Prognostic and immunological potential of PPM1G in hepatocellular carcinoma

Lin, Yi-Ren; Yang, Wenjing; Yang, Guowang

doi:10.18632/aging.202964

Cited by 12 publications

(12 citation statements)

References 59 publications

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“…Preliminary evidence suggests that the anticancer effects of sorafenib in HCC patients are related to these mechanisms. e results of previous studies have confirmed that SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 play important roles in cancer progression [28][29][30][31][32][33][34][35][36][37][38][39]. SLC41A3 is a member of solute carrier family 41 and is involved in many cellular processes.…”

Section: Discussionmentioning

confidence: 77%

A Risk Model Based on Sorafenib-Response Target Genes Predicts the Prognosis of Patients with HCC

Liu

Zeng

et al. 2022

Journal of Oncology

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Sorafenib is used to treat digestive system tumors in patients who do not respond to or cannot tolerate surgery. However, the roles and inhibitory mechanisms of sorafenib against hepatocellular carcinoma (HCC) are unclear. Differentially expressed genes in tissues from responders and nonresponders to sorafenib were investigated using the HCC GSE109211 data set. Biological functions and mechanisms were studied using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The expression levels of differential expressed target genes were identified in HCC tissues, using The Cancer Genome Atlas database, and their prognostic and diagnostic values were explored using survival and receiver operating characteristic curve analysis. A nomogram and risk model of sorafenib-response target genes enabled the evaluation of the prognosis of patients with HCC. The relationship between risk scores and levels of infiltrating immune cells was visualized via correlation analysis. We identified 1620 sorafenib-response target genes involved in the PPAR signaling pathway, antigen processing and presentation, and ferroptosis. SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 were independent risk factors for a poor prognosis for patients with HCC and had diagnostic value. A risk model based on SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 expression showed that patients with HCC in the high-risk group had a worse prognosis. Consensus-clustering analysis (performed with K set to 2) distinguished two clusters (the cluster 1 and cluster 2 groups). Patients in cluster 1 survived significantly longer than those in cluster 2. The risk score correlated with the levels of T cells, cytotoxic lymphocytes, CD8+ T cells, macrophages, memory B cells, follicular helper T cells, and other immune cells. The high risk based on the sorafenib-response targets SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 represented the poor prognosis for patients with HCC and significantly correlated with the levels of immune infiltrating cells in HCC.

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Section: Discussionmentioning

confidence: 77%

A Risk Model Based on Sorafenib-Response Target Genes Predicts the Prognosis of Patients with HCC

Liu

Zeng

et al. 2022

Journal of Oncology

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“…PPM1G is an important member of PPM family, is an Mg2+ / Mn2 + dependent serine / threonine phosphatase [26]. Multiple studies have reported that PPM1G is involved in the dephosphorylation of a variety of histones and is related to a variety of cell biological processes, such as cell cycle regulation, immune response and so on [9]. And many studies have proved that PPM1G is related to pre -mRNA splicing [27], DNA damage response and tumorigenesis [28].…”

Section: Discussionmentioning

confidence: 99%

Prognostic and immunological potential of PPM1G in lung adenocarcinoma

Yin

Tang

et al. 2022

Preprint

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BackgroundLung cancer is one of the malignant tumors with the worst incidence rate and mortality, and the prognosis is very poor. PPM1G is a serine/threonine phosphatase，which is involved in the proliferation, invasion and metastasis of tumor cells. However, there are few reports on the role of PPM1G in lung adenocarcinoma (LUAD).MethodsIn this study, We used public data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to evaluate the expression of PPM1G in LUAD and the relationship between PPM1G expression and prognosis of patients with LUAD.Immunohistochemical staining of PPM1G in lung cancer tissues was detected by HPA database. The correlation between PPM1G and cancer immune signatures was analyzed by single sample gene set enrichment analysis (SSGSEA) on TCGA databases. Kaplan-Meier method was used for survival analysis. Univariate and multivariate Cox regression were used to analyze the prognosis. ResultsOur results showed that PPM1G is highly expressed in cancer tissues of LUAD. The high expression of PPM1G was related with poor clinical stage, T stage, N stage and overall survival in LUAD. We screened 29 genes related to PPM1G and closely related to the cell cycle of LUAD patients. The expression of PPM1G was positively correlated with immune cells TGD, Th2 cells, NK cd56dim cells, and was negatively correlated with B cells, Mast cells, pDC, T helper cells, Macrophages, T cells,CD8 T cells, Tcm, Tem, Neutrophils and TFH. PPM1G was positively correlated with immune detection points. ConclusionsIn conclusion, PPM1G may be involved in the control of lung cancer cell cycle and is associated with prognosis and immune infiltration in patients with LUAD.

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“…It is critical in the pathology of many diseases, especially cancer because it influences the diversity of proteins ( Liu et al, 2013 ). Therefore, PPM1G dysfunction may induce cancer progression by affecting pre-mRNA splicing, making it a hot spot in current research ( Sun et al, 2016 ; Lin et al, 2021 ). The mutation rate of PPM1G was 2.7%, and it overexpressed in HCC patients.…”

Section: Discussionmentioning

confidence: 99%

Identification and verification of a novel epigenetic-related gene signature for predicting the prognosis of hepatocellular carcinoma

et al. 2022

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Hepatocellular carcinoma (HCC) is a common malignant tumor with a poor prognosis. Epigenetic dysregulation is now considered to be related to hepatocarcinogenesis. However, it is unclear how epigenetic-related genes (ERGs) contribute to the prognosis of HCC. In this study, we used the TCGA database to identify prognostic ERGs that were differentially expressed in HCC patients. Then, using least absolute shrinkage and selection operator (LASSO) regression analysis, a six-gene signature was constructed, and patients were divided into high- and low-risk groups. Validation was performed on HCC patients from the ICGC database. Patients in the high-risk group had a significantly lower chance of survival than those in the low-risk group (p < 0.001 in both databases). The predictive ability of the signature was determined by the receiver operating characteristic (ROC) curve. The risk score was then shown to be an independent prognostic factor for the overall survival (OS) of HCC patients based on the results of univariate and multivariate analyses. We also created a practical nomogram combining the prognostic model with other clinical features. Moreover, functional enrichment analysis revealed that these genes are linked to tumor immunity. In conclusion, our findings showed that a novel six-gene signature related to epigenetics can accurately predict the occurrence and prognosis of HCC.

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Prognostic and immunological potential of PPM1G in hepatocellular carcinoma

Cited by 12 publications

References 59 publications

A Risk Model Based on Sorafenib-Response Target Genes Predicts the Prognosis of Patients with HCC

A Risk Model Based on Sorafenib-Response Target Genes Predicts the Prognosis of Patients with HCC

Prognostic and immunological potential of PPM1G in lung adenocarcinoma

Identification and verification of a novel epigenetic-related gene signature for predicting the prognosis of hepatocellular carcinoma

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