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Background: Anaplastic large cell lymphomas represent a group of T-cell lymphomas that have long been broadly classified by the presence or absence of ALK fusion proteins (ALK+ or ALK−, respectively). However, recent discovery of extensive additional molecular heterogeneity has both promoted refinement of disease classification and uncovered new opportunities for biomarker-guided targeted therapy. In addition to recognition of a new genetic subtype, ALK− ALCL with DUSP22 rearrangement (R), a new molecular classification has been proposed based on the recent discovery of 2 overarching molecular types of ALCL, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. BCL2 is a mitochondrial membrane protein that functions to inhibit the actions of pro-apoptotic proteins such as BAX and BAK and can be targeted clinically by BCL2 small molecule inhibitors. BCL2 has been reported to be expressed more frequently in ALK− ALCL than in ALK+ ALCL, but its expression in the context of current molecular findings is unknown. Methods: ALCLs were centrally reviewed and classified by current WHO/ICC criteria. BCL2 was performed using IHC and scored as positive if ≥30% of tumor cells showed staining. DUSP22-R was assessed by fluorescence in situ hybridization (FISH) using a breakapart probe set and a dual-color, dual-fusion (D) probe set for the most common DUSP22 translocation, t(6;7)(p25.3;q32.3). pSTAT3Y705 IHC, which is >90% accurate for Type I/II assignment based on gene expression, was performed and scored based on a previously validated cut-off of ≥30%. Results: We evaluated 217 ALCLs (148M/69F; age: mean, 57 y; range, 5-93 y), including 55 systemic ALK+ ALCLs, 127 systemic ALK− ALCLs, and 35 primary cutaneous (pc) ALCLs. Overall, 86/217 cases were positive for BCL2 (40%). BCL2 was positive in 67/127 ALK− ALCLs (53%) and 15/35 pcALCLs (43%; P=NS), but in only 4/51 ALK+ (7%; P<0.0001). DUSP22-R was present in 90 cases (63 ALK− ALCL and 27 pcALCL). BCL2 was positive in 57/90 cases with DUSP22-R (63%) compared to 29/127 without DUSP22-R (23%; P<0.0001). Among 85 cases with DUSP22-R and informative D-FISH testing, BCL2 was positive in 24/36 cases with t(6;7)(p25.3;q32.3) (67%) and 31/49 cases without t(6;7)(p25.3;q32.3) (63%; P=NS). Among 213 cases with informative pSTAT3Y705 staining, BCL2 was positive in 13/88 pSTAT3+ cases (Type I, 15%) and 70/125 pSTAT3− cases (Type II, 56%; P<0.0001). Conclusions: We identified a complex pattern of BCL2 expression across ALCLs that strongly correlates with a recently introduced molecular classification based on gene expression profiling. While our findings are in keeping with the previously reported low expression in ALK+ ALCL, we found that the higher expression in both systemic ALK− ALCL and pcALCL is particularly associated with DUSP22-R and the absence of pSTAT3Y705 expression (Type II ALCLs). The discovery of 2 overarching types of ALCL associated with the presence or absence JAK-STAT3 pathway activation represents a new conceptual framework for classifying ALCL and understanding its therapeutic vulnerabilities. Of note, previous data demonstrated that Type II ALCLs are enriched for epigenetic alterations and particularly overexpress the histone methyltransferase EZH2. Correlation between BCL2 expression and EZH2 expression also is observed in other lymphomas such as diffuse large B-cell lymphoma, where dual targeting with EZH2 and BCL2 inhibitors has been proposed. Thus, our findings provide further rationale for stratifying Type I and Type II ALCLs and identify BCL2 as a differentially expressed oncoprotein that might represent a target for precision therapy approaches.

