Digital Commons Network^™

Engravings, Secrets, And Interpretability Of Neural Networks, Nathaniel Hobbs, Periklis A Papakonstantinou, Jaideep Vaidya

Faculty, Staff and Student Publications

This work proposes a definition and examines the problem of undetectably engraving special input/output information into a Neural Network (NN). Investigation of this problem is significant given the ubiquity of neural networks and society's reliance on their proper training and use. We systematically study this question and provide (1) definitions of security for secret engravings, (2) machine learning methods for the construction of an engraved network, (3) a threat model that is instantiated with state-of-the-art interpretability methods to devise distinguishers/attackers. In this work, there are two kinds of algorithms. First, the constructions of engravings through machine learning training methods. Second, …

Igamt: Privacy-Preserving Electronic Health Record Synthesization With Heterogeneity And Irregularity, Wenjie Wang, Pengfei Tang, Jian Lou, Yuanming Shao, Lance Waller, Yi-An Ko, Li Xiong

Faculty, Staff and Student Publications

Utilizing electronic health records (EHR) for machine learning-driven clinical research has great potential to enhance outcome predictions and treatment personalization. Nonetheless, due to privacy and security concerns, the secondary use of EHR data is regulated, constraining researchers’ access to EHR data. Generating synthetic EHR data with deep learning methods is a viable and promising approach to mitigate privacy concerns, offering not only a supplementary resource for downstream applications but also sidestepping the privacy risks associated with real patient data. While prior efforts have concentrated on EHR data synthesis, significant challenges persist: addressing the heterogeneity of features including temporal and non-temporal …

Federated Node Classification Over Distributed Ego-Networks With Secure Contrastive Embedding Sharing, Han Xie, Li Xiong, Carl Yang

Faculty, Staff and Student Publications

Federated learning on graphs (a.k.a., federated graph learning- FGL) has recently received increasing attention due to its capacity to enable collaborative learning over distributed graph datasets without compromising local clients' data privacy. In previous works, clients of FGL typically represent institutes or organizations that possess sets of entire graphs (e.g., molecule graphs in biochemical research) or parts of a larger graph (e.g., sub-user networks of e-commerce platforms). However, another natural paradigm exists where clients act as remote devices retaining the graph structures of local neighborhoods centered around the device owners (i.e., ego-networks), which can be modeled for specific graph applications …

Bridging The Gap: Rademacher Complexity In Robust And Standard Generalization, Jiancong Xiao, Ruoyu Sun, Qi Long, Weijie J Su

Faculty, Staff and Student Publications

Training Deep Neural Networks (DNNs) with adversarial examples often results in poor generalization to test-time adversarial data. This paper investigates this issue, known as adversarially robust generalization, through the lens of Rademacher complexity. Building upon the studies by Khim and Loh (2018); Yin et al. (2019), numerous works have been dedicated to this problem, yet achieving a satisfactory bound remains an elusive goal. Existing works on DNNs either apply to a surrogate loss instead of the robust loss or yield bounds that are notably looser compared to their standard counterparts. In the latter case, the bounds have a …

Privacy-Preserving Fingerprinting Against Collusion And Correlation Threats In Genomic Data, Tianxi Ji, Erman Ayday, Emre Yilmaz, Pan Li

Faculty, Staff and Student Publications

Sharing genomic databases is critical to the collaborative research in computational biology. A shared database is more informative than specific genome-wide association studies (GWAS) statistics as it enables “do-it-yourself” calculations. Genomic databases involve intellectual efforts from the curator and sensitive information of participants, thus in the course of data sharing, the curator (database owner) should be able to prevent unauthorized redistributions and protect individuals’ genomic data privacy. As it becomes increasingly common for a single database be shared with multiple recipients, the shared genomic database should also be robust against collusion attack, where multiple malicious recipients combine their individual copies …

Fairness-Aware Estimation Of Graphical Models, Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Qi Long, Li Shen

Faculty, Staff and Student Publications

This paper examines the issue of fairness in the estimation of graphical models (GMs), particularly Gaussian, Covariance, and Ising models. These models play a vital role in understanding complex relationships in high-dimensional data. However, standard GMs can result in biased outcomes, especially when the underlying data involves sensitive characteristics or protected groups. To address this, we introduce a comprehensive framework designed to reduce bias in the estimation of GMs related to protected attributes. Our approach involves the integration of the pairwise graph disparity error and a tailored loss function into a nonsmooth multi-objective optimization problem, striving to achieve fairness across …

