Introduction: Nicotine degradation is a new strategy to block nicotine-induced pathology. The potential of human microbiota to degrade nicotine has not been explored. Aims: This study aimed to uncover the genomic potentials of human microbiota to degrade nicotine. Method: To address this issue, we performed a systematic annotation of Nicotine-Degrading Enzymes (NDEs) from genomes and metagenomes of human microbiota. A total of 26,295 genomes and 1,596 metagenomes for human microbiota were downloaded from public databases and five types of NDEs were annotated with a custom pipeline. We found 959 NdhB, 785 NdhL, 987 NicX, three NicA1, and three NicA2 homologs. Results: Genomic classification revealed that six phylum-level taxa, including Proteobacteria, Firmicutes, Firmicutes_A, Bacteroidota, Actinobacteriota, and Chloroflexota, can produce NDEs, with Proteobacteria encoding all five types of NDEs studied. Analysis of NicX prevalence revealed differences among body sites. NicX homologs were found in gut and oral samples with a high prevalence but not found in lung samples. NicX was found in samples from both smokers and non-smokers, though the prevalence might be different.
{"title":"Genomic and Metagenomic Insights into the Distribution of Nicotine-Degrading Enzymes in Human Microbiota","authors":"Ying Guan, Zhouhai Zhu, Qiyuan Peng, Meng Li, Xuan Li, Jia-Wei Yang, Yan-Hong Lu, Meng Wang, Bin-Bin Xie","doi":"10.2174/0113892029302230240319042208","DOIUrl":"https://doi.org/10.2174/0113892029302230240319042208","url":null,"abstract":"Introduction: Nicotine degradation is a new strategy to block nicotine-induced pathology. The potential of human microbiota to degrade nicotine has not been explored. Aims: This study aimed to uncover the genomic potentials of human microbiota to degrade nicotine. Method: To address this issue, we performed a systematic annotation of Nicotine-Degrading Enzymes (NDEs) from genomes and metagenomes of human microbiota. A total of 26,295 genomes and 1,596 metagenomes for human microbiota were downloaded from public databases and five types of NDEs were annotated with a custom pipeline. We found 959 NdhB, 785 NdhL, 987 NicX, three NicA1, and three NicA2 homologs. Results: Genomic classification revealed that six phylum-level taxa, including Proteobacteria, Firmicutes, Firmicutes_A, Bacteroidota, Actinobacteriota, and Chloroflexota, can produce NDEs, with Proteobacteria encoding all five types of NDEs studied. Analysis of NicX prevalence revealed differences among body sites. NicX homologs were found in gut and oral samples with a high prevalence but not found in lung samples. NicX was found in samples from both smokers and non-smokers, though the prevalence might be different.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"305 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140202090","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 : 2024-03-18DOI: 10.2174/0113892029236347240308054538
Óscar Álvarez-Machancoses, Eshel Faraggi, Enrique deAndrés-Galiana, Juan Fernández-Martínez, Andrzej Kloczkowski
Background: Single Amino Acid Polymorphisms (SAPs) or nonsynonymous Single Nucleotide Variants (nsSNVs) are the most common genetic variations. They result from missense mutations where a single base pair substitution changes the genetic code in such a way that the triplet of bases (codon) at a given position is coding a different amino acid. Since genetic mutations sometimes cause genetic diseases, it is important to comprehend and foresee which variations are harmful and which ones are neutral (not causing changes in the phenotype). This can be posed as a classification problem. Methods: Computational methods using machine intelligence are gradually replacing repetitive and exceedingly overpriced mutagenic tests. By and large, uneven quality, deficiencies, and irregularities of nsSNVs datasets debase the convenience of artificial intelligence-based methods. Subsequently, strong and more exact approaches are needed to address these problems. In the present work paper, we show a consensus classifier built on the holdout sampler, which appears strong and precise and outflanks all other popular methods. objective: Roughly a half of known disease-related mutations are due to non-synonymous variants [8-9], expressed as amino-acid mutations. Therefore, it is important to unravel the links between nonsynonymous Single Nucleotide Variants and associated diseases to discriminate between pathogenic and neutral substitutions. It has been found that these substitutions could be directly related to pathological effects such as Parkinson’s or Alzheimer’s diseases, or to the involvement in complex diseases, such as cancer development. Results: We produced 100 holdouts to test the structures and diverse classification variables of diverse classifiers during the training phase. The finest performing holdouts were chosen to develop a consensus classifier and tested using a k-fold (1 ≤ k ≤5) cross-validation method. We also examined which protein properties have the biggest impact on the precise prediction of the effects of nsSNVs. Conclusion: Our Consensus Holdout Sampler outflanks other popular algorithms, and gives excellent results, highly accurate with low standard deviation. The advantage of our method emerges from using a tree of holdouts, where diverse LM/AI-based programs are sampled in diverse ways.
