Molecular Targets Research Articles

Analyzing the relationship between gene expression and phenotype in space-flown mice using a causal inference machine learning ensemble

Spaceflight has several detrimental effects on human and rodent health. For example, liver dysfunction is a common phenotype observed in space-flown rodents, and this dysfunction is partially reflected in transcriptomic changes. Studies linking transcriptomics with liver dysfunction rely on tools which exploit correlation, but these tools make no attempt to disambiguate true correlations from spurious ones. In this work, we use a machine learning ensemble of causal inference methods called the Causal Research and Inference Search Platform (CRISP) which was developed to predict causal features of a binary response variable from high-dimensional input. We used CRISP to identify genes robustly correlated with a lipid density phenotype using transcriptomic and histological data from the NASA Open Science Data Repository (OSDR). Our approach identified genes and molecular targets not predicted by previous traditional differential gene expression analyses. These genes are likely to play a pivotal role in the liver dysfunction observed in space-flown rodents, and this work opens the door to identifying novel countermeasures for space travel.

Exploring the effect of hsa-miR-19b-3p on IL-1R1 expression and serum levels in alopecia areata.

Alopecia areata (AA) is an autoimmune condition marked by hair loss, linked to inflammatory processes involving the interleukin-1 receptor type 1 (IL-1R1) pathway. This study aims to explore the relationship between IL-1R1 gene expression, serum IL-1R1 levels, and hsa-miR-19b-3p in relation to AA severity. Using a case-control design, we assessed 100 AA patients and 100 healthy controls, measuring serum IL-1R1 through enzyme-linked immunosorbent assay (ELISA) and analyzing IL-1R1 gene and hsa-miR-19b-3p expression levels via quantitative real-time PCR (qRT-PCR). Bioinformatic analysis predicted a binding site for hsa-miR-19b-3p on the IL-1R1 gene, suggesting a regulatory role for this miRNA in AA pathology. Demonstrated significantly higher serum IL-1R1, IL-1R1 gene expression, and hsa-miR-19b-3p levels in AA patients compared to controls. Within the AA cohort, severe cases showed the highest levels, with notable correlations between serum IL-1R1, IL-1R1 gene expression, and hsa-miR-19b-3p. Receiver Operating Characteristic (ROC) curve analysis revealed robust diagnostic potential, with area under the curve (AUC) values of 0.71, 0.73, and 0.76 for serum IL-1R1, hsa-miR-19b-3p, and IL-1R1 gene expression, respectively. Elevated IL-1R1 and hsa-miR-19b-3p levels are associated with AA and its severity, suggesting these markers have potential as diagnostic and prognostic indicators. These findings enhance the understanding of IL-1R1's role in AA and highlight potential molecular targets for future therapeutic approaches.

The GeoTox Package: open-source software for connecting spatiotemporal exposure to individual and population-level risk

BackgroundComprehensive environmental risk characterization, encompassing physical, chemical, social, ecological, and lifestyle stressors, necessitates innovative approaches to handle the escalating complexity. This is especially true when considering individual and population-level diversity, where the myriad combinations of real-world exposures magnify the combinatoric challenges. The GeoTox framework offers a tractable solution by integrating geospatial exposure data from source-to-outcome in a series of modular, interconnected steps.ResultsHere, we introduce the GeoTox open-source R software package for characterizing the risk of perturbing molecular targets involved in adverse human health outcomes based on exposure to spatially-referenced stressor mixtures. We demonstrate its usage in building computational workflows that incorporate individual and population-level diversity. Our results demonstrate the applicability of GeoTox for individual and population-level risk assessment, highlighting its capacity to capture the complex interplay of environmental stressors on human health.ConclusionsThe GeoTox package represents a significant advancement in environmental risk characterization, providing modular software to facilitate the application and further development of the GeoTox framework for quantifying the relationship between environmental exposures and health outcomes. By integrating geospatial methods with cutting-edge exposure and toxicological frameworks, GeoTox offers a robust tool for assessing individual and population-level risks from environmental stressors. GeoTox is freely available at https://niehs.github.io/GeoTox/.

