Biomedical Informatics Commons^™

Allosteric Targeted Drug Delivery For Enhanced Blood-Brain Barrier Penetration Via Mimicking Transmembrane Domain Interactions, Kaicheng Tang, Zhongjie Tang, Miaomiao Niu, Zuyin Kuang, Weiwei Xue, Xinyu Wang, Xinlong Liu, Yang Yu, Seongdong Jeong, Yifan Ma, Annette Wu, Betty Y S Kim, Wen Jiang, Zhaogang Yang, Chong Li

Faculty, Staff and Student Publications

Current strategies for active targeting in the brain are entirely based on the effective interaction of the ligand with the orthosteric sites of specific receptors on the blood-brain barrier (BBB), which is highly susceptible to various pathophysiological factors and limits the efficacy of drug delivery. Here, we propose an allosteric targeted drug delivery strategy that targets classical BBB transmembrane receptors by designing peptide ligands that specifically bind to their transmembrane domains. This strategy prevents competitive interference from endogenous ligands and antibodies by using the insulin receptor and integrin α

Cognitive Correlates Of Borderline Personality Disorder Features In Youth With Bipolar Spectrum Disorders And Bipolar Offspring, Alessio Simonetti, Sherin Kurian, Evelina Bernardi, Antonio Restaino, Francesca Bardi, Claudia Calderoni, Gabriele Sani, Jair C Soares, Kirti Saxena

Faculty, Staff and Student Publications

Background: Bipolar disorder (BD) and borderline personality disorder (BPD) share common cognitive impairments. These deficits are also shared by bipolar offspring (BD-OFF). Nevertheless, little is known regarding the association between cognitive impairments and BPD features in youth with BD and BD-OFF. Objectives: This study aimed to investigate the association between BPD features and cognitive impairments in youth with BD and BD-OFF.

Methods: Thirty-nine participants (7-17 years) with BD, 18 BD-OFF, and 50 healthy controls (HCs) were recruited. BPD features were assessed using the Borderline Personality Features Scale for Children (BPFS-C). Deficits in executive functions and affective processing were assessed using …

Her2-Selective Tyrosine Kinase Inhibitor, Zongertinib (Bi 1810631), In Patients With Advanced/Metastatic Solid Tumors With Her2 Alterations: A Phase Ia Dose-Escalation Study, John V Heymach, Frans Opdam, Minal Barve, Hai-Yan Tu, Yi-Long Wu, David Berz, Lukas Schröter, Yanick Botilde, Behbood Sadrolhefazi, Josep Serra, Kiyotaka Yoh, Noboru Yamamoto

Faculty, Staff and Student Publications

Purpose: Human epidermal growth factor receptor 2 (HER2) alterations occur in many solid cancers, including non-small cell lung cancer (NSCLC). Beamion LUNG-1 (ClinicalTrials.gov identifier: NCT04886804) is assessing the safety/efficacy of zongertinib (BI 1810631), a novel HER2-selective tyrosine kinase inhibitor that spares epidermal growth factor receptor, in patients with HER2-altered solid tumors.

Materials and methods: Beamion LUNG-1 is an ongoing multicenter, multicohort phase Ia/Ib trial. Phase Ia assessed zongertinib administered twice a day (15-150 mg) or once daily (60-360 mg) in pretreated patients with various tumors, including NSCLC. Primary end points were maximum tolerated dose (MTD) and dose-limiting toxicities (DLTs); …

The Zbtb24-Cdca7-Hells Axis Suppresses The Totipotent 2c-Like Reprogramming By Maintaining Dux Methylation And Repression, Dan Guo, Zeling Du, Youqi Liu, Meiqi Lin, Yue Lu, Swanand Hardikar, Yanna Xue, Jinghong Zhang, Taiping Chen, Jiameng Dan

Faculty, Staff and Student Publications

Two-cell-like cells (2CLCs), a rare population (∼0.5%) in mouse embryonic stem cell (mESC) cultures, are in a transient totipotent-like state resembling that of 2C-stage embryos, and their discovery and characterization have greatly facilitated the study of early developmental events, such as zygotic genome activation. However, the molecular determinants governing 2C-like reprogramming remain to be elucidated. Here, we show that ZBTB24, CDCA7, and HELLS, components of a molecular pathway that is involved in the pathogenesis of immunodeficiency, centromeric instability, and facial anomalies (ICF) syndrome, function as negative regulators of 2C-like reprogramming by maintaining DNA methylation of the Dux cluster, a master …