背景：单氨基酸多态性（SAP）或非同义单核苷酸变异（nsSNV）是最常见的基因变异。它们是由错义突变引起的，在错义突变中，单碱基对置换改变了遗传密码，使特定位置的三联碱基（密码子）编码不同的氨基酸。由于基因突变有时会导致遗传疾病，因此理解和预见哪些变异是有害的，哪些变异是中性的（不会导致表型变化）就显得尤为重要。这可以看作是一个分类问题。方法：使用机器智能的计算方法正逐渐取代重复性的、价格过高的诱变试验。总的来说，nsSNVs 数据集的质量参差不齐、缺陷和不规则性削弱了基于人工智能的方法的便利性。因此，需要更强大、更精确的方法来解决这些问题。在本论文中，我们展示了一种建立在holdout采样器基础上的共识分类器，它显得强大而精确，超越了所有其他流行方法：已知的与疾病相关的突变中大约有一半是由非同义变异引起的[8-9]，表现为氨基酸突变。因此，揭示非同义单核苷酸变异与相关疾病之间的联系，以区分致病性和中性变异非常重要。研究发现，这些变异可能与帕金森病或阿尔茨海默病等病理效应直接相关，也可能与癌症发展等复杂疾病有关。结果在训练阶段，我们制作了 100 个暂存模型来测试不同分类器的结构和各种分类变量。我们选取了表现最出色的候选者来开发共识分类器，并使用 k 倍（1 ≤ k ≤5）交叉验证法进行测试。我们还研究了哪些蛋白质特性对精确预测 nsSNV 的影响影响最大。结论我们的 "共识保持采样器 "超越了其他流行的算法，取得了出色的结果，准确度高，标准偏差小。我们的方法的优势来自于使用一棵保留树，在这棵树上，基于 LM/AI 的不同程序以不同的方式进行采样。
{"title":"Prediction of Deleterious Single Amino Acid Polymorphisms with a Consensus Holdout Sampler","authors":"Óscar Álvarez-Machancoses, Eshel Faraggi, Enrique deAndrés-Galiana, Juan Fernández-Martínez, Andrzej Kloczkowski","doi":"10.2174/0113892029236347240308054538","DOIUrl":"https://doi.org/10.2174/0113892029236347240308054538","url":null,"abstract":"Background: Single Amino Acid Polymorphisms (SAPs) or nonsynonymous Single Nucleotide Variants (nsSNVs) are the most common genetic variations. They result from missense mutations where a single base pair substitution changes the genetic code in such a way that the triplet of bases (codon) at a given position is coding a different amino acid. Since genetic mutations sometimes cause genetic diseases, it is important to comprehend and foresee which variations are harmful and which ones are neutral (not causing changes in the phenotype). This can be posed as a classification problem. Methods: Computational methods using machine intelligence are gradually replacing repetitive and exceedingly overpriced mutagenic tests. By and large, uneven quality, deficiencies, and irregularities of nsSNVs datasets debase the convenience of artificial intelligence-based methods. Subsequently, strong and more exact approaches are needed to address these problems. In the present work paper, we show a consensus classifier built on the holdout sampler, which appears strong and precise and outflanks all other popular methods. objective: Roughly a half of known disease-related mutations are due to non-synonymous variants [8-9], expressed as amino-acid mutations. Therefore, it is important to unravel the links between nonsynonymous Single Nucleotide Variants and associated diseases to discriminate between pathogenic and neutral substitutions. It has been found that these substitutions could be directly related to pathological effects such as Parkinson’s or Alzheimer’s diseases, or to the involvement in complex diseases, such as cancer development. Results: We produced 100 holdouts to test the structures and diverse classification variables of diverse classifiers during the training phase. The finest performing holdouts were chosen to develop a consensus classifier and tested using a k-fold (1 ≤ k ≤5) cross-validation method. We also examined which protein properties have the biggest impact on the precise prediction of the effects of nsSNVs. Conclusion: Our Consensus Holdout Sampler outflanks other popular algorithms, and gives excellent results, highly accurate with low standard deviation. The advantage of our method emerges from using a tree of holdouts, where diverse LM/AI-based programs are sampled in diverse ways.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"27 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140165510","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}
Objective: Ignoring the rank information during the enrichment analysis will lead to improper statistical inference. We address this issue by developing of new method to test the significance of ranked gene sets in genome-wide transcriptome profiling data. Methods: A method was proposed by first creating ranked gene sets and gene lists and then applying weighted Kendall's tau rank correlation statistics to the test. After introducing top-down weights to the genes in the gene set, a new software called "Flaver" was developed. Results: Theoretical properties of the proposed method were established, and its differences over the GSEA approach were demonstrated when analyzing the transcriptome profiling data across 55 human tissues and 176 human cell-lines. The results indicated that the TFs identified by our method have higher tendency to be differentially expressed across the tissues analyzed than its competitors. It significantly outperforms the well-known gene set enrichment analyzing tools, GOStats (9%) and GSEA (17%), in analyzing well-documented human RNA transcriptome datasets. Conclusions: The method is outstanding in detecting gene sets of which the gene ranks were correlated with the expression levels of the genes in the transcriptome data.