Background: Anaplastic large cell lymphomas (ALCLs) represent a heterogeneous group of T-cell lymphomas that currently are classified by the presence or absence of ALK tyrosine kinase (TK) fusion genes (ALK+ or ALK−) and clinical presentation (systemic, cutaneous, or breast implant-associated). Two overarching molecular types of ALCL recently were discovered, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. Fusions involving non-ALK TK genes occur in some ALK− cases, but the fusion landscape of ALCL remains incompletely characterized. Methods: Expert consensus pathology review was conducted in the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). RNAseq was performed and fusions were identified using FusionCatcher. Here, we focused on recurrent in-frame coding fusions. Previously unreported fusions were validated by RT-PCR. Type I/II was assigned using a previously validated gene expression-based model. Genes with adjusted (adj) P<0.05 were considered differentially expressed. Overall survival (OS) was assessed for systemic ALCL, when available. Results: We evaluated 379 ALCLs (229M/150F; mean age, 56 y). Of 199 candidate fusions (excluding reciprocal events), 28 were recurrent and passed quality metrics. At least 1 of these 28 fusions was present in 150 cases (40%). ALK fusions were present in 106 ALK+ ALCLs (all Type I; P<0.0001). Of these, NPM1::ALK was seen in 68/106 (64%). Alternate partners (X::ALK) included ATIC (N=24) and CTLC, COL1A2, MSN, MYH9, RNF213, SATB1, TFH, TPM3, and TRAF1 (1-3 cases each). X::ALK was associated with older age (mean, 52 y) than NPM1::ALK (32 y; P<0.0001) and showed relative overexpression of 49 genes, including multiple activators of small GTPases such as CGNL1 (FC, 5.6; Padj=2.4×10-6), SRGAP1, ALS2, DOCK1, and NCKAP1. ALK expression was similar in cases with NPM1::ALK and X::ALK and there was no significant difference in OS. Non-ALK TK fusions were seen in 17/273 ALK− cases (6%), including TYK2 (N=9); JAK2 (N=6); and ROS1 (N=2). All were Type I ALCLs (P<0.0001). ALK− cases with non-ALK TK fusions overexpressed 38 genes compared to ALK− cases without TK fusions, including cytokines involved in the IL17 signaling pathway such as CXCL6 (FC, 12.5; Padj=4.2×10-3), CXCL1, and CSF3. We then assessed the relationship between ALK− cases with non-ALK TK fusions and ALK+ cases by separately comparing each subset to ALK− cases without TK fusions. FC values for ALK− cases with non-ALK TK fusions were significantly correlated with FC values for ALK+ ALCLs over the set of expressed genes (R=0.54; P<0.0001). At a median follow-up of 32 months, 0/4 systemic ALCL patients with non-ALK TK fusions had died, while 30% of those with ALK− ALCL without TK fusions had died, but this was not statistically significant (P=0.26). The other 13 ALK− cases with non-ALK TK fusions were either localized ALCLs or did not have outcome data available. Of 20 TP63 fusions, 17 (85%) were TBL1XR1::TP63 and 3 were X::TP63. As previously reported, TP63 fusions were associated with poor OS (median OS, 10 months; not reached for other ALK− ALCLs; P=0.007). Four ALCLs had a novel NCL::UBTF fusion involving genes encoding the nucleolar proteins nucleolin and nucleolar (upstream binding) transcription factor-1. Four cases each had PARG::BMS1 and TNK1::GPS2 (the latter seen only in Type I ALCLs). Conclusions: This large consortium-based analysis of coding fusions further elucidates the molecular distinction between Type I and Type II ALCLs. Both ALK and non-ALK TK fusions were seen exclusively in Type I ALCLs, which we have shown previously are enriched for JAK-STAT3 pathway genes and correlate strongly with pSTAT3Y705 positivity by immunohistochemistry. These fusions were not identified in Type II ALCLs, which previous data suggest are associated with epigenetic alterations. ALK+ ALCLs with NPM1::ALK and X::ALK showed differences in gene expression, suggesting biological differences. Furthermore, ALCLs with non-ALK TK fusions shared gene expression features with ALK+ ALCL. Clinical fusion detection could enhance molecular classification of Type I and Type II ALCLs and may guide precision therapy.

