Current Issues in Molecular Biology

2025

Jump to: 2024

23 pages, 5795 KB

Open AccessArticle

In Silico Network Pharmacology, Molecular Docking, and Molecular Dynamics Analysis of Rosemary-Derived Compounds as Potential HSP90 Inhibitors for Cancer Therapy

by Radhia Mazri, Mebarka Ouassaf, Afaf Zekri, Shafi Ullah Khan, Kannan R. R. Rengasamy and Bader Y. Alhatlani

Curr. Issues Mol. Biol. 2025, 47(10), 860; https://doi.org/10.3390/cimb47100860 - 18 Oct 2025

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Abstract

Cancer remains a major global health challenge, emphasizing the need for new and effective therapies. This study investigates the anticancer potential of bioactive compounds from rosemary (Rosmarinus officinalis) using an integrative network pharmacology and computational approach. Twelve phytochemicals with favorable pharmacological profiles, optimal [...] Read more.

Cancer remains a major global health challenge, emphasizing the need for new and effective therapies. This study investigates the anticancer potential of bioactive compounds from rosemary (Rosmarinus officinalis) using an integrative network pharmacology and computational approach. Twelve phytochemicals with favorable pharmacological profiles, optimal pharmacokinetics, and acceptable toxicological properties were evaluated, revealing 178 putative cancer-related targets. Protein–protein interaction (PPI) analysis highlighted ten key genes—EGFR, ESR1, HIF1A, HSP90AA1, MAPK1, BCL2, STAT3, TP53, CASP3, and SRC—implicated in the progression of various cancers, including breast, colorectal, liver, and lung tumors. Functional enrichment analysis demonstrated their involvement in multiple cancer-associated pathways. Among these, HSP90AA1 emerged as a critical target. Molecular docking revealed Rosmanol, Chlorogenic acid, and Carnosol as the most promising HSP90AA1 binders with strong predicted affinities. ADMET profiling confirmed their excellent drug-likeness and safety profiles, while molecular dynamics simulations validated the stability of the compound–protein complexes, further supporting their potential as HSP90 inhibitors. These findings suggest that rosemary-derived compounds may represent valuable candidates for anticancer drug development, though experimental validation is required to confirm their therapeutic efficacy. Full article

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15 pages, 1786 KB

Open AccessArticle

Identification and Association of CYP2R1, CYP27B1, and GC Gene Polymorphisms with Vitamin D Deficiency in Apparently Healthy Population and in Silico Analysis of the Binding Pocket of Vitamin D3

by Saima Manzoor, Asifa Majeed, Palvasha Waheed and Amir Rashid

Curr. Issues Mol. Biol. 2025, 47(10), 849; https://doi.org/10.3390/cimb47100849 - 15 Oct 2025

Viewed by 375

Abstract

Vitamin D deficiency is highly prevalent in Pakistan, but there is limited data on its genetic aspects. This case–control pilot study aimed to determine the association of rs782153744, rs200183599, rs118204011, and rs28934604 with vitamin D deficiency along rs7041 which has been studied in [...] Read more.

Vitamin D deficiency is highly prevalent in Pakistan, but there is limited data on its genetic aspects. This case–control pilot study aimed to determine the association of rs782153744, rs200183599, rs118204011, and rs28934604 with vitamin D deficiency along rs7041 which has been studied in our population. The DNA of a total of 600 subjects (300 cases and 300 controls) was extracted and genotyped by tetra ARMS PCR, followed by Sanger DNA sequencing of exon 4 of the CYP2R1 and CYP27B1 genes and exon 8 of the GC gene. SNP Stat was employed to analyze the data, while logistic regression was used to calculate the p-values and odds ratios (ORs). The R package version R studio (2025.05.1) Build 513 was used to statistically analyze rs782153744. In silico modeling of wild and mutant CYP2R1 and GC proteins was performed in Swiss-Model, Swiss-Dock, Discovery Studio, and PyMol using 3c6g and IJ78 as templates to perform binding pocket analysis of vitamin D3. The rs782153744 showed a protective association in the additive (OR: 0.15, 95% CI: 0.08–0.27, p-value < 0.001), recessive (OR: 0.19, 95% CI: 0.10–0.33, p-value < 0.001), and dominant (OR: 0.19, CI = 0.10–0.33, p-value < 0.001) models, while GC rs7041 (T > A, T > G) displayed a p-value < 0.0001 across all genetic models. Sanger sequencing yielded insignificant results, and the SNPs rs200183599, rs118204011, and rs28934604 had no significant association with vitamin D deficiency. The molecular pocket analysis of wild and mutant CYP2R1 proteins carrying rs782153744 polymorphisms revealed no changes. GC proteins carrying the rs7041 polymorphism revealed a shift in their 3D and 2D configuration, as well as a change in the amino acid residue of the binding pocket of VD3. The risk-associated rs7041 and protective rs782153744 variants back genetic screening for vitamin D deficiency risk stratification, allowing targeted supplementation in predisposed subjects and assisting in formulating a genotype-specific therapeutic approach. Full article

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33 pages, 5037 KB

Open AccessArticle

Convergent and Divergent Mitochondrial Pathways as Causal Drivers and Therapeutic Targets in Neurological Disorders

by Yanan Du, Sha-Sha Fan, Hao Wu, Junwen He, Yang He, Xiang-Yu Meng and Xuan Xu

Curr. Issues Mol. Biol. 2025, 47(8), 636; https://doi.org/10.3390/cimb47080636 - 8 Aug 2025

Cited by 1 | Viewed by 1088

Abstract

Mitochondrial dysfunction is implicated across a spectrum of neurological diseases, yet its causal role and mechanistic specificity remain unclear. This study employed a multi-modal integrative analysis of mitochondrial gene expression in Alzheimer’s Disease (AD), Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), and Parkinson’s [...] Read more.

