ArticleCancer medicine2016
Prediction of survival of diffuse large B-cell lymphoma patients via the expression of three inflammatory genes.
Article in Cancer medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The Relationship Between IL-6 and IL-10 Expression Levels and the Prognosis in B-Cell Non-Hodgkin Lymphoma Patients Treated with R-CHOP.Journal of inflammation research · 2025Article
- Identification of an inflammatory response signature associated with prognostic stratification and drug sensitivity in lung adenocarcinoma.Scientific reports · 2022Article
- An Inflammation-Related Nine-Gene Signature to Improve Prognosis Prediction of Lung Adenocarcinoma.Disease markers · 2021Article
- Three inflammation-related genes could predict risk in prognosis and metastasis of patients with breast cancer.Cancer medicine · 2019Article
- Identifying autophagy gene-associated module biomarkers through construction and analysis of an autophagy-mediated ceRNA‑ceRNA interaction network in colorectal cancer.International journal of oncology · 2018Article
- TBX21 predicts prognosis of patients and drives cancer stem cell maintenance via the TBX21-IL-4 pathway in lung adenocarcinoma.Stem cell research & therapy · 2018Article
- Prediction of survival of diffuse large B-cell lymphoma patients via the expression of three inflammatory genes.Cancer medicine · 2016Article
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Authors and funding
5 authors.
Funding
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Abstract
Currently, several gene-expression signatures that were used to predict survival of diffuse large B-cell lymphoma (DLBCL) patients, showed a restriction on the practical work for lack of convenient operation. In this study, we screened inflammatory genes whose expression correlated with survival of DLBCL and established a predictive model including IL6, IL1A and CSF3 through multivariate Cox regression based on the expression of these three genes. We validated the model at protein level in our clinical serum cohort composed of 101 patients of DLBCL and 50 healthy controls and 534 DLBCL patients at mRNA level from three independent Gene Expression Omnibus (GEO) data sets. We found our model to be independent of the International Prognostic Index (IPI), moreover, it can augment the predictive power of IPI. In summary, our three-gene model is sufficient to predict survival of DLBCL patients via measuring the concentration of three inflammatory cytokines in peripheral blood.
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