Uncovering the Regulatory Role of Long Non-Coding RNAs in Colorectal Cancer Progression and Liver Metastasis: Implications for Therapeutic and Diagnostic Targeting

Background: Colorectal cancer (CRC) is a leading cause of cancer-related deaths, largely due to metastasis, particularly to the liver, and the limited understanding of the molecular mechanisms underlying this process. In this study, we aimed to investigate the role of long non-coding Methods: RNAs (lncRNAs) are key regulatory factors in CRC progression and metastasis to liver tissues. Using high-throughput sequencing and microarray approaches, we analyzed gene expression profiles from two independent lncRNA datasets to identify potential players involved in liver metastasis. Results: Our findings revealed five lncRNAs—PROX1-AS1, SOX9-AS1, LINC01594, LINC01555, and APOA1-AS—previously known for their roles in CRC progression, now identified as being involved in the liver metastatic process. Additionally, 20 other lncRNAs, including VCAN-AS1, SYP-AS1, SMIM2-IT1, NCOA7-AS1, and LINC01449, were also identified as potential contributors to CRC liver metastasis. Notably, two lncRNAs—SATB2-AS1 and LINC01116—emerged as common candidates across both datasets, suggesting their significant role in promoting CRC metastasis to the liver. These two lncRNAs hold promise as molecular targets for therapeutic and diagnostic development. Conclusion: Our study uncovers a novel layer of regulatory mechanisms involving lncRNAs in CRC liver metastasis. These findings advance our understanding of the molecular behaviors that drive CRC progression and offer new avenues for targeted therapeutic strategies and diagnostic tools, particularly for liver metastasis in CRC.

Integrating network pharmacology with molecular docking and dynamics to uncover therapeutic targets and signaling mechanisms of vitamin D3 in Parkinson's disease.

Parkinson's disease (PD) is a chronic neurodegenerative disorder marked by dopaminergic neuron degeneration in the substantia nigra. Emerging evidence suggests vitamin D3 (VD) plays a therapeutic role in PD, but its precise molecular mechanisms remain unclear. This study employed network pharmacology and bioinformatics to identify VD's hub targets and related pathways. We identified 24 VD's anti-PD targets, with estrogen receptor 1, estrogen receptor 2 (ESR2), sodium-dependent norepinephrine transporter, and insulin-like growth factor 1 receptor emerging as hub targets. Gene enrichment analysis elucidated that VD's anti-PD mechanism is closely related to the estrogen signaling pathway. Additionally, two-sample Mendelian randomization suggested a positive causal relationship between 25-hydroxyvitamin D and estrogen levels in vivo. To verify the interaction between VD and the hub drug targets, we performed molecular docking and kinetic simulations, finding the strongest interaction between VD and ESR2. Further Mendelian randomization analysis of drug targets confirmed the significant effect of the ESR2 drug target on PD risk. Single-cell nuclear sequencing of dopaminergic neurons, coupled with GSEA analysis, indicated that ESR2 activation upregulates the neuroactive ligand-receptor interaction signaling pathway and downregulates the Parkinson's disease pathway, thereby exerting a neuroprotective effect. In summary, our findings suggest that VD supplementation can not only elevate estradiol levels in humans but also directly activate ESR2, thereby modulating the estrogen signaling pathway in PD patients and providing neuroprotection. These predictive biological targets offer promising avenues for future clinical applications in Parkinson's disease treatment.

JAK3 Inhibitors: Covalent and Noncovalent Interactions of a Cyanamide Group Investigated by Multiscale Free-Energy Simulations.

Janus kinase type 3 (JAK3), an emerging target for treating autoimmune diseases, possesses a front pocket cysteine that is targeted by covalent modifiers, best represented by the marketed drug ritlecitinib (1). Recently, 2,3-dihydro-1H-inden-1-ylcyanamides have been developed as novel JAK3 inhibitors. Among them, the N-(6-(7H-pyrrolo[2,3-d]pyrimidin-4-yl)-2,3-dihydro-1H-inden-1-yl)cyanamide inhibitor (2) and its methylated analogue (3), while being potent inhibitors, displayed different mechanisms of action (covalent vs noncovalent) and binding modes (Casimiro-Garcia et al., J Med Chem 2018). Prompted by this intriguing behavior, we applied a multiscale approach to characterize the reaction mechanism between the JAK3 front-pocket Cys909 and cyanamide-based inhibitors. Quantum mechanics/molecular mechanics simulations showed that 2 can readily form an isothiourea adduct with the Cys909 only when a conserved water molecule assists the reaction as a proton shuttle and that methylation of the 2,3-dihydro-1H-inden-1-ylcyanamide moiety of 2 hampers the isothiourea formation by displacing this water molecule. Metadynamics and thermodynamic integration simulations were applied to investigate the relative abundance of alternative poses accessible to 2,3-dihydro-1H-inden-1-ylcyanamides, explaining the effect of methylation on the relative binding mode preference. This multiscale approach provides new chemical insights into the mechanism of action of cyanamide inhibitors and emerges as an effective protocol to investigate the interaction between drugs and molecular targets.

