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PubMed2026

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↗

PubMed2026

Prognostic significance of NLRP-3 expression in solid cancers: a systematic review and meta-analysis.

BACKGROUND: The inflammasome is a critical immunological sensor comprised of NLRP-3, ASC, and CASPASE-1. Mutations in NLRP-3 are prevalent in inflammatory diseases. However, the role of NLRP-3 in cancer is controversial. This study investigates whether NLRP-3 expression is associated with clinical outcomes in patients with solid cancers. METHODS: PubMed (MEDLINE), Embase, Cochrane, and Google Scholar were searched for articles reporting NLRP-3 expression and disease outcome data in cancer patients. RevMan Review Manager was used to calculate pooled hazard ratios and Mantel-Haenszel pooled odds ratios. RNA sequencing datasets from the TCGA Pan-Cancer (PANCAN) were used for external validation. RESULTS: Patients with higher NLRP-3 expression showed a significant association with larger tumor size, advanced tumor grade, TNM stage, and presence of metastasis. High NLRP-3 expression has a significant association with poor OS (HR:2.12, 95% CI = 1.49-3.03), p < 0.0001) and DFS (HR:1.86, 95% CI = 1.30- 2.65, p = 0.0007). Subgroup analysis showed that higher NLRP-3 expression is associated with worse OS in head and neck cancer (HR: 2.77, 95% CI = 1.88-4.09, p < 0.00001), colorectal cancers (HR:2.14, 95% CI= 1.59- 2.87, p < 0.00001), and pancreatic cancer patients (HR: 3.19, 95% CI = 1.73-5.91, p = 0.0002). CONCLUSION: High NLRP-3 expression is associated with advanced disease and poor outcomes in many solid tumours.

Humans↗

PubMed2026

A dual-dimensional CRISPR toolkit enables one-step high-efficiency multiplex genome editing in Komagataella phaffii.

Against the backdrop of green biomanufacturing, engineering methanol-utilizing Komagataella phaffii (K. phaffii) represents an effective strategy to expand the one carbon (C1) product profile and speed up the industrialization of C1-based bioeconomy. To address the technical challenges of low efficiency and cumbersome experimental procedures for multiplex gene editing and precise large-fragment integration during the reconstruction of complex metabolic pathways in K. phaffii, this study established a CRISPR toolkit - Efficient Multi-Gene Editing System 3.0 (EMGES 3.0) - which enabled one-step large-fragment integration coupled with multiplex gene knockout. EMGES 3.0 was constructed through the synergistic optimization of a repair-engineered chassis and an episomal CRISPR vector. For chassis engineering, five DNA repair modules: Δlig4 (DNA Ligase IV, non-homologous end joining end ligation), ppMRE11(The endogenous MRE11 gene from Pichia pastoris) overexpression (The Meiotic Recombination 11, DNA double-strand break end resection), Δrad9 (Radiation-Sensitive 9, DNA damage checkpoint regulation), Δmph1 (Mutator Phenotype Helicase 1, improvement of homologous recombinant strand extension), and PapRecT-PaSSB co-expression (stabilization of recombination intermediates) were integrated to generate the highly recombinogenic strain Y09. For vector engineering, cenARS was replaced by panARS and the endogenous promoter PGAP was employed to drive the double hammerhead ribozyme-single guide RNA-hepatitis delta virus ribozyme (double HH-sgRNA-HDV: dHgH)-mediated sgRNA expression, yielding the optimized vector Nov_pGAP_panARS_pLAT1_Cas9. These two features on K. phaffii together enhanced the EMGES 3.0 to a higher standard of transformation rate and editing efficiency. According to our results, EMGES 3.0 achieved dual-functional gene knockout efficiencies between 76.6% and 100%. For insertion of medium-long fragments (>4.5 kb), the efficiency achieved 93.3%. In addition, the one-step integration of ultra-long fragments (>16 kb) achieved 14.8%, which was reported for the first time. Furthermore, the efficiency of simultaneous long-fragment integration at three neutral loci reached 38.4% (>15 kb). We applied the system for one-step production of free fatty acids (FFAs, yield: 5.82 ∼ 7.30 mg/L/OD600) and resveratrol (yield: 1.14 ∼ 1.28 mg/L) using methanol as the sole carbon source. EMGES 3.0 provides a robust technical foundation for complex compounds biosynthesis and high-yield industrial strains, while also advancing K. phaffii as an industrial synthetic biology chassis for efficient C1 utilization.

