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Metabolic ketosis attenuates NLRP3 inflammasome activation and is associated with improvements in hepatic steatosis and liver stiffness in MASLD: a pilot randomized controlled trial.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly recognized as a systemic metabolic-inflammatory disorder in which metabolic stress and innate immune activation, particularly through the NLRP3 inflammasome, contribute to disease progression. Metabolic ketosis, characterized by increased levels of circulating ketone bodies, especially &#x3b2;-hydroxybutyrate, has emerged as a promising strategy to modulate substrate utilization, inflammatory signaling, and hepatic injury. However, clinical evidence integrating molecular, metabolic, and hepatic outcomes remains limited. METHODS: In this pilot randomized controlled trial, 20 participants with newly diagnosed MASLD were randomly assigned to either a 3-month intervention with a daily C8-enriched medium-chain fatty acid formulation (m-CAP; meta-Capridin, providing approximately 20 g/day of C8) or a standardized low-carbohydrate dietary protocol. Metabolic indices, inflammatory mediators, adipokines, and hepatic enzymes were assessed. The expression of key inflammasome components (NLRP3, caspase-1, and ASC) was evaluated in peripheral blood mononuclear cells, and hepatic steatosis and liver stiffness were measured via transient elastography. RESULTS: The C8-enriched intervention was associated with increased circulating &#x3b2;-hydroxybutyrate levels, indicating the achievement of nutritional ketosis. Changes over time were observed in metabolic parameters, including fasting serum glucose (p < 0.05), HOMA-IR (p < 0.05), body fat percentage (p < 0.05), and BMI (p < 0.05). Alterations in inflammatory mediators and adipokine-related outcomes were also observed following the intervention. At the molecular level, changes in inflammasome-related markers were detected, including caspase-1 mRNA expression (p < 0.05) and NLRP3 expression at the transcriptional (p < 0.05) and protein levels (p < 0.01), whereas ASC expression remained unchanged. Changes in hepatic steatosis (p < 0.01) and liver stiffness measurements were observed following the intervention. Given the absence of significant Group &#xd7; Time interactions for several secondary outcomes, these findings should be interpreted as exploratory and hypothesis-generating. CONCLUSIONS: Induction of metabolic ketosis was associated with changes in metabolic, inflammatory, and hepatic parameters in patients with MASLD. The observed associations between ketosis, inflammasome-related markers, and noninvasive liver outcomes warrant further investigation of ketosis-based interventions as adjunctive approaches in MASLD. Larger and longer-term clinical trials are needed to confirm these findings and to determine whether short-term changes in liver stiffness reflect sustained alterations in hepatic status rather than structural fibrosis regression. TRIAL REGISTRATION: Iranian Registry of Clinical Trials (IRCT); Unique identifier: IRCT20170315033086N12; Registration date: 19 September 2024; Registry URL: https://www.irct.ir. IRCT is a primary registry in the WHO Registry Network (https://www.who.int/tools/clinical-trials-registry-platform/network/primary-registries).

Humans

Spatial transcriptomics of Ciona adult brains reveals functional zonalization and insights into neural gland function.

The ascidian Ciona is a pivotal chordate model for illuminating the evolutionary origins of the vertebrate brain. Here, spatial transcriptomics of the adult Ciona neural complex, combined with image-based computational super-resolution mapping, resolved distinct tissue domains including the cerebral ganglion, neural gland, ciliated funnel, neural gland duct/dorsal strand, and body wall muscle. Within the cerebral ganglion, high-resolution mapping revealed clear molecular zonalization separating the cortex and medulla, alongside regional specialization within the cortex itself. The neural gland exhibited localized enrichment of genes associated with extracellular matrix and cell-cell interactions. These spatial features suggest that the neural gland functions as a homeostatic and signaling interface, reminiscent of primitive vertebrate meninges or choroid plexus. Overall, this spatially defined gene expression map provides a foundational framework for understanding functional regionalization in the tunicate brain and its evolutionary relationship to vertebrate nervous systems.

