Pub Date : 2024-06-20DOI: 10.2174/0113892029300694240612081006
Qingqing Li, Yuxin Chu, Yi Yao, Qibin Song
Objective: This study aimed to investigate the frequently mutated genes in Gastric Cancer (GC), assess their association with Tumor Mutation Burden (TMB) and the patients’ survival, and identify the potential biomarkers for tailored therapy. Methods: Simple somatic mutation data of GC were collected from the TCGA and ICGC databases. The high-frequency mutated genes were identified from both datasets. The samples were initially dichotomized into wild-type and mutation groups based on the status of overlapping genes. TMB difference between the two groups was evaluated by the Mann-Whitney U-test. Survival difference between the two groups was compared by the Kaplan-Meier method with a log-rank test. The prognostic value of the target gene was assessed by the Cox proportional hazards model. The signaling pathways involved in FAT4 mutation were identified by Gene Set Enrichment Analysis (GSEA). The fractions of different tumor-infiltrating immune cells were calculated by the CIBERSORT algorithm. Results: 21 overlapping genes with frequent mutation were identified in both datasets. Mutation of these genes was significantly associated with higher TMB (P<0.05) in GC. The survival of the FAT4 mutation group was superior to the wild-type group. FAT4 mutation was also identified as an independent favorable prognostic factor for the GC patients. GSEA indicated that FAT4 mutation activated the signaling pathways involved in energy metabolism. Finally, CD4 memory-activated T cells, follicular helper T cells, and gamma delta T cells were significantly more enriched, while naïve B cells and regulatory T cells (Tregs) were significantly less enriched in the FAT4 mutation group (P<0.05). Conclusion: FAT4 mutation is relevant to TMB and favorable prognosis in GC, which may become a useful biomarker for immunotherapy of GC patients.
{"title":"FAT4 Mutation is Related to Tumor Mutation Burden and Favorable Prognosis in Gastric Cancer","authors":"Qingqing Li, Yuxin Chu, Yi Yao, Qibin Song","doi":"10.2174/0113892029300694240612081006","DOIUrl":"https://doi.org/10.2174/0113892029300694240612081006","url":null,"abstract":"Objective: This study aimed to investigate the frequently mutated genes in Gastric Cancer (GC), assess their association with Tumor Mutation Burden (TMB) and the patients’ survival, and identify the potential biomarkers for tailored therapy. Methods: Simple somatic mutation data of GC were collected from the TCGA and ICGC databases. The high-frequency mutated genes were identified from both datasets. The samples were initially dichotomized into wild-type and mutation groups based on the status of overlapping genes. TMB difference between the two groups was evaluated by the Mann-Whitney U-test. Survival difference between the two groups was compared by the Kaplan-Meier method with a log-rank test. The prognostic value of the target gene was assessed by the Cox proportional hazards model. The signaling pathways involved in FAT4 mutation were identified by Gene Set Enrichment Analysis (GSEA). The fractions of different tumor-infiltrating immune cells were calculated by the CIBERSORT algorithm. Results: 21 overlapping genes with frequent mutation were identified in both datasets. Mutation of these genes was significantly associated with higher TMB (P<0.05) in GC. The survival of the FAT4 mutation group was superior to the wild-type group. FAT4 mutation was also identified as an independent favorable prognostic factor for the GC patients. GSEA indicated that FAT4 mutation activated the signaling pathways involved in energy metabolism. Finally, CD4 memory-activated T cells, follicular helper T cells, and gamma delta T cells were significantly more enriched, while naïve B cells and regulatory T cells (Tregs) were significantly less enriched in the FAT4 mutation group (P<0.05). Conclusion: FAT4 mutation is relevant to TMB and favorable prognosis in GC, which may become a useful biomarker for immunotherapy of GC patients.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"18 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141509539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Mitochondria are semi-autonomous organelles present in several copies within most cells in the human body that are controlled by the precise collaboration of mitochondrial DNA (mtDNA) and nuclear DNA (nDNA) encoding mitochondrial proteins. They play important roles in numerous metabolic pathways, such as the synthesis of adenosine triphosphate (ATP), the predominant energy substrate of the cell generated through oxidative phosphorylation (OXPHOS), intracellular calcium homeostasis, metabolite biosynthesis, aging, cell cycles, and so forth. Previous studies revealed that dysfunction of these multi-functional organelles, which may arise due to mutations in either the nuclear or mitochondrial genome, leads to a diverse group of clinically and genetically heterogeneous disorders. These diseases include neurodegenerative and metabolic disorders as well as cardiac and skeletal myopathies in both adults and newborns. The plethora of phenotypes and defects displayed leads to challenges in the diagnosis and treatment of mitochondrial diseases. In this regard, the related literature proposed several diagnostic options, such as high throughput mitochondrial genomics and omics technologies, as well as numerous therapeutic options, such as pharmacological approaches, manipulating the mitochondrial genome, increasing the mitochondria content of the affected cells, and recently mitochondrial diseases transmission prevention. Therefore, the present article attempted to review the latest advances and challenges in diagnostic and therapeutic options for mitochondrial diseases.