Geographic Divergence Of Methicillin-Resistant Staphylococcus Aureus St5-Scc Mec I In The Aftermath Of A Major Earthquake And Tsunami: Impact Of A Plasmid Harboring Heavy Metal Resistance Genes, Jose R W Martínez, Manuel Alcalde-Rico, Estefanía Jara-Videla, Jinnethe Reyes, Lina P Carvajal, Sandra Rincon, Rafael Ríos, Lorena Diaz, Ana Quesille-Villalobos, Roberto Riquelme-Neira, Lina Rivas, Ahmed M Moustafa, Blake Hanson, Eduardo A Undurraga, Jorge Olivares-Pacheco, Patricia García, Rafael Araos, Paul J Planet, César A Arias, Jose M Munita

Faculty, Staff and Student Publications

Methicillin-resistant Staphylococcus aureus (MRSA) is a major public health menace. The global spread of MRSA is characterized by successive waves of epidemic clones dominating specific geographical regions. The acquisition of genes encoding resistance to heavy metals (HMRGs) is thought to be a key feature in the geographic divergence of MRSA. However, the cause-effect relationship between the presence of HMRGs and the divergence of MRSA clones remains to be clarified. In this study, we assessed the role that HMRGs may have played in the evolutionary divergence of the MRSA ST5-SCCmecI lineage in Latin America. We conducted a genomic characterization …

An In Vivo Microscopy Dataset For The Characterization Of Leukocyte Death, Alain Pulfer, Diego Ulisse Pizzagalli, Miguel Palomino Segura, Nina Germic, Tommaso Virgilio, Mauro Di Pilato, Pau Carrillo Barbera, Elisa Palladino, Paola Antonello, Marcus Thelen, Hans-Uwe Simon, Rolf Krause, Santiago F Gonzalez

Faculty, Staff and Student Publications

Recent advancements in intravital microscopy have enabled the study of cell death in vivo under various experimental conditions, such as infection and cancer. However, the limited throughput of this technology, together with a lack of openly accessible datasets, affects the development of algorithms for the automatic detection and characterization of cell death, which in turn require the integration of extensive and curated datasets. To address these needs, we present a curated dataset of microscopy videos depicting the death of neutrophils, eosinophils, and dendritic cells, acquired in the spleen and in the lymph node of mice under inflammatory conditions. The dataset …

Phase 2 Trial Of Ibrutinib And Nivolumab In Patients With Relapsed Cns Lymphomas, Dai Chihara, Raphael E Steiner, Ranjit Nair, Lei Feng, Sairah Ahmed, Paolo Strati, Luis Malpica, Donna P Griffith, Shivon A Mathew, Wirt Montinez, Gita Masand, Felipe Samaniego, Maria A Rodriguez, Fredrick B Hagemeister, Luis E Fayad, Swaminathan P Iyer, Loretta J Nastoupil, Sattva S Neelapu, Christopher R Flowers, Jason R Westin

Faculty, Staff and Student Publications

Treatment options are limited for both relapsed/refractory primary and secondary central nervous system (CNS) lymphoma and the prognosis remains poor. Previous studies have shown the activity of Bruton tyrosine kinase inhibitors and programmed death-1-targeted therapies in CNS lymphoma, and studies suggested potential synergy. Therefore, we conducted a phase 2 trial that combined ibrutinib with nivolumab for patients with relapsed/refractory CNS lymphoma. Patients received 560 mg oral ibrutinib daily with 240 mg IV nivolumab every 14 days (28 days per cycle). Patients who had partial or complete response after 6 cycles of treatment could continue therapy for up to 2 years …

Identifying The Human Olfactory And Chemosignaling Neural Networks Using Event Related Fmri And Graph Theory, Saideh Ferdowsi, Tom Foulsham, Alireza Rahmani, Dimitri Ognibene, Luca Citi, Wen Li

Faculty, Staff and Student Publications

This study aims to characterize and compare the functional neural networks associated with different olfactory stimuli, including air, non-social odours, and human body odours. We introduce a novel processing pipeline based on event-related functional magnetic resonance imaging (fMRI) and graph theory for network identification. To ensure the stability and small worldness of the characterized networks, we conduct statistical validations, network modularity assessments, and robustness measurement against local attacks. The key hypothesis is that human body odours (so-called social odours) and non-social odours engage distinct neural networks, particularly in regions responsible for social processing. We found that the posterior medial orbitofrontal …

