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mRNA profiles to identify metaphase, histone, and cancer testis antigen gene overexpression in metastatic GEP-NETs: An ORIEN analysis.

e16313 Background: Well-differentiated GEP-NETs comprise a heterogenous group of malignancies with variable behavior. While existing grading structures attempt to predict these behaviors, significant variability remains. The ORIEN database contains complementary clinical, genomic, and transcriptomic profiling, providing a novel source for correlating molecular data with clinical characteristics. Methods: mRNA expression profiles were assessed for correlation the presence (M1) or absence (M0) of metastatic disease at diagnosis. The workflow consisted of: (1) Data preparation: RSEM gene expression data were processed, quality-controlled, and mapped to clinical metadata. (2) Differential gene expression: DESeq2 was used to identify significantly differentially expressed genes (FDR < 0.05). (3) Pathway enrichment analysis: Gene Ontology (GO), KEGG, and Reactome enrichment analyses were performed on all differentially expressed genes to identify biological pathways associated with metastatic status. Results: Across all GEP-NETs, 112 genes had significantly different expression levels for M1 (n = 5) vs. M0 (n = 24) stage, including 35 genes expressed at higher levels in M1 disease. In analysis limited to pNETs, 708 genes showed significantly different expression levels between M1 (n = 3) and M0 (n = 20) stages, including 155 genes expressed at higher levels in in M1 disease. In both the entire GEP-NET cohort and pNET subgroup analysis, the most frequently overexpressed Reactome pathways associated with M1 stage were related to the regulation of metaphase transition and DNA-protein (histone) interactions. Cancer testis antigen (CTA) genes were also frequently upregulated (Table 1). Conclusions: Differential mRNA expression data provides a novel means for better characterizing the molecular underpinnings of GEP-NETs. Specifically, cell cycle, histone-related, and CTA gene expression profiles may provide actionable findings on which to base downstream drug development for the prevention and/or treatment of metastatic disease. Most upregulated mRNA profiles by magnitude in metastatic GEP-NETs. Gene Log 2 Fold ∆ a Description / Function GAGE2A 7.41 CTA, chromatin regulator, anti-apoptosis RNF17 5.89 CTA, DNA damage response GTSF1 5.76 CTA, DNA methylation, retrotransposon regulation NBEAP1 5.19 Also called BCL8, little known normal physiologic function ORM1 4.53 Acute phase reactant, angiogenesis, immune evasion HIST2H3C 4.18 Histone H3 regulation, chromatin regulator LYZ 4.12 Lysozyme production, TME inflammation, immune evasion PBK 4.02 CTA, cell cycle regulation, histone phosphorylation, anti-apoptosis HIST2H3A 3.71 Histone H3 regulation, chromatin regulator a All p-values <0.0001.

Using machine learning to predict treatment delivery accuracy in brain stereotactic radiosurgery.

e14007 Background: Accurate dose delivery in SRS is critical when treating small intracranial targets near critical structures. Suboptimal delivery can impact patient outcomes and have the potential to compromise clinical trial results. The SRS Head Phantom, issued by the Radiation Quality Assurance Lab (IROC) is a standardized patient surrogate used as a mandatory credentialing tool for institutions participating in NCI-sponsored clinical trials involving SRS. This study aims to develop ML models capable of predicting SRS delivery accuracy across various platforms and clinical settings. This approach can help identify key factors associated with suboptimal performance and could supplement the physical process to streamline clinical trial credentialing. Methods: We analyzed 930 SRS audit results from 673 institutions participating in the RQALab/IROC program between 2013 and 2023. The phantom contains a 1.9 cm spherical target with embedded detectors. Each test evaluated delivered versus intended dose at the treatment target, requiring agreement within ±5%3mm. We collected 60 features encompassing treatment and planning parameters, plan quality indices, and measures of plan complexity and used these to predict delivery accuracy. Random Forest models were trained to predict dose delivery deviation and pass/fail status. The dataset was divided into seven subgroups based on machine type and treatment planning system. Within each group, models were trained using a 25x4-fold cross-validation approach. SHAP (SHapley Additive exPlanations) values were utilized to identify the top contributing features and ensure model interpretability. Results: Machine-learning models predicted the delivered target dose with a mean absolute error of 2% in the largest practice cohort (N=320). For predicting unacceptable deliveries, the models exhibited high sensitivity (98%) and accuracy (0.93). For dedicated Gamma Knife platforms (N=77), the models achieved 99% prediction accuracy. Interpretability analyses revealed that plan quality metrics were the dominant predictors of suboptimal delivery accuracy; specifically, poor plan quality correlated with larger deviations between planned and delivered doses. Conformity and dose gradient were identified as top contributors across most cohorts. The specific ranking and predictive weight of these features varied by modality; for instance, complexity metrics contributed significantly to modulated plans, whereas target volume metrics played a larger role in deliveries using dedicated SRS treatment machines. Conclusions: Machine learning can effectively identify SRS deliveries at risk of failure through models tailored to specific delivery modalities. By integrating explainable AI methods, this approach highlights actionable strategies to improve precision, standardize performance across institutions, and enhance patient safety.