Mitochondrial dysfunction is implicated across a spectrum of neurological diseases, yet its causal role and mechanistic specificity remain unclear. This study employed a multi-modal integrative analysis of mitochondrial gene expression in Alzheimer’s Disease (AD), Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), and Parkinson’s Disease (PD) to address these gaps. We combined machine learning for predictive modeling with genetic causal inference methods (Mendelian Randomization, colocalization, PheWAS), followed by drug enrichment analysis and molecular docking. Our machine learning models, particularly Support Vector Machine and Multi-layer Perceptron, effectively classified these conditions, with MS exhibiting the highest predictability (mean Accuracy: 0.758). Causal inference analyses identified specific gene–disease links; for instance, genetically predicted increased expression of PDK1 was causally associated with an elevated risk for both AD (OR = 1.041) and ALS (OR = 1.037), identifying pyruvate metabolism as a shared vulnerability. In contrast, genes like SLC25A38 emerged as highly predictive specifically for PD. We also observed evidence of potential brain–periphery interaction, such as a bidirectional causal relationship between red blood cell indices and MS risk. Finally, drug enrichment analysis highlighted Celecoxib, and subsequent molecular docking predicted a strong binding affinity to PDK1 (docking score S = −6.522 kcal/mol), generating hypotheses for potential metabolic modulation. Taken together, this study provides a computational hypothesis framework suggesting mitochondrial pathways and targets that warrant future biological validation. This study provides specific, genetically supported evidence for the causal role of mitochondrial pathways in neurological diseases and identifies tangible targets for future therapeutic development. Full article

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16 pages, 5964 KB

Open AccessArticle

Investigating the Mediating Role of Cardiometabolic Traits in the Causal Link Between SHBG Levels and Stroke Risk via Network Mendelian Randomization

by Peijiang Pan, Hao Liang and Mingli Li

Curr. Issues Mol. Biol. 2025, 47(7), 494; https://doi.org/10.3390/cimb47070494 - 27 Jun 2025

Viewed by 613

Abstract

The causal nature of sex hormone-binding globulin (SHBG) in the pathogenesis of stroke remains uncertain. We explored whether SHBG levels are causally associated with stroke via cardiometabolic traits. A network two-sample Mendelian randomization (MR) study was conducted to determine the mediating roles of [...] Read more.

The causal nature of sex hormone-binding globulin (SHBG) in the pathogenesis of stroke remains uncertain. We explored whether SHBG levels are causally associated with stroke via cardiometabolic traits. A network two-sample Mendelian randomization (MR) study was conducted to determine the mediating roles of cardiometabolic traits in the causal effects of SHBG levels on stroke subtypes. Further two-sample MR analyses were performed to explore the inverse associations between significant cardiometabolic mediators and SHBG levels. The MR results indicated a protective effect of genetically increased SHBG levels on any stroke (odd ratio [OR] = 0.941; 95% confidence interval [CI]: 0.898, 0.984), any ischemic stroke (OR = 0.951; 95% CI: 0.922, 0.981), and small-vessel stroke (OR = 0.871; 95% CI: 0.765, 0.977). Moreover, genetically elevated SHBG levels were associated with lower waist circumference (WC, β = −0.091; 95% CI: −0.136, −0.046), waist-to-hip ratio (WHR, β = −0.057; 95% CI: −0.084, −0.030), triglycerides (TG, β = −0.188; 95% CI: −0.249, −0.127), systolic blood pressure (β = −0.799; 95% CI: −1.068, −0.530), and diastolic blood pressure (β = −0.436; 95% CI: −0.605, −0.267), and a reduced risk of type 2 diabetes mellitus (OR = 0.684; 95% CI: 0.400, 0.968) in both the discovery and replication datasets. The proportions of such cardiometabolic traits that mediated the causal effects of SHBG levels on any stroke, any ischemic stroke, or small-vessel stroke ranged from 17.8% to 52.7%; while the mediating effects of SHBG levels on the causal associations between WC, WHR, and TG and stroke ranged from 18.4% to 68.3%. Our findings suggest a protective effect of genetically elevated SHBG levels on stroke risk via key cardiometabolic mediators, primarily WC, WHR, and TG. The mediating roles of SHBG levels in the causal links from WC, WHR and TG to stroke risk were also established. These pathways support SHBG as a potential biomarker and therapeutic target in stroke prevention. Full article

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24 pages, 8367 KB

Open AccessArticle

by Zuming Xiong, Yirong Lin, Yongjun Yang, Wenxin Li, Wei Huang and Sen Zhang

Curr. Issues Mol. Biol. 2025, 47(6), 465; https://doi.org/10.3390/cimb47060465 - 17 Jun 2025

Viewed by 813

Abstract

Expression patterns and underlying mechanisms of metabolism-related genes SMOX and SUCLG2 in pan-cancer remain unclear. We conducted a comprehensive pan-cancer analysis of SMOX and SUCLG2, to explore their potential roles and mechanisms of action. Comprehensive analysis of SMOX and SUCLG2 was performed through [...] Read more.