Ciona

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology

Colorimetric gold nanosensors for monitoring protein aggregation: implications for Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. It remains a major public health challenge due to the lack of early diagnostic tools and effective disease-modifying therapies. Molecularly, AD is characterized by extracellular amyloid-&#x3b2; (A&#x3b2;) plaques and intracellular Tau tangles, as well as soluble oligomers that are likely the neurotoxic species. However, the transient and heterogeneous nature of these oligomers makes them difficult to detect using conventional biosensing approaches. Nanomaterial-based colorimetric biosensors have emerged as promising platforms for detecting protein aggregates and discovering aggregation inhibitors. Specifically, the localized surface plasmon resonance properties of metallic nanomaterials can enable rapid, label-free, and visually detectable colorimetric sensing of molecular interactions. These features can be leveraged to monitor protein aggregation processes in real time and achieve high-throughput screening of aggregation inhibitors, which may collectively enable early detection and timely intervention of AD progression. This Review Article presents the design and engineering of gold-nanomaterial-based colorimetric biosensors for monitoring protein aggregation and highlights the current challenges and emerging opportunities for applying these nanosensors to combat AD.

Journal Article

Distinct functions of mammalian RAD51 paralogs in genome maintenance.

RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) are evolutionarily conserved essential proteins for cell survival and genome maintenance. RAD51 paralogs were originally identified to play a role in homologous recombination-mediated repair of DNA double-strand breaks (DSBs). However, investigations over the last decade have uncovered new roles of RAD51 paralogs beyond DSB repair in replication stress responses, including replication fork progression, fork stability, and its restart. Recent structural studies have not only uncovered the molecular architecture of previously known RAD51 paralog complexes but also identified novel paralog complex assemblies, providing mechanistic insights into their various genome-maintenance functions. Additionally, a role for RAD51 paralogs in resolving R-loops has been identified, and studies with cancer-associated variants suggest that RAD51 paralogs are potential determinants of cancer susceptibility and therapeutic responses. In the present review, we highlight the recently deciphered structures and novel functions of RAD51 paralog complexes and discuss the clinical and therapeutic implications.

Rad51 Recombinase

Recent advances in supramolecular macrocycle-based artificial light-harvesting systems.

Artificial light-harvesting systems (ALHSs) inspired by the antenna function of natural photosynthesis provide molecular platforms for collecting excitation energy and directing it to emissive or reactive acceptors. In many supramolecular ALHSs, however, practical performance is limited by poorly defined donor-acceptor orientation, aggregation-caused quenching (ACQ), interfacial defects, and limited stability in aqueous or complex media. Supramolecular macrocycles-particularly pillar[n]arenes (PAs), cucurbit[n]urils (CBs), calixarenes (CAs), cyclodextrins (CDs), and supramolecular coordination complexes (SCCs)-offer a useful design space because their cavities, pre-organized scaffolds, and reversible non-covalent interactions can confine chromophores, tune local donor/acceptor ratios, and modulate F&#xf6;rster resonance energy transfer (FRET). This Review systematically examines the unique structural advantages and assembly mechanisms of the five macrocyclic families, with an emphasis on their use in constructing ALHSs-from single-step to cascaded FRET-and in advancing aqueous photocatalysis, near-infrared bioimaging, panchromatic fluorescence modulation, and singlet oxygen generation. The resulting structure-property-application framework is intended to guide the rational design of macrocycle-assisted photofunctional materials while avoiding overextension of the photosynthesis analogy.

Journal Article

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

Association Between Ticagrelor and Glucose Homeostasis Regulation: Insights from Genetic and Transcriptomic Analyses.

