Mohammad Hadi Saeed Modaghegh, Hamid Tanzadehpanah, Mohammad Mahdi Kamyar, Hamed Manoochehri, Mohsen Sheykhhasan, Fatemeh Forouzanfar, Reihaneh Alsadat Mahmoudian, Elham Lotfian, Hanie Mahaki
The lymphatic system, crucial for tissue fluid balance and immune surveillance, can be severely impacted by disorders that hinder its activities. Lymphatic malformations (LMs) are caused by fluid accumulation in tissues owing to defects in lymphatic channel formation, the obstruction of lymphatic vessels or injury to lymphatic tissues. Somatic mutations, varying in symptoms based on lesions' location and size, provide insights into their molecular pathogenesis by identifying LMs' genetic causes. In this review, we collected the most recent findings about the role of genetic and inflammatory biomarkers in LMs that control the formation of these malformations. A thorough evaluation of the literature from 2000 to the present was conducted using the PubMed and Google Scholar databases. Although it is obvious that the vascular endothelial growth factor receptor 3 mutation accounts for a significant proportion of LM patients, several mutations in other genes thought to be linked to LM have also been discovered. Also, inflammatory mediators like interleukin-6, interleukin-8, tumor necrosis factor-alpha and mammalian target of rapamycin are the most commonly associated biomarkers with LM. Understanding the mutations and genes expression responsible for the abnormalities in lymphatic endothelial cells could lead to novel therapeutic strategies based on molecular pathways.
{"title":"The role of key biomarkers in lymphatic malformation: An updated review","authors":"Mohammad Hadi Saeed Modaghegh, Hamid Tanzadehpanah, Mohammad Mahdi Kamyar, Hamed Manoochehri, Mohsen Sheykhhasan, Fatemeh Forouzanfar, Reihaneh Alsadat Mahmoudian, Elham Lotfian, Hanie Mahaki","doi":"10.1002/jgm.3665","DOIUrl":"10.1002/jgm.3665","url":null,"abstract":"<p>The lymphatic system, crucial for tissue fluid balance and immune surveillance, can be severely impacted by disorders that hinder its activities. Lymphatic malformations (LMs) are caused by fluid accumulation in tissues owing to defects in lymphatic channel formation, the obstruction of lymphatic vessels or injury to lymphatic tissues. Somatic mutations, varying in symptoms based on lesions' location and size, provide insights into their molecular pathogenesis by identifying LMs' genetic causes. In this review, we collected the most recent findings about the role of genetic and inflammatory biomarkers in LMs that control the formation of these malformations. A thorough evaluation of the literature from 2000 to the present was conducted using the PubMed and Google Scholar databases. Although it is obvious that the vascular endothelial growth factor receptor 3 mutation accounts for a significant proportion of LM patients, several mutations in other genes thought to be linked to LM have also been discovered. Also, inflammatory mediators like interleukin-6, interleukin-8, tumor necrosis factor-alpha and mammalian target of rapamycin are the most commonly associated biomarkers with LM. Understanding the mutations and genes expression responsible for the abnormalities in lymphatic endothelial cells could lead to novel therapeutic strategies based on molecular pathways.</p>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139906969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<div> <section> <h3> Background</h3> <p>Preeclampsia, a severe pregnancy syndrome, is widely accepted divided into early- and late-onset preeclampsia (EOPE and LOPE) based on the onset time of preeclampsia, with distinct pathophysiological origins. However, the molecular mechanism especially immune-related mechanisms for EOPE and LOPE is currently obscure. In the present study, we focused on placental immune alterations between EOPE and LOPE and search for immune-related biomarkers that could potentially serve as potential therapeutic targets through bioinformatic analysis.</p> </section> <section> <h3> Methods</h3> <p>The gene expression profiling data was obtained from the Gene Expression Omnibus database. ESTIMATE algorithm and Gene Set Enrichment Analysis were employed to evaluate the immune status. The intersection of differentially expressed genes in GSE74341 series and immune-related genes set screened differentially expressed immune-related genes. Protein–protein interaction network and random forest were used to identify hub genes with a validation by a quantitative real-time PCR. Kyoto Encyclopedia of Genes and Genomes pathways, Gene Ontology and gene set variation analysis were utilized to conduct biological function and pathway enrichment analyses. Single-sample gene set enrichment analysis and CIBERSORTx tools were employed to calculate the immune cell infiltration score. Correlation analyses were evaluated by Pearson correlation analysis. Hub genes-miRNA network was performed by the NetworkAnalyst online tool.</p> </section> <section> <h3> Results</h3> <p>Immune score and stromal score were all lower in EOPE samples. The immune system-related gene set was significantly downregulated in EOPE compared to LOPE samples. Four hub differentially expressed immune-related genes (<i>IL15</i>, <i>GZMB</i>, <i>IL1B</i> and <i>CXCL12</i>) were identified based on a protein–protein interaction network and random forest. Quantitative real-time polymerase chain reaction validated the lower expression levels of four hub genes in EOPE compared to LOPE samples. Immune cell infiltration analysis found that innate and adaptive immune cells were apparent lacking in EOPE samples compared to LOPE samples. Cytokine-cytokine receptor, para-inflammation, major histocompatibility complex class I and T cell co-stimulation pathways were significantly deficient and highly correlated with hub genes. We constructed a hub genes-miRNA regulatory network, revealing the correlation between hub genes and hsa-miR-374a-5p, hsa-miR-203a-3p, hsa-miR-128-3p, hsa-miR-155-3p, hsa-miR-129-2-3p and hsa-miR-7-5p.</p> </section> <section> <h3> Conclusions</h3> <p>