Expression patterns and underlying mechanisms of metabolism-related genes SMOX and SUCLG2 in pan-cancer remain unclear. We conducted a comprehensive pan-cancer analysis of SMOX and SUCLG2, to explore their potential roles and mechanisms of action. Comprehensive analysis of SMOX and SUCLG2 was performed through UCSC, TCGA, GEO, and other databases. We validated the expression levels, diagnostic value, and prognostic significance of SMOX and SUCLG2 in CRC using external databases and qPCR. Then, CCK-8 is used to detect proliferation of RKO and HCT116 after silencing or overexpressing of SUCLG2. The expression of SMOX was upregulated and that of SUCLG2 was downregulated in most cancers. Both SMOX and SUCLG2 exhibited significant correlations with cancer prognosis, tumor microenvironment, immune infiltration, stemness scores, tumor mutational burden, and microsatellite instability. The diagnostic and prognostic value of SMOX and SUCLG2 in CRC was confirmed through TCGA, GEO, and HPA, as well as qPCR. SUCLG2 overexpression inhibited the proliferation of RKO and HCT116, whereas SUCLG2 silence promoted their proliferation. Our data provide insights into the role of SMOX and SUCLG2 in pan-cancer, highlighting their association with prognosis, cancer immunity, and other cancer characteristics and also revealing their significance in cancer progression. SUCLG2 may inhibit the proliferation of CRC. Full article

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29 pages, 1319 KB

Open AccessReview

The Potential Use of Digital Twin Technology for Advancing CAR-T Cell Therapy

by Sara Sadat Aghamiri and Rada Amin

Curr. Issues Mol. Biol. 2025, 47(5), 321; https://doi.org/10.3390/cimb47050321 - 30 Apr 2025

Cited by 3 | Viewed by 3248

Abstract

CAR-T cell therapy is a personalized immunotherapy that has shown promising results in treating hematologic cancers. However, its therapeutic efficacy in solid cancers is often limited by tumor evasion mechanisms, resistance pathways, and an immunosuppressive tumor microenvironment. These challenges highlight the need for [...] Read more.

CAR-T cell therapy is a personalized immunotherapy that has shown promising results in treating hematologic cancers. However, its therapeutic efficacy in solid cancers is often limited by tumor evasion mechanisms, resistance pathways, and an immunosuppressive tumor microenvironment. These challenges highlight the need for advanced predictive models to better capture the intricate interactions between CAR-T cells and tumors to enhance their potential. Digital Twins represent a transformative approach for optimizing CAR-T cell therapy by providing a virtual representation of the therapy-tumor trajectory using high-dimensional patient data. In this review, we first define Digital Twins and outline the fundamental steps in their development. We then explore the critical parameters required for designing CAR-T-specific Digital Twins. We examine published case studies demonstrating a few applications of Digital Twins in addressing key challenges in CAR-T cell therapy, including their impact on clinical trials and manufacturing processes. Finally, we discuss the limitations associated with integrating Digital Twins into CAR-T therapy. As Digital Twin technology continues to evolve, the potential to enhance CAR-T therapy through precision modeling and real-time adaptation could redefine the landscape of personalized cancer treatment. Full article

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31 pages, 4089 KB

Open AccessArticle

A Pilot Investigation of Circulating miRNA Expression in Individuals Exposed to Aluminum and Welding Fumes

by Gözde Öztan, Halim İşsever, Tuğçe İşsever, Fatma Oğuz, Sevgi Canbaz, Canan Küçükgergin and Kazım Yalçın Arga

Curr. Issues Mol. Biol. 2025, 47(5), 306; https://doi.org/10.3390/cimb47050306 - 26 Apr 2025

Viewed by 846

Abstract

The objectives of this study comprise the identification of key miRNAs and their target genes associated with severe tolerance in individuals exposed to aluminum and welding fumes, and the elucidation of the underlying regulatory mechanisms. In this study, the levels of seven miRNAs [...] Read more.

The objectives of this study comprise the identification of key miRNAs and their target genes associated with severe tolerance in individuals exposed to aluminum and welding fumes, and the elucidation of the underlying regulatory mechanisms. In this study, the levels of seven miRNAs (hsa-miR-19a-3p, hsa-miR-130b-3p, hsa-miR-25-3p, hsa-miR-363-3p, hsa-miR-92a-3p, hsa-miR-24-3p, and hsa-miR-19b-3p) were analyzed using both hsa-miR-16-5p and RNU6 (U6 snRNA) as reference miRNAs to validate normalization reliability. The qRT-PCR method was used on blood serum samples from 16 workers who were exposed to aluminum, 16 workers who were exposed to welding fumes, and 16 healthy controls who were not exposed to aluminum or welding fumes. We determined heavy metal levels from serum samples of workers exposed to aluminum and welding fumes and control groups using the ICP-OES method. The expression levels of hsa-miR-19a-3p and hsa-miR-19b-3p in aluminum-exposed and control groups were found to be statistically significant (p < 0.05). When workers exposed to welding fumes were compared with the those in the control groups, the expression levels of hsa-miR-19a-3p, hsa-miR-130b-3p, hsa-miR-92a-3p, and hsa-miR-24-3p were observed to be statistically significant (p < 0.05). This study shows that the identification of miRNAs and target genes in different biological functions and pathways plays an important role in understanding the molecular mechanisms of responses to heavy metal toxicity. We share the view that the study will make a significant contribution to the literature in that seven candidate miRNAs can be used as possible biomarkers for exposure to aluminum and welding fumes in humans. Full article

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24 pages, 8232 KB

Open AccessArticle

Bioinformatics Approach to Investigating the Immuno-Inflammatory Mechanisms of Periodontitis in the Progression of Atherosclerosis

by Wenling Yang, Jianhua Xie, Xing Zhao, Xuelian Li, Qingyi Liu, Jinpeng Sun, Ruiyu Zhang, Yumiao Wei and Boyuan Wang

Curr. Issues Mol. Biol. 2025, 47(3), 197; https://doi.org/10.3390/cimb47030197 - 17 Mar 2025

Viewed by 1323

Abstract

Unstable atherosclerotic plaques are a major cause of acute cardiovascular events and ischemic stroke. Clinical studies have suggested a link between periodontitis and atherosclerotic plaque progression, but the underlying mechanisms remain unclear. To investigate this, transcriptomic datasets related to periodontitis and atherosclerosis were [...] Read more.