{"title":"Emerging Multi-Omic Approaches to the Molecular Diagnosis of Mitochondrial Disease and Available Strategies for Treatment and Prevention","authors":"Faeze Khagani, Mahboube Hemmati, Masoumeh Ebrahimi, Arash Salmaninejad","doi":"10.2174/0113892029308327240612110334","DOIUrl":"https://doi.org/10.2174/0113892029308327240612110334","url":null,"abstract":": Mitochondria are semi-autonomous organelles present in several copies within most cells in the human body that are controlled by the precise collaboration of mitochondrial DNA (mtDNA) and nuclear DNA (nDNA) encoding mitochondrial proteins. They play important roles in numerous metabolic pathways, such as the synthesis of adenosine triphosphate (ATP), the predominant energy substrate of the cell generated through oxidative phosphorylation (OXPHOS), intracellular calcium homeostasis, metabolite biosynthesis, aging, cell cycles, and so forth. Previous studies revealed that dysfunction of these multi-functional organelles, which may arise due to mutations in either the nuclear or mitochondrial genome, leads to a diverse group of clinically and genetically heterogeneous disorders. These diseases include neurodegenerative and metabolic disorders as well as cardiac and skeletal myopathies in both adults and newborns. The plethora of phenotypes and defects displayed leads to challenges in the diagnosis and treatment of mitochondrial diseases. In this regard, the related literature proposed several diagnostic options, such as high throughput mitochondrial genomics and omics technologies, as well as numerous therapeutic options, such as pharmacological approaches, manipulating the mitochondrial genome, increasing the mitochondria content of the affected cells, and recently mitochondrial diseases transmission prevention. Therefore, the present article attempted to review the latest advances and challenges in diagnostic and therapeutic options for mitochondrial diseases.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"171 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141530070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-27DOI: 10.2174/0113892029301904240513045755
Chaeyoung Lee, Yeeun An
: Understanding the genetics of susceptibility to classical Hodgkin lymphoma (cHL) is considerably limited compared to other cancers due to the rare Hodgkin and Reed-Sternberg (HRS) tumor cells, which coexist with the predominant non-malignant microenvironment. This article offers insights into genetic abnormalities in cHL, as well as nucleotide variants and their associated target genes, elucidated through recent technological advancements. Oncogenomes in HRS cells highlight the survival and proliferation of these cells through hyperactive signaling in specific pathways (e.g., NF-kB) and their interplay with microenvironmental cells (e.g., CD4+ T cells). In contrast, the susceptibility genes identified from genome-wide association studies and expression quantitative trait locus analyses only vaguely implicate their potential roles in susceptibility to more general cancers. To pave the way for the era of precision oncology, more intensive efforts are imperative, employing the following strategies: exploring genetic heterogeneity by gender and cHL subtype, investigating colocalization with various types of expression quantitative trait loci, and leveraging single-cell analysis. These approaches provide valuable perspectives for unraveling the genetic complexities of cHL.