3D QASR, Antimicrobial Activity and Molecular Docking Studies of C-14 Chiral Matrine Derivatives as Potential Antibiotics.

Antibiotic resistance is recognized as one of the top ten global public health threats, posing a significant challenge to human health. The stereochemistry of chiral molecules, alongside their specific interactions with biological targets, provides essential insights for the development of novel antibacterial agents, This study investigated the antibacterial activity of 32 previously synthesized 14-position chiral matrine derivatives. Among these derivatives, compound Q4 exhibited the strongest activity against Propionibacterium acnes, with a minimum inhibitory concentration (MIC) of 0.007 mg/mL, surpassing that of the positive control (MIC = 0.016 mg/mL). Additionally, compounds Q20 and Q2 demonstrated antibacterial activities comparable to the positive controls. The results indicated that R-configured compounds exhibited significantly greater antibacterial potency than their S-configured counterparts. A systematic analysis using 3D-QSAR modeling elucidated the relationship between molecular structure and antibacterial activity, emphasizing the predominance of steric fields over electrostatic fields, in alignment with experimental observations. Furthermore, molecular docking confirmed the binding interactions between compound Q4 and the target protein. In conclusion, C-14 chiral matrine derivatives exhibit considerable potential as effective antibacterial agents, meriting further exploration in the search for new treatments to combat antibiotic-resistant infections.

Myt1 kinase: An Emerging Cell Cycle Regulator for Cancer Therapeutics.

Cell cycle checkpoints are stringent quality control mechanisms that regulate cell cycle progression and division. Cancer cells often develop a dependency on the G2/M cell cycle checkpoint to facilitate DNA repair and resolve intrinsic or therapy-induced DNA damage. This dependency leads to therapy resistance, continuous cell division, and disease progression. Targeting G2/M checkpoints has been heavily pursued over the past two decades and has progressed into clinical studies. Recent genome-scale functional genomic studies have revealed that Myt1 kinase, an essential but previously overlooked molecule for the G2/M checkpoint, is a promising target for multiple types of cancers. In this work, we summarize the latest discoveries in molecular targeting of Myt1 kinase and discuss the challenges and limitations in expanding its clinical application.

Circular RNAs in the management of human osteoporosis.

Osteoporosis (OP) is a metabolic bone disease producing reduction in bone mass with consequent bone fragility. Circular ribonucleic acid (CircRNA) is a form of RNA that forms a loop structure rather than a linear one. CircRNA can be used for therapeutic purposes, including molecular targets or to test new therapies. A systematic search of different databases to July 2024 was performed to define the role of circRNA in OP therapy. Seventeen suitable studies were identified. CircRNAs may be useful in studying metabolic processes in OP and identify possible therapeutic targets and new drug therapies. The metabolic processes involved in OP are regulated by many genes and cytokines that can be targeted by CircRNAs. However, it is not easy to predict whether the in vitro responses of the studied CircRNAs and their interaction with drugs are also applicable in vivo. Metabolic processes can be affected by gene dysregulation of CircRNAs on various growth factors. Areas timely for developing research: Despite the predictability of CircRNA pharmacological response in vitro, such pharmacological response cannot be expected to be replicated in vivo. The data that support the findings of this study are available from the corresponding author.

