Medical Specialties Commons^™

Effects Of Interventions For The Prevention And Management Of Maternal Anemia In The Advent Of The Covid-19 Pandemic: Systematic Review And Meta-Analysis, John Kyalo Muthuka, Diana Kageni Mbari-Fondo, Francis Muchiri Wambura, Kelly Oluoch, Japheth Mativo Nzioki, Everlyn Musanga Nyamar, Rosemary Nabaweesi

Faculty Publications

Background:The COVID-19 pandemic presented many unknowns for pregnant women, with anemia potentially worsening pregnancy outcomes due to multiple factors.

Objective:This review aimed to determine the pooled effect of maternal anemia interventions and associated factors during the pandemic.

Methods:Eligible studies were observational and included reproductive-age women receiving anemia-related interventions during the COVID-19 pandemic. Exclusion criteria comprised non-English publications, reviews, editorials, case reports, studies with insufficient data, sample sizes below 50, and those lacking DOIs. A systematic search of PubMed, Scopus, Embase, Web of Science, and Google Scholar identified articles published between December 2019 and August 2022. Risk of bias was evaluated …

Heterogeneous Clustering Of Multiomics Data For Breast Cancer Subgroup Classification And Detection, Joseph Pateras, Musaddiq Lodi, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

The rapid growth of diverse -omics datasets has made multiomics data integration crucial in cancer research. This study adapts the expectation–maximization routine for the joint latent variable modeling of multiomics patient profiles. By combining this approach with traditional biological feature selection methods, this study optimizes latent distribution, enabling efficient patient clustering from well-studied cancer types with reduced computational expense. The proposed optimization subroutines enhance survival analysis and improve runtime performance. This article presents a framework for distinguishing cancer subtypes and identifying potential biomarkers for breast cancer. Key insights into individual subtype expression and function were obtained through differentially expressed gene …

Benchmarking Batch-Effect Correction Methods Towards The Construction Of A Triple-Negative Breast Cancer Cell Atlas, Peter Scheible, Amy H. Tang, Jing He, Jiangwen Sun

Computer Science Faculty Publications

Triple-negative breast cancer (TNBC) requires detailed cellular mapping given its aggressive nature, immense tumor heterogeneity and genetic diversity. We integrated 156,794 cells from six scRNA-seq datasets—including tumors, metastases, and cell lines—to build a TNBC scRNA cell atlas, focusing on batch effect mitigation while maintaining biological and molecular details. Preprocessing f ilters noise, normalizes data, and leverages PCA for integration readiness. We utilized scANVI, a semi-supervised tool, to align datasets, preserving TNBC’s complex tumor heterogeneity via marker annotations [1]. UMAPs demonstrate biological clustering in integrated data, contrasted with datasetdriven unintegrated patterns. Assessments verifying effective batch correction. This method aligns with NASA’s …

Multi-Modal Mri Based Segmentation Of Brain Metastases Using Adaptive Self-Attention, Evan Savaria

Computer Science Faculty Publications

Brain metastases (BMs) are the most common adult central nervous system malignancy, affecting 20–40% of cancer patients. Accurate segmentation of metastatic lesions in multi-modal MRI is essential for treatment planning and prognosis however, manual delineation is time consuming and prone to variability. Traditional deep learning models such as U-Net, have improved segmentation accuracy but capture limited long-range dependencies and struggle with variations in metastasis size, shape, and distribution. This study introduces the Adaptive Integrated Multi-modal Segmentation (AIMS) model, an adaptive self-attention framework within a hybrid U-Net and Transformer architecture to enhance BM segmentation by leveraging multi-modal MRI integration. The proposed …

Coldstartcpi: Induced-Fit Theory-Guided Dti Predictive Model With Improved Generalization Performance, Qichang Zhao, Haochen Zhao, Linyuan Gao, Kai Zheng, Yajie Li, Qiao Ling, Jing Tang, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Predicting compound-protein interactions (CPIs) plays a crucial role in drug discovery. Traditional methods, based on the key-lock theory and rigid docking, often fail with novel compounds and proteins due to their inability to account for molecular flexibility and the high sparsity of CPI data. Here, we introduce ColdstartCPI, a framework inspired by induced-fit theory, which leverages unsupervised pre-training features and a Transformer module to learn both compound and protein characteristics. ColdstartCPI treats proteins and compounds as flexible molecules during inference, aligning with biological insights. It outperforms state-of-the-art sequence-based models, particularly for unseen compounds and proteins, and shows strong generalization capability …