Mri-Based Digital Twins To Improve Treatment Response Of Breast Cancer By Optimizing Neoadjuvant Chemotherapy Regimens, Chengyue Wu, Ernesto A B F Lima, Casey E Stowers, Zhan Xu, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane M Rauch, Thomas E Yankeelov

Faculty, Staff and Student Publications

We developed a practical framework to construct digital twins for predicting and optimizing triple-negative breast cancer (TNBC) response to neoadjuvant chemotherapy (NAC). This study employed 105 TNBC patients from the ARTEMIS trial (NCT02276443, registered on 10/21/2014) who received Adriamycin/Cytoxan (A/C)-Taxol (T). Digital twins were established by calibrating a biology-based mathematical model to patient-specific MRI data, which accurately predicted pathological complete response (pCR) with an AUC of 0.82. We then used each patient's twin to theoretically optimize outcome by identifying their optimal A/C-T schedule from 128 options. The patient-specifically optimized treatment yielded a significant improvement in pCR rate of 20.95-24.76%. Retrospective …

A Folding-Docking-Affinity Framework For Protein-Ligand Binding Affinity Prediction, Ming-Hsiu Wu, Ziqian Xie, Degui Zhi

Faculty, Staff and Student Publications

Accurate protein-ligand binding affinity prediction is crucial in drug discovery. Existing methods are predominately docking-free, without explicitly considering atom-level interaction between proteins and ligands in scenarios where crystallized protein-ligand binding conformations are unavailable. Now, with breakthroughs in deep learning AI-based protein folding and binding conformation prediction, can we improve binding affinity prediction? This study introduces a framework, Folding-Docking-Affinity (FDA), which folds proteins, determines protein-ligand binding conformations, and predicts binding affinities from three-dimensional protein-ligand binding structures. Our experimental results indicate that FDA performs comparably to state-of-the-art docking-free methods. We anticipate that our proposed framework serves as a starting point for integrating …

A Scoping Review Of Omop Cdm Adoption For Cancer Research Using Real World Data, Liwei Wang, Andrew Wen, Sunyang Fu, Xiaoyang Ruan, Ming Huang, Rui Li, Qiuhao Lu, Heather Lyu, Andrew E Williams, Hongfang Liu

Faculty, Staff and Student Publications

The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) supports large-scale research by enabling distributed network analyses. However, the breadth of its adoption in cancer research is not well understood. We conducted a scoping review to describe the adoption of the OMOP CDM in cancer research. A total of 49 unique articles were included in the review, with 30 on the data analysis theme, and 20 on the infrastructure theme. This review highlighted that while the OMOP CDM ecosystem has enabled successful data support for cancer research, particularly for collaborative studies, ongoing model development and iterative improvement remain needed …

Benchmarking Large Language Models For Biomedical Natural Language Processing Applications And Recommendations, Qingyu Chen, Yan Hu, Xueqing Peng, Qianqian Xie, Qiao Jin, Aidan Gilson, Maxwell B Singer, Xuguang Ai, Po-Ting Lai, Zhizheng Wang, Vipina K Keloth, Kalpana Raja, Jimin Huang, Huan He, Fongci Lin, Jingcheng Du, Rui Zhang, W Jim Zheng, Ron A Adelman, Zhiyong Lu, Hua Xu

Faculty, Staff and Student Publications

The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While Large Language Models (LLMs) have shown promise in general domains, their effectiveness in BioNLP tasks remains unclear due to limited benchmarks and practical guidelines. We perform a systematic evaluation of four LLMs-GPT and LLaMA representatives-on 12 BioNLP benchmarks across six applications. We compare their zero-shot, few-shot, and fine-tuning performance with the traditional fine-tuning of BERT or BART models. We examine inconsistencies, missing information, hallucinations, and perform cost analysis. Here, we show that traditional fine-tuning outperforms zero- or …

Tobacco Smoke Exposure Is A Driver Of Altered Oxidative Stress Response And Immunity In Head And Neck Cancer, Yang Li, Pedram Yadollahi, Fonma N Essien, Vasanta Putluri, Chandra Shekar R Ambati, Karthik Reddy Kami Reddy, Abu Hena Mostafa Kamal, Nagireddy Putluri, Lama M Abdurrahman, Maria E Ruiz Echartea, Keenan J Ernste, Akshar J Trivedi, Jonathan Vazquez-Perez, William H Hudson, William K Decker, Rutulkumar Patel, Abdullah A Osman, Farrah Kheradmand, Stephen Y Lai, Jeffrey N Myers, Heath D Skinner, Cristian Coarfa, Kwangwon Lee, Antrix Jain, Anna Malovannaya, Mitchell J Frederick, Vlad C Sandulache

Faculty, Staff and Student Publications

Background: Exposomes are critical drivers of carcinogenesis. However, how they modulate tumor behavior remains unclear. Extensive clinical data show cigarette smoke to be a key exposome that promotes aggressive tumors, higher rates of metastasis, reduced response to chemoradiotherapy, and suppressed anti-tumor immunity. We sought to determine whether smoke itself can modulate aggressive tumor behavior in head and neck squamous cell carcinoma (HNSCC) through reprogramming of the cellular reductive state.

