CTNI-39. IDENTIFICATION OF AN AUTOPHAGY-RELATED GENE SIGNATURE AND ESTABLISHMENT OF A NOMOGRAM PREDICTING SURVIVAL OF LOWER-GRADE GLIOMA. (12th November 2021)
- Record Type:
- Journal Article
- Title:
- CTNI-39. IDENTIFICATION OF AN AUTOPHAGY-RELATED GENE SIGNATURE AND ESTABLISHMENT OF A NOMOGRAM PREDICTING SURVIVAL OF LOWER-GRADE GLIOMA. (12th November 2021)
- Main Title:
- CTNI-39. IDENTIFICATION OF AN AUTOPHAGY-RELATED GENE SIGNATURE AND ESTABLISHMENT OF A NOMOGRAM PREDICTING SURVIVAL OF LOWER-GRADE GLIOMA
- Authors:
- Wen, Lei
Wang, hui
Lai, Mingyao
Shan, Changguo
Cai, Linbo - Abstract:
- Abstract: OBJECTIVE: The aim of our study was to establish an autophagy-related signature for individualized risk stratification and prognosis prediction in LGG. METHODS: RNA-sequencing data from The Cancer Genome Atlas (TCGA), Genome Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) were used. The 232 ARGs were obtained from the Human Autophagy Database (HADb). Univariate and Lasso regression were employed to identify differentially expressed autophagy-related genes (ARGs) and establish a prognostic signature whose performance was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index) and calibration curve. RESULTS: Fifty-three autophagy-related DEGs were identified. Four autophagy-related genes (DIRAS3, GNAI3, PTK6, and BIRC5) were selected to establish the prognostic signature and verified in the CGGA validation cohorts. Univariate and multivariate Cox regression indicated that the autophagy signature (HR, 95%CI, P) was an independent predictor of prognosis in LGG. Finally, a prognostic nomogram incorporating age, grade, targeted therapy, new event, tumor status and autophagy signature achieved excellent predicative performance (AUC 0.907, 0.865 and 0.858 for 1-year, 3-year and 5-year survival, respectively) verified by Time-dependent ROC, C-index (0.844, 95% CI, 0.799 to 0.889; P = 1.01e-12) and calibration plots. CONCLUSION: The present study constructed a robust four autophagy-related geneAbstract: OBJECTIVE: The aim of our study was to establish an autophagy-related signature for individualized risk stratification and prognosis prediction in LGG. METHODS: RNA-sequencing data from The Cancer Genome Atlas (TCGA), Genome Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) were used. The 232 ARGs were obtained from the Human Autophagy Database (HADb). Univariate and Lasso regression were employed to identify differentially expressed autophagy-related genes (ARGs) and establish a prognostic signature whose performance was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index) and calibration curve. RESULTS: Fifty-three autophagy-related DEGs were identified. Four autophagy-related genes (DIRAS3, GNAI3, PTK6, and BIRC5) were selected to establish the prognostic signature and verified in the CGGA validation cohorts. Univariate and multivariate Cox regression indicated that the autophagy signature (HR, 95%CI, P) was an independent predictor of prognosis in LGG. Finally, a prognostic nomogram incorporating age, grade, targeted therapy, new event, tumor status and autophagy signature achieved excellent predicative performance (AUC 0.907, 0.865 and 0.858 for 1-year, 3-year and 5-year survival, respectively) verified by Time-dependent ROC, C-index (0.844, 95% CI, 0.799 to 0.889; P = 1.01e-12) and calibration plots. CONCLUSION: The present study constructed a robust four autophagy-related gene signature. A prognostic nomogram in risk stratification and prediction of overall survival in LGG was established. The findings may be beneficial to individualized survival prediction and medical decision-making for LGG. … (more)
- Is Part Of:
- Neuro-oncology. Volume 23: Supplement 6(2021)
- Journal:
- Neuro-oncology
- Issue:
- Volume 23: Supplement 6(2021)
- Issue Display:
- Volume 23, Issue 6 (2021)
- Year:
- 2021
- Volume:
- 23
- Issue:
- 6
- Issue Sort Value:
- 2021-0023-0006-0000
- Page Start:
- vi68
- Page End:
- vi68
- Publication Date:
- 2021-11-12
- Subjects:
- Brain Neoplasms -- Periodicals
Brain -- Tumors -- Periodicals
Brain -- Cancer -- Periodicals
Nervous system -- Cancer -- Periodicals
616.99481 - Journal URLs:
- http://neuro-oncology.dukejournals.org/ ↗
http://neuro-oncology.oxfordjournals.org/ ↗
http://www.oxfordjournals.org/content?genre=journal&issn=1522-8517 ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/neuonc/noab196.264 ↗
- Languages:
- English
- ISSNs:
- 1522-8517
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.288000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20105.xml