Pub Date : 2024-01-01Epub Date: 2024-08-05DOI: 10.2174/138920292505240805091029
{"title":"ACKNOWLEDGEMENT TO REVIEWERS.","authors":"","doi":"10.2174/138920292505240805091029","DOIUrl":"https://doi.org/10.2174/138920292505240805091029","url":null,"abstract":"","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11420566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343139","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 : 2023-12-08DOI: 10.2174/0113892029276542231205065843
Ayushi Gupta, Suresh Nair
Background:: The brown planthopper (BPH) is a monophagous sap-sucking insect pest of rice that is responsible for massive yield loss. BPH populations, even when genetically homogenous, can display a vast range of phenotypes, and the development of effective pest-management strategies requires a good understanding of what generates this phenotypic variation. One potential source could be epigenetic differences. Methods:: With this premise, we explored epigenetic diversity, structure and differentiation in field populations of BPH collected across the rice-growing seasons over a period of two consecutive years. Using a modified methylation-sensitive restriction assay (MSRA) and CpG island amplification- representational difference analysis, site-specific cytosine methylation of five stress-responsive genes (CYP6AY1, CYP6ER1, Carboxylesterase, Endoglucanase, Tf2-transposon) was estimated, for identifying methylation-based epiallelic markers and epigenetic variation across BPH populations. Results:: Using a cost-effective and rapid protocol, our study, for the first time, revealed the epigenetic component of phenotypic variations in the wild populations of BPH. Besides, results showed that morphologically indistinguishable populations of BPH can be epigenetically distinct. Conclusion:: Screening field-collected BPH populations revealed the presence of previously unreported epigenetic polymorphisms and provided a platform for future studies aimed at investigating their significance for BPH. Furthermore, these findings can form the basis for understanding the contribution(s) of DNA methylation in providing phenotypic plasticity to BPH.
背景：：褐飞虱（BPH）是水稻的一种单食性吸汁害虫，是造成大量减产的原因。即使在基因同源的情况下，褐飞虱种群也会表现出各种各样的表型，要想制定有效的害虫管理策略，就必须充分了解是什么导致了这种表型变异。表观遗传差异可能是其中一个潜在来源。方法：：在此前提下，我们探索了连续两年在水稻生长季节收集的 BPH 田间种群的表观遗传多样性、结构和分化。利用改良的甲基化敏感限制分析法（MSRA）和CpG岛扩增-代表性差异分析法，估算了五个应激反应基因（CYP6AY1、CYP6ER1、羧酸酯酶、内切葡聚糖酶、Tf2-转座子）的特异性胞嘧啶甲基化位点，以确定基于甲基化的外显子标记和BPH种群间的表观遗传变异。结果我们的研究采用了一种经济有效的快速方法，首次揭示了 BPH 野生种群表型变异的表观遗传因素。此外，研究结果表明，在形态上难以区分的 BPH 种群在表观遗传学上可能是不同的。结论筛选野外采集的牛肝菌种群发现了以前未报道过的表观遗传多态性，为今后研究这些多态性对牛肝菌的意义提供了一个平台。此外，这些发现可为了解 DNA 甲基化在提供良性前列腺增生症表型可塑性方面的作用奠定基础。
{"title":"Epigenetic Diversity Underlying Seasonal and Annual Variations in Brown Planthopper (BPH) Populations as Revealed by Methylationsensitive Restriction Assay","authors":"Ayushi Gupta, Suresh Nair","doi":"10.2174/0113892029276542231205065843","DOIUrl":"https://doi.org/10.2174/0113892029276542231205065843","url":null,"abstract":"Background:: The brown planthopper (BPH) is a monophagous sap-sucking insect pest of rice that is responsible for massive yield loss. BPH populations, even when genetically homogenous, can display a vast range of phenotypes, and the development of effective pest-management strategies requires a good understanding of what generates this phenotypic variation. One potential source could be epigenetic differences. Methods:: With this premise, we explored epigenetic diversity, structure and differentiation in field populations of BPH collected across the rice-growing seasons over a period of two consecutive years. Using a modified methylation-sensitive restriction assay (MSRA) and CpG island amplification- representational difference analysis, site-specific cytosine methylation of five stress-responsive genes (CYP6AY1, CYP6ER1, Carboxylesterase, Endoglucanase, Tf2-transposon) was estimated, for identifying methylation-based epiallelic markers and epigenetic variation across BPH populations. Results:: Using a cost-effective and rapid protocol, our study, for the first time, revealed the epigenetic component of phenotypic variations in the wild populations of BPH. Besides, results showed that morphologically indistinguishable populations of BPH can be epigenetically distinct. Conclusion:: Screening field-collected BPH populations revealed the presence of previously unreported epigenetic polymorphisms and provided a platform for future studies aimed at investigating their significance for BPH. Furthermore, these findings can form the basis for understanding the contribution(s) of DNA methylation in providing phenotypic plasticity to BPH.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138563305","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 : 2023-12-01DOI: 10.2174/0113892029286632231127055733
Mariya Levkova, Trifon Chervenkov, Lyudmila Angelova, Deyan Dzenkov
