Citations

Abstract INTRODUCTION: Prostate cancer (PC) shows marked heterogeneity in clinical outcomes, from indolent to highly aggressive disease. Alterations in TP53, PTEN, RB1, and DNA damage repair genes are linked to poor patient outcomes, yet how the interaction and co-occurrence of these alterations impact prognosis remains unclear. We leveraged the AACR Project GENIE prostate cancer cohort to assess the prognostic impact of individual and concomitant gene alterations, focusing on key PC drivers (BRCA2, TP53, PTEN, RB1). METHODS: the study was conducted in two stages: (i) identification of candidate alterations at individual gene level through a systematic literature review, followed by analyzing the prevalence and co-occurrence of genes in the AACR Project GENIE Public Release (PR) dataset. (ii) Prognostic analysis of the pre-selected biomarkers in the AACR Project GENIE Biopharma Collaborative (BPC) cohort. Analyses were performed in three clinical settings (entire BPC cohort, n=1114; subgroup of patients with localized disease at diagnosis, n=837; and subgroup of patients with metastatic PC with a biopsy collected before or at the time of mPC, n=455) using two statistical approaches: univariate analysis (UA) and inverse probability weighting using propensity scores (PS). Cox models were applied to estimate overall survival hazard ratios (HRs). RESULTS: after integrating the findings from the systematic review with the analysis of the GENIE PR (n=5684), 107 individual genes and 122 co-occurring alterations were selected for study. In the GENIE BPC (n=1114 patients) 75% were M0 at diagnosis, and 67% presented metastatic PC at any time. Alteration prevalence was: TP53, 25%; PTEN, 15%; BRCA2, 4%; RB1, 4%; co-alterations included, PTEN-TP53 (6.4%), RB1-TP53 (2.1%), PTEN-RB1 (1.3%), and BRCA2-TP53 (1.2%). All four key genes showed a statistically significant prognostic impact in the entire cohort with UA (BRCA2, HR:1.9; TP53, HR:2.6; PTEN, HR:2.4; RB1, HR:4.1, all p<0.001). Results were consistent in the subgroup analysis and when using PS. Additional genes such as FANCA, PIK3CA, and MYC were also associated with poor outcomes. Among co-alterations, BRCA2-TP53 (HR:2.0, p=0.05), RB1-TP53 (HR:3.6, p<0.001), PTEN-TP53 (HR:2.4, p<0.001); PTEN-RB1 (HR:5.5, p<0.001), and PTEN-TP53-RB1 (HR:9.0, p<0.001) were the strongest predictors of poor survival, with consistent effects across subgroups and analytical methods. Other combinations including MYC-TP53 (HR 2.2, p<0.001) and PIK3CA-TP53 (HR 3.2, p<0.001), also showed independent prognostic value. CONCLUSIONS: Genomic alterations in TP53, PTEN, RB1, and BRCA2, alone and in combination, independently associate with poor prognosis. Co-alteration patterns such as PTEN-TP53-RB1 define aggressive molecular subsets. This evidence supports integrating genomic interaction patterns for enhancing clinical risk models and guiding precision patient management. Furthermore, this study highlights the potential of AACR Project GENIE to enable data-driven development of biomarker-informed patient care strategies. Citation Format: Pablo Cresta Morgado, Victor Navarro, Guillermo Vilacampa, Haitham Alatoom, Manuel Ramos del Rio, Irbaz Riaz, Shawn Sweeney, Nikolaus Schultz, Ken Kehl, Gregory Riely, Wasim Abida, Katherine Panageas, Deborah Schrag, Philippe Bedard, Christine Micheel, Xindi Guo, Chelsea Nayan, Rodrigo Dientsmann, Joaquin Mateo. Genomic prognostic biomarkers in prostate cancer from the AACR GENIE cohort [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr A013.

