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Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer.

ABSTRACT: The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan-Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer.

SUBMITTER: Chiao CC

PROVIDER: S-EPMC8699889 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer.

Chiao Chung-Chieh CC Liu Yen-Hsi YH Phan Nam Nhut NN An Ton Nu Thuy NT Ta Hoang Dang Khoa HDK Anuraga Gangga G Minh Xuan Do Thi DT Fitriani Fenny F Putri Hermanto Elvira Mustikawati EM Athoillah Muhammad M Andriani Vivin V Ajiningrum Purity Sabila PS Wu Yung-Fu YF Lee Kuen-Haur KH Chuang Jian-Ying JY Wang Chih-Yang CY Kao Tzu-Jen TJ

Diagnostics (Basel, Switzerland) 20211127 12

The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the <i>PSMA</i> genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBio ...[more]

PMID: 34943457

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Project description:BackgroundBreast cancer (BC) is one of the most lethal malignant tumors and the leading cause of cancer-related death worldwide. Although early diagnostic techniques for BC have been well developed, 40% of cases are still diagnosed at the advanced stage, while for BC patients with distant metastases, the 5-year survival rate is usually lower than 30%. The Snail family, generally regarded as transcriptional repressors, has been indicated to be an essential prognostic factor in malignant tumors. However, limited data exist on public databases concerning the prognostic value of individual Snail family members in BC, especially SNAI3.MethodsData from public databases including cBioPortal for Cancer Genomics, Gene Expression Omnibus, UCSC Xena Browser, and Human Protein Atlas (HPA) were downloaded. Based on the Kaplan¬-Meier plotter platform, correlation of the three members of the Snail family and prognosis in BC were analyzed. Individual Snail family members and their co-expressed genes were respectively enriched on different pathways and biological processes via the functional enrichment analysis (FunRich) tool.ResultsHigh SNAI1 mRNA expression was associated with shorter distant metastasis-free survival (DMFS) in all BC patients regardless of PAM50 subtype. Conversely, high SNAI3 mRNA expression was associated with longer DMFS. Although the presence of SNAI2 expression was significantly associated with DMFS in the whole cohort, no significant correlation was found in patients with luminal A or HER2 subtype. For patients with the most diverse clinicopathological features, high SNAI1 expression was associated with poor survival, with the converse being true for SNAI3. However, the impact on prognosis of patients with different clinicopathological features produced by SNAI2 expression was inconclusive. Furthermore, we discovered that SNAI1 or SNAI2 and their co-expressed genes frequently enriched receptor tyrosine kinase (RTK) signaling and integrin-related pathways which mainly functioned on epithelial-mesenchymal transition and were further involved in several processes of signal transduction and cell communication. Furthermore, as SNAI3, along with its co-expressed genes, enriched immune-related pathways, it may thus play a role in mediating the immune system.ConclusionsOur analysis revealed that SNAI1 mRNA expression may potentially be a negative prognostic factor, whereas SNAI3 mRNA was associated with positive prognosis in BC. Therefore, the assessment of SNAI1 and SNAI3 expression may be valuable for predicting prognosis in BC patients.

Dataset Information

Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer.

Publications

Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer.

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