Cryo-EM reveals multiple mechanisms of ribosome inhibition by doxycycline

Abstract Antimicrobial resistance is driving the search for new antibiotics and a greater understanding of their mechanism of action. Doxycycline is amongst the most-prescribed antimicrobials. It demonstrates a particularly low minimum inhibitory concentration against the zoonotic pathogen Coxiella burnetii . Doxycycline canonically targets the bacterial ribosome by blocking tRNA binding at the decoding centre (A site) of the small subunit. Using cryo-electron microscopy, we analysed doxycycline binding to C. burnetii and Escherichia coli ribosomes. Both structures reveal doxycycline binding at the exit tunnel in the large subunit. In C. burnetii three doxycycline molecules stack to block the tunnel. In E. coli one doxycycline molecule triggers a major change in the conformation of the ribosome. This rearrangement of the peptidyl transferase centre blocks tRNA binding and nascent chain accommodation, abolishing interactions that are fundamental to ribosome function. We identify a distinct ribosomal protein in the C. burnetii large subunit and characterise an additional member of the prokaryotic ribosome hibernation-promoting factor family. These insights into ribosome function and antibiotic action may aid the development of new ribosome inhibitor antibiotics.

Re-evaluating pathologic response as a surrogate endpoint after neoadjuvant immune checkpoint inhibition in resectable mucosal HNSCC: Updated systematic review and meta-analysis.

e18078 Background: Neoadjuvant immune checkpoint inhibition (ICI) is increasingly studied in resectable mucosal head and neck squamous cell carcinoma (HNSCC), where major/partial pathologic response is commonly reported, but its value as a surrogate for survival remains uncertain. We performed an updated systematic review and meta-analysis to evaluate the association of pathologic response with disease-free survival (DFS) and to summarize grade ≥3 toxicity. Methods: We systematically searched five electronic databases from inception to 5 January 2026 for peer-reviewed English-language studies of adults (≥18 years) with mucosal HNSCC treated with neoadjuvant ICI. Prespecified outcomes were DFS by pathologic response (MPR and PPR; pooled as hazard ratios [HRs] with 95% CIs when reported/derivable) and grade ≥3 adverse events (pooled as risk ratios [RRs] with 95% CIs). Random-effects meta-analysis was performed, and heterogeneity was quantified using I². Results: The pooled DFS analysis for partial pathologic response (PPR) showed a non-significant trend toward benefit (HR 0.58, 95% CI 0.28–1.23; I²=1.9%), with a prediction interval of 0.13–2.64. In contrast, DFS for major pathologic response (MPR) was not statistically significant and was highly inconsistent across studies (HR 1.91, 95% CI 0.24–15.36; I²=88.7%), with an extremely wide prediction interval (0.00–9640.39). For grade ≥3 adverse events, neoadjuvant therapy was associated with a significant reduction in severe toxicity (RR 0.54, 95% CI 0.48–0.62; I²=0%), with a prediction interval of 0.24–1.23. Conclusions: Neoadjuvant ICI reduced grade ≥3 toxicity, but MPR/PPR were not reliable surrogates for DFS. Future trials should prioritize DFS endpoints with standardized response definitions and longer follow-up.

Peri-operative nab-paclitaxel with sequential radiotherapy in cardiac angiosarcoma: A single-center retrospective cohort study.

e23549 Background: Primary cardiac angiosarcoma (PCA) is an extremely rare and highly aggressive soft-tissue sarcoma. Due to the anatomical complexity of the heart, complete surgical resection is almost impossible, rendering adjuvant therapy critical for improving postoperative outcomes. Currently, there is no consensus on the optimal adjuvant strategy. While paclitaxel-based chemotherapy has demonstrated promising efficacy in recurrent or metastatic settings, its role in the adjuvant setting remains undefined. Here, we report our initial experience using adjuvant albumin-bound paclitaxel (nab-paclitaxel) and sequential regional radiotherapy in a small cohort of PCA patients. Methods: We retrospectively included six patients with the definite diagnosis of PCA who underwent surgical resection followed by adjuvant nab-paclitaxel at Peking Union Medical College Hospital between 2023 and 2025. Results: The cohort included 4 females and 2 males, with a median age of 33.5 years (range: 25–43). All tumors were localized to the right atrium or adjacent structures, with stage T1-3N0M0. The median maximum diameter was 6.85 cm (range: 4.6–10.2). Five patients (P01-5) received adjuvant nab-paclitaxel, while P06 received neoadjuvant and adjuvant nab-paclitaxel. In addition, 3 patients (P01, P02, P04) received adjuvant radiotherapy. At a median follow-up of 14 months, the median progression-free survival (PFS) was 8 months (range: 2 to 30+; 2 patients censored), and the median overall survival (OS) was 24 months (range: 6+ to 30+; 3 patients alive). Treatment was generally well tolerated, with no serious adverse events leading to discontinuation. Conclusions: This small series suggests that adjuvant nab-paclitaxel and sequential regional radiotherapy is a feasible strategy for patients with resected PCA. The addition of neoadjuvant nab-paclitaxel appears safe in selected cases. Multi-institutional collaboration and prospective studies are urgently needed to validate the safety and efficacy of perioperative nab-paclitaxel in this ultra-rare malignancy. Individual baseline characteristics and treatment. Patient Sex Age (y) Stage Maximum diameter (cm) Primary site Chemotherapy Radiotherapy PFS (m) OS (m) P01 M 31 T2N0M0 8 Lateral wall of right atrium Nab-paclitaxel (adjuvant) Spiral tomography radiotherapy (TOMO) 5 (liver metastases) 24 (hepatic failure) P02 F 35 T1-2N0M0 8 Anterior wall of right atrium Nab-paclitaxel (adjuvant) Radiotherapy 30+ 30+ P03 M 25 T2N0M0 4.6 Right atrium Nab-paclitaxel (adjuvant) 2 (local recurrence, lung metastases, bone metastases?) 10 (progression) P04 F 34 T2N0M0 5.6 Right atrium Nab-paclitaxel (adjuvant) Radiotherapy 11 (local recurrence) 18+ P05 F 43 T2N0M0 5.7 Right atrium Nab-paclitaxel (adjuvant) 5+ 6+ P06 F 33 T2-3N0M0 10.2 Right atrium Nab-paclitaxel (neoadjuvant and adjuvant) 4 (lung metastases) 6+