{"title":"Deciphering the Genetic Complexity of Classical Hodgkin Lymphoma: Insights and Effective Strategies","authors":"Chaeyoung Lee, Yeeun An","doi":"10.2174/0113892029301904240513045755","DOIUrl":"https://doi.org/10.2174/0113892029301904240513045755","url":null,"abstract":": Understanding the genetics of susceptibility to classical Hodgkin lymphoma (cHL) is considerably limited compared to other cancers due to the rare Hodgkin and Reed-Sternberg (HRS) tumor cells, which coexist with the predominant non-malignant microenvironment. This article offers insights into genetic abnormalities in cHL, as well as nucleotide variants and their associated target genes, elucidated through recent technological advancements. Oncogenomes in HRS cells highlight the survival and proliferation of these cells through hyperactive signaling in specific pathways (e.g., NF-kB) and their interplay with microenvironmental cells (e.g., CD4+ T cells). In contrast, the susceptibility genes identified from genome-wide association studies and expression quantitative trait locus analyses only vaguely implicate their potential roles in susceptibility to more general cancers. To pave the way for the era of precision oncology, more intensive efforts are imperative, employing the following strategies: exploring genetic heterogeneity by gender and cHL subtype, investigating colocalization with various types of expression quantitative trait loci, and leveraging single-cell analysis. These approaches provide valuable perspectives for unraveling the genetic complexities of cHL.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"48 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141168800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-10DOI: 10.2174/0113892029293113240427065916
Márcio Fabrício Falcão de Paula Filho, Lara Luisa Lopes Chrisóstomo, Isaac Farias Cansanção
Background: Human papillomavirus (HPV) is the main risk factor for the development of squamous cell cervical cancer, and E6 oncoprotein and E7 oncoprotein are important components of the viral genome and its oncogenic potential. It is known that different viral variants of HPV16 have different pathology and impact on the development of neoplasia, although few studies have been performed on South American variants. Objective: Therefore, the present study aimed to analyze in silico the genomic diversity of HPV16 in 20 complete genome variants of South America in the National Center for Biotechnology Information (NCBI) database. Methods: We performed a descriptive study to characterize the polymorphic regions of the E6 and E7 genes in HPV16 variants, using software for genomic data and single nucleotide polymorphism (SNP) analysis and others for phylogenetic analysis. Results: The variants analyzed included six SNPs linked to cancer (A131G, G145T, C335T, T350G, C712A, and T732C) and significant variation (798 nucleotide substitutions). Despite this, the variants showed low genetic diversity. Eighteen variants of unclear significance (VUS) were identified, 10 of which were in the coding E6 regions and 8 in the coding E7 regions. The prevalence of lineage D variants is of concern due to their pathology in cervical cancer and requires more research and epidemiological vigilance regarding their prevalence in the population. Conclusion: study may contribute to future research on South American variants of HPV16, their pathogenicity, and the development of treatments.
{"title":"HPV16 Genomes: In Silico Analysis of E6 and E7 Oncoproteins in 20 South American Variants","authors":"Márcio Fabrício Falcão de Paula Filho, Lara Luisa Lopes Chrisóstomo, Isaac Farias Cansanção","doi":"10.2174/0113892029293113240427065916","DOIUrl":"https://doi.org/10.2174/0113892029293113240427065916","url":null,"abstract":"Background: Human papillomavirus (HPV) is the main risk factor for the development of squamous cell cervical cancer, and E6 oncoprotein and E7 oncoprotein are important components of the viral genome and its oncogenic potential. It is known that different viral variants of HPV16 have different pathology and impact on the development of neoplasia, although few studies have been performed on South American variants. Objective: Therefore, the present study aimed to analyze in silico the genomic diversity of HPV16 in 20 complete genome variants of South America in the National Center for Biotechnology Information (NCBI) database. Methods: We performed a descriptive study to characterize the polymorphic regions of the E6 and E7 genes in HPV16 variants, using software for genomic data and single nucleotide polymorphism (SNP) analysis and others for phylogenetic analysis. Results: The variants analyzed included six SNPs linked to cancer (A131G, G145T, C335T, T350G, C712A, and T732C) and significant variation (798 nucleotide substitutions). Despite this, the variants showed low genetic diversity. Eighteen variants of unclear significance (VUS) were identified, 10 of which were in the coding E6 regions and 8 in the coding E7 regions. The prevalence of lineage D variants is of concern due to their pathology in cervical cancer and requires more research and epidemiological vigilance regarding their prevalence in the population. Conclusion: study may contribute to future research on South American variants of HPV16, their pathogenicity, and the development of treatments.