Optiselect And Enshap: Integrating Machine Learning And Game Theory For Ischemic Stroke Prediction, Pritam Chakraborty, Anjan Bandyopadhyay, Sricheta Parul, Sujata Swain, Partha Sarathy Banerjee, Tapas Si, Hong Qin, Saurav Mallik

Computer Science Faculty Publications

Stroke analysis using game theory and machine learning techniques. The study investigates the use of the Shapley value in predictive ischemic brain stroke analysis. Initially, preference algorithms identify the most important features in various machine learning models, including logistic regression, K-nearest neighbor, decision tree, support vector machine (linear kernel), support vector machine ( RBF kernel), neural networks, etc. For each sample, the top 3, 4, and 5 features are evaluated and selected to evaluate their performance. The Shapley value method was used to rank the models using their best four features based on their predictive capabilities. As a result, better-performing …

Benchmarking And Improving Foundation Model Dietary Estimates From Meal Images, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Accurate quantifying dietary contents, such as calories, proteins, carbohydrates, and fats, from an image of a meal plate is vital for managing diabetes. Recently, Large Multimodal Models (LMMs) have excelled in complex vision-language tasks due to their use of very large, highly diverse data. This study benchmarked the use of seven LMMs that include full and lightweight models of GPT, Gemini, and Llama for nutrition estimation based on Google's Nutrition5k dataset and our own phone-collected DonateAndLearn dataset. We analyzed the performance of LMMs and the RGB-D fusion model, in which the RGB-D model was specifically trained using Nutrition5k data. On …

Optimal Bag Valve Mask Ventilation Efficacy Of Smart Bag Ventilation Compared To Traditional Adult And Paediatric Bag Valve Ventilation During Cardiopulmonary Resuscitation, Ian Dawson

Theses: Doctorates and Masters

Background: Out-of-Hospital Cardiac Arrest (OHCA) is one of the world’s leading causes of mortality. Survival rates are low, ranging from 3.1–20.4% internationally. The most effective oxygenation method for patients during pre-hospital cardiac arrest is ventilating using a self- inflating Bag-Valve-Mask (BVM). Yet, extensive research has identified a lack of compliance with ventilator guidelines during OHCA cardiopulmonary resuscitation (CPR). As a result, clinicians often ventilate patients too aggressively using the BVM, delivering breaths excessively higher than the International Liaison Committee on Resuscitation (ILCOR) recommended rate of 10 breaths per minute (BPM). Hyperventilation can lead to complications such as aspiration, barotrauma, and …

A Turning Point In Cardiac Remodelling In Obesity: Obesity, Mariella R. Huaman, Carlos J. Toro-Huamanchumo

Research outputs 2022 to 2026

Cardiac remodelling in obesity has received growing attention in the past two decades, particularly as the prevalence of obesity continues to rise globally. In 2013, Aurigemma and colleagues published a seminal study that provided crucial insights into the structural changes in the heart associated with obesity. This study summarized advances in understanding how the disproportionate growth of adipose tissue affects cardiac function, and challenged and reshaped previously established paradigms. Before the publication of this report, the standard paradigm held that obesity-induced haemodynamic stress primarily drove eccentric left ventricular hypertrophy. However, this study instead demonstrated that in individuals with obesity, concentric …

Associations Of Vegetable And Potato Intakes With Markers Of Type 2 Diabetes Risk In The Ausdiab Cohort, Pratik Pokharel, Lauren C. Blekkenhorst, Catherine P. Bondonno, Kevin Murray, Simone Radavelli-Bagatini, Dianna J. Magliano, Robin M. Daly, Jonathan E. Shaw, Joshua Lewis, Jonathan M. Hodgson, Nicola P. Bondonno

Research outputs 2022 to 2026

Context: The associations of vegetable and potato intakes with type 2 diabetes (T2D) appear to be nuanced, depending on vegetable types and preparation method, respectively.

Objective: We investigated the associations of total vegetable, vegetable subgroup, and potato intakes with (1) markers of T2D at baseline and (2) incident T2D cumulative over a 12-year follow-up period in Australian adults.