CRISPR-Cas Systems↗

PubMed2026

Optimized AAV5-RPGR ORF15 Gene Therapy Rescues Photoreceptor Structure and Function in X-Linked Retinitis Pigmentosa Mouse Model.

PURPOSE: To develop and evaluate an rAAV5-based gene therapy vector expressing an optimized human RPGR ORF15 transgene (rAAV5-RPGR) for the treatment of X-linked retinitis pigmentosa caused by RPGR mutations, addressing the challenges of cloning the unstable wild-type ORF15 sequence. DESIGN: This was a prospective experimental study. SUBJECTS: This was an animal study. METHODS: An optimized RPGR ORF15 sequence was designed to eliminate problematic secondary structures and cryptic splice sites. In vitro expression was validated in HEK 293T and photoreceptor-like 661 W cells. A complete Rpgr knockout mouse model (Rpgr-knockout [KO]) was generated and characterized phenotypically. Therapeutic efficacy was assessed in Rpgr-KO mice via subretinal injection of rAAV5-RPGR at low (1 × 10⁹ vg/eye), medium (3 × 10⁹ vg/eye), or high (1 × 10¹⁰ vg/eye) doses. Structural and functional outcomes were evaluated at 12- and 14-month postinjection. Short-term safety was assessed in rabbits 1 month after subretinal injection. MAIN OUTCOME MEASURES: Level of RPGR protein expression and Protein isoform profile (elimination of truncated isoforms), Cellular localization of transgene expression and Dose-dependence of expression, outer nuclear layer thickness, and electroretinography parameters. RESULTS: (1) The optimized vector increased RPGR protein expression 3.3-fold in vitro compared to wild-type and eliminated truncated isoforms. (2) Subretinal delivery of rAAV5-RPGR in mice demonstrated dose-dependent transgene expression localized correctly to photoreceptor inner segments. (3) In Rpgr-KO mice, high-dose treatment significantly preserved outer nuclear layer thickness at the injection site (42% greater than controls at 14 months, P < .01) and central retina (P < .05), reduced aberrant rhodopsin mislocalization (P < .01), and partially restored retinal function. ERG showed significantly improved scotopic a-wave (≥100 vs <90 µV in controls at 10 cd·s/m²) and photopic b-wave amplitudes (49-66 vs 31-46 µV at 30 cd·s/m²) in treated mice. (4) No vector-related toxicity was observed in rabbits. CONCLUSIONS: rAAV5-RPGR mediated efficiently, targeted expression of optimized RPGR-ORF15, significantly preserved photoreceptor structure and function in a severe X-linked retinitis pigmentosa mouse model, and demonstrated a favorable safety profile. This study provides preclinical proof-of-concept for RPGR-targeted gene replacement therapy.

Animals↗

PubMed2026

[Study of a patient with azoospermia due to variant of MOV10L1 gene].

