Digital Commons Network^™

Association Of Pathogenic/Likely Pathogenic Inherited Cardiomyopathy Variants With Heart Failure: A Topmed Multiancestry Analysis, Naman S Shetty, Mokshad Gaonkar, Akhil Pampana, Nirav Patel, April P Carson, Bernhard Haring, Bruce M Psaty, Charles Kooperberg, Eric Boerwinkle, Jerome I Rotter, João A C Lima, Jorge R Kizer, Lisa Warsinger Martin, Kent D Taylor, Michael E Hall, Myriam Fornage, Sanjiv J Shah, Stephen S Rich, Ramachandran S Vasan, Rami Nassir, Peng Li, Garima Arora, Pankaj Arora

Faculty, Staff and Student Publications

OBJECTIVE: To evaluate the prevalence of pathogenic/likely pathogenic inherited cardiomyopathy variants and their association with heart failure in the (TOPMed) TransOmic for Precision of Medicine cohorts.

METHODS: A retrospective cohort study using the TOPMed cohorts, including multi-ancestry US adults (≥18 years of age) with sequencing data, was conducted. Pathogenic/likely pathogenic inherited cardiomyopathy variant carrier status was determined based on ClinVar variants classified with two or more stars of evidence. Individuals without pathogenic/likely pathogenic variants were used as the reference group. The primary outcome was heart failure , adjudicated by an expert panel. Cox proportional hazards models assessed the association between …

Microbial Signals In Primary And Metastatic Brain Tumors, Golnaz Morad, Ashish V Damania, Brenda Melendez, Bharat B Singh, Fabiana J Veguilla, Rebecca A Soto, Yasmine M Hoballah, Pranoti V Sahasrabhojane, Matthew C Wong, Mona M Ahmed, Rene N Rico, Kaitlyn N Lewis, Khalida Wani, Diana D Shamsutdinova, Rossana N Lazcano Segura, Davis R Ingram, Eric A Goethe, Abderrahman Day, Ivonne I Flores, Lauren K Mcdaniel, Manoj Chelvanambi, Sarah B Johnson, Florentia Dimitriou, Pravesh Gupta, Shivangi Oberai, M Anna Zal, Phoebe Doss, Mohamed A Jamal, Eiko Hayase, Chetna Wathoo, Lisa M Norberg, Stephanie L Jenkins, Sara Nass, Joy Gumin, Lihong Long, Jing Yang, Gina R Bradley, Mahesh Prasad Bekal, Antonio G Dono, Pavel S Pichardo-Rojas, Samuel W Andrewes, Leomar Y Ballester, Jillian S Losh, Jiyong Liang, Longfei Huo, Douglas C Nielsen, Brittany C Parker Kerrigan, Priscilla K Brastianos, Natalie Wall Fowlkes, Chia-Chi Chang, Robert R Jenq, Candelaria Gomez-Manzano, Jason T Huse, Michael A Davies, Alexander J Lazar, Krishna P Bhat, Nitin Tandon, Yoshua Esquenazi, Christine B Peterson, Vinay K Puduvalli, Frederick F Lang, Christopher D Johnston, Susan Bullman, Nadim J Ajami, Sherise D Ferguson, Jennifer A Wargo

Faculty, Staff and Student Publications

Gliomas and brain metastases are associated with poor prognosis, necessitating a deeper understanding of brain tumor biology and the development of effective therapeutic strategies. Although our group and others have demonstrated microbial presence in various tumors, recent controversies regarding cancer-type-specific intratumoral microbiota emphasize the importance of rigorous, orthogonal validation. This prospective, multi-institutional study included a total of 243 samples from 221 patients, comprising 168 glioma and brain metastases samples and 75 non-cancerous or tumor-adjacent tissues. Using stringent fluorescence in situ hybridization, immunohistochemistry and high-resolution spatial imaging, we detected intracellular bacterial 16S rRNA and lipopolysaccharides in both glioma and brain metastases …

Exploring Multimodal Large Language Models On Transthoracic Echocardiogram (Tte) Tasks For Cardiovascular Decision Support, Jianfu Li, Yiming Li, Zenan Sun, Evan Yu, Ahmed M Abdelhameed, Weiguo Cao, Haifang Li, Jianping He, Pengze Li, Jingna Feng, Yue Yu, Xinyue Hu, Manqi Li, Rakesh Kumar, Yifang Dang, Fang Li, Shahyar M Gharacholou, Cui Tao

Faculty, Staff and Student Publications

Objective: Multimodal large language models (LLMs) offer new potential for enhancing cardiovascular decision support, particularly in interpreting echocardiographic data. This study systematically evaluates and benchmarks foundation models from diverse domains on echocardiogram-based tasks to assess their effectiveness, limitations and potential in clinical cardiovascular applications.

