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434 Background: Tinengotinib is a spectrum-selective multi-kinase inhibitor with unique binding properties to FGFR, potently inhibited FGFR2 fusion/rearrangement and acquired resistant mutations in pre-clinical models and in phase I trials that included cholangiocarcinoma (CCA) patients (pts). Here we present the efficacy and safety of tinengotinib in a phase II clinical trial. Methods: Eligible pts with advanced/metastatic CCA who had received ≥ 1 prior systemic chemotherapy therapy and ECOG PS 0 or 1 were treated with tinengotinib 10 mg QD. Four cohorts included: Cohort A1: FGFR2 fusion(s) with primary progression on previous FGFR inhibitor ( FGFRi), A2: FGFR2 fusion(s) with progression after prior response to FGFRi (acquired resistance); B: non-fusion FGFR alteration(s): C: FGFR wild-type ( FGFRwt). Primary endpoint was objective response rate (ORR) per RECIST v1.1. CTCAE V5.0 was used for safety assessments. Results: As of 7Aug2023, 48 pts with CCA were enrolled, 13 in Cohort A1, 10 in A2, 12 in B, 13 in C. Median age 61.5 [range 25-81] years old, 41.7% male, 58.3% had ≥ 3 lines of prior therapy. ECOG PS 0 in 47.9% pts. Among 35 pts with FGFR alterations, 80.0% had ≥ 1 prior FGFRi therapy, and 97.1% had prior chemotherapy. Forty (40) pts were efficacy evaluable. In A1, 1 out of 11 pts (9.1%) achieved PR with tumor reduction of 31.8%. In A2, 3 out of 8 pts (37.5%) achieved PR with tumor reduction of 40.7%, 47.0% and 54.6%. In B, 3 out of 9 pts (33.3%) achieved PR with tumor reduction of 36.5%, 48.6%, and 60.6%. No PR was observed in C. Overall DCR was 94.7% (18/19) in FGFR2 fusion/rearrangement pts (A1+A2), 88.9% (8/9) in other FGFR alterations pts (B), and 75% (9/12) in FGFRwt pts (C). Median progression-free survival (mPFS) was 5.26 months (95%CI, 2.86-9.10) in A1+A2, 5.98 months (95%CI, 1.87-NA) in B and 3.84 months (95% CI, 1.84-4.80) in C. Among 48 treated pts, treatment-related AEs (TRAEs) occurred in 45 (93.8%) pts, 14 (29.2%) in G1-2, 29 (60.4%) in G3 and 2 (4.2%) in G4. The most common G3 TRAEs were hypertension in 12 (25%), palmar-plantar erythrodysesthesia syndrome in 3 (6.3%), diarrhea in 3 (6.3%) and stomatitis in 3 (6.3%). One subject had G4 increased TSH and G4 increased lipase, and another subject had G4 posterior reversible encephalopathy syndrome. No G5 TRAE was observed. Conclusions: Tinengotinib has promising clinical benefit for FGFR2 fusion CCA after prior FGFRi and for non-fusion FGFR alterations. Tinengotinib-related toxicities were manageable. An ongoing randomized, controlled phase III study will evaluate the clinical efficacy, safety, and pharmacodynamic effect of Tinengotinib vs Physicians’ choice in subjects with FGFR2-altered refractory/relapsed CCA after prior chemotherapy and FGFRi therapy. Clinical trial information: NCT04919642 .

