Pub Date : 2025-10-24DOI: 10.1016/j.humgen.2025.201498
Javad Omidi
MicroRNAs (miRNAs) are key regulators of post-transcriptional gene expression and have been increasingly implicated in the pathogenesis of rare malignancies such as adrenocortical carcinoma (ACC). Here, a systems biology approach was employed to construct and analyze context-specific competing endogenous RNA (ceRNA) networks using transcriptomic profiles from ACC tumors (TCGA) and normal adrenal tissues obtained from both GTEx 2025 and miRNATissueAtlas 2025 datasets, leveraging a novel integrative analytical framework specifically developed in this study. Comparative network topology revealed extensive regulatory rewiring in tumors, with miR-507 and miR-665 emerging as tumor-specific central miRNAs. While miR-507 was significantly upregulated and associated with favorable patient survival, miR-665 was downregulated and displayed radiation-sensitive expression dynamics. Target gene prediction and correlation analyses identified distinct sets of oncogenic and tumor-suppressive genes regulated by each miRNA. Functional enrichment and PPI network analysis indicated that miR-507 targets are strongly enriched in cell cycle, mitotic checkpoint, and chromosomal stability pathways, whereas miR-665 influences more context-dependent immune and signaling mechanisms. These findings support the prognostic and therapeutic potential of miR-507 in ACC and suggest a radiotherapy-modulated regulatory role for miR-665. This study demonstrates the power of multi-source transcriptomic integration for discovering functional miRNA hubs in rare endocrine cancers.
{"title":"miR-507 and miR-665 as central MicroRNA regulators in the ceRNA network of adrenocortical carcinoma: A systems biology approach","authors":"Javad Omidi","doi":"10.1016/j.humgen.2025.201498","DOIUrl":"10.1016/j.humgen.2025.201498","url":null,"abstract":"<div><div>MicroRNAs (miRNAs) are key regulators of post-transcriptional gene expression and have been increasingly implicated in the pathogenesis of rare malignancies such as adrenocortical carcinoma (ACC). Here, a systems biology approach was employed to construct and analyze context-specific competing endogenous RNA (ceRNA) networks using transcriptomic profiles from ACC tumors (TCGA) and normal adrenal tissues obtained from both GTEx 2025 and miRNATissueAtlas 2025 datasets, leveraging a novel integrative analytical framework specifically developed in this study. Comparative network topology revealed extensive regulatory rewiring in tumors, with miR-507 and miR-665 emerging as tumor-specific central miRNAs. While miR-507 was significantly upregulated and associated with favorable patient survival, miR-665 was downregulated and displayed radiation-sensitive expression dynamics. Target gene prediction and correlation analyses identified distinct sets of oncogenic and tumor-suppressive genes regulated by each miRNA. Functional enrichment and PPI network analysis indicated that miR-507 targets are strongly enriched in cell cycle, mitotic checkpoint, and chromosomal stability pathways, whereas miR-665 influences more context-dependent immune and signaling mechanisms. These findings support the prognostic and therapeutic potential of miR-507 in ACC and suggest a radiotherapy-modulated regulatory role for miR-665. This study demonstrates the power of multi-source transcriptomic integration for discovering functional miRNA hubs in rare endocrine cancers.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201498"},"PeriodicalIF":0.7,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder with significant metabolic, reproductive, and psychological effects. Emerging research indicates that the disruption of circadian rhythm significantly contributes to the onset and progression of PCOS, a feature that has been insufficiently addressed. This paper presents a distinctive and comprehensive exploration of how circadian discordance, through clock gene dysregulation, sleep-wake disturbances, and external factors such as shift work, contributes to the pathophysiology of the polygenic disorder known as PCOS. This review is distinctive in that it offers opportunities to synthesize knowledge in the molecular biology of insulin processes, endocrinology, and behavioral sciences concerning circadian rhythms, insulin sensitivity, glucose metabolism, regulation of reproductive hormones, and mental health outcomes, in contrast to the prior literature. The article is organized into sections that address the molecular basis of circadian imbalance, its impact on the hypothalamic-pituitary-ovarian (HPO) axis, and its psychological implications, including persistent mood disorders and cognitive impairments. Furthermore, it introduces the novel potential of chronotherapy and circadian-based lifestyle modifications as systemic therapeutic alternatives. This review advances the understanding of circadian biology in PCOS by integrating a multidisciplinary body of knowledge, addressing research gaps, and proposing a new avenue of investigation into therapeutic strategies focused on circadian alignment to improve patient outcomes in PCOS.