Methods: Using established human and murine HNSCC cell lines and syngeneic mouse models, we utilized conventional western blotting, steady state and flux metabolomics, RNA sequencing, quantitative proteomics and flow cytometry to …

A Phase Ii Trial Of Sitravatinib + Nivolumab After Progression On Immune Checkpoint Inhibitor In Patients With Metastatic Clear Cell Rcc, Andrew W Hahn, Nabil Adra, Ulka Vaishampayan, Lianchun Xiao, Nazli Dizman, Ying Yuan, Sagar S Mukhida, Matthew T Campbell, Jianjun Gao, Amado J Zurita, Eric Jonasch, Nizar M Tannir, Amishi Y Shah, Pavlos Msaouel

Faculty, Staff and Student Publications

Background: Sitravatinib, an oral multi-kinase inhibitor targeting VEGFR, TAM, and MET, has been shown to resensitize the tumor microenvironment to immune checkpoint inhibitors (ICI) by reducing immune-suppressive myeloid cells in metastatic clear cell RCC (ccRCC). ICI is the standard first-line (1L) treatment of metastatic ccRCC, and there is unmet need for improved treatment outcomes after progression on ICI. We hypothesized that sitravatinib plus nivolumab would revert an immunosuppressive tumor microenvironment (TME) to improve clinical outcomes.

Methods: In this investigator-initiated, phase II, multicenter trial (NCT04904302), patients with progressive metastatic ccRCC after 1-2 lines of treatment were enrolled into 3 …

Hif Regulates Multiple Translated Endogenous Retroviruses: Implications For Cancer Immunotherapy, Qinqin Jiang, David A Braun, Karl R Clauser, Vijyendra Ramesh, Nitin H Shirole, Joseph E Duke-Cohan, Nancy Nabilsi, Nicholas J Kramer, Cleo Forman, Isabelle E Lippincott, Susan Klaeger, Kshiti M Phulphagar, Vipheaviny Chea, Nawoo Kim, Allison P Vanasse, Eddy Saad, Teagan Parsons, Melissa Carr-Reynolds, Isabel Carulli, Katarina Pinjusic, Yijia Jiang, Rong Li, Sudeepa Syamala, Suzanna Rachimi, Eva K Verzani, Jonathan D Stevens, William J Lane, Sabrina Y Camp, Kevin Meli, Melissa B Pappalardi, Zachary T Herbert, Xintao Qiu, Paloma Cejas, Henry W Long, Sachet A Shukla, Eliezer M Van Allen, Toni K Choueiri, L Stirling Churchman, Jennifer G Abelin, Cagan Gurer, Gavin Macbeath, Richard W Childs, Steven A Carr, Derin B Keskin, Catherine J Wu, William G Kaelin

Faculty, Staff and Student Publications

Clear cell renal cell carcinoma (ccRCC), despite having a low mutational burden, is considered immunogenic because it occasionally undergoes spontaneous regressions and often responds to immunotherapies. The signature lesion in ccRCC is inactivation of the VHL tumor suppressor gene and consequent upregulation of the HIF transcription factor. An earlier case report described a ccRCC patient who was cured by an allogeneic stem cell transplant and later found to have donor-derived T cells that recognized a ccRCC-specific peptide encoded by a HIF-responsive endogenous retrovirus (ERV), ERVE-4. We report that ERVE-4 is one of many ERVs that are induced by HIF, translated …

Long-Term Patient-Reported Bowel And Urinary Quality Of Life In Patients Treated With Intensity-Modulated Radiotherapy Versus Intensity-Modulated Proton Therapy For Localized Prostate Cancer, Kimberly R Gergelis, Miao Bai, Jiasen Ma, David M Routman, Bradley J Stish, Brian J Davis, Thomas M Pisansky, Thomas J Whitaker, Richard Choo

Faculty, Staff and Student Publications

Purpose: This study aimed to compare long-term patient-reported outcomes in bowel and urinary domains between intensity-modulated radiotherapy (IMRT) and intensity-modulated proton therapy (IMPT) for localized prostate cancer.

