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Recently Evolved, Stage-Specific Genes Are Enriched at Life-Stage Transitions in Flies.

Understanding how genomic information is selectively utilized across different life stages is essential for deciphering the developmental and evolutionary strategies of metazoans. In holometabolous insects, the dynamic expression of genes enables distinct functional adaptations at embryonic, larval, pupal, and adult stages, likely contributing to their evolutionary success. While Drosophila melanogaster (D. melanogaster) has been extensively studied, less is known about the evolutionary dynamics that could govern stage-specific gene expression. To address this question, we compared the distribution of stage-specific genes, that is, genes expressed in temporally restricted developmental stages, across the development of D. melanogaster and Aedes aegypti (A. aegypti). Using tau-scoring, a computational method to determine gene expression specificity, we found that, on average, a large proportion of genes (20%-30% of all protein-coding genes) in both species exhibit restricted expression to specific developmental stages. Phylostratigraphy analysis, a method to date the age of genes, further revealed that stage-specific genes fall into two major categories: highly conserved and recently evolved. Notably, many of the recently evolved and stage-specific genes identified in A. aegypti and D. melanogaster are restricted to Diptera order (20%-35% of all stage-specific genes), highlighting ongoing evolutionary processes that continue to shape life-stage transitions. Overall, our findings underscore the complex interplay between gene evolutionary age, expression specificity, and morphological transformations in development. These results suggest that the attraction of genes to critical life-stage transitions is an ongoing process that may not be constant across evolutionary time or uniform between different lineages, offering new insights into the adaptability and diversification of dipteran genomes.

Animals

Chemoradiotherapy versus short-course radiotherapy for response-adapted organ preservation in early-stage and intermediate-stage rectal cancer (STAR-TREC): 12-month results of an international, multicentre, open-label, parallel-group, randomised, phase 2/3 trial.

BACKGROUND: Total mesorectal excision (TME) is the standard treatment for most early-stage and intermediate-stage rectal cancer but can cause substantial perioperative morbidity, functional impairment, and reduced quality of life. We assessed whether long-course chemoradiotherapy (LCCRT) or short-course radiotherapy (SCRT) could increase organ preservation and reduce surgery, toxicity, and quality-of-life harms without compromising oncological outcomes. METHODS: STAR-TREC is an international, multicentre, open-label, parallel-group, randomised, phase 2/3 trial in five European countries. Eligible patients were aged 16 years or older in the UK or aged 18 years or older elsewhere, had an Eastern Cooperative Oncology Group (ECOG) performance status of 0-1, and rectal adenocarcinoma (≤40 mm staged as mrT1-T3bN0). In phase 2, participants were randomly assigned (1:1:1) to LCCRT-based organ preservation (LCCRT-OP; 50 Gy in 25 fractions plus oral capecitabine 825 mg/m2 twice daily), SCRT-based organ preservation (SCRT-OP; 25 Gy in five fractions), or primary TME. Phase 2 assessed feasibility, with recruitment at months 12 and 24 as the primary endpoint and feasibility thresholds of four or more and six or more randomisations per month, respectively. Phase 3 adopted a partially randomised patient-preference design, allowing participants to choose either organ preservation or TME. Participants that chose organ preservation were randomly assigned (1:1) to receive LCCRT-OP or SCRT-OP using centralised, computer-generated assignment, with stratification by country and MRI T category (≤T3a vs T3b) using minimisation. The phase 3 primary endpoint was organ-preservation 30 months after treatment initiation, defined as absence of TME, stoma, or local recurrence, which was assessed in the modified intention-to-treat population, which included participants in phase 2 and phase 3. After a planned interim analysis of unmasked phase 2 data, the trial steering committee and independent data monitoring committee recommended reporting a 12-month, modified intention-to-treat analysis of implementation outcomes for participants recruited before Aug 8, 2023. This study is registered with ISRCTN (14240288) and is closed. FINDINGS: Between June 14, 2017, and April 8, 2024, 503 participants were enrolled at 37 sites. Phase 2 enrolled 120 participants, with recruitment rates of three and six participants per month at months 12 and 24, respectively. Overall, 12-month TME-free survival was 60% (47 of 78 participants). After phase 3 recruitment ended, interim analysis of unmasked phase 2 data showed an early TME-free survival benefit with LCCRT versus SCRT (12-month median TME-free survival not reached [95% CI not reached-not reached] vs 7·6 months [95% CI 6·4-not reached]; hazard ratio [HR] 3·7 [95% CI 1·7-8·0]; posterior probability of superiority >99·5%). The trial steering committee and independent data monitoring committee therefore recommended expanded analysis of 426 participants recruited before Aug 8, 2023: 120 from phase 2 and 306 from phase 3. 17 participants withdrew before treatment, leaving 409 in the modified intention-to-treat population: 163 allocated to LCCRT, 168 to SCRT, and 78 to primary TME. 116 (28%) participants were female and 293 (72%) were male. Among participants who opted for organ preservation, 12-month TME-free survival was 78·5% (95% CI 72·4-85·1) with LCCRT and 60·6% (53·6-68·4) with SCRT (HR 1·90 [95% CI 1·29-2·81]). The most common grade 3-4 serious adverse events were gastrointestinal disorders (four [2%] with LCCRT vs six [4%] with SCRT vs six [8%] with TME) and procedural complications (three [2%] with LCCRT vs five [3%] with SCRT vs five [6%] with TME). One participant allocated to primary TME died after an anastomotic leak. INTERPRETATION: These early results support a response-adapted organ-preservation approach, with LCCRT appearing more effective than SCRT at 12 months. Organ-preservation might also reduce treatment-related toxicity compared with primary TME. Longer follow-up is needed for the prespecified 30-month endpoint and definitive functional and oncological outcomes. FUNDING: Cancer Research UK, Stand Up to Cancer, Dutch Cancer Society, Danish Cancer Society, Kom Op Tegen Kanker, Cancerfonden, ALF Region Stockholm, RCC Region Stockholm.

