tbuckley/cabot-search huggingface dataset:
An ALK2 inhibitor, BLU-782, prevents heterotopic ossification in a mouse model of fibrodysplasia ossificans progressiva
Authors: Alison J. Davis, Natasja Brooijmans, Jason D. Brubaker, Faith Stevison, Timothy P. LaBranche, Faris Albayya, Paul Fleming, Brian L. Hodous, Joseph L. Kim, Sean Kim, Riadh Lobbardi, Michael Palmer, Michael P. Sheets, John Vassiliadis, Ruduan Wang, Brett D. Williams, Douglas Wilson, Lan Xu, Xing Julia Zhu, Keith Bouchard, Jeffrey W. Hunter, Chris Graul, Elliot Greenblatt, Amira Hussein, Morgan Lyon, Joelle Russo, Rachel Stewart, Marion Dorsch, Timothy J. Guzi, Vivek Kadambi, Christoph Lengauer, Andrew P. Garner
Journal: Science Translational Medicine (2024)

Fibrodysplasia ossificans progressiva (FOP) is a rare genetic disease driven by gain-of-function variants in activin receptor–like kinase 2 (ALK2), the most common variant being ALK2 R206H . In FOP, ALK2 variants display increased and dysregulated signaling through the bone morphogenetic protein (BMP) pathway resulting in progressive and permanent replacement of skeletal muscle and connective tissues with heterotopic bone, ultimately leading to severe debilitation and premature death. Here, we describe the discovery of BLU-782 (IPN60130), a small-molecule ALK2 R206H inhibitor developed for the treatment of FOP. A small-molecule library was screened in a biochemical ALK2 binding assay to identify potent ALK2 binding compounds. Iterative rounds of structure-guided drug design were used to optimize compounds for ALK2 R206H binding, ALK2 selectivity, and other desirable pharmacokinetic properties. BLU-782 preferentially bound to ALK2 R206H with high affinity, inhibiting signaling from ALK2 R206H and other rare FOP variants in cells in vitro without affecting signaling of closely related homologs ALK1, ALK3, and ALK6. In vivo efficacy of BLU-782 was demonstrated using a conditional knock-in ALK2 R206H mouse model, where prophylactic oral dosing reduced edema and prevented cartilage and heterotopic ossification (HO) in both muscle and bone injury models. BLU-782 treatment preserved the normal muscle-healing response in ALK2 R206H mice. Delayed dosing revealed a short 2-day window after injury when BLU-782 treatment prevented HO in ALK2 R206H mice, but dosing delays of 4 days or longer abrogated HO prevention. Together, these data suggest that BLU-782 may be a candidate for prevention of HO in FOP.
Optimizing thiopurine therapy in autoimmune hepatitis: A multi-center study on monitoring metabolite profiles and co-therapy with allopurinol
Authors: Jan Philipp Weltzsch, Claudius F. Bartel, Moritz Waldmann, Thomas Renné, Stephanie Schulze, Benedetta Terziroli Beretta-Piccoli, Maria Papp, Ye H. Oo, Vincenzo Ronca, Marcial Sebode, Ansgar W. Lohse, Christoph Schramm, Johannes Hartl
Journal: Hepatology (2024)

In autoimmune hepatitis, achieving complete biochemical remission (CBR) with current weight-based thiopurine dosing is challenging. We investigated whether patients could be stratified regarding CBR according to a target range of thiopurine metabolites. Moreover, we explored the effects of azathioprine dosage increases and co-therapy of allopurinol with low-dose thiopurines on metabolite profiles and treatment response.
Platelets harness innate immunity to promote the dissemination of HCC
Authors: Stefania Mantovani, Mario U. Mondelli
Journal: Hepatology (2024)

