Citations

Abstract The CoMMpass study (NCT01454297) is a prospective, longitudinal observational study involving 1,141 newly diagnosed multiple myeloma (NDMM) patients. Bone marrow aspirates from the study participants were collected for comprehensive molecular characterization of tumor (using bulk RNA sequencing and whole genome sequencing) and tumor immune microenvironment using 3’ single-cell RNA sequencing (scRNA-seq). To support exploration of this rich multi-omic dataset, we developed CoMMpass Explorer (CE), an intuitive interactive platform that enables real-time analysis of clinical and genomic data from CoMMpass. A central feature of CE is cohort building, where users can filter and stratify patients by clinical, genomic, and survival data elements to create custom cohorts for analysis. CE provides five main views: Overall Summary for clinical feature distribution, Kaplan-Meier curves, and multivariate Cox proportional hazards models; Mutational Profile for visualizing and comparing somatic mutations; Tumor Profile for bulk differential expression and gene set enrichment; Immune Microenvironment for comparing cell type abundance and cell cycle dynamics between cohorts using scRNA-seq data; and Pseudo-Bulk, which aggregates single-cell expression by cell type to enable cohort-level comparisons of transcriptional programs using DEseq2. CE reproduces prior CoMMpass studies, including WEE1 expression being associated with poorer progression-free survival (Simhal, et al.) and different mutation frequencies between African American and European American patients (Manojlovic, et al.). We further demonstrate CE’s utility by interrogating the 2025 Consensus Genomic Staging (CGS) risk classification system (Avet-Loiseau, et al). We compared CGS high-risk (HR, n=249) vs. CGS standard-risk (SR, n=573) patients. HR patients have significantly worse progression-free survival, overall survival, and time to second-line therapy compared with SR patients. Univariate models recapitulated expected differences in the clinical features that define CGS risk. Bulk tumor RNA-seq and ssGSEA highlighted a more proliferative and genomically unstable transcriptional program in HR group, with upregulation of angiogenesis and cell-cycle-related pathways. In the immune microenvironment, monocytes were more abundant in the SR group. Pseudo-bulk RNA-seq of plasma cells showed overexpression of ANXA1, NSD2, IGF1R, MAF and related genes in HR. CE democratizes access to the CoMMpass multi-omic resource, allowing researchers to interrogate clinical and molecular heterogeneity. By enabling hypothesis generation and replication of published results, CE serves as a valuable tool for identifying prognostic biomarkers and meaningful patterns in gene expression, mutation profiles, and the immune microenvironment. Citation Format: Wanxing Zhang, Chaitanya R. Acharya, Steven M. Foltz, David E. Avigan, Samir Parekh, Ravi Vij, Shaji Kunnathu Kumar, Taxiarchis Kourelis, Sagar Lonial, Hearn Cho, Ioannis S. Vlachos, Sacha Gnjatic, Li Ding, Manoj Bhasin, George Mulligan. CoMMpass Explorer: An interactive platform to explore clinical and genomic data from newly diagnosed multiple myeloma patients from the landmark CoMMpass observational study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5504.

