This review aimed to provide a comprehensive overview of the molecular landscape of HNSCC, focusing on key genetic alterations, epigenetic regulation, and therapeutic challenges associated with HNSCC. We highlighted the deregulations in key cellular signaling pathways, including PI3K/AKT/mTOR, Ras/Raf/MEK/ERK, Wnt/Beta-catenin, Notch, Hedgehog, Hippo-YAP/TAZ, and JAK/STAT, which contribute to tumor initiation, progression, and therapy resistance. In addition, we provided an overview of epigenetic mechanisms in HNSCC including DNA methylation changes, histone modifications, and non-coding RNA regulation. Emerging epigenetic therapeutic strategies under clinical investigation were also highlighted. Moreover, molecular and epigenetic signatures related to HPV-positive and HPV-negative HNSCC further emphasized the complexity and clinical heterogeneity of disease. Head and Neck Squamous Cell Carcinoma (HNSCC) represents a biologically complex malignancy characterized by molecular heterogeneity, high recurrence rate, and poor clinical outcome. A deeper understanding of the genetic and epigenetic mechanisms underlying HNSCC is essential for improving early diagnosis, and therapy response providing a better patient stratification. An extensive review of current literature was conducted using PubMed and Google Scholar which included 280 articles highlighting recent advancements in gene expression profiling in HNSCC. This review summarizes the complex molecular events in HNSCC emphasizing the key deregulations in cellular signaling pathways, differential gene expression regulated by epigenetic modifications. Understanding these molecular mechanisms may facilitate the identification of novel biomarkers and therapeutic targets, contributing to the development of more effective treatment for HNSCC.
Esophageal squamous cell carcinoma (ESCC) continues to pose significant therapeutic challenges due to its aggressive behavior and suboptimal outcomes. The mitochondrial unfolded protein response (MUPR) pathway has emerged as a potential contributor to tumor progression, yet its role in ESCC prognosis and therapy remains insufficiently characterized. This study therefore seeks to systematically identify MUPR-associated prognostic genes in ESCC and to evaluate their potential as targets for therapeutic intervention. This study analyzed public databases to correlate MUPR pathway genes with ESCC prognosis, identifying YME1L1 and ACP2. These genes were used to construct a prognostic risk model, and single-cell RNA sequencing (scRNA-seq) was employed to determine their cellular expression patterns. Furthermore, the expression levels of the identified genes were experimentally validated in human ESCC cell lines using Reverse Transcription-quantitative PCR (RT-qPCR). Subsequently, the potential of these genes as drug targets was assessed. Following computational screening, lycorine emerged as a promising candidate. Rather than relying solely on molecular docking, this study performed molecular dynamics (MD) simulations to assess the stability of the binding interactions over time. The prognostic model was able to stratify patients into high- and low-risk groups that showed significantly different survival outcomes. At the cellular level, YME1L1 and ACP2 exhibited pronounced activity in B cells and neutrophils. RT-qPCR analysis demonstrated a significant downregulation of YME1L1 and ACP2 in ESCC cell lines compared to normal esophageal epithelial cells (P < 0.05), demonstrating high concordance between our bioinformatics predictions and experimental evidence. The drug screening identified lycorine as a promising candidate, with a predicted binding energy of − 9.0 kcal/mol to ACP2. MD simulations demonstrated the stability of these interactions: both the ACP2-lycorine and YME1L1-lycorine complexes remained stable throughout the simulation period, maintaining their structural integrity and key hydrogen bonds. This study identified ACP2 and YME1L1 as a novel prognostic signature in ESCC, supported by preliminary transcriptional validation, and proposed the natural compound lycorine as a computational candidate for inhibiting this axis. Our work established a conceptual link between prognostic biomarkers and a candidate therapeutic, providing a computationally derived rationale for future experimental and translational studies in ESCC. Further investigations are warranted to validate lycorine’s efficacy in vivo and to explore its potential synergy with existing therapies, with the ultimate goal of improving clinical outcomes.