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"15 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140931828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: The fastest way to significantly change the composition of a population is through admixture, an evolutionary mechanism. In animal breeding history, genetic admixture has provided both short-term and long-term advantages by utilizing the phenomenon of complementarity and heterosis in several traits and genetic diversity, respectively. The traditional method of admixture analysis by pedigree records has now been replaced greatly by genome-wide marker data that enables more precise estimations. Among these markers, SNPs have been the popular choice since they are cost-effective, not so laborious, and automation of genotyping is easy. Certain markers can suggest the possibility of a population's origin from a sample of DNA where the source individual is unknown or unwilling to disclose their lineage, which are called Ancestry-Informative Markers (AIMs). Revealing admixture level at the locus-specific level is termed as local ancestry and can be exploited to identify signs of recent selective response and can account for genetic drift. Considering the importance of genetic admixture and local ancestry, in this mini-review, both concepts are illustrated, encompassing basics, their estimation/identification methods, tools/- software used and their applications.
:掺杂是一种进化机制，是显著改变种群组成的最快方法。在动物育种史上，基因掺杂分别利用了若干性状和遗传多样性的互补性和异质性现象，提供了短期和长期的优势。目前，通过血统记录进行混杂分析的传统方法已被全基因组标记数据大大取代，从而可以进行更精确的估计。在这些标记中，SNP 因其成本效益高、不太费力、基因分型自动化容易而成为热门选择。某些标记物可以从来源不明或不愿透露血统的 DNA 样本中提示人群起源的可能性，这些标记物被称为祖先信息标记物（AIM）。在特定位点水平上揭示掺杂水平被称为本地祖先，可用于识别近期选择性反应的迹象，并解释遗传漂移。考虑到遗传混杂和地方祖先的重要性，本微型综述将阐述这两个概念，包括基础知识、估算/识别方法、所用工具/软件及其应用。
{"title":"Global and Local Ancestry and its Importance: A Mini-Review","authors":"Rangasai Chandra Goli, Kiyevi G. Chishi, Indrajit Ganguly, Sanjeev Singh, S.P. Dixit, Pallavi Rathi, Vikas Diwakar, Chandana Sree C, Omkar Maharudra Limbalkar, Nidhi Sukhija, K.K. Kanaka","doi":"10.2174/0113892029298909240426094055","DOIUrl":"https://doi.org/10.2174/0113892029298909240426094055","url":null,"abstract":": The fastest way to significantly change the composition of a population is through admixture, an evolutionary mechanism. In animal breeding history, genetic admixture has provided both short-term and long-term advantages by utilizing the phenomenon of complementarity and heterosis in several traits and genetic diversity, respectively. The traditional method of admixture analysis by pedigree records has now been replaced greatly by genome-wide marker data that enables more precise estimations. Among these markers, SNPs have been the popular choice since they are cost-effective, not so laborious, and automation of genotyping is easy. Certain markers can suggest the possibility of a population's origin from a sample of DNA where the source individual is unknown or unwilling to disclose their lineage, which are called Ancestry-Informative Markers (AIMs). Revealing admixture level at the locus-specific level is termed as local ancestry and can be exploited to identify signs of recent selective response and can account for genetic drift. Considering the importance of genetic admixture and local ancestry, in this mini-review, both concepts are illustrated, encompassing basics, their estimation/identification methods, tools/- software used and their applications.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"61 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140931827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Although the application of mesenchymal stem cells (MSCs) in engineered medicine, such as tissue regeneration, is well known, new evidence is emerging that shows that MSCs can also promote cancer progression, metastasis, and drug resistance. However, no large-scale cohort analysis of MSCs has been conducted to reveal their impact on the prognosis of cancer patients. Objective: We propose the MSC score as a novel surrogate for poor prognosis in pan-cancer Methods: We used single sample gene set enrichment analysis to quantify MSC-related genes into a signature score and identify the signature score as a potential independent prognostic marker for cancer using multivariate Cox regression analysis. TIDE algorithm and neural network were utilized to assess the predictive accuracy of MSC-related genes for immunotherapy. Results: MSC-related gene expression significantly differed between normal and tumor samples across the 33 cancer types. Cox regression analysis suggested the MSC score as an independent prognostic marker for kidney renal papillary cell carcinoma, mesothelioma, glioma, and stomach adenocarcinoma. The abundance of fibroblasts was also more representative of the MSC score than the stromal score. Our findings supported the combined use of the TIDE algorithm and neural network to predict the accuracy of MSC-related genes for immunotherapy. Conclusion: We comprehensively characterized the transcriptome, genome, and epigenetics of MSCs in pan-cancer and revealed the crosstalk of MSCs in the tumor microenvironment, especially with cancer-related fibroblasts. It is suggested that this may be one of the key sources of resistance to cancer immunotherapy.