ABSTRACT Microbial colonization of plant roots involves strong selective pressures that shape the structure and function of root-associated communities. In particular, the endosphere represents a highly selective environment requiring host entry and in planta persistence. However, strain-specific microbial traits that enable endosphere colonization remain poorly understood. Here, we use a defined, genome-resolved community of 28 Variovorax strains isolated from the roots of Populus deltoides and Populus trichocarpa (poplar trees) to determine which strains partition between rhizosphere and endosphere compartments and to identify the genomic traits associated with endosphere specialization. By combining strain-resolved metagenomic profiling, comparative genomics, and functional assays, we demonstrate that dominant endosphere colonizers are enriched in genes related to nutrient metabolism, redox balance, transcriptional regulation, and a conserved L-fucose utilization pathway experimentally shown to enhance root colonization. Not all strains succeed through the same strategy. Community-wide functional profiling revealed a distinct and reduced set of traits in the endosphere, including orthogroups associated with low-abundance strains that were overlooked in strain-level analyses. These findings reveal that multiple ecological strategies, such as metabolic competition, regulatory adaptation, and niche specialization, can support endosphere colonization. Our results advance the understanding of how bacterial colonization traits are distributed and deployed within a plant microbiome and suggest that host filtering selects for distinct, and sometimes complementary, microbial strategies. This work supports a shift toward mechanistic, genome-resolved models of microbiome assembly and offers a framework for linking microbial function to host colonization success. IMPORTANCE Plants often depend on diverse microbial partners to support their growth, resilience, and adaptation to changing environments. Among these microbes, some bacteria inhabit the rhizosphere (the narrow zone around roots where microbes interact with the plant) while others are able to enter and persist within root tissues. The traits that distinguish these two lifestyles remain poorly understood. In this study, we examined a group of related Variovorax strains from poplar tree root microbiomes to ask why some rhizosphere-associated strains also become successful endosphere colonizers. We found that strains appear to succeed through different strategies: some may benefit from rapid growth on plant-derived carbon sources, while others may rely on stress tolerance or fine-tuned regulation. These results suggest that there is no single path from the rhizosphere into the root interior, but rather multiple strategies shaped by the host environment. Understanding this diversity can inform efforts to design resilient plant-microbe communities.

Background: This systematic review examined differences in learner outcomes between traditional learning models (TLMs) and dedicated education units (DEUs) in undergraduate nursing programs. Method: Six databases were searched to identify peer-reviewed literature published between 2000 and 2025. Fifteen articles informed this review. Results: Included studies focused on various student outcomes including evaluation of students' perceptions and student performance. Themes around student perception included learning environment, learning opportunities, and learning performance. Themes around performance included standardized exams, course exams, competency exams, and preceptor evaluation of competency development. Conclusion: Main findings indicate the DEU model for clinical education enhances student satisfaction with the learning environment, increases learning opportunities, and improves self-perceived learning performance. The effects of DEUs on student performance outcomes require additional research, but preliminary research suggests a positive relationship between the DEU and competency development.

Abstract Purpose: Rearranged during transfection (RET) alterations are oncogenic drivers across solid tumors. Selective RET inhibitors (SRI) selpercatinib and pralsetinib have transformed outcomes for patients with RET-altered malignancies. Limited knowledge exists on genomic mechanisms of resistance to SRI. Experimental Design: We established “RETgistry,” a global consortium of patients with advanced RET-altered solid tumors who received SRI and underwent postprogression tissue or plasma biopsies assessed by next-generation sequencing. Frequencies of secondary RET resistance mutations and acquired non-RET gene alterations were determined. Progression-free survival (PFS) and time to treatment discontinuation (TTD) on first SRI were estimated with the Kaplan–Meier method. Results: RETgistry included 109 patients with RET-altered advanced solid tumors (lung, n = 94; thyroid, n = 15) who underwent 143 post-SRI progression biopsies (tissue, 91; plasma, 52). The median PFS and TTD were 13.9 months [95% confidence interval (CI), 10.1–16.6] and 17.3 months (95% CI, 14–20.2), respectively. Secondary RET mutations were detected in 20 (14%) biopsies [lung cancer, 15 (12.4%) and thyroid carcinoma, 5 (22.7%)]. Common acquired off-target alterations involved MET (18.2%; amplification, 15%), TP53 (8.2%), APC (7.6%), KRAS (7.1%), KEAP1 (5.9%), and CDKN2A/B (5.3%). MET alterations were enriched in post-SRI versus pre-SRI specimens (full cohort, 17.6% vs. 2.0%, P = 0.022; lung cancer, 19.1% vs. 2.1%, P = 0.022). Conclusions: The prevalence of secondary RET mutations after SRI was low, underscoring a greater role for off-target resistance. Recurrent acquired alterations involving tumor suppressor genes or upstream regulators of MAPK and PI3K pathways were identified, most commonly MET amplification. Continued efforts to characterize SRI resistance biology are critical to guide the development of novel therapeutic strategies.