Humans

Untargeted-targeted metabolomics: energy metabolism characteristics in heart failure staging and discovery of novel biomarkers.

BACKGROUND: Heart Failure represents the severe stage of various heart diseases. Its global morbidity and mortality are on the rise, making it a serious public health issue that imposes a heavy burden on patients' families and society. Currently, there are relatively few systematic studies on the changes in specific metabolites and pathways in different stages of heart failure, such as Stage A, Stage B and Stage C. AIMS: Using untargeted-targeted metabolomics to explore the metabolic characteristics of Heart Failure, and screen out serum metabolic markers with potential diagnostic and prognostic value. METHODS: This study is a cross-sectional study. A total of 210 heart failure patients from Xiyuan Hospital of China Academy of Chinese Medical Sciences were enrolled between October 2023 and October 2024. Among them, 60 patients were selected for targeted metabolomics analysis via stratified sampling. Serum samples of the patients were collected and pretreated with methanol, then metabolites were detected using untargeted and targeted LC-MS respectively. After the raw data were processed with MSDIAL, pattern recognition was performed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Differential metabolites with variable importance in projection (VIP)&#x2009;>&#x2009;1 and P&#x2009;<&#x2009;0.05 were screened, and relevant pathways were analyzed via enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. RESULTS: Untargeted metabolomics revealed that, compared with patients in Stages A and B, those with heart failure in Stage C had decreased serum levels of alanine, creatine, and branched-chain amino acids, along with increased levels of citric acid, fumaric acid, and malic acid. The differential metabolites were primarily enriched in pathways including the citric acid cycle, central carbon metabolism, and amino acid metabolism, indicating that energy metabolism plays a crucial role in the occurrence and progression of HF. Targeted metabolomics validated the findings from untargeted metabolomics: compared with Stage A, the level of phosphoenolpyruvate in Stage B was reduced; and in comparison with patients in Stage A or B, patients in Stage C showed decreased serum levels of multiple energy metabolites (e.g., glucose-6-phosphate, fructose-6-phosphate, 3-phosphoglyceric acid, AMP, ADP and ATP) as well as increased levels of malic acid, which is consistent with the characteristics of the "hypermetabolism-energy starvation" paradox. CONCLUSION: Stage C of heart failure is characterized by energy metabolism collapse (decreased ATP and TCA compensation), and differential metabolites (such as malic acid) may serve as potential candidate biomarkers pending longitudinal validation.

Humans

Integrative multi-omics analysis of metabolite-protein interaction networks across different stages of coronary heart disease.