{"title":"Testing the Significance of Ranked Gene Sets in Genome-Wide Transcriptome Profiling Data Using Weighted Rank Correlation Statistics","authors":"Min Yao, Hao He, Binyu Wang, Xinmiao Huang, Sunli Zheng, Jianwu Wang, Xuejun Gao, Tinghua Huang","doi":"10.2174/0113892029280470240306044159","DOIUrl":"https://doi.org/10.2174/0113892029280470240306044159","url":null,"abstract":"Objective: Ignoring the rank information during the enrichment analysis will lead to improper statistical inference. We address this issue by developing of new method to test the significance of ranked gene sets in genome-wide transcriptome profiling data. Methods: A method was proposed by first creating ranked gene sets and gene lists and then applying weighted Kendall's tau rank correlation statistics to the test. After introducing top-down weights to the genes in the gene set, a new software called \"Flaver\" was developed. Results: Theoretical properties of the proposed method were established, and its differences over the GSEA approach were demonstrated when analyzing the transcriptome profiling data across 55 human tissues and 176 human cell-lines. The results indicated that the TFs identified by our method have higher tendency to be differentially expressed across the tissues analyzed than its competitors. It significantly outperforms the well-known gene set enrichment analyzing tools, GOStats (9%) and GSEA (17%), in analyzing well-documented human RNA transcriptome datasets. Conclusions: The method is outstanding in detecting gene sets of which the gene ranks were correlated with the expression levels of the genes in the transcriptome data.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"2012 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140147457","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 : 2024-02-27DOI: 10.2174/0113892029280454240214072212
Ali Mahmoudi, Mohammad Mahdi Hajihasani, Muhammed Majeed, Tannaz Jamialahmadi, Amirhossein Sahebkar
Background:: Calebin-A is a minor phytoconstituent of turmeric known for its activity against inflammation, oxidative stress, cancerous, and metabolic disorders like Non-alcoholic fatty liver disease(NAFLD). Based on bioinformatic tools, the present study explored the intersection of possible targets that interacted with Calebin-A and the essential genes involved in NAFLD. Subsequently, the details of the interaction of critical proteins with Calebin-A were investigated using the molecular docking technique. Methods:: We first probed the intersection of genes/ proteins between NAFLD and Calebin-A through online databases. Besides, we performed an enrichment analysis using the ClueGO plugin to investigate signaling pathways and gene ontology. Next, we evaluate the possible interaction of Calebin-A with significant hub proteins involved in NAFLD through a molecular docking study. Results:: We identified 87 intersection genes Calebin-A targets associated with NAFLD. PPI network analysis introduced 10 hub genes (TP53, TNF, STAT3, HSP90AA1, PTGS2, HDAC6, ABCB1, CCT2, NR1I2, and GUSB). In KEGG enrichment, most were associated with Sphingolipid, vascular endothelial growth factor A (VEGFA), C-type lectin receptor, and mitogen-activated protein kinase (MAPK) signaling pathways. The biological processes described in 87 intersection genes are mostly concerned with regulating the apoptotic process, cytokine production, and intracellular signal transduction. Molecular docking results also directed that Calebin-A had a high affinity to bind hub proteins linked to NAFLD. Conclusion:: Here, we showed that Calebin-A, through its effect on several critical genes/ proteins and pathways, might repress the progression of NAFLD.
