Research Paper Volume 13, Issue 7 pp 10369—10386
Tumor infiltrating lymphocyte signature is associated with single nucleotide polymorphisms and predicts survival in esophageal squamous cell carcinoma patients
- 1 Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China
- 2 Fudan University Taizhou Institute of Health Sciences, Taizhou, China
- 3 Center for Molecular Medicine of Children's Hospital of Fudan University, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
- 4 Silesian University of Technology, Data Mining Division, Gliwice, Poland
- 5 State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
- 6 Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, China
- 7 IMBT Bioinformatics Research, Boku University Vienn, Vienna, Austria
- 8 Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- 9 Human Phenome Institute, Fudan University, Shanghai, China
- 10 Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
Received: October 7, 2020 Accepted: February 8, 2021 Published: April 4, 2021https://doi.org/10.18632/aging.202798
How to Cite
Copyright: © 2021 Suo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Purpose: Esophageal cancer is the sixth leading cause of cancer-related death worldwide, and is associated with a poor prognosis. Stromal tumor infiltrating lymphocytes (sTIL) and certain single nucleotide polymorphisms (SNPs) have been found to be predictive of patient survival. In this study, we explored the association between SNPs and sTIL regarding the predictability of disease-free survival in patients with esophageal squamous cell carcinoma (ESCC).
Materials and methods: We collected 969 pathologically confirmed ESCC patients from 2010 to 2013 and genotyped 101 SNPs from 59 genes. The number of sTIL for each patient was determined using an automatic algorithm. A Kruskal-Wallis test was used to determine the association between genotype and sTIL. The genotypes and clinical factors related to survival were analyzed using a Kaplan-Meier curve, Cox proportional hazards model, and log-rank test.
Results: The median age of the patients was 67 (42-85 years), there was a median follow-up of 851.5 days and 586 patients died. The univariable analysis showed that 10 of the 101 SNPs were associated with sTIL. Six SNPs were also associated with disease-free survival. A multivariable analysis revealed that sTIL, rs1801131, rs25487, and rs8030672 were independent prognostic markers for ESCC patients. The model combining SNPs, clinical characteristics and sTIL outperformed the model with clinical characteristics alone for predicting outcomes in ESCC patients.
Conclusion: We discovered 10 SNPs associated with sTIL in ESCC and we built a model of sTIL, SNPs and clinical characteristics with improved prediction of survival in ESCC patients.
ESCC: esophageal squamous cell carcinoma; sTIL: stromal tumor infiltrating lymphocytes; SNPs: single nucleotide polymorphisms; GMM: gaussian mixture model; DFS: disease-free survival; AUC: area under curve; ROC: receiver operating characteristic.