To elucidate the molecular characteristics of synergistic interactions across the clinical stages of coronary heart disease (CHD)-specifically stable angina pectoris (SAP), unstable angina pectoris (UAP), and acute myocardial infarction (AMI)-through integrated metabolomic and proteomic analyses. Based on a cohort including SAP, UAP, AMI, and healthy controls, metabolomic and proteomic analyses were performed to identify differentially expressed molecules, followed by KEGG pathway enrichment analysis. Pathways co-enriched across both omics platforms were selected to construct metabolite-protein interaction networks. The number of pathways co-enriched in both metabolomic and proteomic analyses increased markedly with disease stage. Only two pathways (histidine metabolism and arginine and proline metabolism) were identified in the SAP stage; this number increased to five in the UAP stage (including ferroptosis and efferocytosis) and expanded to 25 in the AMI stage, encompassing three major functional modules: immune inflammation, metabolic reprogramming, and cell signaling. The core network exhibited a stepwise increase in connectivity, shifting from a sparse structure in the SAP stage to a highly interconnected architecture in the AMI stage, with L-glutamate and KNG1 identified as the central hubs in this cross-sectional network. In addition, CNDP1 exhibited a stage-dependent functional transition, shifting from downregulation in SAP to upregulation in AMI. In this cross-sectional analysis, metabolic dysregulation and immune activation exhibited stepwise increases in interconnectivity across the SAP, UAP, and AMI groups, with the most extensive crosstalk observed in the AMI stage-a network configuration consistent with a tightly coupled "molecular storm". These findings provide novel insights into stage-associated molecular signatures of CHD and identify candidate hub molecules for stage-oriented therapeutic investigation.

Humans

Risk stratification in aortic stenosis: exercise haemodynamics to refine risk in early cardiac damage stages.

AIMS: To describe exercise haemodynamics across cardiac damage stages and evaluate the incremental prognostic impact of cardiac damage stage and exercise-induced pulmonary hypertension (exPHT) in patients with symptomatic moderate aortic stenosis (AS) and asymptomatic severe AS. METHODS AND RESULTS: A total of 436 consecutive patients with &#x2265; moderate AS (74 &#xb1; 10 years, 32% women, 56% severe AS) underwent cardiopulmonary exercise testing with echocardiography. The primary endpoint was heart failure (HF) death and HF hospitalizations. Cardiac damage stage was 0 in 93 patients, 1 (LV damage) in 135, 2 (LA/mitral damage) in 135, and 3-4 (pulmonary vasculature/tricuspid or RV damage) in 73. Higher stages were associated with worse exercise capacity and haemodynamics. Over a median follow-up of 37 months, 65 patients met the primary endpoint. After adjustment for age, AS severity, and aortic valve replacement, cardiac damage stage and exPHT were independently associated with HF outcomes [HR per stage increase 1.51 (1.26-1.82); P < 0.001; exPHT HR 2.36 (1.10-5.07); P = 0.03]. exPHT improved risk stratification in early-stage disease (stages 1-2), conferring an approximately five-fold higher risk of HF events in patients with exPHT [HR 4.45 (1.58-12.59); P < 0.01]. CONCLUSION: In patients with &#x2265; moderate AS and discordant symptoms, cardiac damage stage and exPHT independently refined HF risk stratification. ExPHT provides incremental prognostic value in early damage stages (1-2), representing over half of the cohort, supporting a stepwise approach of routine damage staging with selective with exPHT assessment with exercise echocardiography in this subgroup to guide more personalized management and potentially optimize AVR timing.

Humans

Next-Generation Sequencing Completion and Timeliness Using a Reflex Testing Protocol for Patients with Stage II to IV Nonsquamous Non-Small Cell Lung Cancer.

BACKGROUND: Next-generation Sequencing (NGS) is critical for providing treatment recommendations across multiple stages of non-small cell lung cancer (NSCLC). However, a substantial proportion of patients do not undergo testing. This study evaluated the completion rates and timeliness of NGS in patients with stage II to IV NSCLC at a single academic institution with a reflex NGS testing protocol. METHODS: Patients with stage II to IV nonsquamous NSCLC (ns-NSCLC) diagnosed between 2015 and 2022 were identified retrospectively. A reflex, tissue-based testing protocol was initiated in 2015 using in-house NGS. Pyrosequencing was performed if NGS failed. RESULTS: 501 patients were included: 75 (15.0%) with stage II, 82 (16.4%) with stage III, and 344 (68.6%) with stage IV ns-NSCLC. Tissue NGS was completed in 380 (75.8%) patients and 465 (92.8%) completed some tissue-based genomic testing when including pyrosequencing. Median time from biopsy to NGS was 17.0 days (range, 6-61 days). 61.0% of patients had NGS results prior to a first treatment of any type and 88.4% had tissue NGS results prior to systemic therapy. Among stage IV patients with completed NGS, median overall survival was 2.27 years for patients with NGS results prior to first treatment compared to 1.08 years for patients without NGS results prior to treatment initiation (P = .04). CONCLUSIONS: Implementation of an in-house, reflex NGS testing protocol enabled rapid genomic profiling in a high proportion of patients with stage II to IV ns-NSCLC. NGS completion prior to receiving first-line therapy was associated with improved survival compared to completion after first line treatment in stage IV patients.

Humans

Integrated multi-omic profiling enables recurrence risk stratification beyond pathological stage in resected EGFR-mutant lung adenocarcinoma.

