A Ubiquitin-Proteasome Gene Signature for Predicting Prognosis in Patients With Lung Adenocarcinoma

Tang, Yunliang; Guo, Yinhong

doi:10.3389/fgene.2022.893511

Cited by 7 publications

(4 citation statements)

References 41 publications

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“…Indeed, the proteasomal subunit, PSMD2 , has prognostic significance in patients with bladder urothelial carcinoma [ 41 ] and lung adenocarcinoma [ 42 , 43 ]. Other reports demonstrated a role for PSMD6 in lung adenocarcinoma [ 20 ] and esophageal squamous cell carcinoma [ 43 ].…”

Section: Discussionmentioning

confidence: 99%

19S Proteasome Subunits as Oncogenes and Prognostic Biomarkers in FLT3-Mutated Acute Myeloid Leukemia (AML)

Lara

Bencomo‐Alvarez

Gonzalez

et al. 2022

IJMS

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26S proteasome non-ATPase subunits 1 (PSMD1) and 3 (PSMD3) were recently identified as prognostic biomarkers and potential therapeutic targets in chronic myeloid leukemia (CML) and multiple solid tumors. In the present study, we analyzed the expression of 19S proteasome subunits in acute myeloid leukemia (AML) patients with mutations in the FMS-like tyrosine kinase 3 (FLT3) gene and assessed their impact on overall survival (OS). High levels of PSMD3 but not PSMD1 expression correlated with a worse OS in FLT3-mutated AML. Consistent with an oncogenic role for PSMD3 in AML, shRNA-mediated PSMD3 knockdown impaired colony formation of FLT3+ AML cell lines, which correlated with increased OS in xenograft models. While PSMD3 regulated nuclear factor-kappa B (NF-κB) transcriptional activity in CML, we did not observe similar effects in FLT3+ AML cells. Rather, proteomics analyses suggested a role for PSMD3 in neutrophil degranulation and energy metabolism. Finally, we identified additional PSMD subunits that are upregulated in AML patients with mutated versus wild-type FLT3, which correlated with worse outcomes. These findings suggest that different components of the 19S regulatory complex of the 26S proteasome can have indications for OS and may serve as prognostic biomarkers in AML and other types of cancers.

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Section: Discussionmentioning

confidence: 99%

19S Proteasome Subunits as Oncogenes and Prognostic Biomarkers in FLT3-Mutated Acute Myeloid Leukemia (AML)

Lara

Bencomo‐Alvarez

Gonzalez

et al. 2022

IJMS

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“…To compare the prognostic efficacy of CBPRS with existing LUAD models, we integrated 11 previous studies that used different biologically significant features, such as arginine-substituted succinate 30 , copper death 31 , necrotic apoptosis 32 , immune activation 33 , ubiquitin proteasome 34 and autophagy 35 . Notably, CBPRS exhibited better C-index performance than almost all models in the TCGA-LUAD, GSE31210 and GSE50081 datasets (Figure 5 A-C).…”

Section: Resultsmentioning

confidence: 99%

Copper-binding protein modelling by single-cell transcriptome and Bulk transcriptome to predict overall survival in lung adenocarcinoma patients

