Biomarkers and Therapeutic Targets Based on Bioinformatical Studies

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Bioengineering bioengineering	3.8	4.0	2014	16.4 Days	CHF 2700
Biology biology	3.6	5.7	2012	16.4 Days	CHF 2700
Biomimetics biomimetics	3.4	3.5	2016	19.5 Days	CHF 2200
Life life	3.2	4.3	2011	17.8 Days	CHF 2600
Molecules molecules	4.2	7.4	1996	15.1 Days	CHF 2700

22 pages, 2854 KiB

Open AccessArticle

Weighted Gene Networks Derived from Multi-Omics Reveal Core Cancer Genes in Lung Cancer

by Qingcai He, Zhilong Mi, Ziqiao Yin, Zhiming Zheng and Binghui Guo

Biology 2025, 14(3), 223; https://doi.org/10.3390/biology14030223 - 20 Feb 2025

Viewed by 533

Lung cancer remains the leading cause of cancer-related deaths worldwide, driven by its complexity and the heterogeneity of its subtypes, which influence pathogenesis, tumor microenvironment, and genetic alterations. We developed a novel weighted gene regulatory network reconstruction method based on maximum entropy and [...] Read more.

Lung cancer remains the leading cause of cancer-related deaths worldwide, driven by its complexity and the heterogeneity of its subtypes, which influence pathogenesis, tumor microenvironment, and genetic alterations. We developed a novel weighted gene regulatory network reconstruction method based on maximum entropy and Markov chain entropy principles, which integrates gene expression and DNA methylation data to generate biologically informed networks. Applied to LUAD and LUSC datasets, we define a network methylation index to determine whether gene methylation acts as oncogenic or tumor-suppressive. By revealing a stable core set of pathogenic genes, we identify not only genes with significant expression changes, such as CD74 and HGF, but also pathogenic genes with stable expression, such as BRAF and KDM6A. Additionally, we uncover potential driver genes, such as CORO2B and C20orf194, associated with disease stage, gender, and smoking status. This method offers a more comprehensive understanding of NSCLC mechanisms, paving the way for improved therapeutic strategies. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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19 pages, 1459 KiB

Open AccessSystematic Review

Differential Expression of Maternal Plasma microRNAs and Their Respective Gene Targets Can Predict Early Fetal Growth Restriction

by Emmanuel Kolawole, Aparna Duggirala, Oscar Gronow, Agnieszka Wisniewska, Jiamiao Hu and Bee Kang Tan

Life 2025, 15(2), 167; https://doi.org/10.3390/life15020167 - 24 Jan 2025

Viewed by 714

Abstract

Fetal growth restriction (FGR) is a condition where the fetus does not reach its genetically predetermined size, affecting 1 in 10 pregnancies and contributing to up to 50% of all stillbirths before 34 weeks of gestation. Current diagnostic methods primarily involve ultrasound and [...] Read more.

Fetal growth restriction (FGR) is a condition where the fetus does not reach its genetically predetermined size, affecting 1 in 10 pregnancies and contributing to up to 50% of all stillbirths before 34 weeks of gestation. Current diagnostic methods primarily involve ultrasound and Doppler assessments, yet there is growing interest in identifying biomarkers for early diagnosis and improved management. This systematic review examined the role of microRNAs (miRNAs) in the pathogenesis of FGR, focusing on their potential as non-invasive biomarkers. MicroRNAs are small, non-coding RNAs that regulate gene expression. This review systematically assessed studies investigating the differential expression of miRNAs in maternal blood, serum, and plasma samples from FGR-affected pregnancies. A total of nine studies met the inclusion criteria, which showed the differential expression of a total of 48 miRNAs. miR-16-5p was consistently upregulated in multiple studies and trimesters. miR-590-3p and miR-206 were consistently upregulated in multiple trimesters. The common gene targets of these miRNAs are VEGF, PIGF, and MMP9. The downregulation of these genes contributes to impaired angiogenesis, trophoblast invasion, placental function, and fetal growth. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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14 pages, 20836 KiB