1Research Department, Division of Clinical Immunology - Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy 2Department of Internal Medicine and Therapeutics, University of Pavia, Italy Abbreviations: CTC, circulating tumour cells; CTLA4, Cytotoxic T-Lymphocyte Antigen 4; DNAM-1, DNAX Accessory Molecule-1; FAK/JNK/c-Jun, Focal adhesion kinase c-Jun N-terminal kinase; HCC, hepatocellular carcinoma; MASLD, metabolic dysfunction-associated steatotic liver disease; NK, natural killer; PD-1, PD-L1, programmed cell death protein 1 and ligand; TIGIT, T cell immunoreceptor with Ig and ITIM domains; TriKE, Tri-specific killer engager. Correspondence Mario U. Mondelli, Division of Clinical Immunology and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, viale Golgi 19, 27100, Pavia. Email: [email protected]
FAPI PET Imaging Supports Clinical Decision Making in Academic Cardiology Practice
Authors: Stephan Settelmeier, Lukas Kessler, Zohreh Varasteh, Amir A. Mahabadi, Lars Michel, Maria Papathanasiou, Christina Laschinsky, Christoph Rischpler, Wolfgang P. Fendler, Thomas Schlosser, Lale Umutlu, Ken Herrmann, Tienush Rassaf, David Kersting
Journal: JACC. Cardiovascular imaging (2024)

A dvances in nuclear cardiology molecular imaging improve decision making in clinical cardiology.Fibroblast activation protein alpha (FAP) is a homodimeric membrane-bound serine protease with intracellular and extracellular soluble forms.Positron emission tomography (PET) imaging using radiolabeled fibroblast activation protein alpha inhibitors (FAPIs) has emerged as a promising molecular imaging tool for oncology but also cardiology, possibly providing new insights into the pathophysiology of diseases.FAP is specifically expressed by early-stage activated fibroblasts during wound healing and cardiac remodeling.Therefore, FAPI PET provides a unique opportunity to visualize and quantify cardiac fibrosis, a key pathophysiological process involved in several cardiovascular diseases.Hence, this imaging modality is a powerful tool that can aid in clinical decision making.The complete potential of FAPI PET in nuclear cardiology has not been recognized fully to date.The purpose of this pictorial imaging vignette is to demonstrate potential applications of this modality in understanding the pathophysiologic aspects of common and rare myocardial diseases. STRUCTURE OF IMAGING VIGNETTEPET/computed tomography (CT) or PET/magnetic resonance imaging (MRI) was performed using 68 Ga-labeled Ga]Ga-FAPI-46) according to our established imaging protocols (administered activities and imaging delays are provided in Figures 1 to 10).Images are presented from top to bottom clockwise (when applicable) as follows: [ 68 Ga]Ga-FAPI-46 PET maximum-intensity projection (anterior view), myocardial 3-dimensional rendering, bull's-eye representation, and multiplanar reconstructions (transversal and sagittal view); CT/MRI transversal and sagittal view; PET/CT or PET/MRI fusion transversal and sagittal view; and echocardiography parasternal long axis and apical 4-chamber view.If available, other patient-specific molecular imaging modalities are supplemented.
Functional ultrasound imaging of human brain activity through an acoustically transparent cranial window
Authors: Claire Rabut, Sumner L. Norman, Whitney S. Griggs, Jonathan J. Russin, Kay Jann, Vasileios Christopoulos, Charles Liu, Richard A. Andersen, Mikhail G. Shapiro
Journal: Science Translational Medicine (2024)

Visualization of human brain activity is crucial for understanding normal and aberrant brain function. Currently available neural activity recording methods are highly invasive, have low sensitivity, and cannot be conducted outside of an operating room. Functional ultrasound imaging (fUSI) is an emerging technique that offers sensitive, large-scale, high-resolution neural imaging; however, fUSI cannot be performed through the adult human skull. Here, we used a polymeric skull replacement material to create an acoustic window compatible with fUSI to monitor adult human brain activity in a single individual. Using an in vitro cerebrovascular phantom to mimic brain vasculature and an in vivo rodent cranial defect model, first, we evaluated the fUSI signal intensity and signal-to-noise ratio through polymethyl methacrylate (PMMA) cranial implants of different thicknesses or a titanium mesh implant. We found that rat brain neural activity could be recorded with high sensitivity through a PMMA implant using a dedicated fUSI pulse sequence. We then designed a custom ultrasound-transparent cranial window implant for an adult patient undergoing reconstructive skull surgery after traumatic brain injury. We showed that fUSI could record brain activity in an awake human outside of the operating room. In a video game “connect the dots” task, we demonstrated mapping and decoding of task-modulated cortical activity in this individual. In a guitar-strumming task, we mapped additional task-specific cortical responses. Our proof-of-principle study shows that fUSI can be used as a high-resolution (200 μm) functional imaging modality for measuring adult human brain activity through an acoustically transparent cranial window.
Reply: Regarding the use of decision curve analysis in predicting long-term complications of liver cirrhosis
Authors: Chengnan Guo, Zhenqiu Liu, Tiejun Zhang
Journal: Hepatology (2024)

1Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China 2Department of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety (Fudan University), Ministry of Education, Fudan University, Shanghai, China 3State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai, China 4Fudan University Taizhou Institute of Health Sciences, Taizhou, China Abbreviations: APRI, aspartate aminotransferase to platelet ratio index; DCA, decision curve analysis; FIB-4, fibrosis-4 index. Correspondence Tiejun Zhang, Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China. Email: [email protected]
Treatment patterns among HCPs and concordance with expert recommendations in HER2-negative early breast cancer: Analysis of an interactive online treatment decision support tool.
Authors: Kelly G Brandt, Marie N. Becker, Tanya Gupta, Kevin Kalinsky, Laura Spring, Tiffany A. Traina, Denise A. Yardley, Kristen M. Rosenthal
Journal: Journal of Clinical Oncology (2024)

e13601 Background: Management of HER2- EBC continues to evolve with expansion of targeted therapies, including abemaciclib, olaparib, and pembrolizumab, in the adjuvant setting for eligible pts. We sought to identify contemporary practice patterns among HCPs for HER2- EBC and compare them with those of experts using an online interactive decision support tool. Methods: An online decision support tool was developed with input from 5 BC experts to provide tx recommendations for 19 unique pt case scenarios based on considerations including subtype, tx history, and recurrence risk. HCPs entered specific patient criteria along with their intended management for that case, and then were shown 5 expert recommendations. HCPs were asked if the recommendations impacted their intended approach. An analysis of expert recommendations and HCP-selected tx was performed. Results: Between Oct 2023 and Jan 2024, 83 HCPs entered 105 cases. Of the 97 cases where HCPs noted a definitive tx plan, recommendations were discordant from experts in 29%. The most commonly queried cases, expert recommendations, and discordance between HCPs and experts are outlined in the table. Discord with experts was similar among HCP tx plans for cases of TNBC (33%) and HR+/HER2- EBC (27%). HCPs predominantly sought guidance for pts with HR+/HER2- EBC, no g BRCAm, and high-risk disease per monarchE trial criteria (79%), with 22% discordance from expert recommendations. Regardless of BC subtype, the highest level of discord between HCPs and experts (67%) was observed in cases where pts had received neoadjuvant tx and had no residual disease following surgery, although this represents a small subset (n = 12). When asked if the expert recommendations changed their tx choice, 7 of 27 (26%) HCPs who responded indicated that expert recommendations changed their intended tx, whereas 15% noted that there were barriers to implementing those recommendations. Conclusions: These data suggest ongoing challenges with incorporating the newest targeted therapies for high-risk EBC management. Continued education and development of resources for HCPs, including online decision support tools, may be increasingly important as the treatment of EBC continues to evolve. [Table: see text]
Objective acuity measures for infusion therapy staffing: A predictive model approach—Phase I.
Authors: Alden Egan, Daniela Gehrke, Bo He, Jody S. Garey, Ping Ye, Debra Shapert, Jennifer Sassano, Ashley Garnett, Sonia Velador, Judi Payne-De Bock
Journal: Journal of Clinical Oncology (2024)

e13553 Background: Acuity is a measure of the complexity of patient care and an estimate of nursing workload. The use of acuity tools is shown to improve care standards, nurse satisfaction and productivity. Existing acuity tools have barriers to adoption, including increased nursing workload, estimate variations among different nurses and clinical care settings, and poor understanding of validity of acuity measures. We aim to build a predictive model for prospectively determining acuity levels and staffing requirements in infusion therapy to address these gaps. This project will be implemented with a phased approach. Here we describe Phase I, to establish a standard measure and documentation process for acuity, then collect and analyze a large data set to quantify the relationship of acuity scores to selected patient characteristics. Methods: A US Oncology Network nursing committee developed evidence-based guidelines for acuity measurement and documentation in August 2023. Nine sites from four independent, community oncology practices were selected to perform acuity rating and documentation using the developed guidelines. Multiple training sessions on the guidelines were conducted with nurses from selected sites. Nurses documented acuity scores (level 1~6) and start time for patients’ infusion visits in the EHR 8/30/2023 – 11/30/2023. Acuity documentation rates were calculated and provided to each site weekly to gain feedback and engagement. Acuity scores were extracted from the electronic health record using natural language processing. Structured data on potential predictors including patient demographics, performance status, lab, and treatment-related information were also collected. Results: A total of 14,610 infusion room visits (5,139 distinct patients) with documented acuity scores were reported. The acuity documentation rate from each site was consistent by week and ranged 60 – 96%. Table reports prevalence of select features by acuity score. Conclusions: An operational workflow was successfully implemented to collect and analyze acuity scores and relevant features. Features of interest include chemotherapy Cycle 1 Day 1, five or more drugs and highly emetogenic treatment. In Phase II, the collected acuity scores and clinical features will be used to build a predictive model to objectively estimate acuity. Phase III will focus on the deployment of the predictive model to oncology practices. [Table: see text]
OncoGPT: Enhancing oncological decision-making with ASCO guideline–trained AI.
Authors: Ramy El-Assal, Aziz Nazha
Journal: Journal of Clinical Oncology (2024)