Facilitating Clinical Information Extraction With Synthetic Data And Ontology Using Large Language Models, Yan Hu, Huan He, Qingyu Chen, Xiaoqian Jiang, Kirk Roberts, Hua Xu

Faculty, Staff and Student Publications

The rapid growth of unstructured clinical text in electronic health records necessitates robust information extraction systems, yet their development is hindered by the scarcity of high-quality annotated data. This study explores the potential of large language models to generate synthetic data for clinical named entity recognition and examines its impact on model performance. We propose a novel framework that integrates self-verified synthetic data generation with domain-specific semantic mapping using SNOMED-CT. By leveraging GPT-4o-mini for synthetic data creation and refining its quality through iterative verification and anomaly detection, we systematically evaluate the influence of synthetic data quality and quantity on fine-tuning …

Narrative Feature Or Structured Feature? A Study Of Large Language Models To Identify Cancer Patients At Risk Of Heart Failure, Ziyi Chen, Mengyuan Zhang, Mustafa Mohammed Ahmed, Yi Guo, Thomas J George, Jiang Bian, Yonghui Wu

Faculty, Staff and Student Publications

Cancer treatments are known to introduce cardiotoxicity, negatively impacting outcomes and survivorship. Identifying cancer patients at risk of heart failure (HF) is critical to improving cancer treatment outcomes and safety. This study examined machine learning (ML) models to identify cancer patients at risk of HF using electronic health records (EHRs), including traditional ML, Time-Aware long short-term memory (T-LSTM), and large language models (LLMs) using novel narrative features derived from the structured medical codes. We identified a cancer cohort of 12,806 patients from the University of Florida Health, diagnosed with lung, breast, and colorectal cancers, among which 1,602 individuals developed HF …

Descriptor: Synthetic Genomic Dataset With Diverse Ancestry (Syngen6), Xinyue Wang, Sitao Min, Jaideep Vaidya

Faculty, Staff and Student Publications

Advancements in genomic analysis techniques and data-driven research are driving precision medicine. However, in many cases, these advances are not equitable and do not help all subpopulations, since many existing genomic datasets lack diversity, limiting their applicability for studying populations beyond those of European ancestry. Thus, to advance genomic analysis and to allow for a fair benchmarking of novel proposed approaches, there is a significant demand for balanced and representative datasets. To address this issue, we developed,

Impact Of P53-Associated Acute Myeloid Leukemia Hallmarks On Metabolism And The Immune Environment, Monika Chomczyk, Luca Gazzola, Shubhankar Dash, Patryk Firmanty, Binsah S George, Vakul Mohanty, Hussein A Abbas, Natalia Baran

Faculty, Staff and Student Publications

Acute myeloid leukemia (AML), an aggressive malignancy of hematopoietic stem cells, is characterized by the blockade of cell differentiation, uncontrolled proliferation, and cell expansion that impairs healthy hematopoiesis and results in pancytopenia and susceptibility to infections. Several genetic and chromosomal aberrations play a role in AML and influence patient outcomes. TP53 is a key tumor suppressor gene involved in a variety of cell features, such as cell-cycle regulation, genome stability, proliferation, differentiation, stem-cell homeostasis, apoptosis, metabolism, senescence, and the repair of DNA damage in response to cellular stress. In AML, TP53 alterations occur in 5%-12% of de novo AML …

Rural Racial Disparities And Barriers In Mammography Utilization Among Medicare Beneficiaries In Texas: A Longitudinal Study, Zhaoli Liu, Yong Shan, Yong-Fang Kuo, Sharon H Giordano

Faculty, Staff and Student Publications

This study examined rural racial/ethnic disparities in long-term mammography screening practices among Medicare beneficiaries. A retrospective longitudinal study was conducted using 100% Texas Medicare data for women aged 65-74 who enrolled in Medicare between 2010-2013. Of the 114,939 eligible women, 21.2% of Hispanics, 33.3% of non-Hispanic Blacks (NHB), and 38.4% non-Hispanic Whites (NHW) in rural areas were regular users of mammography, compared to 33.5%, 44.9%, and 45.3% of their counterparts in urban areas, respectively. Stratification analyses showed rural Hispanics and NHB were 33% (95% CI, 25% - 40%) and 22% (95% CI, 6% - 36%) less likely to be regular …