{"title":"Polycystic ovary syndrome and the circadian clock: Understanding the link between metabolism, hormones, and sleep","authors":"Chaitanya Sree Somala , Thirunavukarasou Anand , Konda Mani Saravanan , Damal Chandrasekar Mathangi","doi":"10.1016/j.humgen.2025.201497","DOIUrl":"10.1016/j.humgen.2025.201497","url":null,"abstract":"<div><div>Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder with significant metabolic, reproductive, and psychological effects. Emerging research indicates that the disruption of circadian rhythm significantly contributes to the onset and progression of PCOS, a feature that has been insufficiently addressed. This paper presents a distinctive and comprehensive exploration of how circadian discordance, through clock gene dysregulation, sleep-wake disturbances, and external factors such as shift work, contributes to the pathophysiology of the polygenic disorder known as PCOS. This review is distinctive in that it offers opportunities to synthesize knowledge in the molecular biology of insulin processes, endocrinology, and behavioral sciences concerning circadian rhythms, insulin sensitivity, glucose metabolism, regulation of reproductive hormones, and mental health outcomes, in contrast to the prior literature. The article is organized into sections that address the molecular basis of circadian imbalance, its impact on the hypothalamic-pituitary-ovarian (HPO) axis, and its psychological implications, including persistent mood disorders and cognitive impairments. Furthermore, it introduces the novel potential of chronotherapy and circadian-based lifestyle modifications as systemic therapeutic alternatives. This review advances the understanding of circadian biology in PCOS by integrating a multidisciplinary body of knowledge, addressing research gaps, and proposing a new avenue of investigation into therapeutic strategies focused on circadian alignment to improve patient outcomes in PCOS.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201497"},"PeriodicalIF":0.7,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Defining the etiology of multifactorial diseases, such as Parkinson's disease (PD), poses significant challenges in diagnosis, management, and treatment strategies. PD is characterized by progressive neurological degeneration. Current scientific evidence indicates that this condition arises from an intricate interplay of genetic and environmental factors. Notably, single nucleotide polymorphisms (SNPs) identified in various genes have been implicated in enhancing susceptibility to this disease. This study aims to investigate the association of two specific polymorphisms, IL-10 gene; −1087 G > A and mir146a gene; rs2910164 C > G, with the prevalence of PD.
Methods
This investigation employed a case-control design that included 96 participants in both the case and control groups. The identification of alleles was executed using the Tetra-primer Amplification Refractory Mutation System-Polymerase Chain Reaction (T-ARMS-PCR) method. Subsequent genetic and statistical analyses of the findings were performed utilizing POPGENE and SPSS software.
Result
The results indicated that the distribution of mir146a gene SNPs within the control and patient populations did not adhere to Hardy-Weinberg equilibrium. Specifically, the frequency of the G allele in patients diagnosed with PD was significantly lower than that observed in the control cohort. Furthermore, individuals carrying the GC genotype exhibited an elevated risk of developing PD, with p-values <0.05. Conversely, the distribution of IL-10 gene SNPs conformed to Hardy-Weinberg equilibrium within both groups, and no statistically significant association was found between IL-10 gene SNPs and the risk of PD.
Conclusion
The findings from this study suggest that the IL-10 gene −1087 G > A polymorphism does not contribute to increased susceptibility to PD within the studied population. Conversely, the mir146a gene rs2910164 C > G polymorphism appears to be associated with PD risk. Notably, the G allele of this SNP correlates with a decreased risk of the disease, while the GC genotype is linked to an increased likelihood of developing Parkinson's disease.