: Advanced medical technologies are transforming the future of healthcare, in particular, the screening and detection of molecular-genetic changes in patients suspected of having a neoplasm. They are based on the assumption that neoplasms release small amounts of various neoplasm- specific molecules, such as tumor DNA, called circulating DNA (cirDNA), into the extracellular space and subsequently into the blood. The detection of tumor-specific molecules and specific molecular changes in body fluids in a noninvasive or minimally invasive approach is known as “liquid biopsy.” The aim of this review is to summarize the current knowledge of the application of ONT for analyzing circulating DNA in the field of liquid biopsies among cancer patients. Databases were searched using the keywords “nanopore” and “liquid biopsy” and by applying strict inclusion criteria. This technique can be used for the detection of neoplastic disease, including metastases, guiding precision therapy, and monitoring its effects. There are many challenges, however, for the successful implementation of this technology into the clinical practice. The first one is the low amount of tumor-specific molecules in the body fluids. Secondly, a tumor molecular signature should be discriminated from benign conditions like clonal hematopoiesis of unknown significance. Oxford Nanopore Technology (ONT) is a third-generation sequencing technology that seems particularly promising to complete these tasks. It offers rapid sequencing thanks to its ability to detect changes in the density of the electric current passing through nanopores. Even though ONT still needs validation technology, it is a promising approach for early diagnosis, therapy guidance, and monitoring of different neoplasms based on analyzing the cirDNA.
{"title":"Oxford Nanopore Technology and its Application in Liquid Biopsies","authors":"Mariya Levkova, Trifon Chervenkov, Lyudmila Angelova, Deyan Dzenkov","doi":"10.2174/0113892029286632231127055733","DOIUrl":"https://doi.org/10.2174/0113892029286632231127055733","url":null,"abstract":": Advanced medical technologies are transforming the future of healthcare, in particular, the screening and detection of molecular-genetic changes in patients suspected of having a neoplasm. They are based on the assumption that neoplasms release small amounts of various neoplasm- specific molecules, such as tumor DNA, called circulating DNA (cirDNA), into the extracellular space and subsequently into the blood. The detection of tumor-specific molecules and specific molecular changes in body fluids in a noninvasive or minimally invasive approach is known as “liquid biopsy.” The aim of this review is to summarize the current knowledge of the application of ONT for analyzing circulating DNA in the field of liquid biopsies among cancer patients. Databases were searched using the keywords “nanopore” and “liquid biopsy” and by applying strict inclusion criteria. This technique can be used for the detection of neoplastic disease, including metastases, guiding precision therapy, and monitoring its effects. There are many challenges, however, for the successful implementation of this technology into the clinical practice. The first one is the low amount of tumor-specific molecules in the body fluids. Secondly, a tumor molecular signature should be discriminated from benign conditions like clonal hematopoiesis of unknown significance. Oxford Nanopore Technology (ONT) is a third-generation sequencing technology that seems particularly promising to complete these tasks. It offers rapid sequencing thanks to its ability to detect changes in the density of the electric current passing through nanopores. Even though ONT still needs validation technology, it is a promising approach for early diagnosis, therapy guidance, and monitoring of different neoplasms based on analyzing the cirDNA.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138524432","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: The ATM gene encodes a multifunctional kinase involved in important cellular functions, such as checkpoint signaling and apoptosis, in response to DNA damage. Bi-allelic pathogenic variants in this gene cause Ataxia Telangiectasia (AT), while carriers of ATM pathogenic variants are at increased risk of cancer depending on the pathogenicity of the variant they carry. Identifying pathogenic variants can aid in the management of the disease in carriers. Methods: Whole-exome sequencing (WES) was performed on three unrelated patients from the Iranian-Azeri Turkish ethnic group referred to a genetic center for analysis. WES was also conducted on 400 individuals from the same ethnic group to determine the frequencies of all ATM variants. Blood samples were collected from the patients and their family members for DNA extraction, and PCR-Sanger sequencing was performed to confirm the WES results. Results: The first proband with AT disease had two novel compound heterozygote variants (c.2639-2A>T, c.8708delC) in the ATM gene revealed by WES analysis, which was potentially/- likely pathogenic. The second proband with bi-lateral breast cancer had a homozygous pathogenic variant (c.6067G>A) in the ATM gene identified by WES analysis. The third case with a family history of cancer had a heterozygous synonymous pathogenic variant (c.7788G>A) in the ATM gene found by WES analysis. Sanger sequencing confirmed the WES results, and bioinformatics analysis of the mutated ATM RNA and protein structure added evidence for the potential pathogenicity of the novel variants. WES analysis of the cohort revealed 38 different variants, including a variant (rs1800057, ATM:c.3161C>G, p.P1054R) associated with prostate cancer that had a higher frequency in our cohort. Conclusion: Genetic analysis of three unrelated families with ATM-related disorders discovered two novel pathogenic variants. A homozygous missense pathogenic variant was identified in a woman with bi-lateral breast cancer, and a pathogenic synonymous pathogenic variant was found in a family with a history of different cancers.