{"title":"Integrated Analysis of Clinical Outcome of Mesenchymal Stem Cellrelated Genes in Pan-cancer","authors":"Mingzhe Jiang, Dantong Zhu, Dong Zhao, Yongye Liu, Jia Li, Zhendong Zheng","doi":"10.2174/0113892029291247240422060811","DOIUrl":"https://doi.org/10.2174/0113892029291247240422060811","url":null,"abstract":"Background: Although the application of mesenchymal stem cells (MSCs) in engineered medicine, such as tissue regeneration, is well known, new evidence is emerging that shows that MSCs can also promote cancer progression, metastasis, and drug resistance. However, no large-scale cohort analysis of MSCs has been conducted to reveal their impact on the prognosis of cancer patients. Objective: We propose the MSC score as a novel surrogate for poor prognosis in pan-cancer Methods: We used single sample gene set enrichment analysis to quantify MSC-related genes into a signature score and identify the signature score as a potential independent prognostic marker for cancer using multivariate Cox regression analysis. TIDE algorithm and neural network were utilized to assess the predictive accuracy of MSC-related genes for immunotherapy. Results: MSC-related gene expression significantly differed between normal and tumor samples across the 33 cancer types. Cox regression analysis suggested the MSC score as an independent prognostic marker for kidney renal papillary cell carcinoma, mesothelioma, glioma, and stomach adenocarcinoma. The abundance of fibroblasts was also more representative of the MSC score than the stromal score. Our findings supported the combined use of the TIDE algorithm and neural network to predict the accuracy of MSC-related genes for immunotherapy. Conclusion: We comprehensively characterized the transcriptome, genome, and epigenetics of MSCs in pan-cancer and revealed the crosstalk of MSCs in the tumor microenvironment, especially with cancer-related fibroblasts. It is suggested that this may be one of the key sources of resistance to cancer immunotherapy.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"76 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140811924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Chemically modified therapeutic mRNAs have gained momentum recently. In addition to commonly used modifications (e.g., pseudouridine), 5moU is considered a promising substitution for uridine in therapeutic mRNAs. Accurate identification of 5-methoxyuridine (5moU) would be crucial for the study and quality control of relevant in vitro-transcribed (IVT) mRNAs. However, current methods exhibit deficiencies in providing quantitative methodologies for detecting such modification. Utilizing the capabilities of Oxford nanopore direct RNA sequencing, in this study, we present NanoML-5moU, a machine-learning framework designed specifically for the read-level detection and quantification of 5moU modification for IVT data. Method: Nanopore direct RNA sequencing data from both 5moU-modified and unmodified control samples were collected. Subsequently, a comprehensive analysis and modeling of signal event characteristics (mean, median current intensities, standard deviations, and dwell times) were performed. Furthermore, classical machine learning algorithms, notably the Support Vector Machine (SVM), Random Forest (RF), and XGBoost were employed to discern 5moU modifications within NNUNN (where N represents A, C, U, or G) 5-mers. Result: Notably, the signal event attributes pertaining to each constituent base of the NNUNN 5-mers, in conjunction with the utilization of the XGBoost algorithm, exhibited remarkable performance levels (with a maximum AUROC of 0.9567 in the "AGTTC" reference 5-mer dataset and a minimum AUROC of 0.8113 in the "TGTGC" reference 5-mer dataset). This accomplishment markedly exceeded the efficacy of the prevailing background error comparison model (ELIGOs AUC 0.751 for site-level prediction). The model's performance was further validated through a series of curated datasets, which featured customized modification ratios designed to emulate broader data patterns, demonstrating its general applicability in quality control of IVT mRNA vaccines. The NanoML-5moU framework is publicly available on GitHub (https://github.com/JiayiLi21/Nano ML-5moU). Conclusion: NanoML-5moU enables accurate read-level profiling of 5moU modification with nanopore direct RNA-sequencing, which is a powerful tool specialized in unveiling signal patterns in in vitro-transcribed (IVT) mRNAs.