Emerging evidence has demonstrated the additional therapeutic benefits of ticagrelor in acute coronary syndrome (ACS) patients with diabetes. However, the underlying mechanisms of this association remain elusive. Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data on ticagrelor, plasma proteomics and type 2 diabetes was employed to identify causal mediator proteins. RNA sequencing (RNA-seq) of ticagrelor-treated HepG2 cells revealed the molecular pathways regulating glucose metabolism. Genetically proxied ticagrelor was significantly associated with a reduced risk of diabetes (OR&#x2009;=&#x2009;0.859, 95% CI: 0.783-0.934, P&#x2009;=&#x2009;7.98E-05), and 24.41% of this effect was mediated by upregulation of BDH2 protein. In vitro experiments confirmed the enhanced effect of ticagrelor on glucose consumption. Transcriptome analysis revealed that mitochondrial respiratory chain transfer and oxidative phosphorylation (OXPHOS) were significantly enriched, and genes related to ATP biosynthesis were significantly upregulated. These findings highlight the non-platelet function of ticagrelor in maintaining glucose homeostasis, providing insights into potential drug repurposing in the future.

Humans

Functional role and regulatory network of miR-22-3p in chicken hepatic lipid metabolism.

Although microRNA-22-3p (miR-22-3p) is abundantly expressed in the avian liver, its epigenetic role in lipid homeostasis remains largely uncharacterized. To elucidate its in vivo function, 14-day-old female Qingyuan Partridge chickens were intravenously injected with lentiviral vectors to establish miR-22-3p overexpression and knockdown models. Phenotypic analysis demonstrated that miR-22-3p knockdown significantly elevated hepatic triglyceride (TG) levels (p&#xa0;<&#xa0;0.05) and drove marked steatosis, whereas its overexpression reduced TG content. Transcriptome sequencing (RNA-Seq) revealed profound metabolic remodeling, identifying 23 core lipid-associated genes (e.g., ELOVL6, FADS2, ACSBG2, and PTGIS) heavily enriched in steroid biosynthesis, fatty acid metabolism, and elongation pathways. In conclusion, miR-22-3p functions as a bidirectional epigenetic rheostat that negatively regulates hepatic lipid deposition by orchestrating a multilayered polygenic network, providing novel molecular targets for mitigating avian metabolic disorders and optimizing production traits in indigenous poultry breeds.

Animals

Food-derived extracellular vesicles as delivery platforms for medicine-food homology components in metabolic syndrome.

Diet-induced obesity and associated metabolic syndromes have become major global public health challenge, highlighting the urgent need for safe and effective strategies. Recently, food-derived extracellular vesicles (FDEVs) have garnered increasing attention as natural nanocarriers due to their excellent biocompatibility and specific targeted delivery capabilities. FDEVs can efficiently deliver medicine-food homology components (MFHCs) to precisely regulate lipid metabolism, inflammatory responses, and insulin sensitivity, thereby improving obesity and its metabolic abnormalities. This systematic review summarizes recent advances in the use of FDEVs as delivery vehicles for MFHCs to suppress diet-induced obesity and metabolic syndrome, with a particular focus on the underlying molecular mechanisms, including signaling pathway regulation and cellular metabolic remodeling. In addition, the clinical translational potential and industrial application prospects of FDEVs are evaluated, and key challenges related to preparation techniques, safety assessment, and large-scale production are discussed. By integrating current evidence, this review aims to provide theoretical framework and future perspectives for the development of FDEVs as a novel targeted delivery platform and treatment of metabolic diseases.

Extracellular Vesicles

Heat stress in cereal crops: reproductive development and grain filling.