Open AccessArticle

Identification of Clinical Value and Biological Effects of XIRP2 Mutation in Hepatocellular Carcinoma

by Dahuan Li, Xin Bao, Shan Lei, Wenpeng Cao, Zhirui Zeng and Tengxiang Chen

Biology 2024, 13(8), 633; https://doi.org/10.3390/biology13080633 - 19 Aug 2024

Viewed by 1711

Abstract

Hepatocellular carcinoma (HCC) is a prevalent malignant digestive tumor. Numerous genetic mutations have been documented in HCC, yet the clinical significance of these mutations remains largely unexplored. The objective of this study is to ascertain the clinical value and biological effects of xin [...] Read more.

Hepatocellular carcinoma (HCC) is a prevalent malignant digestive tumor. Numerous genetic mutations have been documented in HCC, yet the clinical significance of these mutations remains largely unexplored. The objective of this study is to ascertain the clinical value and biological effects of xin actin binding repeat containing 2 (XIRP2) mutation in HCC. The gene mutation landscape of HCC was examined using data from the Cancer Genome Atlas and the International Cancer Genome Consortium databases. The prognostic significance of the XIRP2 mutation was assessed through KM plot analysis. The association between drug sensitivity and the XIRP2 mutation was investigated using the TIDE algorithm and CCK-8 experiments. The biological effects of the XIRP2 mutation were evaluated through qRT-PCR, protein stability experiments, and relevant biological experiments. The XIRP2 mutation is one of the high-frequency mutations in HCC, and is associated with poor prognosis. A total of 72 differentially expressed genes (DEGs) were observed in HCC tissues with the XIRP2 mutation as compared to those with the XIRP2 wildtype, and these DEGs were closely related to ion metabolic processes. The XIRP2 mutation was linked to alterations in the sensitivity of fludarabine, oxaliplatin, WEHI-539, and LCL-161. CCK-8 assays demonstrated that HCC cells carrying the XIRP2 mutation exhibited increased resistance to fludarabine and oxaliplatin, but enhanced sensitivity to WEHI-539 and LCL-161 as compared with those HCC cells with the XIRP2 wildtype. The XIRP2 mutation was found to have no impact on the mRNA levels of XIRP2 in tissues and cells, but it did enhance the stability of the XIRP2 protein. Mechanically, the inhibition of XIRP2 resulted in a significant increase in sensitivity to oxaliplatin through an elevation in zinc ions and a calcium ion overload. In conclusion, the XIRP2 mutation holds potential as a biomarker for predicting the prognosis and drug sensitivity of HCC and serves as a therapeutic target to enhance the efficacy of oxaliplatin. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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19 pages, 7673 KiB

Open AccessArticle

Hypoxia-Induced Adaptations of Embryonic Fibroblasts: Implications for Developmental Processes

by Zeyu Li, Delong Han, Zhenchi Li and Lingjie Luo

Biology 2024, 13(8), 598; https://doi.org/10.3390/biology13080598 - 8 Aug 2024

Viewed by 1491

Abstract

Animal embryonic development occurs under hypoxia, which can promote various developmental processes. Embryonic fibroblasts, which can differentiate into bone and cartilage and secrete various members of the collagen protein family, play essential roles in the formation of embryonic connective tissues and basement membranes. [...] Read more.

Animal embryonic development occurs under hypoxia, which can promote various developmental processes. Embryonic fibroblasts, which can differentiate into bone and cartilage and secrete various members of the collagen protein family, play essential roles in the formation of embryonic connective tissues and basement membranes. However, the adaptations of embryonic fibroblasts under hypoxia remain poorly understood. In this study, we investigated the effects of hypoxia on mouse embryonic fibroblasts (MEFs). We found that hypoxia can induce migration, promote metabolic reprogramming, induce the production of ROS and apoptosis, and trigger the activation of multiple signaling pathways of MEFs. Additionally, we identified several hypoxia-inducible genes, including Proser2, Bean1, Dpf1, Rnf128, and Fam71f1, which are regulated by HIF1α. Furthermore, we demonstrated that CoCl₂ partially mimics the effects of low oxygen on MEFs. However, we found that the mechanisms underlying the production of ROS and apoptosis differ between hypoxia and CoCl₂ treatment. These findings provide insights into the complex interplay between hypoxia, fibroblasts, and embryonic developmental processes. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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11 pages, 254 KiB