e13607 Background: General-purpose language models like ChatGPT, while proficient in a wide array of topics, often lack the specialized knowledge and precision required for specific fields such as oncology. The American Society of Clinical Oncology (ASCO) guidelines offer a comprehensive resource for oncology professionals, yet sifting through extensive documents for specific information can be daunting. To bridge this gap, we introduce OncoGPT, a specialized GPT model, tailored to provide precise and guideline-adherent oncological advice. Methods: We leveraged GPT-4's advanced language understanding capabilities as the foundation for OncoGPT. This customization involved an extensive training regimen using the complete text of the ASCO clinical guidelines. The training process was meticulously designed to ensure that OncoGPT not only assimilates the detailed information within these guidelines but also understands the context and intricacies of oncological care. Additionally, we created disease-specific versions of OncoGPT, each fine-tuned with guideline subsets pertinent to particular oncological conditions. Further, the training was augmented with specific prompts to foster kind, sincere, and respectful interactions, especially for patient-oriented responses. The model was designed to discern whether the user is a healthcare professional or a patient and adjust the complexity of its responses accordingly. For patients, additional emphasis was placed on delivering information in a kind, responsible, and empathetic manner. Results: OncoGPT's performance was rigorously evaluated for accuracy and reasoning against real-world clinical scenarios. The responses generated by the model were meticulously reviewed by an experienced oncologist to confirm adherence to ASCO guidelines and clinical relevance. This assessment revealed a high level of precision and contextual understanding in OncoGPT's outputs, demonstrating its potential as a valuable tool for oncology practitioners. Importantly, it showed a remarkable ability to tailor its communication style based on the user's background, providing simplified explanations for patients and more detailed responses for professionals. An example of a specific OncoGPT: Breast Cancer OncoGPT: https://chat.openai.com/g/g-VcuECT3jg-oncogpt-breast-cancer Conclusions: OncoGPT represents a significant advancement in the application of AI for medical decision-making. By integrating the depth of ASCO guidelines into a responsive and accurate AI model, OncoGPT offers oncology professionals a powerful tool for accessible, guideline-compliant advice. This development marks a crucial step towards integrating AI more profoundly into specialized medical fields, enhancing both the efficiency and accuracy of clinical decision-making.
Implementation of a virtual tumor board through VA National TeleOncology service.
Authors: Akiko Chiba, Gina McWhirter, Haley Moss, Sarah Violet Colonna, Thomas David Rodgers, Sushma Jonna, Margaret O Johnson, David C. Van Echo, Michael J. Kelley, Vida Almario Passero
Journal: Journal of Clinical Oncology (2024)