Background: Deeper depth of response (DpR) after induction therapy, especially gain of negative minimal residual disease (MRD), has been linked to prolonged survival in multiple myeloma (MM). However, flow-MRD examination focuses on the numbers but not on the biological characteristics of residual plasma cells (PCs). Objectives: To explore whether the genetic features of residual tumor cells affect the survival time of patients with MM. Design: A retrospective cohort study. Methods: We investigated the clonality of cytogenetic abnormalities (CAs) of the residual PCs using interphase fluorescence in situ hybridization (iFISH) in the National Longitudinal Cohort of Hematological Diseases in China (NCT04645199). Here, a longitudinal cohort of 269 patients with patient-paired diagnostic and post-induction iFISH results was analyzed. Results: Persistent CAs after induction therapy were detected in about half of the patients (118/269, 43%), and patients with undetectable CAs showed significantly improved survival compared with those with genetically detectable MRD [median progression-free survival (mPFS): 59.7 versus 35.7 months, p < 0.001; median overall survival (mOS): 97.1 versus 68.8 months, p = 0.011]. In addition, different patterns of therapy-induced clonal evolution were observed by comparing the clonal structure of residual PCs with paired baseline samples. Patients who maintained at a high risk during follow-up had the worst survival (mPFS: 30.5 months; mOS: 54.4 months), while those who returned to lower risk or had iFISH− at both time points had the best survival (mPFS: 62.0 months, mOS: not reached). Conclusion: These findings highlighted the prognostic value of genetic testing in residual tumor cells, which may provide a deep understanding of clonal evolution and guide clinical therapeutic strategies.

Importance Adding fulvestrant to anastrozole (A+F) improved survival in postmenopausal women with advanced estrogen receptor (ER)–positive/ERBB2 (formerly HER2)–negative breast cancer. However, the combination has not been tested in early-stage disease. Objective To determine whether neoadjuvant fulvestrant or A+F increases the rate of pathologic complete response or ypT1-2N0/N1mic/Ki67 2.7% or less residual disease (referred to as endocrine-sensitive disease) over anastrozole alone. Design, Setting, and Participants A phase 3 randomized clinical trial assessing differences in clinical and correlative outcomes between each of the fulvestrant-containing arms and the anastrozole arm. Postmenopausal women with clinical stage II to III, ER-rich (Allred score 6-8 or &amp;gt;66%)/ERBB2-negative breast cancer were included. All analyses were based on data frozen on March 2, 2023. Interventions Patients received anastrozole, fulvestrant, or a combination for 6 months preoperatively. Tumor Ki67 was assessed at week 4 and optionally at week 12, and if greater than 10% at either time point, the patient switched to neoadjuvant chemotherapy or immediate surgery. Main Outcomes and Measures The primary outcome was the endocrine-sensitive disease rate (ESDR). A secondary outcome was the percentage change in Ki67 after 4 weeks of neoadjuvant endocrine therapy (NET) (week 4 Ki67 suppression). Results Between February 2014 and November 2018, 1362 female patients (mean [SD] age, 65.0 [8.2] years) were enrolled. Among the 1298 evaluable patients, ESDRs were 18.7% (95% CI, 15.1%-22.7%), 22.8% (95% CI, 18.9%-27.1%), and 20.5% (95% CI, 16.8%-24.6%) with anastrozole, fulvestrant, and A+F, respectively. Compared to anastrozole, neither fulvestrant-containing regimen significantly improved ESDR or week 4 Ki67 suppression. The rate of week 4 or week 12 Ki67 greater than 10% was 25.1%, 24.2%, and 15.7% with anastrozole, fulvestrant, and A+F, respectively. Pathologic complete response/residual cancer burden class I occurred in 8 of 167 patients and 17 of 167 patients, respectively (15.0%; 95% CI, 9.9%-21.3%), after switching to neoadjuvant chemotherapy due to week 4 or week 12 Ki67 greater than 10%. PAM50 subtyping derived from RNA sequencing of baseline biopsies available for 753 patients (58%) identified 394 luminal A, 304 luminal B, and 55 nonluminal tumors. A+F led to a greater week 4 Ki67 suppression than anastrozole alone in luminal B tumors (median [IQR], −90.4% [−95.2 to −81.9%] vs −76.7% [−89.0 to −55.6%]; P &amp;lt; .001), but not luminal A tumors. Thirty-six nonluminal tumors (65.5%) had a week 4 or week 12 Ki67 greater than 10%. Conclusions and Relevance In this randomized clinical trial, neither fulvestrant nor A+F significantly improved the 6-month ESDR over anastrozole in ER-rich/ERBB2-negative breast cancer. Aromatase inhibition remains the standard-of-care NET. Differential NET response by PAM50 subtype in exploratory analyses warrants further investigation. Trial Registration ClinicalTrials.gov Identifier: NCT01953588

