Search Results (242)

Background/Objectives: Hepatocellular carcinoma (HCC) is the most prevalent primary liver tumor and is often diagnosed at advanced stages with very poor therapeutic response, leading to high mortality. Thus, new therapeutic strategies and biomarkers are urgently needed. We previously showed that the combination of loratadine, raloxifene, and sorafenib exerts synergistic cytotoxicity on HCC cells. Here, we explored potential molecular mechanisms underlying the anticancer effects of this combination using multiomics analyses. Methods: We performed proteomic analyses based on mass spectrometry, transcriptomic analyses using the Clariom D Plus human microarray (Affymetrix), and metabolomic analyses based on nuclear magnetic resonance to investigate the profile changes induced by the drug combination in HuH7 cells. Bioinformatic analyses were applied to associate the omics changes with biological functions, molecular interactions, and clinical relevance in terms of patient survival. Results: We identified several molecules whose expression changed in response to treatment across the three omics profiles analyzed. Some of them were found to be involved in hallmarks of cancer, including sustained proliferation, evasion of growth suppressors, and resistance to cell death. Integrated multi-omics analyses revealed that the drug combination suppresses critical oncogenic drivers (C7orf50, NUP188, and HS2ST1) and that the mitotic cell cycle process, DNA synthesis and cholesterol biosynthesis are the primary pathways affected. Protein–protein interaction analysis revealed five key hubs (KIF2C, PCNA, TRIP13, NDC80, and RPA3), whose expression in HCC is associated with poor clinical prognosis. Conclusions: The combined treatment rewired molecular networks involved in HCC progression. These findings identify clinically relevant molecular targets associated with poor prognosis and provide mechanistic insights into the synergistic anticancer activity of this drug combination. Full article

Background/Objectives: High-grade pulmonary neuroendocrine carcinoma (HGNEC-L), including SCLC and LCNEC, is aggressive and usually treated according to SCLC paradigms. The clinical relevance of de novo actionable genomic alterations (AGA) remains incompletely defined. Methods: We performed a retrospective multicenter analysis of advanced HGNEC-L with de novo AGA, assessing rwORR, rwDCR, rwPFS, and OS. Findings were contextualized by a structured literature review and exploratory pooled reconstructed-IPD Cox analysis, with targeted therapy modeled as a source-stratified time-dependent covariate. Results: Ten patients from four tertiary centers were included. Most were women (90.0%) and never-smokers (70.0%); histology was LCNEC in 60.0% and SCLC/mixed SCLC in 40.0%. AGA included EGFR mutations (n = 6), EML4-ALK fusions (n = 2), KIF5B-RET fusion (n = 1), and KRAS p.G12C (n = 1). Targeted-containing regimens achieved rwORR 77.8%, rwDCR 88.9%, and median rwPFS 9.0 months (95% CI, 2.0–18.7), as opposed to 3.7 months for ICI-containing regimens and 2.6 months for chemotherapy alone. Median OS for the entire cohort was 17.2 months (95% CI, 4.8–36.3); overall survival did not differ significantly between patients with and without targeted-containing exposure (19.0 vs. 17.2 months; log-rank p = 0.50). In pooled reconstructed-IPD time-dependent Cox analysis (72 patients, 39 deaths), targeted therapy showed a favorable but non-significant OS association (HR, 0.89; 95% CI, 0.31–2.56; p = 0.831), maintained directionally in the age/sex-adjusted subset (HR, 0.54; 95% CI, 0.16–1.77; p = 0.306). Conclusions: De novo AGA-positive HGNEC-L represents a clinically relevant subgroup with potential sensitivity to genotype-matched targeted therapy, supporting comprehensive molecular profiling and early targeted therapy consideration. Full article