Methods and materials: Patients with clinical T1-T2 prostate cancer receiving IMRT or IMPT at a tertiary cancer center from 2015-2018 were analyzed to determine the changes in the prospectively collected bowel function (BF), urinary irritative/obstructive symptoms (UO), and urinary incontinence (UI) domains of EPIC-26. The mean changes in EPIC-26 scores were evaluated from pretreatment to 24 months post-radiotherapy for each modality. A score change >50% of the baseline standard deviation was considered a …

Chronic Viral Mimicry Induction Following P53 Loss Promotes Immune Evasion, Charles A Ishak, Sajid A Marhon, Naïri Tchrakian, Anjelica Hodgson, Helen Loo Yau, Isabela M Gonzaga, Melanie Peralta, Ilinca M Lungu, Stephanie Gomez, Sheng-Ben Liang, Shu Yi Shen, Raymond Chen, Jocelyn Chen, Biji Chatterjee, Kevin N Wanniarachchi, Junwoo Lee, Nicholas Zehrbach, Amir Hosseini, Parinaz Mehdipour, Siyu Sun, Alexander Solovyov, Ilias Ettayebi, Kyle E Francis, Aobo He, Taiyi Wu, Shengrui Feng, Tiago Da Silva Medina, Felipe Campos De Almeida, Jane Bayani, Jason Li, Spencer Macdonald, Yadong Wang, Sarah S Garcia, Elisa Arthofer, Noor Diab, Aneil Srivastava, Paul Tran Austin, Peter J B Sabatini, Benjamin D Greenbaum, Catherine A O'Brien, Trevor G Shepherd, Ming Sound Tsao, Katherine B Chiappinelli, Amit M Oza, Blaise A Clarke, Robert Rottapel, Stephanie Lheureux, Daniel D De Carvalho

Faculty, Staff and Student Publications

Epigenetic therapies facilitate transcription of immunogenic repetitive elements that cull cancer cells through ‘viral mimicry’ responses. Paradoxically, cancer-initiating events also facilitate transcription of repetitive elements. Contributions of repetitive element transcription towards cancer initiation, and the mechanisms by which cancer cells evade lethal viral mimicry responses during tumor initiation remain poorly understood. In this report, we characterize premalignant lesions of the fallopian tube along with syngeneic epithelial ovarian cancer models to explore the earliest events of tumorigenesis following loss of the p53 tumor suppressor protein. We report that p53 loss permits transcription of immunogenic repetitive elements and chronic viral mimicry activation …

Conformal Predictive Intervals In Survival Analysis: A Resampling Approach, Jing Qin, Jin Piao, Jing Ning, Yu Shen

Faculty, Staff and Student Publications

The distribution-free method of conformal prediction has gained considerable attention in computer science, machine learning, and statistics. Candès et al. extended this method to right-censored survival data, addressing right-censoring complexity by creating a covariate shift setting, extracting a subcohort of subjects with censoring times exceeding a fixed threshold. Their approach only estimates the lower prediction bound for type I censoring, where all subjects have available censoring times regardless of their failure status. In medical applications, we often encounter more general right-censored data, observing only the minimum of failure time and censoring time. Subjects with observed failure times have unavailable censoring …

Computational Sensitivity Evaluation Of Ultrasound Neuromodulation Resolution To Brain Tissue Sound Speed With Robust Beamforming, Boqiang Fan, Wayne Goodman, Sameer A Sheth, Richard R Bouchard, Behnaam Aazhang

Faculty, Staff and Student Publications

Low-intensity focused ultrasound (LIFU) neuromodulation requires precise targeting and high resolution enabled by phased array transducers and beamforming. However, focusing optimization usually relies on phantom measurements or simulations with inaccurate acoustic properties to degrade neuromodulation resolution. Therefore, this work analyzes the sensitivity of neuromodulation resolution, measured by off-target activation area (OTAA), to brain tissue sound speed. A Robust Optimal Resolution (ROR) beamforming method is proposed to minimize the worst-case OTAA with restricted sound speed inaccuracy and propagation information estimated with deviated sound speed. The propagation estimation model utilizes equivalent source method (ESM) to map sound field between different acoustic parameter …