定义多因素疾病的病因，如帕金森病（PD），在诊断、管理和治疗策略方面提出了重大挑战。PD以进行性神经变性为特征。目前的科学证据表明，这种情况是由遗传和环境因素复杂的相互作用引起的。值得注意的是，在各种基因中发现的单核苷酸多态性（SNPs）与增加对这种疾病的易感性有关。本研究旨在探讨两种特定多态性的关联，IL-10基因；−1087 G >； A和mir146a基因；rs2910164 C >； G，与PD患病率相关。方法本研究采用病例-对照设计，病例组和对照组各96例。等位基因鉴定采用四引物扩增难突变系统-聚合酶链反应（T-ARMS-PCR）方法。随后使用POPGENE和SPSS软件对结果进行遗传和统计分析。结果mir146a基因snp在对照组和患者群体中的分布不符合Hardy-Weinberg平衡。具体来说，诊断为PD的患者中G等位基因的频率明显低于对照组。此外，携带GC基因型的个体患PD的风险增加，p值为<；0.05。相反，IL-10基因snp在两组内的分布符合Hardy-Weinberg平衡，IL-10基因snp与PD风险之间无统计学意义的关联。结论IL-10基因- 1087 G >； A多态性与研究人群PD易感性增加无关。相反，mir146a基因rs2910164 C >； G多态性似乎与PD风险相关。值得注意的是，该SNP的G等位基因与疾病风险降低相关，而GC基因型与患帕金森病的可能性增加相关。
{"title":"Exploring genetic associations in Parkinson's disease: The role of IL-10; −1087G>a and mir146a; rs2910164 C>G polymorphisms","authors":"Javid Ashtari Mahini , Zahra Shahbazi , Maryam Rahimi , Maryam Seyedolmohadesin","doi":"10.1016/j.humgen.2025.201493","DOIUrl":"10.1016/j.humgen.2025.201493","url":null,"abstract":"<div><h3>Introduction</h3><div>Defining the etiology of multifactorial diseases, such as Parkinson's disease (PD), poses significant challenges in diagnosis, management, and treatment strategies. PD is characterized by progressive neurological degeneration. Current scientific evidence indicates that this condition arises from an intricate interplay of genetic and environmental factors. Notably, single nucleotide polymorphisms (SNPs) identified in various genes have been implicated in enhancing susceptibility to this disease. This study aims to investigate the association of two specific polymorphisms, <em>IL-10</em> gene; −1087 G > A and <em>mir146a</em> gene<em>;</em> rs2910164 C > G, with the prevalence of PD.</div></div><div><h3>Methods</h3><div>This investigation employed a case-control design that included 96 participants in both the case and control groups. The identification of alleles was executed using the Tetra-primer Amplification Refractory Mutation System-Polymerase Chain Reaction (T-ARMS-PCR) method. Subsequent genetic and statistical analyses of the findings were performed utilizing POPGENE and SPSS software.</div></div><div><h3>Result</h3><div>The results indicated that the distribution of <em>mir146a</em> gene SNPs within the control and patient populations did not adhere to Hardy-Weinberg equilibrium. Specifically, the frequency of the G allele in patients diagnosed with PD was significantly lower than that observed in the control cohort. Furthermore, individuals carrying the GC genotype exhibited an elevated risk of developing PD, with <em>p</em>-values <0.05. Conversely, the distribution of <em>IL-10</em> gene SNPs conformed to Hardy-Weinberg equilibrium within both groups, and no statistically significant association was found between <em>IL-10</em> gene SNPs and the risk of PD.</div></div><div><h3>Conclusion</h3><div>The findings from this study suggest that the <em>IL-10</em> gene −1087 G > A polymorphism does not contribute to increased susceptibility to PD within the studied population. Conversely, the <em>mir146a</em> gene rs2910164 C > G polymorphism appears to be associated with PD risk. Notably, the G allele of this SNP correlates with a decreased risk of the disease, while the GC genotype is linked to an increased likelihood of developing Parkinson's disease.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201493"},"PeriodicalIF":0.7,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-13DOI: 10.1016/j.humgen.2025.201495
Joseph Faith
{"title":"Commentary on Livni & Skorecki, “Distinguishing between Founder and Host Population mtDNA Lineages in the Ashkenazi Population”","authors":"Joseph Faith","doi":"10.1016/j.humgen.2025.201495","DOIUrl":"10.1016/j.humgen.2025.201495","url":null,"abstract":"","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201495"},"PeriodicalIF":0.7,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145319601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-13DOI: 10.1016/j.humgen.2025.201494
Ankur Datta , Esther Graceia Precious A , Akshata Shetty , Sridhar Raj S , George Priya Doss C
