MUC16 facilitates cervical cancer progression via JAK2/STAT3 phosphorylation-mediated cyclooxygenase-2 expression

Shen, Hui; Guo, Meng; Wang, Lu; Cui, Xinyue

doi:10.1007/s13258-019-00885-9

Cited by 35 publications

(24 citation statements)

References 25 publications

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“…The top 30 most frequently mutated genes of these two cohorts were displayed in Figures 4A,B. Interestingly, TTN, PIK3CA, MUC4, KMT2C, and MUC16 were the top mutations in both cohorts, which were reported to regulate various tumor biological processes in CC (Xu et al, 2017;Jiang et al, 2018;Shen et al, 2020), indicating that they are less participated in the process of immune infiltration but mainly involved in tumorigenesis and progression. Besides, there appeared a larger percentage of mutated genes in the high immunity group comparing to the low one, suggesting patients with more gene mutation tended to have higher immune infiltration.…”

Section: Identification Of Dmgs In CC Patientsmentioning

confidence: 99%

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

Shen

2021

Front. Cell Dev. Biol.

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Tumor microenvironment (TME) is emerging as an essential part of cervical cancer (CC) tumorigenesis and development, becoming a hotspot of research these years. However, comprehending the specific composition of TME is still facing enormous challenges, especially the immune and stromal components. In this study, we downloaded the RNA-seq profiles and somatic mutation data of 309 CC cases from The Cancer Genome Atlas (TCGA) database, which were analyzed by integrative bioinformatical methods. Initially, ESTIMATE computational method was employed to calculate the amount of immune and stromal components. Then, based on the high- and low-immunity cohorts, we recognized the differentially expressed genes (DEGs) as well as the differentially mutated genes (DMGs). Additionally, we conducted an intersection analysis of DEGs and DMGs, ultimately determining an immune-related prognostic signature, GTPase, IMAP Family Member 4 (GIMAP4). Moreover, sequential analyses demonstrated that GIMAP4 was a protective factor in CC, positively correlated with the overall survival (OS) and negatively with distant metastasis. Besides, we utilized the Gene Set Enrichment Analysis (GSEA) to explore the enrichment-pathways in high and low-expression cohorts of GIMAP4. The results indicated that the genes of the high-expression cohort had a high enrichment in immune-related biological processes and metabolic activities in the low one. Furthermore, CIBERSORT analysis was applied to evaluate the proportion of tumor-infiltrating immune cells (TICs), illustrating that several activated TICs were strongly associated with GIMAP4 expression, which suggested that GIMAP4 had the potential to be an indicator for the immune state in TME of CC. Hence, GIMAP4 contributed to predicting the CC patients’ clinical outcomes, such as survival rate, distant metastasis and immunotherapy response. Moreover, GIMAP4 could serve as a promising biomarker for TME remodeling, suggesting the possible underlying mechanisms of tumorigenesis and CC progression, which may provide different therapeutic perceptions of CC, and therefore improve treatment.

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Section: Identification Of Dmgs In CC Patientsmentioning

confidence: 99%

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

Shen

2021

Front. Cell Dev. Biol.

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“…As mentioned earlier, ERO1L promoted the migration of lung cancer cell lines, and this promotion effect was achieved indirectly through the MUC16-C. The full-length MUC16 protein has a particularly high molecular weight, and it can promote the occurrence and development of many tumors 25,[34][35][36][37][38][39][40][41][42][43][44] . However, the full-length protein is usually cut into three functional fragments after synthesis 45 .…”

Section: Discussionmentioning

confidence: 99%

ERO1L promotes IL6/sIL6R signaling and regulates MUC16 expression to promote CA125 secretion and the metastasis of lung cancer cells