Antibiotic resistance in Streptococcus pneumoniae remains a major clinical challenge, particularly for macrolides such as erythromycin. This resistance is commonly associated with transposons Tn2009 and Tn2010 carrying the mefA gene, which encodes a macrolide efflux protein. This study investigated the genetic characteristics of mefA from Indonesian clinical isolates and elucidated its efflux mechanism using integrated genomic analysis and molecular dynamics simulations. Whole-genome sequencing confirmed the presence of Tn2009 and Tn2010 in clinical isolates. Multiple sequence alignment showed high conservation of mefA (98-100% identity), indicating strong evolutionary stability within the species. A homology model of the mefA encoded efflux protein was constructed and used for molecular docking, revealing stable erythromycin binding within the efflux channel with multiple favorable binding poses. Molecular dynamics simulations (200 ns) demonstrated structural stability of the protein, with an average root mean square deviation of 0.174 nm. Root mean square fluctuation analysis identified localized flexibility in residues Asn195-Ser199, suggesting a functionally relevant intracellular loop involved in conformational dynamics. Despite stable interactions, erythromycin remained confined within a localized channel region and did not undergo spontaneous translocation under equilibrium conditions. Steered molecular dynamics simulations indicated that ligand transport requires external force to overcome an initial energetic barrier of 553.07 kJ/mol/nm, followed by stepwise displacement through multiple transient binding sites, consistent with a multi-site relay mechanism. Umbrella sampling further revealed a rugged free energy landscape, with a maximum potential of mean force (PMF) of ~ 45 kcal/mol near the channel exit region. The PMF profile, reconstructed using WHAM across ~ 30 windows, showed well-converged overlap and multiple intermediate minima, indicating a stable sampling of the reaction coordinate. Collectively, these findings provide structural and energetic insights into mefA mediated erythromycin resistance in S. pneumoniae. The results support a mechanism involving stable substrate binding, localized conformational flexibility, and substantial energy barriers requiring active transport, highlighting potential targets for efflux inhibition strategies.
Understanding DNA sequence similarity is essential for uncovering evolutionary relationships and functional insights across diverse biological systems, particularly in the era of rapidly expanding genomic data, DNA sequence similarity analysis plays a central role in comparative genomics, evolutionary biology, and phylogenetic reconstruction. However, the rapid expansion of genomic databases has made large-scale sequence comparison increasingly challenging for traditional alignment-based approaches due to their high computational cost and limited efficiency for highly divergent sequences. Alignment-free methods provide an attractive alternative, but many existing techniques still face limitations in phylogenetic accuracy and computational efficiency. In this study, we propose a novel alignment-free method for DNA sequence similarity analysis based on dynamic template matching and subsequence similarity representation. The approach generates a sub-sequence similarity score number (SSSN) vector using direct and complementary nucleotide matching and reconstructs phylogenetic relationships from the resulting feature vectors. The method was evaluated using two benchmark datasets and four standard biological datasets. Experimental results show that the proposed approach achieves high phylogenetic accuracy (95–100%) while significantly reducing computational requirements. In particular, it is 55–1747 times faster than the MEGA tool and requires 30–99% less memory than several existing approaches. Overall, the proposed method provides an efficient and scalable framework for DNA sequence similarity analysis and phylogenetic inference in large genomic datasets. These findings demonstrate that the proposed method provides an accurate and computationally efficient framework for large-scale DNA sequence analysis, with strong potential for applications in comparative genomics, evolutionary studies, and future high-throughput genomic research. The datasets and source code supporting this study are publicly available at the provided https://github.com/machbah/DPTM_Seq_Sim Github repository.
The long non-coding RNA ANRIL and several single-nucleotide polymorphisms have been strongly implicated in genetic susceptibility to coronary artery disease (CAD). However, how these variants influence gene expression remains incompletely understood. This study aims to investigate genotype-dependent differences in linear and circular ANRIL isoform expression and selected CAD- and diabetes-related genes in monocyte-derived macrophages from healthy adult males carrying rs1333049, rs10757274, and rs564398 variants. Peripheral blood monocytes from healthy male donors with specific ANRIL genotypes were isolated and differentiated into macrophages using macrophage colony-stimulating factor. Monocyte identity and macrophage differentiation were confirmed by flow cytometry and confocal imaging. Gene expression levels of CDKN2A, CDKN2B, ABCA1, PRKAA1, PPARGC1A, TNFA, TNFAIP3, and circular and linear ANRIL transcripts were quantified by qRT-PCR. Expression differences across genotype groups and genotype-dependent correlations were assessed. The rs10757274/rs1333049 AA/CC genotype was associated with reduced expression of PPARGC1A and ABCA1, accompanied by lower TNFA and higher TNFAIP3 expression. In contrast, carriage of the G allele at rs10757274/rs1333049 was associated with increased expression of CDKN2A and linear ANRIL. The rs564398 CC genotype was associated with reduced PPARGC1A expression and altered PRKAA1 levels. Correlation analyses revealed genotype-specific associations between ANRIL isoforms and selected genes. These findings suggest that ANRIL variants are associated with genotype-dependent differences in macrophage gene expression across pathways of cell cycle regulation, inflammation, lipid metabolism, and energy homeostasis. Although exploratory, the results support the possibility that CAD- and diabetes-associated 9p21.3 variants may partly exert their effects through such transcriptional alterations.