Diagnosing Pancreatic Cancer (PC) remains a formidable challenge for both clinicians and biomedical researchers due to its complex pathophysiology and late-stage detection. Although numerous investigations have elucidated key molecular pathways implicated in PC progression, this study advances the diagnostic paradigm by leveraging integrative transcriptomic analysis through sophisticated machine learning (ML) methodologies, notably LASSO regression and XGBoost. The closed-box characteristic of the XGBoost ML algorithm was resolved using the eXplainable artificial intelligence (XAI) based SHAP architecture. Data concerning gene expression profiles, mapped via microarray assays, from multiple datasets were retrieved and processed. A high-dimensional dataframe comprising 18,156 gene features for 464 patients was subjected to dimensionality reduction via LASSO regression to identify significant gene(s). The expression profiles of the 281 genes identified by LASSO were used to train the XGBoost disease classifier model, with an 80:20 train: test ratio. Conducting a 10-fold cross-validation yielded an average accuracy of 85 % for the XGBoost ML model. The SHAP framework highlighted the top gene features contributing to the decision-making of the XGBoost disease classifier model. The LASSO identified gene features were then biologically annotated to unravel the underlying mechanisms associated with PC disease. The proposed workflow, implemented in the current study, aims to enhance the existing landscape of PC diagnosis, reduce the rate of false positives typically observed with microarray-based techniques, and provide a strong foundation for computational studies with promising aspects for future cancer diagnostics and therapeutics.
{"title":"Utilizing explainable AI to decipher transcriptomic alterations in pancreatic cancer","authors":"Ankur Datta , Esther Graceia Precious A , Akshata Shetty , Sridhar Raj S , George Priya Doss C","doi":"10.1016/j.humgen.2025.201494","DOIUrl":"10.1016/j.humgen.2025.201494","url":null,"abstract":"<div><div>Diagnosing Pancreatic Cancer (PC) remains a formidable challenge for both clinicians and biomedical researchers due to its complex pathophysiology and late-stage detection. Although numerous investigations have elucidated key molecular pathways implicated in PC progression, this study advances the diagnostic paradigm by leveraging integrative transcriptomic analysis through sophisticated machine learning (ML) methodologies, notably LASSO regression and XGBoost. The closed-box characteristic of the XGBoost ML algorithm was resolved using the eXplainable artificial intelligence (XAI) based SHAP architecture. Data concerning gene expression profiles, mapped via microarray assays, from multiple datasets were retrieved and processed. A high-dimensional dataframe comprising 18,156 gene features for 464 patients was subjected to dimensionality reduction via LASSO regression to identify significant gene(s). The expression profiles of the 281 genes identified by LASSO were used to train the XGBoost disease classifier model, with an 80:20 train: test ratio. Conducting a 10-fold cross-validation yielded an average accuracy of 85 % for the XGBoost ML model. The SHAP framework highlighted the top gene features contributing to the decision-making of the XGBoost disease classifier model. The LASSO identified gene features were then biologically annotated to unravel the underlying mechanisms associated with PC disease. The proposed workflow, implemented in the current study, aims to enhance the existing landscape of PC diagnosis, reduce the rate of false positives typically observed with microarray-based techniques, and provide a strong foundation for computational studies with promising aspects for future cancer diagnostics and therapeutics.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201494"},"PeriodicalIF":0.7,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145319599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-13DOI: 10.1016/j.humgen.2025.201489
Nimisha Ghosh , Walter Arancio , Tariq Al Jabry , Raya Al Maskari , Daniele Santoni
Autism Spectrum Disorders (ASD) encompass a group of neurodevelopmental disorders in which an affected individual faces challenges in social interaction and communication, along with restricted and repetitive stereotypic behavioral patterns and interests. In this work, we have studied the differential gene regulation between patients and controls, mediated by Transcription Factors (TFs), of key genes involved in ASD. Nine and seven TFs have been identified as potential regulators of the set of syndromic and non-syndromic key high confident genes retrieved by the Simons Foundation Autism Research Initiative (SFARI) database. We have also identified significant couples of Transcription Factor - Target Gene potentially associated with an altered regulation in ASD patients. Consistently, many identified couples are involved in processes associated with brain morphogenesis and development. In this regard, this biased regulation could be the target of some experimental design in order to (1) test this hypothesis and (2) try to target this altered regulation pattern in ASD samples. In conclusion, we would like to emphasize that the present work proposes an effective and reliable computational approach that could be applied to any disease with known key genes and available gene expression data.