Decoding BTN3A3: A potential biomarker and therapeutic target to promote glycolytic metabolism reprogramming and nasopharyngeal carcinoma progression.

e15193 Background: Butyrophilin subfamily 3 member A3 (BTN3A3) is expressed in various tumors, where it modulates glycolysis, proliferation, invasion, and migration to influence progression. However, its molecular mechanisms in nasopharyngeal carcinoma (NPC) remain unclear. This study aims to elucidate BTN3A3's role in NPC progression, identify biomarkers for invasion/metastasis risk stratification, and provide foundations for novel therapeutic targets. Methods: Immunohistochemistry (IHC) profiled BTN3A3 expression in nasopharyngeal tissues and correlated it with clinicopathological parameters and prognosis. BTN3A3 was overexpressed or silenced in NPC cell lines. Proliferation and tumorigenicity were assessed via CCK-8, colony-formation, and subcutaneous xenograft assays. Cell motility was quantified by wound-healing and transwell assays. RNA-sequencing and KEGG pathway enrichment were used to identify BTN3A3-regulated pathways. Western blotting evaluated its impact on glycolytic proteins. Integrated analysis of mass-spectrometry interactome data and the GeneCards glycolysis gene set identified PKM2 as a candidate binding partner. The BTN3A3–PKM2 interaction was predicted by molecular docking and validated by co-immunoprecipitation and immunofluorescence co-localization. Functional rescue experiments were conducted using PKM2 knockdown. Results: BTN3A3 mRNA and protein levels were significantly elevated in NPC versus chronic inflammation tissues (P < 0.001), and further increased in metastatic primary tumors (P = 0.003). Multivariate Cox analysis identified BTN3A3 as an independent predictor of poorer overall and progression-free survival. KEGG enrichment of RNA-seq data identified glycolysis as the top pathway regulated by BTN3A3, and western blotting confirmed BTN3A3 manipulation altered key glycolytic enzymes (GLUT1, HK2, LDHA; P < 0.01). Integrated interactome analysis nominated PKM2 as a candidate partner, and molecular docking predicted a high-affinity BTN3A3–PKM2 interaction, which was validated by co-immunoprecipitation and co-localization. BTN3A3 increased total and phospho-PKM2-Ser37 levels. Functionally, PKM2 knockdown attenuated BTN3A3-driven increases in proliferation, invasion, migration, and glycolytic flux (P < 0.05). Furthermore, BTN3A3 promoted PKM2 nuclear translocation, and enhanced the association between ERK1/2 and PKM2, indicating it facilitates ERK1/2-mediated phosphorylation and nuclear shuttling of PKM2 to drive glycolysis and NPC progression. Conclusions: BTN3A3 is upregulated in NPC and associated with poor prognosis and distant metastasis. Functionally, it promotes glycolytic reprogramming and tumor progression by enhancing ERK1/2-dependent phosphorylation of PKM2 at Ser37 and PKM2 nuclear translocation.

ReDiscover-2, a phase 3 study of zovegalisib (zovega, RLY-2608) + fulvestrant (fulv) versus capivasertib (capi) + fulv as treatment for locally advanced or metastatic <i>PIK3CA</i> -mutant HR+/ HER2- breast cancer following recurrence or progression on or after treatment with a CDK4/6 inhibitor.

TPS1148 Background: PIK3CA mutations constitutively activate PI3Kα and drive ~40% of HR+/HER2- breast cancer (BC). The PI3K inhibitors alpelisib and inavolisib and the AKT inhibitor capi are approved therapeutic options; however, they are limited by significant toxicity, notably hyperglycemia, rash, and diarrhea, due to non-selective targeting of the pathway. Zovega is a pan-mutant-selective allosteric PI3Kα inhibitor designed to optimize dose intensity and target inhibition with reduced toxicity and improved tolerability. The first-in-human ReDiscover study of zovega demonstrated encouraging antitumor activity with a median progression-free survival (PFS) of 10.3 mo (95% CI: 7.2, 18.4) across a range of PIK3CA genotypes and a favorable safety profile when combined with fulv in patients with PIK3CA -mutated HR+/HER2- advanced BC previously treated with a CDK4/6 inhibitor. Based on these findings, zovega in combination with fulv is being studied in this phase 3 study, ReDiscover-2 (NCT06982521), in PIK3CA -mutated HR+/HER2- advanced BC following recurrence or progression on or after a CDK4/6 inhibitor. Methods: ReDiscover-2 is a global, multicenter, open-label, randomized phase 3 study comparing the efficacy and safety of zovega + fulv to capi + fulv in patients with PIK3CA -mutated HR+/HER2- advanced BC. Approximately 540 patients will be randomized 1:1 to receive zovega (400 mg BID with food) + standard-dose fulv or capi (400 mg BID, 4 days on and 3 days off, with or without food) + fulv. Randomization will be stratified by PIK3CA mutation type, visceral disease, and geographic region. The primary endpoint is PFS assessed by blinded independent central review in patients having tumors with PIK3CA kinase domain mutations and in all patients. Overall survival is a key secondary endpoint within the same populations. Key eligibility criteria: ≥18 years of age with ECOG performance status of 0-1; confirmed diagnosis of HR+/HER2- locally advanced or metastatic BC with radiological or objective evidence of recurrence or progression; presence of one or more oncogenic PIK3CA mutations without evidence of AKT or PTEN alterations; measurable disease per RECIST v1.1 or evaluable bone-only disease; previous treatment for HR+/HER2- advanced BC with at least 1 and no more than 2 lines of endocrine therapy (ET) (prior fulv is allowed) or 1 prior line of CDK4/6 inhibitor therapy; HbA1c &lt;7.0% (&lt;53 mmol/mol) and fasting plasma glucose &lt;140 mg/dL (Type 1 diabetes or Type 2 diabetes requiring antihyperglycemic medication are excluded); no prior PI3K, AKT, or mTOR inhibitors. ReDiscover-2 (NCT06982521) is open for enrollment. For information: clinicaltrials@relaytx.com. Clinical trial information: NCT06982521 .