BACKGROUND: Early-stage EGFR-mutant lung adenocarcinoma (LUAD) demonstrates heterogeneous outcomes after curative surgery, yet adjuvant treatment decisions are guided by pathological stage alone. Following the ADAURA trial, adjuvant osimertinib is the standard of care for resected stage IB-IIIA EGFR-mutant LUAD; however, real-world data demonstrate that up to 40% of patients remain disease-free at five years without adjuvant osimertinib, underscoring the need for improved risk stratification. PATIENTS AND METHODS: We performed integrated clinical, genomic and transcriptomic profiling of 400 patients with resected stage IA-IIIA EGFR-mutant LUAD. EGFR-mutant recurrence risk models integrating clinical, genomic and transcriptomic data were developed and validated across one internal and three external cohorts. RESULTS: Genomic instability, including TP53 co-mutations, copy number alterations and APOBEC-associated mutational signatures, increased with pathological stage. RBM10 co-mutations were enriched in tumours with L858R mutations and correlated with upregulation of WNT signalling and epithelial-mesenchymal transition. Transcriptomic features outperformed clinical or genomic variables alone in predicting recurrence risk, and a multi-omic model demonstrated superior and reproducible performance, achieving a median concordance index of 75.4% across four independent validation cohorts. The multi-omic model stratified recurrence risk within individual pathological stages, including stage I disease, and identified patients most likely to benefit from adjuvant EGFR TKI. CONCLUSIONS: These findings define the molecular heterogeneity of early-stage EGFR-mutant LUAD and support multi-omic risk stratification to inform adjuvant EGFR TKI decisions beyond pathological stage. Prospective validation in larger cohorts will be required to confirm these findings.

Journal Article

Automated Extraction of Tumor Staging and Diagnosis Information From Surgical Pathology Reports.

PURPOSE: Typically stored as unstructured notes, surgical pathology reports contain data elements valuable to cancer research that require labor-intensive manual extraction. Although studies have described natural language processing (NLP) of surgical pathology reports to automate information extraction, efforts have focused on specific cancer subtypes rather than across multiple oncologic domains. To address this gap, we developed and evaluated an NLP method to extract tumor staging and diagnosis information across multiple cancer subtypes. METHODS: The NLP pipeline was implemented on an open-source framework called Leo. We used a total of 555,681 surgical pathology reports of 329,076 patients to develop the pipeline and evaluated our approach on subsets of reports from patients with breast, prostate, colorectal, and randomly selected cancer subtypes. RESULTS: Averaged across all four cancer subtypes, the NLP pipeline achieved an accuracy of 1.00 for International Classification of Diseases, Tenth Revision codes, 0.89 for T staging, 0.90 for N staging, and 0.97 for M staging. It achieved an F1 score of 1.00 for International Classification of Diseases, Tenth Revision codes, 0.88 for T staging, 0.90 for N staging, and 0.24 for M staging. CONCLUSION: The NLP pipeline was developed to extract tumor staging and diagnosis information across multiple cancer subtypes to support the research enterprise in our institution. Although it was not possible to demonstrate generalizability of our NLP pipeline to other institutions, other institutions may find value in adopting a similar NLP approach-and reusing code available at GitHub-to support the oncology research enterprise with elements extracted from surgical pathology reports.

Humans

Transcriptomic analysis of eggs, rediae and cercariae reveal stage-specific adaptations in the rumen fluke Calicophoron daubneyi.

Rumen flukes, particularly the trematode Calicophoron daubneyi, are emerging parasites of livestock in Europe, yet transcriptomic insights into their environmental and intermediate host stages remain limited. Here, we present a comprehensive transcriptomic analysis of eggs at three distinct developmental stages (freshly excreted, early developmental and eye-spot stages), as well as rediae and cercariae, of C. daubneyi. High-quality RNA-sequencing (RNA-seq) datasets revealed both shared and stage-specific transcriptional profiles with each developmental stage exhibiting its own distinct expression pattern. Subsequent GO-Term enrichment analyses revealed that fully embryonated eggs in eye-spot-stage especially upregulated genes related to cilia assembly, movement and motility, reflecting preparation for miracidial hatching and host-seeking behavior. Rediae showed enhanced transcription of genes involved in diverse metabolic and biosynthetic processes, supporting rapid asexual proliferation within the snail intermediate host. Cercariae exhibited predominant upregulation of genes associated with signal transduction and energy metabolism, indicating the adaptation to its changing environmental conditions. These findings provide the first transcriptomic insights into the biology of C. daubneyi outside the definitive host, reveal molecular mechanisms underlying development, transmission and adaptation to a changing environment and identify stage-specific genes as potential targets for interventions aimed at disrupting the parasites life cycle and controlling rumen flukes in the future.