Shengping,

Luyao,

Yiluo

et al. 2024

J. Cancer

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Background: Copper and copper-binding proteins are key components of tumour progression as they play an important role in tumour invasion and migration, and abnormal accumulation of copper (Cu) may be intimately linked to with lung adenocarcinoma (LUAD). Methods: Data on lung adenocarcinoma were sourced from the Cancer Genome Atlas (TCGA) database and the National Centre for Biotechnology Information (GEO). 10x scRNA sequencing, which is from Bischoff P et al, was used for down-sequencing clustering and subgroup identification using TSNE. The genes for Copper-binding proteins (CBP) were acquired from the MSigDB database. LASSO-Cox analysis was subsequently used to construct a model for copper-binding proteins (CBPRS), which was then compared to lung adenocarcinoma models developed by others. External validation was carried out in the GSE31210 and GSE50081 cohorts. The effectiveness of immunotherapy was evaluated using the TIDE algorithm and the IMvigor210, GSE78220, and TCIA cohorts. Furthermore, differences in mutational profiles and the immune microenvironment between different risk groups were investigated. The CBPRS's key regulatory genes were screened using ROC diagnostic and KM survival curves. The differential expression of these genes was then verified by RT-qPCR. Results: The six CBP genes were identified as highly predictive of LUAD prognosis and significantly correlated with it. Multivariate analysis showed that patients in the low-risk group had a higher overall survival rate than those in the high-risk group, indicating that the model was an independent predictor of LUAD. The CBPRS demonstrated superior predictive ability compared to 11 previously published models. We constructed a column-line graph that includes CBPRS and clinical characteristics, which exhibits high predictive performance. Additionally, we observed significant differences in biological functions, mutational landscapes, and immune cell infiltration in the tumour microenvironment between the high-risk and low-risk groups. It is noteworthy that immunotherapy was also significant in both the high- and low-risk groups. These results suggest that the model has good predictive efficacy. Conclusions: The CBP model demonstrated good predictive performance, revealing characteristics of the tumour microenvironment. This provides a new method for assessing the efficacy of pre-immunisation and offers a potential strategy for future treatment of lung adenocarcinoma.

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“…GSE118985 included bone marrow samples from 68 normal controls and 460 newly diagnosed patients with MM and 132 MM patients in complete remission. A list of 804 UPS genes ( Supplementary Table 1 ) were identified in the previous studies and used as the basis of our evaluations in the current study [ 15 , 16 ].…”

Section: Methodsmentioning

confidence: 99%

A nomogram for predicting prognosis of multiple myeloma patients based on a ubiquitin-proteasome gene signature

Liu

Sun

et al. 2022

Aging

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Background: Multiple myeloma (MM) is a malignant hematopoietic disease that is usually incurable. However, the ubiquitin-proteasome system (UPS) genes have not yet been established as a prognostic predictor for MM, despite their potential applications in other cancers. Methods: RNA sequencing data and corresponding clinical information were acquired from Multiple Myeloma Research Foundation (MMRF)-COMMPASS and served as a training set (n=787). Validation of the prediction signature were conducted by the Gene Expression Omnibus (GEO) databases (n=1040). To develop a prognostic signature for overall survival (OS), least absolute shrinkage and selection operator regressions, along with Cox regressions, were used. Results: A six-gene signature, including KCTD12, SIAH1, TRIM58, TRIM47, UBE2S, and UBE2T, was established. Kaplan-Meier survival analysis of the training and validation cohorts revealed that patients with high-risk conditions had a significantly worse prognosis than those with low-risk conditions. Furthermore, UPS-related signature is associated with a positive immune response. For predicting survival, a simple to use nomogram and the corresponding web-based calculator (https://jiangyanxiamm.shinyapps.io/MMprognosis/) were built based on the UPS signature and its clinical features. Analyses of calibration plots and decision curves showed clinical utility for both training and validation datasets. Conclusions: As a result of these results, we established a genetic signature for MM based on UPS. This genetic signature could contribute to improving individualized survival prediction, thereby facilitating clinical decisions in patients with MM.

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A Ubiquitin-Proteasome Gene Signature for Predicting Prognosis in Patients With Lung Adenocarcinoma

Cited by 7 publications

References 41 publications

19S Proteasome Subunits as Oncogenes and Prognostic Biomarkers in FLT3-Mutated Acute Myeloid Leukemia (AML)

19S Proteasome Subunits as Oncogenes and Prognostic Biomarkers in FLT3-Mutated Acute Myeloid Leukemia (AML)

Copper-binding protein modelling by single-cell transcriptome and Bulk transcriptome to predict overall survival in lung adenocarcinoma patients

A nomogram for predicting prognosis of multiple myeloma patients based on a ubiquitin-proteasome gene signature

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