The development and maintenance of the nervous system depend on a tightly regulated intracellular transport network in which kinesin superfamily (KIF) motor proteins drive microtubule-based delivery of synaptic vesicle precursors, organelles, mRNAs, and signaling components along axons and dendrites. Disruption of this machinery underlies a clinically heterogeneous spectrum of neurodevelopmental disorders (NDDs), including intellectual disability, epilepsy, autism spectrum disorder, microcephaly, malformations of cortical development, spasticity, and axonal neuropathy. Here, we synthesize current knowledge on how kinesin dysfunction shapes neurodevelopment. We outline the physiological roles of kinesins in neuronal polarity, organelle and mitochondrial positioning, synaptogenesis, and progenitor division, and survey principal disease-associated genes, including KIF1A, KIF5A, KIF7, KIF11, KIF2A, KIF5C, and emerging members such as KIF14, KIF15, and KIF16B. We detail how distinct pathogenic mechanisms, such as loss of motility, impaired cargo coupling, motor hyperactivity, mitotic spindle defects, and disrupted ciliary signaling, converge on shared cellular endpoints, and how tubulin isotypes and posttranslational modifications further modulate motor output. In this review, we discuss translational implications, including variant-resolved diagnosis and precision strategies to restore transport, dampen pathological hyperactivity, or stabilize the microtubule track. Collectively, these advances reframe kinesinopathies as mechanistically stratified disorders of neuronal transport. Full article

Peripheral T-cell lymphomas (PTCLs) are a heterogeneous group of clinically aggressive mature T-cell and natural killer (NK)-cell neoplasms that account for approximately 10–15% of all non-Hodgkin lymphomas in Western countries . The most common subtypes include extranodal NK/T-cell lymphoma (ENKTL), nodal T-follicular helper cell lymphomas, peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS), anaplastic large cell lymphoma (ALK-positive and ALK-negative), and T-cell lymphoblastic lymphoma. Non-coding RNAs (ncRNAs) constitute the majority of the human transcriptome and play critical roles in regulating gene expression, cellular proliferation, differentiation, migration, and apoptosis. Among these, long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) have emerged as key regulators of lymphomagenesis and disease progression in PTCLs. These molecules modulate diverse oncogenic pathways through chromatin remodeling, transcriptional regulation, competing endogenous RNA activity, and interactions with RNA-binding proteins, thereby influencing proliferation, immune evasion, treatment resistance, and clinical outcomes. Representative examples include the lncRNA TCLlnc1, which promotes PTCL progression through activation of transforming growth factor-β (TGF-β) signaling, and the circRNAs circKIF4A, circADARB1, and circ-LAMP1, which regulate miRNA-dependent signaling networks involving PDK1/BCL11A, STAT3, and DDR2, respectively. In this review, we summarize the current understanding of the biological and clinical roles of lncRNAs and circRNAs in PTCL and related T-cell and NK-cell neoplasms and highlight their potential as diagnostic and prognostic biomarkers as well as therapeutic targets. We also discuss recent advances and future directions for integrating ncRNA-based approaches into precision medicine for T-cell lymphoma. Full article

High-altitude environments expose aquatic organisms to complex environmental challenges, including fluctuations in dissolved oxygen levels, water temperature, and other habitat conditions. The freshwater snail Cipangopaludina cathayensis has limited dispersal ability and is strongly associated with local habitat conditions, making it a suitable species for investigating biological responses to long-term environmental variation. In this study, high-altitude and low-altitude populations of Cipangopaludina cathayensis were compared using biochemical assays, shell elemental composition analysis, transcriptomics, and metabolomics to explore altitude-associated physiological and molecular responses. Environmental monitoring showed that the high-altitude habitat exhibited lower water temperatures, greater thermal variability, and significantly higher dissolved oxygen availability than the low-altitude habitat, indicating distinct environmental conditions between the two populations. The high-altitude population exhibited significantly higher superoxide dismutase (SOD) and pyruvate kinase (PK) activities than the low-altitude population, whereas malondialdehyde (MDA) content and total ATPase (T-ATPase) activity showed no significant differences between populations. Shell microstructure and elemental analyses revealed altitude-associated differences in biomineralization. Transcriptomic analysis identified differentially expressed genes involved in intracellular transport, including KIF10, KIF11, KIF13, KIF17, MYO3, and MYO7A, as well as apoptosis-associated genes, including CASP2, CASP3, and BCL-2. Integrated transcriptomic and metabolomic analyses further highlighted purine metabolism, D-amino acid metabolism, insulin resistance, and alanine, aspartate and glutamate metabolism as shared enriched pathways between the two populations. These findings indicate that Cipangopaludina cathayensis may cope with high-altitude environments through coordinated regulation of antioxidant defense, intracellular transport, apoptosis-associated pathways, and metabolic homeostasis. Full article

