Citations

Abstract Approximately two-thirds of hypopharyngeal squamous cell carcinoma (HPSCC) are diagnosed in advanced stage, with the worst prognosis among head and neck squamous cell carcinomas (HNSCCs). Identifying biomarkers for high-risk patients who need aggressive treatment is crucial. We present mutational, transcriptomic and proteomic studies of 103 Chinese HPSCC patients, observing a higher prevalence and poorer prognosis in males comparing to females. Genes in estrogen response pathways are up-regulated and proteins phosphorylated by protein kinase C (PKC) and Cyclin-dependent kinases (CDKs) are aberrantly regulated. We identify aberrant copy number regions including SOX2 (3q26.33), FGFR (8p11.23), CCND1 (11q13.3), CDKN2A/2B (9p21.3), and MYC (8q24.21). HPV status combined with highly mutated genes as predictive markers was assessed, including SYNE1 in HPV(-), MUC4 in HPV(+) patients. We confirm the presence of four known gene expression (GE) subtypes of HNSCC in our HPSCC cohort and present the genomic alterations, patient characteristics and survival status of each subtype. A predictive model involving clinical factors and transcriptomic expression of six genes was established and cross-site validated. The findings open new opportunities for stratifying high-risk patients and molecular targets for novel therapeutic strategies. Citation Format: Yanxin Ren, Wei Xiong, Chun Feng, Dan Yu, Xiaoyan Wang, Qing Yang, Siting Yu, Hongjiang Zhang, Bangyun Huo, Honglu Jiang, Zuli Li, Junlin Wang, Yu-Xiong Su, Ping Yang, Yong Liao, Qi Zhong, Junwen Wang. Multi-omics insights into the molecular signature and prognosis of hypopharyngeal squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4999.

ImportanceThe safety and effectiveness of combining surgical peripheral iridectomy (SPI) with goniosynechialysis (GSL) and goniotomy (GT) vs trabeculectomy for intraocular pressure (IOP) reduction remains unknown.ObjectiveTo investigate the safety and effectiveness at 1 year of SPI + GSL + GT vs trabeculectomy in advanced primary angle-closure glaucoma (PACG) without cataract.Design, Setting, and ParticipantsThis noninferiority randomized clinical trial was conducted at 8 tertiary eye centers in China. A total of 88 Chinese patients (88 eyes) with advanced PACG without cataract were enrolled from January 2022 to July 2023. Data were analyzed from August 2024 to September 2024. Mean (SD) patient age was 60.3 (7.3) years, and 52 patients (59.1%) were female. Forty-three patients were randomized to SPI + GSL + GT and 45 were randomized to trabeculectomy; 86 patients (97.7%) completed the 12-month follow-up.InterventionsParticipants were randomized 1:1 to receive SPI + GSL + GT or trabeculectomy.Main Outcomes and MeasuresThe primary outcome was IOP at 12 months (noninferior margin: 4 mm Hg). Secondary outcomes included surgical success (IOP: 5-18 mm Hg, ≥20% reduction from baseline, with or without antiglaucoma medications); postoperative complications and interventions, including bleb massage, suture lysis, or releasable sutures; and number of antiglaucomatous medications prescribed.ResultsAt 12 months, the SPI + GSL + GT group had a mean (SD) IOP of 15.6 (4.0) mm Hg vs 14.9 (4.2) mm Hg in the trabeculectomy group (difference, 0.5 mm Hg; 95% CI, −1.2 to 2.2; P = .55), which was within the 4-mm Hg noninferiority margin. Qualified success rates were 38 of 43 participants (88.4%) for SPI + GSL + GT and 42 of 45 participants (93.3%) for trabeculectomy (difference, −5.0%; 95% CI, −19.6% to 8.5%; P = .48). However, complete success rates were lower in the SPI + GSL + GT group (26 participants [60.5%]) vs the trabeculectomy group (37 participants [82.2%]; difference, −21.8%; 95% CI, −40.2% to −2.4%; P = .03). Postoperative complications were present for 8 participants (18.6%) in the SPI + GSL + GT group vs 9 participants (20.0%) in the trabeculectomy group (difference, −1.4%; 95% CI, −17.9% to 15.1%; P = .71). Postoperative interventions were lower in the SPI + GSL + GT group (3 participants [7.0%] vs 25 participants [55.6%]; difference, 48.6%; 95% CI, 32.2%-65.0%; P < .001). Median (IQR) numbers of medications used decreased from 2 (0-3) to 0 (0-1) in the SPI + GSL + GT group and from 2 (2-3) to 0 (0-0) in the trabeculectomy group (difference, −0.81; 95% CI, −1.36 to −0.26; P = .004).Conclusions and RelevanceIn this randomized clinical trial among patients with advanced PACG without cataract, SPI + GSL + GT demonstrated noninferiority (4-mm Hg margin) to trabeculectomy for IOP at 12 months, with fewer interventions (including bleb massage, suture lysis, or releasable sutures) but no difference in postoperative medication use. This suggests SPI + GSL + GT as a potential alternative to trabeculectomy for similar cases, pending validation in larger sample sizes with smaller noninferiority margins.Trial RegistrationClinicalTrials.gov Identifier: NCT05163951