Prenatal hormonal imprinting reflected by anogenital distance and risk of breast cancer: A case-control study of 839 women.

10554 Background: Anogenital distance (AGD) is a sexually dimorphic, stable anthropometric marker set during fetal development and widely used as a proxy of prenatal androgen/estrogen balance. We hypothesized that AGD is associated with the risk of developing breast cancer (BC), a hormone-dependent disease. Methods: We conducted a prospective case–control study in Murcia (Spain) including 422 incident BC cases and 417 controls (2022–2024). Two AGD measures were obtained by trained examiners: ano-clitoral (AGDAC, “long”) and ano-fourchette (AGDAF, “short”). Models were adjusted for age and BMI; quintile-based logistic regressions assessed non-linear associations. Stratified analyses were performed by menopausal status. Molecular subtype and Oncotype Recurrence Score (RS) (n=81 luminal tumors) were explored. Results: Compared with controls, BC cases showed longer AGDAC (mean 85.0 vs 81.2 mm; p &lt;0.01) and shorter AGDAF (28.6 vs 29.8 mm; p =0.02). Across AGDAC quintiles, we observed an inverse risk gradient: lowest quintile vs highest, aOR 0.34 (95% CI 0.22–0.54; p &lt;0.001). The association was stronger in premenopausal women (Q1 vs Q5 aOR 0.31; 95% CI 0.16–0.59; p =0.001). AGD was not associated with tumor subtype (luminal A/B, HER2+, triple-negative) nor with genomic risk (RS&gt;25 vs ≤25). Conclusions: AGD, especially AGDAC, emerges as a non-invasive, inexpensive clinical marker of BC susceptibility, independent of molecular subtype and genomic risk. Findings suggest prenatal endocrine programming may prime lifetime BC risk, with a pronounced effect in hormonally active (premenopausal) women. If validated, AGD could enhance risk stratification and early detection pathways in population screening and prevention clinics. Odds ratio (OR) for cases of breast cancer controls according to quintiles of AGD measures, taking the fifth quintile as a reference. Breast cancer (n=422) vs. controls (n=417) AGD in quintiles(Median for each quintile) Cases Controls Odds Ratio a (95%CI) P- trend Odds Ratio b (95%CI) P- trend AGD AF 5 th (38.0 mm) 80 89 1.0 (reference) 1.0 (reference) 4 th (32.1 mm) 75 93 0.90 (0.58-1.4) 0.95 (0.61-1.5) 3 rd (28.5 mm) 84 80 1.2 (0.76-1.8) 1.5 (0.95-2.3) 2 nd (25.3 mm) 87 80 1.2 (0.76-1.8) 1.5 (0.95-2.3) 1 st (21.4 mm) 96 75 1.4 (0.93-2.2) 0.26 1.9 (1.3-3.1) 0.01 AGD AC 5 th (99.0 mm) 114 54 1.0 (reference) 1.0 (reference) 4 th (88.4 mm) 79 88 0.43 (0.27-0.66) 0.40 (0.26-0.63) 3 rd (82.6 mm) 82 87 0.45 (0.29-0.60) 0.42 (0.27-0.66) 2 nd (77.0 mm) 75 92 0.39 (0.25-0.60) 0.37 (0.23-0.58) 1 st (69.3 mm) 72 96 0.36 (0.23-0.55) &lt;0.001 0.34 (0.22-0.54) &lt;0.001 a Unadjusted OR. b OR adjusted by age and BMI. c OR adjusted by. AGDAF: Anogenital distance from the upper verge of the anus to the posterior fourchette AGDAC: Anogenital distance from the upper verge of the anus to the anterior clitoral surface.

Indefinite versus 2 years fixed duration of immune checkpoint inhibition in metastatic non–small cell lung cancer.

