Citations

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.

Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPis) are an important therapy for high-grade serous ovarian cancer (HGSOC). However, PARPi resistance frequently emerges, necessitating previously unrecognized approaches to improve HGSOC responses. Here, we showed that the anaplastic lymphoma kinase (ALK) inhibitor brigatinib enhances PARPi activity in HGSOC cells by disrupting an adaptive survival mechanism orchestrated by Fos-related antigen 1 (FRA1) in response to PARPi. This effect of brigatinib occurred through an ALK-independent pathway, wherein brigatinib induced a dual blockade of focal adhesion kinase (FAK) and EPH receptor A2 (EPHA2) tyrosine kinases, leading to the suppression of protein kinase B (Akt) and extracellular-regulated kinase (ERK) signaling accompanied by disruption of a phosphorylation event crucial for FRA1 protein stability. Moreover, in HGSOC patient-derived xenograft (PDX) models, brigatinib and PARPi combination therapy induced tumor regression and improved overall survival compared with PARPi alone, particularly in models with high FAK and EPHA2. These findings support dual targeting of FAK and EPHA2 as a strategy to achieve effective and durable PARPi responses and identify a promising biomarker-based combinatorial approach using brigatinib and PARPi for HGSOC, particularly the subset characterized by high FAK and EPHA2.

ABSTRACT Neurodegenerative diseases are characterised by the assembly of a limited number of disease-specific proteins into amyloid filaments, which form intracellular inclusions or extracellular deposits in the central nervous system (CNS) 1,2 . We previously found that amyloid filaments of TATA-binding protein-associated factor 15 (TAF15) characterise a subtype of frontotemporal lobar degeneration with FET protein-immunoreactive inclusions (FTLD-FET) 3 , termed atypical FTLD with ubiquitin-positive inclusions (aFTLD-U) 4 , which causes early-onset, rapidly progressive behavioural variant frontotemporal dementia (FTD). However, it was not clear if TAF15 proteinopathy was more widespread in neurodegenerative diseases. Two additional FTLD-FET subtypes have been proposed, neuronal intermediate filament inclusion body disease (NIFID) and basophilic inclusion body disease (BIBD) 5,6 , which have more heterogenous clinical presentations including FTD, motor neuron diseases (MND) and movement disorders. Here, we used electron cryo-microscopy (cryo-EM) to determine a total of 32 amyloid filament structures from the brains of 17 individuals encompassing all three proposed subtypes of FTLD-FET and their diverse clinical presentations. All cases were characterised by TAF15 filaments, in the absence of filaments of the other FET proteins, fused in sarcoma (FUS) and Ewing’s sarcoma (EWS). All three aFTLD-U cases had the previously-reported TAF15 fold 3 . Unexpectedly, we found four distinct TAF15 folds among 11 NIFID cases. Eight of these cases shared a common fold, while the remaining three were each distinct. Furthermore, we found distinct TAF15 folds for each of the three BIBD cases. Neuropathological reassessment of the neocortical TAF15 inclusion pathology of these cases distinguished the NIFID cases with the common fold from the others. Thus, TAF15 filament structures form the basis of a new, expanded classification of FTLD-FET subtypes. Moreover, we discovered a TAF15 Y38C variant in the filament fold of one of the individuals with BIBD. The structure is unable to incorporate wild-type TAF15, despite the individual being heterozygous, suggesting that this variant drives TAF15 filament assembly. This study provides structural and genetic evidence that TAF15 amyloid filaments underlie the diverse group of neurodegenerative diseases currently termed FTLD-FET, which we therefore rename FTLD-TAF15.

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 Staphylococcus aureus is a challenging pathogen which causes a multiplicity of human diseases around the globe, acquired in the community and healthcare settings alike. Treatment of S. aureus infection can be challenging and is further compromised by antimicrobial resistance. Understanding of its pathogenesis, transmission pathways and the dynamics of its genome evolution and associated adaptations is incomplete. One strategy to assess genome evolution is to assess codon bias. Historically, studies have focused on the consequences of coding changes; assessing silent mutations in the form of synonymous codon usage bias represents a novel approach to studying genetic adaptation.Figure 1.Principal component analysis (PCA) (A) and sPLS-DA (B) separate S. aureus from complex mates.sPLS-DA component 1 relies on a hypothetical protein, identified here by its NCTC 8325 genomic coordinates, as important for separating S. aureus from complex mates (C). Methods Here, the codon bias of 2,872 genes was queried against all publicly available complete S. aureus plasmids and genomes. Using public BioSample data, genomes were sorted by disease state (e.g., bacteremia, pulmonary infection) and geographical collection site. Results Isolates from Nairobi, Kenya were most different from other isolates, suggesting that geographical isolation may shape codon bias signature. In addition, codon bias of two MSCRAMM proteins implicated in human disease - SdrC and FnBPB - varied between isolation sources, suggesting a role for codon bias in S. aureus genetic adaptation to selective pressures of infection. Additionally, codon bias out-performed coding and nucleic acid mutational metrics in separating members of the S. aureus complex, S. aureus, Staphylococcus argenteus, Staphylococcus schweitzeri, and Staphylococcus roterodami; Fig 1, sparse partial least squares analysis (sPLS-DA) mean AUC codon: 0.89762, nucleic acid: 0.82266, codon bias: 0.9996 (relying on hypothetical protein NC_007795.1:516850-517419). Conclusion This analysis suggests that codon bias in S. aureus is a source of genetic adaptation that can be used to separate strains by geographical isolation source, and separate S. aureus sensu stricto from other S. aureus complex members. Disclosures Nicholas Bedard, MD, Stryker: Advisor/Consultant Robin Patel, MD, a patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication, a patent on PET imaging of bacterial infection: a patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication, a patent on PET imaging of bacterial infection|MicuRx Pharmaceuticals and bioMérieux: Grant/Research Support|PhAST, Day Zero Diagnostics, DEEPULL DIAGNOSTICS, S.L., Nostics, HealthTrackRx, bioMérieux and CARB-X: Advisor/Consultant|Up-to-Date and the Infectious Diseases Board Review Course: Honoraria