{"title":"Comparison of immune-related gene signatures and immune infiltration features in early- and late-onset preeclampsia","authors":"Quanfeng Wu, Xiang Ying, Weiwei Yu, Huanxi Li, Wei Wei, Xueyan Lin, Meilin Yang, Xueqin Zhang","doi":"10.1002/jgm.3676","DOIUrl":"10.1002/jgm.3676","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Preeclampsia, a severe pregnancy syndrome, is widely accepted divided into early- and late-onset preeclampsia (EOPE and LOPE) based on the onset time of preeclampsia, with distinct pathophysiological origins. However, the molecular mechanism especially immune-related mechanisms for EOPE and LOPE is currently obscure. In the present study, we focused on placental immune alterations between EOPE and LOPE and search for immune-related biomarkers that could potentially serve as potential therapeutic targets through bioinformatic analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The gene expression profiling data was obtained from the Gene Expression Omnibus database. ESTIMATE algorithm and Gene Set Enrichment Analysis were employed to evaluate the immune status. The intersection of differentially expressed genes in GSE74341 series and immune-related genes set screened differentially expressed immune-related genes. Protein–protein interaction network and random forest were used to identify hub genes with a validation by a quantitative real-time PCR. Kyoto Encyclopedia of Genes and Genomes pathways, Gene Ontology and gene set variation analysis were utilized to conduct biological function and pathway enrichment analyses. Single-sample gene set enrichment analysis and CIBERSORTx tools were employed to calculate the immune cell infiltration score. Correlation analyses were evaluated by Pearson correlation analysis. Hub genes-miRNA network was performed by the NetworkAnalyst online tool.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Immune score and stromal score were all lower in EOPE samples. The immune system-related gene set was significantly downregulated in EOPE compared to LOPE samples. Four hub differentially expressed immune-related genes (<i>IL15</i>, <i>GZMB</i>, <i>IL1B</i> and <i>CXCL12</i>) were identified based on a protein–protein interaction network and random forest. Quantitative real-time polymerase chain reaction validated the lower expression levels of four hub genes in EOPE compared to LOPE samples. Immune cell infiltration analysis found that innate and adaptive immune cells were apparent lacking in EOPE samples compared to LOPE samples. Cytokine-cytokine receptor, para-inflammation, major histocompatibility complex class I and T cell co-stimulation pathways were significantly deficient and highly correlated with hub genes. We constructed a hub genes-miRNA regulatory network, revealing the correlation between hub genes and hsa-miR-374a-5p, hsa-miR-203a-3p, hsa-miR-128-3p, hsa-miR-155-3p, hsa-miR-129-2-3p and hsa-miR-7-5p.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139742823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Colorectal cancer (CRC) poses a significant health challenge. This study aims to investigate the prognostic value of a regulatory T cell (Treg)-related gene signature in CRC.
Methods
We extracted the gene expression and clinical data on CRC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The gene module related to Treg was identified by weighted gene co-expression network analysis (WGCNA). The genes in the significant module were filtered by univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. A riskscore model was established in terms of the key Treg-related genes. The reliability of this riskscore model was validated using the external GEO dataset. The association of riskscore with clinical features, mutation patterns and signaling pathways was explored.
Results
Genes in the blue module showed the strongest association with Tregs. After a series of filtering cycles, seven Treg-related key genes, GDE1, GSR, HSPB1, AOC2, TBX19, TAMM41 and TIGD6, were selected to construct a riskscore model. This model performed well in evaluating the patients’ survival in TCGA cohort, and was further affirmed by the GSE17536 validation cohort. For precise evaluation of the patients’ survival, we established a nomogram in light of riskscore and clinical factors. Patients in different risk groups had distinct clinical features, mutation patterns and signaling pathway activities. The expression of five key genes was significantly associated with Treg infiltration in the CRC samples.
Conclusion
We established a useful riskscore model in light of seven Treg-related genes. This model may contribute to the prognosis evaluation, direct tailored treatment, and hopefully improve clinical outcomes of the CRC patients.