AbstractBackgroundEasily accessible and self‐administered cognitive assessments that can aide early identification of individuals at risk for Alzheimer’s disease (AD) dementia are critical for timely intervention. Mayo Test Drive (MTD) is a remote, self‐administered, multi‐device compatible, web‐based cognitive assessment (Stricker et al., 2022). We investigated continuous associations between MTD and amyloid and tau PET biomarkers and compared the strength of association to PET biomarkers and in‐person cognitive measures.Method556 adults from the Mayo Clinic Study of Aging participated (mean age = 70.6; mean education = 16.0 years; 50.7% female; 97.5% white). Participants were predominantly cognitively unimpaired (95.3%; 4.7% had a consensus diagnosis of mild cognitive impairment). Participants completed (1) brain amyloid and tau PET scans, (2) in‐person neuropsychological assessment including Mayo Preclinical Alzheimer’s disease Cognitive Composite (Mayo‐PACC) and Global‐z, and (3) remote MTD comprised of the Stricker Learning Span (SLS) and the Symbols test, which are combined into an MTD composite. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers [amyloid meta‐region of interest (ROI), tau meta‐ROI, and tau entorhinal cortex (EC)‐ROI)] and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites.ResultLower performances on MTD composite and Mayo‐PACC were associated with higher amyloid meta‐ROI (p’s<.05; Table 1). MTD composite was also negatively associated with tau meta‐ROI and EC‐ROI (p’s<.05). For memory measures, SLS sum of trials was negatively associated with tau meta‐ROI (p = .01) and EC‐ROI (p<.001) with no associations between AVLT sum of trials and PET (p’s≥.06; Table 2). Among processing speed/executive function measures, worse Trails B performance was associated with higher amyloid meta‐ROI (p<.001). Symbols and Digit Symbol Coding were not associated with PET (p’s≥.29). A multivariable model with MTD explained significantly less variance (p = .04) for amyloid meta‐ROI (adjusted R‐squared = 0.165) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.176); remote and in‐person composite measures were comparable for other associations (p’s>.05).ConclusionMTD is associated with continuous measures of amyloid and tau PET biomarkers of AD, demonstrating criterion validity for MTD. Several associations were comparable to relationships between gold‐standard in‐person neuropsychological tests and imaging biomarkers.

AbstractBackgroundBrief self‐administered cognitive assessments deployed remotely and combined with plasma biomarkers of Alzheimer’s disease (AD) are well suited to assess clinical symptoms and underlying biology in large‐scale decentralized studies. We investigated whether associations of self‐administered cognitive measures and plasma biomarkers were comparable to associations of in‐person cognitive measures and plasma biomarkers.MethodParticipants included 327 adults from the Mayo Clinic Study of Aging (mean age = 70.8; 48% female; mean education = 16.0 years; 96.9% white). Most (94.5%) were cognitively unimpaired; 5.5% had consensus diagnosis of mild cognitive impairment. Participants completed Mayo Test Drive (MTD; Stricker et al., 2022), a remote, self‐administered, multi‐device compatible web‐based cognitive assessment comprised of the Stricker Learning Span (SLS) and Symbols test that are combined into a MTD composite. Participants also completed in‐person neuropsychological assessment (global‐z; Mayo Preclinical Alzheimer’s disease Cognitive Composite [Mayo‐PACC]) and fasting venipuncture. Plasma was assayed via HD‐X simoa platform for amyloid‐beta (Aβ)‐42 and Aβ‐40 to create an Aβ42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) using the N4PE Quanterix kit as well as phosphorylated‐tau protein 181 (p‐tau181). P‐tau181, GFAP, and NfL were log10‐transformed. Multiple regression analyses adjusting for age, sex, and education examined associations between plasma biomarkers and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites.ResultLower performances on MTD, global‐z, and Mayo‐PACC (Table 1) were associated with higher GFAP (p’s≤.02), NfL (p’s≤.003), and p‐tau181 (p’s = .04). For memory, worse SLS and AVLT sum of trials were associated with higher GFAP (p’s≤.01) and NfL (p’s≤.03). For processing speed/executive function, worse Symbols and Trails B were associated with higher p‐tau181 (p’s≤.02). Worse Trails B and Digit Symbol Coding were associated with higher NfL (p’s≤.02), and worse Digit Symbol Coding was associated with lower Aβ42/40 (p = 0.03; Table 2). A multivariable model with MTD explained significantly more variance (p = .04) for NfL (adjusted R‐squared = 0.461) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.447); remote and in‐person composite measures were comparable for other associations (p’s>.05).ConclusionRemote and in‐person composite measures showed comparable associations with AD‐related plasma biomarkers, supporting MTD’s criterion validity.