The Baseline Hemoglobin Level Is A Positive Biomarker For Immunotherapy Response And Can Improve The Predictability Of Tumor Mutation Burden For Immunotherapy Response In Cancer, Yin He, Tong Ren, Chengfei Ji, Li Zhao, Xiaosheng Wang

Faculty, Staff and Student Publications

Purpose: Because only a subset of cancer patients can benefit from immunotherapy, identifying predictive biomarkers of ICI therapy response is of utmost importance.

Methods: We analyzed the association between hemoglobin (HGB) levels and clinical outcomes in 1,479 ICIs-treated patients across 16 cancer types. We explored the dose-dependent associations between HGB levels and survival and immunotherapy response using the spline-based cox regression analysis. Furthermore, we investigated the associations across subgroups of patients with different clinicopathological characteristics, treatment programs and cancer types using the bootstrap resampling method.

Results: HGB levels correlated positively with clinical outcomes in cancer patients receiving immunotherapy but not …

A Brief But Comprehensive Three-Item Social Connectedness Screener For Use In Social Risk Assessment Tools, Nancy P Gordon, Matthiew C Stiefel

Faculty, Staff and Student Publications

BACKGROUND: The 2014 IOM report "Capturing Social and Behavioral Domains and Measures in Electronic Health Records" described three subdomains of social relationships that affect patient health and well-being. However, most social risk screeners currently assess only one subdomain, frequency of social connections. We are proposing a three-item Brief Social Connectedness (SC) screener that additionally assesses risks in social/emotional support and loneliness/social isolation subdomains.

METHODS: For this cross-sectional study, we used data from a 2021 Kaiser Permanente Northern California (KPNC) social risk survey for 2244 members ages 35-85 years. The survey included three validated questions that covered the SC subdomains (frequencies …

Failure To Mate Enhances Investment In Behaviors That May Promote Mating Reward And Impairs The Ability To Cope With Stressors Via A Subpopulation Of Neuropeptide F Receptor Neurons, Julia Ryvkin, Liora Omesi, Yong-Kyu Kim, Mali Levi, Hadar Pozeilov, Lital Barak-Buchris, Bella Agranovich, Ifat Abramovich, Eyal Gottlieb, Avi Jacob, Dick R Nässel, Ulrike Heberlein, Galit Shohat-Ophir

Faculty, Staff and Student Publications

Living in dynamic environments such as the social domain, where interaction with others determines the reproductive success of individuals, requires the ability to recognize opportunities to obtain natural rewards and cope with challenges that are associated with achieving them. As such, actions that promote survival and reproduction are reinforced by the brain reward system, whereas coping with the challenges associated with obtaining these rewards is mediated by stress-response pathways, the activation of which can impair health and shorten lifespan. While much research has been devoted to understanding mechanisms underlying the way by which natural rewards are processed by the reward …

Sudden Unexpected Intrapartum Death And Left Ventricular Noncompaction Involving The Right Ventricle, Giulia Ottaviani, Tobia Tomasello, Francesca Boggio, Letterio Runza, Alessandro Del Gobbo, L Maximilian Buja

Faculty, Staff and Student Publications

Left ventricular noncompaction (LVNC), involving mainly the right ventricle, is a rare form of congenital heart disorder characterized by a developmental arrest in myocardial compaction, resulting in a spongy appearance of the myocardium, mainly of the right ventricle, rarely detected in fetuses. We report the case of a female fetus with a gestational age of 41+4 weeks who came to our attention for intrapartum sudden unexpected death, resulting in stillbirth. The ventricular walls, particularly the right ventricular wall, appeared thick, hypertrabeculated and spongy, leading to the diagnosis of LVNC involving mainly the right ventricle. The atrioventricular node and His bundle …

