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Accurate quantification of canine mitochondrial DNA copy number from canine blood and brain samples.

Acute brain injury is difficult to evaluate in veterinary medicine and tools to investigate the potential involvement of mitochondrial involvement are limited. The brain is highly enriched in mitochondria and contains thousands of copies of mitochondrial DNA (mtDNA) per cell, but robust methods for quantifying mitochondrial DNA copy number (mtDNA-CN) in canine tissues are lacking. We describe the development of a quantitative real-time PCR assay for absolute measurement of mtDNA-CN which was validated in canine blood and brain tissue. To minimize amplification of nuclear mitochondrial insertion sequences (NumtS) and repetitive regions, species-specific oligonucleotide primers were designed following in silico genomic filtering. The assay was applied to a small pilot cohort comprising blood samples from dogs with and without acute brain injury (n = 4-6 per group) and cerebral cortex samples (n = 1 per group) to assess feasibility and biological plausibility. In non-brain injury dogs, blood mtDNA-CN ranged from 98 to 288 copies per nuclear genome (mean 193 ± 72), while values in brain-injured cases ranged from 163 to 228 copies per genome (mean 200 ± 33). Cerebral cortex samples exhibited higher mtDNA-CN than blood, consistent with known tissue-specific mitochondrial enrichment. In a single brain-injured case with serial sampling, mtDNA-CN increased over five days. This study presents a validated assay and pilot data for mtDNA-CN quantification in canine samples. While not powered for biomarker evaluation, this method may enable future studies of mitochondrial dynamics in canine brain injury and metabolic disease.

Animals

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans

Algae-to-host horizontal gene transfer in Paramecium bursaria is associated with host adaptation during endosymbiosis.

Paramecium bursaria maintains a stable endosymbiosis with green algae, yet the evolutionary consequences of this association remain unclear. Here, we screened the host genome for algal-derived horizontally transferred genes (HTGs) using a lineage-aware workflow designed to detect horizontal gene transfer (HGT) between two defined lineages. We identified 16 candidate HTGs, including four putative newly transferred genes and 12 homologous transferred genes, most of which were functionally associated with redox homeostasis and metabolism. Five HTGs showed symbiosis-dependent expression. RNAi knockdown of GH32s and SATs reduced host proliferation, total cell area, and motility, while GH32s knockdown also reduced endosymbiont load. Duplication patterns suggest that most transfers may have occurred after the P. bursaria lineage diverged from the sampled Paramecium species but before its lineage-specific whole-genome duplication (WGD). The HTGs also showed host-associated shifts in GC content and gene length, while representative HTGs retained conserved domains and functional motifs. Together, our results support algae-to-host HGT in P. bursaria and suggest that some transferred genes may contribute to metabolic integration during endosymbiosis.

Gene Transfer, Horizontal

Long-term (>7-year) parental consumption of genetically modified maize (Cry1Ab/Cry2Aj and EPSPS) induces no adverse sperm DNA methylation alterations across two generations of cynomolgus monkeys.

This study assessed the long-term safety of genetically modified (GM) maize from a male reproductive perspective, using a non-human primate model. We analyzed the sperm DNA methylation profiles in cynomolgus monkeys fed GM maize, non-GM parental maize, or a conventional diet over two generations (F0/F1). Whole-genome bisulfite sequencing (WGBS) revealed no significant differences in global methylation levels among groups. The identified differentially methylated regions (DMRs) were short, enriched in non-regulatory genomic areas, and did not cluster after treatment. Functional enrichment analysis showed that DMR-associated genes were consistently involved in the same core biological pathways (e.g., mTOR and Wnt signaling) across all dietary comparisons. These findings indicate that GM maize consumption did not induce specific adverse epigenetic alterations in sperm, with the observed changes reflecting common physiological adaptations to dietary variations rather than GM-related effects.

Animals

Construction of an infectious clone of Spodoptera frugiperda densovirus and its biological characteristics.