Identifiability And Model Selection Frameworks For Models Of High-Grade Glioma Response To Chemoradiation, Khushi C Hiremath, Kenan Atakishi, Ernesto A B F Lima, Maguy Farhat, Bikash Panthi, Holly Langshaw, Mihir D Shanker, Wasif Talpur, Sara Thrower, Jodi Goldman, Caroline Chung, Thomas E Yankeelov, David A Hormuth Ii

Faculty, Staff and Student Publications

We have developed a family of biology-based mathematical models of high-grade glioma (HGG), capturing the key features of tumour growth and response to chemoradiation. We now seek to quantify the accuracy of parameter estimation and determine, when given a virtual patient cohort, which model was used to generate the tumours. In this way, we systematically test both the parameter and model identifiability. Virtual patients are generated from unique growth parameters whose growth dynamics are determined by the model family. We then assessed the ability to recover model parameters and select the model used to generate the tumour. We then evaluated …

Ven In Combination With 10-Day Dec In Newly Diagnosed Elderly Or Relapsed/Refractory Acute Myeloid Leukemia, And High-Risk Myelodysplastic Syndrome: Long Term Follow-Up Of A Phase 2 Trial, Mahesh Swaminathan, Courtney D Dinardo, Abhishek Maiti, Naveen Pemmaraju, Maro Ohanian, Navel G Daver, Guillermo Garcia-Manero, Ghayas C Issa, Gautam Borthakur, Farhad Ravandi, Guillermo Montalban-Bravo, Tapan M Kadia, Yesid Alvarado, Elias J Jabbour, Nicholas J Short, William G Wierda, Nitin Jain, Steven M Kornblau, Lucia Masarova, Sherry A Pierce, Wei Qiao, Jing Ning, Hagop Kantarjian, Marina Y Konopleva

Faculty, Staff and Student Publications

No abstract provided.

An Examination Of Ambulatory Care Code Specificity Utilization In Icd-10-Cm Compared To Icd-9-Cm: Implications For Icd-11 Implementation, Susan H Fenton, Cassandra Ciminello, Vickie M Mays, Mary H Stanfill, Valerie Watzlaf

Faculty, Staff and Student Publications

Objective: The ICD-10-CM classification system contains more specificity than its predecessor ICD-9-CM. A stated reason for transitioning to ICD-10-CM was to increase the availability of detailed data. This study aims to determine whether the increased specificity contained in ICD-10-CM is utilized in the ambulatory care setting and inform an evidence-based approach to evaluate ICD-11 content for implementation planning in the United States.

Materials and methods: Diagnosis codes and text descriptions were extracted from a 25% random sample of the IQVIA Ambulatory EMR-US database for 2014 (ICD-9-CM, n = 14 327 155) and 2019 (ICD-10-CM, n = 13 062 900). Code …

Llm-Ie: A Python Package For Biomedical Generative Information Extraction With Large Language Models, Enshuo Hsu, Kirk Roberts

Faculty, Staff and Student Publications

Objectives: Despite the recent adoption of large language models (LLMs) for biomedical information extraction (IE), challenges in prompt engineering and algorithms persist, with no dedicated software available. To address this, we developed LLM-IE: a Python package for building complete IE pipelines.

Materials and methods: The LLM-IE supports named entity recognition, entity attribute extraction, and relation extraction tasks. We benchmarked it on the i2b2 clinical datasets.

Results: The sentence-based prompting algorithm resulted in the best 8-shot performance of over 70% strict F1 for entity extraction and about 60% F1 for entity attribute extraction.

Discussion: We developed a Python package, LLM-IE, …

External Validation Of An Algorithm To Detect Vertebral Level Mislabeling And Autocontouring Errors, Tucker J Netherton, Didier Duprez, Tina Patel, Gizem Cifter, Laurence E Court, Christoph Trauernicht, Ajay Aggarwal

Faculty, Staff and Student Publications

Background and purpose: This work performs external validation of a previously developed vertebral body autocontouring tool and investigates a post-processing method to increase performance to clinically acceptable levels.