Introduction/Background: Bispecific T cell engagers (TCE) targeting BCMA and CD3 induce deep hematologic responses in approximately 60% of heavily pre-treated multiple myeloma (MM) patients. There is an unmet need to overcome primary resistance, as this off-the-shelf therapy is readily available to patients with aggressive disease relapse and has the potential to be delivered in the community. We and others found that high tumor burden leads to primary resistance to TCE 1,2,3,4 and that combination with immunomodulatory drugs (IMiDs) transiently improves responses yet exacerbates T cell exhaustion2. Here, we present preclinical strategies to overcome primary resistance which are tolerable and provide more durable responses specifically for the high tumor burden setting. Methods: We evaluated response and survival to a murine surrogate BCMA/CD3 TCE in the Vk*MYC immunocompetent mouse model of MM expressing human CRBN to investigate tumor burden as a mechanism underpinning primary resistance. We evaluated dosing methods and combination strategies with IMiDs or novel CELMoDs, checkpoint inhibitors, and dexamethasone to improve response rates while maintaining a manageable safety profile. Results: We investigated primary resistance in an expanded panel of Vk*MYC models reflecting differing genomic heterogeneity and confirmed that a threshold of tumor burden limits T cell activation and correlates with resistance to TCE. BCMA is cleaved from the tumor cell surface by gamma-secretase and thus, high density of shed BCMA may act as a sponge to BCMA TCE. However, we found that administration of gamma-secretase inhibitors, while stabilizing BCMA expression on MM cells, is not sufficient to overcome high tumor burden-driven resistance to TCE. We previously reported the combinatorial activity of BCMA TCE with IMiDs and revealed a role for tumor-extrinsic effects of IMiDs in allowing mice with a high tumor burden to transiently respond to BCMA-TCE before T cell exhaustion prevailed2. To build on that combination strategy, we first hypothesized that the addition of a PD1 checkpoint inhibitor could reduce T cell exhaustion that occurs in response the BCMA-TCE in the resistant setting. We found that this triple combination provides more persistent activation and expansion of cytolytic T cells and sustains remission but leads to toxic cytokine release syndrome and early mortality in half of the cohort. Next, to address the acute toxicity from the hyperactivated T cell response and reduce tumor burden, we combined the triple combination with dexamethasone (Dex). To our surprise, concurrent Dex, even in the absence of IMiDs/CELMoDs, boosts responses to TCE. We observe that Dex moderates T cell proliferation in response to the TCE and leads to a moderate sustained cytokine production (IFN-γ, TNF, and IL-2R) systemically and in the bone marrow compared with a high transient burst seen with TCE alone or the concurrent treatment with IMiD + PD1 blockade. We determined that incremental step-up TCE dosing allows the combination of IMiDs or CELMoDs (iberdomide or mezigdomide) with Dex to be completely tolerated. To investigate whether delivering IMiD or CELMoDs before or during TCE administration altered efficacy, we tested pre-treatment with IMiDs/CELMoDs + Dex compared with concurrent dosing and found pre-treatment led to superior durable responses. Pre-treatment with iberdomide + Dex followed by step-up dosed TCE generated 100% response rate and the highest overall survival in subjects bearing a high tumor burden. This was accompanied by a more favorable T cell profiling over time, with limited expansion of regulatory T cells and reduced accumulation of exhausted T cells. Conclusion: Modelling the dosing and combination strategies of a BCMA-TCE in our immunocompetent system has allowed us to understand the dynamic changes in T cell fitness that are required for effective, tolerable, and durable TCE therapy for MM. We illustrate how improvements to TCE therapy mitigate T cell exhaustion and overcome primary resistance, and importantly, suggest a strong immunotherapeutic strategy for MM patients with challenging-to-treat actively progressing disease. 1. Lee et al., Nat Med 29, 2295-2306 (2023) 2. Meermeier et al. Blood Cancer Discov. 2021 Jul;2(4):354-369. 3. Rees et al. Blood Cancer J. 2024 Jul 23;14(1):122. 4. Girgis et al. Blood Adv. 2023 Feb 28;7(4):644-648

