ArticleOncology letters2019
A predicted risk score based on the expression of 16 autophagy-related genes for multiple myeloma survival.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization.International journal of molecular sciences · 2023Pooled it
- Genome-wide identification of potential biomarkers in multiple myeloma using meta-analysis of mRNA and miRNA expression data.Scientific reports · 2021Pooled it
- Dual Roles of NIX/BNIP3L in Tumors: Friend or Foe.Biology · 2026Review
- A new perspective on the autophagic and non-autophagic functions of the GABARAP protein family: a potential therapeutic target for human diseases.Molecular and cellular biochemistry · 2024Review
- EVA1A, a novel and promising prognostic biomarker in colorectal cancer.Frontiers in oncology · 2024Article
- Identification and panoramic analysis of drug response-related genes in triple negative breast cancer using as an example NVP-BEZ235.Scientific reports · 2023Article
- Autophagy-related genes affect the survival of multiple myeloma patients depending on chromosomal abnormality.Asian biomedicine : research, reviews and news · 2022Article
- Development and validation of an RNA-seq-based transcriptomic risk score for asthma.Scientific reports · 2022Article
- NCKAP1 is a Prognostic Biomarker for Inhibition of Cell Growth in Clear Cell Renal Cell Carcinoma.Frontiers in genetics · 2022Article
- A Novel Defined Super-Enhancer Associated Gene Signature to Predict Prognosis in Patients With Diffuse Large B-Cell Lymphoma.Frontiers in genetics · 2022Article
- Hypoxia-Immune-Related Gene SLC19A1 Serves as a Potential Biomarker for Prognosis in Multiple Myeloma.Frontiers in immunology · 2022Article
- The Significance of mRNA in the Biology of Multiple Myeloma and Its Clinical Implications.International journal of molecular sciences · 2021Review
- Identification of autophagy-related risk signatures for the prognosis, diagnosis, and targeted therapy in cervical cancer.Cancer cell international · 2021Article
- Prognostic Signature of Osteosarcoma Based on 14 Autophagy-Related Genes.Pathology oncology research : POR · 2021Article
- Machine learning identifies two autophagy-related genes as markers of recurrence in colorectal cancer.The Journal of international medical research · 2020Article
- Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients.Frontiers in cell and developmental biology · 2020Article
- Identification and Validation of a Potential Prognostic 7-lncRNA Signature for Predicting Survival in Patients with Multiple Myeloma.BioMed research international · 2020Article
- Flubendazole elicits anti-cancer effects via targeting EVA1A-modulated autophagy and apoptosis in Triple-negative Breast Cancer.Theranostics · 2020Article
- Expression and Clinical Significance of BCL2 Interacting Protein 3 Like in Multiple Myeloma.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autophagy has an important role in the pathogenesis of plasma cell development and multiple myeloma (MM); however, the prognostic role of autophagy-related genes (ARGs) in MM remains undefined. In the present study, the expression profiles of 234 ARGs were obtained from a Gene Expression Omnibus dataset (accession GSE24080), which contains 559 samples of patients with MM analyzed with 54,675 probes. Univariate Cox regression analysis identified 55 ARGs that were significantly associated with event-free survival of MM. Furthermore, a risk score with 16 survival-associated ARGs was developed using multivariate Cox regression analysis, including ATIC, BNIP3L, CALCOCO2, DNAJB1, DNAJB9, EIF4EBP1, EVA1A, FKBP1B, FOXO1, FOXO3, GABARAP, HIF1A, NCKAP1, PRKAR1A and SUPT20H, was constructed. Using this prognostic signature, patients with MM could be separated into high- and low-risk groups with distinct clinical outcomes. The area under the curve values for the receiver operating characteristic curves were 0.740, 0.741 and 0.712 for 3, 5 and 10 years prognosis predictions, respectively. Notably, the prognostic role of this risk score could be validated with another four independent cohorts (accessions: GSE57317, GSE4581, GSE4452 and GSE4204). In conclusion, ARGs may serve vital roles in the progression of MM, and the ARGs-based prognostic model may provide novel ideas for clinical applications in MM.
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