{"title":"Identification of Two Novel Pathogenic Variants of the ATM Gene in the Iranian-Azeri Turkish Ethnic Group by Applying Whole Exome Sequencing","authors":"Amir-Reza Dalal Amandi, Neda Jabbarpour, Shadi Shiva, Mortaza Bonyadi","doi":"10.2174/0113892029268949231104165301","DOIUrl":"https://doi.org/10.2174/0113892029268949231104165301","url":null,"abstract":"Background: The ATM gene encodes a multifunctional kinase involved in important cellular functions, such as checkpoint signaling and apoptosis, in response to DNA damage. Bi-allelic pathogenic variants in this gene cause Ataxia Telangiectasia (AT), while carriers of ATM pathogenic variants are at increased risk of cancer depending on the pathogenicity of the variant they carry. Identifying pathogenic variants can aid in the management of the disease in carriers. Methods: Whole-exome sequencing (WES) was performed on three unrelated patients from the Iranian-Azeri Turkish ethnic group referred to a genetic center for analysis. WES was also conducted on 400 individuals from the same ethnic group to determine the frequencies of all ATM variants. Blood samples were collected from the patients and their family members for DNA extraction, and PCR-Sanger sequencing was performed to confirm the WES results. Results: The first proband with AT disease had two novel compound heterozygote variants (c.2639-2A>T, c.8708delC) in the ATM gene revealed by WES analysis, which was potentially/- likely pathogenic. The second proband with bi-lateral breast cancer had a homozygous pathogenic variant (c.6067G>A) in the ATM gene identified by WES analysis. The third case with a family history of cancer had a heterozygous synonymous pathogenic variant (c.7788G>A) in the ATM gene found by WES analysis. Sanger sequencing confirmed the WES results, and bioinformatics analysis of the mutated ATM RNA and protein structure added evidence for the potential pathogenicity of the novel variants. WES analysis of the cohort revealed 38 different variants, including a variant (rs1800057, ATM:c.3161C>G, p.P1054R) associated with prostate cancer that had a higher frequency in our cohort. Conclusion: Genetic analysis of three unrelated families with ATM-related disorders discovered two novel pathogenic variants. A homozygous missense pathogenic variant was identified in a woman with bi-lateral breast cancer, and a pathogenic synonymous pathogenic variant was found in a family with a history of different cancers.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138524457","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 : 2023-11-29DOI: 10.2174/0113892029269523231101051455
Sony K. Ahuja, Deepti D. Shrimankar, Aditi R. Durge
: Human gene sequences are considered a primary source of comprehensive information about different body conditions. A wide variety of diseases including cancer, heart issues, brain issues, genetic issues, etc. can be pre-empted via efficient analysis of genomic sequences. Researchers have proposed different configurations of machine learning models for processing genomic sequences, and each of these models varies in terms of their performance & applicability characteristics. Models that use bioinspired optimizations are generally slower, but have superior incrementalperformance, while models that use one-shot learning achieve higher instantaneous accuracy but cannot be scaled for larger disease-sets. Due to such variations, it is difficult for genomic system designers to identify optimum models for their application-specific & performance-specific use cases. To overcome this issue, a detailed survey of different genomic processing models in terms of their functional nuances, application-specific advantages, deployment-specific limitations, and contextual future scopes is discussed in this text. Based on this discussion, researchers will be able to identify optimal models for their functional use cases. This text also compares the reviewed models in terms of their quantitative parameter sets, which include, the accuracy of classification, delay needed to classify large-length sequences, precision levels, scalability levels, and deployment cost, which will assist readers in selecting deployment-specific models for their contextual clinical scenarios. This text also evaluates a novel Genome Processing Efficiency Rank (GPER) for each of these models, which will allow readers to identify models with higher performance and low overheads under real-time scenarios.