{"title":"Transcription Factor driven gene regulation in Autism Spectrum Disorder","authors":"Nimisha Ghosh , Walter Arancio , Tariq Al Jabry , Raya Al Maskari , Daniele Santoni","doi":"10.1016/j.humgen.2025.201489","DOIUrl":"10.1016/j.humgen.2025.201489","url":null,"abstract":"<div><div>Autism Spectrum Disorders (ASD) encompass a group of neurodevelopmental disorders in which an affected individual faces challenges in social interaction and communication, along with restricted and repetitive stereotypic behavioral patterns and interests. In this work, we have studied the differential gene regulation between patients and controls, mediated by Transcription Factors (TFs), of key genes involved in ASD. Nine and seven TFs have been identified as potential regulators of the set of syndromic and non-syndromic key high confident genes retrieved by the Simons Foundation Autism Research Initiative (SFARI) database. We have also identified significant couples of Transcription Factor - Target Gene potentially associated with an altered regulation in ASD patients. Consistently, many identified couples are involved in processes associated with brain morphogenesis and development. In this regard, this biased regulation could be the target of some experimental design in order to (1) test this hypothesis and (2) try to target this altered regulation pattern in ASD samples. In conclusion, we would like to emphasize that the present work proposes an effective and reliable computational approach that could be applied to any disease with known key genes and available gene expression data.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201489"},"PeriodicalIF":0.7,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145319598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-03DOI: 10.1016/j.humgen.2025.201487
Raushan Kumar Chaudhary , Allen Pinto , Niyas Rehman , Debodipta Das , Rajesh Raju
YES1 is a novel proto-oncogene that has largely gained popularity in oncology over the last few years owing to its pivotal role in tumorigenesis, and drug resistance to various targeted therapy (EGFR, HER2) and cancer chemotherapy, resulting in poor survival outcomes, which has been frequently linked with its amplification rather than the mutation. Thus, this study hypothesizes that cancer development might also be linked with a mutation in YES1, not merely amplification of the gene. In the present study, YES1 gene-associated missense SNPs were retrieved from the dbSNP-NCBI database, which were screened for deleterious/damaging and pathogenicity. The pathogenic SNPs were assessed for their stability and potential to cause cancer. The oncogenic SNPs were further evaluated for its location in the domain, conservation, structural effect, and interactions. Further, YES1 expression in cancer, its hallmark efficiency and mutation in cancer was assessed to support the study findings. A total of 381 SNPs were identified from dbSNP-NCBI of which 7 SNPs were found to be deleterious, damaging and pathogenic by applying six tools. Out of these 7 SNPs, YES1 c.596C>T (p.Arg199His) and YES1 c.868C>T (p.Glu290Lys) were predicted destabilize the protein and associated with blood cancer, and solid cancer like reproductive organ cancer, and gastrointestinal (GI) cancer respectively. Both these oncogenic SNPs occurs in core biologically active conserved domain (SH2 and tyrosine kinase) of YES1 protein thereby influences the protein geometry, electrostatic interaction, impairs the ATP/substrate binding and kinase activity of the protein which might dysregulate the protein-protein interaction and modulate various cancer pathways. Further, its significant expression in cancer (hematologic, reproductive and GI cancer), role in driving invasion/metastasis, and evidence of YES1 mutation profile in cancer cohort strengthen the findings of current study. Thus, R199H and E290K SNPs are the most probable SNPs that should be screened among cancer patients to establish a plausible link which can guide towards the precision therapy to counter the drug resistance and enhance the clinical benefit in upcoming years.