Densoviruses are highly pathogenic to their insect hosts and have great potential for biocontrol. Spodoptera frugiperda densovirus (SfDV) was isolated from diseased larvae of Spodoptera frugiperda, while its biological functions remain unclear. Herein, we successfully constructed an infectious clone of SfDV. The S. frugiperda larvae transfected with the infectious clone exhibited anorexia, stunted growth, and reduced activity. Histopathological analysis further showed that the epidermis, fat body and trachea were infected instead of muscle and midgut tissues. Transmission electron microscopy (TEM) revealed that numerous virions of about 22 nm were distributed within both the nucleoplasm and cytoplasm of epidermal cells. Moreover, many virions were also found contained within vesicles in the cytoplasm. The replication kinetics of the rescued SfDV (rSfDV) was similar to that of the parental SfDV. The median lethal dose (LD50) and median lethal time (LT50) values of rSfDV were 6.63 × 107 viral genome copies (vgc), 5.23 d, respectively, which were also comparable to those of the parental SfDV. Taken together, the infectious clone of SfDV provides an important tool for further exploring the genome function, pathogenesis, and interactions with its hosts.

Animals

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans

UNCX/SIN3A-Mediated H4K8 decrotonylation suppresses FOXO3 to drive TNBC progression and docetaxel resistance.

Triple-negative breast cancer (TNBC) remains a clinically challenging subtype characterized by aggressive behavior and limited treatment options. Though docetaxel remains a cornerstone chemotherapy for TNBC, the frequent emergence of resistance highlights the urgent need to identify novel therapeutic targets. In this study, we report that uncoordinated homeobox (UNCX) is upregulated in docetaxel-resistant breast cancer cells, genomically amplified in breast cancer, and associated with poor survival in breast carcinoma patients. Functional studies revealed that UNCX promotes breast cancer cell proliferation, migration and reduces the docetaxel sensitivity. Mechanistically, UNCX functions as a transcriptional repressor by recruiting the SIN3A complex. Genome-wide profiling indicated that the UNCX/SIN3A complex directly binds to the promoters of tumor-suppressor genes including FOXO3, and represses their transcription by removing histone H4K8 crotonylation (H4K8cr). Additionally, the UNCX/SIN3A complex enhances FOXO3 phosphorylation and inhibits its nuclear translocation, further inhibiting its activity. Notably, SIN3A knockdown, FOXO3 overexpression, or crotonylation restoration effectively reverses UNCX-induced malignant phenotypes. These findings collectively establish the UNCX/SIN3A-H4K8cr-FOXO3 axis as a pivotal epigenetic regulator of TNBC progression and chemoresistance, revealing new avenues for targeted therapeutic development against this aggressive breast cancer subtype.

Humans

Viral replication through phase separation: Cytosolic and nuclear condensates.

Replication of many RNA and DNA viruses occurs within specialized intracellular hubs organized as membraneless biomolecular condensates (BCs) driven by liquid-liquid phase separation. As obligate intracellular parasites, viruses depend on the host cell machinery to complete their replication cycles and therefore actively remodel the intracellular environment to favor viral genome replication, transcription, and assembly. Cytosolic and nuclear phase-separated replication compartments (RC) provide concentrated and dynamic platforms that promote efficient interactions between viral genomes and viral or host proteins essential for infection. The formation of viral replication BCs is typically facilitated by viral proteins enriched in intrinsically disordered regions and low-complexity domains, which enable multivalent interactions with viral nucleic acids and cellular factors. These interactions are mediated by diverse biophysical forces, including hydrophobic and π interactions, hydrogen bonding, molecular crowding, and osmotic effects. Throughout infection, viral BCs remain highly dynamic, allowing continuous exchange of components and functional maturation of replication hubs. Their properties and activities are further regulated by post-translational modifications of viral and host proteins, such as phosphorylation, acetylation, and methylation. In this review, we summarize current evidence supporting liquid-liquid phase separation as a central organizing principle of viral RCs. We focus on representative RNA and DNA viruses that replicate in the cytosol or nucleus, highlighting virus-specific strategies, conserved mechanisms, and the consequences of BC formation for viral replication efficiency, host antiviral responses, and therapeutic intervention.