Methods: Using data from the Australian Diabetes, Obesity and Lifestyle Study, intakes of vegetables and potatoes were assessed via a food frequency questionnaire at baseline. Associations between vegetable intake and (1) fasting plasma glucose (FPG), 2-hour postload plasma glucose (PLG), updated homeostasis …

Defining Spine Cancer Pain Syndromes: A Systematic Review And Proposed Terminology, Markian Pahuta, Ilya Laufer, Sheng-Fu Larry Lo, Stefano Boriani, Charles Fisher, Nicolas Dea, Michael H Weber, Dean Chou, Arjun Sahgal, Laurence Rhines, Jeremy Reynolds, Aron Lazary, Alessandro Gasbarrinni, Jorrit-Jan Verlaan, Ziya Gokaslan, Chetan Bettegowda, Mohamed Sarraj, Ori Barzilai, Ao Spine Knowledge Forum Tumor

Faculty, Staff and Student Publications

STUDY DESIGN: Systematic Review.

OBJECTIVES: Formalized terminology for pain experienced by spine cancer patients is lacking. The common descriptors of spine cancer pain as mechanical or non-mechanical is not exhaustive. Misdiagnosed spinal pain may lead to ineffective treatment recommendations for cancer patients.

METHODS: We conducted a systematic review of pain terminology that may be relevant to spinal oncology patients. We provide a comprehensive and unbiased summary of the existing evidence, not limited to the spine surgery literature, and subsequently consolidate these data into a practical, clinically relevant nomenclature for spine oncologists.

RESULTS: Our literature search identified 3515 unique citations. Through …

The Influence Of The Microbiome On Radiotherapy And Dna Damage Responses, Aadil Sheikh, Michael A Curran

Faculty, Staff and Student Publications

Colorectal cancer (CRC) is one of the most prevalent cancers in terms of diagnosis and mortality. Radiotherapy (RT) remains a mainstay of CRC therapy. As RT relies on DNA damage to promote tumor cell death, the activity of cellular DNA damage repair pathways can modulate cancer sensitivity to therapy. The gut microbiome has been shown to influence intestinal health and is independently associated with CRC development, treatment responses and outcomes. The microbiome can also modulate responses to CRC RT through various mechanisms such as community structure, toxins and metabolites. In this review we explore the use of RT in the …

Patient-Reported Outcomes During Pelvic Radiation Therapy: A Secondary Analysis On Sexual Function From Nrg-Rtog 1203, Kelsey L Corrigan, Rebecca Paulus, Ann H Klopp, Lari B Wenzel, Anamaria R Yeung, J Spencer Thompson, Desiree E Doncals, Vijayananda Kundapur, Nancy H Wiggers, Dasarahally S Mohan, Sharad A Ghamande, Shannon N Westin, Kara L Schnarr, Michael L Haas, David K Gaffney, Steven E Waggoner, Pamela J Vanderwall, Noha T Jastaniyah, Stephanie L Pugh, Lisa A Kachnic

Faculty, Staff and Student Publications

Purpose: NRG-RTOG 1203 reported that intensity-modulated radiation therapy (IMRT) reduced patient-reported GI toxicities in patients with cervical/endometrial cancer receiving postoperative RT, compared with 3-dimensional conformal radiation therapy (3DRT). We conducted a secondary analysis of patient-reported sexual function (PR-SF) among treatment groups to identify factors associated with sexual dysfunction.

Methods and materials: Patients on NRG-RTOG 1203 were randomly assigned to 3DRT versus IMRT and completed Patient-Reported Outcomes (PRO)-Common Terminology Criteria for Adverse Events (CTCAE) and FACT-Cx surveys at baseline, week 5 of RT, and at 4-6 weeks, 1 year, and 3 years after RT. Patient responses to FACT-Cx sexual function questions …

Reproducibility And Repeatability Of 18f-(2s, 4r)-4-Fluoroglutamine Pet Imaging In Preclinical Oncology Models, Gregory D Ayers, Allison S Cohen, Seong-Woo Bae, Xiaoxia Wen, Alyssa Pollard, Shilpa Sharma, Trey Claus, Adria Payne, Ling Geng, Ping Zhao, Mohammed Noor Tantawy, Seth T Gammon, H Charles Manning

Faculty, Staff and Student Publications

Introduction: Measurement of repeatability and reproducibility (R&R) is necessary to realize the full potential of positron emission tomography (PET). Several studies have evaluated the reproducibility of PET using 18F-FDG, the most common PET tracer used in oncology, but similar studies using other PET tracers are scarce. Even fewer assess agreement and R&R with statistical methods designed explicitly for the task. 18F-(2S, 4R)-4-fluoro-glutamine (18F-Gln) is a PET tracer designed for imaging glutamine uptake and metabolism. This study illustrates high reproducibility and repeatability with 18F-Gln for in vivo research.