Unstable atherosclerotic plaques are a major cause of acute cardiovascular events and ischemic stroke. Clinical studies have suggested a link between periodontitis and atherosclerotic plaque progression, but the underlying mechanisms remain unclear. To investigate this, transcriptomic datasets related to periodontitis and atherosclerosis were downloaded from Gene Expression Omnibus. A weighted gene co-expression network analysis was used to identify gene modules associated with periodontitis, and the Limma R package identified differentially expressed genes (DEGs) between unstable and stable plaques. Overlapping genes were defined as periodontitis-related DEGs, followed by functional enrichment analysis and protein–protein interaction network construction. Machine learning methods were used to identify biomarkers for unstable plaques related to periodontitis, which were validated using external datasets. Immune infiltration and single-cell analyses were performed to explore the relationship between biomarkers and immune cells. A total of 161 periodontitis-related DEGs were identified, with the pathway analysis showing associations with immune regulation and collagen matrix degradation. HCK, NCKAP1L, and WAS were identified as biomarkers for unstable plaques, demonstrating a high diagnostic value (AUC: 0.9884, 95% CI: 0.9641–1). Immune infiltration analysis revealed an increase in macrophages within unstable plaques. Single-cell analysis showed HCK expression in macrophages and dendritic cells, while NCKAP1L and WAS were expressed in macrophages, dendritic cells, NK cells, and T cells. Consensus clustering identified three expression patterns within unstable plaques. Our findings were validated in atherosclerotic mouse models with periodontitis. This study provides insights into how periodontitis contributes to plaque instability, supporting diagnosis and intervention in patients with periodontitis. Full article

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26 pages, 12261 KB

Open AccessArticle

Unravelling Convergent Signaling Mechanisms Underlying the Aging-Disease Nexus Using Computational Language Analysis

by Marina Junyent, Haki Noori, Robin De Schepper, Shanna Frajdenberg, Razan Khalid Abdullah Hussen Elsaigh, Patricia H. McDonald, Derek Duckett and Stuart Maudsley

Curr. Issues Mol. Biol. 2025, 47(3), 189; https://doi.org/10.3390/cimb47030189 - 14 Mar 2025

Viewed by 1197

Abstract

Multiple lines of evidence suggest that multiple pathological conditions and diseases that account for the majority of human mortality are driven by the molecular aging process. At the cellular level, aging can largely be conceptualized to comprise the progressive accumulation of molecular damage, [...] Read more.

Multiple lines of evidence suggest that multiple pathological conditions and diseases that account for the majority of human mortality are driven by the molecular aging process. At the cellular level, aging can largely be conceptualized to comprise the progressive accumulation of molecular damage, leading to resultant cellular dysfunction. As many diseases, e.g., cancer, coronary heart disease, Chronic obstructive pulmonary disease, Type II diabetes mellitus, or chronic kidney disease, potentially share a common molecular etiology, then the identification of such mechanisms may represent an ideal locus to develop targeted prophylactic agents that can mitigate this disease-driving mechanism. Here, using the input of artificial intelligence systems to generate unbiased disease and aging mechanism profiles, we have aimed to identify key signaling mechanisms that may represent new disease-preventing signaling pathways that are ideal for the creation of disease-preventing chemical interventions. Using a combinatorial informatics approach, we have identified a potential critical mechanism involving the recently identified kinase, Dual specificity tyrosine-phosphorylation-regulated kinase 3 (DYRK3) and the epidermal growth factor receptor (EGFR) that may function as a regulator of the pathological transition of health into disease via the control of cellular fate in response to stressful insults. Full article

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2024

Jump to: 2025

10 pages, 263 KB

Open AccessArticle

Genetic Predisposition to Prediabetes in the Kazakh Population

by Gulnara Svyatova, Galina Berezina, Alexandra Murtazaliyeva, Altay Dyussupov, Tatyana Belyayeva, Raida Faizova and Azhar Dyussupova

Curr. Issues Mol. Biol. 2024, 46(10), 10913-10922; https://doi.org/10.3390/cimb46100648 - 28 Sep 2024

Viewed by 1852

Abstract

The aim of this study was to conduct a comparative analysis of the population frequencies of the minor allele of polymorphic variants in the genes TCF7L2 (rs7903146) and PPARG (rs1801282), based on the genome-wide association studies analysis data associated with the risk of [...] Read more.

The aim of this study was to conduct a comparative analysis of the population frequencies of the minor allele of polymorphic variants in the genes TCF7L2 (rs7903146) and PPARG (rs1801282), based on the genome-wide association studies analysis data associated with the risk of developing prediabetes, in an ethnically homogeneous Kazakh population compared to previously studied populations worldwide. This study utilized a genomic database consisting of 1800 ethnically Kazakh individuals who were considered in healthy condition. Whole-genome genotyping was performed using Illumina OmniChip 2.5–8 arrays, which interrogated approximately 2.5 million single nucleotide polymorphisms. The distribution of genotypes for the TCF7L2 (rs7903146) and PPARG (rs1801282) polymorphisms in the Kazakh sample was found to be in Hardy–Weinberg equilibrium (p > 0.05). The minor G allele of the “Asian” protective polymorphism rs1801282 in the PPARG gene was observed at a frequency of 13.8% in the Kazakh population. This suggests a potentially more significant protective effect of this polymorphism in reducing the risk of prediabetes among Kazakhs. The frequency of the unfavorable T allele of the insulin secretion-disrupting gene TCF7L2 (rs7903146) in Kazakhs was 15.2%. Studying the associations of genetic markers for prediabetes enables the timely identification of “high-risk groups” and facilitates the implementation of effective preventive measures. Further results from replicative genomic research will help identify significant polymorphic variants of genes underlying the alteration of prediabetes status. Full article

15 pages, 41414 KB

Open AccessArticle

A Theoretical Study of the Interaction of PARP-1 with Natural and Synthetic Inhibitors: Advances in the Therapy of Triple-Negative Breast Cancer

by Albert Gabriel Turpo-Peqqueña, Emily Katherine Leiva-Flores, Sebastián Luna-Prado and Badhin Gómez

Curr. Issues Mol. Biol. 2024, 46(9), 9415-9429; https://doi.org/10.3390/cimb46090558 - 27 Aug 2024

Viewed by 2650

Abstract

In the current study, we have investigated the secondary metabolites present in ethnomedical plants used for medicinal purposes—Astilbe chinensis (EK1), Scutellaria barbata D. Don (EK2), Uncaria rhynchophylla (EK3), Fallugia paradoxa (EK4), and Curcuma zedoaria (Christm.) Thread (EK5)—and we have compared them with five [...] Read more.