{"title":"A Treg-related riskscore model may improve the prognosis evaluation of colorectal cancer","authors":"Qingqing Li, Yuxin Chu, Yi Yao, Qibin Song","doi":"10.1002/jgm.3668","DOIUrl":"10.1002/jgm.3668","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Colorectal cancer (CRC) poses a significant health challenge. This study aims to investigate the prognostic value of a regulatory T cell (Treg)-related gene signature in CRC.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We extracted the gene expression and clinical data on CRC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The gene module related to Treg was identified by weighted gene co-expression network analysis (WGCNA). The genes in the significant module were filtered by univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. A riskscore model was established in terms of the key Treg-related genes. The reliability of this riskscore model was validated using the external GEO dataset. The association of riskscore with clinical features, mutation patterns and signaling pathways was explored.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Genes in the blue module showed the strongest association with Tregs. After a series of filtering cycles, seven Treg-related key genes, GDE1, GSR, HSPB1, AOC2, TBX19, TAMM41 and TIGD6, were selected to construct a riskscore model. This model performed well in evaluating the patients’ survival in TCGA cohort, and was further affirmed by the GSE17536 validation cohort. For precise evaluation of the patients’ survival, we established a nomogram in light of riskscore and clinical factors. Patients in different risk groups had distinct clinical features, mutation patterns and signaling pathway activities. The expression of five key genes was significantly associated with Treg infiltration in the CRC samples.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We established a useful riskscore model in light of seven Treg-related genes. This model may contribute to the prognosis evaluation, direct tailored treatment, and hopefully improve clinical outcomes of the CRC patients.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139718073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Previous studies have established a connection between Hashimoto’s thyroiditis (HT) and an increased risk of papillary thyroid carcinoma (PTC). However, the molecular mechanisms driving this association are not well understood. The long non-coding RNA (lncRNA) BRAF-activated non-coding RNA (BANCR) has been implicated in various cancers, suggesting a potential role in the HT-PTC linkage.
Methods
This study investigated the expression levels of BANCR in PTC and HT samples, compared to control tissues. We also examined the association between BANCR expression and clinicopathological features, including lymph node metastasis. Furthermore, we explored the molecular mechanisms of BANCR in PTC pathogenesis and its potential as a therapeutic target.
Results
BANCR expression was significantly lower in PTC samples than in controls, while it was moderately increased in HT samples. In PTC cases with concurrent HT, BANCR expression was markedly reduced compared to normal tissues. Our analysis revealed BANCR’s role as an oncogene in PTC, influencing various cancer-related signaling pathways. Interestingly, no significant correlation was found between BANCR expression and lymph node metastasis.
Conclusion
Our findings underscore the involvement of BANCR in the connection between HT and PTC. The distinct expression patterns of BANCR in PTC and HT, especially in PTC with concurrent HT, provide new insights into the molecular interplay between these conditions. This study opens avenues for the development of innovative diagnostic and therapeutic strategies targeting BANCR in PTC and HT.
{"title":"Interaction of BANCR in the relationship between Hashimoto’s thyroiditis and papillary thyroid carcinoma expression patterns and possible molecular mechanisms","authors":"Jiabo Zhang, Lingli Yao, Yu Guo","doi":"10.1002/jgm.3663","DOIUrl":"10.1002/jgm.3663","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Previous studies have established a connection between Hashimoto’s thyroiditis (HT) and an increased risk of papillary thyroid carcinoma (PTC). However, the molecular mechanisms driving this association are not well understood. The long non-coding RNA (lncRNA) BRAF-activated non-coding RNA (BANCR) has been implicated in various cancers, suggesting a potential role in the HT-PTC linkage.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study investigated the expression levels of BANCR in PTC and HT samples, compared to control tissues. We also examined the association between BANCR expression and clinicopathological features, including lymph node metastasis. Furthermore, we explored the molecular mechanisms of BANCR in PTC pathogenesis and its potential as a therapeutic target.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>BANCR expression was significantly lower in PTC samples than in controls, while it was moderately increased in HT samples. In PTC cases with concurrent HT, BANCR expression was markedly reduced compared to normal tissues. Our analysis revealed BANCR’s role as an oncogene in PTC, influencing various cancer-related signaling pathways. Interestingly, no significant correlation was found between BANCR expression and lymph node metastasis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our findings underscore the involvement of BANCR in the connection between HT and PTC. The distinct expression patterns of BANCR in PTC and HT, especially in PTC with concurrent HT, provide new insights into the molecular interplay between these conditions. This study opens avenues for the development of innovative diagnostic and therapeutic strategies targeting BANCR in PTC and HT.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139718074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qiuyun Yuan, Mengqian Mao, Xiaoqiang Xia, Wanchun Yang
Background
Head and neck squamous cell carcinoma (HNSCC) represents one of the most malignant cancers worldwide, with poor survival. Experimental evidence implies that glycolysis/hypoxia is associated with HNSCC. In this study, we aimed to construct a novel glycolysis-/hypoxia-related gene (GHRG) signature for survival prediction of HNSCC.