Primary resistance to BCMA-directed bispecific antibodies (BCMA-BsAb) is a major clinical hurdle despite their outstanding efficacy for relapsed and refractory multiple myeloma (MM). Primary resistance has been linked clinically to patient characteristics including tumor burden. Our previous work in the immunocompetent Vk*MYC model of MM credentialed that tumor burden also correlates with resistance to a murine BCMA-BsAb, which we addressed through drug combinations with MM backbone agents. Pairing the BsAb with cyclophosphamide (Cy) was well-tolerated, reversed primary resistance, reshaped an immunosuppressive tumor microenvironment (TME) and led to durable responses with immunosurveillance in all but the most aggressive settings. Here, we aimed to improve the BCMA-BsAb and Cy combination strategy with a goal of curing models representing clinically relevant Cy-refractory aggressive settings, by adding T cell checkpoint blockade. Despite a lack of single agent activity of checkpoint inhibitors in MM (and in our models), PD1 and TIGIT are relevant targets as their expression on T cells correlates with both primary and acquired resistance to BCMA-directed cell therapies. Our team hypothesized that blockade of either PD1 or TIGIT with concurrent BCMA-BsAb and Cy would deepen anti-MM responses and provide a more durable immunotherapy regimen by sustaining activation of the T cell repertoire. Methods: We preclinically tested the ability of two weeks of concurrent dosing of BCMA-BsAb with Cy, checkpoint inhibitors targeting either PD1 or TIGIT, or the triple combination to overcome primary resistance and improve survival in a Cy-resistant transplantable Vk*MYC model of MM. We followed the response longitudinally in the blood, and in the bone marrow and spleen after complete responses were achieved at five weeks. Results: The double combination of a checkpoint inhibitor to the BCMA-BsAb was well-tolerated and abolished primary resistance, yet, failed to provide curative responses. Whereas the triple combination with either PD1 or TIGIT blockade remained safe, provided robust initial responses that overcame primary resistance and resulted in durable complete and curative responses in the entire cohort. These survival benefits represent significant improvements over control combinations tested here but also over all historical preclinical anti-MM therapy tested in our models to date. Both PD1 and TIGIT blockade with Cy/BCMA-BsAb triple combinations delivered a similar multiphasic potent anti-tumor response. This response was first characterized by highly effective T cell-mediated lysis of the tumor, as evidenced by deep reduction of M-spike after two weeks of treatment. As we previously published, the addition of Cy to BCMA-BsAb rapidly reshapes the TME by depleting Tregs and exhausted T cells and brings naive T cells to the tumor. However, we observed elevated T cell checkpoint expression at times of BsAb-relapse in aggressive models, suggesting that blockade of these pathways may help sustain T cell activation. Indeed, the ensuing T cell response in the triple combination gradually builds and encourages a pool of less terminally differentiated T cells to proliferate to allow for a more sustained response with repeat dosing. For the first time, we observe that the triple combination significantly engages the CD4 T cell compartment, which can be essential for a complete anti-tumor response. At the time of complete response, single cell analysis displays that T cells retained in the BM were less exhausted and defined by elevated CCR2 expression, a known marker of activated memory T cells, suggestive of ongoing immunosurveillance. Conclusions: Here we demonstrated through controlled in vivo experimentation how the addition of Cy reverts primary resistance to BCMA-BsAb by reshaping the TME in our Cy-insensitive preclinical model. Adding checkpoint inhibitors targeting TIGIT or PD1 further improves the durability of BsAb and Cy combination to cure all mice in these cohorts, by critically lysing the tumor, resetting the suppressive TME, and instigating a gradual, multiphasic, and sustained anti-MM T cell response. The concurrently delivered triple combination is well tolerated and provides optimal temporal control of MM especially in a preclinical model reflecting primary resistance mediated by high tumor burden and may have translational benefit to MM patients.