e13571 Background: Multidisciplinary tumor boards are critical to optimize treatment of patients with malignancies. The Veterans Affairs (VA) National TeleOncology (NTO) service was created to provide equitable, state of the art oncologic care virtually to centers across the largest integrated health care system in the US. According to American Society of Clinical Oncology report, 66% of rural counties have no oncologist. Fifty-six percent of Veterans who received cancer care through NTO in 2022 lived in rural areas. We describe a virtual multi-institutional, multidisciplinary tumor board across several malignancies. Through NTO, virtual tumor board (VTB) demonstrates a novel approach to leveraging nationwide oncologic expertise to support patients receiving cancer care at VA Medical Centers (VAMC) across the US. Methods: A VTB was conducted with participation of multiple VAMCs throughout the US. There were five separate VTB oncologic sub-specialties: hematologic, breast/gynecologic, CNS, thoracic and cutaneous malignancies. Each case was presented by the treating provider or designated representative. Pathology and pertinent imaging were reviewed and presented by disease-specific expert specialists. Core attendees included medical oncologists, surgical oncologists, radiation oncologists, pathologists, radiologists, genetic counselors, clinical pharmacists, advanced practice providers and nurses. VTB records were analyzed from VTB inception on March 1, 2022 to February 1, 2024. Data collected included attendance and case presentation information. Results: A total of 113 VTB sessions were conducted every 2 weeks to monthly depending on specialty (35 hematologic, 32 beast/gyn, 24 thoracic, 13 CNS, 9 cutaneous malignancies) with a total of 233 patient cases presented from 51 VA facilities in 33 states and Puerto Rico. The total unique attendees were 468 in 41 states, DC and Puerto Rico. The highest case volume per VA location were from Durham, Houston, Pittsburgh, Sioux Falls and Salem. The highest attendee locations included Durham, Boston, Palo Alto, Pittsburgh, and Richmond. Conclusions: This study demonstrates the feasibility of a national multi-institutional, multi-disciplinary VTB. Tumor board sessions provide access to specialized oncologic expertise with the goal of improving cancer care across the entire VA healthcare system. Further growth of national VTB to increase participation at additional sites and incorporated discussion of clinical trials is ongoing. Future research evaluating quality and outcomes for those cases discussed at VTB will be considered.
Prediction of therapeutic response and cancer outcomes in solid tumours via in silico clinical trials.
Authors: Uzma Saddia Asghar, Matthew Griffiths, Amanzhol Kubeyev, Jordan Laurie, Andrea Giorni, Luiz A Zillmann da Silva, Prabu Sivasubramaniam, Matthew Foster, Andrew V. Biankin
Journal: Journal of Clinical Oncology (2024)

e13603 Background: Oncology therapeutic development has high failure rates with substantial costs. Advances in technology, including molecular characterisations of cancer and computational power, provide the opportunity to better model therapeutic response for existing and emerging therapies. Methods: Concr adapted Bayesian statistical principles used by astrophysicists to effectively integrate multi-dimensional data (genomic &amp; transcriptomic) for accurate modelling of cancer biology. Our proprietary computational framework was applied to predict clinical response and survival through construction of digital twins and in silico simulations of clinical trials. Predicted log odds ratios (LOR) were generated for drug response and compared to published data from 8 suitable historical clinical trials. Three distinct models underpin this framework: Drug Efficacy, Treatment Response &amp; Overall Survival (OS). Three publicly available datasets were used for training: Cancer Therapeutic Response Portal ( in vitro dose-response data), Cancer Cell Line Encyclopaedia and TCGA. Results: For all 8 clinical studies, the digital twin model accurately simulated both trial arms, compared drug efficacy across arms and predicted which treatment was most active. Unblinded evaluation: Our model accurately predicted gemcitabine would have greater clinical benefit than 5-FU (LOR -0.10, P &lt;0.0001) in metastatic pancreatic cancer. In advanced breast cancer, the model predicted docetaxel had a higher response rate than doxorubicin, and carboplatin response rates were similar to docetaxel in BRCA wild-type patients. In platinum-sensitive recurrent ovarian cancer, the model predicted cisplatin-based combination had a higher response rate than paclitaxel. Blinded evaluation: Using data for paclitaxel, the model correctly predicted that nab-paclitaxel+gemcitabine response rates were higher than gemcitabine in metastatic pancreatic cancer (predicted LOR -0.090, p = &lt;0.001). In all 3 early breast cancer studies, predictions mirrored clinical trial results, adjuvant ECF &gt; CMF, adjuvant TC &gt; AC and adjuvant tamoxifen was superior to capecitabine. The underlying pan-tumour Overall Survival model used a Random Survival Forest approach, trained on 23 cancers with predictive accuracy of 0.78 AUC ROC and C-index 0.71. To enable cohort enrichment for drug response, the model segmented patient cohorts into treatment responder and non-responder. Using this approach, the log odds increased for drug response rate for 16 of the 19 different cancers and 14 of the different 17 drugs. Conclusions: Our digital twin model represents transformative technology for clinical trial simulation with strong potential for accelerating and de-risking clinical drug development, and utility for synthetic control arms.