{"title":"A Study and Analysis of Disease Identification using Genomic Sequence Processing Models: An Empirical Review","authors":"Sony K. Ahuja, Deepti D. Shrimankar, Aditi R. Durge","doi":"10.2174/0113892029269523231101051455","DOIUrl":"https://doi.org/10.2174/0113892029269523231101051455","url":null,"abstract":": Human gene sequences are considered a primary source of comprehensive information about different body conditions. A wide variety of diseases including cancer, heart issues, brain issues, genetic issues, etc. can be pre-empted via efficient analysis of genomic sequences. Researchers have proposed different configurations of machine learning models for processing genomic sequences, and each of these models varies in terms of their performance & applicability characteristics. Models that use bioinspired optimizations are generally slower, but have superior incrementalperformance, while models that use one-shot learning achieve higher instantaneous accuracy but cannot be scaled for larger disease-sets. Due to such variations, it is difficult for genomic system designers to identify optimum models for their application-specific & performance-specific use cases. To overcome this issue, a detailed survey of different genomic processing models in terms of their functional nuances, application-specific advantages, deployment-specific limitations, and contextual future scopes is discussed in this text. Based on this discussion, researchers will be able to identify optimal models for their functional use cases. This text also compares the reviewed models in terms of their quantitative parameter sets, which include, the accuracy of classification, delay needed to classify large-length sequences, precision levels, scalability levels, and deployment cost, which will assist readers in selecting deployment-specific models for their contextual clinical scenarios. This text also evaluates a novel Genome Processing Efficiency Rank (GPER) for each of these models, which will allow readers to identify models with higher performance and low overheads under real-time scenarios.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138524431","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 : 2023-11-29DOI: 10.2174/0113892029277262231108105441
Yi-Mei Xiong, Fang Zhou, Jia-Wen Zhou, Fei Liu, Si-Qi Zhou, Bo Li, Zhong-Jian Liu, Yang Qin
Introduction: Hepatocellular carcinoma (HCC) has a high mortality rate, with curative resection being the primary treatment. However, HCC patients have a large possibility of recurrence within 5 years after curative resection. Method: Thus, identifying biomarkers to predict recurrence is crucial. In our study, we analyzed data from CCLE, GEO, and TCGA, identifying eight oncogenes associated with HCC. Subsequently, the expression of 8 genes was tested in 5 cases of tumor tissues and the adjacent non-tumor tissues. Then ATP6AP1, PSMD14 and HSP90AB1 were selected to verify the expression in 63 cases of tumor tissues and the adjacent non-tumor tissues. The results showed that ATP6AP1, PSMD14, HSP90AB1 were generally highly expressed in tumor tissues. A five-year follow-up of the 63 clinical cases, combined with Kaplan-Meier Plotter's relapse-free survival (RFS) analysis, found a significant correlation between PSMD14 expression and recurrence in HCC patients. Subsequently, we analyzed the PSMD14 mutations and found that the PSMD14 gene mutations can lead to a shorter disease-free survival time for HCC patients. Results: The results of enrichment analysis indicated that the differentially expressed genes related to PSMD14 are mainly enriched in the signal release pathway. Conclusion: In conclusion, our research showed that PSMD14 might be related to recurrence in HCC patients, and the expression of PSMD14 in tumor tissue might be a potential prognostic biomarker after tumor resection in HCC patients.