Abstract Background The Global Leadership Initiative on Malnutrition (GLIM) introduced an approach for malnutrition diagnosis in 2019 that comprised screening followed by assessment of three phenotypic criteria (weight loss, low body mass index [BMI], and low muscle mass) and two etiologic criteria (reduced food intake/assimilation and inflammation/disease burden). This planned update reconsiders the GLIM framework based on published knowledge and experience over the past 5 years. Methods A working group ( n = 43 members) conducted a literature search spanning 2019–2024 using the keywords “Global Leadership Initiative on Malnutrition or GLIM.” Prior GLIM guidance activities for using the criteria on muscle mass and inflammation were reviewed. Successive rounds of revision and review were used to achieve consensus. Results More than 400 scientific reports were published in peer‐reviewed journals, forming the basis of 10 systematic reviews, some including meta‐analyses of GLIM validity that indicate strong construct and predictive validity. Limitations and future priorities are discussed. Working group findings suggest that assessment of low muscle mass should be guided by experience and available technological resources. Clinical judgment may suffice to evaluate the inflammation/disease burden etiologic criterion. No revisions of the weight loss, low BMI, or reduced food intake/assimilation criteria are suggested. After two rounds of review and revision, the working group secured 100% agreement with the conclusions reported in the 5‐year update. Conclusion Ongoing initiatives target priorities that include malnutrition risk screening procedures, GLIM adaptation to the intensive care setting, assessment in support of the reduced food intake/assimilation criterion, and determination of malnutrition in obesity.

Abstract Hereditary tumor predisposition syndromes pose a challenge for early detection and timely treatment of tumors. In von Hippel–Lindau disease, desirable personalized surveillance programs are lacking due to insufficient data on genotype-specific risk profiles of individual mutations. To describe neoplastic risk profiles for carriers of pathogenic and likely pathogenic VHL germline mutations, our observational study recruited 1,350 participants from 40 centers worldwide. 432 different VHL germline mutations were observed, with p.Asn78Ser, p.Arg161Ter, p.Arg161Gln, p.Arg167Gln, p.Arg167Trp and p.Tyr98His being the six most frequent, occurring in a total of 493 carriers (36.5%) and in ≥30 patients each. Age-related penetrance risks for retinal hemangioblastoma, central nervous system hemangioblastoma, renal cell carcinoma, pancreatic neuroendocrine tumors and pheochromocytoma/paraganglioma in carriers of the most frequent VHL mutations were assessed. In addition, the number of organs affected, the frequency of surgery and the outcome are reported. Pairwise comparisons of the age-dependent tumor penetrance of these six mutations showed that 47 out of 90 pairs were significantly different. The most significant associations were found in p.Tyr98His (n = 19), followed by p.Arg161Ter (n = 10). All pairwise comparisons of mutations affecting different codons showed at least one significant (P < 0.05) difference, except for p.Asn78Ser vs p.Arg161Ter. Thus, tumor risk varied by VHL mutation type and location, but did not differ between the truncating mutation p.Arg161Ter and the missense mutation p.Asn78Ser. Our study demonstrates the importance of mutation-specific phenotype prediction. With appropriate validation, the data have important implications for risk assessment and decision making in tumor prevention for carriers of the respective VHL mutations.