Long non-coding RNAs (lncRNAs) are increasingly recognized as key regulators of gene expression and cancer progression; however, the majority remain functionally uncharacterized, limiting their translational and clinical relevance. In particular, the extent to which lncRNA functions are conserved across species and contribute to melanoma progression remains poorly understood. This study presents an integrative in silico characterization of mouse lncRNA Gm26982, previously implicated in melanoma models, alongside comparison with its human counterpart LINC00852, to elucidate structural, regulatory, and functional conservation with potential translational and clinical relevance. We implemented a comprehensive and robust bioinformatics pipeline integrating diverse computational tools, web servers, and publicly available databases to systematically evaluate the coding potential, synteny, sequence conservation, expression profiles, subcellular localization, secondary structure, and interaction networks of Gm26982, including its associations with miRNAs and RNA-binding proteins. Our results demonstrate that Gm26982 possesses low coding potential despite a complete reading frame, and is predominantly expressed in neural and immune-related murine tissues. Synteny analysis established its ortholog in human LINC00852 with overlapping expression domains and subcellular localization. Despite modest sequence similarity, both lncRNAs share conserved genomic contexts, overlapping tissue-specific expression patterns, and similar regulatory interactions. Notably, both transcripts were predicted to interact with miR-140-3p, suggesting a conserved regulatory mechanism potentially mediated through competing endogenous RNA (ceRNA) activity. Structural analysis further revealed differences in thermodynamic stability and folding complexity, indicating evolutionary divergence in regulatory capacity. Collectively, these findings suggest that Gm26982 and LINC00852 represent conserved lncRNAs with potential roles in melanoma-associated regulatory networks, particularly through miRNA-mediated post-transcriptional regulation. This study provides a foundation for future experimental validation. It highlights the importance of integrative computational approaches in identifying functionally relevant lncRNAs, with potential implications for biomarker discovery and therapeutic targeting in cancer.
Although observational research shows that physical activity and sedentary behavior are associated with the risk of gestational diabetes mellitus (GDM), lipid, and body mass index (BMI), their causal direction and potential mediating mechanism are still unclear, which limits the development of precise prevention strategies. Based on the genetic data on the European ancestry population, the study aimed to investigate the causal relationship of GDM with physical activity and sedentary behavior using Mendelian randomization (MR), and quantify the mediating roles of BMI and lipids in it. The bidirectional dual sample MR analysis based on whole genome association research data revealed that there was a significant negative causal association between physical activity time and the risk of GDM in females (OR = 0.977, 95% CI: 0.956-0.998, P = 0.030), while leisure screen time had a positive causal association with the risk of developing GDM (OR = 1.125, 95% CI: 1.023-1.238, P = 0.015). Mediation analysis indicated that BMI was the primary causal pathway for reducing the risk of GDM through physical activity time, with a mediation ratio of 53.6%. Multivariate MR analysis showed that after adjusting for BMI, the direct effect was no longer significant, indicating that BMI played a major and almost complete mediating role. In the causal pathway of increased GDM risk in leisure screen time, BMI, high-density lipoprotein cholesterol (HDL-C), and Apolipoprotein A1 (ApoA1) effectively mediated the causal relationship between leisure screen time and GDM risk, with mediation proportions of 81.8%, 11.2% and 10.1%, respectively. Physical activity can indirectly reduce the risk of GDM by lowering BMI, while excessive leisure screen time significantly increases the risk of GDM by affecting BMI, HDL-C, and ApoA1. These findings support the potential value of prioritizing weight control and integrating interventions that increase physical activity and limit sedentary behavior as core measures, in order to fundamentally block the pathway of GDM by synergistically optimizing weight and lipid metabolism.