AbstractBackgroundIn Alzheimer’s disease (AD), tau accumulates with a stereotyped progressive involvement of brain regions. The cellular mechanism for this is the neuron‐to‐neuron propagation of tau, but the factors that influence tau propagation are not fully understood. We hypothesize that AD‐associated post‐translational modifications (PTMs) of tau reduce its propagation since lysines are critical for LRP1‐mediated tau uptake.MethodA construct was designed to model tau propagation in Chinese hamster ovary (CHO) cells and allow identification of donor and recipient cells by immunocytochemistry and flow cytometry. In addition to the wildtype (WT) tau sequence, constructs were made with pseudophosphorylation and pseudoacetylation mutations corresponding to the phosphorylations and acetylations found on low molecular weight (LMW) and high molecular weight (HMW) tau species in AD brains. Additionally, individual PTM mimic mutations corresponding to PTMs of the LMW tau species were made. The constructs were transfected into CHO cells and tau propagation was assessed by flow cytometry after 48 hours. Statistical analysis was performed by ANOVA with adjustment for multiple comparisons.ResultTau propagation using this cell culture model was demonstrated by immunocytochemistry and flow cytometry. Comparison of the WT, LMW‐mimic (8D2Q mutant), and HMW‐mimic (20D3Q mutant) tau propagation constructs revealed that the 8D2Q and 20D3Q mutants displayed reduced tau propagation compared to WT by 23.7% (p = 0.0186) and 26.5% (p = 0.0087), respectively. Comparing the ten single mutant constructs to WT, T181D and T231D showed increased tau propagation by 20.3% (p = 0.0002) and 15.9% (p = 0.0094), respectively. Compared to WT, T217D, K281Q, K353Q, and S404D showed reduced tau propagation by 17.3% (p = 0.0030), 15.3% (p = 0.0123), 23.7% (p <0.0001), and 16.6% (p = 0.0046), respectively.ConclusionThe mimics of AD‐associated tau PTMs found on LMW and HMW tau reduce tau propagation, consistent with the initial hypothesis. The impact of individual PTM mimics on tau propagation is variable, but notably both pseudoacetylation mimics reduce propagation, possibly due to lower affinity with LRP1. Understanding how AD‐associated tau PTMs impact tau propagation may suggest novel targets to slow the progression of AD pathology.

