Search Results (232)

Thyroid cancer (TC) is the most common endocrine malignancy, with incidence increasing worldwide. Although most differentiated TCs have a favorable prognosis, radioiodine (RAI)-refractory differentiated thyroid cancer (DTC), BRAF inhibitor-resistant papillary thyroid cancer, and anaplastic thyroid cancer (ATC) remain major areas of unmet clinical need. The sirtuin (SIRT) family of NAD⁺-dependent enzymes has emerged as a multifaceted regulator of TC biology, with isoform-specific dichotomous roles: SIRT1, SIRT6, and SIRT7 act as tumor promoters through engagement of BRAF/MAPK, PI3K/AKT, epithelial–mesenchymal transition (EMT), and Hippo pathways, while SIRT3 and SIRT4 function as tumor suppressors via mitochondrial metabolic regulation. This review synthesizes recent developments that expand the therapeutic landscape: (i) the recognition that SIRT7 functions as a desuccinylase with preclinically identified oncogenic substrates, modifying KIF23 in ATC and LATS1 in PTC; (ii) the emerging roles of isoform-specific SIRT axes, including the NAMPT–SIRT1–PD-L1 axis, SIRT6-associated regulatory T-cell biology, and SIRT2 as a T-cell metabolic checkpoint, as determinants of immune microenvironment state and potential modulators of immune checkpoint inhibitor response; and (iii) the SIRT6–nuclear receptor coactivator 4 (NCOA4) ferritinophagy axis as a supported ferroptosis vulnerability in ATC, with potential but still hypothesis-generating relevance to dedifferentiated and RAI-refractory DTC. Importantly, the therapeutic logic for SIRT6 is disease-state-specific rather than contradictory: SIRT6 inhibition is rationalized in BRAF-driven aggressive PTC and DTC contexts where SIRT6 supports MAPK signaling, EMT, and ferroptosis resistance, whereas in SIRT6-high ATC, the same enzyme’s NCOA4-dependent ferritinophagy activity may instead be exploited to enhance ferroptosis sensitivity. We review the current SIRT modulator pharmacological toolkit—including EX-527, OSS_128167, and emerging SIRT7-selective inhibitors—and identify the substantial clinical translation gap, with no SIRT-targeted clinical trial yet conducted in TC, despite strong preclinical rationale. We outline biomarker-stratified combination strategies with BRAF/MEK inhibitors, multikinase inhibitors, immune checkpoint inhibitors, and ferroptosis inducers, prioritizing biomarker-driven preclinical validation and, where supported by efficacy and safety data, subsequent early-phase evaluation in BRAF V600E-mutant and SIRT6-high thyroid cancer. Sirtuins thus represent a mechanistically promising and potentially biomarker-stratifiable therapeutic hypothesis for difficult-to-treat thyroid cancer; however, clinical translation remains at an early stage and requires validated biomarkers, isoform-selective compounds, and disease-specific in vivo evidence. Full article

Premature coronary artery disease (PCAD) is a growing public health concern, especially in South Asia, where traditional risk factors fail to fully explain the increasing incidence of early-onset myocardial infarction. To explore its molecular underpinnings, we conducted a pilot study analyzing plasma proteins and lipids to identify potential biomarkers and dysregulated pathways associated with PCAD. Label-free quantitative proteomics revealed distinct molecular signatures separating PCAD patients from age- and sex-matched healthy controls. Key alterations included upregulation of GALE, immunoglobulin genes, and KIF20B, suggesting enhanced inflammatory responses and proliferative activity associated with post-myocardial infarction cellular repair. Similarly, down regulations of various proteins linked to multiple functions, such as myocardial infarction, hemoglobinopathy, complement and coagulation cascade, and fatty acid and lipoprotein transport in hepatocytes, were observed. Untargeted lipidomics further revealed significant elevations in several phosphatidylcholine species (PC 42:5, PC 40:3, and PC 42:7), highlighting disruption of highly unsaturated phospholipid metabolism. Overall, these findings indicate that PCAD is a multifactorial disorder involving metabolic, immune, and vascular dysfunction beyond conventional lipid abnormalities, underscoring the need for larger cohort studies to validate these biomarkers and uncover novel therapeutic targets. Full article