Clear cell renal cell carcinoma (ccRCC), hepatocellular carcinoma (HCC), lung adenocarcinoma (LUAD), and pancreatic ductal adenocarcinoma (PDAC) are highly lethal cancers that share molecular mechanisms underlying tumor progression, yet common biomarkers across these cancers remain largely unexplored. Microarray datasets for the four cancers were analyzed to identify differentially expressed genes (DEGs) using adjusted $p<0.05$ and $\left|{\log }_2\mathrm{FC}\right|>1$ as significance thresholds. Disease-associated gene targets were collected from CTD, DISEASES, and GeneCards databases. Shared genes were identified across cancers, and functional enrichment analysis revealed their involvement in key cancer-related pathways, particularly the cell cycle. Protein–protein interaction networks identified ten candidate hub biomarkers (HGF, CDK1, CCNB1, RRM2, KIF14, DCN, SERPINE1, CCNA2, DLGAP5, and MAD2L1) consistently dysregulated across all four cancers. Survival analysis supported their potential as therapeutic targets, correlating with poor prognosis. These findings highlight candidate pan-cancer biomarkers for improved diagnosis and therapy. Full article

Estrogen receptor (ER)-positive breast cancer (BrCa) accounts for two-thirds of all BrCa cases worldwide. Therefore, ER-targeted endocrine therapy is the standard treatment for this disease. There has been a recent trend towards developing combination therapies using molecularly targeted drugs to improve outcomes. This study aimed to identify therapeutic targets demonstrating efficacy when combined with fulvestrant (a selective ER downregulator/degrader). We generated microRNA (miRNA) signatures from fulvestrant-treated MCF-7 cells by RNA sequencing. From the signature, we evaluated miR-374b-5p because its expression was elevated by fulvestrant treatment in MCF-7 cells. Also, in expression analysis by subtype of BrCa patients, miR-374b-5p expression was suppressed only in luminal BrCa. Ectopic expression assays revealed that miR-374b-5p attenuated the malignant phenotypes of MCF-7 cells. We searched for genes regulated by miR-374b-5p and discovered that 11 (NEK2, NUF2, HMMR, DEPDC1B, FOXM1, ELOVL6, KIF20A, NCAPH, CENPK, FAM83D, and KIAA0101) are closely involved in BrCa molecular pathogenesis. Among these target genes, we focused on forkhead box M1 (FOXM1), a transcription factor regulating cell cycle progression and division. Notably, combination therapy with fulvestrant and a FOXM1 inhibitor significantly suppressed MCF-7 cell proliferation. From the miRNA signature established in this study, we identified antitumor miR-374b-5p and its target genes and used these findings to explore candidate drugs with potential efficacy when combined with fulvestrant. Full article

Prostate adenocarcinoma is characterized by substantial inter-patient heterogeneity, limiting the clinical reliability of conventional diagnostic tools, including prostate-specific antigen testing. This limitation underscores the need for robust molecular biomarkers that may complement conventional diagnostic tools, highlighting the urgent need for biomarkers capable of enhancing diagnostic accuracy and enabling more precise risk stratification. In the present study, transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed using an integrative bioinformatics and machine learning pipeline., The proposed workflow was designed as a stepwise and reproducible biomarker prioritization framework in which differential expression analysis, functional enrichment, protein–protein interaction (PPI) based network interpretation, graph-convolutional feature selection, and hybrid ensemble machine learning were sequentially integrated. Differential gene expression analysis was combined with pathway enrichment (Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome), protein–protein interaction network construction, and graph-convolutional feature selection. Multiple machine learning algorithms, including Random Forest, Gradient Boosting Machine, Support Vector Classifier, Artificial Neural Network, and AdaBoost, were systematically evaluated. A hybrid ensemble model integrating Gradient Boosting Machine and Random Forest (GBM+RF) was subsequently developed. Model performance was assessed using accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic (ROC) and externally validated using the independent GSE14206 dataset. The analysis revealed a coordinated molecular pattern characterized by dysregulated cell cycle activity and enhanced interferon-mediated immune signaling. Protein–protein interaction analysis identified STAT1 and PLK1 as highly connected network hub genes within immune-related and cell-cycle-associated modules. Among the evaluated models, the hybrid GBM+RF framework achieved the highest predictive performance on the TCGA dataset, with AUC: 0.9526; Accuracy: 97.49%. External validation using the GSE14206 dataset confirmed the robustness of this model (AUC: 0.9156; Accuracy: 91.53%). These findings support a broader multi-gene candidate signature in prostate adenocarcinoma, in which machine learning prioritized genes such as XAF1, APP, RPA3, IFIH1, UBE2D2, RSAD2, KIF2C, and PLK1, while STAT1 and PLK1 provided complementary network-level biological relevance. The proposed framework provides a robust and transferable strategy for biomarker discovery and precision oncology. Full article

