Abstract
Relevance
Proteasome, a cylindrical complex containing 19S regulatory particle lid, 19S regulatory particle base, and 20S core particle, acted as a major mechanism to regulate the levels of intracellular proteins and degrade misfolded proteins, which involved in many cellular processes, and played important roles in cancer biological processes. Elucidation of proteasome alterations across multiple cancer types will directly contribute to cancer medical services in the context of predictive, preventive, and personalized medicine (PPPM / 3P medicine).
Purpose
This study aimed to investigate proteasome gene alterations across 33 cancer types for discovery of effective biomarkers and therapeutic targets in the framework of PPPM practice in cancers.
Methods
Proteasome gene data, including gene expression RNAseq, somatic mutation, tumor mutation burden (TMB), copy number variant (CNV), microsatellite instability (MSI) score, clinical characteristics, immune phenotype, 22 immune cells, cancer stemness index, drug sensitivity, and related pathways, were systematically analyzed with publically available database and bioinformatics across 11,057 patients with 33 cancer types.
Results
Differentially expressed proteasome genes were extensively found between tumor and control tissues. PSMB4 occurred the top mutation event among proteasome genes, and those proteasome genes were significantly associated with TMB and MSI score. Most of proteasome genes were positively related to CNV among single deletion, control copy number, and single gain. Kaplan–Meier curves and COX regression survival analysis showed proteasome genes were significantly associated with patient survival rate across 33 cancer types. Furthermore, the expressions of proteasome genes were significantly different among different clinical stages and immune subtypes. The expressions of proteasome genes were correlated with immune-related scores (ImmuneScore, StromalScore, and ESTIMATEScore), 22 immune cells, and cancer stemness. The sensitivities of multiple drugs were closely related to proteasome gene expressions. The identified proteasome and proteasome-interacted proteins were significantly enriched in various cancer-related pathways.
Conclusions
This study provided the first landscape of proteasome alterations across 11,057 patients with 33 cancer types and revealed that proteasome played a significant and wide functional role in cancer biological processes. These findings are the precious scientific data to reveal the common and specific alterations of proteasome genes among 33 cancer types, which benefits the research and practice of PPPM in cancers.
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Data accessibility
All data and materials were provided in this manuscript and supplementary materials.
Abbreviations
- ACC:
-
Adrenocortical carcinoma
- ADRM1:
-
Proteasome 26S subunit, non-ATPase 13
- BLCA:
-
Bladder urothelial carcinoma
- BP:
-
Biological process
- BRCA:
-
Breast cancer
- CC:
-
Cellular component
- CDKs:
-
Cyclin-dependent kinases
- CESC:
-
Cervical squamous cell carcinoma and endocervical adenocarcinoma
- CHOL:
-
Cholangiocarcinoma
- CNV:
-
Copy number variant
- COAD:
-
Colon adenocarcinoma
- DEGs:
-
Differentially expressed genes
- DLBC:
-
Lymphoid neoplasm diffuse large b-cell lymphoma
- DTP:
-
Developmental therapeutics program
- ESCA:
-
Esophageal carcinoma
- GBM:
-
Glioblastoma multiforme
- GO:
-
Gene Ontology
- GSVA:
-
Gene set variation analysis
- HNSC:
-
Head and neck squamous carcinoma
- HR:
-
Hazard ratio
- KEGG:
-
Kyoto Encyclopedia of Genes and Genomes
- KICH:
-
Kidney chromophobe
- KIRC:
-
Kidney renal clear cell carcinoma
- KIRP:
-
Kidney renal papillary cell carcinoma
- LAML:
-
Acute myeloid leukemia
- LGG:
-
Brain lower grade glioma
- LIHC:
-
Liver hepatocellular carcinoma
- LUAD:
-
Lung adenocarcinoma
- LUSC:
-
Lung squamous cell carcinoma
- MESO:
-
Mesothelioma
- MF:
-
Molecular function
- MHC:
-
Major histocompatibility complex class I
- MMR:
-
DNA mismatch repair
- mRNA:
-
Messenger RNA
- MSI:
-
Microsatellite instability
- OV:
-
Ovarian serous cystadenocarcinoma
- PAAD:
-
Pancreatic adenocarcinoma
- PCPG:
-
Pheochromocytoma and paraganglioma
- PRAD:
-
Prostate adenocarcinoma
- PSMA1:
-
Proteasome 20S subunit alpha 1
- PSMA2:
-
Proteasome 20S subunit alpha 2
- PSMA3:
-
Proteasome 20S subunit alpha 3
- PSMA4:
-
Proteasome 20S subunit alpha 4
- PSMA5:
-
Proteasome 20S subunit alpha 5
- PSMA6:
-
Proteasome 20S subunit alpha 6
- PSMA7:
-
Proteasome 20S subunit alpha 7
- PSMB1:
-
Proteasome 20S subunit beta 1
- PSMB10:
-
Proteasome 20S subunit beta 10
- PSMB11:
-
Proteasome subunit beta 11
- PSMB2:
-
Proteasome 20S subunit beta 2
- PSMB3:
-
Proteasome 20S subunit beta 3
- PSMB4:
-
Proteasome 20S subunit beta 4
- PSMB5:
-
Proteasome 20S subunit beta 5
- PSMB6:
-
Proteasome 20S subunit beta 6
- PSMB7:
-
Proteasome 20S subunit beta 7
- PSMB8:
-
Proteasome 20S subunit beta 8
- PSMB9:
-
Proteasome 20S subunit beta 9
- PSMC1:
-
Proteasome 26S subunit, ATPase 1
- PSMC2:
-
Proteasome 26S subunit, ATPase 2
- PSMC3:
-
Proteasome 26S subunit, ATPase 3
- PSMC4:
-
Proteasome 26S subunit, ATPase 4
- PSMC5:
-
Proteasome 26S subunit, ATPase 5
- PSMC6:
-
Proteasome 26S subunit, ATPase 6
- PSMD1:
-
Proteasome 26S subunit, non-ATPase 1
- PSMD11:
-
Proteasome 26S subunit, non-ATPase 11
- PSMD12:
-
Proteasome 26S subunit, non-ATPase 12
- PSMD13:
-
Proteasome 26S subunit, non-ATPase 13
- PSMD14:
-
Proteasome 26S subunit, non-ATPase 14
- PSMD2:
-
Proteasome 26S subunit, non-ATPase 2
- PSMD3:
-
Proteasome 26S subunit, non-ATPase 3
- PSMD4:
-
Proteasome 26S subunit, non-ATPase 4
- PSMD6:
-
Proteasome 26S subunit, non-ATPase 6
- PSMD7:
-
Proteasome 26S subunit, non-ATPase 7
- PSMD8:
-
Proteasome 26S subunit, non-ATPase 8
- PSMD9:
-
Proteasome 26S subunit, non-ATPase 9
- PSME1:
-
Proteasome activator subunit 1
- PSME2:
-
Proteasome activator subunit 2
- PSME3:
-
Proteasome activator subunit 3
- PSME4:
-
Proteasome activator subunit 4
- READ:
-
Rectum adenocarcinoma
- RNAss:
-
RNA expression-based stemness scores
- SARC:
-
Sarcoma
- SEM1:
-
SEM1 26S proteasome complex subunit
- SKCM:
-
Skin cutaneous melanoma
- STAD:
-
Stomach adenocarcinoma
- TCGA:
-
The Cancer Genome Atlas
- TGCT:
-
Testicular germ cell tumors
- THCA:
-
Thyroid carcinoma
- THYM:
-
Thymoma
- TMB:
-
Tumor mutation burden
- TME:
-
Tumor microenvironment
- UCEC:
-
Uterine corpus endometrial carcinoma
- UCS:
-
Uterine carcinosarcoma
- UVM:
-
Uveal melanoma
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Acknowledgements
We would like to thank The Cancer Genome Atlas (TCGA) project organizers as well as all study participants for providing the publically available TCGA RNA-seq data and clinical data.
Funding
This work was supported by the Shandong First Medical University Talent Introduction Funds (to X.Z.), the Hunan Provincial Hundred Talent Plan (to X.Z.), the National Natural Science Foundation of China (82172866), and the Academic Promotion Program of Shandong First Medical University (2019ZL002).
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N.L. designed, analyzed data, prepared figures and tables, and wrote the manuscript. X.Z. conceived the concept, supervised results, designed, wrote and critically revised manuscript, and was responsible for its financial supports and the corresponding works. All authors approved the final manuscript.
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Li, N., Zhan, X. Integrated genomic analysis of proteasome alterations across 11,057 patients with 33 cancer types: clinically relevant outcomes in framework of 3P medicine. EPMA Journal 12, 605–627 (2021). https://doi.org/10.1007/s13167-021-00256-z
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DOI: https://doi.org/10.1007/s13167-021-00256-z