Materials and methods: Vertebral bodies within CT scans from two separate institutions (40 from institution A and 41 from institution B) were automatically 1) localized and enumerated, 2) contoured, and 3) screened as a means of quality assurance (QA) for errors. Identification rate, contour acceptability rate, and QA accuracy were calculated to assess the tool's performance. These metrics were compared to those calculated on CTs from the model's original training dataset, and …

A New Cure Model Accounting For Longitudinal Data And Flexible Patterns Of Hazard Ratios Over Time, Can Xie, Xuelin Huang, Ruosha Li, Yu Shen, Nicholas J Short, Kapil N Bhalla

Faculty, Staff and Student Publications

With the advancement of medical treatments, many historically incurable diseases have become curable. An accurate estimation of the cure rates is of great interest. When there are no clear biomarker indicators for cure, the estimation of cure rate is intertwined with and influenced by the specification of hazard functions for uncured patients. Consequently, the commonly used proportional hazards (PH) assumption, when violated, may lead to biased cure rate estimation. Meanwhile, longitudinal biomarker measurements for individual patients are usually available. To accommodate non-PH functions and incorporate individual longitudinal biomarker trajectories, we propose a new joint model for cure, survival, and longitudinal …

Diet And Survival After A Diagnosis Of Ovarian Cancer: A Pooled Analysis From The Ovarian Cancer Association Consortium, Christina M Nagle, Torukiri I Ibiebele, Renhua Na, Elisa V Bandera, Daniel Cramer, Jennifer A Doherty, Graham G Giles, Marc T Goodman, Gillian E Hanley, Holly R Harris, Allan Jensen, Susanne K Kjaer, Alice Lee, Valerie Mcguire, Roger L Milne, Bo Qin, Jean Richardson, Naoko Sasamoto, Joellen M Schildkraut, Weiva Sieh, Kathryn L Terry, Linda Titus, Britton Trabert, Nicolas Wentzensen, Anna H Wu, Andrew Berchuck, Malcolm C Pike, Celeste Leigh Pearce, Penelope M Webb, Multidisciplinary Ovarian Cancer Outcomes Group And Ovarian Cancer Association Consortium

Faculty, Staff and Student Publications

Background: Prognosis after a diagnosis of invasive epithelial ovarian cancer is poor. Some studies have suggested modifiable behaviors, like diet, are associated with survival but the evidence is inconsistent.

Objectives: This study aims to pool data from studies conducted around the world to evaluate the relationships among dietary indices, foods, and nutrients from food sources and survival after a diagnosis of ovarian cancer.

Methods: This analysis from the Multidisciplinary Ovarian Cancer Outcomes Group within the Ovarian Cancer Association Consortium included 13 studies with 7700 individuals with ovarian cancer, who completed food-frequency questionnaires regarding their prediagnosis diet. Adjusted hazard ratios (aHRs) …

Immunotherapy Targeting A Leader Sequence Cathepsin G-Derived Peptide, Chunhua Shi, Ze Tian, Jun Yan, Mao Zhang, Pariya Sukhumalchandra, Edward Chang, Guojun Yang, Junping You, Meng Cui, Qing Shi, Celine Kerros, Anne Philips, Na Qiao, Hiroki Torikai, Sathvik Patchametla, Anna Sergeeva, Lisa St John, Helen He, Dmitri Wiederschain, Benjamin H Lee, Geraldine L C Paulus, Dongxing Zha, Jeffrey Molldrem, Gheath Alatrash

Faculty, Staff and Student Publications

Myeloid azurophil granules provide a rich source of intracellular leukemia antigens. Cathepsin G (CG) is a serine protease that has higher expression in acute myeloid leukemia (AML) blasts in comparison to normal myeloid progenitors. Based on the unique biology of HLA-A*0201 (HLA-A2), in which presentation of leader sequence (LS)-derived peptides is favored, we focused on the LS-CG-derived peptide CG1 (FLLPTGAEA). We previously detected CG1/HLA-A2 complexes on the surface of primary HLA-A2+ AML blasts and cell lines, and immunity targeting CG1/HLA-A2 in leukemia patients. T cell receptor (TCR)-mimic (m) antibodies are immunotherapeutic antibodies that target peptide-HLA (pHLA) complexes. Here we report …

Crowd-Sourced Benchmarking Of Single-Sample Tumor Subclonal Reconstruction, Adriana Salcedo, Maxime Tarabichi, Alex Buchanan, Shadrielle M G Espiritu, Hongjiu Zhang, Kaiyi Zhu, Tai-Hsien Ou Yang, Ignaty Leshchiner, Dimitris Anastassiou, Yuanfang Guan, Gun Ho Jang, Mohammed F E Mootor, Kerstin Haase, Amit G Deshwar, William Zou, Imaad Umar, Stefan Dentro, Jeff A Wintersinger, Kami Chiotti, Jonas Demeulemeester, Clemency Jolly, Lesia Sycza, Minjeong Ko, Pcawg Evolution And Heterogeneity Working Group, Smc-Het Participants, David C Wedge, Quaid D Morris, Kyle Ellrott, Peter Van Loo, Paul C Boutros

