Nomogram to predict lymph node metastasis in patients with early oesophageal squamous cell carcinoma

2018 ◽  
Vol 105 (11) ◽  
pp. 1464-1470 ◽  
Author(s):  
H. Zheng ◽  
H. Tang ◽  
H. Wang ◽  
Y. Fang ◽  
Y. Shen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Oesophageal Squamous Cell Carcinoma ◽  
Node Metastasis

scholarly journals MMS22L Expression as a Predictive Biomarker for the Efficacy of Neoadjuvant Chemoradiotherapy in Oesophageal Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiyu Luo ◽  
Wenwu He ◽  
Tianqin Mao ◽  
Xuefeng Leng ◽  
Hong Wu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cell Carcinoma ◽  
Mrna Expression ◽  
Squamous Cell ◽  
Neoadjuvant Chemoradiotherapy ◽  
Molecular Networks ◽  
Oesophageal Squamous Cell Carcinoma ◽  
Node Metastasis

Long-term survival in oesophageal squamous cell carcinoma (ESCC) is related with pathological response after neoadjuvant chemoradiotherapy (NCRT) followed by surgery. However, effective biomarkers to predict the pathologic response are still lacking. Therefore, a systematic analysis focusing on genes associated with the efficacy of chemoradiotherapy in ESCC will provide valuable insights into the regulation of molecular processes. By screening publications deposited in PubMed, we collected genes associated with the efficacy of chemoradiotherapy. A specific subnetwork was constructed using the Steiner minimum tree algorithm. Survival analysis in Kaplan-Meier Plotter online resources was performed to explore the relationship between gene mRNA expression and the prognosis of patients with ESCC. Quantitative real-time polymerase chain reaction (qRT-PCR), Western blotting, and immunohistochemical staining (IHC) were used to evaluate the expression of key genes in cell lines and human samples. The areas under the receiver operating characteristic (ROC) curves (AUCs) were used to describe performance and accuracy. Transwell assays assessed cell migration, and cell viability was detected using the Cytotoxicity Assay. Finally, we identified 101 genes associated with efficacy of chemoradiotherapy. Additionally, specific molecular networks included some potential related genes, such as CUL3, MUC13, MMS22L, MME, UBC, VAPA, CYP1B1, and UGDH. The MMS22L mRNA expression level showed the most significant association with the ESCC patient outcome (p < 0.01). Furthermore, MMS22L was downregulated at both the mRNA (p < 0.001) and protein levels in tumour tissues compared with that in normal tissues. Lymph node metastasis was significantly associated with low MMS22L expression (p < 0.01). MMS22L levels were inversely correlated with the NCRT response in ESCC (p < 0.01). The resulting area under the ROC curve was 0.847 (95% CI: 0.7232 to 0.9703; p < 0.01). In conclusion, low expression of MMS22L is associated with poor response to NCRT, worse survival, lymph node metastasis, and enhanced migration of tumour cells in ESCC.

scholarly journals A nomogram to predict lymph node metastasis risk for early esophageal squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaofeng Duan ◽  
Xiaobin Shang ◽  
Jie Yue ◽  
Zhao Ma ◽  
Chuangui Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Early Stage ◽  
Derivation Cohort ◽  
Node Metastasis

Abstract Background A nomogram was developed to predict lymph node metastasis (LNM) for patients with early-stage esophageal squamous cell carcinoma (ESCC). Methods We used the clinical data of ESCC patients with pathological T1 stage disease who underwent surgery from January 2011 to June 2018 to develop a nomogram model. Multivariable logistic regression was used to confirm the risk factors for variable selection. The risk of LNM was stratified based on the nomogram model. The nomogram was validated by an independent cohort which included early ESCC patients underwent esophagectomy between July 2018 and December 2019. Results Of the 223 patients, 36 (16.1%) patients had LNM. The following three variables were confirmed as LNM risk factors and were included in the nomogram model: tumor differentiation (odds ratio [OR] = 3.776, 95% confidence interval [CI] 1.515–9.360, p = 0.004), depth of tumor invasion (OR = 3.124, 95% CI 1.146–8.511, p = 0.026), and tumor size (OR = 2.420, 95% CI 1.070–5.473, p = 0.034). The C-index was 0.810 (95% CI 0.742–0.895) in the derivation cohort (223 patients) and 0.830 (95% CI 0.763–0.902) in the validation cohort (80 patients). Conclusions A validated nomogram can predict the risk of LNM via risk stratification. It could be used to assist in the decision-making process to determine which patients should undergo esophagectomy and for which patients with a low risk of LNM, curative endoscopic resection would be sufficient.

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