Prediction of Lymph Node Metastasis with Use of Artificial Neural Networks Based on Gene Expression Profiles in Esophageal Squamous Cell Carcinoma

2004 ◽  
Vol 11 (12) ◽  
pp. 1070-1078 ◽  
Author(s):  
Takatsugu Kan ◽  
Yutaka Shimada ◽  
Fumiaki Sato ◽  
Tetsuo Ito ◽  
Kan Kondo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Networks ◽  
Squamous Cell Carcinoma ◽  
Artificial Neural Networks ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Node Metastasis

Prediction of lymph node metastasis by analysis of gene expression profiles in non-small cell lung cancer1

2004 ◽  
Vol 122 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Minoru Takada ◽  
Mitsuhiro Tada ◽  
Eiji Tamoto ◽  
Akiko Kawakami ◽  
Katsuhiko Murakawa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Small Cell ◽  
Small Cell Lung ◽  
Node Metastasis

scholarly journals Gene Expression of Mesenchyme Forkhead 1 (FOXC2) Significantly Correlates With the Degree of Lymph Node Metastasis in Colorectal Cancer

2011 ◽  
Vol 96 (3) ◽  
pp. 207-216 ◽  
Author(s):  
Toshiaki Watanabe ◽  
Takashi Kobunai ◽  
Yoko Yamamoto ◽  
Keiji Matsuda ◽  
Soichiro Ishihara ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Node Metastases ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Node Metastasis ◽  
Node Metastases ◽  
Colorectal Cancer Patients

Abstract In stage III colorectal cancer, patients with N1 stage tumors show poorer outcome than patients with N2 stage tumors. Our objective was to identify genes that are predictive for the presence of lymph node metastasis, and to characterize the aggressiveness of lymph node metastases. Gene expression profiles of colorectal cancer were determined by microarray in training (n  =  116) and test (n  =  25) sets of patients. We identified 40 discriminating probes in patients with and without lymph node metastases. Using these probes, we could predict the presence of lymph node metastasis with an accuracy of 87.1% (training set) and 76.0% (test set). Among discriminating probes, FOXC2 expression was significantly correlated with the degree of lymph node metastasis. FOXC2 was expressed significantly and disparately in patients with N1 and N2 stage tumors as analyzed by real-time reverse transcriptase–polymerase chain reaction. FOXC2 appears to be involved in determining the aggressiveness of lymph node metastasis in colorectal cancer.

scholarly journals Maintenance of Head and Neck Tumor Gene Expression Profiles upon Lymph Node Metastasis

2006 ◽  
Vol 66 (23) ◽  
pp. 11110-11114 ◽  
Author(s):  
Paul Roepman ◽  
Alike de Jager ◽  
Marian J.A. Groot Koerkamp ◽  
J. Alain Kummer ◽  
Piet J. Slootweg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Head And Neck ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Head And Neck Tumor ◽  
Node Metastasis ◽  
Tumor Gene Expression ◽  
Tumor Gene

scholarly journals Prediction of Lymph Node Metastasis by Analysis of Gene Expression Profiles in Primary Lung Adenocarcinomas

2005 ◽  
Vol 11 (11) ◽  
pp. 4128-4135 ◽  
Author(s):  
Liqiang Xi ◽  
James Lyons-Weiler ◽  
Michael C. Coello ◽  
Xin Huang ◽  
William E. Gooding ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Node Metastasis ◽  
Lung Adenocarcinomas

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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