{"title":"Aberrant Expressions of PSMD14 in Tumor Tissue are the Potential Prognostic Biomarkers for Hepatocellular Carcinoma after Curative Resection","authors":"Yi-Mei Xiong, Fang Zhou, Jia-Wen Zhou, Fei Liu, Si-Qi Zhou, Bo Li, Zhong-Jian Liu, Yang Qin","doi":"10.2174/0113892029277262231108105441","DOIUrl":"https://doi.org/10.2174/0113892029277262231108105441","url":null,"abstract":"Introduction: Hepatocellular carcinoma (HCC) has a high mortality rate, with curative resection being the primary treatment. However, HCC patients have a large possibility of recurrence within 5 years after curative resection. Method: Thus, identifying biomarkers to predict recurrence is crucial. In our study, we analyzed data from CCLE, GEO, and TCGA, identifying eight oncogenes associated with HCC. Subsequently, the expression of 8 genes was tested in 5 cases of tumor tissues and the adjacent non-tumor tissues. Then ATP6AP1, PSMD14 and HSP90AB1 were selected to verify the expression in 63 cases of tumor tissues and the adjacent non-tumor tissues. The results showed that ATP6AP1, PSMD14, HSP90AB1 were generally highly expressed in tumor tissues. A five-year follow-up of the 63 clinical cases, combined with Kaplan-Meier Plotter's relapse-free survival (RFS) analysis, found a significant correlation between PSMD14 expression and recurrence in HCC patients. Subsequently, we analyzed the PSMD14 mutations and found that the PSMD14 gene mutations can lead to a shorter disease-free survival time for HCC patients. Results: The results of enrichment analysis indicated that the differentially expressed genes related to PSMD14 are mainly enriched in the signal release pathway. Conclusion: In conclusion, our research showed that PSMD14 might be related to recurrence in HCC patients, and the expression of PSMD14 in tumor tissue might be a potential prognostic biomarker after tumor resection in HCC patients.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138524442","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 : 2023-11-22DOI: 10.2174/1389202924666230726112233
Giulia Cursano, Emanuele Frigo, Elham Sajjadi, Mariia Ivanova, Konstantinos Venetis, Elena Guerini-Rocco, Carmen Criscitiello, Giuseppe Curigliano, Nicola Fusco
{"title":"Trop-2 as an Actionable Biomarker in Breast Cancer.","authors":"Giulia Cursano, Emanuele Frigo, Elham Sajjadi, Mariia Ivanova, Konstantinos Venetis, Elena Guerini-Rocco, Carmen Criscitiello, Giuseppe Curigliano, Nicola Fusco","doi":"10.2174/1389202924666230726112233","DOIUrl":"10.2174/1389202924666230726112233","url":null,"abstract":"","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10761338/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47376928","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}
Background: Currently, prostate-specific antigen (PSA) is commonly used as a prostate cancer (PCa) biomarker. PSA is linked to some factors that frequently lead to erroneous positive results or even needless biopsies of elderly people. Objectives: In this pilot study, we undermined the potential genes and mutations from several databases and checked whether or not any putative prognostic biomarkers are central to the annotation. The aim of the study was to develop a risk prediction model that could help in clinical decision-making. Methods: An extensive literature review was conducted, and clinical parameters for related comorbidities, such as diabetes, obesity, as well as PCa, were collected. Such parameters were chosen with the understanding that variations in their threshold values could hasten the complicated process of carcinogenesis, more particularly PCa. The gathered data was converted to semi-binary data (-1, -0.5, 0, 0.5, and 1), on which machine learning (ML) methods were applied. First, we cross-checked various publicly available datasets, some published RNA-seq datasets, and our whole-exome sequencing data to find common role players in PCa, diabetes, and obesity. To narrow down their common interacting partners, interactome networks were analysed using GeneMANIA and visualised using Cytoscape, and later cBioportal was used (to compare expression level based on Z scored values) wherein various types of mutation w.r.t their expression and mRNA expression (RNA seq FPKM) plots are available. The GEPIA 2 tool was used to compare the expression of resulting similarities between the normal tissue and TCGA databases of PCa. Later, top-ranking genes were chosen to demonstrate striking clustering coefficients using the Cytoscape-cytoHubba module, and GEPIA 2 was applied again to ascertain survival plots. Results: Comparing various publicly available datasets, it was found that BLM is a frequent player in all three diseases, whereas comparing publicly available datasets, GWAS datasets, and published sequencing findings, SPFTPC and PPIMB were found to be the most common. With the assistance of GeneMANIA, TMPO and FOXP1 were found as common interacting partners, and they were also seen participating with BLM. Conclusion: A probabilistic machine learning model was achieved to identify key candidates between diabetes, obesity, and PCa. This, we believe, would herald precision scale modeling for easy prognosis.
