Xunyu Xu

Dr. Xunyu Xu


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 June 2022 in Frontiers in Oncology
Verified
Journal Article
Open access
YKYanli Kang
Yanli Kang
JYJianbin You
Jianbin You
YGYuhan Gan
Yuhan Gan
QCQianshun Chen
Qianshun Chen
CHChen Huang
Chen Huang
LCLiangyuan Chen
Liangyuan Chen
Background: Circular RNAs (circRNAs) play an important role in tumorigenesis and several circulating circRNA signatures are closely associated with tumor diagnosis. However, the expression and clinical significance of the two forms of circulating circRNAs, serum and serum exosomal, in patients with lung adenocarcinoma (LUAD), have not been characterized.Methods: Three differentially expressed exosomal circRNAs, hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896, were selected based on previous exosomal circRNA sequencing data analyses of LUAD patients. The expression of these circRNAs in serum and serum-derived exosomes of LUAD patients was assessed using quantitative real-time PCR (qRT-PCR), and correlations between circRNA expression and clinicopathological characteristics were analyzed. The reliability of serum and serum exosomal hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 to diagnose LUAD was evaluated using receiver operating characteristic (ROC) analysis.Results: Expression of serum and serum exosomal hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 were significantly higher in LUAD patients than in healthy donors, and significantly lower after surgery. These three serum exosomal circRNAs were also associated with a higher cancer stage. Exosomal hsa_circ_0001492 expression was positively correlated with carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) levels. An association between the expression of the three serum circRNAs and clinical characteristics was not observed. In addition, the three serum exosomal circRNAs had higher diagnostic sensitivity and specificity than the serum circRNAs, and the area under the curve (AUC) of all three serum exosomal circRNAs was >0.75. The combination of exosomal hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 had better diagnostic sensitivity and specificity than that of a single marker, with an AUC value of 0.805.Conclusions: The serum and serum exosomal circRNAs, hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896, were upregulated in LUAD patients. Serum exosomal circRNAs may serve as more effective biomarkers than serum circRNAs for LUAD diagnosis and may further aid the detection of this disease.

10 August 2022 in Frontiers in Oncology
Verified
Journal Article
Open access
CHChen Huang
Chen Huang
YDYongmei Dai
Yongmei Dai
QCQianshun Chen
Qianshun Chen
HCHongchao Chen
Hongchao Chen
YLYuanfeng Lin
Yuanfeng Lin
XCXiao Chen
Xiao Chen
Objective: To compare the performance of a deep learning survival network with the tumor, node, and metastasis (TNM) staging system in survival prediction and test the reliability of individual treatment recommendations provided by the network.Methods: In this population-based cohort study, we developed and validated a deep learning survival model using consecutive cases of newly diagnosed stage I to IV esophageal cancer between January 2004 and December 2015 in a Surveillance, Epidemiology, and End Results (SEER) database. The model was externally validated in an independent cohort from Fujian Provincial Hospital. The C statistic was used to compare the performance of the deep learning survival model and TNM staging system. Two other deep learning risk prediction models were trained for treatment recommendations. A Kaplan–Meier survival curve was used to compare survival between the population that followed the recommended therapy and those who did not.Results: A total of 9069 patients were included in this study. The deep learning network showed more promising results in predicting esophageal cancer-specific survival than the TNM stage in the internal test dataset (C-index=0.753 vs. 0.638) and external validation dataset (C-index=0.687 vs. 0.643). The population who received the recommended treatments had superior survival compared to those who did not, based on the internal test dataset (hazard ratio, 0.753; 95% CI, 0.556-0.987; P=0.042) and the external validation dataset (hazard ratio, 0.633; 95% CI, 0.459-0.834; P=0.0003).Conclusion: Deep learning neural networks have potential advantages over traditional linear models in prognostic assessment and treatment recommendations. This novel analytical approach may provide reliable information on individual survival and treatment recommendations for patients with esophageal cancer.

19 January 2017 in World Journal of Surgical Oncology
Verified
Journal Article
Open access
PDF file
CHChen Huang
Chen Huang
XXXunhai Xu
Xunhai Xu
BZBinbin Zhuang
Binbin Zhuang
WCWenshu Chen
Wenshu Chen
XXXunyu Xu
Xunyu Xu
SLShengmei Lin
Shengmei Lin
The delta-shaped anastomosis has been reported to reduce anastomotic complications for a decade. However, little has been written comparing this technique with the circular stapler technique. The objective of this retrospective study was to assess the safety and efficacy of cervical delta-shaped anastomosis after esophagectomy. Medical records of patients with esophageal squamous cell carcinoma who underwent McKeown (three-incision) esophagectomy between September 2013 and June 2015 were reviewed. Either circular stapled anastomosis (CSA) or delta-shaped anastomosis (DSA) was performed at the cervical stage. The clinical characteristics and short-term outcome were retrospectively assessed to identify the differences between the two groups. A total of 81 patients were included in this study. The clinical characteristics were similar between the two groups. Cervical anastomotic leakage occurred in 3 (7.7%) of 39 patients in the DSA group and in 8 (19%) of 42 patients in the CSA group (P = 0.197). The average anastomotic orifice width was 16.1 ± 4.9 mm and 11.7 ± 2.2 mm, respectively (P < 0.001). The incidence of anastomotic stenosis was 2.6% (1/39) and 23.5% (10/42) in the DSA and CSA groups, respectively (P = 0.007). There was no significant difference in surgical duration, blood loss, pulmonary complication, postoperative mortality, time of hospitalisation and time of ICU stay between the two groups. Delta-shaped anastomosis may be an effective alternative method for gastroesophageal anastomosis after esophagectomy, with lower incidence of leakage and stenosis.