Abstract Background: Chronic inflammation is implicated in ovarian carcinogenesis, but how different inflammation-related exposures individually or jointly affect histotype-specific associations remains unclear. Materials and Methods: We pooled data from 16 case-control studies in the Ovarian Cancer Association Consortium to evaluate associations of eight inflammation-related factors (anti-inflammatory: aspirin use, tubal ligation (TL); pro-inflammatory: endometriosis, obesity, lifetime ovulatory cycles (LOC), smoking, pelvic inflammatory disease (PID), polycystic ovary syndrome (PCOS)) with epithelial ovarian cancer (OvC) by histologic subtype. We examined individual associations and clustering of risk factors across histotypes and computed population attributable risk (PAR) for each factor. We assessed additive and multiplicative interactions for exposure combinations. Results: Associations with OvC risk differed by histotype (e.g., high-grade serous: aspirin: OR=0.90; 95%CI 0.82, 0.99; TL: OR=0.80; 95%CI 0.73, 0.88; overall serous: endometriosis: OR=1.17; 95%CI 1.03, 1.31; high LOC: OR=1.42; 95%CI 1.28, 1.58; obesity (low-grade serous): OR=1.50; 95%CI 1.14, 1.98). Clustering analyses showed highly correlated risk profiles in endometrioid and clear cell (r=0.91). High-grade serous and mucinous profiles were moderately correlated with endometrioid and clear cell (r=0.60) tumors. The profile for low-grade serous (r=0.36) tumors was distinct from other histotypes. PAR estimates suggested modifying aspirin use, TL, and LOCs could substantially reduce burdens of endometrioid, clear cell and mucinous tumors. Out of 28 exposure combinations tested in overall OvC and 189 by histotype, we observed 12 interactions. Not using aspirin regularly showed positive additive interactions with obesity and high LOCs, particularly in endometrioid tumors (obesity relative excess risk due to interaction (RERI)=0.74, 95%CI 0.31, 1.18; Pint=0.001 for; LOCs RERI=0.80, 95%CI 0.03, 1.56; Pint=0.04). Not using aspirin regularly also showed a positive additive interaction with endometriosis in clear cell tumors (RERI=1.77, 95%CI 0.03, 3.52; Pint=0.05). Lack of TL showed positive interactions with obesity in endometrioid (RERI=0.86, 95%CI 0.17, 1.53; Pint=0.01) and mucinous (RERI=1.10, 95%CI 0.23, 1.97; Pint=0.01) tumors, while negative additive interactions were observed for smoking and endometriosis in endometrioid tumors (RERI=-1.12, 95%CI -2.19, -0.05; Pint=0.04). A multiplicative interaction was observed between obesity and endometriosis in mucinous tumors (Pint=0.01). Conclusion: The findings suggest ovarian tumorigenesis is strongly shaped by pro- and anti-inflammatory pathways that act largely independently. Further examining these pathways may clarify the origins of histotype heterogeneity and guide prevention strategies. Citation Format: Maxwell Akonde, Britton Trabert, SHELLEY TWOROGER, Allan Jensen, Kathryn L. Terry, Joshua Sampson, Hoda Anton-Culver, David Bowtell, Elisa V. Bandera, Angela Brooks-Wilson, Andrew Berchuck, Daniel William Cramer, Linda S. Cook, Julie M. Cunningham, Jennifer A. Doherty, Ellen L. Goode, Marc T. Goodman, Holly Ruth Harris, Susanne K. Kjaer, Nhu Le, Alice Wen-Ron Lee, Francesmary Modugno, Kirsten B. Moysich, Celeste Pearce, Malcolm C. Pike, Harvey A. Risch, Mary A. Rossing, Joellen M. Schildkrau, Daniel O. Stram, Rebecca Sutphen, David Van Den Berg, Penelope M. Webb, Anna Wu, Argyrios Ziogas, Nicolas A. Wentzensen. Inflammation-related exposures and histotype- specific ovarian cancer risk in the Ovarian Cancer Association Consortium (OCAC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6261.

Abstract Introduction: Pathological complete response (pCR) is a strong prognostic marker, but survival outcomes comparing treatment to control do not reliably align with treatment-control differences in pCR rates in breast cancer. A novel Bayesian hierarchical framework models treatments within trials, allowing us to predict treatment effects on distant recurrence-free survival (DRFS) from pCR with greater accuracy. Methods: We analyzed 12 neoadjuvant breast cancer trials (6,000 patients, all HR/HER2 subtypes; including I-SPY2). The framework of Burzykowski, Molenberghs & Buyse (2005) is extended to a novel arm-based hierarchical structure providing a distribution of pCR and DRFS treatment effects controlling for subtype (HR/HER2), N and T stage, grade, and calendar year. Three held-out trials (877 patients; 26 regimens; med follow-up >4 years) validate predictions of DRFS treatment benefit from pCR. All data was used to estimate treatment-effect correlation and the surrogate threshold effect (STE). Analyses were repeated for Residual Cancer Burden Index (binary RCB01, continuous RCB). Results: Predicted probability of DRFS benefit closely matched actual DRFS follow-up (mean absolute error 0.06; Pearson r = 0.9). Across all trials, pCR showed moderate surrogacy (ρ = 0.82, R2 = 0.67). A 60% increase in pCR odds achieves ≥95% probability of DRFS benefit (STE = OR of 1.60). RCB outperforms pCR across all metrics, with 92% sensitivity and 93% specificity for detecting DRFS benefit in 26 validation regimens (Table 1). Conclusion: This novel Bayesian meta-analytic framework reveals that pCR, RCB01 and continuous RCB reliably predict survival benefit across heterogeneous trials, with RCB performing the best in an external validation. This provides a statistical foundation for accelerated approval decisions using robust early biomarkers in modern neoadjuvant trial designs by accurately predicting survival at the treatment arm level. Citation Format: Keli S. Santos-Parker, Jessica R. Santos-Parker, W. Fraser Symmans, Laura J. Esserman, Christina Yau, Angie DeMichele, Laura van't Veer, Doug Yee, Fabien Reyal, Helena Earl, Jean Abraham, David Cameron, Peter Hall, Judy Boughey, Matthew Goetz, Gabe Sonke, Miguel Martín, Sara López-Tarruella, Priyanka Sharma, Rachel Freiberg, Jane Perlmutter, Aditya Bardia, Martin Eklund, Rachel Freiberg, Lajos Pusztai. A novel statistical framework for surrogate endpoint prediction of survival in neoadjuvant breast cancer trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1401.