YES1是一种新的原癌基因，由于其在肿瘤发生中的关键作用，以及对各种靶向治疗（EGFR, HER2）和癌症化疗的耐药性，在过去几年中在肿瘤学中得到了很大程度上的普及，导致生存结果较差，这通常与其扩增而不是突变有关。因此，这项研究假设癌症的发展也可能与YES1的突变有关，而不仅仅是基因的扩增。在本研究中，从dbSNP-NCBI数据库中检索YES1基因相关错义snp，并对其进行有害/破坏性和致病性筛选。对致病性snp的稳定性和致癌潜力进行了评估。我们进一步评估了这些致癌snp在结构域的位置、保守性、结构效应和相互作用。此外，我们还评估了YES1在癌症中的表达、其在癌症中的标志效率和突变，以支持研究结果。应用6种工具从dbSNP-NCBI中共鉴定出381个snp，其中7个snp为有害、破坏性和致病性snp。在这7个snp中，预计YES1 c.596C > T （p.a arg199his）和YES1 c.868C > T （p.g glu290lys）会破坏该蛋白的稳定性，并分别与血癌、生殖器官癌和胃肠道（GI）癌等实体癌相关。这两种致癌snp都发生在YES1蛋白的核心生物活性保守结构域（SH2和酪氨酸激酶），从而影响蛋白质的几何形状、静电相互作用、损害蛋白质的ATP/底物结合和激酶活性，从而可能失调蛋白质-蛋白质相互作用并调节各种癌症途径。此外，它在癌症（血液癌、生殖癌和胃肠道癌）中的显著表达，在驱动侵袭/转移中的作用，以及在癌症队列中存在YES1突变谱的证据，加强了本研究的发现。因此，R199H和E290K snp是最可能在癌症患者中筛选的snp，以建立合理的联系，指导精准治疗，对抗耐药，提高临床获益。
{"title":"YES1 c.596C>T (p.Arg199His) and YES1 c.868C>T (p.Glu290Lys) missense polymorphism linked to hematological and reproductive organ cancer: A hidden Markov model (HMM) based approach","authors":"Raushan Kumar Chaudhary , Allen Pinto , Niyas Rehman , Debodipta Das , Rajesh Raju","doi":"10.1016/j.humgen.2025.201487","DOIUrl":"10.1016/j.humgen.2025.201487","url":null,"abstract":"<div><div><em>YES1</em> is a novel proto-oncogene that has largely gained popularity in oncology over the last few years owing to its pivotal role in tumorigenesis, and drug resistance to various targeted therapy (<em>EGFR, HER2</em>) and cancer chemotherapy, resulting in poor survival outcomes, which has been frequently linked with its amplification rather than the mutation. Thus, this study hypothesizes that cancer development might also be linked with a mutation in <em>YES1,</em> not merely amplification of the gene. In the present study, <em>YES1</em> gene-associated missense SNPs were retrieved from the dbSNP-NCBI database, which were screened for deleterious/damaging and pathogenicity. The pathogenic SNPs were assessed for their stability and potential to cause cancer. The oncogenic SNPs were further evaluated for its location in the domain, conservation, structural effect, and interactions. Further, <em>YES1</em> expression in cancer, its hallmark efficiency and mutation in cancer was assessed to support the study findings. A total of 381 SNPs were identified from dbSNP-NCBI of which 7 SNPs were found to be deleterious, damaging and pathogenic by applying six tools. Out of these 7 SNPs, <em>YES1 c.596C</em> <em>></em> <em>T (p.Arg199His)</em> and <em>YES1 c.868C</em> <em>></em> <em>T (p.Glu290Lys)</em> were predicted destabilize the protein and associated with blood cancer, and solid cancer like reproductive organ cancer, and gastrointestinal (GI) cancer respectively. Both these oncogenic SNPs occurs in core biologically active conserved domain (SH2 and tyrosine kinase) of <em>YES1</em> protein thereby influences the protein geometry, electrostatic interaction, impairs the ATP/substrate binding and kinase activity of the protein which might dysregulate the protein-protein interaction and modulate various cancer pathways. Further, its significant expression in cancer (hematologic, reproductive and GI cancer), role in driving invasion/metastasis, and evidence of <em>YES1</em> mutation profile in cancer cohort strengthen the findings of current study. Thus, R199H and E290K SNPs are the most probable SNPs that should be screened among cancer patients to establish a plausible link which can guide towards the precision therapy to counter the drug resistance and enhance the clinical benefit in upcoming years.