PSME2 identifies immune-hot tumors in breast cancer and associates with well therapeutic response to immunotherapy

Wu, Cen; Ren, Zhongzhou; Sun, Xiaofei; Shi, Jinqiao

doi:10.3389/fgene.2022.1071270

Cited by 3 publications

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Construction and validation of a hypoxia-related gene signature to predict the prognosis of breast cancer

Qiu,

Wang,

et al. 2024

BMC Cancer

View full text Add to dashboard Cite

Background Among the most common forms of cancer worldwide, breast cancer posed a serious threat to women. Recent research revealed a lack of oxygen, known as hypoxia, was crucial in forming breast cancer. This research aimed to create a robust signature with hypoxia-related genes to predict the prognosis of breast cancer patients. The function of hypoxia genes was further studied through cell line experiments. Materials and methods In the bioinformatic part, transcriptome and clinical information of breast cancer were obtained from The Cancer Genome Atlas(TCGA). Hypoxia-related genes were downloaded from the Genecards Platform. Differentially expressed hypoxia-related genes (DEHRGs) were identified. The TCGA filtered data was evenly split, ensuring a 1:1 distribution between the training and testing sets. Prognostic-related DEHRGs were identified through Cox regression. The signature was established through the training set. Then, it was validated using the test set and external validation set GSE131769 from Gene Expression Omnibus (GEO). The nomogram was created by incorporating the signature and clinicopathological characteristics. The predictive value of the nomogram was evaluated by C-index and receiver operating characteristiccurve. Immune microenvironment and mutation burden were also examined. In the experiment part, the function of the two most significant hypoxia-related genes were further explored by cell-line experiments. Results In the bioinformatic part, 141 up-regulated and 157 down-regulated DEHRGs were screened out. A prognostic signature was constructed containing nine hypoxia genes (ALOX15B, CA9, CD24, CHEK1, FOXM1, HOTAIR, KCNJ11, NEDD9, PSME2) in the training set. Low-risk patients exhibited a much more favorable prognosis than higher-risk ones (P < 0.001). The signature was double-validated in the test set and GSE131769 (P = 0.006 and P = 0.001). The nomogram showed excellent predictive value with 1-year OS AUC: 0.788, 3-year OS AUC: 0.783, and 5-year OS AUC: 0.817. Patients in the high-risk group had a higher tumor mutation burden when compared to the low-risk group. In the experiment part, the down-regulation of PSME2 inhibited cell growth ability and clone formation capability of breast cancer cells, while the down-regulation of KCNJ11 did not have any functions. Conclusion Based on 9 DEHRGs, a reliable signature was established through the bioinformatic method. It could accurately predict the prognosis of breast cancer patients. Cell line experiment indicated that PSME2 played a protective role. Summarily, we provided a new insight to predict the prognosis of breast cancer by hypoxia-related genes.

show abstract

Construction and validation of a hypoxia-related gene signature to predict the prognosis of breast cancer

Qiu,

Wang,

et al. 2024

BMC Cancer

View full text Add to dashboard Cite

show abstract

Construction and validation of a hypoxia-related gene signature to predict the prognosis of invasive ductal breast carcinoma

Qiu,

Wang,

et al. 2023

Preprint

View full text Add to dashboard Cite

Background: Invasive ductal carcinoma (IDC), the most common type of breast cancer, was known for its aggressive nature. Recent research revealeda lack of oxygen, known as hypoxia, wascrucial in forming breast cancer. This research aimed to create a robustsignature with hypoxia-related genes to predict the prognosis of IDC patients. The function of hypoxia genes was further studied through cell line experiments. Materials and Methods: In the bioinformatic part, transcriptome and clinical information of breast IDC were obtained from The Cancer Genome Atlas. Hypoxia-related genes were downloaded from the Genecards Platform. Differentially expressed hypoxia-related genes (DEHRGs) were identified. Training and test sets were defined with a 1:1 ratio. Prognostic-related DEHRGs were identified through Cox regression; then the signature was established and validated. The nomogram was created by incorporating the signature and clinicopathological characteristics. The predictive value of the nomogram was evaluated by C-index and receiver operating characteristic cure. Immune microenvironment and mutation burden were also examined. In the experiment part, the function of the two most significant hypoxia-related genes were further explored by cell-line experiments. Results: In the bioinformatic part, 37 up-regulated and 55 down-regulated DEHRGs were screened out. A prognostic signature was constructed containing nine hypoxia genes (ALOX15B, CA9, CD24, CHEK1, FOXM1, HOTAIR, KCNJ11, NEDD9, PSME2) in the training set. Low-risk patients exhibited a much more favorable prognosis tthan higher-risk ones(P<0.001). The signature was double-validated in the test set and GSE131769 (P=0.006 and P=0.001). The nomogram showed excellent predictive value with 1-year OS AUC: 0.788, 3-year OS AUC: 0.783, and 5-year OS AUC: 0.817. Patients in the high-risk group had a higher tumor mutation burden when compared to the low-risk group. In the experiment part, the down-regulation of PSME2 inhibited cell growth ability and clone formation capability of breast cancercells, while the down-regulation of KCNJ11 did not have any functions. Conclusion: Based on 9 DEHRGs, a reliable signature was established through the bioinformatic method. It could accurately predict the prognosis of breast IDC patients. Cell line experiment indicated that PSME2 played a protective role. Summarily, we provided a new insight to predict the prognosis of breast IDC by hypoxia-related genes.

show abstract

Comprehensive Analysis of PSME2 and Its Significant Role in Non- small cell lung cancer

Ma,

Jiang,

Han

et al. 2024

Preprint

View full text Add to dashboard Cite

Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer, but its mechanisms of occurrence and development remain incompletely understood. The proteasome activator complex subunit 2 (PSME2) is a member of the family of protease-activating subgenes and is strongly associated with the emergence of several cancer types. However, the role of PSME2 in NSCLC is unclear. In this study, we investigated the clinical significance and prognostic value of PSME2 expression in NSCLC progression. We utilized data from The Cancer Genome Atlas (TCGA) database for bioinformatic analyses. We carried out experimental validation at both the tissue and cellular levels. Gene set enrichment analysis (GSEA) and various databases, such as Kaplan-Meier Plotter (KM), STRING, Tumor Immune Estimation Resource (TIMER), TIMER2.0, were used to investigate the role of PSME2 in NSCLC. Statistical analysis was performed using R (v.4.3.1). Our findings revealed the predictive significance of PSME2 in NSCLC patients. PSME2 is highly expressed in pathological tissues and cell lines of NSCLC patients. PSME2 expression was associated with patient's age, sex, tumor stage, lymph node stage, pathological stage. GSEA analysis identified associations between PSME2 and extracellular matrix organization, as well as immune-related pathways. Immunological analysis revealed a positive correlation between the level of immune cell permeation, the activation of anti-tumor immune cycle stages, and the level of PSME2 expression. Identifying PSME2 as a novel biomarker for NSCLC could shed light on the promotion of NSCLC development by the immune environment.

show abstract

PSME2 identifies immune-hot tumors in breast cancer and associates with well therapeutic response to immunotherapy

Cited by 3 publications

References 39 publications

Construction and validation of a hypoxia-related gene signature to predict the prognosis of breast cancer

Construction and validation of a hypoxia-related gene signature to predict the prognosis of breast cancer

Construction and validation of a hypoxia-related gene signature to predict the prognosis of invasive ductal breast carcinoma

Comprehensive Analysis of PSME2 and Its Significant Role in Non- small cell lung cancer

Contact Info

Product

Resources

About