The microRNA212 regulated PEA15 promotes ovarian cancer progression by inhibiting of apoptosis

Luo, Yang; Fang, C; Jin, Lan; Ding, Huafeng; Lyu, Yuanyuan; Ni, Guantai

doi:10.7150/jca.32886

Cited by 7 publications

(5 citation statements)

References 33 publications

(32 reference statements)

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“…Proliferation and Apoptosis Adaptor Protein 15 (PEA15) consists of 130 amino acid residues and performs various antiapoptotic functions. It is also involved in the development of tumours, such as breast cancer, thyroid cancer, and colon cancer tumours 35 . In HCC, PEA15 has been found to promote HCC cell migration and increase HCC cell resistance to sorafenib 36 .…”

Section: Discussionmentioning

confidence: 99%

Identification and verification of a prognostic autophagy-related gene signature in hepatocellular carcinoma

Ma,

Chen,

Liu

et al. 2024

Sci Rep

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This study aimed to investigate the potential of autophagy-related genes (ATGs) as a prognostic signature for HCC and explore their relationships with immune cells and immune checkpoint molecules. A total of 483 samples were collected from the GEO database (n = 115) and The Cancer Genome Atlas (TCGA) database (n = 368). The GEO dataset was used as the training set, while the TCGA dataset was used for validation. The list of ATGs was obtained from the human autophagy database (HADB). Using Cox regression and LASSO regression methods, a prognostic signature based on ATGs was established. The independent use of this prognostic signature was tested through subgroup analysis. Additionally, the predictive value of this signature for immune-related profiles was explored. Following selection through univariate Cox regression analysis and iterative LASSO Cox analysis, a total of 11 ATGs were used in the GEO dataset to establish a prognostic signature that stratified patients into high- and low-risk groups based on survival. The robustness of this prognostic signature was validated using an external dataset. This signature remained a prognostic factor even in subgroups with different clinical features. Analysis of immune profiles revealed that patients in the high-risk group exhibited immunosuppressive states characterized by lower immune scores and ESTIMATE scores, greater tumour purity, and increased expression of immune checkpoint molecules. Furthermore, this signature was found to be correlated with the infiltration of different immune cell subpopulations. The results suggest that the ATG-based signature can be utilized to evaluate the prognosis of HCC patients and predict the immune status within the tumour microenvironment (TME). However, it is important to note that this study represents a preliminary attempt to use ATGs as prognostic indicators for HCC, and further validation is necessary to determine the predictive power of this signature.

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Section: Discussionmentioning

confidence: 99%

Identification and verification of a prognostic autophagy-related gene signature in hepatocellular carcinoma

Ma,

Chen,

Liu

et al. 2024

Sci Rep

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“…PEA15 is a 15 kDa multifunctional phosphoprotein involved in various biological processes, such as the proliferation and apoptosis of cancer cells. Studies have shown that microrNA212-regulated PEA15 promotes the progression of ovarian cancer by inhibiting cell apoptosis 33 . The proteins encoded by MAPK1 and MAPK3 are members of the MAP kinase family, and serine/threonine kinases are important components of the MAP kinase signal transduction pathway.…”

Section: Discussionmentioning

confidence: 99%

Construction and Validation of Protein Expression-related Prognostic Models in Clear Cell Renal Cell Carcinoma