Methods
A multistage screening strategy was used to establish the GHRG prognostic model by univariate/least absolute shrinkage and selection operator (LASSO)/step multivariate Cox regressions from The Cancer Genome Atlas cohort. A nomogram was constructed to quantify the survival probability. Correlations between risk score and immune infiltration and chemotherapy sensitivity were explored.
Results
We established a 12-GHRG mRNA signature to predict the prognosis in HNSCC patients. Patients in the high-risk score group had a much worse prognosis. The predictive power of the model was validated by external HNSCC cohorts, and the model was identified as an independent factor for survival prediction. Immune infiltration analysis showed that the high-risk score group had an immunosuppressive microenvironment. Finally, the model was effective in predicting chemotherapeutic sensitivity.
Conclusions
Our study demonstrated that the GHRG model is a robust prognostic tool for survival prediction of HNSCC. Findings of this work provide novel insights for immune infiltration and chemotherapy of HNSCC, and may be applied clinically to guide therapeutic strategies.
{"title":"Clinical and prognostic significance analysis of glycolysis-related genes in HNSCC","authors":"Qiuyun Yuan, Mengqian Mao, Xiaoqiang Xia, Wanchun Yang","doi":"10.1002/jgm.3670","DOIUrl":"10.1002/jgm.3670","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Head and neck squamous cell carcinoma (HNSCC) represents one of the most malignant cancers worldwide, with poor survival. Experimental evidence implies that glycolysis/hypoxia is associated with HNSCC. In this study, we aimed to construct a novel glycolysis-/hypoxia-related gene (GHRG) signature for survival prediction of HNSCC.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A multistage screening strategy was used to establish the GHRG prognostic model by univariate/least absolute shrinkage and selection operator (LASSO)/step multivariate Cox regressions from The Cancer Genome Atlas cohort. A nomogram was constructed to quantify the survival probability. Correlations between risk score and immune infiltration and chemotherapy sensitivity were explored.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We established a 12-GHRG mRNA signature to predict the prognosis in HNSCC patients. Patients in the high-risk score group had a much worse prognosis. The predictive power of the model was validated by external HNSCC cohorts, and the model was identified as an independent factor for survival prediction. Immune infiltration analysis showed that the high-risk score group had an immunosuppressive microenvironment. Finally, the model was effective in predicting chemotherapeutic sensitivity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our study demonstrated that the GHRG model is a robust prognostic tool for survival prediction of HNSCC. Findings of this work provide novel insights for immune infiltration and chemotherapy of HNSCC, and may be applied clinically to guide therapeutic strategies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139713456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Proliferation, metabolism, tumor occurrence and development in gliomas are greatly influenced by RNA modifications. However, no research has integrated the four RNA methylation regulators of m6A, m1A, m5C and m7G in gliomas to analyze their relationship with glioma prognosis and intratumoral heterogeneity.
Methods
Based on three in-house single-cell RNA-sequencing (scRNA-seq) data, the glioma heterogeneity and characteristics of m6A/m1A/m5C/m7G-related regulators were elucidated. Based on publicly available bulk RNA-sequencing (RNA-seq) data, a risk-score system for predicting the overall survival (OS) for gliomas was established by three machine learning methods and multivariate Cox regression analysis, and validated in an independent cohort.
Results
Seven cell types were identified in gliomas by three scRNA-seq data, and 22 m6A/m1A/m5C/m7G-related regulators among the marker genes of different cell subtypes were discovered. Three m6A/m1A/m5C/m7G-related regulators were selected to construct prognostic risk-score model, including EIFA, NSUN6 and TET1. The high-risk patients showed higher immune checkpoint expression, higher tumor microenvironment scores, as well as higher tumor mutation burden and poorer prognosis compared with low-risk patients. Additionally, the area under the curve values of the risk score and nomogram were 0.833 and 0.922 for 3 year survival and 0.759 and 0.885 for 5 year survival for gliomas. EIF3A was significantly highly expressed in glioma tissues in our in-house RNA-sequencing data (p < 0.05).
Conclusion
These findings may contribute to further understanding of the role of m6A/m1A/m5C/m7G-related regulators in gliomas, and provide novel and reliable biomarkers for gliomas prognosis and treatment.