Background and Objectives: Lung adenocarcinoma (LUAD) is a clinically heterogeneous malignancy, and reliable prognostic biomarkers are still needed. Kinesin family members 4A and 4B (KIF4A and KIF4B) are mitosis-related motor proteins with potential functional overlap as paralogs. However, their coordinated prognostic significance in LUAD has not been systematically investigated. Materials and Methods: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) were analyzed to evaluate the expression patterns, clinicopathologic associations, and prognostic significance of KIF4A and KIF4B in LUAD. Correlation analysis, Kaplan–Meier survival analysis, and Cox proportional hazards regression analyses were performed. In addition, a combined paralog score and four-group expression model were evaluated. An independent LUAD cohort from the Gene Expression Omnibus (GEO; GSE81089) was analyzed for external validation. Results: KIF4A and KIF4B expression showed a strong positive correlation (r = 0.767, p < 0.001), and both genes were positively correlated with EGFR, KRAS, BRAF, MKI67, and PCNA expression. High KIF4A expression was significantly associated with age, sex, smoking status, pathologic stage, N stage, and T stage, whereas high KIF4B expression was significantly associated with age and pathologic stage. Kaplan–Meier analysis demonstrated that high expression of both KIF4A and KIF4B was associated with poorer overall survival. In Cox regression analyses, elevated expression of both genes remained significantly associated with unfavorable overall survival in univariable and multivariable models. However, when both genes were simultaneously included in the same Cox model, their individual prognostic effects were attenuated, suggesting substantial overlap in prognostic information. By contrast, the combined paralog score remained independently associated with poor overall survival. In four-group analysis, only patients with concurrent high expression of both KIF4A and KIF4B showed significantly worse overall survival compared with the low/low group. External validation demonstrated generally consistent survival patterns, although the prognostic associations were attenuated after multivariable adjustment. Conclusions: KIF4A and KIF4B expression showed substantial prognostic overlap in LUAD, and their concurrent high expression was associated with poorer overall survival. These findings suggest that KIF4A/KIF4B co-expression may serve as a candidate prognostic indicator that warrants validation in independent clinical cohorts and functional studies. Full article

KIF21A, a member of the Kinesin-4 family of motor proteins, is involved in the regulation of microtubule dynamics and intracellular transport, with emerging evidence suggesting its potential role in cancer progression. In this study, we performed an integrative analysis of over 3825 human phosphoproteomics studies to characterize site-specific phosphorylation of KIF21A. Three predominant phosphosites were identified in KIF21A (S853, S1212, and S1239) with the highest detection frequency across phosphoproteomics studies, and were analyzed for co-regulation patterns to identify potential kinase associations and functional networks. Phosphosite S853 showed a strong association with cytoskeletal organization and cortical microtubule stabilization complexes (CMSCs) components, including KANK1 (S186), PHLDB2 (S513, S42) and CLASP1 (S600, S572, S646), indicating its role in cytoskeletal organization. Upstream kinase analysis identified potential regulators, such as PAK2, RPS6KA1/A3, RPS6KB1, CHEK1/2 and CDK18/16 with site-specific variability in their associations with KIF21A predominant sites. Interestingly, phosphosite-specific correlation analysis between KIF21A and candidate kinases revealed that the KIF21A S1239 phosphosite exhibited tumor-specific correlations with CDK18 across multiple cancer types. Functional enrichment revealed that co-regulated phosphoproteins were involved in cytoskeleton regulation, cell cycle regulation, and carcinogenesis. Pan-cancer analysis demonstrated dysregulated expression of KIF21A in multiple tumor types, with stage-associated upregulation in selected cancers. Gene-level validation further supported these findings, showing consistent positive correlations between KIF21A and key regulators such as CTNND1 and PTK2, as well as other cytoskeleton and cancer-associated genes. Overall, this study highlights site-specific phosphorylation as a key regulatory mechanism of KIF21A and suggests its involvement in cytoskeleton-associated signaling networks in cancer. Full article

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