Increasingly frequent extreme heat events threaten cereal production and food security under a changing climate. The reproductive-to-grain formation continuum of cereals is particularly vulnerable to elevated temperatures, as heat stress disrupts developmental processes from inflorescence formation and fertilization to grain filling and quality establishment. These disruptions reduce reproductive success, impair yield formation, and compromise grain quality. A comprehensive understanding of the developmental, physiological, molecular, and genetic basis of cereal heat tolerance is therefore essential for developing climate-adapted crops. This review summarizes recent advances in understanding heat stress during cereal reproduction and grain filling across major cereal crops. We first discuss how heat stress affects sequential developmental processes, including inflorescence development, gametophyte development, flowering and pollination, fertilization, and grain filling. We then integrate emerging evidence on cross-cutting mechanisms that connect stage-specific heat responses, focusing on hormonal and redox homeostasis, carbohydrate metabolism and source-sink coordination, proteostasis and endomembrane organization, and genome stability and multilayered gene regulation. Finally, we summarize the genetic basis of cereal heat tolerance by highlighting genetic determinants, favorable alleles, and their potential applications in breeding. We further discuss current bottlenecks and future opportunities for breeding heat-tolerant cereals.

Cereals

Circular RNAs in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of motor neurons, with most cases lacking a clear genetic basis. Emerging evidence highlights the involvement of non-coding RNAs, particularly circular RNAs (circRNAs), in disease onset and progression. Here, we investigated circRNAs implicated in ALS and related motor neuron diseases (MNDs). Here, we provide a general overview of circular RNA metabolism and cellular functions. We then present our systematic literature review that identified ALS-associated circRNAs, followed by in silico analyses of 15 circular RNA candidates that were selected based on the most compelling data regarding ALS. Our results revealed that several circular RNAs regulate ALS-related genes, such as unfolded protein response, oxidative stress, cell cycle regulation, and apoptosis. Protein-RNA interaction analysis further showed that ALS-related circRNAs can sponge 20 RNA-binding proteins. Additionally, molecular docking analysis demonstrated that ALS-associated FUS variants significantly alter its binding affinity to circular RNAs. RNA-seq data from ALS patients confirmed significant alterations in the expression of host genes of ALS-related circRNAs and hub proteins in ALS-affected CNS tissues. Collectively, our findings identify circRNAs as potential key contributors to ALS pathogenesis.

Amyotrophic Lateral Sclerosis

Recovery of polysaccharides from marc and pomace through sequential extractions assisted by ultrasound, enzymes and acid maceration.

This study evaluated the pilot-scale recovery of polysaccharides from Vitis vinifera pomace/marc using sequential extraction strategies combining high-power ultrasound (UAE), enzymes (EAE), and acid maceration (AAE). Laboratory-scale trials identified optimal conditions for enzyme dosage and liquid/solid ratio (L/S). Pilot-scale trials demonstrated that the extraction sequence and the processing byproducts influenced extraction efficiency, total soluble polysaccharide in the extract (TSP), and polysaccharide composition. Post-maceration at pH&#xa0;3.2, with/without the maximum enzyme dose after UAE in a L/S of 1.3/1, improved structural polysaccharide extraction from Viura pomace, while Tempranillo marc showed better recovery of pectic families and TSP with UAE&#xa0;+&#xa0;EAE. Separating grape pomace extract (UAE) from the post-maceration stage at pH&#xa0;3.2 produced two extracts: E1, with higher yield (19.9%), enriched in structural polysaccharides and oligosaccharides, and E2, enriched in high and medium molecular weight pectic polysaccharides (58.03%), a low degree of esterification (17.1%) and more complex rhamnogalacturan structures.

Polysaccharides

Extended Reality Interventions for Osteoarthritis of the Knee and Recovery After Total Knee Arthroplasty: Systematic Review and Meta-Analyses.