Fine particulate matter with a diameter ≤2.5 μm (PM_2.5) pollution poses a global public health crisis, demonstrating significant threats to human health. This study focused on the strategically important Chengdu-Chongqing Economic Circle in western China, systematically comparing the toxic effects of urban and rural PM_2.5 across five levels. PMF and regression analysis were used to identify source contributions, dual-omics to pinpoint key molecules, and epidemiological data with a GAM model to assess health risks. Findings demonstrate that rural PM_2.5 possesses greater biotoxicity than its urban counterpart. Cytotoxicity in urban and rural PM_2.5 originated from road dust/vehicle emissions and biomass burning, respectively. Subsequently, integrated omics and molecular biology analyses identify kinesin family member 20A (KIF20A) as a shared key target, which mediates toxicity induced by both urban and rural PM_2.5. Finally, epidemiological analysis reveals that females and ≥65 years old exhibit relatively high sensitivity to urban PM_2.5 exposure trends, with rhinitis showing a comparatively higher impact among various related diseases. The novelty of this work lies in its pioneering application of a multi-tiered investigative approach. This approach spans “environmental samples-cellular mechanisms-population health” within the Chengdu-Chongqing economic circle context, systematically elucidating common and distinct respiratory health risk of urban and rural PM_2.5. This work offers a vital scientific foundation for advancing region-specific, precise air pollution prevention and control measures. Full article

This study aimed to integrate apoptosis-associated and proliferation–apoptosis-coupled transcriptomic signatures with explainable machine learning to construct an exploratory molecular classification model for psoriasis. Transcriptomic datasets GSE30999 and GSE53552 were merged as the skin-tissue training cohort, and GSE55201, a whole-blood transcriptomic dataset, was used as an independent cross-tissue external validation cohort. Differential expression analysis identified 3707 DEGs, and intersection with GeneCards apoptosis-related genes yielded 894 overlapping genes. After PPI-based hub gene selection, eight machine learning algorithms were exploratorily compared within a preselected 25-gene feature space. DALEX-based permutation feature importance analysis identified a five-gene apoptosis-associated and proliferation–apoptosis-coupled signature comprising CCNB1, KIF11, HDAC1, TPX2, and MELK. The five-gene model achieved an AUC of 0.966 in the training cohort and 0.811 in the external whole-blood validation cohort, indicating moderate cross-tissue generalizability. Calibration and decision-curve analyses were performed only in the training cohort and should be interpreted as exploratory analyses rather than evidence of clinical utility. Overall, this study provides an interpretable transcriptomic classification framework for distinguishing psoriasis from healthy controls, while its ability to differentiate psoriasis from clinically similar dermatoses remains to be validated in independent disease-control cohorts. Full article

Postherpetic neuralgia (PHN) is a chronic neuropathic pain condition that arises following varicella-zoster virus reactivation and represents a significant clinical burden. Despite known risk factors, the genetic basis of PHN remains poorly understood. This study aimed to identify genetic variants associated with PHN through the secondary analysis of GWAS summary data (GCST012124). One genome-wide significant locus (KIF1B) and several suggestive variants (PTPRZ1, PRKCE, CXCR4) were identified. These genes converge on pathways related to axonal transport, neuroinflammation, and nociceptive sensitization. Findings support a multifactorial genetic contribution to PHN and highlight potential targets for future research and therapeutic development. Full article

Impairment of axonal transport may contribute to the degeneration of dopaminergic (DAergic) neurons in the substantia nigra (SN), a key event in Parkinson’s disease (PD) pathogenesis. Due to the lack of early diagnosis, changes in axonal transport at the preclinical stage can only be studied in PD models. We assessed gene expression (RT-PCR after cell sorting) and protein levels (semiquantitative immunohistochemistry) of axonal transport-related proteins in SN DAergic neurons from mice in subchronic MPTP models of PD (preclinical and clinical stages) and controls. The proteins studied included α-tubulin (Tuba1a), β-tubulin (Tubb3), kinesin (Kif5b, Klc1), dynein (Dynll1, Dync1i1), dynactin (Dctn1), microtubule affinity-regulating kinase 1 (Mark1), and tau (Mapt). In the preclinical stage, Kif5b expression and Kif5B level were increased, possibly to compensatorily preserve anterograde transport. Dynll1 and Tuba1a were upregulated, whereas Dync1i1 and Mapt were downregulated, with no change in tubulin or tau protein levels. In the clinical stage, Klc1, Dync1i1, Dctn1, Mark1, and Mapt expression and Kif5B protein levels decreased. These data indicate that transcriptional alterations in axonal transport proteins precede protein-level changes in DAergic neurons. The upregulation of Kif5B in the preclinical stage suggests that axonal transport proteins may serve as potential early therapeutic targets in PD. Full article