Abstract Background: Liquid biopsy approaches for cancer detection often rely on tissue-specific methylation or fragmentation features to infer tumor origin. However, a pan-aerodigestive cancer detection strategy is clinically valuable given shared risk exposures, field cancerization, and frequent diagnostic ambiguity among lung, esophageal, and head & neck cancers. We hypothesized that advanced-stage disease exhibits convergent chromatin remodeling, producing a dominant malignancy-associated fragmentomic signal that supersedes subtler tissue-of-origin patterns. Methods: Whole-genome EM-seq (∼15×) was performed on plasma cfDNA from 120 patients with stage III/IV aerodigestive cancers (lung, esophageal, head & neck; squamous and adenocarcinoma) and 60 age-matched controls. Four fragmentomic modalities were assessed: (1) genome-wide fragmentation in 5-Mb bins (DELFI-like), (2) NMF spectral components, (3) 4-mer end motifs, and (4) promoter-centric nucleosome scores (Griffin). All preprocessing occurred strictly within each training fold of a repeated stratified 10-fold CV (100 repeats) to prevent data leakage. No test-sample information was used in training. Hyperparameters were tuned only within training partitions. Random Forest classifiers were trained under this fully nested scheme. Results: The multimodal classifier robustly detected advanced aerodigestive malignancies with a mean AUROC 0.86 and AUPRC 0.94. However, modality dissection revealed a clear performance hierarchy: nucleosome positioning (Griffin) alone achieved AUROC 0.85 and AUPRC 0.93, nearly matching the full integrated model, whereas end motifs performed poorly (AUROC 0.61). Biological interpretation demonstrated prominent nucleosome depletion centered at promoters of proliferation-associated genes, indicating a convergent epigenetic state of promoter opening across late-stage aerodigestive malignancies. Conclusions: Advanced aerodigestive cancers exhibit a dominant, convergent chromatin remodeling signature detectable in plasma cfDNA, driven primarily by altered nucleosome positioning. In late-stage disease, this shared malignancy-associated fragmentomic signal outweighs tissue-of-origin-dependent patterns. These findings highlight the utility of nucleosome-based fragmentomics not merely for detection, but for resolving diagnostic ambiguity in patients with indeterminate masses and for monitoring total tumor burden in high-risk aerodigestive malignancies. Citation Format: Axel Misael Hidalgo, Ayesha Hashmi, Jeff Szymanski, Pradeep Chauhan, Lilli Greiner, Faridi Qaium, Daniel J. Ma, David M. Routman, Katie M. Van Abel, Aadel A. Chaudhuri.. Convergent chromatin remodeling enables pan-aerodigestive detection of advanced malignancies in plasma cfDNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3862.