Background: Pretibial dermopathy (PTD) is a rare, disfiguring manifestation of Graves’ disease. The shared pathophysiology with thyroid eye disease (TED), centered on fibroblast activation via a thyroid-stimulating hormone receptor and insulin-like growth factor-1 receptor (IGF-1R) complex, provides a strong rationale for using the IGF-1R inhibitor, teprotumumab. Methods: We present a case series of five patients with severe PTD and concomitant TED who were treated with teprotumumab. A review of reported cases in the literature was also conducted. Results: All patients experienced significant clinical improvement, including regression of skin thickening as well as enhanced functional capacity. Side effects included mild hearing loss, muscle cramps, and fatigue. One patient experienced a severe gastrointestinal event requiring treatment discontinuation, while those experiencing a recurrence of PTD, responded to a second course of therapy. Conclusions: Teprotumumab showed promising efficacy in the treatment of PTD. Further studies are needed to confirm its durability and safety.

163 Background: Being physically inactive is an independent predictor of poor outcomes in patients with stage III colon cancer. Whether physical activity can mitigate the oncologic risk of postoperative MRD is unknown. Methods: We concluded a post hoc analysis of a phase III trial evaluating celecoxib vs. placebo and 3 vs. 6 months of adjuvant chemotherapy in patients with resected stage III colon cancer. Self-reported physical activity was assessed in standardized measures of metabolic equivalent hours per week (MET-h/wk) at 2 timepoints: 1) midway through and 2) 6 months after completing adjuvant chemotherapy, modeled as a time-weighted average. MRD was determined via a clinically validated, tumor-informed circulating tumor DNA (ctDNA) assay (Signatera, Natera, Inc.). Disease-free survival (DFS) and overall survival (OS) were estimated using flexible parametric survival models. Results: Among 763 patients (median follow-up 6.0 years), 24% were highly active (≥18 MET-h/wk) and 32% were inactive (<3 MET-h/wk); 18% were ctDNA positive. Adjusting for covariates, DFS improved in patients who were ctDNA negative and moderately active (Ref: inactive; 3-17.9 MET-h/wk; HR=0.62, 95% CI [0.40-0.97]) or highly active (HR = 0.53 [0.30-0.94]). No benefit was seen among patients who were ctDNA positive (Ref: inactive; moderately active: HR = 1.20 [0.75-1.92]; highly active: HR=0.83 [0.45-1.54]). The interaction was not significant (Pint=0.269). Physical activity did not impact OS regardless of ctDNA status. The interaction of physical activity and adjuvant celecoxib use is shown in Table. Conclusions: Among patients who were ctDNA negative, physical activity was associated with improved DFS, and may demonstrate increased survival benefit alongside adjuvant celecoxib. The additive effects of both interventions were inconclusive among those who were ctDNA positive. Support: U10CA180821, U10CA180882, U24CA196171; https://acknowledgments.alliancefound.org; Natera, Pfizer; NCT01150045. Disease-free survival by physical activity level and celecoxib use, stratified by ctDNA status. 3-yr event # at risk Adjusted HR (95% CI) P-value Pint ctDNA Negative 0.258 Inactive + placebo 23 182 Ref Active + placebo 17 132 0.74 (0.43-1.28) 0.283 Inactive + celecoxib 23 167 0.92 (0.57-1.48) 0.720 Active + celecoxib 10 146 0.40 (0.22-0.79) 0.007 ctDNA Positive 0.221 Inactive + placebo 26 33 Ref Active + placebo 15 20 0.96 (0.50-1.84) 0.903 Inactive + celecoxib 34 54 0.62 (0.37-1.05) 0.076 Active + celecoxib 14 29 0.34 (0.18-0.64) 0.001 ctDNA, circulating tumor DNA; HR, hazard ratio; CI, confidence interval. Active = ≥9 MET-h/week, inactive = <9 MET-h/week. Celecoxib use defined by assignment in CALGB/SWOG 80702. Models adjusted by T and N stage, age, sex, race, assigned cycles of fluorouracil, leucovorin, and oxaliplatin, KRAS and BRAF status, BMI, and Western diet.