Animals

Large Language Model and Knowledge Graph-Driven AJCC Staging of Prostate Cancer Using Pathology Reports.

Background/Objectives: To develop an automated American Joint Committee on Cancer (AJCC) staging system for radical prostatectomy pathology reports using large language model-based information extraction and knowledge graph validation. Methods: Pathology reports from 152 radical prostatectomy patients were used. Five additional parameters (Prostate-specific antigen (PSA) level, metastasis stage (M-stage), extraprostatic extension, seminal vesicle invasion, and perineural invasion) were extracted using GPT-4.1 with zero-shot prompting. A knowledge graph was constructed to model pathological relationships and implement rule-based AJCC staging with consistency validation. Information extraction performance was evaluated using a local open-source large language model (LLM) (Mistral-Small-3.2-24B-Instruct) across 16 parameters. The LLM-extracted information was integrated into the knowledge graph for automated AJCC staging classification and data consistency validation. The developed system was further validated using pathology reports from 88 radical prostatectomy patients in The Cancer Genome Atlas (TCGA) dataset. Results: Information extraction achieved an accuracy of 0.973 and an F1-score of 0.986 on the internal dataset, and 0.938 and 0.968, respectively, on external validation. AJCC staging classification showed macro-averaged F1-scores of 0.930 and 0.833 for the internal and external datasets, respectively. Knowledge graph-based validation detected data inconsistencies in 5 of 150 cases (3.3%). Conclusions: This study demonstrates the feasibility of automated AJCC staging through the integration of large language model information extraction and knowledge graph-based validation. The resulting system enables privacy-protected clinical decision support for cancer staging applications with extensibility to broader oncologic domains.

artificial intelligence

Stage shift, histological differentiation, and survival patterns of lung squamous cell carcinoma versus adenocarcinoma in low-dose CT screening.

BACKGROUND: Whether LDCT-associated stage shift translates into similar survival patterns across lung cancer histologies remains uncertain. We compared stage shift, histological differentiation, tumor characteristics, and survival between lung squamous cell carcinoma (LUSC) and adenocarcinoma (LUAD) in the National Lung Screening Trial. METHODS: Among participants diagnosed with LUSC or LUAD, stage distribution and histological differentiation were compared between LDCT and chest X-ray (CXR) arms. Survival among diagnosed cases was measured from randomization. Multivariable models tested screening arm-by-histology interactions. Screen-detected LDCT tumors were compared by histology. RESULTS: During 6.5 years of median follow-up, 498 LUAD and 249 LUSC cases were diagnosed in the LDCT arm, and 374 and 212, respectively, were diagnosed in the CXR arm. LDCT was associated with higher odds of stage I disease for LUAD (adjusted odds ratio [aOR], 2.48; 95% CI 1.88-3.28) and LUSC (aOR, 1.71; 95% CI 1.17-2.48), without significant interaction (P&#x202f;=&#x202f;0.116). LDCT was associated with lower hazard of lung cancer-specific death among diagnosed LUAD cases (adjusted hazard ratio [aHR], 0.54; 95% CI 0.43-0.66), but not among diagnosed LUSC cases (aHR, 1.04; 95% CI 0.78-1.39; P for interaction<0.001). LUSC had lower screening sensitivity, more frequent detection in annual screening rounds, greater prediagnostic tumor size increase, and fewer well-differentiated stage I tumors than LUAD. CONCLUSION: LDCT was associated with stage shift for both subtypes, but favorable survival patterns among diagnosed cases were mainly observed for LUAD. Lower screening sensitivity, greater prediagnostic tumor size increase, and poorer histological differentiation may help explain why stage shift did not translate into similar survival patterns for LUSC. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00047385.

Humans

Integrative dual-track transcriptomics reveals stage-specific coordination, regulatory divergence, and HSP90AA1-associated remodeling in human folliculogenesis.