Prolonged exposure to pesticides is linked to neurodegenerative disorders through mechanisms involving oxidative stress, inflammation, and neuronal signaling. Therapeutic plants may offer a promising and natural alternative for protecting against such damage. Hence, the present study aims to understand the role of Curcuma amada in mitigating pesticide-induced neurotoxicity and its molecular mechanism in Drosophila. The pesticidal stress was induced in Drosophila through oral feed of ethion and its action was confirmed through behavioural assay. The stressed flies were treated with C. amada rhizome and the effect of both ethion and ethion +  C. amada was assessed through RNA profiling and gut microbiome analysis. Decrease in locomotory activity on exposure to ethion represents the induced neuronal stress and an increase was seen after C. amada was fed to the stressed flies. Many DEGs were identified through RNAseq results of stressed and C. amada treated which were further analysed using Cytoscape. In ethion and ethion + C. amada treated flies, the upregulated and downregulated genes were found to be associated with neuronal signal processing and mitochondrial function [MRPs, Dop2R, 5-HT1A, aminoacyl-tRNA synthetase (AARs), ND-B17]. A significant change in the gut microbial population (especially decrease in Lactiplantibacillus species) was observed in stressed flies. But the restoration of healthy bacterial population such as Lactiplantibacillus in C. amada treated flies evidencing the crucial role of gut microbiome in neuronal health. This study highlights the beneficial effects of C. amada from pesticidal stress which needs to be further researched to understand the underlying molecular mechanisms.
Carbapenem-resistant Pseudomonas aeruginosa (CRPA) represents a major health threat due to its extensive resistance to last‑resort antibiotics. Although carbapenemase determinants are key drivers of global CRPA dissemination, comprehensive genomic investigations delineating their chromosomal versus plasmid contexts are sparse. Therefore, in this study we conducted an integrated comparative genomic analysis of P. aeruginosa strains harboring major carbapenemase genes (blaGES, blaKPC, blaSPM, blaNDM, blaVIM, and blaIMP), with a focus on their genomic localization, surrounding genetic architectures, and associated mobility elements. Chromosomes and plasmids carrying carbapenemase genes (retrieved from GenBank through 2025) were systematically characterized for sequence types, genetic environments, co‑occurring antimicrobial resistance genes (ARGs), and plasmid mobility features using established bioinformatic pipelines. Genetic relatedness of plasmids was inferred via ClustAGE and UPGMA clustering. Multilocus sequence typing (MLST) was employed to assess clonal relatedness of isolates. Among 398 carbapenemase-carrying genomic fragments, blaVIM, blaKPC, and blaGES were the most prevalent. blaVIM, blaIMP, and blaNDM showed broad geographic distribution. High-risk clones including ST235, ST111, ST233, ST357, ST308, and ST277 were among the most common sequence types. Notably, a minority (10.28%) of carbapenemase-carrying plasmids were predicted to be conjugative or mobilizable. The mex, and opr families, and sul1 were most frequent co-existing ARGs. These findings highlight the dominant role of established high-risk lineages and integrative mobile elements in shaping the epidemiology of resistance. The relatively low frequency of self-transmissible plasmids suggests that horizontal resistance dissemination is likely mediated through a combination of integrative mobile genetic elements and clonal expansion. Our results underscore the necessity for enhanced genomic surveillance strategies that integrate clonal tracking with mobile resistance determinant monitoring to better understand and control the spread of carbapenem resistance.
Polygalacturonases (PGs) are key enzymes that hydrolyze pectin, a complex polysaccharide in plant cell walls, with essential roles in biological processes and industrial applications. This study presents a comprehensive genome-wide identification and in-silico characterization of PGs from four fungal species: Aspergillus oryzae, Aspergillus flavus, Neurospora crassa, and Rhizoctonia solani. A total of 44 PG protein sequences were retrieved from the NCBI database, confirming the presence of the Glyco_hydro_28 (GH28) domain, which is essential for pectin hydrolysis. Phylogenetic analysis using the Neighbor-Joining method revealed four major clades (A, B, C, D), with A. flavus and A. oryzae sharing a close evolutionary relationship (bootstrap support = 93%). Gene structure analysis revealed that A. flavus (Af1) and A. oryzae (Ao1) each have one exon, while Neurospora crassa (NSc1) contains one intron. Ten conserved motifs were identified, with Motif 1 present in Rz1, Rz2, and Rz5, and Motif 2 in all sequences except Ao15 and Ao16. Chromosomal mapping indicated species-specific gene distributions, with A. oryzae showing genes spread across five chromosomes. Gene expression analysis of A. oryzae under various growth conditions revealed 20 differentially expressed genes (DEGs), including 10 upregulated (e.g., Gene_Ao1, LFC = 2.50, FDR = 0.00450) and 10 downregulated (e.g., Gene_AO9, LFC = -2.87, FDR = 1.1e-05). Pathway enrichment analysis highlighted significant involvement of PGs in apoptosis (FDR = 1.2e0-03), cell cycle regulation (FDR = 9.7e-03), and DNA repair (FDR = 2.3e-02). Protein-protein interaction (PPI) network analysis revealed 41 nodes and 400 edges, with an average node degree of 19.5. Structural modeling of the expressed protein LOCUS (XP_Ao1820953) with PDB ID: 5ZU2 showed high stability and flexibility, supported by molecular dynamics simulations. These results provide new insights into the evolutionary, structural, and functional roles of fungal PGs, with implications for their applications in biofuel production, food processing, and fiber retting.