8590 Background: Clinical trials of immune checkpoint inhibitors (ICIs) in metastatic non-small cell lung cancer (mNSCLC) limited treatment duration to 2 years despite the absence of evidence defining the optimal time on therapy. In routine clinical practice, however, many patients receive ICIs for more than 2 years. We evaluated survival outcomes in patients treated with 2 years versus &gt; 2 years of therapy. Methods: We conducted a global, retrospective cohort study of patients with mNSCLC treated with ICIs for at least 2 years. Patients were classified as receiving fixed-duration ICI (discontinued at 2 years) or indefinite ICI therapy. Outcomes included progression-free survival (PFS), and overall survival (OS) from ICI start. Multivariable Cox regression, propensity score matching, and 2-year landmark analyses with inverse probability weighting (IPW) were used to address time-dependent biases and adjust for relevant covariates. Results: Among 889 patients who received at least 24 months of ICI therapy, median age was 65.5 years; 45.6% were women; 92.8% had a smoking history; 80.2% had adenocarcinoma histology; 70% of patients received ICI as first-line therapy and median PD-L1 tumor proportion score was 60%. Overall, 58.8% received indefinite ICI and 41.2% discontinued at 2 years. Median PFS and OS for the overall cohort were 5.7 years and 8.1 years, respectively. Baseline clinicopathologic characteristics, including age, sex, histology, PD-L1 expression, ECOG performance status, and smoking history, were well balanced between groups. Indefinite ICI therapy was associated with significantly longer PFS (HR 0.75, p &lt; 0.01) and OS (HR 0.62, p &lt; 0.001) compared to 2 years of therapy. These findings were consistent in a propensity-matched analyses (PFS HR 0.62, p &lt; 0.01; OS HR 0.60, p &lt; 0.001) and multivariable models (adjusted PFS HR 0.75, p = 0.02; adjusted OS HR 0.57, p &lt; 0.001). In 24-month landmark analyses with IPW, indefinite ICI remained associated with improved PFS (HR 0.74, p = 0.02) and OS (HR 0.56, p &lt; 0.001). Benefit with indefinite therapy was observed across all predefined subgroups, including age, sex, histology, PD-L1 strata, ECOG performance status, smoking history. Among 98 patients who received ICI rechallenge at disease progression, the objective response rate was 45%, with a median PFS of 12.9 months and a median OS of 30.2 months. Conclusions: Continuation of ICI therapy beyond 2 years was consistently associated with superior PFS and OS compared with treatment limited to 2 years across subgroups and sensitivity analyses. These findings highlight the limitations of arbitrary treatment caps in clinical trial design, support individualized duration decisions, and underscore the need for prospective trials to define the optimal duration of ICI therapy in NSCLC.

Predictive and prognostic value of MRI radiomics in patients with hormone-receptor–positive, HER2-negative breast cancer: A multicenter study.

e12559 Background: Treatment decisions for patients (pts) with early-stage hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC) routinely rely on the use of a genomic-based (21-gene) biomarker. Insufficient samples can preclude its use. We sought to evaluate whether a new breast MRI image-based artificial intelligence (AI) tool, with or without standard clinicopathologic (CP) factors, can (1) predict high 21-gene score (≥26) for guiding adjuvant chemotherapy and (2) prognosticate 5-year recurrence risk better than the 21-gene assay. Methods: In this multicenter, retrospective study, we built the MRI-based AI predictive/prognostic tool on a single-institution development cohort (DC), then validated its performance on an independent validation cohort (VC) comprised of three institutions. The AI tool used 1,688 MRI-derived radiomic features extracted from each pre-treatment breast MRI, with and without CP factors. The AI classification tool for predicting the high 21-gene score optimized discrimination between the binary endpoints of ≥26 versus &lt; 26 using elastic-net logistic regression with nested cross-validation. Discrimination ability was quantified by area under the receiver operating characteristic curve (AUC) with performance metrics and reported at a derived Youden threshold. We assessed prognostic performance of 5-year recurrence risk using the IPCW concordance index (C-index). Results: 1,277 pts (DC n = 516; VC n = 761) with HR+/HER2- BC diagnosed between January 2010 and December 2024 with pre-treatment breast MRI were included from four institutions. The Kaplan–Meier 5-year recurrence incidence was 9.6% (95% CI, 7.9%–11.7%). For predicting 21-gene score ≥26, combining MRI-derived radiomic features with CP predictors improved classification in the DC compared with CP predictors alone (AUC 0.81 vs 0.77) and increased balanced accuracy at the Youden operating point (0.76 vs 0.74), driven by higher sensitivity (0.78 vs 0.58) with similar specificity (0.78 vs 0.79). In the VC, the combined model also improved AUC (0.80 vs 0.78) and achieved higher balanced accuracy at the Youden threshold (0.72 vs 0.70), with sensitivity (0.76 vs 0.60) and specificity (0.69 vs 0.70), respectively. For prognostication, radiomic features demonstrated higher discrimination ability for 5-year recurrence risk than a model combining the 21-gene score with CP factors, improving the C-index from 0.62 to 0.71 in the DC (Δ = +0.09) and from 0.55 to 0.61 in VC (Δ = +0.06; p &lt; 0.0001). Conclusions: In early-stage HR+/HER2− BC, an AI tool comprised of MRI-based and CP features predicted high 21-gene score (≥26) (AUC 0.8), as well as prognosticated 5-year recurrence better than the 21-gene score combined with CP factors. Given the ubiquity of breast MRI, this tool may serve as a proxy for the 21-gene score when not available.