Background: Flow cytometry (FC) is widely utilized for the identification of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL), providing an essential laboratory indicator for prognostic assessment and therapeutic management. Unfortunately, the high level of expertise required, long manual analysis time, and complexity of FC data files limit the offering of this testing to selected reference laboratories. Methods: We developed an artificial intelligence (AI) pipeline to automatically enhance unaltered FC files, minimizing the expertise and manual analysis time needed to detect CLL MRD on a single-tube 10-color panel (CD5, CD19, CD20, CD22, CD38, CD43, CD45, CD200, kappa and lambda). Raw FC files corresponding to peripheral blood or bone marrow specimens from 166 CLL MRD positive cases (MRD < 5%, median = 0.17%, 122 patients), and 61 MRD-negative cases (45 patients) were processed through our CCADDAS (Clustering and Classification of All events, Dimensionality reduction, Downsampling and Aberrancy Scaling) pipeline on a cloud environment (Google Vertex AI). Automated processing steps included elimination of acquisition errors (FlowCut), state-of-the-art clustering (PARC), dimensionality reduction (UMAP), cluster-based anomaly detection compared to negative controls (15 bone marrow aspirates and 14 peripheral bloods), and cluster-informed downsampling with preservation of low-event subsets. In addition, a deep neural network (DNN) trained on expert-defined subpopulations from negative controls was included for automatic gating of normal subsets (Tensorflow v2). AI-enhanced data files were analyzed using a general purpose flow cytometry analysis software (Kaluza v 3.5, Beckman Coulter), and %MRD estimates compared to reported results based on expert analysis of original FC files. Results: Cluster-informed downsampling reduced the number of cells per case to be manually analyzed from 1.1 million to 165,010 cells on average (85% cellularity reduction); resulting in a smaller FC data file (from 62.1 MB to 15.2 MB; 75% data reduction). Importantly, low-level MRD events were adequately preserved after downsampling (median 100% retention for both MRD<0.01% and MRD 0.01-1%). True number of events were accurately estimated on gated subsets using an “upsampling factor” parameter [observed # events x mean (upsampling factor)]. Gating of normal subsets was completely automated using a DNN classifier parameter. Rapid identification of suspected MRD was aided by an AI-generated “aberrancy scale” parameter that discriminated CLL MRD (mean ± 2SD: 969 ± 144) from background B-lymphoid cells (mean ± 2SD: 395 ± 401) (p<0.0001) (AUC = 0.98), with a performance superior to CD5 (AUC = 0.93), CD20 (AUC = 0.83), CD43 (AUC = 0.8) and CD200 (AUC = 0.7). Immunoglobulin light chain-positive CLL MRD was visually identified on a pre-calculated UMAP plot as a single-colored cluster, after dual coloring for kappa and lambda. The use of AI-enhanced files reduced manual analysis time from 11.6 minutes (SD = 4.5) to 0.8 minutes (SD = 0.4) per case, on average (p < 0.01) (93% reduction). CLL MRD was detected in all positive cases above clinically relevant threshold (≥0.01%, as recommended by NCCN guidelines), and in 17 of 21 (81%) cases below this threshold, with excellent quantitative correlation with conventional analysis on original FC files (linear regression slope = 1.02, intercept = 0.001%, R squared = 0.98, P < 0.0001). Conclusion: We introduce a largely unsupervised AI pipeline that transforms raw CLL-MRD FC data into a markedly smaller, AI-annotated and software-agnostic FC file, including comparison to normal controls. This CCADDAS pipeline simplifies and accelerates detection of CLL-MRD in clinical diagnostics, reducing number of cells analyzed by 85% and manual analysis time by 93%, without impacting test performance. Moreover, CCADDAS can be utilized for any laboratory-developed CLL-MRD assay, and its small-sized export is compatible with any clinical FC software, computing platform and analysis strategy. Adoption of CCADDAS is likely to facilitate the implementation of CLL MRD FC analysis by more clinical laboratories.