Klebsiella pneumoniae (K. pneumoniae) is a leading cause of nosocomial infections and is increasingly linked to multidrug resistance and hypervirulence. Comprehensive genomic characterization is essential for understanding the emergence of multidrug resistant and hypervirulent K. pneumoniae strains. Therefore, this study comprehensively investigated the resistome, virulome, and plasmidome profile of 310 clinical K. pneumoniae genomes to elucidate genetic determinants of virulence and antimicrobial resistance (AMR). Multi-locus sequence typing identified 86 sequence types, with ST11 being the predominant lineage associated with KL64 and KL47 capsular types. Resistome analysis detected widespread β-lactam resistance genes, with most genomes carrying extended-spectrum β-lactamases (ESBLs). Carbapenemases namely KPC and NDM were detected in 31% and 15% of genomes respectively. The co-occurrence of multiple ESBLs (CTX-M, SHV, and TEM) within the same genome was observed in nearly half of the genomes (146/310), suggesting a strong genetic determinant of resistance to third-generation cephalosporins. ST23 genomes showed an increased abundance of siderophore-associated virulence genes, including aerobactin, yersiniabactin, and colibactin. Plasmidome profiling revealed that several resistance determinants were found on conjugative plasmids encoding β-lactamase and aminoglycoside resistance genes which underscores their potential for horizontal dissemination. The open pan-genome exhibited substantial diversity, with accessory genome enriched in mobilome-associated genes (14.6%) compared to core genome (0.1%). Overall, these results reveal the extensive genomic plasticity of K. pneumoniae and widespread distribution of resistance and virulence determinants, largely mediated by mobile genetic elements. These findings are pivotal for guiding future genomic surveillance and to support the development of targeted therapeutic approaches to combat AMR.
Robinow syndrome is a rare genetic disorder characterized by distinct craniofacial dysmorphism, mesomelic limb shortening and genital hypoplasia. The disorder has been reported to be inherited in an autosomal dominant as well as recessive patterns with a prevalence of 1:500000. In this study, we aimed to identify the genetic basis and structural consequences of disease in a clinically diagnosed case. A 3-months old male child from the Southwest Punjab region of India, born out of a consanguineous marriage, was presented with features including hypertelorism, midface hypoplasia, short stature, brachydactyly and genital anomalies. Whole-exome sequencing revealed a novel heterozygous pathogenic frameshift mutation, c.1644del (p.F549Sfs*125) in exon 14 of the DVL1 gene. This variant was absent in significant population databases and was therefore classified as pathogenic based on ACMG criteria. Familial segregation analysis by Sanger sequencing indicated it to be a de novo mutation since it was not observed in the parents as well as the elder male sibling. Further, comparative molecular dynamics analyses reveal that the mutation profoundly destabilizes DVL1, as the wild-type protein maintains stable Root Mean Square Deviation (RMSD), moderate flexibility, compact folding, and controlled essential motions, consistent with a properly folded, functional state. In contrast, the mutant displays persistent structural instability, excessive flexibility, loss of compactness, disrupted hydrogen-bond networks, and exaggerated collective motions, collectively indicating loss of stable dynamic features required for normal DVL1 function and likely non-functionality. In conclusion, this study reports a novel pathogenic variant in DVL1 associated with Robinow syndrome in this geographical region and highlights the importance of integrating genomic and structural analyses to understand disease mechanisms. These findings expand the mutational spectrum and have important implications for precise diagnosis, genetic counselling, and future studies on targeted molecular mechanisms.