Methods: Twenty mice bearing colorectal cancer cell line xenografts were injected with ~9 …

Patterns Of Loco-Regional Progression And Patient Outcomes After Definitive-Dose Radiation Therapy For Anaplastic Thyroid Cancer, Julianna K Bronk, Alexander Augustyn, Abdallah S R Mohamed, C David Fuller, Adam S Garden, Amy C Moreno, Anna Lee, William H Morrison, Jack Phan, Jay P Reddy, David I Rosenthal, Michael T Spiotto, Steven J Frank, Ramona Dadu, Naifa Busaidy, Mark Zafereo, Jennifer R Wang, Anastasios Maniakas, Renata Ferrarotto, Priyanka C Iyer, Maria E Cabanillas, G Brandon Gunn

Faculty, Staff and Student Publications

Background: The aim of this study is to characterize the patterns of loco-regional progression (LRP) and outcomes after definitive-dose intensity modulated radiation therapy (IMRT) for anaplastic thyroid cancer (ATC) with macroscopic neck disease at the time of IMRT.

Methods: Disease/treatment characteristics and outcomes for patients with unresected or incompletely resected ATC who received IMRT (≥45 Gy) were retrospectively reviewed. For those with LRP after IMRT, progressive/recurrent gross tumor volumes (rGTV) were contoured on diagnostic CTs and co-registered with initial planning CTs using deformable image registration. rGTVs were classified based on established spatial/dosimetric criteria.

Results: Forty patients treated between 2010-2020 formed …

Selective Inhibition Of Canonical Stat3 Signaling Suppresses K-Ras Mutant Lung Tumorigenesis And Reinvigorates Anti-Tumor Immunity, Michael J Clowers, Zahraa Rahal, Sung-Nam Cho, Avantika Krishna, Bo Yuan, Leticia G Hamana Zorrilla, T Kris Eckols, Moses M Kasembeli, Samuel Liu, Stephen Peng, Marco Ramos-Castaneda, Annamarie L Thompson, Carlos Ignacio Rodriguez Reyna, Katherine E Larsen, Maria T Grimaldo, Shanshan Deng, Nastaran Karimi, Cody Chou, Walter V Velasco, Melody Zarghooni, Sayan Alekseev, Luisa M Solis Soto, Edwin J Ostrin, Humam Kadara, Suhendan Ekmekcioglu, David J Tweardy, Seyed Javad Moghaddam

Faculty, Staff and Student Publications

Introduction: K-ras mutant lung adenocarcinoma (KM-LUAD) is a difficult-to-treat cancer subtype in which chronic inflammation pervades the tumor immune microenvironment (TIME). Pro-inflammatory pathways dampen the response to treatments, including immune checkpoint inhibitors, necessitating therapies that target this inflammatory signaling network in the TIME. One of the lynchpins of chronic inflammation in KM-LUAD is signal transducer and activator of transcription 3 (STAT3).

Methods: Here, we tested the anti-tumor and early immunotherapeutic efficacy of TTI-101, a selective small-molecule inhibitor of canonical STAT3 signaling, in a K-rasG12D mutant lung cancer mouse model (CC-LR).

Results: Treatment of CC-LR mice with TTI-101 resulted in reduced …

Dedifferentiated Liposarcomas Treated With Immune Checkpoint Blockade: The Md Anderson Experience, Madeline B Torres, Cheuk Hong Leung, Marianne Zoghbi, Rossana Lazcano, Davis Ingram, Khalida Wani, Emily Z Keung, M Alejandra Zarzour, Christopher P Scally, Kelly K Hunt, Anthony Conley, Andrew J Bishop, B Ashleigh Guadagnolo, Ahsan Farooqi, Devarati Mitra, Alison K Yoder, Michael S Nakazawa, Dejka Araujo, Andrew Livingston, Ravin Ratan, Shreyaskumar Patel, Vinod Ravi, Alexander J Lazar, Christina L Roland, Neeta Somaiah, Elise F Nassif Haddad