Introduction: Advances in AI have enabled the generation of synthetic individual patient data (SynthIPD) that mimics the statistical properties of the real IPD, which can help generate subgroup-specific insights in the absence of subgroup-specific IPD. We apply this technology in evaluating Daratumumab treatment benefit in high-risk cytogenetic multiple myeloma subgroup. The addition of daratumumab to standard multiple myeloma (MM) regimens has been associated with improved response rates and clinical outcomes. A systematic review (meta-analysis) enables further evaluation of the effectiveness of daratumumab for MM patients with high-risk cytogenetic factors. However, concerns have been raised about meta-analyses due to the statistical model assumptions they impose. This study aims to address these limitations by employing SynthIPD to provide a more robust analysis. Methods: This study focuses on newly diagnosed multiple myeloma (NDMM) and relapsed or refractory multiple myeloma (RRMM) patients with high-risk cytogenetic profiles. We included six published studies: ALCYONE, CASSIOPEIA, and MAIA for NDMM, and CANDOR, CASTOR, and POLLUX for RRMM. Large language models were used to extract up-to-date clinical evidence from the literature. SynthIPD including cytogenetic risk profile were generated via digitization and an innovative optimization algorithm. Meta-analyses based on random effects models were then conducted, and the results were compared with those from pooled analyses using synthetic data. Results: SynthIPD for cytogenetic high-risk patients were generated for three studies for NDMM: ALCYONE (treatment vs control: n=53 vs n=45), CASSIOPEIA (n=82 vs n=86), MAIA (n=48 vs n=44); and three studies for RRMM: CANDOR(n=48 vs n=26), CASTOR (n=40 vs n=35), POLLUX (n=35 vs n=35). The generated hazard ratios (HRs) for each study closely aligned with the reported HRs for high-risk patients, with a maximum relative error of less than 2%. By pooling these datasets, we obtained SynthIPD datasets for NDMM and RRMM patients. Stratified Cox regression analyses yielded HRs of 0.764 (95% CI 0.529-1.104) for NDMM and 0.431 (95% CI 0.294-0.613) for RRMM. Random-effects meta-analyses showed HRs of 0.764 (95% CI 0.529-1.104) for NDMM and 0.425 (95% CI 0.287-0.621) for RRMM. Compared with traditional meta-analysis techniques, the synthetic data approach provides additional clinical insights that were not available in the original publications. For instance, the clinical results for the six studies within high-risk group (e.g., KM curves in high-risk subgroup) can be reproduced, which were not reported in the original studies. Conclusion: AI-generated synthetic data enhances the robustness of conventional meta-analysis outcomes. The identification of HRs and corresponding confidence intervals through SynthIPD enhances the credibility of our proposed method, offering a reliable approach to evaluating the efficacy of daratumumab in high-risk patients. Since SynthIPD includes individual covariate information, any statistical results derived from the original IPD can be effectively approximated using SynthIPD. Using the SynthIPD, we show that the addition of daratumumab to standard regimens improves PFS for RRMM patients with high-risk cytogenetic factors, although its benefit for NDMM patients is not statistically significant. This analysis can be extended to other multiple myeloma high risk subgroups.