Utilization of Cannabidiol in Post-Organ-Transplant Care

Cannabidiol (CBD) is one of the major phytochemical constituents of cannabis, Cannabis sativa, widely recognized for its therapeutic potential. While cannabis has been utilized for medicinal purposes since ancient times, its psychoactive and addictive properties led to its prohibition in 1937, with only the medical use being reauthorized in 1998. Unlike tetrahydrocannabinol (THC), CBD lacks psychoactive and addictive properties, yet the name that suggests its association with cannabis has significantly contributed to its public visibility. CBD exhibits diverse pharmacological properties, most notably anti-inflammatory effects. Additionally, it interacts with key drug-metabolizing enzyme families, including cytochrome P450 (CYP) and uridine 5′-diphospho-glucuronosyltransferase (UGT), which mediate phase I and phase II metabolism, respectively. By binding to these enzymes, CBD can inhibit the metabolism of co-administered drugs, which can potentially enhance their toxicity or therapeutic effects. Mild to moderate adverse events associated with CBD use have been reported. Advances in chemical formulation techniques have recently enabled strategies to minimize these effects. This review provides an overview of CBD, covering its historical background, recent clinical trials, adverse event profiles, and interactions with molecular targets such as receptors, channels, and enzymes. We particularly emphasize the mechanisms underlying its anti-inflammatory effects and interaction with drugs relevant to organ transplantation. Finally, we explore recent progress in the chemical formulation of CBD in order to enhance its bioavailability, which will enable decreasing the dose to use and increase its safety and efficacy.

Treatment of delayed fracture healing with Bushen Tiansui decoction: Analysis of active agents and targets using bioinformatics and network pharmacology analysis.

This study aims to utilize bioinformatics and network pharmacology to identify the active components of Bushen Tiansui decoction (BSTSD) and elucidate its molecular mechanisms and targets in promoting delayed fracture healing. Using various databases and tools, we identified 155 active compounds within BSTSD's herbal components. Key compounds such as eriodictyol and β-sitosterol were noted for their significant anti-inflammatory, antioxidant, and immunomodulatory effects, which are crucial for promoting fracture healing. Network analysis revealed compounds such as kaempferol and luteolin as having high centrality within the network, indicating their central role in the therapeutic effects of BSTSD. Gene ontology (GO) enrichment analysis highlighted that biological processes such as gland development and aging are vital for fracture healing. Cellular components like membrane rafts and microdomains are essential for maintaining cellular functions and signal transduction during bone repair. Molecular functions such as protein serine/threonine kinase activity play key roles in regulating bone cell proliferation, differentiation, and remodeling. KEGG pathway analysis identified critical pathways including prostate cancer, proteoglycans in cancer, lipid and atherosclerosis, EGFR tyrosine kinase inhibitor resistance, chemical carcinogenesis receptor activation, PI3K-Akt signaling pathway, hepatitis B, endocrine resistance, HIF-1 signaling pathway, and estrogen signaling pathway. Molecular docking results showed strong binding affinities between key compounds and target proteins, supporting the reliability of the network pharmacology predictions. This study provides a comprehensive understanding of the molecular mechanisms by which BSTSD promotes fracture healing, identifying active compounds and pathways that offer scientific bases for the clinical application of BSTSD and paving the way for further experimental validation and therapeutic development.

Advancements in molecular imaging probes for precision diagnosis and treatment of prostate cancer.

Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.

Characterization and molecular targeting of CFIm25 (NUDT21/CPSF5) mRNA using miRNAs.

Changes in protein levels of the mammalian cleavage factor, CFIm25, play a role in regulating pathological processes including neural dysfunction, fibrosis, and tumorigenesis. However, despite these effects, little is known about how CFIm25 (NUDT21) expression is regulated at the RNA level. A potential regulator of NUDT21 mRNA are small non-coding microRNAs (miRNAs). In general, miRNAs bind to the 3'untranslated regions (3'UTRs) and can target the bound mRNA for degradation or inhibit translation thus affecting the levels of protein in cells. Interestingly, a mechanism known as alternative polyadenylation (APA) enables mRNAs to escape miRNA regulation by generating mRNAs with 3'UTRs of different sizes. As many miRNA target sites are located within the 3'UTR, shortening the 3'UTR allows mRNAs to evade miRNAs targeting this region. The differences in the lengths and the sequence composition of the 3'UTRs may also impact the mRNA's translatability and subcellular localization. APA has been reported to regulate over 70% of protein coding genes, thus increasing the transcript repertoire. Several proteins, including mammalian cleavage factor, CFIm25 (NUDT21), have been shown to regulate APA. In this study we wanted to determine whether CFIm25 (NUDT21), itself a regulator of APA, undergoes APA to evade miRNA regulation. We used the blood cancer mantle cell lymphoma (MCL) cells as a model and showed that in these cells, NUDT21 is relatively stable with a long half-life. In addition, the NUDT21 pre-mRNA undergoes alternative APA within the same terminal exon. The three different sized NUDT21 mRNAs have different 3'UTR lengths and they each use a different canonical polyadenylation signal, AAUAAA, for 3'end cleavage and polyadenylation. Use of miRNA mimics and inhibitors showed that miR-23a, miR-222, and miR-323a play a significant role in regulating NUDT21 expression. Hence, these results suggest that NUDT21 mRNA is stable and the different 3'UTRs generated through APA of NUDT21 play an important role in evading miRNA regulation and offers insights into how levels of CFIm25 (NUDT21) may be fine-tuned as needed under different physiological and pathological conditions.