Chronic Lymphocytic Leukemia: Disease Biology, Stefan Koehrer, Jan A Burger

Faculty, Staff and Student Publications

Background: B-cell receptor (BCR) signaling is crucial for normal B-cell development and adaptive immunity. In chronic lymphocytic leukemia (CLL), the malignant B cells display many features of normal mature B lymphocytes, including the expression of functional B-cell receptors (BCRs). Cross talk between CLL cells and the microenvironment in secondary lymphatic organs results in BCR signaling and BCR-driven proliferation of the CLL cells. This critical pathomechanism can be targeted by blocking BCR-related kinases (BTK, PI3K, spleen tyrosine kinase) using small-molecule inhibitors. Among these targets, Bruton tyrosine kinase (BTK) inhibitors have the highest therapeutic efficacy; they effectively block leukemia cell proliferation and …

Enhancing Associative Learning In Rats With A Computationally Designed Training Protocol, Xu O Zhang, Yili Zhang, Claire E Cho, Douglas S Engelke, Paul Smolen, John H Byrne, Fabricio H Do-Monte

Faculty, Staff and Student Publications

Background: Learning requires the activation of protein kinases with distinct temporal dynamics. In Aplysia, nonassociative learning can be enhanced by a computationally designed learning protocol with intertrial intervals (ITIs) that maximize the interaction between fast-activated PKA (protein kinase A) and slow-activated ERK (extracellular signal-regulated kinase). Whether a similar strategy can enhance associative learning in mammals is unknown.

Methods: We simulated 1000 training protocols with varying ITIs to predict an optimal protocol based on empirical data for PKA and ERK dynamics in rat hippocampus. Adult male rats received the optimal protocol or control protocols in auditory fear conditioning and fear …

Author Correction: Enhanced Cd19 Activity In B Cells Contributes To Immunodeficiency In Mice Deficient In The Icf Syndrome Gene Zbtb24, Zhengzhou Ying, Swanand Hardikar, Joshua B Plummer, Tewfik Hamidi, Bin Liu, Yueping Chen, Jianjun Shen, Yunxiang Mu, Kevin M Mcbride, Taiping Chen

Faculty, Staff and Student Publications

No abstract provided.

Risk Stratification And Prediction Of Severity Of Covid-19 Infection In Patients With Preexisting Cardiovascular Disease, Stanislava Matejin, Igor D Gregoric, Rajko Radovancevic, Slobodan Paessler, Vladimir Perovic

Faculty, Staff and Student Publications

Introduction: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 is a highly contagious viral disease. Cardiovascular diseases and heart failure elevate the risk of mechanical ventilation and fatal outcomes among COVID-19 patients, while COVID-19 itself increases the likelihood of adverse cardiovascular outcomes.

Methods: We collected blood samples and clinical data from hospitalized cardiovascular patients with and without proven COVID-19 infection in the time period before the vaccine became available. Statistical correlation analysis and machine learning were used to evaluate and identify individual parameters that could predict the risk of needing mechanical ventilation and patient survival.

Results: Our results confirmed that COVID-19 …

Clinical Characteristics And Outcomes Of Adult Alveolar Rhabdomyosarcoma Patients On First-Line Systemic Therapies: A Single-Institution Cohort, Michael S Nakazawa, J Andrew Livingston, Maria A Zarzour, Andrew J Bishop, Ravin Ratan, Joseph A Ludwig, Dejka M Araujo, Neeta Somaiah, Vinod Ravi, Elise F Nassif, Christina L Roland, Alexander J Lazar, B Ashleigh Guadagnolo, Douglas J Harrison, Robert S Benjamin, Shreyaskumar R Patel, Anthony P Conley

Faculty, Staff and Student Publications

Background: Rhabdomyosarcomas are the most common soft tissue sarcoma in children, and pediatric alveolar rhabdomyosarcoma (ARMS) prognosis has improved based on cooperative studies. However, in adults, ARMS is significantly rarer, has poorer outcomes, and currently lacks optimal treatment strategies. Objective: This study aimed to evaluate the clinical outcome of an adult ARMS population with different front-line systemic chemotherapies and determine if any chemotherapy regimen is associated with improved survival. ]

Materials and methods: This is a retrospective study of histologically confirmed fusion-positive ARMS patients over 18 years of age, who were treated at MD Anderson Cancer Center (MDACC) from 2004 …

Bayesian Optimal Designs For Multi-Arm Multi-Stage Phase Ii Randomized Clinical Trials With Multiple Endpoints, Guillaume Mulier, Sylvie Chevret, Ruitao Lin, Lucie Biard