162 Background: In preclinical studies, the tryptophan-metabolizing enzyme, Indoleamine 2, 3-dioxygenase 1 (IDO1), promotes resistance to radiation in colorectal cancer, and IDO1 inhibition with epacadostat improves tumor radiosensitivity. In a phase 1 trial, patients (pts) with locally advanced rectal cancer (LARC, n=17) were treated with epacadostat in combination with short course radiotherapy (SCRT) and CAPOX which was well-tolerated, and the recommended phase 2 dose (RP2D) of epacadostat was 400mg BID. Here we report efficacy and safety from the NCI-supported phase 2 (NCT03516708) multicenter, open-label trial (treatment cohort). Methods: Pts were treated with standard of care (SOC) SCRT, then SOC neoadjuvant chemotherapy (NAC) followed by SOC surgical resection or non-operative management (NOM). Epacadostat (400 mg BID) started with SCRT and continued until starting NAC (a minimum of 21 days). Eight pts were enrolled prior to discontinuation of epacadostat by Incyte in February/March 2025. The primary endpoint is Neoadjuvant Rectal (NAR) score. In patients who underwent NOM, we calculated MRI-based tumor regression grade (MR-TRG). Secondary endpoints are pathologic complete response (pCR) rate, complete clinical response (cCR) rate, and progression free survival (PFS). Results: Table 1 summarizes baseline characteristics and endpoints (primary and secondary). NOM was pursued in 7/8 (87.5%) pts, surgical resection was performed on 1/8 (12.5%). At median follow-up of 12 months, local tumor regrowth occurred in 1 pt initially treated with NOM (after tumor regrowth, he underwent salvage surgery and is currently on surveillance). Treatment with epacadostat was interrupted in 2/8 (25%) patients due to grade 3 maculopapular skin rash. Most frequent treatment-emergent adverse events (TEAEs) regardless of causality (all grades (G)/G3-4) were bloating (75%/0%), increased ALT (62.5%/0%), increased AST (50%/0%), nausea (50%/0%), and constipation (50%/0%). Grade 3 diarrhea and grade 3 non-cardiac chest pain occurred in 1 patient each (both unrelated to epacadostat). Conclusions: Epacadostat demonstrates promising efficacy and manageable safety in patients with LARC. The biomarker cohort and correlative studies are ongoing. Clinical trial information: NCT03516708 . Baseline characteristics and endpoints. Patient Age Sex Ethnicity Stage Surgery/NOM NAR MR-TRG cCR/pCR Recurrence 1 52 M Caucasian T3N1 NOM NA 2 Y/NA No 2 45 M Caucasian T3N1 NOM NA 3 Y/NA Local tumor regrowth 3 48 M Caucasian T3N2 NOM NA 3 Y/NA No 4 61 M Caucasian T4N2 NOM NA 3 Y/NA No 5 57 M Caucasian T3N0 NOM NA 1 Y/NA No 6 60 F Caucasian T3N1 Surgery 15 3 N/ypT3N0 No 7 67 M Caucasian T4N0 NOM NA 3 Y/NA No 8 51 M Caucasian T4N2 NOM NA P NA No