The immunosuppressive tumor microenvironment (TME) serves as a central driver of bladder cancer (BCa) progression and prognosis. While its significance is widely acknowledged, the key cellular subsets that mediate this immunosuppressive state and their core regulatory genes remain incompletely understood. Key immunosuppressive cellular subsets and their signature genes were systematically identified using single-cell RNA sequencing (scRNA-seq) data from BCa samples. A prognostic risk model was then constructed via univariate and multivariate Cox regression analyses, based on bulk RNA-seq datasets and the identified signature genes. The role of SUSD2 was further validated in vitro using qRT-PCR, Western blot, immunofluorescence, proliferation, and invasion assays. Compared with adjacent normal tissues, BCa tissues showed significant enrichment of stromal cells (e.g., epithelial cells, fibroblasts). Among these stromal populations, the proportion of myofibroblast-like cancer-associated fibroblasts (myCAFs) was significantly increased in BCa tissues, and high myCAF infiltration was closely associated with poor patient prognosis. Pseudotime trajectory analysis confirmed that fibroblast differentiation in BCa shifts toward a terminal state (State 3), which is predominantly composed of myCAFs. A prognostic model established using myCAF-related signature genes (TMEM74B, ABCC9, FCMR, ALG9, SUSD2, and ETV7) exhibited stable predictive performance in both training and validation cohorts, with SUSD2 identified as a risk-related gene. In vitro experiments revealed that SUSD2 knockdown inhibited myCAF activation and extracellular matrix secretion, thereby attenuating its promotional effects on BCa cell proliferation and invasion. The TGF-β receptor inhibitor SB-431542could reverse the facilitative effects of SUSD2 overexpression on tumor cell proliferation and migration. Our findings identify myCAFs as a core regulatory cellular subset and SUSD2 as a key molecule within the immunosuppressive TME of BCa. Additionally, SUSD2 may trigger the activation of the TGF-β/Smad signaling cascade to induce myCAF activation, thereby accelerating BCa progression. These results provide novel potential targets and a theoretical basis for prognosis assessment and TME-targeted therapy in BCa.
In bacterial multireplicon genomes, in addition to the main chromosome, there is a widespread class of secondary replicons with a distinct evolutionary status known as chromids. These elements possess plasmid-like replication and partitioning systems, while their nucleotide composition and gene functions are highly similar to those of the main chromosome. Therefore, chromids are considered to play important roles in the evolution of bacterial genome architecture and in environmental adaptation. With advances in long-read sequencing technologies and breakthroughs in bioinformatics methods, metagenomic data resources have been greatly expanded. Using our previously developed automated tool, "Chromid-Finder", we systematically identified and collected chromid sequences from large-scale metagenomic assemblies. These data were then uniformly curated, classified, and centrally managed to construct a public database platform dedicated to chromids-Chromid Database. On this basis, we conducted comprehensive analyses of the evolutionary and genetic characteristics of chromids. Phylogenetic analyses revealed the overall evolutionary landscape of chromids. Variation analyses showed that SNP distributions on chromids exhibit clear and well-organized patterns, depicting a dynamic population that is continuously adapting to the environment through fine-scale sequence tuning and non-coding regulatory mechanisms. Structural variation analyses further identified several hotspot regions significantly enriched in key genes related to metabolic functions, nutrient acquisition, and antibiotic resistance. The distribution patterns of recombination events suggest that their occurrence is likely driven primarily by non-phylogenetic factors such as environmental conditions and ecological niches. In addition, systematic quantification of heritable mobile genetic elements indicated that the number of integrative and conjugative elements (ICEs) largely determines the overall mobile element burden within chromids.
The synergy between HTS and CRISPR/Cas is changing how genes, biomarkers, and diseases are studied. Very useful due to the ability to scan entire molecular libraries in a single assay and its extreme rapidity. CRISPR/Cas systems, however, are crucial for achieving control and specificity, properties essential for precise genetic editing and targeted detection. HTS could be combined with CRISPR in two ways: HTS would expand the search space, and CRISPR would narrow it. This perspective highlights recent advances in which both platforms have been used together - for example, to find genetic variants and molecular markers in cancer, infectious diseases, and even biosensors to track the environment and metabolism. We discuss technical advances as well as practical issues that make the use of CRISPR/Cas more challenging in the clinical environment, including off-target activity, reproducibility, and the increasing complexity and dimensionality of data.
Diamond-Blackfan Anaemia (DBA) is a rare inherited bone marrow failure syndrome conventionally attributed to ribosomal protein gene haploinsufficiency, resulting in impaired ribosome assembly and compromised erythroid precursor viability. However, contemporary research reveals considerably more complex molecular mechanisms driving disease pathology. This study aimed to comprehensively characterise the transcriptional and post-transcriptional regulatory networks contributing to DBA pathogenesis using integrative mRNA–miRNA sequencing of patient-derived bone marrow specimens. Our analysis revealed extensive dysregulation across immune, proliferative, and erythroid differentiation pathways. A coordinated elevation of immune-associated genes, such as TNF, CXCL8, TLR2/4, and CD44, suggests the establishment of a hyperinflammatory bone marrow microenvironment. In contrast, significant downregulation of essential mitotic and epigenetic regulatory factors, particularly CDC25A/C, CDK1/2, and AURKA, reflects disrupted cell cycle dynamics and impaired hematopoietic proliferation. Integrative miRNA–mRNA analysis identified dysregulated miRNAs as critical mediators of these processes. Downregulation of anti-inflammatory miRNAs (e.g., miR-93-5p, miR-143-3p, miR-19a-3p) and upregulation of mitotic suppressor miRNAs (e.g., let-7a, miR-141, miR-31, miR-21) indicate post-transcriptional disruption of immune and cell-cycle balance. Together, these findings reveal a multifaceted regulatory framework in DBA where transcriptional and miRNA-mediated perturbations converge to drive immune activation and impaired erythropoiesis, challenging prevailing ribosomopathy-centric models and highlighting potential molecular targets for therapeutic intervention.