{"title":"Detection and Quantification of 5moU RNA Modification from Direct RNA Sequencing Data","authors":"Jiayi Li, Feiyang Sun, Kunyang He, Lin Zhang, Jia Meng, Daiyun Huang, Yuxin Zhang","doi":"10.2174/0113892029288843240402042529","DOIUrl":"https://doi.org/10.2174/0113892029288843240402042529","url":null,"abstract":"Background: Chemically modified therapeutic mRNAs have gained momentum recently. In addition to commonly used modifications (e.g., pseudouridine), 5moU is considered a promising substitution for uridine in therapeutic mRNAs. Accurate identification of 5-methoxyuridine (5moU) would be crucial for the study and quality control of relevant in vitro-transcribed (IVT) mRNAs. However, current methods exhibit deficiencies in providing quantitative methodologies for detecting such modification. Utilizing the capabilities of Oxford nanopore direct RNA sequencing, in this study, we present NanoML-5moU, a machine-learning framework designed specifically for the read-level detection and quantification of 5moU modification for IVT data. Method: Nanopore direct RNA sequencing data from both 5moU-modified and unmodified control samples were collected. Subsequently, a comprehensive analysis and modeling of signal event characteristics (mean, median current intensities, standard deviations, and dwell times) were performed. Furthermore, classical machine learning algorithms, notably the Support Vector Machine (SVM), Random Forest (RF), and XGBoost were employed to discern 5moU modifications within NNUNN (where N represents A, C, U, or G) 5-mers. Result: Notably, the signal event attributes pertaining to each constituent base of the NNUNN 5-mers, in conjunction with the utilization of the XGBoost algorithm, exhibited remarkable performance levels (with a maximum AUROC of 0.9567 in the \"AGTTC\" reference 5-mer dataset and a minimum AUROC of 0.8113 in the \"TGTGC\" reference 5-mer dataset). This accomplishment markedly exceeded the efficacy of the prevailing background error comparison model (ELIGOs AUC 0.751 for site-level prediction). The model's performance was further validated through a series of curated datasets, which featured customized modification ratios designed to emulate broader data patterns, demonstrating its general applicability in quality control of IVT mRNA vaccines. The NanoML-5moU framework is publicly available on GitHub (https://github.com/JiayiLi21/Nano ML-5moU). Conclusion: NanoML-5moU enables accurate read-level profiling of 5moU modification with nanopore direct RNA-sequencing, which is a powerful tool specialized in unveiling signal patterns in in vitro-transcribed (IVT) mRNAs.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"27 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.2174/0113892029296712240405053201
Rashid Mehmood
:: N6-methyladenosine (m6A) is an RNA modification wherein the N6-position of adenosine is methylated. It is one of the most prevalent internal modifications of RNA and regulates various aspects of RNA metabolism. M6A is deposited by m6A methyltransferases, removed by m6A demethylases, and recognized by reader proteins, which modulate splicing, export, translation, and stability of the modified mRNA. Recent evidence suggests that various classes of non-- coding RNAs (ncRNAs), including microRNAs (miRNAs), circular RNAs (circRNAs), and long con-coding RNAs (lncRNAs), are also targeted by this modification. Depending on the ncRNA species, m6A may affect the processing, stability, or localization of these molecules. The m6A-- modified ncRNAs are implicated in a number of diseases, including cancer. In this review, the author summarizes the role of m6A modification in the regulation and functions of ncRNAs in tumor development. Moreover, the potential applications in cancer prognosis and therapeutics are discussed.