OBJECTIVE: To explore the clinical and genotypic characteristics of a patient with Sertoli cell-only syndrome (SCOS) due to variants of MOV10L1 gene. METHODS: A 27-year-old patient with Non-obstructive azoospermia (NOA) underwent routine semen analysis. Serum levels of follicle-stimulating hormone (FSH), luteinizing hormone (LH), progesterone (P), estradiol (E2), prolactin (PRL), and testosterone (T) were determined by chemiluminescence assays. Peripheral blood samples were collected for G-banded karyotyping analysis. Multiplex PCR fluorescence detection was used to screen for AZF gene microdeletions. Whole exome sequencing (WES) and Sanger sequencing were performed simultaneously. Testicular biopsy tissues were subjected to Hematoxylin-Eosin (HE) staining to assess seminiferous tubule cell composition, and MOV10L1 protein expression was detected by immunohistochemical staining. Bioinformatics tools were employed to predict the pathogenicity of variants and their impact on protein structure and function. This study was approved by the Medical Ethics Committee of the Guangdong Institute of Reproductive Sciences [Ethics No.: 2023(01)]. RESULTS: The patient's two semen analyses had failed to detect any sperm. Hormone tests indicated elevated FSH (22.32 mIU/mL) and PRL (397.6 mIU/mL), while T (3.68 nmol/L) and E2 (38.32 pmol/L) were reduced. Chromosomal karyotyping revealed 46,XY, and no AZF gene deletion was detected. WES and Sanger sequencing detected compound heterozygous variants of the MOV10L1 gene, including a c.345C>A (p.C115X) nonsense variant and a c.3323C>T (p.T1108I) missense variant, with the former being unreported previously. HE staining showed only Sertoli cells in the seminiferous tubules, confirming the diagnosis of SCOS. Immunohistochemical staining revealed absent MOV10L1 protein expression in the testicular tissue. Based on the guidelines from American College of Medical Genetics and Genomics (ACMG), the c.345C>A (p.C115X) was classified as a pathogenic variant (PVS1+PM2_Supporting+PP4), while the c.3323C>T (p.T1108I) was deemed variant of uncertain significance (PM2_Supporting+PP3_Supporting+PP4). Bioinformatics analysis demonstrated that c.345C>A (p.C115X) may cause premature termination of protein translation, while c.3323C>T (p.T1108I) may disrupt the hydrophobicity of the RNA helicase domain, reducing the active pocket volume and decreasing its affinity for MILI protein. CONCLUSION: This study has diagnosed a case of SCOS due to compound heterozygous variants of the MOV10L1 gene, which also enriched its mutational spectrum.

Humans↗

PubMed2026

Diagnostic performance of intraoperative in vivo hyperspectral imaging for meningioma grading and molecular alterations: results from a prospective feasibility study.

OBJECTIVE: Hyperspectral imaging (HSI) is an emerging intraoperative, noninvasive, contrast agent-free imaging modality that enables quantitative assessment of tissue composition. The present study aimed to investigate whether HSI-derived tissue parameters correlate with WHO grade and molecular markers of aggressiveness in cranial meningiomas. METHODS: In this prospective study, intraoperative in vivo HSI was performed using the TIVITA tissue system, capturing spectral signatures between 500 and 1000 nm. Quantitative tissue parameters included tissue oxygen saturation (StO2), near-infrared perfusion index, organ hemoglobin index (OHI), and tissue water index (TWI). HSI parameters were correlated with histopathological WHO grade and molecular alterations, including CDKN2A/B deletion, TERT promoter mutation, and 1p/22q loss. Group differences were analyzed using one-way ANOVA, and diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. RESULTS: Forty-six meningiomas were included, comprising WHO grade 1 (n = 35) and WHO grade 2-3 (n = 11) tumors. TWI was significantly higher in WHO grade 2-3 meningiomas compared with WHO grade 1 tumors (mean 0.49 [SD 0.12] vs 0.38 [SD 0.17], p = 0.048). ROC analysis demonstrated an area under the ROC curve (AUC) of 0.71 (95% CI 0.56-0.86, p = 0.036) for TWI in discriminating higher-grade disease. A TWI cutoff ≥ 0.367 identified all WHO grade 2-3 meningiomas with 100% sensitivity and 100% negative predictive value. In a molecular subgroup (n = 15), OHI appeared higher in tumors with homozygous CDKN2A/B deletion than in nondeleted tumors (mean 0.77 [SD 0.04] vs 0.62 [SD 0.10]). However, only 3 CDKN2A/B-deleted cases were available, and these findings should be considered descriptive. ROC analysis yielded an AUC of 0.89 (95% CI 0.71-1.00). An OHI cutoff ≥ 0.712 identified all three CDKN2A/B-deleted tumors (100% sensitivity), with 83.3% specificity and 86.7% accuracy. CONCLUSIONS: The present investigation demonstrated that HSI-derived tissue water and hemoglobin metrics provide biologically meaningful information in meningiomas. Low tissue water content appeared to rule out higher-grade diseases in this first subset cohort, while elevated hemoglobin showed a potential association with CDKN2A/B deletion in a small exploratory subgroup. These findings support the potential of HSI as a real-time noninvasive tool for intraoperative risk stratification and should be evaluated in large-scale studies. German Clinical Trials Register no. DRKS00036771 (www.drks.de).

Humans↗

PubMed2026

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↗