{"title":"Characterization of the m6A/m1A/m5C/m7G-related regulators on the prognosis and immune microenvironment of glioma by integrated analysis of scRNA-seq and bulk RNA-seq data","authors":"Longkun Yang, Zhicong Huang, Ying Deng, Xing Zhang, Zhonghua Lv, Hao Huang, Qian Sun, Hui Liu, Hongsheng Liang, Baochang He, Fulan Hu","doi":"10.1002/jgm.3666","DOIUrl":"https://doi.org/10.1002/jgm.3666","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Proliferation, metabolism, tumor occurrence and development in gliomas are greatly influenced by RNA modifications. However, no research has integrated the four RNA methylation regulators of m6A, m1A, m5C and m7G in gliomas to analyze their relationship with glioma prognosis and intratumoral heterogeneity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Based on three in-house single-cell RNA-sequencing (scRNA-seq) data, the glioma heterogeneity and characteristics of m6A/m1A/m5C/m7G-related regulators were elucidated. Based on publicly available bulk RNA-sequencing (RNA-seq) data, a risk-score system for predicting the overall survival (OS) for gliomas was established by three machine learning methods and multivariate Cox regression analysis, and validated in an independent cohort.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Seven cell types were identified in gliomas by three scRNA-seq data, and 22 m6A/m1A/m5C/m7G-related regulators among the marker genes of different cell subtypes were discovered. Three m6A/m1A/m5C/m7G-related regulators were selected to construct prognostic risk-score model, including <i>EIFA</i>, <i>NSUN6</i> and <i>TET1</i>. The high-risk patients showed higher immune checkpoint expression, higher tumor microenvironment scores, as well as higher tumor mutation burden and poorer prognosis compared with low-risk patients. Additionally, the area under the curve values of the risk score and nomogram were 0.833 and 0.922 for 3 year survival and 0.759 and 0.885 for 5 year survival for gliomas. <i>EIF3A</i> was significantly highly expressed in glioma tissues in our in-house RNA-sequencing data (<i>p</i> < 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>These findings may contribute to further understanding of the role of m6A/m1A/m5C/m7G-related regulators in gliomas, and provide novel and reliable biomarkers for gliomas prognosis and treatment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139700653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaoyu Li, Yunjie Jin, Jianwei Huang, Chu Feng, Xi Chen, Liang Zuo, Guyue Liu, Fei Chen, Jiashu Fan, Lin Fang
Background
Triple-negative breast cancer (TNBC) represents the most aggressive form of breast cancer. While the involvement of long non-coding RNA (lncRNA) in the progression of TNBC has been demonstrated, the role of Lnc00113 in TNBC remains unexplored. We aimed to explore the function of Lnc00113 in TNBC.
Methods
Expression levels and the clinical significance of Lnc00113 were assessed in The Cancer Genome Atlas (TCGA) database. The expression levels of Lnc00113 in TNBC tissues and cell lines were examined using qRT-PCR (quantitative Real-Time Polymerase chain reaction). The proliferation, apoptosis and invasion abilities were evaluated using CCK-8 (Cell Counting Kit-8), EdU (5-Ethynyl-2'-deoxyuridine), apoptosis and transwell assays following Lnc00113 knockdown/overexpression. Dual-luciferase and fluorescence in situ hybridization assays were employed to detect the correlation between Lnc00113, miR-107 and Nin-one binding protein (NOB-1).
Results
We identified significant upregulation of Lnc00113 in TNBC tissues and cell lines, with high Lnc00113 expression correlating with advanced pathological staging and poorer prognosis in the TCGA database. Functional assessments through knockdown/overexpression experiments revealed that Lnc00113 promoted TNBC cell proliferation, apoptosis and invasion. Fluorescence in situ hybridization experiments showed cytoplasmic localization of both Lnc00113 and NOB-1. Dual-luciferase assays demonstrated direct binding between Lnc00113 and miR-107, while miR-107 directly interacted with NOB-1. Mechanistically, our findings indicated that Lnc00113 promotes TNBC progression through the miR-107/NOB-1/MAPK signaling axis.
Conclusion
Lnc00113 emerges as a potential driver of TNBC growth and progression through modulation of the NOB-1/MAPK signaling axis, providing insights into diagnostic biomarkers and therapeutic targets for TNBC.