Abstract Background Easily accessible and self‐administered cognitive assessments that can aide early identification of individuals at risk for Alzheimer’s disease (AD) dementia are critical for timely intervention. Mayo Test Drive (MTD) is a remote, self‐administered, multi‐device compatible, web‐based cognitive assessment (Stricker et al., 2022). We investigated continuous associations between MTD and amyloid and tau PET biomarkers and compared the strength of association to PET biomarkers and in‐person cognitive measures. Method 556 adults from the Mayo Clinic Study of Aging participated (mean age = 70.6; mean education = 16.0 years; 50.7% female; 97.5% white). Participants were predominantly cognitively unimpaired (95.3%; 4.7% had a consensus diagnosis of mild cognitive impairment). Participants completed (1) brain amyloid and tau PET scans, (2) in‐person neuropsychological assessment including Mayo Preclinical Alzheimer’s disease Cognitive Composite (Mayo‐PACC) and Global‐z, and (3) remote MTD comprised of the Stricker Learning Span (SLS) and the Symbols test, which are combined into an MTD composite. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers [amyloid meta‐region of interest (ROI), tau meta‐ROI, and tau entorhinal cortex (EC)‐ROI)] and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites. Result Lower performances on MTD composite and Mayo‐PACC were associated with higher amyloid meta‐ROI (p’s<.05; Table 1). MTD composite was also negatively associated with tau meta‐ROI and EC‐ROI (p’s<.05). For memory measures, SLS sum of trials was negatively associated with tau meta‐ROI (p = .01) and EC‐ROI (p<.001) with no associations between AVLT sum of trials and PET (p’s = .06; Table 2). Among processing speed/executive function measures, worse Trails B performance was associated with higher amyloid meta‐ROI (p<.001). Symbols and Digit Symbol Coding were not associated with PET (p’s = .29). A multivariable model with MTD explained significantly less variance (p = .04) for amyloid meta‐ROI (adjusted R‐squared = 0.165) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.176); remote and in‐person composite measures were comparable for other associations (p’s>.05). Conclusion MTD is associated with continuous measures of amyloid and tau PET biomarkers of AD, demonstrating criterion validity for MTD. Several associations were comparable to relationships between gold‐standard in‐person neuropsychological tests and imaging biomarkers.

Abstract Background Brief self‐administered cognitive assessments deployed remotely and combined with plasma biomarkers of Alzheimer’s disease (AD) are well suited to assess clinical symptoms and underlying biology in large‐scale decentralized studies. We investigated whether associations of self‐administered cognitive measures and plasma biomarkers were comparable to associations of in‐person cognitive measures and plasma biomarkers. Method Participants included 327 adults from the Mayo Clinic Study of Aging (mean age = 70.8; 48% female; mean education = 16.0 years; 96.9% white). Most (94.5%) were cognitively unimpaired; 5.5% had consensus diagnosis of mild cognitive impairment. Participants completed Mayo Test Drive (MTD; Stricker et al., 2022), a remote, self‐administered, multi‐device compatible web‐based cognitive assessment comprised of the Stricker Learning Span (SLS) and Symbols test that are combined into a MTD composite. Participants also completed in‐person neuropsychological assessment (global‐z; Mayo Preclinical Alzheimer’s disease Cognitive Composite [Mayo‐PACC]) and fasting venipuncture. Plasma was assayed via HD‐X simoa platform for amyloid‐beta (Aß)‐42 and Aß‐40 to create an Aß42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) using the N4PE Quanterix kit as well as phosphorylated‐tau protein 181 (p‐tau181). P‐tau181, GFAP, and NfL were log10‐transformed. Multiple regression analyses adjusting for age, sex, and education examined associations between plasma biomarkers and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites. Result Lower performances on MTD, global‐z, and Mayo‐PACC (Table 1) were associated with higher GFAP (p’s = .02), NfL (p’s = .003), and p‐tau181 (p’s = .04). For memory, worse SLS and AVLT sum of trials were associated with higher GFAP (p’s = .01) and NfL (p’s = .03). For processing speed/executive function, worse Symbols and Trails B were associated with higher p‐tau181 (p’s = .02). Worse Trails B and Digit Symbol Coding were associated with higher NfL (p’s = .02), and worse Digit Symbol Coding was associated with lower Aß42/40 (p = 0.03; Table 2). A multivariable model with MTD explained significantly more variance (p = .04) for NfL (adjusted R‐squared = 0.461) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.447); remote and in‐person composite measures were comparable for other associations (p’s>.05). Conclusion Remote and in‐person composite measures showed comparable associations with AD‐related plasma biomarkers, supporting MTD’s criterion validity.