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201487"},"PeriodicalIF":0.7,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MicroRNAs (miRNAs) have pivotal role in post-transcriptional gene regulation by binding to target mRNAs, resulting in their degradation or translational repression. They contribute to the pathogenesis of several disorders, including cancer, autoimmune conditions and metabolic disorders. Among these non-coding transcripts is miR-576, a miRNA with dual roles in tumorigenesis and significant participation in non-malignant conditions. Through modulation of key cellular processes such as proliferation, apoptosis, migration, and immune responses, this miRNA participates in the pathoetiology of a variety of human disorders. This manuscript aims to comprehensively review the current understanding of miR-576 in malignant and non-malignant disorders, emphasizing its mechanistic roles, clinical implications, and therapeutic potential. By integrating the current knowledge on its role, we offer insights into the dual nature of miR-576 in disease pathogenesis and discover future directions for research and therapeutic development.
{"title":"A review on the role of miR-576 in human disorders","authors":"Alireza Soleimani , Mohsen Ahmadi , Mahla Sanati , Hadi Adabi , Soudeh Ghafouri-Fard","doi":"10.1016/j.humgen.2025.201491","DOIUrl":"10.1016/j.humgen.2025.201491","url":null,"abstract":"<div><div>MicroRNAs (miRNAs) have pivotal role in post-transcriptional gene regulation by binding to target mRNAs, resulting in their degradation or translational repression. They contribute to the pathogenesis of several disorders, including cancer, autoimmune conditions and metabolic disorders. Among these non-coding transcripts is miR-576, a miRNA with dual roles in tumorigenesis and significant participation in non-malignant conditions. Through modulation of key cellular processes such as proliferation, apoptosis, migration, and immune responses, this miRNA participates in the pathoetiology of a variety of human disorders. This manuscript aims to comprehensively review the current understanding of miR-576 in malignant and non-malignant disorders, emphasizing its mechanistic roles, clinical implications, and therapeutic potential. By integrating the current knowledge on its role, we offer insights into the dual nature of miR-576 in disease pathogenesis and discover future directions for research and therapeutic development.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201491"},"PeriodicalIF":0.7,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MAGEA3, a cancer-testis antigen selectively expressed in tumors, has been widely explored as a target for cancer immunotherapy, yet its broader immunoregulatory function in the lung tumor microenvironment remains insufficiently characterized. In this study, we conducted an integrative in silico analysis using transcriptomic data from TCGA-LUSC to delineate the expression landscape, immune contexture, and molecular interactions of MAGEA3. Protein–protein interaction networks constructed via STRING and ranked through CytoHubba identified TRIM28 and HLA-A as key co-regulatory molecules, implicating MAGEA3 in transcriptional repression and antigen presentation. TIMER2.0 deconvolution revealed cell-type–specific associations, including differential relationships with CD8+ T cells, dendritic cells, and macrophages. Gene-wise survival modeling in TCGA-LUSC indicated MAGEA3 and MAGEA6 associate with reduced overall survival, whereas TRIM28 showed a borderline protective trend. Experimental validation via RT-qPCR in A549 cells confirmed detectable expression of MAGEA3, TRIM28, and HLA-A, reinforcing the computational predictions and highlighting potential cross-histological relevance. Collectively, these findings position MAGEA3 within immunomodulatory circuits of lung cancer and support its consideration in multimodal immunotherapeutic paradigms.