Silymarin as a Therapeutic Agent for Hepatocellular Carcinoma: A Multi-Approach Computational Study

Background: Hepatocellular carcinoma (HCC) is a prevalent and lethal form of liver cancer with limited treatment options. Silymarin, a flavonoid complex derived from milk thistle, has shown promise in liver disease treatment due to its antioxidant, anti-inflammatory, and anticancer properties. This study aims to explore the therapeutic potential of silymarin in HCC through a comprehensive in silico approach. Methods: This study employed a network pharmacology approach to identify key molecular targets of silymarin in HCC. The Genecards and Metascape databases were used for target identification and functional annotation. Molecular docking analysis was conducted on the primary silymarin components against VEGFA and SRC proteins, which are critical in HCC progression. MD simulations followed to assess the stability and interactions of the docked complexes. Results: Network pharmacology analysis identified several key molecular targets and pathways implicated in HCC. The molecular docking results revealed strong binding affinities of silymarin components to VEGFA and SRC, with Silybin A and Isosilybin B showing the highest affinities. MD simulations confirmed the stability of these interactions, indicating potential inhibitory effects on HCC progression. Conclusions: This study provides a comprehensive in silico evaluation of silymarin’s therapeutic potential in HCC. The findings suggest that silymarin, particularly its components Silybin A and Isosilybin B, may effectively target VEGFA and SRC proteins, offering a promising avenue for HCC treatment. Further experimental validation is warranted to confirm these findings and facilitate the development of silymarin-based therapeutics for HCC.

MicroRNAs in pancreatic cancer drug resistance: mechanisms and therapeutic potential

Pancreatic cancer (PC) remains one of the most lethal malignancies, primarily due to its intrinsic resistance to conventional therapies. MicroRNAs (miRNAs), key regulators of gene expression, have been identified as crucial modulators of drug resistance mechanisms in this cancer type. This review synthesizes recent advancements in our understanding of how miRNAs influence treatment efficacy in PC. We have thoroughly summarized and discussed the complex role of miRNA in mediating drug resistance in PC treatment. By highlighting specific miRNAs that are implicated in drug resistance pathways, we provide insights into their functional mechanisms and interactions with key molecular targets. We also explore the potential of miRNA-based strategies as novel therapeutic approaches and diagnostic tools to overcome resistance and improve patient outcomes. Despite promising developments, challenges such as specificity, stability, and effective delivery of miRNA-based therapeutics remain. This review aims to offer a critical perspective on current research and propose future directions for leveraging miRNA-based interventions in the fight against PC.

Artificial Intelligence in Computer-Aided Drug Design (CADD) Tools for the Finding of Potent Biologically Active Small Molecules: Traditional to Modern Approach.