Abstract Background: Multiple myeloma is the second most common adult blood cancer and remains incurable, despite recent advances. The IMWG/IMS recently published updated risk criteria, Consensus Genomic Staging (CGS), combining genomic events with clinical measures to identify high-risk patients (Avet-Loiseau, et al. JCO 2025). We applied CGS risk criteria to baseline samples from the Multiple Myeloma Research Foundation CoMMpass Study (NCT01454297), a prospective, longitudinal observational study that enrolled more than1100 participants between 2011-2017. Methods: We assessed patient risk following CGS criteria. Criteria 1: del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation. Criteria 2: an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32). Criteria 3: monoallelic del(1p32) along with 1q+ or biallelic del(1p32). Criteria 4: beta-2 microglobulin >= 5.5 mg/L with normal creatinine. Patients meeting one or more criteria were classified as High Risk. To test if risk showed association with genetic ancestry, we grouped patients into those with high African genetic ancestry and those with low African genetic ancestry. Genetic ancestry was measured using ADMIXTURE in comparison to 1000 Genomes. Results: We evaluated the CGS risk status of 877 CoMMpass patients, finding 69.2% (573/828) to be Standard Risk (SR) and 30.8% (255/828) to be High Risk (HR). HR patients showed worse progression-free survival (median PFS 26.3 months vs. 42.5 months; log rank test, p < 0.0001) and overall survival (median OS 63.9 months vs. median not reached; p < 0.0001). 10.6% (91/858) of patients met Criteria 1, 10.7% (93/873) met Criteria 2, 5.6% (49/877) met Criteria 3, and 8.7% (73/835) met Criteria 4. We found 14.2% (123/867) of patients to have high African-like genetic ancestry (AFR-high) and 85.8% (744/867) to have low African-like genetic ancestry (AFR-low). We observed significantly fewer HR patients within the AFR-high group (20%, 23/115) than in the AFR-low group (32.4%, 231/712) (Fisher’s exact test, p = 0.0065). The AFR-high group met HR criteria at a lower rate across all criteria, but only with Criteria 3 was the difference significant (p-value = 0.03). Higher levels of creatinine in AFR-high patients may have impacted meeting the normal creatinine requirement of Criteria 4. Conclusions: HR patients comprise 30.8% of CoMMpass subjects and show significantly worse PFS and OS than SR patients. AFR-high patients met HR criteria at a lower rate than AFR-low patients according to the CGS criteria. Clinical trials that utilize CGS criteria to determine patient eligibility may be challenged to enroll a representative patient population, including AFR-high patients. Screening and eligibility criteria should be carefully considered to mitigate potential enrollment disparities. Citation Format: Steven M. Foltz, Chaitanya R. Acharya, Alexander Gout, Yuxin Jin, David E. Avigan, Ravi Vij, Shaji Kunnathu Kumar, Sagar Lonial, Hearn Cho, Katie Wozniak, Jonathan J. Keats, Craig Cole, John D. Carpten, George J. Mulligan. Multiple myeloma risk classification of CoMMpass using Consensus Genomic Staging identifies differences between patients with high and low African genetic ancestry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3887.

Abstract Background: Personalizing chemoradiotherapy (chemoRT) for locally advanced non-small cell lung cancer (LA-NSCLC) is limited by the lack of early biomarkers that inform response during treatment. Current circulating tumor DNA (ctDNA) molecular residual disease assays predict post-treatment outcomes but lack mid-treatment utility. ctDNA burden estimation has traditionally relied on variant-centric metrics such as maximum variant allele fraction (Max VAF), which rely on mutation-specific signals and may be confounded by histology-dependent shedding variability, allelic imbalance, and clonal hematopoiesis. Here we present circulating tumor fraction estimate (ctFE), a machine-learning composite score that integrates VAF distributions, copy-number alterations, and germline B-allele frequency deviations to approximate global tumor burden using a widely available, tumor-naïve clinical platform. Methods: A burden-based ctFE threshold was derived using pre-treatment plasma from a prospective phase II clinical trial of MR-guided hypofractionated chemoRT (LA-WU, n=26), locked, and applied unchanged to early mid-treatment samples (day 10-14). To test scalability and generalizability, its prognostic performance was validated in two real-world cohorts: 94 LA-NSCLC patients receiving definitive chemoRT (LA-RW) and 309 oligometastatic NSCLC patients receiving consolidative RT (OM-RW). ctFE and Max VAF were compared as continuous predictors across cohorts. Results: ctFE consistently outperformed Max VAF. In LA-WU, pre-treatment ctFE was associated with overall survival (OS HR=1.15, p=0.04) and progression-free survival (PFS HR=1.84, p=0.009), whereas Max VAF was not. Mid-treatment ctFE remained prognostic for PFS (HR=1.14, p=0.026). Early ctFE dynamics defined three molecular response groups with marked OS separation: consistently low, responder, and nonresponder groups (median OS 60.8 vs 13.0 vs 2.9 months, respectively; p<0.001). In multivariable models including both biomarkers, higher ctFE remained independently associated with worse survival in LA-RW (OS HR=1.88, p=0.010) and OM-RW (OS HR=1.37, p=0.040; PFS HR=1.45, p=0.008), whereas Max VAF did not. The locked ctFE threshold stratified OS across all cohorts (LA-WU HR=5.93; LA-RW HR=9.08; OM-RW HR=2.26; all p<0.001). Conclusion: ctFE provides clinically meaningful pre- and mid-treatment risk stratification and consistently outperforms Max VAF across locally advanced and oligometastatic NSCLC cohorts. We show that ctFE is a biologically informative, clinically generalizable and scalable ctDNA burden metric measurable using a tumor-naïve, off-the-shelf assay, supporting its practical utility in biomarker-adapted radiotherapy strategies. Citation Format: Ayesha Hashmi, Jessica Linford, Pradeep S. Chauhan, Kaushal Parikh, Rotem Ben-Shachar, John Guittar, Malvika Pillai, Jyoti Patel, Matteo Bergsagel, Nicholas P. Semenkovich, Kenneth R. Olivier, Sean S. Park, Dawn Owen, David M. Routman, Katie N. Lee, Alex D. Sherry, Aaron S. Mansfield, Daniel Morgensztern, Ramaswamy Govindan, Clifford G. Robinson, Carmen Bergom, Saiama N. Waqar, Bruna Pellini Ferreira, Gregory R. Vlacich, Aadel A. Chaudhuri. Early ctDNA quantification by ctFE outperforms Max VAF for survival stratification across locally advanced and oligometastatic NSCLC treated with radiotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1183.

Abstract Background: MHC class II molecules are normally restricted to professional antigen-presenting cells. Prior TNBC studies have focused on immune-compartment MHC-II. Using spatial transcriptomics, we recently identified aberrant tumor-cell MHC-II expression. Here, we characterized the immune architecture surrounding HLA-DRA-expressing tumor cells. Methods: High-plex single-cell spatial transcriptomics (CosMxTM SMI) was performed on treatment-naïve TNBC (Mayo TMA, n=65) and two neoadjuvant pembrolizumab cohorts (Mayo n=8; Emory n=4). Spatial neighborhoods were mapped relative to HLA-DRA-high tumor cells. Differential expression and adaptive immune gene-set scores were evaluated. Clinical relevance was assessed using FinXX (n=114), I-SPY2 (n=364), and Caris CODEai (n=3,662). Results: HLA-DRA-high tumor regions showed significant enrichment of adaptive immune subsets within ≤50 μm, including B cells, CD8+ T cells, NK cells, macrophages, and plasmacytoid dendritic cells. In pembrolizumab-treated cohorts, responders exhibited higher proportions of HLA-DRA-high tumor cells and greater numbers of B cells, plasmablasts, CD4+ and CD8+ T cells, and macrophages near tumor cells. Responders’ tumors showed upregulation of antigen-presentation machinery, B-cell/plasma-cell programs, CXCL13, and NOTCH3/DLL1. Across I-SPY2 and FinXX, higher HLA-DRA correlated with pathologic complete response and improved survival. In CODEai TNBC, high HLA-DRA expression correlated with higher CXCL13 (median TPM 7.5 vs. 1.1, q<0.05) and longer overall survival (24.2 vs. 18.5 months, HR 0.77, 95% CI 0.71-0.83, p<0.0001). This association was TNBC-specific. High CXCL13 also predicted improved survival (26.6 vs. 16.5 months, HR 0.64, 95% CI 0.59-0.69, p<0.0001). Conclusions: Tumor-cell HLA-DRA expression defines a highly organized adaptive immune niche enriched with B cells and activated T-cell populations in close proximity. Adaptive immune programs—including enhanced antigen presentation and CXCL13-mediated B-cell/plasma-cell pathways—consistently associate with improved outcomes across TNBC cohorts treated with chemotherapy and immune checkpoint blockade. Aberrant tumor-cell MHC-II expression may contribute to antitumor immunity and warrants further investigation as a potential therapeutic target. Citation Format: Yi Liu, Sachin Kumar Deshmukh, Thiti Susiriwatananont, Panuch Eiamprapaporn, Bogang Wu, Heikki Joensuu, Roberto A. Leon-Ferre, David Zahrieh, Judy C. Boughey, James Newell Ingle, Fergus J. Couch, Sharon Wu, Shipra Gandhi, Maryam Lustberg, George W. Sledge, Matthew P. Goetz, Keith L. Knutson, E Aubrey Thompson, Jodi Carter, Saranya Chumsri. Spatially resolved tumor-cell MHC class II shapes adaptive immunity and therapeutic response in triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1200.