Real-world assessment of the impact of neighborhood vulnerabilities on prostate cancer outcomes in the Medstar Health Network.

e17140 Background: The disparities in prostate cancer (PC) treatment outcomes are thought to be multifactorial, resulting from complex interactions between social determinants of health (SDoH), disease biology, and healthcare-related factors. The impact of SDoH on PC mortality remains unclear. This study examines whether equal access to standard of care eliminates outcome disparities among men with advanced PC in the Medstar Health Network. Methods: This is a retrospective analysis of factors associated with treatment outcomes among men with advanced PC who received standard of care treatment in the Medstar Health Network from 2014-2025. Social Vulnerability Index (SVI) was used as a validated tool to quantify patients’ vulnerabilities. We compared age, disease stage at diagnosis, mortality between the highest (Q4) and lowest (Q1) vulnerability quartiles and between racial groups using chi-squared tests and t-tests. Results: We identified a cohort of 360 men diagnosed with PC which included 166 (46.1%) Black and 139 (38.6%) White patients. Median age was 73 years (IQR 66-80). Staging data were available for 281 patients, with 215 (78%) initially diagnosed with stage IV disease. SVI data were collected for 324 (90%) patients and Gleason scores were available for 239 (66.4%) patients. Median treatment follow-up was 26 months (IQR 10.8-53.7). A total of 116 patients (32.8%) died. SVI and outcomes: Significant differences were observed between Q1 and Q4 groups in stage IV diagnosis rates (Q4 areas 85% vs Q1 areas 64.7%, p = 0.012, OR = 3.21). However, mortality was equivalent between groups (32.1% vs 34.6%, p = 0.87) as was age at diagnosis (70.8 vs 72.3 years, p = 0.30). Race and Outcomes: Stage IV diagnosis rates were similar between Black and White patients (77.7% vs 72.3%, p = 0.41). However, Black patients were diagnosed significantly younger (mean age 70.3 vs 74.6 years, p = 0.0001), with a mean difference of 4.3 years. Mortality rates were comparable (33.3% vs 37.2%, p = 0.56). Black patients resided in significantly more disadvantaged areas (mean SVI 0.545 vs 0.316, p = 0.0001). Conclusions: Among patients treated at the Medstar Health Network, there were significant racial disparities in age at diagnosis, whereas patients in disadvantaged areas were more likely to be diagnosed with stage IV disease. However, no significant differences in mortality were observed by race or SVI. These findings suggest that equitable access to high-quality care may mitigate outcome disparities despite persistent contextual disadvantages. This dataset has limitations related to its retrospective nature and its limited sample size. However, these results are consistent with prior studies that demonstrate similar outcomes between populations when patients receive standard of care. This study adds rationale to promote health equity, ensuring broader access to screening and treatment to minority populations.

Prospective prostate cancer screening in germline pathogenic variant carriers: The PATROL study.

10505 Background: Germline pathogenic variants (gPV) in prostate cancer (PCa) risk genes are associated with aggressive disease, but optimal screening thresholds for this population are unclear. We report early results from the Prostate Cancer Screening for People at Genetic Risk for Aggressive Disease (PATROL) study. Methods: PATROL is a multicenter, prospective study enrolling participants ≥40 years with a gPV in at least one of 13 PCa risk genes. Biopsy is recommended using age-specific prostate-specific antigen (PSA) thresholds: &gt; 1.0 ng/mL (&lt; 50y), &gt; 1.5 (50–59y), &gt; 2.0 (≥60y). Prostate multiparametric MRI is encouraged at baseline and within 1 year of biopsy. Clinically significant PCa (csPCa) was defined as Grade Group (GG) ≥2 (NCT04472338). Results: As of 12/1/2025, 436 participants were enrolled; 69% carried BRCA1/2 gPVs ( BRCA2 46%, BRCA1 22%), 12% carried mismatch repair gene variants, and gPVs in other genes were each ≤7%. Overall, 106 participants underwent 119 on-study biopsies (median age 61 [IQR 53–68]) with a median PSA 2.3 ng/mL [IQR 1.3–3.9]). GG1 disease was detected in 21/119 (18%) biopsies and csPCa in 21/119 (18%) biopsies. Among csPCa, the median PSA was 3.2 ng/mL (IQR 2.2-4.1), and 76% (16/21) had a PIRADS 4-5 lesion. Fifteen (71%) and 14 (67%) of GG1 and csPCa, respectively, were identified in participants with BRCA1/2 gPVs. In multivariable logistic regression adjusting for age, PSA, and genetic status, PI-RADS 4-5 was associated with csPCa (OR 12.2, 95% CI 3.3-45.4). Of the 17 men with GG1 PCa, 11 (65%) elected active surveillance. Of the 11 men on surveillance, median follow up time was 19 months, with one (9%) upgraded to GG ≥2 and who underwent definitive treatment. In total, 25 participants underwent definitive treatment; 18 with initial diagnosis of csPCA, six GG1 who elected for definitive treatment and one enrollee with GG1 upgraded to GG ≥2. Of the 25 patients who elected definitive treatment, 88% (22/25) of underwent surgery, two underwent radiation, and one underwent focal therapy. Of surgery patients, there were no postoperative complications. At a median follow-up time of 16 months, all currently have undetectable PSA, and one patient required salvage radiation therapy. Conclusions: Age-specific PSA-driven biopsy in gPV carriers yielded ~20% csPCa detection, with two-thirds occurring at PSA &lt; 4 ng/mL (common biopsy threshold). MRI (PI-RADS 4–5) strongly predicted csPCa and may improve inherited-risk screening algorithms. With limited follow-up, surveillance of low-risk PCa among gPV carriers appears to be feasible, and definitive treatment of gPV carriers found with csPCa is effective. Clinical trial information: NCT04472338 .