Computer-Aided Drug Design (CADD) entails designing molecules that could potentially interact with a specific biomolecular target and promising their potential binding. The stereo- arrangement and stereo-selectivity of small molecules (SMs)--based chemotherapeutic agents significantly influence their therapeutic potential and enhance their therapeutic advantages. CADD has been a well-established field for decades, but recent years have observed a significant shift toward acceptance of computational approaches in both academia and the pharmaceutical industry. Recently, artificial intelligence (AI), bioinformatics, and data science have played a significant role in drug discovery to accelerate the development of effective treatments, reduce expenses, and eliminate the need for animal testing. This shift can be attributed to the availability of extensive data on molecular properties, binding to therapeutic targets, and their 3D structures. Increasing interest from legislators, pharmaceutical companies, and academic and industrial scientists is evidence that AI is reshaping the drug discovery industry. To achieve success in drug discovery, it is necessary to optimize pharmacodynamic, pharmacokinetic, and clinical outcome-related properties. Moreover, the advent of on-demand virtual libraries containing billions of drug-like SMs, coupled with abundant computing capacities, has further facilitated this transition. To fully capitalize on these resources, rapid computational methods are needed for effective ligand screening. This includes structure-based virtual screening (SBVS) of vast chemical spaces, aided by fast iterative screening approaches. At the same time, advances in deep learning (DL) predictions of ligand properties and target activities have become very helpful, as they no longer need information about the structure of the receptor. This study examines recent progress in the drug discovery and development (DDD) approach, their potential to reshape the entire DDD process, and the challenges they face. This review examines the role of artificial intelligence as a fundamental component in drug discovery, particularly focusing on small molecules. It also discusses how AI-driven approaches can expedite the identification of diverse, potent, target-specific, and drug-like ligands for protein targets. This advancement has the potential to make drug discovery more efficient and cost-effective, ultimately facilitating the development of safer and more effective therapeutics.

Identification and mechanistic insights of cell senescence-related genes in psoriasis

Background Psoriasis is a chronic inflammatory skin disease affecting 2–3% of the global population, characterised by red scaly patches that significantly affect patients’ quality of life. Recent studies have suggested that cell senescence, a state in which cells cease to divide and secrete inflammatory mediators, plays a critical role in various chronic diseases, including psoriasis. However, the involvement and mechanisms of action of senescence-related genes in psoriasis remain unclear. Methods This study aimed to identify senescence-related genes associated with psoriasis and explore their molecular mechanisms. RNA sequencing data from psoriasis and control samples were obtained from the GEO database. Differential expression analysis was performed using DESeq2 to identify differentially expressed genes (DEGs). The intersection of DEGs with cell senescence-related genes from the CellAge database was used to identify the candidate genes. Protein-protein interaction networks, Gene Ontology, and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to explore the functions and pathways of these genes. Machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support vector machine-recursive feature elimination (SVE-RFE), were used to select feature genes that were validated by qRT-PCR. Additionally, an immune cell infiltration analysis was performed to understand the roles of these genes in the immune response to psoriasis. Results This study identified 4,913 DEGs in psoriasis, of which 46 were related to cell senescence. Machine learning highlighted four key genes, CXCL1, ID4, CCND1, and IRF7, as significant. These genes were associated with immune cell infiltration and validated by qRT-PCR, suggesting their potential as therapeutic targets for psoriasis. Conclusions This study identified and validated key senescence-related genes involved in psoriasis, providing insights into their molecular mechanisms and potential therapeutic targets and offering a foundation for developing targeted therapies for psoriasis.

Prevention of liver cancer in the era of next-generation antivirals and obesity epidemic.

Preventive interventions are expected to substantially improve the prognosis of patients with primary liver cancer, predominantly hepatocellular carcinoma (HCC) and cholangiocarcinoma. HCC prevention is challenging in the face of the evolving etiological landscape, particularly the sharp increase in obesity-associated metabolic disorders, including metabolic dysfunction-associated steatotic liver disease (MASLD). Next-generation anti-HCV and HBV drugs have substantially reduced, but not eliminated, the risk of HCC and have given way to new challenges in identifying at-risk patients. The recent development of new therapeutic agents and modalities has opened unprecedented opportunities to refine primary, secondary, and tertiary HCC prevention strategies. For primary prevention (before exposure to risk factors), public health policies, such as universal HBV vaccination, have had a substantial prognostic impact. Secondary prevention (after or during active exposure to risk factors) includes regular HCC screening and chemoprevention. Emerging biomarkers and imaging modalities for HCC risk stratification and detection may enable individual risk-based personalized and cost-effective HCC screening. Clinical studies have suggested the potential utility of lipid-lowering, anti-diabetic/obesity, and anti-inflammatory agents for secondary prevention, and some of them are being evaluated in prospective clinical trials. Computational and experimental studies have identified potential chemopreventive strategies directed at diverse molecular, cellular, and systemic targets for etiology-specific and/or agnostic interventions. Tertiary prevention (in conjunction with curative-intent therapies for HCC) is an area of active research with the development of new immune-based neo/adjuvant therapies. Cholangiocarcinoma prevention may advance with recent efforts to elucidate risk factors. These advances will collectively lead to substantial improvements in liver cancer mortality rates.