Faculty, Staff and Student Publications

There is a growing need to evaluate of multiple competing drugs in phase II trials where the number of patients is often limited, and simultaneous assessment of both efficacy and toxicity is crucial. To avoid the waste of research resources, it is indeed more efficient to screen multiple drugs at once in a platform phase II setting. We aim to adapt the Bayesian optimal phase II (BOP2) design to multi-arm trials for both uncontrolled and controlled settings. The binary efficacy and toxicity endpoints are modeled by a Dirichlet distribution as a vector of four outcomes. Posterior marginal distributions at each …

On The Relative Conservativeness Of Bayesian Logistic Regression Method In Oncology Dose-Finding Studies, Cheng-Han Yang, Guanghui Cheng, Ruitao Lin

Faculty, Staff and Student Publications

The Bayesian logistic regression method (BLRM) is a widely adopted and flexible design for finding the maximum tolerated dose in oncology phase I studies. However, the BLRM design has been criticized in the literature for being overly conservative due to the use of the overdose control rule. Recently, a discussion paper titled "Improving the performance of Bayesian logistic regression model with overall control in oncology dose-finding studies" in Statistics in Medicine has proposed an overall control rule to address the "excessive conservativeness" of the standard BLRM design. In this short communication, we discuss the relative conservativeness of the standard BLRM …

Systematic Review And Meta-Analysis Of Acupuncture For Modulation Of Immune And Inflammatory Markers In Cancer Patients, Wenli Liu, Baisong Zhong, Richard W Wagner, M Kay Garcia, Jennifer L Mcquade, Wen Huang, Yisheng Li, Graciela M Nogueras Gonzalez, Michael R Spano, Alessandro Cohen, Yimin Geng, Lorenzo Cohen

Faculty, Staff and Student Publications

Introduction: Inflammation is associated with tumor initiation, and existing tumors are associated with immune suppression locally and systemically. Cancer treatment is also associated with immune suppression. This review evaluates evidence related to the use of acupuncture for modulation of inflammation and the immune system in cancer patients.

Methods: Nine databases were searched for prospective, randomized, controlled trials evaluating the use of acupuncture for modulation of the immune system in cancer patients through March 2024. Only studies involving needle insertion into acupuncture points were included. No language limitations were applied. Studies were assessed for risk of bias (ROB) according to Cochrane …

Commitment Complex Splicing Factors In Cancers Of The Gastrointestinal Tract-An In Silico Study, Yun Zhang, Alexandria Carrasquillo Simko, Uzondu Okoro, Deja Jamese Sibert, Jin Hyung Moon, Bin Liu, Angabin Matin

Faculty, Staff and Student Publications

The initial step in pre-mRNA splicing involves formation of a spliceosome commitment complex (CC) or E-complex by factors that serve to bind and mark the exon-intron boundaries that will undergo splicing. The CC component U1 snRNP assembles at the 5'-splice site (ss), whereas SF1, U2AF2, and U2AF1 define the 3'-ss of the intron. A PRP40 protein bridges U1 snRNP with factors at the 3'-ss. To determine how defects in CC components impact cancers, we analyzed human gastrointestinal (GI) cancer patient tissue and clinical data from cBioPortal. cBioPortal datasets were analyzed for CC factor alterations and patient outcomes in GI cancers …

Pancreatic Cancer Action Network's Spark: A Cloud-Based Patient Health Data And Analytics Platform For Pancreatic Cancer, Kawther Abdilleh, Omar Khalid, Dennis Ladnier, Wenshuai Wan, Sara Seepo, Garrett Rupp, Valentin Corelj, Zelia F Worman, Divya Sain, Jack Digiovanna, Bruce Press, Satty Chandrashekhar, Eric Collisson, Karen Y Cui, Anirban Maitra, Paul A Rejto, Kevin P White, Lynn Matrisian, Sudheer Doss

Faculty, Staff and Student Publications

Purpose: Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools …

Harnessing Endoscopic Ultrasound-Guided Radiofrequency Ablation To Reshape The Pancreatic Ductal Adenocarcinoma Microenvironment And Elicit Systemic Immunomodulation, Vishali Moond, Bhumi Maniyar, Prateek Suresh Harne, Jennifer M Bailey-Lundberg, Nirav C Thosani