Open AccessArticle

Effect of Ultrasound-Guided Renal Biopsies on Urinary N-Acetyl-Beta-D-Glucosaminidase Index Activity in Dogs with Diffuse Parenchymal Nephropathies

by Andrei Răzvan Codea, Romeo Popa, Bogdan Sevastre, Alexandra Biriș, Daniela Neagu, Cristian Popovici, Mircea Mircean and Ciprian Ober

Life 2024, 14(7), 867; https://doi.org/10.3390/life14070867 - 11 Jul 2024

Viewed by 1150

Abstract

Background: Ultrasound-guided kidney biopsy is an essential diagnostics method that can increase the accuracy of the differential diagnosis between acute and chronic nephropathies. In addition, it will help clinicians perform an etiologic diagnosis, issue a prognosis, and orient therapy for the majority of [...] Read more.

Background: Ultrasound-guided kidney biopsy is an essential diagnostics method that can increase the accuracy of the differential diagnosis between acute and chronic nephropathies. In addition, it will help clinicians perform an etiologic diagnosis, issue a prognosis, and orient therapy for the majority of parenchymal nephropathies. Due to the relative invasiveness and potential adverse effects, the use of kidney biopsies is limited among practitioners. Results: Twenty-eight dogs, of mixed breed and variable ages, of which 11 (39, 29%) were males and 17 (60, 71%) were females, were examined and underwent an ultrasound-guided kidney biopsy to establish a definitive diagnosis. The patients were presented with a variety of diffuse nephropathies, such as kidney lymphoma: 1 (3.57%), glomerulonephritis: 13 (46.43%), tubulointerstitial nephritis: 11 (39.29%), and nephrocalcinosis. A total of 3 (10.71%) of 18 (64.29%) were in acute kidney injury, and 10 (35.71%) were CKD patients. The type and the severity of the kidney lesions were correlated with changes in the urinary n-acetyl-beta-d-glucosaminidase index (iNAG. To quantify the side effects of percutaneous kidney biopsy, the magnitude of post-biopsy hematuria and changes in urinary iNAG activity were evaluated. The results indicate a significant post-biopsy increase in the urinary iNAG activity in all the patients that underwent this procedure (100.08 ± 34.45 U/g), with a pre-biopsy iNAG vs. 147.65 ± 33.26 U/g post-biopsy iNAG (p < 0.001), suggesting an intensification in the kidney tubular damage that comes consecutives to kidney puncture and sampling. Transitory macro- or microhematuria were constant findings in all the dogs that underwent ultrasound-guided kidney biopsy, but the magnitude and extent could not be associated with the platelet count (PLT 109/L), aPTT (s), and PT (s) levels in our patients, and they were also resolved after 12–24 h without therapeutic interventions. Conclusions: Ultrasound-guided renal biopsy was shown to be a minimally invasive diagnostic procedure that causes transient and limited effects on kidney structures. Although these effects were minor and resolved without intervention, we feel that the benefit of obtaining higher-quality biopsied tissue outweighs the higher risks associated with this procedure. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

17 pages, 4515 KiB

Open AccessArticle

Efficacy of Glycyrrhetinic Acid in the Treatment of Acne Vulgaris Based on Network Pharmacology and Experimental Validation

by Lingna Xie, Congwei Ma, Xinyu Li, Huixiong Chen, Ping Han, Li Lin, Weiqiang Huang, Menglu Xu, Hailiang Lu and Zhiyun Du

Molecules 2024, 29(10), 2345; https://doi.org/10.3390/molecules29102345 - 16 May 2024

Cited by 1 | Viewed by 2699

Abstract

Glycyrrhetinic acid (GA) is a saponin compound, isolated from licorice (Glycyrrhiza glabra), which has been wildly explored for its intriguing pharmacological and medicinal effects. GA is a triterpenoid glycoside displaying an array of pharmacological and biological activities, including anti-inflammatory, anti-bacterial, antiviral and antioxidative [...] Read more.