In the current study, we have investigated the secondary metabolites present in ethnomedical plants used for medicinal purposes—Astilbe chinensis (EK1), Scutellaria barbata D. Don (EK2), Uncaria rhynchophylla (EK3), Fallugia paradoxa (EK4), and Curcuma zedoaria (Christm.) Thread (EK5)—and we have compared them with five compounds of synthetic origin for the inhibition of PARP-1, which is linked to abnormal DNA replication, generating carcinogenic cells. We have studied these interactions through molecular dynamics simulations of each interacting system under physiological conditions (pH, temperature, and pressure) and determined that the compounds of natural origin have a capacity to inhibit PARP-1 (Poly(ADP-ribose) Polymerase 1) in all the cases inspected in this investigation. However, it is essential to mention that their interaction energy is relatively lower compared to that of compounds of synthetic origin. Given that binding energy is mandatory for the generation of a scale or classification of which is the best interacting agent, we can say that we assume that compounds of natural origin, having a complexation affinity with PARP-1, induce cell apoptosis, a potential route for the prevention of the proliferation of carcinogenic cells. Full article

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8 pages, 864 KB

Open AccessCommunication

Genetic Variants Associated with Body Mass Index Changes in Korean Adults: The Anseong and Ansan Cohorts of the Korean Genome and Epidemiology Study

by Sang-Im Lee, Su-Kang Kim and Sang-Wook Kang

Curr. Issues Mol. Biol. 2024, 46(8), 9074-9081; https://doi.org/10.3390/cimb46080536 - 19 Aug 2024

Cited by 3 | Viewed by 1669

Abstract

Although previous studies have examined the relationship between obesity and genetics in response to the growing obesity epidemic, research on the relationship between obesity and long-term changes in body mass index (BMI) is limited. To investigate this relationship, data from 1030 cases in [...] Read more.

Although previous studies have examined the relationship between obesity and genetics in response to the growing obesity epidemic, research on the relationship between obesity and long-term changes in body mass index (BMI) is limited. To investigate this relationship, data from 1030 cases in the Anseong and Ansan cohorts were collected from the Korean Genome and Epidemiology Study conducted by the Korea National Institute of Health between 2000 and 2014. Cases lacking participants’ BMI data throughout the study were excluded, resulting in a final sample size of 3074. An increase or decrease in BMI was analyzed using PLINK, STRING, and DAVID, with significant differences observed in the AEN, ANKS1B, CSF1, EEF2K, FRAS1, GRIK4, PDGFC, THTPA, and TREH genes. These genes were observed to cluster with pathways related to type 2 diabetes, cardiovascular disease, metabolic processes, and endocytosis-related genes. These results suggest that several genes are involved in BMI changes and that several pathways are associated with obesity risk. Moreover, some genetic variants appear to influence BMI changes in Korean adults. Full article

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11 pages, 1393 KB

Open AccessArticle

A Bioinformatic Analysis Predicts That Cannabidiol Could Function as a Potential Inhibitor of the MAPK Pathway in Colorectal Cancer

by Julianne du Plessis, Aurelie Deroubaix, Aadilah Omar and Clement Penny

Curr. Issues Mol. Biol. 2024, 46(8), 8600-8610; https://doi.org/10.3390/cimb46080506 - 5 Aug 2024

Cited by 4 | Viewed by 1754

Abstract

Colorectal cancer (CRC), found in the intestinal tract, is initiated and progresses through various mechanisms, including the dysregulation of signaling pathways. Several signaling pathways, such as EGFR and MAPK, involved in cell proliferation, migration, and apoptosis, are often dysregulated in CRC. Although cannabidiol [...] Read more.

Colorectal cancer (CRC), found in the intestinal tract, is initiated and progresses through various mechanisms, including the dysregulation of signaling pathways. Several signaling pathways, such as EGFR and MAPK, involved in cell proliferation, migration, and apoptosis, are often dysregulated in CRC. Although cannabidiol (CBD) has previously induced apoptosis and cell cycle arrest in vitro in CRC cell lines, its effects on signaling pathways have not yet been determined. An in silico analysis was used here to assess partner proteins that can bind to CBD, and docking simulations were used to predict precisely where CBD would bind to these selected proteins. A survey of the current literature was used to hypothesize the effect of CBD binding on such proteins. The results predict that CBD could interact with EGFR, RAS/RAF isoforms, MEK1/2, and ERK1/2. The predicted CBD-induced inhibition might be due to CBD binding to the ATP binding site of the target proteins. This prevents the required phosphoryl transfer to activate substrate proteins and/or CBD binding to the DFG motif from taking place, thus reducing catalytic activity. Full article

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19 pages, 5514 KB

Open AccessArticle

Using Copy Number Variation Data and Neural Networks to Predict Cancer Metastasis Origin Achieves High Area under the Curve Value with a Trade-Off in Precision

by Michel-Edwar Mickael, Norwin Kubick, Atanas G. Atanasov, Petr Martinek, Jarosław Olav Horbańczuk, Nikko Floretes, Michael Michal, Tomas Vanecek, Justyna Paszkiewicz, Mariusz Sacharczuk and Piotr Religa

Curr. Issues Mol. Biol. 2024, 46(8), 8301-8319; https://doi.org/10.3390/cimb46080490 - 1 Aug 2024

Cited by 1 | Viewed by 1534

Abstract

The accurate identification of the primary tumor origin in metastatic cancer cases is crucial for guiding treatment decisions and improving patient outcomes. Copy number alterations (CNAs) and copy number variation (CNV) have emerged as valuable genomic markers for predicting the origin of metastases. [...] Read more.