Faculty, Staff and Student Publications

Background: Dedifferentiated liposarcoma (DDLPS) is one of the most common types of soft tissue sarcoma (STS) characterized by liposarcomatous differentiation and a predilection for the retroperitoneum. Despite the growing number of histology-specific immune checkpoint blockade (ICB) trials in STS, it is still difficult to identify the radiographic objective response rate (ORR) for DDLPS in the real world setting. This study aimed to evaluate the ORR and survival of patients with DDLPS treated with ICB at a single center.

Methods: We conducted a retrospective study of 31 patients with pathologically confirmed DDLPS treated with ICB at MD Anderson Cancer Center between …

A Plain Language Summary Of The Final Analysis Of The Griffin Study Of Daratumumab Plus Lenalidomide, Bortezomib, And Dexamethasone For People With Newly Diagnosed Multiple Myeloma, Peter M Voorhees, Douglas W Sborov, Jacob Laubach, Jonathan L Kaufman, Brandi Reeves, Cesar Rodriguez, Rebecca Silbermann, Luciano J Costa, Larry D Anderson, Nitya Nathwani, Nina Shah, Naresh Bumma, Yvonne A Efebera, Sarah A Holstein, Caitlin Costello, Andrzej Jakubowiak, Tanya M Wildes, Robert Z Orlowski, Kenneth H Shain, Andrew J Cowan, Shira Dinner, Katharine S Gries, Huiling Pei, Annelore Cortoos, Sharmila Patel, Thomas S Lin, Saad Z Usmani, Paul G Richardson

Faculty, Staff and Student Publications

No abstract provided.

Grape-Pi: Graph-Based Neural Networks For Enhanced Protein Identification In Proteomics Pipelines, Chunhui Gu, Seyyed Mahmood Ghasemi, Yining Cai, Johannes F Fahrmann, James P Long, Hiroyuki Katayama, Chong Wu, Jody Vykoukal, Jennifer B Dennison, Samir Hanash, Kim-Anh Do, Ehsan Irajizad

Faculty, Staff and Student Publications

Motivation: Protein identification via mass spectrometry (MS) is the primary method for untargeted protein detection. However, the identification process is challenging due to data complexity and the need to control false discovery rates (FDR) of protein identification. To address these challenges, we developed a graph neural network (GNN)-based model, Graph Neural Network using Protein-Protein Interaction for Enhancing Protein Identification (Grape-Pi), which is applicable to all proteomics pipelines. This model leverages protein-protein interaction (PPI) data and employs two types of message-passing layers to integrate evidence from both the target protein and its interactors, thereby improving identification accuracy.

Results: Grape-Pi achieved significant …

A Critical Assessment Of Artificial Intelligence In Magnetic Resonance Imaging Of Cancer, Chengyue Wu, Meryem Abbad Andaloussi, David A Hormuth, Ernesto A B F Lima, Guillermo Lorenzo, Casey E Stowers, Sriram Ravula, Brett Levac, Alexandros G Dimakis, Jonathan I Tamir, Kristy K Brock, Caroline Chung, Thomas E Yankeelov

Faculty, Staff and Student Publications

Given the enormous output and pace of development of artificial intelligence (AI) methods in medical imaging, it can be challenging to identify the true success stories to determine the state-of-the-art of the field. This report seeks to provide the magnetic resonance imaging (MRI) community with an initial guide into the major areas in which the methods of AI are contributing to MRI in oncology. After a general introduction to artificial intelligence, we proceed to discuss the successes and current limitations of AI in MRI when used for image acquisition, reconstruction, registration, and segmentation, as well as its utility for assisting …

Ganglioside Gd2 Contributes To A Stem-Like Phenotype In Intrahepatic Cholangiocarcinoma, Antonella Mannini, Mirella Pastore, Alessia Giachi, Margherita Correnti, Elena Spínola Lasso, Tiziano Lottini, Benedetta Piombanti, Ignazia Tusa, Elisabetta Rovida, Cédric Coulouarn, Jesper B Andersen, Monika Lewinska, Claudia Campani, V Lokesh Battula, Bin Yuan, Massimo Aureli, Emma V Carsana, Caterina Peraldo Neia, Paola Ostano, Alessia Tani, Daniele Nosi, Anna Vanni, Laura Maggi, Luca Di Tommaso, Giuseppina Comito, Stefania Madiai, Annarosa Arcangeli, Fabio Marra, Chiara Raggi