Impact of concurrent tissue (TBx) and liquid (LBx)–based comprehensive genomic profiling (CGP) on biomarker detection and first-line (1L) treatment in metastatic CRC (mCRC).

e15619 Background: While biomarker testing to inform the use of anti-EGFR therapies in mCRC has long been a guideline-recommended practice, the growing number of approved targeted therapies heightens the importance of comprehensive biomarker testing to best inform 1L treatment. Methods: The US-based deidentified Flatiron Health-Foundation Medicine (FMI) CRC Clinico-Genomic Database (CGDB) was queried to assess the patterns of 1L biomarker ( KRAS , NRAS , and BRAF V600E) testing performed at FMI (FoundationOne CDx, FoundationOne Liquid CDx [F1LCDx]) and non-FMI central lab CGP providers for 1,270 patients (pts) diagnosed with mCRC between 9/2020-6/2025. TBx and LBx testing was classified as concurrent if both were ordered before either reported, reflex if a LBx was ordered before 1L and the TBx was ordered 1-60 days after the LBx report. Positive percent agreement (PPA) was assessed for LBx-based biomarker detection relative to TBx. For FMI samples, clonality was assessed with a method leveraging the variant allele frequency (VAF) and the copy number model to determine the allelic context and ctDNA tumor fraction (TF) was quantified using a combination of aneuploidy and VAF. Results: Of 1,270 mCRC pts with TBx and/or LBx-based biomarker testing prior to 1L, 146 (11%) had concurrent, 81 (6.4%) had reflex, 803 (63%) had TBx-only, and 240 (19%) had LBx-only testing. There were no significant differences in sex, age, socioeconomic status, CRC site, stage at diagnosis, ECOG, or MSI/dMMR status between cohorts, and LBx-first testing was more frequently at academic centers (21% vs. 5.7%, p &lt; 0.001) and in pts with non-European ancestry (34% vs 26%, p = 0.049). The highest rates of 1L biomarker positivity were observed in pts with TBx and LBx (concurrent or reflex, 64%) vs pts with TBx (61%, p = 0.36) or LBx-only (54%, p = 0.03) testing. In pts with F1LCDx, the PPA was 81% and increased to 95% in the subset with TF ≥ 1% (n = 70). Discordant TBx/LBx results, were partially due to subclonal variants missed by both LBx ( KRAS K117N [TBx VAF 0.7%]) and TBx testing ( KRAS A146V [LBx VAF 0.2%]). Overall, 352 (28%) pts received 1L informed by only a LBx report, representing 32% of concurrent (n = 46), 82% of reflex (n = 66), and 100% of LBx-only (n = 240) pts. In the subset of 255 pts with F1LCDx, 44 (17%) had TF &lt; 1%. In pts with 1L informed by both TBx and LBx results, concurrent ordering trended towards a faster time from first order to 1L compared to reflex (26 vs 31 days, p = 0.37). Conclusions: In this cohort, TBx and LBx-based testing was associated with higher rates of 1L biomarker detection, particularly compared to LBx-testing alone, including clonal drivers to inform 1L therapy selection and subclonal mutations with potential resistance implications. A concurrently ordered combined TBx and LBx profiling approach may be best suited for a timely, fully-informed 1L treatment decision.

Solar fields in farmlands, their impact on bat presence and activity

Bat populations are facing numerous challenges due to human activities, and the development of solar energy in agricultural landscapes may add to these issues. Effects of solar fields on bat populations are still poorly understood. In this study, we compared bat activity in six solar fields that each had two grassland controls (agricultural grassland and natural meadows). Using passive bat detectors, bat calls were recorded along the edges of these plots, where the highest bat species diversity and activity were expected. The effects of landscape composition and configuration on the diversity, presence, and activity of different bat species were evaluated for each plot type at yearly, seasonal, and monthly scales. All seven bat species studied were less active in the solar fields compared to the two grassland controls. Specifically, both the number of nights that bats were present and the activity of bats were reduced in solar fields. As the number of solar fields keeps increasing in the agricultural landscape, it is thus essential to monitor their effect on the population levels.

Electronic structure and defect properties of Bi-doped GaN: Origins of photoluminescence and optical absorption

Extreme lattice-mismatched III–V nitrides, such as Bi-incorporated GaN, have been realized experimentally thanks to recent advances in epitaxial growth and characterization techniques. However, theoretical insights into defect-related optical absorption and emission phenomena in these materials remain scarce. Here, we apply hybrid density functional theory to systematically explore the role of substitutional bismuth atoms on both cationic (BiGa) and anionic (BiN) sites in Bi-incorporated GaN, as well as their complexes with native vacancies. Our calculations reveal that the charge-compensated (BiN+VGa)3− and (BiN+VGa)3+ defect complexes stabilize anionic bismuth incorporation, accounting for the experimentally observed absorption peaks at 0.86 and 2.95 eV. We further uncover the origins of the reported band edge emissions near 2.0 and 2.5 eV by examining various charge states of BiGa and BiN centers. We further show that Bi-related defects introduce deep mid-gap states that can act as efficient non-radiative recombination centers, potentially explaining the experimentally observed suppression of photoluminescence. Our findings elucidate the defect-level physics of Bi-doped GaN and provide practical guidelines for controlling the incorporation of Bi into GaN.

Biologically synthesized silver nanoparticles for industrial dye degradation

Ion‐Replenishing Interlayer and Tailored Electrolyte Jointly Activate Four‐Electron Zinc–Iodine Batteries

ABSTRACT Activating four‐electron iodine chemistry in zinc–iodine (Zn–I 2 ) batteries promises higher energy density, yet remains challenged by polyiodide shuttling and the instability of high‐valence I + species. Here, we demonstrate that a customized NH 4 Cl‐based aqueous electrolyte, coupled with an ion‐replenishing Cl‐functionalized covalent organic framework (COF–Cl) interlayer, enables long‐lived four‐electron Zn–I 2 batteries. The optimized electrolyte promotes I + –Cl − complexation, while the COF–Cl interlayer immobilizes polyiodides and continuously releases Cl − to stabilize I + against hydrolysis, collectively ensuring reversible I − /I 0 /I + redox conversion. In situ spectroscopic and theoretical analyses reveal accelerated high‐valence redox kinetics and strong I + /polyiodide interactions. As a result, the optimized cell delivers high energy density (278 Wh kg − 1 ), fast kinetics (128 mAh g − 1 at 10 A g − 1 ), and remarkable cycling durability over 45000 cycles at –5°C with an ultralow decay rate of 0.00039% per cycle, with the strategy further validated in pouch cells under low‐temperature conditions. This work establishes an effective ion‐replenishing interlayer–electrolyte strategy for robust, high‐energy aqueous Zn–I 2 batteries.