AbstractBackgroundThe 17q21.31 region with various structural forms characterized by the H1/H2 haplotypes and three large copy number variations (CNVs) represents the strongest risk locus in progressive supranuclear palsy (PSP).ObjectiveTo investigate the association between CNVs and structural forms on 17q.21.31 with the risk of PSP.MethodsUtilizing whole genome sequencing data from 1684 PSP cases and 2392 controls, the three large CNVs (α, β, and γ) and structural forms within 17q21.31 were identified and analyzed for their association with PSP.ResultsWe found that the copy number of γ was associated with increased PSP risk (odds ratio [OR] = 1.10, P = 0.0018). From H1β1γ1 (OR = 1.21) and H1β2γ1 (OR = 1.24) to H1β1γ4 (OR = 1.57), structural forms of H1 with additional copies of γ displayed a higher risk for PSP. The frequency of the risk sub‐haplotype H1c rises from 1% in individuals with two γ copies to 88% in those with eight copies. Additionally, γ duplication up‐regulates expression of ARL17B, LRRC37A/LRRC37A2, and NSFP1, while down‐regulating KANSL1. Single‐nucleus RNA‐seq of the dorsolateral prefrontal cortex analysis reveals γ duplication primarily up‐regulates LRRC37A/LRRC37A2 in neuronal cells.ConclusionsThe copy number of γ is associated with the risk of PSP after adjusting for H1/H2, indicating that the complex structure at 17q21.31 is an important consideration when evaluating the genetic risk of PSP. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Abstract Objective The fast accumulation of vast pharmacogenomics data of cancer cell lines provide unprecedented opportunities for drug sensitivity prediction (DSP), a crucial prerequisite for the advancement of precision oncology. Recently, Generative Large Language Models (LLM) have demonstrated performance and generalization prowess across diverse tasks in the field of natural language processing (NLP). However, the structured format of the pharmacogenomics data poses challenge for the utility of LLM in DSP. Therefore, the objective of this study is multi-fold: to adapt prompt engineering for structured pharmacogenomics data toward optimizing LLM’s DSP performance, to evaluate LLM’s generalization in real-world DSP scenarios, and to compare LLM’s DSP performance against that of state-of-the-science baselines. Methods We systematically investigated the capability of the Generative Pre-trained Transformer (GPT) as a DSP model on four publicly available benchmark pharmacogenomics datasets, which are stratified by five cancer tissue types of cell lines and encompass both oncology and non-oncology drugs. Essentially, the predictive landscape of GPT is assessed for effectiveness on the DSP task via four learning paradigms: zero-shot learning, few-shot learning, fine-tuning and clustering pretrained embeddings. To facilitate GPT in seamlessly processing the structured pharmacogenomics data, domain-specific novel prompt engineering is employed by implementing three prompt templates (i.e., Instruction, Instruction-Prefix, Cloze) and integrating pharmacogenomics-related features into the prompt. We validated GPT’s performance in diverse real-world DSP scenarios: cross-tissue generalization, blind tests, and analyses of drug-pathway associations and top sensitive/resistant cell lines. Furthermore, we conducted a comparative evaluation of GPT against multiple Transformer-based pretrained models and existing DSP baselines. Results Extensive experiments on the pharmacogenomics datasets across the five tissue cohorts demonstrate that fine-tuning GPT yields the best DSP performance (28% F1 increase, p-value= 0.0003) followed by clustering pretrained GPT embeddings (26% F1 increase, p-value= 0.0005), outperforming GPT in-context learning (i.e., few-shot). However, GPT in the zero-shot setting had a big F1 gap, resulting