Construction and validation of a risk scoring model for diffuse large B-cell lymphoma based on ferroptosis-related genes and its association with immune infiltration
| Autor: | Dan Xiong, Mojuan Li, Chong Zeng |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Cancer Research
LDH lactic dehydrogenase NK natural killer cells AUC area under the receiver operating characteristic curve LNCRNA long non-coding RNAs immune system diseases hemic and lymphatic diseases KEGG Kyoto encyclopedia of genes and genomes Ferroptosis neoplasms RC254-282 Original Research GO gene ontology TCGA the cancer genome atlas LASSO least absolute shrinkage and selection operator ROC the receiver operating characteristic Neoplasms. Tumors. Oncology. Including cancer and carcinogens CC cellular component MF molecular function Immune infiltration DLBCL diffuse large b-cell lymphoma miRNA microrna Oncology DLBCL Risk scoring model BP biological process UCSC The University of California Santa Cruz GEO the gene expression omnibus |
| Zdroj: | Translational Oncology Translational Oncology, Vol 16, Iss, Pp 101314-(2022) |
| ISSN: | 1936-5233 |
| Popis: | Highlights • Categorization of DLBCL into four clusters based on survival- and ferroptosis-related factors. • Establishment of an efficient risk scoring model is established for patients with DLBCL. • Ferroptosis-based risk scoring model reveals immune infiltration correlation in DLBCL. Backgrounds The prognostic significance of ferroptosis-related genes is well known. However, survival- and ferroptosis-related genes are not currently considered in risk scoring models for diffuse large B-cell lymphoma (DLBCL). Materials and methods Ferroptosis regulators and markers were downloaded from the FerrDb database. The transcriptome profiling data were collected from the cancer genome atlas (TCGA). Transcriptome data and corresponding clinical information of DLBCL were downloaded from the gene expression omnibus (GEO). The validation data were downloaded using the UCSC Xena browser. ConsensusClusterPlus was used to categorize DLBCL samples according to gene expression profiles. The survival function was plotted with the Kaplan-Meier plots. The nomogram was built using multivariate logistic regression analysis and the Cox proportional hazards regression model. Results Based on the GSE11318 dataset of 203 samples and 267 ferroptosis-related gene expression profiles, we identified four clusters. A total of 19 survival-related genes were found associated with ferroptosis. The prognostic risk scoring model was constructed based on the regression coefficients. The obtained area under the receiver operating characteristic curve (AUC) values were 0.769, 0.801, and 0.791 for 1-, 3-, and 5-year survival, respectively. DLBCL samples with cluster 2 or cancer stage IV have shorter survival. Correlations between the immune infiltration and risk scores of the 12 immune cells were demonstrated. The response of DLBCL to doxorubicin was effectively validated by the risk scoring model. Conclusions In this study, a ferroptosis-based risk scoring model for patients with DLBCL was constructed and validated in an independent dataset. This risk score model has a better efficacy in predicting survival compared to clinical characteristics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|