The accurate identification of the primary tumor origin in metastatic cancer cases is crucial for guiding treatment decisions and improving patient outcomes. Copy number alterations (CNAs) and copy number variation (CNV) have emerged as valuable genomic markers for predicting the origin of metastases. However, current models that predict cancer type based on CNV or CNA suffer from low AUC values. To address this challenge, we employed a cutting-edge neural network approach utilizing a dataset comprising CNA profiles from twenty different cancer types. We developed two workflows: the first evaluated the performance of two deep neural networks—one ReLU-based and the other a 2D convolutional network. In the second workflow, we stratified cancer types based on anatomical and physiological classifications, constructing shallow neural networks to differentiate between cancer types within the same cluster. Both approaches demonstrated high AUC values, with deep neural networks achieving a precision of 60%, suggesting a mathematical relationship between CNV type, location, and cancer type. Our findings highlight the potential of using CNA/CNV to aid pathologists in accurately identifying cancer origins with accessible clinical tests. Full article

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12 pages, 4039 KB

Open AccessArticle

Application of Transcriptome-Based Gene Set Featurization for Machine Learning Model to Predict the Origin of Metastatic Cancer

by Yeonuk Jeong, Jinah Chu, Juwon Kang, Seungjun Baek, Jae-Hak Lee, Dong-Sub Jung, Won-Woo Kim, Yi-Rang Kim, Jihoon Kang and In-Gu Do

Curr. Issues Mol. Biol. 2024, 46(7), 7291-7302; https://doi.org/10.3390/cimb46070432 - 9 Jul 2024

Cited by 2 | Viewed by 1980

Abstract

Identifying the primary site of origin of metastatic cancer is vital for guiding treatment decisions, especially for patients with cancer of unknown primary (CUP). Despite advanced diagnostic techniques, CUP remains difficult to pinpoint and is responsible for a considerable number of cancer-related fatalities. [...] Read more.

Identifying the primary site of origin of metastatic cancer is vital for guiding treatment decisions, especially for patients with cancer of unknown primary (CUP). Despite advanced diagnostic techniques, CUP remains difficult to pinpoint and is responsible for a considerable number of cancer-related fatalities. Understanding its origin is crucial for effective management and potentially improving patient outcomes. This study introduces a machine learning framework, ONCOfind-AI, that leverages transcriptome-based gene set features to enhance the accuracy of predicting the origin of metastatic cancers. We demonstrate its potential to facilitate the integration of RNA sequencing and microarray data by using gene set scores for characterization of transcriptome profiles generated from different platforms. Integrating data from different platforms resulted in improved accuracy of machine learning models for predicting cancer origins. We validated our method using external data from clinical samples collected through the Kangbuk Samsung Medical Center and Gene Expression Omnibus. The external validation results demonstrate a top-1 accuracy ranging from 0.80 to 0.86, with a top-2 accuracy of 0.90. This study highlights that incorporating biological knowledge through curated gene sets can help to merge gene expression data from different platforms, thereby enhancing the compatibility needed to develop more effective machine learning prediction models. Full article

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23 pages, 5027 KB

Open AccessArticle

Multiomics Analysis of the PHLDA Gene Family in Different Cancers and Their Clinical Prognostic Value

by Safia Iqbal, Md. Rezaul Karim, Shahnawaz Mohammad, Ramya Mathiyalagan, Md. Niaj Morshed, Deok-Chun Yang, Hyocheol Bae, Esrat Jahan Rupa and Dong Uk Yang

Curr. Issues Mol. Biol. 2024, 46(6), 5488-5510; https://doi.org/10.3390/cimb46060328 - 30 May 2024

Cited by 4 | Viewed by 2048

Abstract

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. [...] Read more.

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. The predictive significance of PHLDA genes in cancer remains unclear. To determine the role of pleckstrin as a prognostic biomarker in human cancers, we conducted a systematic multiomics investigation. Through various survival analyses, pleckstrin expression was evaluated, and their predictive significance in human tumors was discovered using a variety of online platforms. By analyzing the protein–protein interactions, we also chose a collection of well-known functional protein partners for pleckstrin. Investigations were also carried out on the relationship between pleckstrins and other cancers regarding mutations and copy number alterations. The cumulative impact of pleckstrin and their associated genes on various cancers, Gene Ontology (GO), and pathway analyses were used for their evaluation. Thus, the expression profiles of PHLDA family members and their prognosis in various cancers may be revealed by this study. During this multiomics analysis, we found that among the PHLDA family, PHLDA1 may be a therapeutic target for several cancers, including kidney, colon, and brain cancer, while PHLDA2 can be a therapeutic target for cancers of the colon, esophagus, and pancreas. Additionally, PHLDA3 may be a useful therapeutic target for ovarian, renal, and gastric cancer. Full article

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13 pages, 266 KB

Open AccessArticle

Exome Sequencing for the Diagnostics of Osteogenesis Imperfecta in Six Russian Patients

by Yulia S. Koshevaya, Mariia E. Turkunova, Anastasia O. Vechkasova, Elena A. Serebryakova, Maxim Yu. Donnikov, Svyatoslav I. Papanov, Alexander N. Chernov, Lev N. Kolbasin, Lyudmila V. Kovalenko, Andrey S. Glotov and Oleg S. Glotov

Curr. Issues Mol. Biol. 2024, 46(5), 4106-4118; https://doi.org/10.3390/cimb46050252 - 29 Apr 2024

Cited by 1 | Viewed by 1776

Abstract

Osteogenesis imperfecta (OI) is a group of inherited disorders of connective tissue that cause significant deformities and fragility in bones. Most cases of OI are associated with pathogenic variants in collagen type I genes and are characterized by pronounced polymorphisms in clinical manifestations [...] Read more.