{"title":"Effect of Calebin-A on Critical Genes Related to NAFLD: A Protein-Protein Interaction Network and Molecular Docking Study","authors":"Ali Mahmoudi, Mohammad Mahdi Hajihasani, Muhammed Majeed, Tannaz Jamialahmadi, Amirhossein Sahebkar","doi":"10.2174/0113892029280454240214072212","DOIUrl":"https://doi.org/10.2174/0113892029280454240214072212","url":null,"abstract":"Background:: Calebin-A is a minor phytoconstituent of turmeric known for its activity against inflammation, oxidative stress, cancerous, and metabolic disorders like Non-alcoholic fatty liver disease(NAFLD). Based on bioinformatic tools, the present study explored the intersection of possible targets that interacted with Calebin-A and the essential genes involved in NAFLD. Subsequently, the details of the interaction of critical proteins with Calebin-A were investigated using the molecular docking technique. Methods:: We first probed the intersection of genes/ proteins between NAFLD and Calebin-A through online databases. Besides, we performed an enrichment analysis using the ClueGO plugin to investigate signaling pathways and gene ontology. Next, we evaluate the possible interaction of Calebin-A with significant hub proteins involved in NAFLD through a molecular docking study. Results:: We identified 87 intersection genes Calebin-A targets associated with NAFLD. PPI network analysis introduced 10 hub genes (TP53, TNF, STAT3, HSP90AA1, PTGS2, HDAC6, ABCB1, CCT2, NR1I2, and GUSB). In KEGG enrichment, most were associated with Sphingolipid, vascular endothelial growth factor A (VEGFA), C-type lectin receptor, and mitogen-activated protein kinase (MAPK) signaling pathways. The biological processes described in 87 intersection genes are mostly concerned with regulating the apoptotic process, cytokine production, and intracellular signal transduction. Molecular docking results also directed that Calebin-A had a high affinity to bind hub proteins linked to NAFLD. Conclusion:: Here, we showed that Calebin-A, through its effect on several critical genes/ proteins and pathways, might repress the progression of NAFLD.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"11 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140004337","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 : 2024-02-23DOI: 10.2174/138920292501240205235837
Fabio Coppedè
{"title":"Preface 25 Years of Current Genomics.","authors":"Fabio Coppedè","doi":"10.2174/138920292501240205235837","DOIUrl":"10.2174/138920292501240205235837","url":null,"abstract":"","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"25 1","pages":"1"},"PeriodicalIF":1.8,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10964086/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140305146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-21DOI: 10.2174/0113892029268176240125055419
Aditi R. Durge, Deepti D. Shrimankar
Problem: Analyzing genomic sequences plays a crucial role in understanding biological diversity and classifying Bamboo species. Existing methods for genomic sequence analysis suffer from limitations such as complexity, low accuracy, and the need for constant reconfiguration in response to evolving genomic datasets. Aim: This study addresses these limitations by introducing a novel Dual Heuristic Feature Selection- based Ensemble Classification Model (DHFS-ECM) for the precise identification of Bamboo species from genomic sequences. Methods: The proposed DHFS-ECM method employs a Genetic Algorithm to perform dual heuristic feature selection. This process maximizes inter-class variance, leading to the selection of informative N-gram feature sets. Subsequently, intra-class variance levels are used to create optimal training and validation sets, ensuring comprehensive coverage of class-specific features. The selected features are then processed through an ensemble classification layer, combining multiple stratification models for species-specific categorization. Results: Comparative analysis with state-of-the-art methods demonstrate that DHFS-ECM achieves remarkable improvements in accuracy (9.5%), precision (5.9%), recall (8.5%), and AUC performance (4.5%). Importantly, the model maintains its performance even with an increased number of species classes due to the continuous learning facilitated by the Dual Heuristic Genetic Algorithm Model. Conclusion: DHFS-ECM offers several key advantages, including efficient feature extraction, reduced model complexity, enhanced interpretability, and increased robustness and accuracy through the ensemble classification layer. These attributes make DHFS-ECM a promising tool for real-time clinical applications and a valuable contribution to the field of genomic sequence analysis.