Faculty, Staff and Student Publications

BACKGROUND & AIMS: GD2, a member of the ganglioside (GS) family (sialic acid-containing glycosphingolipids), is a potential biomarker of cancer stem cells (CSC) in several tumours. However, the possible role of GD2 and its biosynthetic enzyme, GD3 synthase (GD3S), in intrahepatic cholangiocarcinoma (iCCA) has not been explored.

METHODS: The stem-like subset of two iCCA cell lines was enriched by sphere culture (SPH) and compared to monolayer parental cells (MON). GS profiles were evaluated by chromatography, after feeding with radioactive sphingosine. Membrane GD2 expression was evaluated by FACS, and the expression of enzymes of GS biosynthesis was analysed by RT-qPCR. The …

Ft538, Ipsc-Derived Nk Cells, Enhance Aml Cell Killing When Combined With Chemotherapy, Amanda Eckstrom, Anudishi Tyagi, Sajid Mahmood, Lilly Wong, Bahram Valamehr, Adishwar Rao, Akriti Agrawal, Maryam Siddiqui, V Lokesh Battula

Faculty, Staff and Student Publications

Induced pluripotent stem cell (iPSC)-derived natural killer (NK) cells offer an opportunity for a standardized, off-the-shelf treatment with the potential to treat a wider population of acute myeloid leukaemia (AML) patients than the current standard of care. FT538 iPSC-NKs express a high-affinity, noncleavable CD16 to maximize antibody dependent cellular cytotoxicity, a CD38 knockout to improve metabolic fitness, and an IL-15/IL-15 receptor fusion preventing the need for cytokine administration, the main source of adverse effects in NK cell-based therapies. Here, we sought to evaluate the potential of FT538 iPSC-NKs as a therapy for AML through their effect on AML cell lines …

18 Kda Translocator Protein (Tspo) Is Upregulated In Rat Brain After Peripheral Nerve Injury And Downregulated By Diroximel Fumarate, Rafael A Cazuza, Sever M Zagrai, Anamaria R Grieco, Thomas D Avery, Andrew D Abell, Hsiao-Ying Wey, Marco L Loggia, Peter M Grace

Faculty, Staff and Student Publications

Neuroimmune signaling is a key process underlying neuropathic pain. Clinical studies have demonstrated that 18 kDa translocator protein (TSPO), a putative marker of neuroinflammation, is upregulated in discrete brain regions of patients with chronic pain. However, no preclinical studies have investigated TSPO dynamics in the brain in the context of neuropathic pain and in response to analgesic treatments. We used positron emission tomography-computed tomography (PET-CT) and [18F]-PBR06 radioligand to measure TSPO levels in the brain across time after chronic constriction injury (CCI) of the sciatic nerve in both male and female rats. Up to 10 weeks post-CCI, TSPO expression was …

High-Grade B-Cell Lymphoma Not Otherwise Specified, With Diffuse Large B-Cell Lymphoma Gene Expression Signatures: Genomic Analysis And Potential Therapeutics, Waseem Lone, Alyssa Bouska, Tyler A Herek, Catalina Amador, Joo Song, Alexander M Xu, Dylan Jochum, Issa Ismail Issa, Dennis D Weisenburger, Xuan Zhang, Sharath Kumar Bhagavathi, Tayla B Heavican-Foral, Sunandini Sharma, Ab Rauf Shah, Abdul Rouf Mir, Aisha Ahmad Alkhinji, Dalia El-Gamal, Bhavana J Dave, Keenan Hartert, Jiayu Yu, Mallick Saumyaranjan, Timothy C Greiner, Julie Vose, Timothy W Mckeithan, Kai Fu, Michael Green, Chengfeng Bi, Akil Merchant, Wing C Chan, Javeed Iqbal