{"title":"Ramifications of m6A Modification on ncRNAs in Cancer","authors":"Rashid Mehmood","doi":"10.2174/0113892029296712240405053201","DOIUrl":"https://doi.org/10.2174/0113892029296712240405053201","url":null,"abstract":":: N6-methyladenosine (m6A) is an RNA modification wherein the N6-position of adenosine is methylated. It is one of the most prevalent internal modifications of RNA and regulates various aspects of RNA metabolism. M6A is deposited by m6A methyltransferases, removed by m6A demethylases, and recognized by reader proteins, which modulate splicing, export, translation, and stability of the modified mRNA. Recent evidence suggests that various classes of non-- coding RNAs (ncRNAs), including microRNAs (miRNAs), circular RNAs (circRNAs), and long con-coding RNAs (lncRNAs), are also targeted by this modification. Depending on the ncRNA species, m6A may affect the processing, stability, or localization of these molecules. The m6A-- modified ncRNAs are implicated in a number of diseases, including cancer. In this review, the author summarizes the role of m6A modification in the regulation and functions of ncRNAs in tumor development. Moreover, the potential applications in cancer prognosis and therapeutics are discussed.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"4 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.2174/0113892029273121240401060228
Dan Li, Xulian Wan, Yu Yun, Yongkun Li, Weigang Duan
Background: Understanding organic functions at a molecular level is important for scientists to unveil the disease mechanism and to develop diagnostic or therapeutic methods. background: Understanding organic functions at a molecular level are important for scientists to unveil the mechanism of disease and to develop diagnostic or therapeutic methods. Aim: The present study tried to find genes selectively expressed in 11 rat organs, including the adrenal gland, brain, colon, duodenum, heart, ileum, kidney, liver, lung, spleen, and stomach. objective: Understanding organic functions at a molecular level are important for scientists to unveil the mechanism of disease and to develop diagnostic or therapeutic methods. The present study tried to find genes selectively expressed in 11 rat organs, including the adrenal gland, brain, colon, duodenum, heart, ileum, kidney, liver, lung, spleen, and stomach. Method: Three normal male Sprague-Dawley (SD) rats were anesthetized, their organs mentioned above were harvested, and RNA in the fresh organs was extracted. Purified RNA was reversely transcribed and sequenced using the Solexa high-throughput sequencing technique. The abundance of a gene was measured by the expected value of fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM). Genes in organs with the highest expression level were sought out and compared with their median value in organs. If a gene in the highest expressed organ was significantly different (p < 0.05) from that in the medianly expressed organ, accompanied by q value < 0.05, and accounted for more than 70% of the total abundance, the gene was assumed as the selective gene in the organ. Results & Discussion: The Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) pathways were enriched by the highest expressed genes. Based on the criterion, 1,406 selective genes were screened out, 1,283 of which were described in the gene bank and 123 of which were waiting to be described. KEGG and GO pathways in the organs were partly confirmed by the known understandings and a good portion of the pathways needed further investigation. Conclusion: The novel selective genes and organic functional pathways are useful for scientists to unveil the mechanisms of the organs at the molecular level, and the selective genes’ products are candidate disease markers for organs.