18 July 2022 in Pathology - Research and Practice
Verified
Journal Article
Closed access
LCLiangyuan Chen
Liangyuan Chen
YKYanli Kang
Yanli Kang
YJYingfeng Jiang
Yingfeng Jiang
JYJianbin You
Jianbin You
CHChen Huang
Chen Huang
FCFalin Chen
Falin Chen

20 September 2022 in Frontiers in Oncology
Verified
Journal Article
Open access
JYJianbin You
Jianbin You
GYGuoliu Yang
Guoliu Yang
YWYi Wu
Yi Wu
XLXuan Lu
Xuan Lu
SHShuyu Huang
Shuyu Huang
LCLiangyuan Chen
Liangyuan Chen
Objective: TRNA-derived fragments (tRFs) and tRNA-derived stress-induced RNAs (tiRNAs) are recognized as novel and potential types of non-coding RNAs (ncRNAs), and several tRF/tiRNA signatures are closely associated with tumor diagnosis. This study aimed to analyze the expression profiles of plasma tRFs/tiRNAs and to clarify their diagnostic value in lung adenocarcinoma (LUAD).Methods: The differential expression profiles of plasma tRFs/tiRNAs in patients with four patients with early LUAD, four patients with advanced LUAD, and four healthy controls were analyzed using high-throughput sequencing technology. Then, plasma tRFs/tiRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR), and their diagnostic efficiency was appraised by receiver operating characteristic curve analysis. The correlation of candidate plasma tRFs/tiRNAs with clinicopathological features was also analyzed. Finally, bioinformatics analysis was performed to explore and identify the potential biological pathways induced by tRFs/tiRNAs.Results: The sequencing results revealed that tRFs/tiRNAs from plasma samples in patients with LUAD were differently expressed, supporting the necessity of exploring their potential as biomarkers. The validation results of qRT-PCR demonstrated that the expression level of tRF-1:29-Pro-AGG-1-M6 was downregulated in LUAD, while that of tRF-55:76-Tyr-GTA-1-M2 was upregulated, which was consistent with the sequencing data. The areas under the receiver operating characteristic curve of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 were 0.882 and 0.896, respectively, which have significant values in the diagnosis of LUAD. The expressions of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 in LUAD were obviously correlated with various clinicopathological features such as tumor–node–metastasis stage, node stage, and the expression levels of carcinoembryonic antigen. In addition, their expression was significantly altered from before to after tumor resection in LUAD patients. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses further indicated that tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 are widely distributed and apparently enriched in several tumor-related signaling pathways.Conclusions: Plasma tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 may be promising components in the development of highly sensitive and non-invasive biomarkers for LUAD diagnosis.

6 February 2022 in Cancer Medicine
Verified
Journal Article
Open access
PDF file
HCHongchao Chen
Hongchao Chen
CHChen Huang
Chen Huang
HGHuiqing Ge
Huiqing Ge
QCQianshun Chen
Qianshun Chen
JCJing Chen
Jing Chen
XXXunyu Xu
Xunyu Xu
Introduction: The current American Joint Committee on Cancer (AJCC) M1a staging of non‐small cell lung cancer (NSCLC) encompasses a wide disease spectrum, showing diverse prognosis.Methods: Patients who diagnosed in an earlier period formed the training cohort, and those who diagnosed thereafter formed the validation cohort. Kaplan–Meier analysis was performed for the training cohort by dividing the M1a stage into three subgroups: (I) malignant pleural effusion (MPE) or malignant pericardial effusion (MPCE); (II) separate tumor nodules in contralateral lung (STCL); and (III) pleural tumor nodules on the ipsilateral lung (PTIL). Gender, age, histologic, N stage, grade, surgery for primary site, lymphadenectomy, M1a groups, and chemotherapy were selected as independent prognostic factors using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. And a nomogram was constructed using Cox hazard regression analysis. Accuracy and clinical practicability were separately tested by Harrell's concordance index, the receiver operating characteristic (ROC) curve, calibration plots, residual plot, the integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA).Results: The concordance index (0.661 for the training cohort and 0.688 for the validation cohort) and the area under the ROC curve (training cohort: 0.709 for 1‐year and 0.727 for 2‐year OS prediction; validation cohort: 0.737 for 1‐year and 0.734 for 2‐year OS prediction) indicated satisfactory discriminative ability of the nomogram. Calibration curve and DCA presented great prognostic accuracy, and clinical applicability. Its prognostic accuracy preceded the AJCC staging with evaluated NRI (1‐year: 0.327; 2‐year: 0.302) and IDI (1‐year: 0.138; 2‐year: 0.130).Conclusion: Our study established a nomogram for the prediction of 1‐ and 2‐year OS in patients with NSCLC diagnosed with stage M1a, facilitating healthcare workers to accurately evaluate the individual survival of M1a NSCLC patients. The accuracy and clinical applicability of this nomogram were validated.