Background: Growth factor therapy often fails in diabetic foot ulcers (DFUs). The reason remains unclear. Standard differential expression analysis may miss functionally critical genes with modest expression changes. Methods: We performed a secondary computational analysis of a longitudinal DFU transcriptomic dataset (Dryad; 17 patients, 117 serial biopsy samples, 12-week follow-up). Co-expression networks were built separately for healed (n = 37) and non-healed (n = 80) samples. Virtual gene knockout (VGK) was used to rank genes by topological impact on network cohesion. Single-cell analysis (GSE165816) assessed the association between endogenous KIF13A expression and keratinocyte migration-related signatures. A conceptual Hill-equation simulation was used to illustrate the transport-signaling threshold relationship. Drug repurposing used DSigDB enrichment. An independent bulk DFU cohort (GSE134431) was used for external validation. Results: KIF13A showed no differential expression (log₂FC = 0.173, p = 0.263) yet ranked first by VGK topological impact. In keratinocytes, high KIF13A expression correlated with greater migration scores versus zero-detection cells (p = 0.0058). A clear threshold effect emerged: below the 30th expression percentile, EGF, PDGF, and FGF pathway activation scores remained near baseline. In a structural-equation model, transport activity negatively predicted inflammation (standardized β = −0.92, p < 0.001). HIF1A showed the strongest positive correlation with KIF13A in keratinocytes (Spearman ρ = 0.26, p < 0.001), and FOS showed a negative correlation in the single-cell analysis (ρ = −0.16, p < 0.001) and in the bulk longitudinal cohort (ρ = −0.32, p < 0.001, n = 117). Recurrent AKR1B1-related drug signatures nominated the aldose-reductase pathway, and epalrestat was therefore prioritized as a hypothesis-generating candidate compound rather than a direct top-ranked enrichment hit. External validation confirmed consistent upregulation of KIF13A (Fold-Change = 1.58, adj. p = 0.0075), EPN1, and CLIP1 in DFU tissue. Despite population-level upregulation, a subset of cells fell below the functional signaling threshold. Conclusions: These computational findings suggest that KIF13A-associated vesicle transport impairment may represent a candidate systems-level bottleneck for growth-factor responsiveness in DFUs, a network-level pattern not captured by standard differential-expression analysis. Epalrestat, an AKR1B1 inhibitor prioritized through recurrent AKR1B1-related drug signatures, is presented as a candidate compound for further evaluation. As the present analysis is observational and computational, the findings should be interpreted as hypothesis-generating; experimental perturbation studies and prospective clinical validation are required. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with limited effective therapies. Dihydroartemisinin (DHA), a derivative of artemisinin, exhibits potent antitumor activity, but its molecular mechanisms in HCC are unclear. Here, we identified kinesin family member 11 (KIF11) as a critical effector of DHA. Methods: Bioinformatic analyses revealed that KIF11 is significantly upregulated in HCC and associated with poor prognosis, and gene expression profiling suggested its oncogenic role via the PI3K/Akt pathway. Functional studies demonstrated that DHA inhibits HCC cell proliferation, migration, invasion, and colony formation, while inducing apoptosis. Xenograft models of nude mice were established for validation. Results: DHA downregulated KIF11 and epithelial–mesenchymal transition markers, whereas KIF11 overexpression attenuated DHA’s inhibitory effects; the inhibition of PI3K restored DHA sensitivity in KIF11-overexpressing cells. In vivo, DHA markedly suppressed tumor growth and malignancy in xenograft models, consistent with modulation of KIF11 and EMT-related proteins. Conclusions: DHA exerts antitumor effects in HCC by acting via KIF11 and PI3K/Akt modulation, providing a potential therapeutic strategy. Full article