{"title":"Identification of Plausible Candidates in Prostate Cancer Using Integrated Machine Learning Approaches","authors":"Bhumandeep Kour, Nidhi Shukla, Harshita Bhargava, Devendra Sharma, Amita Sharma, Jayaraman Valadi, TC Sadasukhi, Sugunakar Vuree, Prashanth Suravajhala","doi":"10.2174/0113892029240239231109082805","DOIUrl":"https://doi.org/10.2174/0113892029240239231109082805","url":null,"abstract":"Background: Currently, prostate-specific antigen (PSA) is commonly used as a prostate cancer (PCa) biomarker. PSA is linked to some factors that frequently lead to erroneous positive results or even needless biopsies of elderly people. Objectives: In this pilot study, we undermined the potential genes and mutations from several databases and checked whether or not any putative prognostic biomarkers are central to the annotation. The aim of the study was to develop a risk prediction model that could help in clinical decision-making. Methods: An extensive literature review was conducted, and clinical parameters for related comorbidities, such as diabetes, obesity, as well as PCa, were collected. Such parameters were chosen with the understanding that variations in their threshold values could hasten the complicated process of carcinogenesis, more particularly PCa. The gathered data was converted to semi-binary data (-1, -0.5, 0, 0.5, and 1), on which machine learning (ML) methods were applied. First, we cross-checked various publicly available datasets, some published RNA-seq datasets, and our whole-exome sequencing data to find common role players in PCa, diabetes, and obesity. To narrow down their common interacting partners, interactome networks were analysed using GeneMANIA and visualised using Cytoscape, and later cBioportal was used (to compare expression level based on Z scored values) wherein various types of mutation w.r.t their expression and mRNA expression (RNA seq FPKM) plots are available. The GEPIA 2 tool was used to compare the expression of resulting similarities between the normal tissue and TCGA databases of PCa. Later, top-ranking genes were chosen to demonstrate striking clustering coefficients using the Cytoscape-cytoHubba module, and GEPIA 2 was applied again to ascertain survival plots. Results: Comparing various publicly available datasets, it was found that BLM is a frequent player in all three diseases, whereas comparing publicly available datasets, GWAS datasets, and published sequencing findings, SPFTPC and PPIMB were found to be the most common. With the assistance of GeneMANIA, TMPO and FOXP1 were found as common interacting partners, and they were also seen participating with BLM. Conclusion: A probabilistic machine learning model was achieved to identify key candidates between diabetes, obesity, and PCa. This, we believe, would herald precision scale modeling for easy prognosis.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138524455","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 : 2023-11-22DOI: 10.2174/1389202924666230823094608
Xiaofeng Du, Donald P McManus, Juliet D French, Haran Sivakumaran, Rebecca L Johnston, Olga Kondrashova, Conor E Fogarty, Malcolm K Jones, Hong You
Background: Recent studies on CRISPR/Cas9-mediated gene editing in Schistosoma mansoni have shed new light on the study and control of this parasitic helminth. However, the gene editing efficiency in this parasite is modest.
Methods: To improve the efficiency of CRISPR/Cas9 genome editing in schistosomes, we used lentivirus, which has been effectively used for gene editing in mammalian cells, to deliver plasmid DNA encoding Cas9 nuclease, a sgRNA targeting acetylcholinesterase (SmAChE) and a mCherry fluorescence marker into schistosomes.
Results: MCherry fluorescence was observed in transduced eggs, schistosomula, and adult worms, indicating that the CRISPR components had been delivered into these parasite stages by lentivirus. In addition, clearly changed phenotypes were observed in SmAChE-edited parasites, including decreased SmAChE activity, reduced hatching ability of edited eggs, and altered behavior of miracidia hatched from edited eggs. Next-generation sequencing analysis demonstrated that the lentiviral transduction-based CRISPR/Cas9 gene modifications in SmAChE-edited schistosomes were homology-directed repair predominant but with much lower efficiency than that obtained using electroporation (data previously published by our laboratory) for the delivery of CRISPR components.