BACKGROUND: Nonpharmacologic interventions are important for treating knee pain due to osteoarthritis or after total knee arthroplasty (TKA), and extended reality (XR) technology may enhance treatments for these indications. OBJECTIVE: This systematic review aimed to evaluate XR interventions for pain due to knee osteoarthritis (KOA) or for recovery after TKA. METHODS: Databases were searched through May 2023 and updated in December 2025. Eligible trials evaluated XR interventions to treat KOA pain or after TKA. We classified interventions by depth of immersion and clinical mechanism. We used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria to determine the certainty of evidence for prioritized outcomes. Meta-analyses were performed when &#x2265;3 studies evaluated similar comparisons, outcomes, and time points. RESULTS: Eligible trials addressed KOA (k=12) or recovery after TKA (k=9). Sample sizes ranged from 36 to 306 participants, and most studies had a follow-up of &#x2264;3 months. Nineteen studies assessed pain-related functioning and pain intensity, and 5 assessed adverse events (AEs). For KOA, 10 studies examined interactive digital rehabilitation (IDR), and 2 examined virtual reality (VR)-digitally augmented exercise (DAE). IDR for KOA may result in better pain-related functioning (low certainty of evidence [COE]; pooled standardized mean difference [SMD] -0.59, 95% CI -1.11 to -0.06; prediction interval [PI] -1.72 to 0.55; k=5) and lower pain intensity at 6-8 weeks (low COE; pooled SMD -0.46, 95% CI -0.92 to 0.00; PI -1.39 to 0.47; k=4). VR-DAE for KOA (k=2) produced inconsistent results (very low COE). For post-TKA studies, 5 examined IDR, 2 examined VR-DAE, 1 examined VR-distraction, and 1 examined VR-psychoeducation. Post-TKA IDR may result in better pain-related functioning (low [k=4] and moderate COE [k=1]) but little to no difference in pain intensity (low-moderate COE; pooled SMD at 3-4 months -0.12, 95% CI -0.75 to 0.52; PI -1.63 to 1.27; k=3). VR-psychoeducation probably results in lower pain at 4 weeks (moderate COE; k=1), and VR-distraction may result in 6 months (low COE; k=1), whereas VR-DAE produced mixed findings (k=2; very low COE). IDR was not associated with AEs, and VR may not be associated with AEs for KOA (high and low COE), though AE reporting was uncommon (k=5) and evidence was very uncertain for post-TKA. CONCLUSIONS: IDR may augment treatment for KOA and post-TKA recovery, and VR may benefit post-TKA rehabilitation. This review is the first to stratify by level of immersion, clinical mechanism, and follow-up duration and to systematically evaluate AEs. IDR may be ready for integration into KOA care, while use after TKA needs more evidence. Randomized controlled trials with implementation outcomes could determine how XR interventions can be used for KOA, whereas trials evaluating efficacy and AEs are needed before their use for post-TKA.

Humans

Genetic diversity and recombination of&#xa0;NA-PRRSV field strains in Vietnam: Implications for vaccine efficacy.

Porcine reproductive and respiratory syndrome (PRRS) causes severe reproductive losses in pregnant sows and piglets, resulting in substantial economic impact on the swine industry worldwide. However, due to the significant genetic diversity and rapid evolutionary changes of the pathogen, continuous surveillance and detailed genetic analysis of circulating strains are essential. The current study aimed to evaluate the genetic diversity of the hypervariable (HV) region of non-structural protein 2 (nsp2) among North American PRRSV strains isolated from swine farms in Vietnam. Phylogenetic analysis and multiple sequence alignment were conducted to determine subtype classification and assess genetic variability. A total of 48 field isolates were obtained, of which 12.5% belonged to classical NA-PRRSV, 16.6% to NADC30-like and 70.9% to HP-PRRSV, primarily distributed across sublineages 1.4, 5.1, 8.7 and 8.9. Amino acid comparisons found multiple insertions, deletions and substitutions at various positions within the hypervariable region of nsp2. The study revealed substantial genetic variation in the HV region of nsp2 among NA-PRRSV field strains, largely associated with recombination and immune escape. These findings highlight epidemiological risks to vaccine efficacy and underscore the need for continuous molecular surveillance to support effective PRRSV control in Vietnam.

PRRSV

Multiomic insights into fungal polylactic acid degradation: Metabolic adaptation and hydrolytic mechanisms of Sporobolomyces pararoseus.