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, underscoring the need for robust molecular biomarkers to improve prognosis and therapeutic strategies. Although advances have been made in imaging, surgery, as well as systemic therapies, the prognosis of HCC remains poor due to late detection, high recurrence, and molecular heterogeneity, underscoring the significance of identifying robust prognostic biomarkers and therapeutic targets. mRNA-sequencing data from the TCGA-HCC cohort were examined to recognize differentially expressed genes (DEGs) between tumor and normal tissues. Weighted gene co-expression network analysis (WGCNA) was applied to uncover key gene modules and hub genes. Protein–protein interaction network (PPIN) construction and modular analysis further refined candidate genes. Univariate overall survival (OS) analysis identified five genes (TTK, CENPA, NUF2, KIF2C, and CDCA8) whose elevated expression significantly correlated with poor patient survival. Pathway enrichment analysis exhibited a strong association with mitotic checkpoint and kinetochore signaling pathways. Mutational profiling demonstrated frequent genomic alterations, particularly in NUF2, whereas immune infiltration analysis demonstrated significant correlations between NUF2 expression and multiple immune cell populations. In this study, we employed an integrative transcriptomic and systems biology approach to recognize prognostically relevant hub genes in HCC. Collectively, this finding highlights the critical genes that may serve as prognostic biomarkers and potential therapeutic targets in HCC. Full article

Spinocerebellar Ataxia type 2 (SCA2) and Amyotrophic Lateral Sclerosis type 13 (ALS13) are triggered by polyglutamine expansion in Ataxin-2 (ATXN2). To understand these neurodegenerative disorders at the molecular level, the brains of 10-month-old Atxn2-CAG100-knockin mice were analyzed as microglial, astroglial and neuronal fractions via global RNA sequencing. Data were validated by comparison with the spinal cord oligonucleotide microarray profile or filtered by RNA-seq consistency. Here, we show that the mutation causes a massive inflammatory response in microglia and a reciprocal loss of neuronal transcripts in glial fractions, suggesting severe synapse loss. Beyond these general neurodegenerative signs, we identify pathognomonic changes in the machinery for protein translation and RNA splicing. Glial fractions showed upregulation of Gpnmb (to 2082%), Cst7, Clec7a, Axl, Csf1, Lgals3, Lgals3bp, Slc11a1, and Usp18 as an unspecific neuroinflammatory signature, versus downregulation of axonal Nefh (to <19%), and synaptic Scn4b, Camk2b, Rab15, and Grin1 mRNAs correlating with circuit disconnection. In all fractions, reductions in Kif5a, Rph3a, and Cplx1 were noted versus disease-specific inductions of ribosomal subunits, presumably mirroring the partial loss-of-function of ATXN2 as RNA translation modulator. Selective accumulations of embryonic factors Rnu1b2 and Eef1a1 versus downregulation of adult Eef1a2 specify the mutation impact on splicing and translation elongation. As a potential underpinning of toxic gain-of-function, the proteostasis transcript Rnf213 appeared increased in astroglial and microglial fractions. These transcriptome data suggest altered ribosomal and spliceosome machinery, with massive microgliosis versus mild astrogliosis, at the core of SCA2 and ALS13. Full article

K-Rev Interaction Trapped protein-1 (KRIT1) is a scaffold protein that forms functional protein complexes involved in physiologically important signaling networks. While it is primarily recognized for its association with Cerebral Cavernous Malformations (CCMs), KRIT1 may also play critical roles in tumor formation and the acquisition of malignant phenotypes, regulating cell adhesion, cytoskeletal dynamics, and angiogenesis. In this study, we investigated the role of KRIT1 in cancer cell migration and metastasis, with a focus on identifying novel interacting proteins and characterizing the intracellular signaling pathways activated upon its loss. By using a yeast two-hybrid screening, we identified Kinesin Family Member 1C (KIF1C), a protein involved in regulating podosome and invadopodium elongation, as a novel binding partner of KRIT1, and the interaction was confirmed in melanoma and epithelial cancer cells. In silico docking and interaction interface analyses supported the KRIT1–KIF1C interaction, providing structural insight into the binding mode as shown experimentally. We also found that SRC and focal adhesion kinase (FAK) phosphorylation, as well as Ras homolog family member A (RhoA) expression, represent additional pathways affected by the loss of KRIT1. This study confirms our earlier hypothesis that KRIT1 functions as a tumor suppressor and uncovers a compelling link between its loss and enhanced cancer aggressiveness. Full article