Human folliculogenesis depends on coordinated yet non-identical developmental remodeling in the oocyte and its surrounding granulosa cells. When these two compartments remain synchronized and when they diverge into lineage-specific regulatory states, however, remains incompletely resolved. Here we performed an integrative dual-track re-analysis of the human RNA-seq dataset GSE107746, modeling oocytes and granulosa cells as distinct but developmentally linked compartments across follicular progression. Analysis of 148 sequencing libraries showed that compartment identity was the dominant source of transcriptomic variation, supporting compartment-aware downstream interpretation. Within this framework, oocytes followed a relatively continuous developmental trajectory, with substantial transcriptional remodeling already evident across adjacent stages, whereas granulosa cells showed weaker early-stage contrasts but markedly stronger late-stage reorganization, particularly around the antral and preovulatory transitions. Functional enrichment indicated that oocyte maturation was associated with RNA-processing and broader genome-regulatory remodeling, whereas granulosa maturation was dominated by progressive mitochondrial and bioenergetic activation. Co-expression analysis showed that both compartments contained strong late-stage programmes together with inverse early-state modules, indicating a shared systems-level architecture of maturation, although the hub-gene composition and biological content of these programmes were largely compartment-specific. Machine-learning validation reinforced this asymmetry: oocyte stage classification was best recovered from a compact eigengene-based representation, whereas granulosa stage discrimination was better resolved by a broader differential-expression-derived feature set. At the gene level, HSP90AA1 emerged as a stage-associated marker with compartment-specific behavior, showing progressive attenuation across oocyte development, assignment to the selected oocyte blue module, and sharper transitional dynamics in granulosa cells. Together, these findings support a model in which human folliculogenesis proceeds through coordinated but non-equivalent transcriptomic remodeling, with shared developmental logic at the systems level but distinct molecular execution in germline and somatic compartments.

Co-expression networks

primary analysis of the RANDOMIZED eortc-2139/columbus-ad trial: Adjuvant encorafenib and binimetinib versus placebo in high-risk stage II BRAF-V600E/K melanoma.

PURPOSE: Stage IIB/IIC melanoma has a high risk of recurrence after resection. Combined BRAF/MEK inhibitor therapy showed benefit in resected high-risk stage III and advanced melanoma. The objective of this study was to investigate its role in stage IIB/IIC. METHODS: Adult patients with resected stage IIB/IIC cutaneous melanoma which had a BRAF V600E/K mutation were randomized 1:1 to receive encorafenib (enco) 450&#x202f;mg QD&#x202f;+&#x202f;binimetinib (bini) 45&#x202f;mg BID orally for one year or placebo. The study planned to randomize 815 patients and was designed to demonstrate superiority regarding recurrence-free survival (RFS). Following a premature termination of accrual, the study was amended with safety as the primary endpoint and RFS as secondary endpoint. RESULTS: Between June 9, 2022, and October 9, 2023, 339 patients were screened for a BRAF mutation and 110 randomized. Data cutoff was 19 Nov. 2024, after the last patient discontinued study participation. Among randomized patients, 87 (79%) had a BRAF V600E mutation, and 39 (35%) AJCC8 stage IIC. Median follow-up was 12 and 7 months for enco/bini and placebo arms, respectively. Among 54 patients who initiated enco&#x202f;+&#x202f;bini, grade &#x2265;&#x202f;3 treatment-related adverse events (AE) occurred in 13 (24%) patients, and 18 (33%) patients had an AE leading to permanent treatment discontinuation. RFS at 12 months was 86% (95% CI: 65-95%) in the enco&#x202f;+&#x202f;bini and 70% (95% CI: 46-85%) in the placebo arm, distant metastasis-free survival at 12 months was 92% (95% CI: 77-97%) for enco&#x202f;+&#x202f;bini and 82% (95% CI: 55-93%) for placebo. CONCLUSION: EORTC 2139 - Columbus-AD demonstrated a consistent and manageable safety profile and encouraging efficacy results for the combination of enco and bini in resected stage IIB/C BRAF V600E/K-mutated cutaneous melanomas.