Osteogenesis imperfecta (OI) is a group of inherited disorders of connective tissue that cause significant deformities and fragility in bones. Most cases of OI are associated with pathogenic variants in collagen type I genes and are characterized by pronounced polymorphisms in clinical manifestations and the absence of clear phenotype–genotype correlation. The objective of this study was to conduct a comprehensive molecular–genetic and clinical analysis to verify the diagnosis of OI in six Russian patients with genetic variants in the COL1A1 and COL1A2 genes. Clinical and laboratory data were obtained from six OI patients who were observed at the Medical Genetics Center in Saint Petersburg from 2016 to 2023. Next-generation sequencing on MGISEQ G400 (MGI, China) was used for DNA analysis. The GATK bioinformatic software (version 4.5.0.0) was used for variant calling and hard filtering. Genetic variants were verified by the direct automatic sequencing of PCR products using the ABI 3500X sequencer. We identified six genetic variants, as follows pathogenic c.3505G>A (p. Gly1169Ser), c.769G>A (p.Gly257Arg), VUS c.4123G>A (p.Ala1375Thr), and c.4114A>T (p.Asn1372Tyr) in COL1A1; and likely pathogenic c.2035G>A (p.Gly679Ser) and c.739-2A>T in COL1A2. In addition, clinical cases are presented due to the presence of the c.4114A>T variant in the COL1A2 gene. Molecular genetics is essential for determining different OI types due to the high similarity across various types of the disease and the failure of unambiguous diagnosis based on clinical manifestations alone. Considering the variable approaches to OI classification, an integrated strategy is required for optimal patient management. Full article

15 pages, 3208 KB

Open AccessArticle

Genetic Signatures for Distinguishing Chemo-Sensitive from Chemo-Resistant Responders in Prostate Cancer Patients

by Lemohang Gumenku, Mamello Sekhoacha, Beynon Abrahams, Samson Mashele, Aubrey Shoko and Ochuko L. Erukainure

Curr. Issues Mol. Biol. 2024, 46(3), 2263-2277; https://doi.org/10.3390/cimb46030145 - 11 Mar 2024

Cited by 1 | Viewed by 2925

Abstract

Prostate cancer remains a significant public health concern in sub-Saharan Africa, particularly impacting South Africa with high mortality rates. Despite many years of extensive research and significant financial expenditure, there has yet to be a definitive solution to prostate cancer. It is not [...] Read more.

Prostate cancer remains a significant public health concern in sub-Saharan Africa, particularly impacting South Africa with high mortality rates. Despite many years of extensive research and significant financial expenditure, there has yet to be a definitive solution to prostate cancer. It is not just individuals who vary in their response to treatment, but even different nodules within the same tumor exhibit unique transcriptome patterns. These distinctions extend beyond mere differences in gene expression levels to encompass the control and networking of individual genes. Escalating chemotherapy resistance in prostate cancer patients has prompted increased research into its underlying mechanisms. The heterogeneous nature of transcriptomic organization among men makes the pursuit of universal biomarkers and one-size-fits-all treatments impractical. This study delves into the expression of drug resistance-associated genes, ABCB1 and CYP1B1, in cancer cells. Employing bioinformatics, we explored the molecular pathways and cascades linked to drug resistance following upregulation of these genes. Samples were obtained from archived prostate cancer patient specimens through pre-treatment biopsies of two categories: good vs. poor responders, with cDNAs synthesized from isolated RNAs subjected to qPCR analysis. The results revealed increased ABCB1 and CYP1B1 expression in tumor samples of the poor responders. Gene enrichment and network analysis associated ABCB1 with ABC transporters and LncRNA-mediated therapeutic resistance (WP3672), while CYP1B1 was linked to ovarian steroidogenesis, tryptophan metabolism, steroid hormone biosynthesis, benzo(a)pyrene metabolism, the sulindac metabolic pathway, and the estrogen receptor pathway, which are associated with drug resistance. Both ABCB1 and CYP1B1 correlated with microRNAs in cancer and the Nuclear Receptors Meta-Pathway. STRING analysis predicted protein–protein interactions of ABCB1 and CYP1B1 with Glutathione S-transferase Pi, Catechol O-methyltransferase, UDP-glucuronosyltransferase 1-6, Leucine-rich Transmembrane and O-methyltransferase (LRTOMT), and Epoxide hydrolase 1, with scores of 0.973, 0.971, 0.966, 0.966, and 0.966, respectively. Furthermore, molecular docking analysis of the chemotherapy drug, docetaxel, with CYP1B1 and ABCB1 revealed robust molecular interactions, with binding energies of −20.37 and −15.25 Kcal/mol, respectively. These findings underscore the susceptibility of cancer patients to drug resistance due to increased ABCB1 and CYP1B1 expression in tumor samples from patients in the poor-responders category that affects associated molecular pathways. The potent molecular interactions of ABCB1 and CYP1B1 with docetaxel further emphasize the potential basis for chemotherapy resistance. Full article

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22 pages, 3836 KB

Open AccessArticle

In Silico Approach to Molecular Profiling of the Transition from Ovarian Epithelial Cells to Low-Grade Serous Ovarian Tumors for Targeted Therapeutic Insights

by Asim Leblebici, Ceren Sancar, Bahar Tercan, Zerrin Isik, Mehmet Emin Arayici, Ender Berat Ellidokuz, Yasemin Basbinar and Nuri Yildirim

Curr. Issues Mol. Biol. 2024, 46(3), 1777-1798; https://doi.org/10.3390/cimb46030117 - 26 Feb 2024

Cited by 2 | Viewed by 2725

Abstract

This paper aims to elucidate the differentially coexpressed genes, their potential mechanisms, and possible drug targets in low-grade invasive serous ovarian carcinoma (LGSC) in terms of the biologic continuity of normal, borderline, and malignant LGSC. We performed a bioinformatics analysis, integrating datasets generated [...] Read more.