{"title":"Integrated in silico and experimental analysis identifies MAGE-A3, TRIM28, and HLA-A as immunomodulatory targets in lung cancer","authors":"Gaurang Telang , Smriti Mishra , Anurag Sureshbabu , Sagar Barage , A.W. Santhosh Kumar , Rajshri Singh","doi":"10.1016/j.humgen.2025.201492","DOIUrl":"10.1016/j.humgen.2025.201492","url":null,"abstract":"<div><div>MAGEA3, a cancer-testis antigen selectively expressed in tumors, has been widely explored as a target for cancer immunotherapy, yet its broader immunoregulatory function in the lung tumor microenvironment remains insufficiently characterized. In this study, we conducted an integrative in silico analysis using transcriptomic data from TCGA-LUSC to delineate the expression landscape, immune contexture, and molecular interactions of MAGEA3. Protein–protein interaction networks constructed via STRING and ranked through CytoHubba identified TRIM28 and HLA-A as key co-regulatory molecules, implicating MAGEA3 in transcriptional repression and antigen presentation. TIMER2.0 deconvolution revealed cell-type–specific associations, including differential relationships with CD8<sup>+</sup> T cells, dendritic cells, and macrophages. Gene-wise survival modeling in TCGA-LUSC indicated MAGEA3 and MAGEA6 associate with reduced overall survival, whereas TRIM28 showed a borderline protective trend. Experimental validation via RT-qPCR in A549 cells confirmed detectable expression of MAGEA3, TRIM28, and HLA-A, reinforcing the computational predictions and highlighting potential cross-histological relevance. Collectively, these findings position MAGEA3 within immunomodulatory circuits of lung cancer and support its consideration in multimodal immunotherapeutic paradigms.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201492"},"PeriodicalIF":0.7,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-29DOI: 10.1016/j.humgen.2025.201490
Amir Mohammad Mazhari , Farshad Safaei , Mahsa Torkamanian-Afshar , Ali Najafi
Background
The Gene Expression Omnibus (GEO) database was established by the National Center for Biotechnology Information (NCBI) to facilitate sharing molecular biology data. This repository hosts numerous datasets related to complex diseases such as cancer, generated by researchers worldwide. One of the most challenging issues is finding non-invasive biomarkers in the vast amount of data deposited in public databases related to a specific type of cancer.
Results
To address this issue, we have designed a Liquid Biopsy Biomarker Discovery (LiqBiMark) pipeline that compares two datasets on the same type of cancer, but with different sample sources, to propose potential biomarker candidates. Additionally, the LiqBiMark generates co-expression networks and conducts clustering analysis.
Conclusions
The pipeline is designed to be accessible even to users with minimal experience, allowing them to obtain results quickly and efficiently.
{"title":"LiqBiMark: An advanced bioinformatics pipeline for integrative transcriptomic analysis and identification of non-invasive prognostic biomarkers using GEO datasets","authors":"Amir Mohammad Mazhari , Farshad Safaei , Mahsa Torkamanian-Afshar , Ali Najafi","doi":"10.1016/j.humgen.2025.201490","DOIUrl":"10.1016/j.humgen.2025.201490","url":null,"abstract":"<div><h3>Background</h3><div>The Gene Expression Omnibus (GEO) database was established by the National Center for Biotechnology Information (NCBI) to facilitate sharing molecular biology data. This repository hosts numerous datasets related to complex diseases such as cancer, generated by researchers worldwide. One of the most challenging issues is finding non-invasive biomarkers in the vast amount of data deposited in public databases related to a specific type of cancer.</div></div><div><h3>Results</h3><div>To address this issue, we have designed a Liquid Biopsy Biomarker Discovery (LiqBiMark) pipeline that compares two datasets on the same type of cancer, but with different sample sources, to propose potential biomarker candidates. Additionally, the LiqBiMark generates co-expression networks and conducts clustering analysis.</div></div><div><h3>Conclusions</h3><div>The pipeline is designed to be accessible even to users with minimal experience, allowing them to obtain results quickly and efficiently.</div></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"46 ","pages":"Article 201490"},"PeriodicalIF":0.7,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145319600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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