Glycyrrhetinic acid (GA) is a saponin compound, isolated from licorice (Glycyrrhiza glabra), which has been wildly explored for its intriguing pharmacological and medicinal effects. GA is a triterpenoid glycoside displaying an array of pharmacological and biological activities, including anti-inflammatory, anti-bacterial, antiviral and antioxidative properties. In this study, we investigated the underlying mechanisms of GA on acne vulgaris through network pharmacology and proteomics. After the intersection of the 154 drug targets and 581 disease targets, 37 therapeutic targets for GA against acne were obtained. A protein–protein interaction (PPI) network analysis highlighted TNF, IL1B, IL6, ESR1, PPARG, NFKB1, STAT3 and TLR4 as key targets of GA against acne, which is further verified by molecular docking. The experimental results showed that GA inhibited lipid synthesis in vitro and in vivo, improved the histopathological damage of skin, prevented mast cell infiltration and decreased the level of pro-inflammatory cytokines, including TNF-α, IL-1β and IL-6. This study indicates that GA may regulate multiple pathways to improve acne symptoms, and the beneficial effects of GA against acne vulgaris might be through the regulation of sebogenesis and inflammatory responses. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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15 pages, 3602 KiB

Open AccessArticle

PRMT5 Mediated HIF1α Signaling and Ras-Related Nuclear Protein as Promising Biomarker in Hepatocellular Carcinoma

by Wafaa Abumustafa, Darko Castven, Fatemeh Saheb Sharif-Askari, Batoul Abi Zamer, Mawieh Hamad, Jens-Uwe Marquardt and Jibran Sualeh Muhammad

Biology 2024, 13(4), 216; https://doi.org/10.3390/biology13040216 - 27 Mar 2024

Cited by 1 | Viewed by 2009

Abstract

Protein arginine N-methyltransferase 5 (PRMT5) has been identified as a potential therapeutic target for various cancer types. However, its role in regulating the hepatocellular carcinoma (HCC) transcriptome remains poorly understood. In this study, publicly available databases were employed to investigate PRMT5 expression, its [...] Read more.

Protein arginine N-methyltransferase 5 (PRMT5) has been identified as a potential therapeutic target for various cancer types. However, its role in regulating the hepatocellular carcinoma (HCC) transcriptome remains poorly understood. In this study, publicly available databases were employed to investigate PRMT5 expression, its correlation with overall survival, targeted pathways, and genes of interest in HCC. Additionally, we utilized in-house generated NGS data to explore PRMT5 expression in dysplastic nodules compared to hepatocellular carcinoma. Our findings revealed that PRMT5 is significantly overexpressed in HCC compared to normal liver, and elevated expression correlates with poor overall survival. To gain insights into the mechanism driving PRMT5 overexpression in HCC, we analyzed promoter CpG islands and methylation status in HCC compared to normal tissues. Pathway analysis of PRMT5 knockdown in the HCC cells revealed a connection between PRMT5 expression and genes related to the HIF1α pathway. Additionally, by filtering PRMT5-correlated genes within the HIF1α pathway and selecting up/downregulated genes in HCC patients, we identified Ras-related nuclear protein (RAN) as a target associated with overall survival. For the first time, we report that PRMT5 is implicated in the regulation of HIF1A and RAN genes, suggesting the potential prognostic utility of PRMT5 in HCC. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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27 pages, 1435 KiB

Open AccessReview

Molecular Assessment of Methylglyoxal-Induced Toxicity and Therapeutic Approaches in Various Diseases: Exploring the Interplay with the Glyoxalase System

by Muhanad Alhujaily

Life 2024, 14(2), 263; https://doi.org/10.3390/life14020263 - 17 Feb 2024

Cited by 6 | Viewed by 3362

Abstract

This comprehensive exploration delves into the intricate interplay of methylglyoxal (MG) and glyoxalase 1 (GLO I) in various physiological and pathological contexts. The linchpin of the narrative revolves around the role of these small molecules in age-related issues, diabetes, obesity, cardiovascular diseases, and [...] Read more.