Regulatory role of lnc-MAP3K13-3:1 on miR-6894-3p and SHROOM2 in modulating cellular dynamics in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is a prevalent primary liver malignancy and a leading cause of cancer-related mortality worldwide. Despite advancements in therapeutic strategies, the 5-year survival rate for individuals undergoing curative resection remains between 10% and 15%. Consequently, identifying molecular targets that specifically inhibit the proliferation and metastasis of HCC cells is critical for improving treatment outcomes. Database analysis using Targetscan identified complementary binding sites for the human-specific miRNA hsa-miR-6894-3p (hereafter referred to as miR-6894-3p) on SHROOM2, and Starbase data suggested a potential regulatory interaction between lnc-MAP3K13-3:1 and miR-6894-3p in liver cancer.ObjectiveThis study aimed to investigate the role of lnc-MAP3K13-3:1 in regulating miR-6894-3p, with a focus on its impact on proliferation, apoptosis, migration, and related cellular processes in liver cancer cells via SHROOM2 regulation.MethodsQuantitative PCR (qPCR) was initially employed to measure the expression levels of lnc-MAP3K13-3:1 and miR-6894-3p in three HCC cell lines: HepG2, HuH-7, and Li-7. Based on these initial assessments, two cell lines were selected for further experimentation. Stable cell lines overexpressing lnc-MAP3K13-3:1 were developed, and cells were transfected with miR-6894-3p mimics or a mimic negative control (NC). After 24 h, qPCR was utilized to quantify the relative expression of lnc-MAP3K13-3:1, miR-6894-3p, SHROOM2, and Caspase9 mRNA in each group. Cell proliferation was analyzed using the cell counting Kit-8 assay, while flow cytometry was used to assess cell cycle distribution and apoptosis. Migration capabilities were evaluated through cell scratch assays, and dual-luciferase assays were utilized to verify interactions between miR-6894-3p, lnc-MAP3K13-3:1, and SHROOM2.ResultsOverexpression of lnc-MAP3K13-3:1 and miR-6894-3p mimic transfection resulted in increased expression of SHROOM2 and Caspase9 mRNA, as demonstrated by qPCR. The miR-6894-3p mimic regulated the activity of lnc-MAP3K13-3:1. Functional assays showed that lnc-MAP3K13-3:1 overexpression inhibited proliferation in HuH-7 and Li-7 cells, promoted apoptosis, reduced migration in Li-7 cells, but enhanced migration in HuH-7 cells. Additionally, lnc-MAP3K13-3:1 overexpression significantly increased the proportion of HuH-7 cells in the G2/M phase and Li-7 cells in the S phase. The miR-6894-3p mimic modulated the effects of lnc-MAP3K13-3:1 on cell proliferation, apoptosis, and migration. Dual-luciferase assays confirmed direct binding between lnc-MAP3K13-3:1 and miR-6894-3p, as well as between miR-6894-3p and SHROOM2.ConclusionThese findings indicate that overexpression of lnc-MAP3K13-3:1 regulates SHROOM2 expression through targeting miR-6894-3p, thereby influencing cell proliferation, apoptosis, migration, and other cellular processes associated with HCC.

Impaired hydrogen sulfide biosynthesis underlies eccentric contraction-induced force loss in dystrophin-deficient skeletal muscle.

Eccentric contraction- (ECC) induced force loss is a hallmark of murine dystrophin-deficient (mdx) skeletal muscle that is used to assess efficacy of potential therapies for Duchenne muscular dystrophy. While virtually all key proteins involved in muscle contraction have been implicated in ECC force loss, a unifying mechanism that orchestrates force loss across such diverse molecular targets has not been identified. We showed that correcting defective hydrogen sulfide (H2S) signaling in mdx muscle prevented ECC force loss. We also showed that the cysteine proteome of skeletal muscle functioned as a redox buffer in WT and mdx muscle during ECCs, but that buffer capacity in mdx muscle was significantly compromised by elevated basal protein oxidation. Finally, chemo-proteomic data suggested that H2S protected several proteins central to muscle contraction against irreversible oxidation through persulfidation-based priming. Our results support a unifying, redox-based mechanism of ECC force loss in mdx muscle.