This paper aims to elucidate the differentially coexpressed genes, their potential mechanisms, and possible drug targets in low-grade invasive serous ovarian carcinoma (LGSC) in terms of the biologic continuity of normal, borderline, and malignant LGSC. We performed a bioinformatics analysis, integrating datasets generated using the GPL570 platform from different studies from the GEO database to identify changes in this transition, gene expression, drug targets, and their relationships with tumor microenvironmental characteristics. In the transition from ovarian epithelial cells to the serous borderline, the FGFR3 gene in the “Estrogen Response Late” pathway, the ITGB2 gene in the “Cell Adhesion Molecule”, the CD74 gene in the “Regulation of Cell Migration”, and the IGF1 gene in the “Xenobiotic Metabolism” pathway were upregulated in the transition from borderline to LGSC. The ERBB4 gene in “Proteoglycan in Cancer”, the AR gene in “Pathways in Cancer” and “Estrogen Response Early” pathways, were upregulated in the transition from ovarian epithelial cells to LGSC. In addition, SPP1 and ITGB2 genes were correlated with macrophage infiltration in the LGSC group. This research provides a valuable framework for the development of personalized therapeutic approaches in the context of LGSC, with the aim of improving patient outcomes and quality of life. Furthermore, the main goal of the current study is a preliminary study designed to generate in silico inferences, and it is also important to note that subsequent in vitro and in vivo studies will be necessary to confirm the results before considering these results as fully reliable. Full article

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10 pages, 252 KB

Open AccessBrief Report

Association between Single Nucleotide Polymorphisms in Monoamine Oxidase and the Severity of Addiction to Betel Quid

by Chung-Chieh Hung, Ying-Chin Ko and Chia-Min Chung

Curr. Issues Mol. Biol. 2024, 46(2), 1010-1019; https://doi.org/10.3390/cimb46020064 - 23 Jan 2024

Cited by 3 | Viewed by 1772

Abstract

Betel quid (BQ) is the fourth most popular psychoactive substance in the world, and BQ use disorder (BUD) is prevalent in Asian countries. Although the mechanisms underlying BUD remain unclear, studies have reported influences from monoamine oxidase inhibitor. We enrolled 50 patients with [...] Read more.

Betel quid (BQ) is the fourth most popular psychoactive substance in the world, and BQ use disorder (BUD) is prevalent in Asian countries. Although the mechanisms underlying BUD remain unclear, studies have reported influences from monoamine oxidase inhibitor. We enrolled 50 patients with BUD and assessed their BQ consumption habits, emotional conditions, and the clinical severity of addiction—assessed using the Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition] (DSM-5) criteria, Substance Use Severity Rating Scale, and Yale–Brown Obsessive Compulsive Disorder Rating Scale for BQ. Patients were categorized into the severe group when showing six or more symptoms defined by DSM-5. A genome-wide association study was conducted for single nucleotide polymorphisms in BRCA1, COL9A1, NOTCH1, HSPA13, FAT1, and MAOA by using patients’ blood samples. More severe BUD symptoms were associated with younger age of using BQ and poor oral hygiene and with severe craving for and more anxiety toward BQ use. The MAOA rs5953210 polymorphism was significantly associated with severe BUD (odds ratio, 6.43; 95% confidence interval, 5.12–7.74; p < 0.01) and might contribute to BQ-associated cancer risk. Further studies are required to investigate the addictive properties of BQ and the development of novel diagnostic tools and pharmacotherapeutic alternatives to BUD treatment. Full article

13 pages, 3055 KB

Open AccessArticle

AG1^® Induces a Favorable Impact on Gut Microbial Structure and Functionality in the Simulator of Human Intestinal Microbial Ecosystem^® Model

by Trevor O. Kirby, Philip A. Sapp, Jeremy R. Townsend, Marlies Govaert, Cindy Duysburgh, Massimo Marzorati, Tess M. Marshall and Ralph Esposito

Curr. Issues Mol. Biol. 2024, 46(1), 557-569; https://doi.org/10.3390/cimb46010036 - 5 Jan 2024

Cited by 1 | Viewed by 5511

Abstract

Modulation of the human gut microbiome has become an area of interest in the nutraceutical space. We explored the effect of the novel foundational nutrition supplement AG1^® on the composition of human microbiota in an in vitro experimental design. Employing the Simulator [...] Read more.

Modulation of the human gut microbiome has become an area of interest in the nutraceutical space. We explored the effect of the novel foundational nutrition supplement AG1^® on the composition of human microbiota in an in vitro experimental design. Employing the Simulator of Human Intestinal Microbial Ecosystem (SHIME^®) model, AG1^® underwent digestion, absorption, and subsequent colonic microenvironment simulation under physiologically relevant conditions in healthy human fecal inocula. Following 48 h of colonic simulation, the gut microbiota were described using shallow shotgun, whole genome sequencing. Metagenomic data were used to describe changes in community structure (alpha diversity, beta diversity, and changes in specific taxa) and community function (functional heterogeneity and changes in specific bacterial metabolic pathways). Results showed no significant change in alpha diversity, but a significant effect of treatment and donor and an interaction between the treatment and donor effect on structural heterogeneity likely stemming from the differential enrichment of eight bacterial taxa. Similar findings were observed for community functional heterogeneity likely stemming from the enrichment of 20 metabolic pathways characterized in the gene ontology term database. It is logical to conclude that an acute dose of AG1 has significant effects on gut microbial composition that may translate into favorable effects in humans. Full article

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