{"title":"Lnc00113 promotes triple-negative breast cancer progression via the NOB-1/MAPK signaling axis","authors":"Xiaoyu Li, Yunjie Jin, Jianwei Huang, Chu Feng, Xi Chen, Liang Zuo, Guyue Liu, Fei Chen, Jiashu Fan, Lin Fang","doi":"10.1002/jgm.3662","DOIUrl":"10.1002/jgm.3662","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Triple-negative breast cancer (TNBC) represents the most aggressive form of breast cancer. While the involvement of long non-coding RNA (lncRNA) in the progression of TNBC has been demonstrated, the role of Lnc00113 in TNBC remains unexplored. We aimed to explore the function of Lnc00113 in TNBC.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Expression levels and the clinical significance of Lnc00113 were assessed in The Cancer Genome Atlas (TCGA) database. The expression levels of Lnc00113 in TNBC tissues and cell lines were examined using qRT-PCR (quantitative Real-Time Polymerase chain reaction). The proliferation, apoptosis and invasion abilities were evaluated using CCK-8 (Cell Counting Kit-8), EdU (5-Ethynyl-2'-deoxyuridine), apoptosis and transwell assays following Lnc00113 knockdown/overexpression. Dual-luciferase and fluorescence <i>in situ</i> hybridization assays were employed to detect the correlation between Lnc00113, miR-107 and Nin-one binding protein (NOB-1).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified significant upregulation of Lnc00113 in TNBC tissues and cell lines, with high Lnc00113 expression correlating with advanced pathological staging and poorer prognosis in the TCGA database. Functional assessments through knockdown/overexpression experiments revealed that Lnc00113 promoted TNBC cell proliferation, apoptosis and invasion. Fluorescence <i>in situ</i> hybridization experiments showed cytoplasmic localization of both Lnc00113 and NOB-1. Dual-luciferase assays demonstrated direct binding between Lnc00113 and miR-107, while miR-107 directly interacted with NOB-1. Mechanistically, our findings indicated that Lnc00113 promotes TNBC progression through the miR-107/NOB-1/MAPK signaling axis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Lnc00113 emerges as a potential driver of TNBC growth and progression through modulation of the NOB-1/MAPK signaling axis, providing insights into diagnostic biomarkers and therapeutic targets for TNBC.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139666812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Long Xu, Renquan Ding, Shuxi Song, Junling Liu, Jingyu Li, Xing Ju, Baozhao Ju
Background
Aberrant activation of the phosphatidlinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway has been shown to play an important role in lung adenocarcinoma (LUAD). The effect of KRAS mutations, one of the important signatures of LUAD, on the PI3K/AKT/mTOR pathway in LUAD remains unclear.
Methods
The Seurat package and principal component analysis were used for cell categorization of single-cell RNA sequencing data of LUAD. The AUCell score was used to assess the activity of the PI3K/AKT/mTOR pathway. Meanwhile, using the gene expression profiles and mutation profiles in the The Cancer Genome Atlas dataset, LUAD patients were categorized into KRAS-mutant (KRAS-MT) and KRAS-wild-types (KRAS-WT), and the corresponding enrichment scores were calculated using gene set enrichment analysis analysis. Finally, the subpopulation of cells with the highest pathway activity was identified, the copy number variation profile of this subpopulation was inscribed using the inferCNV package and the CMap database was utilized to make predictions for drugs targeting this subpopulation.
Results
There is higher PI3K/AKT/mTOR pathway activity in LUAD epithelial cells with KRAS mutations, and high expression of KRAS, PIK3CA, AKT1 and PDPK1. In particular, we found significantly higher levels of pathway activity and associated gene expression in KRAS-MT than in KRAS-WT. We identified the highest pathway activity on a subpopulation of GRB2+ epithelial cells and the presence of amplified genes within its pathway. Finally, drugs were able to target GRB2+ epithelial cell subpopulations, such as wortmannin, palbociclib and angiogenesis inhibitor.
Conclusions
The present study provides a basic theory for the activation of the PI3K/AKT/mTOR signaling pathway as a result of KRAS mutations.
{"title":"Single-cell RNA sequencing reveals the mechanism of PI3K/AKT/mTOR signaling pathway activation in lung adenocarcinoma by KRAS mutation","authors":"Long Xu, Renquan Ding, Shuxi Song, Junling Liu, Jingyu Li, Xing Ju, Baozhao Ju","doi":"10.1002/jgm.3658","DOIUrl":"10.1002/jgm.3658","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Aberrant activation of the phosphatidlinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway has been shown to play an important role in lung adenocarcinoma (LUAD). The effect of KRAS mutations, one of the important signatures of LUAD, on the PI3K/AKT/mTOR pathway in LUAD remains unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The Seurat package and principal component analysis were used for cell categorization of single-cell RNA sequencing data of LUAD. The AUCell score was used to assess the activity of the PI3K/AKT/mTOR pathway. Meanwhile, using the gene expression profiles and mutation profiles in the The Cancer Genome Atlas dataset, LUAD patients were categorized into KRAS-mutant (KRAS-MT) and KRAS-wild-types (KRAS-WT), and the corresponding enrichment scores were calculated