This comprehensive exploration delves into the intricate interplay of methylglyoxal (MG) and glyoxalase 1 (GLO I) in various physiological and pathological contexts. The linchpin of the narrative revolves around the role of these small molecules in age-related issues, diabetes, obesity, cardiovascular diseases, and neurodegenerative disorders. Methylglyoxal, a reactive dicarbonyl metabolite, takes center stage, becoming a principal player in the development of AGEs and contributing to cell and tissue dysfunction. The dual facets of GLO I—activation and inhibition—unfold as potential therapeutic avenues. Activators, spanning synthetic drugs like candesartan to natural compounds like polyphenols and isothiocyanates, aim to restore GLO I function. These molecular enhancers showcase promising outcomes in conditions such as diabetic retinopathy, kidney disease, and beyond. On the contrary, GLO I inhibitors emerge as crucial players in cancer treatment, offering new possibilities in diseases associated with inflammation and multidrug resistance. The symphony of small molecules, from GLO I activators to inhibitors, presents a nuanced understanding of MG regulation. From natural compounds to synthetic drugs, each element contributes to a molecular orchestra, promising novel interventions and personalized approaches in the pursuit of health and wellbeing. The abstract concludes with an emphasis on the necessity of rigorous clinical trials to validate these findings and acknowledges the importance of individual variability in the complex landscape of health. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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40 pages, 7326 KiB

Open AccessArticle

Enhancement of Classifier Performance Using Swarm Intelligence in Detection of Diabetes from Pancreatic Microarray Gene Data

by Dinesh Chellappan and Harikumar Rajaguru

Biomimetics 2023, 8(6), 503; https://doi.org/10.3390/biomimetics8060503 - 22 Oct 2023

Cited by 2 | Viewed by 2023

Abstract

In this study, we focused on using microarray gene data from pancreatic sources to detect diabetes mellitus. Dimensionality reduction (DR) techniques were used to reduce the dimensionally high microarray gene data. DR methods like the Bessel function, Discrete Cosine Transform (DCT), Least Squares [...] Read more.

In this study, we focused on using microarray gene data from pancreatic sources to detect diabetes mellitus. Dimensionality reduction (DR) techniques were used to reduce the dimensionally high microarray gene data. DR methods like the Bessel function, Discrete Cosine Transform (DCT), Least Squares Linear Regression (LSLR), and Artificial Algae Algorithm (AAA) are used. Subsequently, we applied meta-heuristic algorithms like the Dragonfly Optimization Algorithm (DOA) and Elephant Herding Optimization Algorithm (EHO) for feature selection. Classifiers such as Nonlinear Regression (NLR), Linear Regression (LR), Gaussian Mixture Model (GMM), Expectation Maximum (EM), Bayesian Linear Discriminant Classifier (BLDC), Logistic Regression (LoR), Softmax Discriminant Classifier (SDC), and Support Vector Machine (SVM) with three types of kernels, Linear, Polynomial, and Radial Basis Function (RBF), were utilized to detect diabetes. The classifier’s performance was analyzed based on parameters like accuracy, F1 score, MCC, error rate, FM metric, and Kappa. Without feature selection, the SVM (RBF) classifier achieved a high accuracy of 90% using the AAA DR methods. The SVM (RBF) classifier using the AAA DR method for EHO feature selection outperformed the other classifiers with an accuracy of 95.714%. This improvement in the accuracy of the classifier’s performance emphasizes the role of feature selection methods. Full article

(This article belongs to the Topic Biomarkers and Therapeutic Targets Based on Bioinformatical Studies)

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