Adult

Spatial proteomics reveals four-stage molecular evolution in cancer immunotherapy-related gastritis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, yet immune-related adverse events (irAEs) including immunotherapy-related gastritis (IRAEG) pose significant clinical challenges-often necessitating treatment interruption that may compromise antitumor efficacy. IRAEG presents with atypical symptoms, lacks specific biomarkers, and shows histopathological overlap with other forms of gastritis, complicating diagnosis and management. Despite increasing clinical recognition, a systematic understanding of spatial molecular alterations across the full disease course remains limited. Here, we used spatial proteomics to map the molecular landscape of IRAEG during disease progression and to define stage-specific patterns of molecular evolution relevant to cancer immunotherapy management. METHODS: We analyzed tissue samples from seven patients, including four non-immunotherapy-related gastritis controls and three cancer patients who developed IRAEG following ICI therapy for solid tumors, sampled longitudinally across four disease stages: baseline (G1), acute severe inflammation (G2), early recovery (G3), and complete recovery (G4). Using laser capture microdissection coupled with data-independent acquisition mass spectrometry, we profiled 177 spatially resolved gastric tissue regions. Multiplex immunohistochemistry and immunofluorescence characterized features of the immune microenvironment, while Gene Ontology, KEGG pathway analysis, Gene Set Variation Analysis, and xCell inference enabled functional, metabolic, and immune profiling. Key immune and NET-related findings were further validated by multiplex immunofluorescence in an independent, expanded cohort of IRAEG and non-immunotherapy-related gastritis samples. RESULTS: IRAEG was characterized by widespread HLA molecule activation and enhanced antigen processing, resembling the immune phenotype observed in organ transplant rejection. The acute G2 stage exhibited excessive neutrophil extracellular trap formation, profound metabolic suppression, and collapse of immune homeostasis-features that may inform early intervention strategies to preserve ICI treatment continuity. During early recovery (G3), inflammatory injury transitioned toward repair, marked by activation of fatty acid metabolism and PPAR signaling. Notably, even at complete clinical recovery (G4), more than 1,000 proteins remained differentially expressed, reflecting sustained enhancement of metabolic and immune functions and establishing a distinct molecular "memory" state with implications for ICI rechallenge decisions. CONCLUSIONS: These findings define four molecularly distinct stages of IRAEG progression and recovery. The stage-specific signatures identified here serve as candidate biomarkers for diagnosis, disease staging, and therapeutic response assessment, and may guide clinical decisions regarding irAE management, treatment modification, and safe ICI rechallenge to support continued antitumor therapy.

Humans

Sleep stage-dependent distribution of interictal epileptiform discharges in epilepsy: A systematic review.

BACKGROUND: Sleep and epilepsy interact through complex bidirectional mechanisms. Although NREM sleep facilitates interictal epileptiform discharges (IED), the diagnostic contribution of individual sleep stages remains uncertain. In particular, it is unclear whether deeper sleep stages such as N3 provide an advantage over N2 for spike detection or localization in clinical (electroencephalography) EEG practice. METHODS: This systematic review followed PRISMA 2020 guidelines. PubMed and Web of Science were searched for studies reporting quantitative IED measures across sleep stages in patients with epilepsy. Eligible studies included scalp EEG, video-EEG, polysomnography, or intracranial recordings. Mean IED rates per minute were derived when possible. Comparisons between NREM and REM sleep and between N2 and N3 stages were performed using study level non-parametric tests. Risk of bias was assessed with the ROBINS-I tool. RESULTS: Ten observational studies including 266 patients (mean age 30.1&#xa0;years) were analyzed. IED rates were significantly higher during NREM than REM sleep (Wilcoxon signed-rank test, W&#xa0;=&#xa0;0, p&#xa0;=&#xa0;0.0019, r&#xa0;=&#xa0;0.87). No significant difference was observed between N2 and N3 sleep, although median spike rates were slightly higher during N3 than N2 (0.99 vs 0.86 IED/min). REM showed the lowest activity. CONCLUSIONS: NREM sleep consistently exhibited higher IED rates than REM sleep, reinforcing the neurophysiological association between sleep stage and epileptiform activity without establishing diagnostic superiority.

Humans

Comprehensive bioinformatics analysis identifies candidate ciliogenesis-related genes preferentially associated with N0-stage lung squamous cell carcinoma.

PURPOSE: There is few research on which genes play an important role in tumors without lymph metastasis. This study aimed to identify candidate molecular alterations preferentially associated with N0-stage LUSC. METHODS: we conducted a comprehensive bioinformatics analysis using publicly available The Cancer Genome Atlas (TCGA) data. Differentially expressed genes (DEGs) were identified separately by comparing N0 tumors and N+ tumors with normal lung tissues. Genes dysregulated in both N0 and N+ tumors were excluded to identify candidate N0-associated genes PPI networks were constructed using STRING and Cytoscape, with module analysis performed via MCODE. Hub genes were identified using multiple Cytohubba algorithms. Functional enrichment analyses were conducted using GO, and KEGG pathways using DAVID. Gene interaction networks were further explored using GeneMANIA. Immune cell infiltration was evaluated with TIMER. Associations with pathological stage and patient survival were assessed using GEPIA and other relevant tools. RESULTS: A total of 1103 candidate N0-associated DEGs were identified, including 748 upregulated and 355 downregulated genes. The PPI network contained five major MCODE clusters. One cluster (MCODE 4) included TTC30A, TTC30B, BBS7, and KIF3B genes implicated in ciliogenesis. TTC30B showed significant differential expression across pathological stages in the overall LUSC cohort. Seven consensus hub genes (ERBB2, CHUK, CASP8, NOTCH1, HNF4A, CREBBP, and IRS1) were identified based on their consistent ranking across multiple CytoHubba algorithms. Upregulated candidate N0-associated genes were primarily enriched in immune-related processes, including B-cell-mediated immunity and humoral responses, whereas downregulated genes were enriched in lysosomal and trans-Golgi network-related pathways. Exploratory immune infiltration analyses identified associations between the four ciliogenesis-related genes and several immune cell populations. CONCLUSIONS: This study identified candidate molecular signatures preferentially associated with N0-stage LUSC, including ciliogenesis-related genes and consensus hub genes. These findings provide hypotheses regarding molecular features of N0-stage LUSC and warrant further validation in independent cohorts and experimental studies.