Conclusion: Taken together, electroporation is more efficient than lentiviral transduction in the delivery of CRISPR/Cas9 into schistosomes for programmed genome editing. The exploration of tactics for enhancing CRISPR/Cas9 gene editing provides the basis for the future improvement of programmed genome editing in S. mansoni.
{"title":"Lentiviral Transduction-based CRISPR/Cas9 Editing of <i>Schistosoma mansoni</i> Acetylcholinesterase.","authors":"Xiaofeng Du, Donald P McManus, Juliet D French, Haran Sivakumaran, Rebecca L Johnston, Olga Kondrashova, Conor E Fogarty, Malcolm K Jones, Hong You","doi":"10.2174/1389202924666230823094608","DOIUrl":"10.2174/1389202924666230823094608","url":null,"abstract":"<p><strong>Background: </strong>Recent studies on CRISPR/Cas9-mediated gene editing in <i>Schistosoma mansoni</i> have shed new light on the study and control of this parasitic helminth. However, the gene editing efficiency in this parasite is modest.</p><p><strong>Methods: </strong>To improve the efficiency of CRISPR/Cas9 genome editing in schistosomes, we used lentivirus, which has been effectively used for gene editing in mammalian cells, to deliver plasmid DNA encoding Cas9 nuclease, a sgRNA targeting acetylcholinesterase (<i>SmAChE</i>) and a mCherry fluorescence marker into schistosomes.</p><p><strong>Results: </strong>MCherry fluorescence was observed in transduced eggs, schistosomula, and adult worms, indicating that the CRISPR components had been delivered into these parasite stages by lentivirus. In addition, clearly changed phenotypes were observed in <i>SmAChE</i>-edited parasites, including decreased <i>SmAChE</i> activity, reduced hatching ability of edited eggs, and altered behavior of miracidia hatched from edited eggs. Next-generation sequencing analysis demonstrated that the lentiviral transduction-based CRISPR/Cas9 gene modifications in <i>SmAChE</i>-edited schistosomes were homology-directed repair predominant but with much lower efficiency than that obtained using electroporation (data previously published by our laboratory) for the delivery of CRISPR components.</p><p><strong>Conclusion: </strong>Taken together, electroporation is more efficient than lentiviral transduction in the delivery of CRISPR/Cas9 into schistosomes for programmed genome editing. The exploration of tactics for enhancing CRISPR/Cas9 gene editing provides the basis for the future improvement of programmed genome editing in <i>S. mansoni</i>.</p>","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10761339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47811375","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 : 2023-11-10DOI: 10.2174/0113892029273388231023072050
Yulin Zhou, Yu Jiang
Abstract: pinal muscular atrophy (SMA) is one of the most common genetic disorders worldwide, and genetic testing plays a key role in its diagnosis and prevention. The last decade has seen a continuous flow of new methods for SMA genetic testing that, along with traditional approaches, have affected clinical practice patterns to some degree. Targeting different application scenarios and selecting the appropriate technique for genetic testing have become priorities for optimizing the clinical pathway for SMA. In this review, we summarize the latest technological innovations in genetic testing for SMA, including MassArray®, digital PCR (dPCR), next-generation sequencing (NGS), and third-generation sequencing (TGS). Implementation recommendations for rationally choosing different technical strategies in the tertiary prevention of SMA are also explored.
{"title":"Current Advances in Genetic Testing for Spinal Muscular Atrophy","authors":"Yulin Zhou, Yu Jiang","doi":"10.2174/0113892029273388231023072050","DOIUrl":"https://doi.org/10.2174/0113892029273388231023072050","url":null,"abstract":"Abstract: pinal muscular atrophy (SMA) is one of the most common genetic disorders worldwide, and genetic testing plays a key role in its diagnosis and prevention. The last decade has seen a continuous flow of new methods for SMA genetic testing that, along with traditional approaches, have affected clinical practice patterns to some degree. Targeting different application scenarios and selecting the appropriate technique for genetic testing have become priorities for optimizing the clinical pathway for SMA. In this review, we summarize the latest technological innovations in genetic testing for SMA, including MassArray®, digital PCR (dPCR), next-generation sequencing (NGS), and third-generation sequencing (TGS). Implementation recommendations for rationally choosing different technical strategies in the tertiary prevention of SMA are also explored.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135136664","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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