The patient is a male in his 60s with morbid obesity and end-stage renal disease secondary to hypertension and diabetes. After a lifelong struggle with weight management, he was approved for bariatric surgery. Following completion of the bariatric clinic courses, he underwent laparoscopic Roux-en-Y gastric bypass. There were no intraoperative complications nor divergences from our routine practice. Postoperatively, the patient resumed peritoneal dialysis (PD) on postoperative day zero. He tolerated the operation and dialysis well, noting that the drained abdominal fluid remained serosanguinous for 5 days after surgery. While the traditional practice after intra-abdominal surgery is to temporarily transition to haemodialysis in patients who require dialysis, we demonstrate that immediate resumption of PD may be safe and efficacious. However, patients should be educated regarding the temporary change in colour of the drained intra-abdominal fluid. More robust data is required for further research and future practice guideline development.

Background/Objectives: Radiofrequency (RF) wire energy can be used for tissue ablation across many conditions. Adjusting RF generator parameters allows RF energy to puncture tissue with minimal adjacent damage. When RF energy is applied to tissue, however, microbubbles are produced, obstructing intravascular ultrasound (IVUS). Mitigation of RF-generated microbubbles has been studied for ablation but not for puncture. Methods: This paper describes an in vitro bench study using ex vivo bovine live tissue. A model was created with bovine liver tissue and an IVUS catheter submerged in a saline bath. Tissue was punctured with an RF guidewire to recreate microbubbles. Following the puncture, various methods were applied: altering the mechanical index of the IVUS, applying a VF10-5 Linear probe (Siemens), and applying a L12-3 Linear probe (Philips). Regions of interest (ROIs) were selected to track pixel brightness as a proxy for microbubbles. Results: The control increased ROI brightness by 1.5%. Altering the mechanical index of IVUS reduced ROI brightness by 1.2%. VF10-5 probe application increased ROI brightness by 1.2%. L12-3 probe application reduced ROI brightness by 33.0% (p = 0.046, n = 3, one-sample t-test). Brightness reduction was most pronounced at the site of initial RF wire puncture, where microbubbles accumulated. Tip visualization improved, allowing for more precise wire trajectory adjustments. Conclusions: External US with an L12-3 probe was able to dissipate microbubbles effectively to improve IVUS guidance following RF wire puncture in an in vitro exploratory bench model.

ABSTRACT BACKGROUND Increasing evidence suggests that accurate prediction of Alzheimer’s disease (AD) symptom onset requires more than amyloid- and tau-centric biomarkers such as cerebrospinal fluid (CSF) Aβ42/40, total tau and p-tau181 and plasma p-tau217. Autosomal dominant AD (ADAD), caused by pathogenic PSEN1, PSEN2 and APP mutations with predictable age at symptom onset, presents a unique opportunity to characterize the chronological changes in proteins beyond amyloid and tau and clarify them as early biomarkers of disease onset or as biomarkers related to disease staging and progression monitoring. METHODS We measured 972 CSF samples corresponding to 484 participants of the Dominantly Inherited Alzheimer Disease Network (DIAN) using the NULISASeq 120 CNS Disease Panel. We first benchmarked the technology against gold-standard measurements followed by the identification of proteins that were differentially abundant in relation to mutation status and symptomatology. Next, we determined the chronological emergence of protein changes in relation to the estimated years to onset (EYO). Finally, we assessed whether specific protein measures improved the prediction of EYO in the ADAD. FINDINGS NULISA measurements were comparable to those previously published. We demonstrated that known early alterations in CSF amyloid and tau were followed by inflammatory and neurodegenerative responses suggesting that clinical manifestation of AD happens before the inflammatory processes is fully developed. Finally, we found a multi-protein composite approach for predicting EYO that outperformed single biomarker values. INTERPRETATION Our results suggest that the main CSF proteomic landscape changes in ADAD are due to the presence of a pathogenic mutation and occur prior to symptom onset. Improved performance of multi-protein composite to predict EYO compared to single biomarker values highlights the added value of multiplex proteomic signatures for biomarker panel development. FUNDING National Institute on Aging, Alzheimer’s Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea, Spanish Institute of Health Carlos III.