molecular mechanisms that dictate clinical heterogeneity. DESIGN: We developed a robust prediction model for recurrence based on the analysis of the expression profile data of sncRNAs from 108 fresh frozen ESCC specimens as a discovery set and assessment of the associations between sncRNAs and recurrence-free survival (RFS). We also evaluated the mechanistic and therapeutic implications of sncRNA obtained through integrated analysis from multiple datasets. RESULTS: We developed a risk assessment score (RAS) for recurrence with three sncRNAs (microRNA (miR)-223, miR-1269a and nc886) whose expression was significantly associated with RFS in the discovery cohort (n=108). RAS was validated in an independent cohort of 512 patients. In multivariable analysis, RAS was an independent predictor of recurrence (HR, 2.27; 95% CI, 1.26 to 4.09; p=0.007). This signature implies the expression of ΔNp63 and multiple alterations of driver genes like PIK3CA. We suggested therapeutic potentials of immune checkpoint inhibitors in low-risk patients, and Polo-like kinase inhibitors, mammalian target of rapamycin (mTOR) inhibitors, and histone deacetylase inhibitors in high-risk patients. CONCLUSION: We developed an easy-to-use prognostic model with three sncRNAs as robust prognostic markers for postoperative recurrence of ESCC. We anticipate that such a stratified and systematic, tumour-specific biological approach will potentially contribute to significant improvement in ESCC treatment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
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