Understanding how proteins dynamically adapt to diverse and changing physiological microenvironments is a fundamental challenge in modern biological sciences. Junctional adhesion molecules (JAMs) are a family of conserved proteins critically involved in immune regulation and cell adhesion. In this study, we investigate the evolutionary and structural dynamics of three paralogs across 274 mammalian taxa, which share similar tertiary structures but differ in isoelectric points (pI). By integrating phylogenetic modeling, partial correlation, network topology, and evolutionary molecular dynamics in physiological pH (6.5-10.5) gradient, we explored potential explanations driving this diversification. Our analysis identified JAM-B as a likely central node in the conservation network, with Lys and Cys residues as central evolutionary residues. Evolutionary mapping revealed recent episodic selection bursts across 17% to 26% of mammalian lineages, could indicate that specific functional interfaces are undergoing rapid, lineage-specific innovation. Notably, we identified episodic hotspots in JAM-A at the distal D1 viral entry interface, consistent with an ongoing host-pathogen arms race, and parallel adaptive clusters at the C-terminal motifs across all paralogs. AlphaMissense profiling revealed that acidic-> basic mutations exhibit significantly lower pathogenicity scores. In preliminary early-onset dynamics simulations, root-mean-square-deviation profiles could suggest a pI-stability relationship, JAM-A and JAM-C displayed biphasic pH-dependent deviations (at pH 8.0 and pH 8.5). Dynamics-aware evolutionary profiling identified key dynamic-conserved residues: JAM-A at Gln66, JAM-B at Gln36 and Val57, and JAM-C at several basic residues. Together, these results suggest that isoelectric divergence correlates with residue evolution and microenvironment-specific structural dynamics. Ultimately, our integrated computational framework provides genomic insights into paralog diversification, offering a testable architectural blueprint for targeted mutagenesis or therapeutic modulation of pH-sensitive adhesion processes.
Lung adenocarcinoma (LUAD) is the most lethal subtype of lung cancer, and its occurrence and progression are closely correlated with immune escape. CEP55 is upregulated in a variety of malignancies and participates in tumor progression, yet its specific role in the immune regulation of LUAD remains poorly defined. Due to the unclear mechanism of immune escape, the therapeutic efficacy of immunotherapy for LUAD is still unsatisfactory. Therefore, it is essential to further elucidate the underlying molecular mechanisms and identify novel therapeutic targets. This study aims to explore the biological function of CEP55 in LUAD immune escape, as well as to clarify its upstream regulatory mechanism and downstream signaling pathways. CEP55 expression in LUAD tissues was assessed utilizing data from TCGA-LUAD and validated in cells. Bioinformatics approaches were employed to explore CEP55-enriched signaling pathways and their link to CD8⁺ T cell infiltration. A CD8⁺ T-tumor cell co-cultured model was established, and LDH release, ELISA, and CFSE staining were utilized to assess CD8⁺ T cell cytotoxicity and proliferation. To uncover the role of CEP55 in LUAD cell behavior, we employed CCK-8, EdU labeling, Transwell assays, and flow cytometry to systematically evaluate its effects on proliferation, migration, invasion, and apoptosis. Western blotting was performed to measure key signaling pathway proteins expression level. Potential upstream regulators of CEP55 m6A modification were identified through database mining, followed by validation using RIP, MeRIP-qPCR, and WB. CEP55 was highly expressed in LUAD and inversely associated with CD8⁺ T cell infiltration. Knockdown of CEP55 in LUAD enhanced tumor-killing activity of CD8⁺ T cells in a co-culture system and significantly suppressed LUAD cell proliferation, migration, invasion, and anti-apoptotic capacity. CEP55 was positively correlated with WTAP in LUAD. WTAP stabilized CEP55 mRNA expression via m6A modification, while CEP55 activated the PI3K/AKT/mTOR pathway, upregulating PD-L1. This led to CD8⁺ T cell exhaustion and promoted tumor immune evasion. This study reveals a critical mechanism whereby WTAP upregulates CEP55 expression via m⁶A modification, thereby activating the PI3K/AKT/mTOR signaling pathway, inhibiting the anti-tumor activity of CD8⁺ T cells, and ultimately facilitating LUAD progression. These findings indicate that CEP55 serves as a promising therapeutic target for LUAD immunotherapy, providing novel theoretical evidence to improve the efficacy of immune treatment.
