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Integrated genomic analysis of proteasome alterations across 11,057 patients with 33 cancer types: clinically relevant outcomes in framework of 3P medicine

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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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Correspondence to Xianquan Zhan.

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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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