K. Sun
Peking Union Medical College
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Featured researches published by K. Sun.
The Annals of Thoracic Surgery | 2014
W. Zhang; Hongxia Zhu; Xiao Liu; Q. Wang; Xun Zhang; Jie He; K. Sun; Xiangyang Liu; Zongmei Zhou; Ningzhi Xu; Zefen Xiao
BACKGROUNDnOur previous study indicated the survival rate for esophageal squamous cell cancer (ESCC) patients in stage III and positive lymph node groups with postoperative radiation therapy was significantly increased compared with surgery alone. But a predictive biomarker was needed to identify the patients who would benefit from postoperative radiotherapy. This study aims to evaluate epidermal growth factor receptor (EGFR) as an indicator to predict the prognosis of ESCC and to identify the patients who would benefit from postoperative radiotherapy.nnnMETHODSnTissue samples were collected from our previous randomized study: 243 in the surgery alone group and 198 in the surgery plus radiotherapy group. Expression of EGFR was analyzed by immunohistochemical staining.nnnRESULTSnThe expression of EGFR is correlated with depth of tumor invasion (p=0.005), lymph node metastasis (p<0.001), and pathologic stage (p<0.001). The survival rate of patients with high EGFR expression is significantly lower than that of patients with low EGFR expression (p=0.000). Notably, in stage IIA cases, the 5-year survival rate is 57.6% in the low EGFR expression group and 36.6% in the high expression group (p=0.020). EGFR is one of the independent variants that influence the prognosis. Moreover, for high EGFR expression patients the survival rate of the surgery plus radiotherapy group is higher than that of the surgery alone group (p=0.034).nnnCONCLUSIONSnExpression of EGFR can be a prognostic predictor for ESCC. Patients with high expression of EGFR may benefit from postoperative radiation therapy.
World Journal of Surgical Oncology | 2013
Q. Wang; Hongxia Zhu; Zefen Xiao; W. Zhang; Xiao Liu; Xun Zhang; Jie He; K. Sun; L. Wang; Ningzhi Xu
BackgroundThe overall survival of patients with esophageal squamous cell carcinoma (ESCC) remains poor. Prognostic predictions in ESCC are usually based on histological assessment of tumor invasion and lymph node metastasis, but a biomarker with better predictive accuracy could be more useful. Because overexpression of epidermal growth factor receptor (EGFR) has been associated with poor prognosis, this study investigated whether EGFR is an independent prognostic factor for overall survival and disease-free survival of ESCC patients.MethodsESCC tissue specimens from 243 patients obtained during surgical resection between 1980 and 1997 were retrieved for immunohistochemical analysis of EGFR expression.ResultsThe data showed that EGFR protein was overexpressed in 187 of 243 (77%) ESCC tissues. Elevated expression was associated with higher pathologic tumor stages (P = 0.001), lymph node metastasis (P = 0.002), and higher Union for International Cancer Control (UICC) stage (P <0.0001), as well as poorer disease-free survival and overall survival of ESCC patients (P <0.0001). A multivariate analysis showed that overexpression of EGFR protein was an independent factor for disease-free survival (P = 0.003) and overall survival (P = 0.001) of these patients. Subgroup analysis of patients with stage IIA (UICC 2002) showed that EGFR overexpression was associated with poorer disease-free survival (P = 0.007) and overall survival (P = 0.010) of the patients in univariate analyses.ConclusionsThe current study demonstrated that EGFR overexpression was an independent prognostic factor for overall survival and disease-free survival of ESCC patients. However, targeting of EGFR activity using gefitinib or erlotinib could be useful for clinical treatment of ESCC patients.
Oncotarget | 2017
Wei Deng; Q. Wang; Zefen Xiao; Lijun Tan; Zhao Yang; Zongmei Zhou; Hongxing Zhang; Dongfu Chen; Qinfu Feng; J. Liang; Li Y; Jie He; Shugeng Gao; K. Sun; Guiyu Cheng; Liu Xy; D. Fang; Qi Xue; Yousheng Mao; Dali Wang; and Jian Li
Background Currently, the AJCC staging system or pathological complete response (pCR) are considered not sufficiently accurate to evaluate the survival of patients with esophageal squamous cell carcinoma after neoadjuvant radiotherapy or chemoradiotherapy. This study aimed to establish a nomogram and a recursive partitioning analysis (RPA) model to estimate prognosis and to provide advice for subsequent treatments. Methods We analyzed retrospectively 407 patients that were diagnosed with thoracic esophageal squamous cell carcinoma (TESCC) and received neoadjuvant radiotherapy or chemoradiotherapy. Hazard ratios and 95% confidence intervals of categorical clinicopathological characteristics with overall survival (OS) were calculated using the Cox proportional hazard model. The nomogram and RPA model were then established and total scores according to each variable were calculated and stratified to predict OS. Results Patients were followed-up over a median 49.9 months. AJCC did not perform well in distinguishing OS among each stage except for IIB and IIIA. Patients were divided into 4 groups according to the total scores based on nomogram (low risk: ≤180; intermediate risk: 180-270; high risk: 270-340; very high risk: >340). The 5-year OS was 57.3%, 40.7%, 18.3%, 6.1% respectively (p<0.05). RPA model also divide the patients into 4 groups, though group2 and group3 were not statistically significant (p=0.574). Conclusion The nomogram is a good evaluation model for estimating the prognosis of patients with TESCC after neoadjuvant radiotherapy or chemoradiotherapy compared with the AJCC and RPA. The results of this study also suggested that the high-risk subgroups need further treatments.