{"title":"Genes Selectively Expressed in Rat Organs","authors":"Dan Li, Xulian Wan, Yu Yun, Yongkun Li, Weigang Duan","doi":"10.2174/0113892029273121240401060228","DOIUrl":"https://doi.org/10.2174/0113892029273121240401060228","url":null,"abstract":"Background: Understanding organic functions at a molecular level is important for scientists to unveil the disease mechanism and to develop diagnostic or therapeutic methods. background: Understanding organic functions at a molecular level are important for scientists to unveil the mechanism of disease and to develop diagnostic or therapeutic methods. Aim: The present study tried to find genes selectively expressed in 11 rat organs, including the adrenal gland, brain, colon, duodenum, heart, ileum, kidney, liver, lung, spleen, and stomach. objective: Understanding organic functions at a molecular level are important for scientists to unveil the mechanism of disease and to develop diagnostic or therapeutic methods. The present study tried to find genes selectively expressed in 11 rat organs, including the adrenal gland, brain, colon, duodenum, heart, ileum, kidney, liver, lung, spleen, and stomach. Method: Three normal male Sprague-Dawley (SD) rats were anesthetized, their organs mentioned above were harvested, and RNA in the fresh organs was extracted. Purified RNA was reversely transcribed and sequenced using the Solexa high-throughput sequencing technique. The abundance of a gene was measured by the expected value of fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM). Genes in organs with the highest expression level were sought out and compared with their median value in organs. If a gene in the highest expressed organ was significantly different (p < 0.05) from that in the medianly expressed organ, accompanied by q value < 0.05, and accounted for more than 70% of the total abundance, the gene was assumed as the selective gene in the organ. Results & Discussion: The Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) pathways were enriched by the highest expressed genes. Based on the criterion, 1,406 selective genes were screened out, 1,283 of which were described in the gene bank and 123 of which were waiting to be described. KEGG and GO pathways in the organs were partly confirmed by the known understandings and a good portion of the pathways needed further investigation. Conclusion: The novel selective genes and organic functional pathways are useful for scientists to unveil the mechanisms of the organs at the molecular level, and the selective genes’ products are candidate disease markers for organs.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"38 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-04DOI: 10.2174/0113892029300247240325080421
Stefanos Roumeliotis, Maria Divani, Eleni Stamellou, Vassilios Liakopoulos
: Diabetic Kidney Disease (DKD) remains the leading cause of Chronic and End Stage Kidney Disease (ESKD) worldwide, with an increasing epidemiological burden. However, still, the disease awareness remains low, early diagnosis is difficult, and therapeutic management is ineffective. These might be attributed to the fact that DKD is a highly heterogeneous disease, with disparities and variability in clinical presentation and progression patterns. Besides environmental risk factors, genetic studies have emerged as a novel and promising tool in the field of DKD. Three decades ago, family studies first reported that inherited genetic factors might confer significant risk to DKD development and progression. During the past decade, genome-wide association studies (GWASs) screening the whole genome in large and multi-ethnic population-based cohorts identified genetic risk variants associated with traits defining DKD in both type 1 and 2 diabetes. Herein, we aim to summarize the existing data regarding the progress in the field of genomics in DKD, present how the revolution of GWAS expanded our understanding of pathophysiologic disease mechanisms and finally, suggest potential future directions.
{"title":"Genomics in Diabetic Kidney Disease: A 2024 Update","authors":"Stefanos Roumeliotis, Maria Divani, Eleni Stamellou, Vassilios Liakopoulos","doi":"10.2174/0113892029300247240325080421","DOIUrl":"https://doi.org/10.2174/0113892029300247240325080421","url":null,"abstract":": Diabetic Kidney Disease (DKD) remains the leading cause of Chronic and End Stage Kidney Disease (ESKD) worldwide, with an increasing epidemiological burden. However, still, the disease awareness remains low, early diagnosis is difficult, and therapeutic management is ineffective. These might be attributed to the fact that DKD is a highly heterogeneous disease, with disparities and variability in clinical presentation and progression patterns. Besides environmental risk factors, genetic studies have emerged as a novel and promising tool in the field of DKD. Three decades ago, family studies first reported that inherited genetic factors might confer significant risk to DKD development and progression. During the past decade, genome-wide association studies (GWASs) screening the whole genome in large and multi-ethnic population-based cohorts identified genetic risk variants associated with traits defining DKD in both type 1 and 2 diabetes. Herein, we aim to summarize the existing data regarding the progress in the field of genomics in DKD, present how the revolution of GWAS expanded our understanding of pathophysiologic disease mechanisms and finally, suggest potential future directions.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"69 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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