Faculty, Staff and Student Publications

High-grade B-cell lymphoma not otherwise specified (HGBCL, NOS) has overlapping morphological and genetic features with diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma (BL), leading to uncertainty in its diagnosis and clinical management. Using functional genomic approaches, we previously characterized HGBCL and NOS, that demonstrate gene expression profiling (GEP), and genetic signatures similar to BL. Herein, we characterize distinct HGBCL, NOS, cohort (n = 55) in adults (n = 45) and in children (n = 10), and compared the GEP, genomic DNA copy number (CN), and mutational spectrum with de novo DLBCL (n = 85) and BL (n = 52). …

Plasma Dna Methylation-Based Biomarkers For Mpnst Detection In Patients With Neurofibromatosis Type 1, Katarzyna Tomczak, Manishkumar S Patel, Angela D Bhalla, Christine B Peterson, Sharon M Landers, S Carson Callahan, Di Zhang, Justin Wong, Jace P Landry, Alexander J Lazar, J Andrew Livingston, B Ashleigh Guadagnolo, Heather G Lyu, Heather Lillemoe, Christina L Roland, Emily Z Keung, Christopher P Scally, Kelly K Hunt, Ian E Mccutcheon, John M Slopis, Jian Gu, Paul Scheet, Liang Wang, Kunal Rai, Keila E Torres

Faculty, Staff and Student Publications

Malignant peripheral nerve sheath tumor (MPNST) development is characterized by an altered DNA methylation landscape, which presents a promising area for developing MPNST-specific biomarkers for screening patients with NF1. Genome-wide DNA methylation profiling of a cohort of 13 patients with MPNST (29 samples of tumor and adjacent neurofibroma tissues) and of NF1-MPNST cell lines was performed to identify and validate candidate MPNST-specific CpG sites (CpGs). A logistic regression prediction model was constructed to select MPNST-specific CpGs distinct from adjacent neurofibromas and normal tissues. To test if hypermethylation at selected CpGs can also be detected in plasma from patients with MPNST, …

Approach To Determining Etiology Of Hypophosphatemia In A Patient With Coexisting Phosphaturic Mesenchymal Tumor And Fibrous Dysplasia, Madhuri D Patil, Sintawat Wangsiricharoen, Alexander J Lazar, Bryan Moon, John E Madewell, Michael T Collins, Theresa A Guise

Faculty, Staff and Student Publications

Dysregulated FGF23 production is a demonstrated cause of hypophosphatemia and osteomalacia. Diseases associated with these conditions include phosphaturic mesenchymal tumor (PMT) causing tumor induced osteomalacia, various forms of rickets, and fibrous dysplasia (FD). Coexistence of 2 conditions that can increase FGF23 concentrations is rare. We report a case of a 79-yr-old man who presented with rib and right flank pain. Imaging revealed bone lesions in the right iliac wing, left supra-acetabular area, and L4 vertebral body. Biopsies showed a right iliac PMT and left supra-acetabular FD. Cryoablation of both lesions resolved the phosphaturia with normalization of phosphorus level. Coexistence of …

Ntrk Fusion-Positive Thyroid Carcinoma: From Diagnosis To Targeted Therapy, Vicente R Marczyk, Sasan Fazeli, Ramona Dadu, Naifa L Busaidy, Priyanka Iyer, Mimi I Hu, Steven I Sherman, Sarah Hamidi, Sayed Mohsen Hosseini, Michelle D Williams, Salmaan Ahmed, Mark J Routbort, Raja Luthra, Sinchita Roy-Chowdhuri, Francis Anthony San Lucas, Keyur P Patel, David S Hong, Mark Zafereo, Jennifer R Wang, Anastasios Maniakas, Steven G Waguespack, Maria E Cabanillas

Faculty, Staff and Student Publications

Purpose: Neurotrophic tropomyosin receptor kinase (NTRK) fusions may act as an oncogenic driver in thyroid carcinomas. Given their low frequency, clinical, pathological, and molecular data on these patients and their responses to targeted therapies are limited.

Methods: This is an observational retrospective study conducted at a single high-volume cancer center in the United States. Data were retrospectively collected from medical records.