Polylactic acid (PLA), a biodegradable polyester from renewable resources, is a sustainable alternative to petrochemical plastics. However, its environmental degradation is inefficient naturally, requiring specific microbial activities. While bacterial PLA-degrading mechanisms are well documented, fungal degrading systems-particularly their molecular mechanisms-are underexplored.We isolated Sporobolomyces pararoseus ZRQ01 from the gut microbiota of PLA-fed mealworms. This fungal strain noticeably degraded PLA in PLA-containing medium supplemented with 2% glucose. Biodegradation assays revealed 22.8% loss of the PLA film weight after 35&#xa0;days of incubation, and scanning electron microscopy confirmed extensive surface erosion and pore formation. Integrated transcriptomic and proteomic analyses, together with the reference genome of S. pararoseus ZRQ01, revealed that S. pararoseus ZRQ01 upregulates hydrolytic enzymes at both transcript and protein levels to cleave PLA into lactic acid. After lactic acid is transferred into S. pararoseus ZRQ01 cells by monocarboxylate transporters with increased abundance, it is assimilated by pathways of pyruvate metabolism and the TCA cycle with increased protein abundance. Intriguingly, upregulation of genes in autophagy-related and MAPK signaling pathways underscores an adaptive stress response potentially supporting cellular homeostasis and degradation-related gene expression. Our results highlight S. pararoseus ZRQ01's metabolic potential for bioremediation and offer insights into fungal bioplastic degradation pathways.

Polyesters

Targeted sequencing reveals a distinct genetic alteration landscape in oral multiple primary squamous cell carcinomas.

OBJECTIVE: Oral multiple primary cancers (MPCs) are associated with poor clinical outcomes, yet their genomic characteristics remain insufficiently understood. DESIGN: Fifty-four formalin-fixed paraffin-embedded (FFPE) tumor samples from 30 patients with oral MPCs were analyzed using high-depth targeted sequencing of a customized 14-gene panel derived from prior whole-exome sequencing data. Detected alterations were analyzed after removal of synonymous mutations. RESULTS: Non-silent genomic alterations were identified in 59.3% (32/54) of samples, involving 19 patients. A total of 70 variant loci across 13 genes were detected. AKAP13 was the most frequently mutated gene at both the sample (22.2%, 12/54), with recurrent mutations observed across multiple patients. In contrast, TP53 mutations occurred at a substantially lower frequency (11.1%, 6/54). Marked inter- and intra-patient mutational heterogeneity was observed. CONCLUSIONS: FFPE-based targeted sequencing enabled an initial characterization of genomic alterations in oral MPCs. Recurrent alterations in AKAP13, GLI2, JMJD1C, and DNAH8, together with the relatively low frequency of TP53 alterations, identify candidate genomic features for further investigation and provide a basis for future studies of the molecular basis of oral MPCs.

Humans

Sarcomas: Research on Ultrarare Subtypes Gains Ground.

Rare cancers account for almost one fourth of all cancers. Sarcomas belong to the group of cancerous diseases with an incidence of less than 6 cases per 100,000 inhabitants. Over the past decade, activities were launched worldwide to elucidate the peculiarities of many of the more than 100 sarcoma subtypes described in the World Health Organization handbook. The major contributor to exact diagnosis is molecular pathology. The subgroup of ultrarare sarcomas (URS) poses a significant problem as each URS type has its own morphology, biology, natural history, and prognosis. In 2020, 35 international sarcoma centers agreed to standards of evaluating URS. The threshold was set to an incidence of less than 1 case per 1,000,000 inhabitants, and 77 URS subtypes were defined. Also quality criteria for centers to be selected for retrieving data to registries were consented. This issue of Cancer Epidemiology, Biomarkers & Prevention contains the first article to validate these principles of URS using the data from a nationwide cancer database. The authors from Taiwan also pointed out limitations of the approach. Combination with the national death database allowed to calculate overall survival (OS) and identified age as a significant factor for OS per URS type. These new data might foster future research on diagnosis and treatment of URS. See related article by Lee et al., p. 1654.

Humans