Lei

Zang

et al. 2020

Cell Death Dis

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The abnormal secretion of CA125, a classic tumor marker, is usually related to a poor prognosis in various tumors. Thus, this study aimed to explore the potential mechanisms that promote CA125 secretion in lung cancer. By querying the database, the gene endoplasmic reticulum oxidoreductase 1L (ERO1L) was identified and chosen as the research subject. The antibody chips were used to screen the lung cancer cell supernatant and found that the most obvious secreted protein was CA125. ERO1L was found to promote the secretion of IL6R by affecting the formation of disulfide bonds. IL6R bound to IL6 and triggered the activation of the NF-κB signaling pathway. Then, NF-κB bound to the promoter of MUC16, resulting in overexpression of MUC16. The extracellular segment of MUC16 was cleaved to form CA125, while the C terminus of MUC16 promoted the EMT phenotype and the release of IL6, forming a positive feedback pathway. In conclusion, ERO1L might affect the secretion of CA125 through the IL6 signaling pathway and form a positive feedback loop to further promote the development of lung cancer. This might expand the application scope of CA125 in lung cancer.

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“…Waterfall plot representing the mutant landscape of the top 30 in Fig 10. Interestingly, TTN [20], TP53 [21], MUC16 [22], and ARID1A [23] were the top mutations in both cohorts, which were involved in various biological processes. Besides, the frequencies of all mutated genes were higher in the high-risk group (96.74%) (Fig 10a) than in the low-risk group (84.75%) (Fig 10b), suggesting somatic mutation was positively correlated risk scores.…”

Section: Validation Of Prognostic Performance Of the Frgs Signature In Gcmentioning

confidence: 99%

Identification the ferroptosis-related gene signature in Gastric cancer based on weighted gene co-expression network analysis (WGCNA)

Wang¹,

Cheng²,

Chen³

et al. 2021

Preprint

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Background Ferroptosis is a mode of regulated cell death that depends on iron, plays pivotal roles in regulating various biological process in human cancers. However, the role of ferroptosis in Gastric cancer (GC) remains unclear. Methods A total of 2721 differentially expressed genes (DEGs) were filtered base on The Cancer Genome Atlas (TCGA) (n = 375) dataset. Gene modules were identified based on co-expression network analysis (WGCNA). Functional analysis was performed to explore the biological function. Lasso-penalized and univariate Cox regression (UCR) analysis, survival genes were screened out to construct a prognostic model, which validated by the GSE43292 dataset. Gene set enrichment analysis (GSEA) for prognostic index was performed. Finally, the correlations of ferroptosis and immune cells were assessed through the TIMER database. Results Compared to normal specimens, 1063 highly upregulated and 1658 downregulated genes respectively and their normal counterparts in GC specimens were screened. WGCNA analysis was used and identified 7 modules, of which, blue module with the most significant enrichment result was selected. By taking intersections of blue module and differentially expressed ferroptosis-related genes (DEFRGs), we got 23 common genes. Functional analysis was performed to explore the biological function of the interested genes, and with the consequences Lasso-penalized and univariate Cox regression (UCR) analysis, survival genes were screened out to construct a prognostic model based on 3 genes (SLC1A5, ANGPTL4, and CGAS), which could play a role in predicting the survival of GC patients. UCR and multivariate Cox regression (MCR) analysis revealed that the prognostic index could be used as independent prognostic indicators and validated using another GSE84437 dataset. Notably, patients in high-risk groups had higher levels of higher mutation frequencies such as TTN and TP53.Mechanistically. Gene set enrichment analysis (GSEA) unveiled several significant and pathways involved in GC. TIMER analysis demonstrated that risk score strongly correlated with Macrophage and CD4 + T cells infiltration. In addition, high- and low-risk group illustrated different distributions in different immune status. Conclusions In this study, a novel FRGs signature was built. It could accurately predict GC prognosis and pave the new way for diagnosis and therapy strategy. May reflect the status of tumor immune microenvironment.

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MUC16 facilitates cervical cancer progression via JAK2/STAT3 phosphorylation-mediated cyclooxygenase-2 expression

Cited by 35 publications

References 25 publications

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

ERO1L promotes IL6/sIL6R signaling and regulates MUC16 expression to promote CA125 secretion and the metastasis of lung cancer cells

Identification the ferroptosis-related gene signature in Gastric cancer based on weighted gene co-expression network analysis (WGCNA)

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