- 作者: Jing Lu, Francesco Annunziata, Dovydas Sirvinskas, Omid Omrani, Huahui Li, Seyed Mohammad Mahdi Rasa, Anna Krepelova, Lisa Adam & Francesco Neri
- 作者服務機構: 1.Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Jena, Germany 2.Present address: Life Sciences and Systems Biology Department, University of Torino, MBC, via Nizza 52, 10126, Turin, Italy
- 中文摘要:
- 英文摘要:
Background: Patients with colon adenocarcinoma (COAD) exhibit signifcant heterogeneity in overall survival. The
current tumor-node-metastasis staging system is insufcient to provide a precise prediction for prognosis. Identifcation and evaluation of new risk models by using big cancer data may provide a good way to identify prognosisrelated signature.
Methods: We integrated diferent datasets and applied bioinformatic and statistical methods to construct a robust
immune-associated risk model for COAD prognosis. Furthermore, a nomogram was constructed based on the gene
signature and clinicopathological features to improve risk stratifcation and quantify risk assessment for individual
patients.
Results: The immune-associated risk model discriminated high-risk patients in our investigated and validated
cohorts. Survival analyses demonstrated that our gene signature served as an independent risk factor for overall
survival and the nomogram exhibited high accuracy. Functional analysis interpreted the correlation between our risk
model and its role in prognosis by classifying groups with diferent immune activities. Remarkably, patients in the lowrisk group showed higher immune activity, while those in the high-risk group displayed a lower immune activity.
Conclusions: Our study provides a novel tool that may contribute to the optimization of risk stratifcation for survival
and personalized management of COAD. - 中文關鍵字:
- 英文關鍵字: Colon adenocarcinoma, Immune tumor microenvironment, Prognosis, Risk model, Cancer infammation, NCOA7, Immunoglobulin