Shugan Jianpi Formula (SGJPF), a traditional Chinese herbal formulation, has been clinically used for decades in the management of various chronic liver diseases, including liver fibrosis (LF). Previous studies have demonstrated the efficacy of SGJPF in ameliorating pathological manifestations in murine models of LF. However, the precise molecular mechanisms underlying its therapeutic effects remains unclear. In the present study, we aimed to explore the therapeutic mechanisms of SGJPF through comprehensive analysis of LncRNA-mRNA co-expression network.The therapeutic efficacy of SGJPF in a CCL4-induced LF murine model was assessed by histopathological alterations, α-smooth muscle actin (α-SMA) and collagen Ⅰ expression. To elucidate the molecular mechanisms underlying the efficacy of SGJPF, whole transcriptome RNA sequencing technology was conducted to identify the LncRNAs and mRNAs expression profiles across control, model, and SGJPF-treated groups. GO function and KEGG pathway enrichment analysis was performed to identify the biological functions and signaling pathways associated with the differentially expressed genes (DEGs). Subsequently, the hub LncRNAs and mRNAs were identified based on fold change and correlation analysis. Finally, biological relevance of these core genes were further validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in mouse liver tissue, revealing the regulatory interactions between LncRNAs and their target mRNAs. Compared with the control group, 401 differentially expressed (DE) LncRNAs and 1224 DE mRNAs were found in the model group. In addition, compared with the model group, 98 DE LncRNAs and 147 DE mRNAs were identified following treatment with SGJPF. Subsequently, 31 DE LncRNAs and 39 DE mRNAs were obtained and served as potential target genes of SGJPF. Functional annotation of the 31 DE LncRNAs revealed predominant involvement in small molecule metabolic processes, with significant associations observed in circadian rhythm regulation, p53 signaling pathway, TGF beta signaling pathway, and Hippo signaling pathway. Correlation analysis indicated significant associations between these 31 DE LncRNAs and 39 DE mRNAs (|PCC|> 0.65, P < 0.05). Additionally, the expression of 2 LncRNAs (Gm28857, D030074P21Rik) and 5 mRNAs (Cdkn1a, Id1, Id4, Wnt9b, Gadd45g) were confirmed by RT-qPCR in mouse liver tissue, which were consistent with RNA sequencing data. This study delineates the comprehensive LncRNA/mRNA expression profiles in LF treated with SGJPF, which may provide valuable insights into the molecular mechanisms underlying LF pathogenesis and identifying potential therapeutic targets for further investigation.
Gastric cancer (GC), a highly aggressive and heterogeneous malignancy, remains challenging in immunotherapy despite recent advancements. This study aims to identify novel biomarkers and construct a prognostic model to improve outcome prediction and therapeutic strategies. Mendelian randomization (MR) analysis identified immune cell subtypes linked to GC using FinnGen and GWAS cohorts. CIBERSORT and WGCNA algorithms were applied to define M2 tumor-associated macrophage (TAM)-related gene modules. Key prognostic genes were selected via Lasso-Cox regression to establish a risk model, validated using GEO datasets. Biological function disparities, tumor microenvironment heterogeneity, and therapeutic sensitivities were assessed via GSEA and immune infiltration analysis. Protein-level validation was performed using TCGA, HPA, and Western blot. MR analysis revealed 26 immune cell subtypes associated with GC. WGCNA identified 20 gene modules, with the most M2 TAM-correlated module prioritized. A prognostic signature incorporating SEC61G, BGN, and STC1 was developed, stratifying patients into distinct risk groups with divergent survival outcomes (1-/3-/5-year, all P < 0.05). High-risk patients exhibited enriched calcium signaling pathways, reduced immunotherapy responsiveness, and increased sensitivity to veriparib and palbociclib. Protein overexpression of key genes was validated in GC tissues. This integrated bioinformatics-MR framework establishes a TAM-driven prognostic model for GC, demonstrating clinical utility in survival prediction, immunotherapy efficacy evaluation, and personalized therapeutic targeting. The findings provide actionable insights for advancing precision immunotherapy in GC.