in the worst performance. Within the scope of prompt engineering, performance enhancement was achieved by directly instructing GPT about the DSP task and resorting to a concise context format (i.e., instruction-prefix), leading to F1 performance gain of 22% (p-value=0.02); while incorporation of drug-cell line prompt context derived from genomics and/or molecular features further boosted F1 score by 2%. Compared to state-of-the-science DSP baselines, GPT significantly asserted superior mean F1 performance (16% gain, p-value<0.05) on the GDSC dataset. In the crosstissue analysis, GPT showcased comparable generalizability to the within-tissue performances on the GDSC and PRISM datasets, while statistically significant F1 performance improvements on the CCLE (8%, p-value=0.001) and DrugComb (19%, p-value=0.009) datasets. Evaluation on the challenging blind tests suggests GPT’s competitiveness on the CCLE and DrugComb datasets compared to random splitting. Furthermore, analyses of the drug-pathway associations and log probabilities provided valuable insights that align with previous DSP findings. Conclusion The diverse experiment setups and in-depth analysis underscore the importance of generative LLM, such as GPT, as a viable in silico approach to guide precision oncology. Availability https://github.com/bioIKEA/SensitiveCancerGPT

Migraine with aura(MwA) is associated with an increased risk of stroke and adverse vascular outcomes compared to those with migraine without aura (MwoA). AI-ECG prediction models developed at our institution can evaluate the probability of atrial fibrillation (AF) and estimate a patient’s age based on a normal sinus rhythm (NSR) ECG. Delta age, AI-ECG estimated age minus chronological age, indicates endothelial dysfunction and is associated with cardiovascular mortality. We aim to assess how AI-ECG prediction model outputs, specifically the AF probability and delta age, are associated with adverse vascular outcomes in patients with migraine. Adult patients diagnosed with MwA and MwoA from 2000-2020 with at least one digital, standard 12-lead ECG were identified. The first ECG that showed NSR is used as the index ECG. Patients with any adverse vascular outcomes before the index ECG were excluded. Adverse vascular outcomes used as endpoints include acute ischemic stroke, acute myocardial infarction, deep vein thrombosis/pulmonary embolism, AF, and carotid artery dissection. A total of 31301 patients (13783 MwA, 17518 MwoA) were included in our analysis. The mean age at the time of the index ECG was 44.3 (14.5), and the average follow-up time was 71.6 (69.8) months. Based on the index ECG, the mean AF probability was significantly higher in MwA compared to MwoA (2.39 vs 2.06, p< 0.001), while the delta age was lower in MwA compared to MwoA (3.7 vs 4.2, p <.001). The prevalences of all vascular outcomes are summarized in Table 1. Multivariate Cox regression models showed that a higher AF prediction model output (every 10% increase), as well as a higher delta age (every 10-year increase), are associated with an increased risk of composite vascular outcomes (HR1.20, 95%CI 1.17-1.23, p<.001, and HR1.19, 95%CI 1.14-1.23, p < .001) [Table 2]. The Kaplan-Meier curve of adverse vascular outcome-free survival by AF prediction model output, using 1% as the cutoff (HR 1.49, 95% CI 1.41, 1.57, p<.001), and by delta age, using 2-year as the cutoff (HR 1.14, 95% CI 1.08, 1.21, p <. 001) are presented in Figure 1. Having aura, older age, male, coronary artery disease, congestive heart failure, diabetes, hypertension, and tobacco use were also associated with a higher risk of adverse vascular outcomes. Our results demonstrated the potential of using AI-ECG AF prediction model output and delta age to identify migraine patients at risk for adverse vascular outcomes.