Integrative analysis of the prognostic value and immune microenvironment of mitophagy-related signature for multiple myeloma.

Publisher: BioMed Central Country of Publication: England NLM ID: 100967800 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2407 (Electronic) Linking ISSN: 14712407 NLM ISO Abbreviation: BMC Cancer Subsets: MEDLINE

Original Publication: London : BioMed Central, [2001-

Multiple Myeloma*/drug therapy ; Multiple Myeloma*/genetics; Humans ; Prognosis ; Mitophagy/genetics ; Genes, Regulator ; Protein Kinases ; Tumor Microenvironment/genetics ; Tumor Suppressor Proteins ; Ubiquitin-Protein Ligases/genetics

Background: Multiple myeloma (MM) is a fatal malignant tumor in hematology. Mitophagy plays vital roles in the pathogenesis and drug sensitivity of MM.
Methods: We acquired transcriptomic expression data and clinical index of MM patients from NCI public database, and 36 genes involved in mitophagy from the gene set enrichment analysis (GSEA) database. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted to construct a risk score prognostic model. Kaplan-Meier survival analysis and receiver operation characteristic curves (ROC) were conducted to identify the efficiency of prognosis and diagnosis. ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) was performed to uncover the level of immune infiltration. QRT-PCR was performed to verify gene expression in clinical samples of MM patients. The sensitivity to chemotherapy drugs was evaluated upon the database of the genomics of drug sensitivity in cancer (GDSC).
Results: Fifty mitophagy-related genes were differently expressed in two independent cohorts. Ten out of these genes were identified to be related to MM overall survival (OS) rate. A prognostic risk signature model was built upon on these genes: VDAC1, PINK1, VPS13C, ATG13, and HUWE1, which predicted the survival of MM accurately and stably both in training and validation cohorts. MM patients suffered more adverse prognosis showed more higher risk core. In addition, the risk score was considered as an independent prognostic element for OS of MM patients by multivariate cox regression analysis. Functional pathway enrichment analysis of differentially expressed genes (DEGs) based on risk score showed terms of cell cycle, immune response, mTOR pathway, and MYC targets were obviously enriched. Furthermore, MM patients with higher risk score were observed lower immune scores and lower immune infiltration levels. The results of qRT-PCR verified VDAC1, PINK1, and HUWE1 were dysregulated in new diagnosed MM patients. Finally, further analysis indicated MM patients showed more susceptive to bortezomib, lenalidomide and rapamycin in high-risk group.
Conclusion: Our research provided a neoteric prognostic model of MM based on mitophagy genes. The immune infiltration level based on risk score paved a better understanding of the participation of mitophagy in MM.
(© 2023. BioMed Central Ltd., part of Springer Nature.)

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2020JQ-558 Natural Science Foundation of China Shaanxi Province; 82100150 National Natural Science Foundation of China; 82170140 National Natural Science Foundation of China; 2019YFA0801804 National Key Research and Development Program of China

Keywords: Immune infiltration; Mitophagy; Multiple myeloma; Nomogram; Prognosis; Risk signature

EC 2.7.- (Protein Kinases)
EC 2.3.2.26 (HUWE1 protein, human)
0 (Tumor Suppressor Proteins)
EC 2.3.2.27 (Ubiquitin-Protein Ligases)

Date Created: 20230912 Date Completed: 20230914 Latest Revision: 20231123

20231215

PMC10496355

10.1186/s12885-023-11371-7

37700273