Abstract Task Group (TG) 314 of the American Association of Physicists in Medicine (AAPM) was charged to develop guidance for recovering from fault states in radiation therapy, specifically regarding the delivery of photon or electron beams using a linear accelerator (linac) including ancillary systems. The fault conditions addressed may involve software, hardware, or a combination of causes. The report provides detailed recommendations for the proactive steps to be taken before a fault, the actions to be taken at the time of a fault, and the safety steps before returning a linac to clinical service, as well as the activities that device manufacturers and standard organizations can do to prevent and resolve the faults. A user‐maintained log of prior faults; establishment of remote access by the vendor; and user training in emergency gantry, couch, and door motions are all useful proactive steps. At the moment of downtime and after ensuring the safety of the patient, the report stresses the importance of capturing fault information, prompt contact with the service engineer after the initial assessment, and considerations for communicating the estimated duration before the linac is returned to service. The medical physicist has a critical responsibility to assess the impact of the fault on patient care. Before resuming clinical use, the medical physicist must both determine the level of testing required to ensure safe operation of the linac and ensure any partially or totally delivered treatments have been correctly saved for accurate completion of the treatment fraction. The report stresses the roles of the radiation therapist, medical physicist, and service engineer to efficiently and safely address linac downtime. The appendices contain a description of the efforts of several organizations regarding linac safety: Integrating the Healthcare Enterprise—Radiation Oncology, International Standards Organization/International Electrotechnical Commission, Radiation Oncology Safety Stakeholder Initiative, and the AAPM Vendor Relations and Product Usability Subcommittee. Disclaimer: The recommendations of this TG should not be used to establish regulations. These recommendations are guidelines for Qualified Medical Physicists and others to use and appropriately interpret for their institution and clinical setting. Each institution may have site‐specific or state‐mandated needs and requirements which may modify their usage of these recommendations.

Background: With demographic trends transitioning towards older adults, dementia and cognitive impairment are predicted to increase dramatically. We aim to elucidate the relationship between subclinical myocardial injury, as indicated by asymptomatic increased levels of high-sensitivity cardiac Troponin (hs-cTnT), and cognitive performance. Methods: We studied MESA participants from Exam 1 (2000-02) to Exam 6 (2016-18), categorizing them based on baseline hs-cTnT at Exam 1. Cognitive decline was defined as a decrease of ≥5 units in CASI between Exam 5&6. We used Pearson correlation and linear regression to analyze the association of hs-cTnT levels with CASI scores, and logistic regression to examine the association with cognitive decline. We also explored the relationship between different hs-cTnT categories and cognitive measures. Models were adjusted for demographics, lifestyle, APOE status, comorbidities, and medication use ( Figure ). Results: 4445 participants had both baseline hs-cTnT and valid Exam 5 CASI scores while only 1776 participants had valid Exam 6 CASI scores. Cohort was predominantly female (53%), mean age of 60 years, and 27% had at least one APOE e4 allele. Median hs-cTnT was 6.32 ng/L, and median CASI scores were 89 at Exam 5 and 91.5 at Exam 6. We found a negative correlation between the log-hs-cTnT at Exam 1 and Exam 5 with CASI scores at Exam 5. An increase of one unit in log-hs-cTnT level was associated with a decrease of 0.67 (CI -1.17, -0.17) in CASI and corresponded to higher odds (OR: 1.44; CI 1.05-1.95) of cognitive decline, after adjusting for covariates. When comparing various categories of hs-cTnT with category 1, we observe that the odd of cognitive decline increases as the category increases. However, this trend does not hold for category 5 with significantly lower sample size ( Figure ). Conclusion: Our findings indicate an inverse relationship between hs-cTnT and cognitive function years later, which is significantly attenuated by known risk factors for cognitive decline. Further research is needed to determine hs-cTnT as a predictor of future global cognitive functions.

Abstract This study reports the first pig-to-human lung xenotransplantation using a six gene-edited pig lung. A left lung from a gene-edited Chinese Bama Xiang pig was transplanted into a 39-year-old brain-dead human recipient. The xenograft maintained viability and functionality for 216 hours without signs of hyperacute rejection. Postoperatively, severe edema resembling primary graft dysfunction (PGD) was observed, potentially due to ischemia-reperfusion injury. Antibody-mediated rejection appeared to contribute to xenograft damage on postoperative days 3 and 6, with partial recovery by day 9 under the current immunosuppressive regimen. This pioneering study suggests that genetically modified pig lungs could potentially be used for future clinical applications in xenotransplantation.