Abstract Background Older adults with brain tau pathology but no evident amyloid‐beta (A) pathology can be referred to as primary age‐related tauopathy (PART). However, in vivo characterization of PART using biomarkers remains unclear, varying based on the method used to define tau pathology (e.g. different tau‐PET tracers). Here, we conducted a head‐to‐head characterization of PART using two different tau‐PET tracers. Method We studied 433 individuals from the HEAD cohort (244 CU, 138 MCI, and 51 with dementia). Participants underwent clinical assessments, MRI, A‐PET, both MK‐6240 and Flortaucipir scans, and a subset with plasma biomarkers ( n = 332). A‐PET positivity was defined as Centiloid>24. Tau‐positivity(T) was determined by MK‐6240 and Flortaucipir SUVR values exceeding the mean+2SD in at least one Braak region anchored in CU A‐ individuals followed by visual confirmation in A‐/T+ cases. Concordance across biomarkers was assessed among PART (A‐/T+), A‐/T‐ and A+/T+ groups. Plasma GFAP, p ‐tau217, NFL levels, and Centiloids were compared across A/T groups using linear regression. Result We found a total of 25 (5.8 %) cases classified as A‐/T+ defined by at least one tau tracer (74±6.3 years, 52% females, 17 CU, 3 MCI, 5 with dementia). Detection of A‐/T+ cases varied by tracer: MK‐6240( n = 20), Flortaucipir( n = 16) (Figure 1A). Among A‐/T+ individuals, MK‐6240 identified 13 CU, 4 MCI, and 3 dementia cases, while Flortaucipir identified 11 CU, 3 MCI, and 2 dementia cases(Figure 1B). Concordance between MK‐6240 and Flortaucipir in A‐/T+ cases was low ( n = 11, 44%)(Figure 1C). A‐/T+ individuals showed no significant biomarker differences from A‐/T‐ but had lower biomarker levels than A+/T+: Centiloids (MK‐6240: T=15.08, p <0.001; Flortaucipir: T=14.36, p <0.001), GFAP (MK‐6240: T=5.04, p < 0.01; Flortaucipir: T=2.92, p <0.001), p ‐tau217 (MK‐6240: T=7.77, p <0.001; Flortaucipir: T=6.34, p <0.001), except for NFL (MK‐6240: T=1.35, p = 0.18; Flortaucipir: T=1.14, p = 0.25)(Figure 2). Representative A and tau biomarker cases (Figure 3A), along with discordant cases classified as T+ by only one tracer (Figure 3B), are illustrated. Conclusion Our preliminary analysis revealed a higher prevalence of A‐/T+ cases with MK‐6240 than Flortaucipir, low concordance between tracers and consistently lower biomarker levels in A‐/T+ compared to A+/T+. Larger studies and longitudinal analyses are necessary to ascertain the pathological trajectories of A‐/T+ individuals with varying tau biomarker profiles.