Background Costosternal cartilages and the costal margin, collectively termed costal cartilage, are hyaline cartilage connecting ribs to the sternum and to adjacent ribs, respectively. Presence of intact costal cartilage is essential for elasticity of the chest wall. Anecdotally, costal cartilage injuries are underdiagnosed on trauma CT scan in patients with rib fractures. Our aim was to determine a baseline frequency of acute costal cartilage injury among patients presenting with rib fractures. Methods We performed a retrospective cohort study of injured adult patients admitted to Level I/II trauma centers with rib fractures from January 2020 to July 2024. CT images obtained at admission were manually reviewed by chest wall surgeons for presence of costal cartilage injury. Concordance with the original radiology report was obtained. Multivariable regression was used to analyze factors associated with costal cartilage injury and missed cartilage fractures. Results 1441 patients were identified; 197 (14%) had a costal cartilage fracture. A plurality of injuries included falls (n=667, 46%). Median ISS (Injury Severity Score) was 13 (IQR: 9 to 21), median Abbreviated Injury Scale thorax score was 3 (IQR: 3 to 3), and median number of fractured ribs was 3 (IQR: 3 to 7). 294 (21%) patients had radiographic flail segments, and 136 (9%) had sternal fractures. 172 (87%) patients had a costal cartilage fracture missed on initial trauma chest CT. On multivariable analysis, ISS (adjusted OR (aOR) 1.02 (95% CI 1.01 to 1.04), radiographic flail segment (aOR 1.6 (95% CI 1.10 to 2.31)) and presence of sternal fracture (aOR 1.85 (95% CI 1.19 to 2.89)) were associated with costal cartilage fractures. Only the total number of rib fractures was associated with a missed costal cartilage fracture on univariate analysis (OR 1.17 (95% CI 1.01 to 1.36)). Conclusions Costal cartilage injuries are common and frequently are not identified during interpretation of the initial trauma CT. A higher index of suspicion is warranted for costal cartilage fractures among patients with greater injury burden, radiographic flail segment, and sternal fractures. Level of evidence Level III.

Objectives: To identify factors associated with short-term mortality among patients receiving microaxial flow pump (mAFP) therapy for acute myocardial infarction-related cardiogenic shock (AMI-CS). Data Sources: We searched four databases (MEDLINE, Embase, CENTRAL, and Scopus) from January 1, 2004, to January 1, 2025. Study Selection: We selected English-language studies that included adults with AMI-CS receiving mAFP and evaluated factors associated with short-term mortality. We excluded patients receiving concurrent venoarterial extracorporeal membrane oxygenation, as well as studies that solely included patients presenting with out-of-hospital cardiac arrest. Data Extraction: Two authors performed citation screening and data extraction. For each factor evaluated in at least two studies, we performed meta-analyses of adjusted odds ratios (aORs) using a random-effects model. Risk of bias was evaluated using the Quality in Prognosis Studies tool, and the certainty of evidence was evaluated using Grading of Recommendations, Assessment, Development, and Evaluations methodology. Data Synthesis: Our primary analysis included 18 studies, encompassing 20,617 patients. Median short-term mortality across studies was 50.7% (interquartile range 38.4–55.3%). Factors associated with short-term mortality based on high-certainty evidence included: increased age (aOR, 1.04 per year [95% CI, 1.03–1.05 per year] or ≥ 65 yr (aOR, 2.42 yr [95% CI, 0.77–7.64 yr]), female sex (aOR, 1.26 [95% CI, 1.09–1.45]), higher body mass index (aOR, 1.05 per point [95% CI, 1.04–1.07 per point]), higher heart rate (aOR, 1.02 per beats/min [95% CI, 1.01–1.02 per beats/min]), higher serum creatinine (aOR, 1.35 per mg/dL [95% CI, 1.08–1.70 per mg/dL]), mechanical ventilation (aOR, 2.53 [95% CI, 1.82–3.53]), vasopressors (aOR, 1.52 [95% CI, 1.11–2.08] for any vasopressors and aOR, 1.37 [95% CI, 1.18–1.58] per each vasopressor), presentation with ST-elevation myocardial infarction (aOR, 1.59 [95% CI, 1.11–2.26]), cardiac arrest (aOR, 2.85 [95% CI, 2.22–3.64]), and hypoxic-ischemic brain injury (aOR, 5.36 [95% CI, 3.03–9.47]). Conclusions: We identified several prognostic factors associated with short-term mortality in AMI-CS patients receiving mAFP support. This work may help inform clinicians, patients, and families regarding utilization of mAFP in AMI-CS.