{"title":"DHFS-ECM: Design of a Dual Heuristic Feature Selection-based Ensemble Classification Model for the Identification of Bamboo Species from Genomic Sequences","authors":"Aditi R. Durge, Deepti D. Shrimankar","doi":"10.2174/0113892029268176240125055419","DOIUrl":"https://doi.org/10.2174/0113892029268176240125055419","url":null,"abstract":"Problem: Analyzing genomic sequences plays a crucial role in understanding biological diversity and classifying Bamboo species. Existing methods for genomic sequence analysis suffer from limitations such as complexity, low accuracy, and the need for constant reconfiguration in response to evolving genomic datasets. Aim: This study addresses these limitations by introducing a novel Dual Heuristic Feature Selection- based Ensemble Classification Model (DHFS-ECM) for the precise identification of Bamboo species from genomic sequences. Methods: The proposed DHFS-ECM method employs a Genetic Algorithm to perform dual heuristic feature selection. This process maximizes inter-class variance, leading to the selection of informative N-gram feature sets. Subsequently, intra-class variance levels are used to create optimal training and validation sets, ensuring comprehensive coverage of class-specific features. The selected features are then processed through an ensemble classification layer, combining multiple stratification models for species-specific categorization. Results: Comparative analysis with state-of-the-art methods demonstrate that DHFS-ECM achieves remarkable improvements in accuracy (9.5%), precision (5.9%), recall (8.5%), and AUC performance (4.5%). Importantly, the model maintains its performance even with an increased number of species classes due to the continuous learning facilitated by the Dual Heuristic Genetic Algorithm Model. Conclusion: DHFS-ECM offers several key advantages, including efficient feature extraction, reduced model complexity, enhanced interpretability, and increased robustness and accuracy through the ensemble classification layer. These attributes make DHFS-ECM a promising tool for real-time clinical applications and a valuable contribution to the field of genomic sequence analysis.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"134 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139951511","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: Pakistan has a high burden of oral cancers, with a prevalence rate of around 9%. Oral Squamous Cell Carcinoma (OSCC) accounts for about 90% of oral cancer cases. Epithelial to Mesenchymal Transition (EMT) gets highly stimulated in tumor cells by adopting subsequent malignant features of highly invasive cancer populations. Zinc Finger E-Box binding factors, ZEB1 and ZEB2, are regulatory proteins that promote EMT by suppressing the adherent ability of cells transforming into highly motile cancerous cells. The present study aimed to analyze the expression of EMT regulators, ZEB1 and ZEB2, and their association with the clinicopathological features in different grades of OSCC patients. Methods: Tissue samples were collected for both case and control groups from the recruited study participants. Cancer tissues (cases) were collected from the confirmed OSCC patients, and healthy tissues (controls) were collected from third-molar dental extraction patients. The study participants were recruited with informed consent and brief demographic and clinical characteristics. The case group was further segregated with respect to the histological cancer grading system into well-differentiated (WD), moderately differentiated (MD), and poorly differentiated (PD) squamous cell carcinoma (SCC) groups. RNA was extracted from the tissue samples for expression profiling of ZEB1 and ZEB2 genes through quantitative real-time PCR (qRT-PCR) Results: All of the recruited participants had a mean age of 46.55 ± 11.7 (years), with most of them belonging to Urdu speaking ethnic group and were married. The BMI (kg/m2 ) of the healthy participants was in the normal range (18-22 kg/m2 ). However, BMI was found to be reduced with the proliferation in the pathological state of cancer. The oral hygiene of patients was better than the healthy participants, possibly due to the strict oral hygiene practice concerns of consultants. Every recruited OSCC patient had one or multiple addiction habits for more than a year. Patients reported health frailty (46.6%), unhealed mouth sores (40%), swallowing difficulties and white/reddish marks (80%), and restricted mouth opening (64.4%). Furthermore, 82.2% of the recruited patients observed symptoms within 1-12 months, and buccal mucosa was the most exposed tumor site among 55.6% of the patients. Expression profiling of EMT regulators showed gradual over-expressions of ZEB1 (8, 20, and 42 folds) and ZEB2 (4, 10, and 18 folds) in respective histological cancer grades. Conclusion: High expressions of ZEBs have been significantly associated with cancer progression and poor health. However, no association was found between OSCC with other clinicopathological features when compared to healthy controls