Ma¹,

Sun²

2023

J. Cancer

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Objective: To construct a prognostic evaluation model for clear cell renal cell carcinoma (ccRCC) patients using bioinformatics method and to screen potential drugs for ccRCC . Methods: ccRCC RNA sequencing data, clinical data, and protein expression data were downloaded from the TCGA database. Univariate Cox and Lasso regression analyses were performed on the combined data to screen out the proteins related to the prognosis, and they were included in a multivariate Cox proportional hazard model. The patients were divided into high and low-risk groups for a survival difference analysis. The predictive power of the model was evaluated on the basis of overall survival, progression-free survival, independent prognostic, clinically relevant receiver operating characteristic (ROC) curve, C-index, principal component, and clinical data statistics analyses. GSEA enrichment and immune function correlation analyses were performed. The samples were divided into different subtypes based on the expression of the risk proteins, and survival analysis of the subtypes was performed. The risk-related protein and RNA sequencing data were analyzed to screen out sensitive drugs with significant differences between the high and low-risk groups. Results: A total of 469 ccRCC-related proteins were screened, of which 13 proteins with independent prognostic significance were screened by univariate Cox, Lasso, and multivariate Cox regression analyses to construct the prognostic model. The sensitivity and accuracy of the model in predicting the survival of patients with ccRCC were high (1 year: 0.811, 3 years: 0.783, 5 years: 0.777). The 13 proteins were closely related to immunity, and the model proteins were different between kidney and tumor tissues according to the HPA database. The samples were divided into three subtypes, and there were obvious clinical characteristics of the three subtypes in the grade and T, N and M stages. According to the IC50 values, CGP-60474, vinorelbine, doxorubicin, etoposide, FTI-277, JQ12, OSU-03012, pyrimethamine, and other drugs were more sensitive in the high-risk group. Conclusions: A prognostic model of protein expression in ccRCC was successfully constructed, which had good predictive ability for the prognosis of ccRCC patients. The ccRCC-related proteins in the model can be used as targets for studying the pathogenesis and targeted therapy.

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“…The utility of PDK1-pS241 was similar to that of MAPK-pT202Y204, showing beneficial effects for ccRCC patients. PEA-15 consists of 130 amino acid residues and has a special role in the regulation of the ERK/MAPK signaling pathway ( Sulzmaier et al, 2012 ; Tang et al, 2019 ) and the progression of a variety of tumors ( Dong et al, 2019 ; Jiang et al, 2019 ; Luo et al, 2020 ). Our study found that high expression of this protein may lead to tumor metastasis and high grade.…”

Section: Discussionmentioning

confidence: 99%

Identification of a Novel Protein-Based Signature to Improve Prognosis Prediction in Renal Clear Cell Carcinoma

Chu

Zhu

et al. 2021

Front. Mol. Biosci.

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BackgroundClear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney cancer, and its incidence and mortality are not optimistic. It is well known that tumor-related protein markers play an important role in cancer detection, prognosis prediction, or treatment selection, such as carcinoembryonic antigen (CEA), programmed cell death 1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and cytotoxic T lymphocyte antigen 4 (CTLA-4), so a comprehensive analysis was performed in this study to explore the prognostic value of protein expression in patients with ccRCC.Materials and MethodsProtein expression data were obtained from The Cancer Proteome Atlas (TCPA), and clinical information were downloaded from The Cancer Genome Atlas (TCGA). We selected 445 patients with complete information and then separated them into a training set and testing set. We performed univariate, least absolute shrinkage and selection operator (LASSO) Cox analyses to find prognosis-related proteins (PRPs) and constructed a protein signature. Then, we used stratified analysis to fully verify the prognostic significance of the prognostic-related protein signature score (PRPscore). Besides, we also explored the differences in immunotherapy response and immune cell infiltration level in high and low score groups. The consensus clustering analysis was also performed to identify potential cancer subgroups.ResultsFrom the training set, a total of 233 PRPs were selected, and a seven-protein signature was constructed, including ACC1, AR, MAPK, PDK1, PEA15, SYK, and BRAF. Based on the PRPscore, patients could be divided into two groups with significantly different overall survival rates. Univariate and multivariate Cox regression analyses proved that this signature was an independent prognostic factor for patients (P < 0.001). Moreover, the signature showed a high ability to distinguish prognostic outcomes among subgroups, and the low score group had a better prognosis (P < 0.001) and better immunotherapy response (P = 0.003) than the high score group.ConclusionWe constructed a novel protein signature with robust predictive power and high clinical value. This will help to guide the disease management and individualized treatment of ccRCC patients.

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The microRNA212 regulated PEA15 promotes ovarian cancer progression by inhibiting of apoptosis

Cited by 7 publications

References 33 publications

Identification and verification of a prognostic autophagy-related gene signature in hepatocellular carcinoma

Identification and verification of a prognostic autophagy-related gene signature in hepatocellular carcinoma

Construction and Validation of Protein Expression-related Prognostic Models in Clear Cell Renal Cell Carcinoma

Identification of a Novel Protein-Based Signature to Improve Prognosis Prediction in Renal Clear Cell Carcinoma

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