Results: We included 65 patients (37 adult, 28 pediatric) with an NTRK fusion-positive thyroid carcinoma (24 NTRK1, 41 NTRK3), of which 54 were papillary thyroid carcinomas (PTC), four poorly differentiated thyroid carcinomas (PDTC), and seven …

Overview Of The Head And Neck Tumor Segmentation For Magnetic Resonance Guided Applications (Hnts-Mrg) 2024 Challenge, Kareem A Wahid, Cem Dede, Dina M El-Habashy, Serageldin Kamel, Michael K Rooney, Yomna Khamis, Moamen R A Abdelaal, Sara Ahmed, Kelsey L Corrigan, Enoch Chang, Stephanie O Dudzinski, Travis C Salzillo, Brigid A Mcdonald, Samuel L Mulder, Lucas Mccullum, Qusai Alakayleh, Carlos Sjogreen, Renjie He, Abdallah S R Mohamed, Stephen Y Lai, John P Christodouleas, Andrew J Schaefer, Mohamed A Naser, Clifton D Fuller

Faculty, Staff and Student Publications

Magnetic resonance (MR)-guided radiation therapy (RT) is enhancing head and neck cancer (HNC) treatment through superior soft tissue contrast and longitudinal imaging capabilities. However, manual tumor segmentation remains a significant challenge, spurring interest in artificial intelligence (AI)-driven automation. To accelerate innovation in this field, we present the Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024 Challenge, a satellite event of the 27th International Conference on Medical Image Computing and Computer Assisted Intervention. This challenge addresses the scarcity of large, publicly available AI-ready adaptive RT datasets in HNC and explores the potential of incorporating multi-timepoint data to enhance RT …

Lp-118 Is A Novel B-Cell Lymphoma 2 / Extra-Large Inhibitor That Demonstrates Efficacy In Models Of Venetoclaxresistant Chronic Lymphocytic Leukemia, Janani Ravikrishnan, Daisy Y Diaz-Rohena, Elizabeth Muhowski, Xiaokui Mo, Tzung-Huei Lai, Shrilekha Misra, Charmelle D Williams, John Sanchez, Andrew Mitchell, Suresh Satpati, Elizabeth Perry, Tierney Kaufman, Chaomei Liu, Arletta Lozanski, Gerard Lozanski, Kerrya Rogers, Adam S Kittai, Seema A Bhat, Mary C Collins, Matthew S Davids, Nitin Jain, William G Wierda, Rosa Lapalombella, John C Byrd, Fenlai Tan, Yi Chen, Yu Chen, Yue Shen, Stephen P Anthony, Jennifer A Woyach, Deepa Sampath

Faculty, Staff and Student Publications

Patients with chronic lymphocytic leukemia (CLL) respond well to initial treatment with the B-cell lymphoma 2 (BCL2) inhibitor venetoclax. Upon relapse, they often retain sensitivity to BCL2 targeting, but durability of response remains a concern. We hypothesize that targeting both BCL2 and B-cell lymphoma-extra large (BCLXL) will be a successful strategy to treat CLL, including for patients who relapse on venetoclax. To test this hypothesis, we conducted a pre-clinical investigation of LP-118, a highly potent inhibitor of BCL2 with moderate BCLXL inhibition to minimize platelet toxicity. This study demonstrated that LP-118 induces efficient BAK activation, cytochrome C release, and apoptosis …

Optimal Timing Of Organs-At-Risk-Sparing Adaptive Radiation Therapy For Head-And-Neck Cancer Under Re-Planning Resource Constraints, Fatemeh Nosrat, Cem Dede, Lucas B Mccullum, Raul Garcia, Abdallah S R Mohamed, Jacob G Scott, James E Bates, Brigid A Mcdonald, Kareem A Wahid, Mohamed A Naser, Renjie He, Aysenur Karagoz, Amy C Moreno, Lisanne V Van Dijk, Kristy K Brock, Jolien Heukelom, Seyedmohammadhossein Hosseinian, Mehdi Hemmati, Andrew J Schaefer, Clifton D Fuller

Faculty, Staff and Student Publications

Background and purpose: Prior work on adaptive organ-at-risk (OAR)-sparing radiation therapy has typically reported outcomes based on fixed-number or fixed-interval re-planning, which represent one-size-fits-all approaches and do not account for the variable progression of individual patients' toxicities. The purpose of this study was to determine the personalized optimal timing of re-planning in adaptive OAR-sparing radiation therapy, considering limited re-planning resources, for patients with head and neck cancer (HNC).

Materials and methods: A novel Markov decision process (MDP) model was developed to determine optimal timing of re-planning based on the patient's expected toxicity, characterized by normal tissue complication probability (NTCP), for …