{"title":"Expression Profiling of EMT Transcriptional Regulators ZEB1 and ZEB2 in Different Histopathological Grades of Oral Squamous Cell Carcinoma Patients","authors":"Neha Baqai, Rafat Amin, Tehseen Fatima, Zeba Ahmed, Nousheen Faiz","doi":"10.2174/0113892029284920240212091903","DOIUrl":"https://doi.org/10.2174/0113892029284920240212091903","url":null,"abstract":"Background: Pakistan has a high burden of oral cancers, with a prevalence rate of around 9%. Oral Squamous Cell Carcinoma (OSCC) accounts for about 90% of oral cancer cases. Epithelial to Mesenchymal Transition (EMT) gets highly stimulated in tumor cells by adopting subsequent malignant features of highly invasive cancer populations. Zinc Finger E-Box binding factors, ZEB1 and ZEB2, are regulatory proteins that promote EMT by suppressing the adherent ability of cells transforming into highly motile cancerous cells. The present study aimed to analyze the expression of EMT regulators, ZEB1 and ZEB2, and their association with the clinicopathological features in different grades of OSCC patients. Methods: Tissue samples were collected for both case and control groups from the recruited study participants. Cancer tissues (cases) were collected from the confirmed OSCC patients, and healthy tissues (controls) were collected from third-molar dental extraction patients. The study participants were recruited with informed consent and brief demographic and clinical characteristics. The case group was further segregated with respect to the histological cancer grading system into well-differentiated (WD), moderately differentiated (MD), and poorly differentiated (PD) squamous cell carcinoma (SCC) groups. RNA was extracted from the tissue samples for expression profiling of ZEB1 and ZEB2 genes through quantitative real-time PCR (qRT-PCR) Results: All of the recruited participants had a mean age of 46.55 ± 11.7 (years), with most of them belonging to Urdu speaking ethnic group and were married. The BMI (kg/m2 ) of the healthy participants was in the normal range (18-22 kg/m2 ). However, BMI was found to be reduced with the proliferation in the pathological state of cancer. The oral hygiene of patients was better than the healthy participants, possibly due to the strict oral hygiene practice concerns of consultants. Every recruited OSCC patient had one or multiple addiction habits for more than a year. Patients reported health frailty (46.6%), unhealed mouth sores (40%), swallowing difficulties and white/reddish marks (80%), and restricted mouth opening (64.4%). Furthermore, 82.2% of the recruited patients observed symptoms within 1-12 months, and buccal mucosa was the most exposed tumor site among 55.6% of the patients. Expression profiling of EMT regulators showed gradual over-expressions of ZEB1 (8, 20, and 42 folds) and ZEB2 (4, 10, and 18 folds) in respective histological cancer grades. Conclusion: High expressions of ZEBs have been significantly associated with cancer progression and poor health. However, no association was found between OSCC with other clinicopathological features when compared to healthy controls","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"87 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139751828","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}
: SARS-CoV-2 is a highly contagious and transmissible viral infection that first emerged in 2019 and since then has sparked an epidemic of severe respiratory problems identified as “coronavirus disease 2019” (COVID-19) that causes a hazard to human life and safety. The virus developed mainly from bats. The current epidemic has presented a significant warning to life across the world by showing mutation. There are different tests available for testing Coronavirus, and RTPCR is the best, giving more accurate results, but it is also time-consuming. There are different options available for treating n-CoV-19, which include medications such as Remdesivir, corticosteroids, plasma therapy, Dexamethasone therapy, etc. The development of vaccines such as BNT126b2, ChAdOX1, mRNA-1273 and BBIBP-CorV has provided great relief in dealing with the virus as they decreased the mortality rate. BNT126b2 and ChAdOX1 are two n-CoV vaccines found to be most effective in controlling the spread of infection. In the future, nanotechnology-based vaccines and immune engineering techniques can be helpful for further research on Coronavirus and treatment of this deadly virus. The existing knowledge about the existence of SARS-- CoV-2, along with its variants, is summarized in this review. This review, based on recently published findings, presents the core genetics of COVID-19, including heritable characteristics, pathogenesis, immunological biomarkers, treatment options and clinical updates on the virus, along with patents.