Phase Separation

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU·mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans

Genetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1, and CMIP variants.

BACKGROUND: Gestational diabetes mellitus (GDM) has a high global prevalence and arises from complex interactions between genetic predisposition and environmental factors. GDM is associated with metabolic disturbances and chronic low-grade inflammation, both of which contribute to its pathogenesis. This study aimed to investigate the association between GDM and 135 single-nucleotide polymorphisms (SNPs) across 20 genes related to metabolic traits. METHODS: In this case-control study, 152 pregnant women with GDM and 684 pregnant women with normal glucose tolerance (NGT) who underwent antenatal examination at Siriraj Hospital, Bangkok, were enrolled. Clinical data and blood samples were collected from all participants. Genomic DNA was isolated and subjected to whole-genome sequencing using the DNBSEQ-T7RS high-throughput sequencing platform. Genotype analyses were performed using R software, and haplotype analyses were conducted using the online SNPStats software. RESULTS: After adjusting for maternal age and pre-pregnancy body mass index, polymorphisms in TCF7L2 (rs34872471, rs7901695, rs4506565, rs7903146, rs12243326, and rs12255372), NEDD1 (rs10431408, rs11830756, rs249579, rs249585, and rs4762339), CMIP (rs2306115 and rs201681534), CDKAL1 (rs4710942), GCKR (rs2293572 and rs2293571), and GCK (rs5883890) were significantly associated with the risk of GDM. Haplotype analysis demonstrated that the TCF7L2 rs12243326-rs12255372 CA haplotype was associated with a decreased risk of GDM (OR = 0.44, 95% CI: 0.23-0.81), while the NEDD1 rs249579-rs249585-rs4762339 GGT haplotype was associated with an increased risk of GDM (OR = 1.40, 95% CI: 1.08-1.82). CONCLUSIONS: These findings suggest that genetic variations in TCF7L2, NEDD1, CMIP, CDKAL1, GCK, and GCKR contribute to GDM susceptibility in the Thai population.

Humans

Systematic review of the mutations in the active antigenic site Ø of the prefusion F protein of the Respiratory Syncytial Virus (RSV) following the implementation of monoclonal antibody prophylaxis.

BACKGROUND: Monoclonal antibody (mAb) nirsevimab, which targets the antigenic site &#xd8; of the prefusion F protein (pre-F) of RSV, was introduced for RSV prophylaxis in several countries. METHODS: A systematic search was conducted between January 1, 2022, and July 31, 2026 for studies analyzing substitutions within the epitope of pre-F RSV protein, which is the target of nirsevimab, after the implementation of the mAb. We searched across PubMed, Scopus, Web of Science and ClinicalTrial.gov for studies involving children with confirmed RSV infection, that conducted genomic analysis. RESULTS: Seven studies (five observational and two randomized controlled trials) including 2156 RSV-positive samples (RSV-A: 1347, RSV-B: 809) were analyzed. RSV-A strains showed limited variability within antigenic site &#xd8;, with K65R being the most common substitution and K209E being the only intermediate-resistance RSV-A substitution. RSV-B strains demonstrated substantially higher substitution frequencies, particularly involving I206M, Q209R, and S211N. Most identified substitutions appeared to represent naturally occurring polymorphisms and retained susceptibility to nirsevimab, while multiple RSV-B substitutions and combinations involving residues 64-68 and 204-208 demonstrated reduced susceptibility or high-level resistance. Resistance-associated variants were detected in 28 of 2156 (1.3%) RSV-positive samples and exclusively among nirsevimab breakthrough infections. In a sub-analysis restricted to nirsevimab-treated individuals, resistance-associated variants were significantly more frequent among RSV-B than RSV-A (9.8% vs 0.5%; p&#xa0;<&#xa0;0.001). CONCLUSION: Most substitutions that were detected within the nirsevimab antigenic site reflect ongoing natural RSV evolution and do not significantly affect nirsevimab susceptibility. However, detection of resistance-associated variants highlights the importance of continuous genomic and phenotypic surveillance.