A novel hybrid control framework for frequency regulation in RES and EV-enriched power grids of Delhi power distribution utility

Abstract The depletion of fossil fuels and the rising demand for electricity are driving the global shift toward renewable energy sources (RES). The primary goal of incorporating RES into the conventional smart grid is to establish a more ecological and eco-friendly energy system. However, due to their lower system inertia, RESs struggle to effectively respond to fluctuations in load demand. This study investigates how a Dual Loop LADRC-FOPIDN-(1 + TD) controller can improve frequency regulation in a multi-area deregulated electricity system while taking RES’s intermittent nature into account. By integrating LADRC with a cascade controller, the proposed approach delivers improved transient performance over selected benchmark controllers (LADRC, FOPIDN, FOPIDN-(1 + TD)) under the tested scenarios. Furthermore, an enhanced Quasi Opposition Arithmetic Optimization Algorithm (QOAOA) is employed to optimize controller parameters for improved efficiency. Simulation results highlight its strong adaptability to specific uncertainties modeled in this study, such as RES intermittency, load fluctuations, and delay effects, ensuring grid stability. Moreover, this study addresses the use of electric vehicles (EVs) to regulate frequencies in a hybrid power system under the conditions of real-time load demand variations. Plug-in Electric Vehicles (PEVs) are incorporated in every system region as a measure to reduce undesirable transient components on load frequency and power sharing. PEVs absorb unnecessary electrical energy and give it back to the grid when needed, which offers useful grid support, particularly within RES-dominated networks. The proposed controller is tested on a better IEEE-39 bus system with real-time load variation and variability of RES, through data provided by BSES Rajdhani Power Limited (BRPL), Delhi. Lastly, OPAL-RT hardware is used to run a real-time simulation environment, which targets the integration of real hardware with a virtual test environment, to test the effectiveness and the robustness of the controller. Finally, the MATLAB simulation results are compared with OPAL-RT hardware results.

Phosphate release from myosin Va occurs after the initial powerstroke but before the secondary powerstroke associated with ADP-release

Impact of NCCN-guided training on large language model performance in mNSCLC.

8535 Background: Publicly available large language models (LLMs) such as ChatGPT may support clinical decision-making in precision oncology by rapidly synthesizing complex information. We previously evaluated ChatGPT’s ability to generate NCCN-concordant first-line (1L) treatment recommendations for metastatic non-small cell lung cancer (mNSCLC) using a novel Generative AI Performance Score (G-PS). We evaluated whether NCCN-guideline–based training improves LLM treatment recommendations across multiple lines of therapy and targetable genotypes in metastatic NSCLC. Methods: NCCN Guidelines (v3.2025) were reviewed and eight driver alterations with FDA-approved therapies were selected: EGFR Ex19del, BRAF V600E, ALK fusion, KRAS G12C, NTRK1/2/3 fusion, ROS1 fusion, RET fusion, and MET exon 14 skipping. Standardized prompts requesting 1L, second-line (2L), and third-line (3L) recommendations were generated and run through ChatGPT-5.2. Prompts included information on patient demographics, disease stage, and prior therapy where appropriate. Each scenario was repeated five times per line of treatment (N = 15 per mutation). In trained sessions, the LLM was explicitly instructed to defer to an uploaded PDF copy of the NCCN guidelines prior to generating recommendations. Responses were scored using the G-PS, which quantifies guideline concordance on a continuous scale from -1 (all hallucinations) to 1 (all correct answers) based on alignment with NCCN-recommended therapies. Additionally, we calculated ratios for the mean trained G-PS and untrained G-PS across groups, to estimate the relative fold change effect of training on ChatGPT performance (called the “Training Ratio”). Results: A total of 240 prompts were analyzed (120 untrained, 120 trained). NCCN-guided training significantly improved overall LLM guideline concordance (mean G-PS 0.462 vs 0.313, p = 0.049) and reduced irrelevant recommendations (mean irrelevant rate of 23.7% vs 39.8%, p &lt; 0.001) but did not significantly affect the rate of hallucinations (10.4% vs 8.1%, p = 0.297). 1L responses demonstrated significantly higher mean G-PS than 2L (p &lt; 0.001) or 3L (p &lt; 0.001) for both trained and untrained sessions. Training also significantly improved the mean G-PS of 1L responses compared to untrained responses (0.902 vs 0.647, p &lt; 0.001) but not in 2L or 3L. The overall Training Ratio was 1.48, with the greatest Training Ratio seen in EGFR Ex19del and ALK fusion ( &gt; 4) and the poorest in NTRK fusions (0.53). Conclusions: While guideline-based training improves ChatGPT’s overall performance and reduces irrelevant outputs, recommendation quality declines substantially beyond the first line of therapy and shows marked variability by mutation. These findings highlight important limitations of LLMs in complex oncology decision-making and reinforce that clinicians must independently verify recommendations against established guidelines.