{"title":"COVID-19: Recent Insight in Genomic Feature, Pathogenesis, Immunological Biomarkers, Treatment Options and Clinical Updates on SARS-CoV-2","authors":"Rohitas Deshmukh, Ranjit K Harwansh, Akash Garg, Sakshi Mishra, Rutvi Agrawal, Rajendra Jangde","doi":"10.2174/0113892029291098240129113500","DOIUrl":"https://doi.org/10.2174/0113892029291098240129113500","url":null,"abstract":": SARS-CoV-2 is a highly contagious and transmissible viral infection that first emerged in 2019 and since then has sparked an epidemic of severe respiratory problems identified as “coronavirus disease 2019” (COVID-19) that causes a hazard to human life and safety. The virus developed mainly from bats. The current epidemic has presented a significant warning to life across the world by showing mutation. There are different tests available for testing Coronavirus, and RTPCR is the best, giving more accurate results, but it is also time-consuming. There are different options available for treating n-CoV-19, which include medications such as Remdesivir, corticosteroids, plasma therapy, Dexamethasone therapy, etc. The development of vaccines such as BNT126b2, ChAdOX1, mRNA-1273 and BBIBP-CorV has provided great relief in dealing with the virus as they decreased the mortality rate. BNT126b2 and ChAdOX1 are two n-CoV vaccines found to be most effective in controlling the spread of infection. In the future, nanotechnology-based vaccines and immune engineering techniques can be helpful for further research on Coronavirus and treatment of this deadly virus. The existing knowledge about the existence of SARS-- CoV-2, along with its variants, is summarized in this review. This review, based on recently published findings, presents the core genetics of COVID-19, including heritable characteristics, pathogenesis, immunological biomarkers, treatment options and clinical updates on the virus, along with patents.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"49 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139751750","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 : 2024-01-29DOI: 10.2174/0113892029278082240118053857
Aiyan Xing, Dongxiao Lv, Changshun Wu, Kai Zhou, Tianhui Zhao, Lihua Zhao, Huaqing Wang, Hong Feng
Objectives: This study aims to assess the prognostic implications of gene signature of the tertiary lymphoid structures (TLSs) in head and neck squamous cell carcinoma (HNSCC) and scrutinize the influence of TLS on immune infiltration. Methods: Patients with HNSCC from the Cancer Genome Atlas were categorized into high/low TLS signature groups based on the predetermined TLS signature threshold. The association of the TLS signature with the immune microenvironment, driver gene mutation status, and tumor mutational load was systematically analyzed. Validation was conducted using independent datasets (GSE41613 and GSE102349). Results: Patients with a high TLS signature score exhibited better prognosis compared to those with a low TLS signature score. The group with a high TLS signature score had significantly higher immune cell subpopulations compared to the group with a low TLS signature score. Moreover, the major immune cell subpopulations and immune circulation characteristics in the tumor immune microenvironment were positively correlated with the TLS signature. Mutational differences in driver genes were observed between the TLS signature high/low groups, primarily in the cell cycle and NRF2 signaling pathways. Patients with TP53 mutations and high TLS signature scores demonstrated a better prognosis compared to those with TP53 wild-type. In the independent cohort, the relationship between TLS signatures and patient prognosis and immune infiltration was also confirmed. Additionally, immune-related biological processes and signaling pathways were activated with elevated TLS signature. Conclusion: High TLS signature is a promising independent prognostic factor for HNSCC patients. Immunological analysis indicated a correlation between TLS and immune cell infiltration in HNSCC. These findings provide a theoretical basis for future applications of TLS signature in HNSCC prognosis and immunotherapy.