To compare the genetic causes, prevalence, and clinical characteristics of syndromic and non-syndromic familial exudative vitreoretinopathy (FEVR). A total of 281 patients with FEVR who underwent clinical and genetic evaluation at five ophthalmological institutions in Japan between 2010 and 2023 were included. Whole-exome sequencing, Sanger sequencing, or karyotype analysis was performed using blood samples from probands and available family members. Clinical characteristics of FEVR probands were assessed according to the presence or absence of systemic abnormalities. Among the 281 FEVR probands, 42 (15%) had syndromic FEVR and 239 (85%) had non-syndromic FEVR. Syndromic FEVR was more frequently diagnosed during infancy (95% vs. 57%, p < 0.0001) and occurred more often in sporadic cases (69% vs. 50%, p = 0.028). Variants in Norrin/β-catenin signaling genes were less common in syndromic FEVR (29% vs. 54%, p = 0.0026), whereas symmetrical retinal severity was more frequently observed (67% vs. 39%, p = 0.001). Sex distribution did not differ between groups. Pathogenic variants were identified in 71% of syndromic cases, most commonly in KIF11, NDP, CTNNB1, DOCK6, TSPAN12, and LRP5. Syndromic FEVR exhibits distinct and heterogeneous genetic and clinical features compared with non-syndromic FEVR. Genotype–phenotype characterization may enable earlier diagnosis. Full article

Osteosarcoma (OS) is an aggressive bone malignancy with poor prognosis, characterized by high metastasis rates. Kinesin family member 18B (KIF18B), a key protein in cell division and mitosis, has emerged as a potential diagnostic and therapeutic target in various cancers, including OS. This study investigates the role of KIF18B in OS progression and its underlying mechanisms. We found that KIF18B expression is significantly upregulated in OS tissues and correlates with lymph node metastasis (N-stage) and clinical stage. Knockdown of KIF18B inhibited OS cell migration, invasion, proliferation, and tumorigenesis. Mechanistically, KIF18B promotes OS survival through the ubiquitin–proteasome system (UPS) by regulating Skp2 protein degradation. KIF18B knockdown accelerated Skp2 ubiquitination, leading to reduced Skp2 levels and inhibited OS cell viability and glycolytic metabolism. Overexpression of KIF18B enhanced OS cell viability and glycolysis in an Skp2-dependent manner. These findings suggest that the KIF18B-Skp2 axis plays a critical role in the metabolic reprogramming of OS cells and serves as a novel prognostic biomarker and therapeutic target in OS. Full article

Background: Breast cancer (BC) is one of the most diagnosed malignancies and a leading cause of cancer-related mortality among women worldwide, thereby posing a substantial threat to women’s health worldwide. However, clinically robust diagnostic biomarkers with high sensitivity and specificity, as well as well-validated molecular targets for targeted therapy, remain limited. Methods: BC transcriptomic data from seven GEO datasets and the TCGA-BRCA cohort (n = 1231) were integrated for analysis. After batch-effect correction, candidate genes were screened through DEA, WGCNA, and PPI networks analysis. An ensemble machine learning (ML) framework incorporating 127 algorithmic combinations was constructed, and SHAP analysis was applied to identify hub genes. Further analyses included functional enrichment, immune infiltration, miRNA regulatory network analysis, and SMR analysis. The expression patterns were validated using single-cell transcriptome data. Drug repositioning analysis and AI-assisted virtual screening were performed to prioritize compounds with favorable drug-like properties. The predicted binding modes of candidate compounds with CHEK1 were assessed by molecular docking. Results: Thirty core genes were obtained through differential expression, WGCNA, and PPI screening. Integrated ML (127 algorithms) determined the optimal model (AUC = 0.919), and SHAP identified nine feature genes, among which CHEK1 and KIF23 showed preliminary diagnostic potential across four external cohorts (AUC: 0.625–0.938). Functional enrichment indicated that both are enriched in the cell cycle and p53 pathways, closely associated with BRCA1/ATR; immune infiltration revealed significant correlations with macrophages and CD8⁺ T cells, with hsa-miR-15a-5p and hsa-miR-607 being common upstream regulatory miRNAs. SMR analysis supported a causal relationship between CHEK1 expression and BC genetic susceptibility (p_SMR < 0.05, p_HEIDI > 0.05); single-cell analysis confirms its heterogeneous expression. AI-assisted virtual screening identified 25 A-grade computational candidate compounds from 171 candidates. Molecular docking suggested that Olaparib and LY294002 can form favorable interactions with the CHEK1 active pocket. Conclusions: The study identified CHEK1 as a key diagnostic gene for BC through 127 ML algorithms and SMR causal inference. By combining AI-assisted virtual screening and molecular docking, computational candidate compounds targeting CHEK1 were prioritized. These findings represent hypothesis-generating in silico predictions and require experimental validation before any therapeutic conclusions can be drawn. Full article