Faculty, Staff and Student Publications

Subclonal reconstruction algorithms use bulk DNA sequencing data to quantify parameters of tumor evolution, allowing an assessment of how cancers initiate, progress and respond to selective pressures. We launched the ICGC-TCGA (International Cancer Genome Consortium-The Cancer Genome Atlas) DREAM Somatic Mutation Calling Tumor Heterogeneity and Evolution Challenge to benchmark existing subclonal reconstruction algorithms. This 7-year community effort used cloud computing to benchmark 31 subclonal reconstruction algorithms on 51 simulated tumors. Algorithms were scored on seven independent tasks, leading to 12,061 total runs. Algorithm choice influenced performance substantially more than tumor features but purity-adjusted read depth, copy-number state and read mappability …

Daratumumab/Lenalidomide/Dexamethasone In Transplant-Ineligible Newly Diagnosed Myeloma: Maia Long-Term Outcomes, Thierry Facon, Philippe Moreau, Katja Weisel, Hartmut Goldschmidt, Saad Z Usmani, Ajai Chari, Torben Plesner, Robert Z Orlowski, Nizar Bahlis, Supratik Basu, Cyrille Hulin, Hang Quach, Michael O'Dwyer, Aurore Perrot, Caroline Jacquet, Christopher P Venner, Noopur Raje, Mourad Tiab, Margaret Macro, Laurent Frenzel, Xavier Leleu, Gordon Cook, George Wang, Huiling Pei, Maria Krevvata, Robin Carson, Fredrik Borgsten, Shaji K Kumar

Faculty, Staff and Student Publications

In the MAIA study, daratumumab plus lenalidomide and dexamethasone (D-Rd) improved progression-free survival (PFS) and overall survival (OS) versus lenalidomide and dexamethasone (Rd) alone in transplant-ineligible patients with newly diagnosed multiple myeloma (NDMM). We report updated efficacy and safety from MAIA (median follow-up, 64.5 months), including a subgroup analysis by patient age (< 70, ≥70 to < 75, ≥75, and ≥80 years). Overall, 737 transplant-ineligible patients with NDMM were randomized 1:1 to D-Rd or Rd. The primary endpoint, PFS, was improved with D-Rd versus Rd (median, 61.9 vs 34.4 months; hazard ratio [HR], 0.55; 95% confidence interval [CI], 0.45-0.67; P <  0.0001). Median OS was not reached in the D-Rd group versus 65.5 months in the Rd group (HR, 0.66; 95% CI, 0.53-0.83; P = 0.0003); estimated 60-month OS rates were 66.6% and 53.6%, respectively. D-Rd achieved higher rates of complete response or better (≥CR; 51.1% vs 30.1%), minimal residual disease (MRD) negativity (32.1% vs 11.1%), and sustained MRD negativity (≥18 months: 16.8% vs 3.3%) versus Rd (all P <  0.0001). D-Rd demonstrated clinically meaningful efficacy benefits across age groups. No new safety concerns were observed. Updated results (median follow-up, >5 years) continue to support frontline use of D-Rd in transplant-ineligible patients with NDMM.

Staged Screening Identifies People With Biomarkers Related To Neuronal Alpha-Synuclein Disease, Ethan G Brown, Lana M Chahine, Andrew Siderowf, Caroline Gochanour, Ryan Kurth, Micah J Marshall, Chelsea Caspell-Garcia, Michael C Brumm, Craig E Stanley, Monica Korell, Bridget Mcmahon, Maggie Kuhl, Kimberly Fabrizio, Laura Heathers, Luis Concha-Marambio, Claudio Soto, Sohini Chowdhury, Christopher S Coffey, Tatiana M Foroud, Tanya Simuni, Kenneth Marek, Caroline M Tanner

Faculty, Staff and Student Publications

Objective: Remote identification of individuals with severe hyposmia may enable scalable recruitment of participants with underlying alpha-synuclein aggregation. We evaluated the performance of a staged screening paradigm using remote smell testing to enrich for abnormal dopamine transporter single-photon emission computed tomography imaging (DAT-SPECT) and alpha-synuclein aggregation.

Methods: The Parkinson's Progression Markers Initiative (PPMI) recruited participants for the prodromal cohort who were 60-years and older without a Parkinson's disease diagnosis. Participants were invited to complete a University of Pennsylvania Smell Identification Test (UPSIT) independently through an online portal. Hyposmic participants were invited to complete DAT-SPECT, which determined eligibility for enrollment in …