Abstract Background Tau phosphorylation and aggregation are hallmark features of Alzheimer's disease pathology(AD). Previous studies have shown that plasma phosphorylated tau( p ‐tau) at threonine 217 can detect AD‐related tau tangle pathology. However, the head‐to‐head association between p ‐tau217 and different tau PET tracers remains unexplored. Here, we conducted a head‐to‐head comparison of the association between plasma p ‐tau217 and four distinct tau PET tracers[MK6240, Flortaucipir(FTP), PI2620, RO948]. Method We studied 338 individuals across the AD continuum from the HEAD study[190 cognitively unimpaired elderly(CU), 109 with mild cognitive impairment(MCI), and 39 with dementia] with available FTP, MK6240, and plasma p ‐tau217 measured by ALZpath assay. A subset of 64 individuals(28 CU, 25 MCI, and 11 dementia) also had PI2620 and RO948, and p ‐tau217 measured by Lumipulse. The strength of the association was determined using t‐value maps from regression models testing the association between each tau PET tracer and plasma p ‐tau217, and the extent was measured by the percentage of significant voxels(t‐value>3.2). R‐square metric was used to determine how much of the variance in tau PET tracer estimates was explained by plasma p ‐tau217 concentrations. Associations between p ‐tau217 with tau PET were evaluated using the Spearman test. Result We found that in CU, both the extent and magnitude of the association with plasma p ‐tau217 were higher for MK6240 compared to FTP (Figure 1A‐D). Plasma p ‐tau217 explained a greater proportion of the variance in MK6240 than in FTP (Figure 1E‐F). In CI, the extent and magnitude of the association were similar for MK6240 and FTP. Additionally, plasma p ‐tau217 explained a similar proportion of the variance in MK6240 and FTP. Using the subset of individuals who had all tau tracers, MK6240 showed a slightly higher extent of association with p ‐tau217, followed by FTP, PI2620, and RO948 (Figure 2A‐B). The magnitude of association was stronger for MK6240, followed by PI2620, RO948, and FTP (Figure 2C‐D). Plasma p ‐tau217 explained a greater proportion of the variance in MK6240, followed by FTP, RO948, and PI2620 (Figure 2E‐F). We compared the associations between different p ‐tau217 assays, and both assays presented similar associations with all tau PET tracers (Figure 3). Conclusion In summary, our results indicate that the four tau PET tracers exhibit robust associations with plasma p ‐tau217 in similar topographical regions.

Abstract Background Tau accumulation in the brain is postulated to follow a hierarchical pattern, known as Braak staging, originally defined in postmortem brains. PET‐based Braak stages have since been proposed, however, tau PET tracers exhibit distinct binding characteristics that might influence the detectable trajectories of tau accumulation and its relationship with other biomarkers across the AD continuum. In a head‐to‐head study, we investigated the emergence of tau positivity in each Braak region, along with plasma p ‐tau217 and GFAP, as a function of Aβ PET deposition. Method We evaluated 352 individuals from the HEAD study (205 cognitively unimpaired and 147 cognitively impaired) with head‐to‐head Aβ PET, MK6240 and Flortaucipir tau PET, and plasma p ‐tau217 (ALZpath) and GFAP (Quanterix) measures. Tau PET Braak regions, plasma p ‐tau217 and GFAP trajectories were modeled as functions of Aβ burden (Centiloid scale) using the Lowess method. Biomarkers were z‐scored anchored on young individuals ( n = 19, <28 years old). Positivity for plasma biomarkers and for each Braak region was determined when values surpassed 2.5 z‐score from the mean. Result Among the tested markers, plasma GFAP was the earliest to show abnormality as a function of Centiloid, occurring at 11 Centiloids. For MK6240, Braak I was the first regions to became positive (at 22 Centiloids), followed by Braak II (at 32 Centiloids), Braak IV (at 42 Centiloids), Braak III (at 52 Centiloids), Braak V (at 70 Centiloids) and Braak VI (at 123 Centiloid; Figure 1A). For Flortaucipir the first region to became positive was Braak IV (at 50 Centiloids), followed by Braak I and II (both at 56 Centiloids), Braak III (at 85 Centiloids) and Braak V (at 92 Centiloids). Braak VI region did not reach the threshold for positivity in our population (Figure 1B). Plasma p ‐tau217 reached the positivity threshold at 38 Centiloids. Conclusion MK6240 follows a Braak stage‐like pattern of abnormality as a function of Aβ burden, whereas for Flortaucipir, Braak IV is the first region to became abnormal. MK6240 becomes abnormal at lower Aβ burden levels compared to plasma p ‐tau217 and Flortaucipir but after plasma GFAP. Our findings suggest that MK6240 might detect tau pathology in earlier disease stages than Flortaucipir.