using gene set enrichment analysis analysis. Finally, the subpopulation of cells with the highest pathway activity was identified, the copy number variation profile of this subpopulation was inscribed using the inferCNV package and the CMap database was utilized to make predictions for drugs targeting this subpopulation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>There is higher PI3K/AKT/mTOR pathway activity in LUAD epithelial cells with KRAS mutations, and high expression of KRAS, PIK3CA, AKT1 and PDPK1. In particular, we found significantly higher levels of pathway activity and associated gene expression in KRAS-MT than in KRAS-WT. We identified the highest pathway activity on a subpopulation of GRB2<sup>+</sup> epithelial cells and the presence of amplified genes within its pathway. Finally, drugs were able to target GRB2<sup>+</sup> epithelial cell subpopulations, such as wortmannin, palbociclib and angiogenesis inhibitor.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The present study provides a basic theory for the activation of the PI3K/AKT/mTOR signaling pathway as a result of KRAS mutations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139558334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mingming Tang, Hao Wu, Huaiqin Zhang, Xinjiang Xu, Bin Jiang, Qingwen Chen, Yingze Wei, Hongyan Qian, Liang Han
<div> <section> <h3> Background</h3> <p>The present study aimed to explore the biological role and underlying mechanism of the long non-coding RNA actin filament-associated protein 1-antisense RNA1 (lncRNA AFAP1-AS1) in the progression of tongue squamous cell carcinoma (TSCC).</p> </section> <section> <h3> Methods</h3> <p>A quantitative reverse transcriptase-PCR (RT-qPCR) was conducted to assess relative levels of the miR-133a-5p, lncRNAs AFAP1-AS1 and zinc finger family member 2 (ZIC2) in TSCC cell lines and specimens, whereas ZIC2 protein levels were measured using western blotting. After modifying the levels of expression of lncRNA AFP1-AS1, miR-133a-5p and ZIC2 using lentivirus or plasmid transfection, we examined AKT/epithelial–mesenchymal transition signaling pathway alterations, in vivo carcinogenesis of TSCC in nude mice and in vitro malignant phenotypes. A dual-luciferase reporter assay was conducted to confirm the targeting relationship between ZIC2 and miR-133a-5p, as well as between miR-133a-5p and lncRNA AFAP1-AS1. Based on The Cancer Genome Atlas (TCGA) database, we additionally validated AFP1-AS1. The potential biological pathway for AFP1-AS1 was investigated using gene set enrichment analysis (GSEA). We also evaluated the clinical diagnostic capacities of AFP1-AS1 and clustered the most potential biomarkers with the Mfuzz expression pattern. Finally, we also made relevant drug predictions for AFP1-AS1.</p> </section> <section> <h3> Results</h3> <p>In TSCC cell lines and specimens, lncRNA AFAP1-AS1 was upregulated. ZIC2 was upregulated in TSCC cells as a result of lncRNA AFAP1-AS1 overexpression, which also promoted TSCC cell migration, invasion, viability, and proliferation. Via the microRNA sponge effect, it was found that lncRNA AFAP1-AS1 could upregulate ZIC2 by competitively inhibiting miR-133a-5p. Interestingly, knockdown of ZIC2 reversed the biological roles of lncRNA AFAP1-AS1 with respect to inducing malignant phenotypes in TSCC cells. In addition, in vivo overexpression of lncRNA AFAP1-AS1 triggered subcutaneous tumor growth in nude mice implanted with TSCC cells and upregulated ZIC2 in the tumors. The TCGA database findings revealed that AFAP1-AS1 was significantly upregulated in TSCC specimens and had good clinical diagnostic value. The results of GSEA showed that peroxisome proliferator-activated receptor signaling pathway was significantly correlated with low expression of AFP1-AS1. Finally, the results of drug prediction indicated that the group with high AFAP1-AS1 expression was more sensitive to docetaxel, AZD4547, AZD7762 and nilotinib.</p> </section> <section> <h3> Conclusions</h3> <p>The upregula
{"title":"Actin filament-associated protein 1-antisense RNA1 promotes the development and invasion of tongue squamous cell carcinoma via the AFAP1-AS1/miR-133a-5p/ZIC2 axis","authors":"Mingming Tang, Hao Wu, Huaiqin Zhang, Xinjiang Xu, Bin Jiang, Qingwen Chen, Yingze Wei, Hongyan Qian, Liang Han","doi":"10.1002/jgm.3654","DOIUrl":"10.1002/jgm.3654","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The present study aimed to explore the biological role and underlying mechanism of the long non-coding RNA actin filament-associated protein 1-antisense RNA1 (lncRNA AFAP1-AS1) in the progression of tongue squamous cell carcinoma (TSCC).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A quantitative reverse transcriptase-PCR (RT-qPCR) was conducted to assess relative levels of the miR-133a-5p, lncRNAs AFAP1-AS1 and zinc finger family member 2 (ZIC2) in TSCC cell lines and specimens, whereas ZIC2 protein levels were measured using western blotting. After modifying the levels of expression of lncRNA AFP1-AS1, miR-133a-5p and ZIC2 using lentivirus or plasmid transfection, we examined AKT/epithelial–mesenchymal transition signaling pathway alterations, in vivo carcinogenesis of TSCC in nude mice and in vitro malignant phenotypes. A dual-luciferase reporter assay was conducted to confirm the targeting relationship between ZIC2 and miR-133a-5p, as well as between miR-133a-5p and lncRNA AFAP1-AS1. Based on The Cancer Genome Atlas (TCGA) database, we additionally validated AFP1-AS1. The potential biological pathway for AFP1-AS1 was investigated using gene set enrichment analysis (GSEA). We also evaluated the clinical diagnostic capacities of AFP1-AS1 and clustered the most potential biomarkers with the Mfuzz expression pattern. Finally, we also made relevant drug predictions for AFP1-AS1.