Humans

Protein persulfidation emerges as a conserved component of the redox response to DNA damage.

Genotoxic stress is frequently accompanied by alterations in cellular redox homeostasis; however, the mechanisms linking redox regulation to the DNA damage response (DDR) remain incompletely understood. Here, we investigated the early redox response to DNA damage induced by methyl methanesulfonate (MMS) in Saccharomyces cerevisiae, focusing on cysteine oxidative post-translational modifications (PTM). We show that activation of the DNA damage response is accompanied by rapid redox changes that occur in the absence of a generalized oxidative stress response. MMS exposure promotes selective remodeling of cysteine oxidative modifications, characterized by decreased free thiols, robust induction of protein persulfidation, and comparatively modest changes in sulfenylation. These alterations are accompanied by increased intracellular hydrogen sulfide levels, supporting the involvement of reactive sulfur species in the cellular response to DNA damage. Proteome-wide analyses revealed that cysteine oxidative modifications preferentially target proteins involved in central metabolism, nucleotide biosynthesis, and genome maintenance. Consistent with these observations, MMS-induced genotoxic stress promotes metabolic adaptation characterized by increased mitochondrial respiration, elevated ATP production, and mitochondrial morphological remodeling, linking bioenergetic adaptation to redox regulation. Importantly, perturbation of intracellular redox balance using N-acetylcysteine compromises survival under DNA-damaging conditions, supporting a functional role for redox signaling during the DDR. Finally, MMS treatment also induces protein persulfidation in mammalian cells. Moreover, exposure to etoposide, a mechanistically distinct genotoxic agent that induces DNA double-strand breaks through topoisomerase II inhibition, showed a similar trend, suggesting that protein persulfidation may not be restricted to alkylation-induced DNA damage. Together our findings identify protein persulfidation as a prominent component of the redox response to DNA damage and provide new insight into the functional interplay between mitochondrial metabolism, cysteine-based redox regulation, and genome maintenance.

Oxidation-Reduction

Targeting SIRT6: the design and therapeutic implications of activators and inhibitors.

Sirtuin 6 (SIRT6) is an NAD+-dependent deacylase that maintains genomic stability, regulates metabolism, and influences aging, making it an attractive but challenging therapeutic target. Pharmacological modulation of SIRT6 holds promise for cancer and metabolic disorders, yet its context-dependent functions demand precise intervention strategies. Potent, selective, and drug-like chemical probes are therefore essential to dissect SIRT6 biology and to validate its therapeutic potential. This review critically evaluates recent medicinal chemistry advances in SIRT6 modulation. We focus on structure-guided design strategies and structure-activity relationships (SAR) that have transformed initial hits into optimized leads for both activators and inhibitors, highlighting the remaining challenges in achieving isoform selectivity and drug-like properties.

Sirtuins

The identification of growth-promoting lncRNAs in oral cavity squamous cell carcinoma.

Oral Cavity Squamous Cell Carcinoma (OCSCC) is an aggressive tumor that develops within the mouth of patients. Tumor-suppressor gene loss and genomic arrangements fuel tumorigenesis and transcriptional reprogramming. Understanding how these alterations contribute to OCSCC growth and cell survival may identify new therapeutic vulnerabilities or biomarkers. We profiled the role of long non-coding RNAs (lncRNAs) in the growth of three OCSCC cell lines using a CRISPRi-screen and identified 19 lncRNAs that contribute to OCSCC proliferation. By comparing these lncRNAs to other screens, we find that these lncRNAs are uniquely required in OCSCC and not other malignancies. We show that these lncRNAs are abundantly expressed in OCSCC cells and tumors. Independent testing of candidate lncRNAs confirms their role in supporting OCSCC growth. Our results show that a novel subset of lncRNAs are required for the growth of OCSCC cancer cells and that these lncRNAs are cell lineage specific.

CRISPRi