Journal of Thoracic Oncology | 2017
Jinsong Yang; W. Zhang; Zefen Xiao; Q. Wang; Zongmei Zhou; Hongxing Zhang; Dongfu Chen; Qingfu Feng; Jie He; Shugeng Gao; K. Sun; Xiangyang Liu; D. Fang; Ju-Wei Mu; Dali Wang; Yexiong Li
Introduction: The role of conformal radiotherapy (cRT) in thoracic esophageal squamous cell carcinoma (TESCC) has not been addressed in adjuvant settings. The aim of this study was to investigate whether postoperative radiotherapy using cRT after an R0 resection improves outcomes in pT3N0M0 TESCC compared with resection alone. Methods: This study included 678 patients with pT3N0M0 TESCC who were treated at the Cancer Hospital, Chinese Academy of Medical Sciences, from January 2004 to December 2011. The patients were divided into two groups: a surgery plus cRT group (S+cRT group) comprising patients who underwent cRT after an R0 resection and a surgery group (S group), comprising a control group of patients who underwent an R0 resection alone. Propensity score matching was used to create patient groups that were balanced across several covariates (n = 83 in each group). Outcome measures included overall survival (OS), disease‐free survival (DFS), and recurrence. Results: In the overall study cohort, 5‐year OS (75.2% versus 58.5%, p = 0.004) and DFS (71.8% versus 49.2%, p = 0.001) rates were significantly higher in the S+cRT group than in the S group. These data were confirmed in the matched samples (5‐year OS, 75.7% versus 58.8% [p = 0.017]; DFS, 71.7% versus 50.3% [p = 0.009]). The overall (p = 0.001) and locoregional (p = 0.004) recurrence rates in the S+cRT group were significantly lower than in the S group. Multivariate Cox analyses in the matched samples revealed that surgery and postoperative cRT were independently associated with longer OS (hazard ratio = 0.505, 95% confidence interval: 0.291–0.876, p = 0.015) and longer DFS (hazard ratio = 0.513, 95% confidence interval: 0.309–0.854, p = 0.010) than resection alone. Conclusions: Postoperative radiotherapy using cRT is strongly associated with improved OS and DFS in patients with pT3N0M0 TESCC. A multicenter, randomized phase III clinical trial is warranted to confirm these findings.
International Journal of Radiation Oncology Biology Physics | 2005
Zefen Xiao; Zong-Yi Yang; Yan-Jun Miao; Weibo Yin; Xian-Zhi Gu; De-Chao Zhang; K. Sun; Gui-Yu Chen; Jie He
International Journal of Radiation Oncology Biology Physics | 2018
W. Deng; J.Q. Chen; Zhijian Xiao; W. Ni; C. Li; X. Chang; Jianliang Yang; S.F. Yu; W. Zhang; Z. Zhou; D. Chen; F. Qinfu; Xiaoguang Chen; Y. Lin; K. Zhu; Jiuming He; Shugeng Gao; Q. Xue; Y. Mao; G. Cheng; K. Sun; Xinmin Liu; D. Fang
International Journal of Radiation Oncology Biology Physics | 2018
W. Ni; J.Q. Chen; Zhijian Xiao; S.F. Yu; W. Zhang; Z. Zhou; D. Chen; F. Qinfu; Xiaoguang Chen; Y. Lin; K. Zhu; Jiuming He; Shugeng Gao; Q. Xue; Y. Mao; G. Cheng; K. Sun; Xinmin Liu; D. Fang
International Journal of Radiation Oncology Biology Physics | 2018
W. Ni; J.Q. Chen; Zhijian Xiao; S.F. Yu; W. Zhang; Z. Zhou; D. Chen; F. Qinfu; Xiaoguang Chen; Y. Lin; K. Zhu; Jiuming He; Shugeng Gao; Q. Xue; Y. Mao; G. Cheng; K. Sun; Xinmin Liu; D. Fang
International Journal of Radiation Oncology Biology Physics | 2017
W. Deng; Jianliang Yang; Zhijian Xiao; X. Wang; Z. Zhou; H. Zhang; D. Chen; Q. Feng; J. Liang; J. Lv; T. Zhang; N. Bi; Wei-Hu Wang; L. Deng; Z. Hui; L. Wang; Jiuming He; Shugeng Gao; Q. Xue; Y. Mao; K. Sun; Xinmin Liu; D. Fang; J. Li; Dali Wang; J. Mou; J. Zhao; Z. Li; W. Lei; Yongsheng Wang
International Journal of Radiation Oncology Biology Physics | 2016
Jianliang Yang; Zhijian Xiao; Jiuming He; Shugeng Gao; K. Sun; Xinmin Liu; D. Fang; Ju-Wei Mu; Dali Wang