{"title":"Tertiary Lymphoid Structures Gene Signature Predicts Prognosis and Immune Infiltration Analysis in Head and Neck Squamous Cell Carcinoma","authors":"Aiyan Xing, Dongxiao Lv, Changshun Wu, Kai Zhou, Tianhui Zhao, Lihua Zhao, Huaqing Wang, Hong Feng","doi":"10.2174/0113892029278082240118053857","DOIUrl":"https://doi.org/10.2174/0113892029278082240118053857","url":null,"abstract":"Objectives: This study aims to assess the prognostic implications of gene signature of the tertiary lymphoid structures (TLSs) in head and neck squamous cell carcinoma (HNSCC) and scrutinize the influence of TLS on immune infiltration. Methods: Patients with HNSCC from the Cancer Genome Atlas were categorized into high/low TLS signature groups based on the predetermined TLS signature threshold. The association of the TLS signature with the immune microenvironment, driver gene mutation status, and tumor mutational load was systematically analyzed. Validation was conducted using independent datasets (GSE41613 and GSE102349). Results: Patients with a high TLS signature score exhibited better prognosis compared to those with a low TLS signature score. The group with a high TLS signature score had significantly higher immune cell subpopulations compared to the group with a low TLS signature score. Moreover, the major immune cell subpopulations and immune circulation characteristics in the tumor immune microenvironment were positively correlated with the TLS signature. Mutational differences in driver genes were observed between the TLS signature high/low groups, primarily in the cell cycle and NRF2 signaling pathways. Patients with TP53 mutations and high TLS signature scores demonstrated a better prognosis compared to those with TP53 wild-type. In the independent cohort, the relationship between TLS signatures and patient prognosis and immune infiltration was also confirmed. Additionally, immune-related biological processes and signaling pathways were activated with elevated TLS signature. Conclusion: High TLS signature is a promising independent prognostic factor for HNSCC patients. Immunological analysis indicated a correlation between TLS and immune cell infiltration in HNSCC. These findings provide a theoretical basis for future applications of TLS signature in HNSCC prognosis and immunotherapy.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"50 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139584907","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}
Objective:: Specific methylation sites have shown promise in the early diagnosis of lung adenocarcinoma (LUAD). However, their utility in predicting LUAD prognosis remains unclear. This study aimed to construct a reliable methylation-based predictor for accurately predicting the prognosis of LUAD patients. Method:: DNA methylation data and survival data from LUAD patients were obtained from the TCGA and a GEO series. A DNA methylation-based signature was developed using univariate least absolute shrinkage and selection operators and multivariate Cox regression models. Result:: Eight CpG sites were identified and validated as optimal prognostic signatures for the overall survival of LUAD patients. Receiver operating characteristic analysis demonstrated the high predictive ability of the eight-site methylation signature combined with clinical factors for overall survival. Conclusion:: This research successfully identified a novel eight-site methylation signature for predicting the overall survival of LUAD patients through bioinformatic integrated analysis of gene methylation markers used in the early diagnosis of lung cancer.
{"title":"A Novel Methylation-Based Model for Prognostic Prediction in Lung Adenocarcinoma","authors":"Manyuan Li, Xufeng Deng, Dong Zhou, Xiaoqing Liu, Jigang Dai, Quanxing Liu","doi":"10.2174/0113892029277397231228062412","DOIUrl":"https://doi.org/10.2174/0113892029277397231228062412","url":null,"abstract":"Objective:: Specific methylation sites have shown promise in the early diagnosis of lung adenocarcinoma (LUAD). However, their utility in predicting LUAD prognosis remains unclear. This study aimed to construct a reliable methylation-based predictor for accurately predicting the prognosis of LUAD patients. Method:: DNA methylation data and survival data from LUAD patients were obtained from the TCGA and a GEO series. A DNA methylation-based signature was developed using univariate least absolute shrinkage and selection operators and multivariate Cox regression models. Result:: Eight CpG sites were identified and validated as optimal prognostic signatures for the overall survival of LUAD patients. Receiver operating characteristic analysis demonstrated the high predictive ability of the eight-site methylation signature combined with clinical factors for overall survival. Conclusion:: This research successfully identified a novel eight-site methylation signature for predicting the overall survival of LUAD patients through bioinformatic integrated analysis of gene methylation markers used in the early diagnosis of lung cancer.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"60 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139557725","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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