Faculty, Staff and Student Publications

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognostics and substantial therapeutic challenges, with dismal survival rates. Tumor resistance in PDAC is primarily attributed to its fibrotic, hypoxic, and immune-suppressive tumor microenvironment (TME). Endoscopic ultrasound-guided radiofrequency ablation (EUS-RFA), an Food and Drug Administration (FDA)-approved minimally invasive technique for treating pancreatic cancer, disrupts tumors with heat and induces coagulative necrosis, releasing tumor antigens that may trigger a systemic immune response-the abscopal effect. We aim to elucidate the roles of EUS-RFA-mediated thermal and mechanical stress in enhancing anti-tumor immunity in PDAC. A comprehensive literature review focused on radiofrequency immunomodulation and immunotherapy in …

Individual Ingredients Of Np-101 (Thymoquinone Formula) Inhibit Sars-Cov-2 Pseudovirus Infection, Abdelrahim Maen, Betul Gok Yavuz, Yehia I Mohamed, Abdullah Esmail, Jianming Lu, Amr Mohamed, Asfar S Azmi, Mohamed Kaseb, Osama Kasseb, Dan Li, Michelle Gocio, Mehmet Kocak, Abdelhafez Selim, Qing Ma, Ahmed O Kaseb

Faculty, Staff and Student Publications

Thymoquinone TQ, an active ingredient of Nigella Sativa, has been shown to inhibit COVID-19 symptoms in clinical trials. Thymoquinone Formulation (TQF or NP-101) is developed as a novel enteric-coated medication derivative from Nigella Sativa. TQF consists of TQ with a favorable concentration and fatty acids, including palmitic, oleic, and linoleic acids. In this study, we aimed to investigate the roles of individual ingredients of TQF on infection of SARS-CoV-2 variants

Effects Of Huoxue Qufeng Decoction Combined With Tongguan Liquefying Acupoint Penetration Therapy On Swallowing Function And Quality Of Life In Patients With Ischemic Stroke, Xuzhong Liang, Li Ma, Lixia Zhang, Dongnian Yang, Lanrui Zeng

Faculty, Staff and Student Publications

Objective: To analyze the effects of Huoxue Qufeng Decoction combined with Tongguan Liquefying Acupoint Penetration therapy on swallowing function and quality of life in patients with ischemic stroke.

Methods: A total of 145 patients with post-stroke dysphagia admitted to Dingxi People's Hospital from January 2019 to May 2022 were selected with 65 patients in the control group and 80 patients in the observation group. The control group received Huoxue Qufeng Decoction alone, while the observation group received additional Tongguan Liquefying Acupoint Penetration therapy. Clinical efficacy, NIH Stroke Scale (NIHSS) score, Water Swallow Test, Swallowing Function Assessment (SSA) score, MD Anderson …

Leptomeningeal Disease In Melanoma: An Update On The Developments In Pathophysiology And Clinical Care, Inna Smalley, Adrienne Boire, Priscilla Brastianos, Harriet M Kluger, Eva Hernando-Monge, Peter A Forsyth, Kamran A Ahmed, Keiran S M Smalley, Sherise Ferguson, Michael A Davies, Isabella C Glitza Oliva

Faculty, Staff and Student Publications

Leptomeningeal disease (LMD) remains a major challenge in the clinical management of metastatic melanoma patients. Outcomes for patient remain poor, and patients with LMD continue to be excluded from almost all clinical trials. However, recent trials have demonstrated the feasibility of conducting prospective clinical trials in these patients. Further, new insights into the pathophysiology of LMD are identifying rational new therapeutic strategies. Here we present recent advances in the understanding of, and treatment options for, LMD from metastatic melanoma. We also annotate key areas of future focus to accelerate progress for this challenging but emerging field.

Myeloid Lineage Switch In Kmt2a- Rearranged Acute Lymphoblastic Leukemia Treated With Lymphoid Lineagedirected Therapies, Alex Bataller, Tareq Abuasab, David Mccall, Wei Wang, Branko Cuglievan, Ghayas C Issa, Elias Jabbour, Nicholas Short, Courtney D Dinardo, Guilin Tang, Guillermo Garcia-Manero, Hagop M Kantarjian, Koji Sasaki

Faculty, Staff and Student Publications

No abstract provided.