Humans

Multidimensional GWAS analyses on longitudinal phenotypes reveal candidate genes regulating multi-stage egg production traits in Wannan yellow chicken.

Egg production performance directly determines the economic viability of indigenous chicken breeding. However, the genetic regulation of multi-stage egg production traits remains difficult to characterize due to their complex and dynamic nature. Here, we integrated a multidimensional GWAS framework, including single-trait GWAS, multi-trait GWAS (MTAG), and longitudinal trajectory-based GWAS (TrajGWAS), to identify stage-specific and shared genetic effects underlying egg production traits in Wannan yellow chickens (WNY). Whole-genome sequencing of 354 WNY hens (10&#xd7; depth) and quality control yielded 14,253,816 SNPs for analysis. Selective sweep analyses comparing red jungle fowl, commercial layers, and WNY identified a genomic region containing IGF1 under significant selection pressure. Single-trait GWAS identified SNPs 4_57990480 (BMPR1B) and 17_370912 (LOC112531479) associated with egg production across three laying stages (21-30, 31-40, and 21-40 weeks). MTAG further identified loci 8_4336468 (FASLG) and 21_654726 (CHD5) with shared effects across the laying period, whereas TrajGWAS revealed longitudinal associations involving PRKG1 and identified dynamic loci associated with clutch traits, including GRID1. For clutch traits, stage-specific loci were detected for average clutch size (ACS) and maximum clutch size (MCS), including SNP 8_8542036 at 21-30 weeks, PROK1 at 31-40 weeks, and CUL5, ALKBH8 across the entire laying period. These results demonstrate that integrating complementary GWAS strategies improves the resolution of genetic architecture underlying egg production traits by capturing trait-specific, shared, and stage-dependent genetic effects. The identified GWAS loci and selective-sweep candidate regions provide insights into the genetic architecture of egg production traits and breed differentiation.

Egg production

Transcriptomic and metabolomic analyses revealed the action mechanism of nesfatin-1 gene on glucolipid metabolism during early development stage of largemouth bass.

Nesfatin-1 has biological roles including the suppression of food intake and the regulation of glucose and lipid metabolism. However, the information available regarding nesfatin-1 in the glycolipid metabolism in the early development stage of fish is still limited. In order to investigate the role of the nesfatin-1 gene in the early development stage of the largemouth bass (Micropterus salmoides), the nesfatin-1 gene was knocked down using siRNA interference technology. Then, we evaluated its mRNA expression levels, transcriptomes and metabolomes. The mRNA expression levels of nesfatin-1 gene were appreciably decreased at 48&#xa0;h, 72&#xa0;h and 96&#xa0;h after injection of nesfatin-1 siRNA in the early development stage. The omics results revealed that knockdown of the nesfatin-1 gene induced 1833 differentially expressed genes (DEGs) and 2370 differentially expressed metabolites (DEMs). Bioinformatic analysis enriched the most affected molecular pathways (sphingolipid metabolism, fatty acid elongation, amino sugar and nucleotide sugar metabolism and biosynthesis of unsaturated fatty acids) and metabolic pathways (biosynthesis of unsaturated fatty acids, sphingolipid metabolism and amino sugar and nucleotide sugar metabolism) in early development stage of largemouth bass. In amino sugar and nucleotide sugar metabolism, increased expression levels of genes such as chic, chs1, and gck genes, alongside decreased expression levels of the chia.1 gene, resulted in significantly elevated concentrations of N-Acetyl-D-glucosamine, &#x3b2;-d-fructose 6-phosphate, &#x3b2;-d-Fructose, D-mannose 6-phosphate, d-glucose, d-glucose 1-phosphate, UDP-glucose, and UDP-glucuronate, whilst the concentration of UDP-N-acetyl-&#x3b1;-D-glucosamine was markedly reduced. Therefore, the nesfatin-1 gene may influence the early development stage of largemouth bass by affecting signaling pathways associated with glycolipid metabolism. Our findings further expand the understanding of&#xa0;molecular mechanisms of the nesfatin-1 gene, and provide further theoretical support for the initial breeding and feed adaptation of largemouth bass.

Animals