PDIA3 correlates with clinical malignant features and immune signature in human gliomas

Zhang, Hao; Zhou, Yulai; Cheng, Quan; Dai, Ziyu; Wang, Zeyu; Liu, Fangkun; Fan, Fan; Cui, Biqi; Cao, Hui

doi:10.18632/aging.103601

Cited by 36 publications

(28 citation statements)

References 56 publications

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“…In this study, we retrieved and downloaded 787 ER stress-related genes from the GeneCards website. Among them, 190 survival- 61 and DNM1L plays a regulatory role in the immune response of NKT cells to tumours. 62 The role of SHISA5 and SLN in cancers has not been previously studied.…”

Section: Discussionmentioning

confidence: 99%

Characterization of an endoplasmic reticulum stress‐related signature to evaluate immune features and predict prognosis in glioma

Zhang

Guan

Peng

et al. 2021

J Cellular Molecular Medi

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Glioma is the most prevalent primary brain tumour in adults. As well as being highly invasive, it is characterized by diffuse infiltration, fuzzy boundaries and aggressive proliferation. 1 With the development of molecular biological techniques, our understanding of the pathogenesis of glioma has greatly improved, and clinically, important genetic changes have been identified. In the revised classification of central nervous system (CNS) tumours proposed by the World Health Organization (WHO) in 2016, gliomas were classified based on a combination of histological findings and molecular findings, namely isocitrate dehydrogenase (IDH) mutations, 1p19q codeletion, H3 Lys27Met and RELA-fusion. 2 However, although the diagnosis and treatment of gliomas have been greatly improved, the outcome of glioma patients is still unfavourable, with a mortality rate of nearly 80% during the first year of diagnosis. 3 For glioblastomas (GBMs), median survival is only approximately 15 months. 4 Thus, there is an urgent need to improve the diagnosis and treatment of glioma.

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Section: Discussionmentioning

confidence: 99%

Characterization of an endoplasmic reticulum stress‐related signature to evaluate immune features and predict prognosis in glioma

Zhang

Guan

Peng

et al. 2021

J Cellular Molecular Medi

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“…System. Differential expressional genes (909 DEGs in total; the screen criteria was 0.677, which was automatically calculated by considering the mean and standard deviation of logFC) between clusters 1 and 2 were identified with P packages "limma" [29,30]. log FC � mean(|log FC|) + 2 * sd(|log FC).…”

Section: Construction Of the Scoringmentioning

confidence: 99%

“…e GO and KEGG analyses were analyzed by conducting the GSVA and the GSEA analysis, respectively [32,33].…”

Section: Potential Mechanisms Predictionmentioning

confidence: 99%

“…e Immune Infiltration of High-Score Group. Immunocytes such as invasive immune cells and stromal cells infiltrating the tumor microenvironment are thought to play an important role in tumor growth, progression, and drug resistance [33,34]. In the TCGA array-Agilent training data set, we used the estimate algorithm to calculate estimate score, immune score, purity score, and stromal score to explain immune cell and stromal cell infiltration situation.…”

Section: 5mentioning

confidence: 99%

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Ferroptosis-Related Gene Signature Promotes Ovarian Cancer by Influencing Immune Infiltration and Invasion

Yang

Huang

et al. 2021

Journal of Oncology

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Ovarian cancer is a kind of gynecological malignancy with high mortality. Ferroptosis is a new type of iron-dependent cell death characterized by the formation of lipid peroxides and excessive accumulation of reactive oxygen species. Studies have shown that ferroptosis modulates tumor genesis, progression, and invasion, including ovarian cancer. Based on the mRNA expression data from TCGA, we construct a scoring system using consensus clustering analysis, univariate Cox regression analysis, and least absolute selection operator. Then, we systematically evaluate the relationship between score and clinical characteristics of ovarian cancer. The result from the prediction of biofunction pathways shows that score serves as an independent prognostic marker for ovarian cancer and affects tumor progression by modulating tumor metastasis. Moreover, immunocytes such as activated CD4 T cell, activated CD8 T cell, regulatory T cells, macrophage, and stromal cells, including adipocytes, epithelial cells, and fibroblast infiltrate more in the tumor microenvironment in a high-score group, indicating ferroptosis can also affect tumor immune landscape. Critically, four potentially sensitive drugs, including staurosporine, epothilone B, DMOG, and HG6-64-1 based on the scores, are predicted, and DMOG is recognized as a novel targeted drug for ovarian cancer. In general, we construct the scoring system based on ferroptosis-related genes that can predict the prognosis of ovarian cancer patients and propose that ferroptosis may affect ovarian cancer progression by mediating tumor metastasis and immune landscape. Novel drugs to target ovarian cancer are also predicted.

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“…Immunotherapy, represented by anti-PD-1 therapy, has been regarded as a promising therapeutic option in melanoma and urothelial cancer (37)(38)(39)(40)(41). So far, clinical trials of immunotherapy have not demonstrated satisfactory results in glioma patients.…”

Section: Discussionmentioning

confidence: 99%

The Predictive Value of Monocytes in Immune Microenvironment and Prognosis of Glioma Patients Based on Machine Learning

Zhang

Dai

et al. 2021

Front. Immunol.

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Gliomas are primary malignant brain tumors. Monocytes have been proved to actively participate in tumor growth. Weighted gene co-expression network analysis was used to identify meaningful monocyte-related genes for clustering. Neural network and SVM were applied for validating clustering results. Somatic mutation and copy number variation were used for defining the features of identified clusters. Differentially expressed genes (DEGs) between the stratified groups after performing elastic regression and principal component analyses were used for the construction of risk scores. Monocytes were associated with glioma patients’ survival and exhibited high predictive value. The prognostic value of risk score in glioma was validated by the abundant expression of immune checkpoint and metabolic profile. Additionally, high risk score was positively associated with the expression of immunogenic and antigen presenting factors, which indicated high immune infiltration. A prognostic model based on risk score demonstrated high accuracy rate of receiver operating characteristic curves. Compared with previous studies, our research dissected functional roles of monocytes from large-scale analysis. Findings of our analyses strongly support an immune modulatory and prognostic role of monocytes in glioma progression. Notably, monocyte could be an effective predictor for therapy responses of glioma patients.

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PDIA3 correlates with clinical malignant features and immune signature in human gliomas

Cited by 36 publications

References 56 publications

Characterization of an endoplasmic reticulum stress‐related signature to evaluate immune features and predict prognosis in glioma

Characterization of an endoplasmic reticulum stress‐related signature to evaluate immune features and predict prognosis in glioma

Ferroptosis-Related Gene Signature Promotes Ovarian Cancer by Influencing Immune Infiltration and Invasion

The Predictive Value of Monocytes in Immune Microenvironment and Prognosis of Glioma Patients Based on Machine Learning

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