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In TSCC cell lines and specimens, lncRNA AFAP1-AS1 was upregulated. ZIC2 was upregulated in TSCC cells as a result of lncRNA AFAP1-AS1 overexpression, which also promoted TSCC cell migration, invasion, viability, and proliferation. Via the microRNA sponge effect, it was found that lncRNA AFAP1-AS1 could upregulate ZIC2 by competitively inhibiting miR-133a-5p. Interestingly, knockdown of ZIC2 reversed the biological roles of lncRNA AFAP1-AS1 with respect to inducing malignant phenotypes in TSCC cells. In addition, in vivo overexpression of lncRNA AFAP1-AS1 triggered subcutaneous tumor growth in nude mice implanted with TSCC cells and upregulated ZIC2 in the tumors. The TCGA database findings revealed that AFAP1-AS1 was significantly upregulated in TSCC specimens and had good clinical diagnostic value. The results of GSEA showed that peroxisome proliferator-activated receptor signaling pathway was significantly correlated with low expression of AFP1-AS1. Finally, the results of drug prediction indicated that the group with high AFAP1-AS1 expression was more sensitive to docetaxel, AZD4547, AZD7762 and nilotinib.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The upregula","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139517129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The progression and the metastatic potential of colorectal cancer (CRC) are intricately linked to the epithelial–mesenchymal transition (EMT) process. The present study harnesses the power of machine learning combined with multi-omics data to develop a risk stratification model anchored on EMT-associated genes. The aim is to facilitate personalized prognostic assessments in CRC. We utilized publicly accessible gene expression datasets to pinpoint EMT-associated genes, employing a CoxBoost algorithm to sift through these genes for prognostic significance. The resultant model, predicated on gene expression levels, underwent rigorous independent validation across various datasets. Our model demonstrated a robust capacity to segregate CRC patients into distinct high- and low-risk categories, each correlating with markedly different survival probabilities. Notably, the risk score emerged as an independent prognostic indicator for CRC. High-risk patients were characterized by an immunosuppressive tumor milieu and a heightened responsiveness to certain chemotherapeutic agents, underlining the model's potential in steering tailored oncological therapies. Moreover, our research unearthed a putative repressive interaction between the long non-coding RNA PVT1 and the EMT-associated genes TIMP1 and MMP1, offering new insights into the molecular intricacies of CRC. In essence, our research introduces a sophisticated risk model, leveraging machine learning and multi-omics insights, which accurately prognosticates outcomes for CRC patients, paving the way for more individualized and effective oncological treatment paradigms.
{"title":"Constructing a personalized prognostic risk model for colorectal cancer using machine learning and multi-omics approach based on epithelial–mesenchymal transition-related genes","authors":"Shuze Zhang, Wanli Fan, Dong He","doi":"10.1002/jgm.3660","DOIUrl":"https://doi.org/10.1002/jgm.3660","url":null,"abstract":"<p>The progression and the metastatic potential of colorectal cancer (CRC) are intricately linked to the epithelial–mesenchymal transition (EMT) process. The present study harnesses the power of machine learning combined with multi-omics data to develop a risk stratification model anchored on EMT-associated genes. The aim is to facilitate personalized prognostic assessments in CRC. We utilized publicly accessible gene expression datasets to pinpoint EMT-associated genes, employing a CoxBoost algorithm to sift through these genes for prognostic significance. The resultant model, predicated on gene expression levels, underwent rigorous independent validation across various datasets. Our model demonstrated a robust capacity to segregate CRC patients into distinct high- and low-risk categories, each correlating with markedly different survival probabilities. Notably, the risk score emerged as an independent prognostic indicator for CRC. High-risk patients were characterized by an immunosuppressive tumor milieu and a heightened responsiveness to certain chemotherapeutic agents, underlining the model's potential in steering tailored oncological therapies. Moreover, our research unearthed a putative repressive interaction between the long non-coding RNA PVT1 and the EMT-associated genes TIMP1 and MMP1, offering new insights into the molecular intricacies of CRC. In essence, our research introduces a sophisticated risk model, leveraging machine learning and multi-omics insights, which accurately prognosticates outcomes for CRC patients, paving the way for more individualized and effective oncological treatment paradigms.</p>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139480506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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