Methods: We curated three cardiovascular imaging datasets-EchoNet-Dynamic, TMED2, and an expert-annotated echocardiogram (TTE) dataset-to evaluate performance on four critical tasks: (1) cardiac function evaluation through ejection fraction (EF) prediction, (2) cardiac view classification, (3) aortic stenosis (AS) severity assessment, and (4) cardiovascular disease classification. We evaluated six multimodal LLMs: EchoClip (cardiovascular-specific), BiomedGPT and LLaVA-Med (medical-domain), and …

Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, And Multi-Modal Learning, Cheng Peng, Kai Zhang, Mengxian Lyu, Hongfang Liu, Lichao Sun, Yonghui Wu

Faculty, Staff and Student Publications

Objective: To advance biomedical vision language model capabilities through scaling up, fine-tuning, and instruction tuning, develop vision-language models with improved performance in handling long text, explore strategies to efficiently adopt vision language models for diverse multi-modal biomedical tasks, and examine the zero-shot learning performance.

Methods: We developed two biomedical vision language models, BiomedGPT-Large and BiomedGPT-XLarge, based on an encoder-decoder-based transformer architecture. We fine-tuned the two models on 23 benchmark datasets from 6 multi-modal biomedical tasks, including one image-only task (image classification), three language-only tasks (text understanding, text summarization, and question answering), and two vision-language tasks (visual question answering and image …

Outcomes And Patterns Of Relapse Of Npm1 Mutated Acute Myeloid Leukemia Treated With Venetoclax Based Therapies, Wei-Ying Jen, Sanam Loghavi, Alexandre Bazinet, Alex Bataller, Ian Bouligny, Naval G Daver, Ghayas C Issa, Naszrin Arani, Emmanuel Almanza Huante, Abhishek Maiti, Guillermo Montalban-Bravo, Gautam Borthakur, Nicholas J Short, Sherry Pierce, Elias Jabbour, Guillermo Garcia-Manero, Farhad Ravandi, Hagop M Kantarjian, Courtney D Dinardo, Tapan M Kadia

Faculty, Staff and Student Publications

No abstract provided.

A Tour Of Leukemia Progress In 2025, Viewed Through The Md Anderson Leukemia Research Lens, Hagop M Kantarjian, Gautam Borthakur, Naval Daver, Courtney Dinardo, Guillermo Garcia-Manero, Ghayas Issa, Elias Jabbour, Nitin Jain, Tapan Kadia, Sanam Loghavi, Farhad Ravandi, Guilin Tang, Mary Alma Welch, William Wierda

Faculty, Staff and Student Publications

Advances in the prognostication, monitoring, and treatment of both the acute and chronic leukemias have led to drastically improved outcomes over the past 2 decades. With the advent of targeted therapies, including antibodies such as blinatumomab and inotuzumab and small molecule inhibitors, such as the BCR::ABL1 tyrosine kinase inhibitors, Bruton tyrosine kinase inhibitors, and venetoclax, the treatment landscape of leukemia has drastically changed, improving survival outcomes while relying less on overall chemotherapy intensity in many leukemia types. This progress has allowed the categorization of more leukemia types as favorable (i.e., chronic lymphocytic leukemia, younger acute lymphoblastic leukemia [patients younger than …

Brain-Wide Patterns Of Crf Receptor 1 Expression In The Transgenic Crfr1-Cre-2a-Tdtom Rat, Douglas S Engelke, Lierni Ugartemendia, Jonathan Tao, Shivakumar Rajamanikam, Fabricio H Do Monte, Nicholas J Justice

Faculty, Staff and Student Publications

The ability to manipulate neurons that express corticotropin-releasing factor (CRF) or its receptors has led to many new discoveries about how CRF signaling modulates stress-related behaviors in mice. However, similar advances in rats have been limited by the lack of reporter lines targeting CRF receptors, restricting access to behavioral paradigms that are more suitable for, or specific to, rats. Here, we provide an extensive neuroanatomical characterization of a recently generated CRFR1-Cre rat. We show that Cre and tdTomato are expressed in a pattern that closely aligns with previously reported CRFR1 expression patterns, as determined by in situ hybridization in rats …

Probabilistic Template Matching For Detecting Resting-State Functional Mri Language Network In Brain Tumor Patients, Jian Ming Teo, Vinodh A Kumar, Alexander M Khalaf, Kyle R Noll, Sherise D Ferguson, Chibawanye I Ene, Sujit S Prabhu, Max Wintermark, Ho-Ling Liu

Faculty, Staff and Student Publications

Background: Intersubject variation among patients with brain tumors complicates the template matching process for detecting the resting-state (rs) functional MRI (fMRI) language network when using independent component analysis (ICA).

Purpose: This study aimed to develop methods that use a probabilistic language atlas to incorporate intersubject variation in brain tumor patients into the template matching process.

Methods: This retrospective study included 79 patients with brain tumors (average age, 50 ± 15 years) who underwent presurgical task-based (tb)-fMRI and rs-fMRI at clinical 3T scanners. At varying template generation thresholds (τ), binary and probabilistic templates were obtained from the language atlas. A binary …

Tagraxofusp, A Cd123-Targeted Therapy, For Chronic Myelomonocytic Leukemia: Final Results Of A Phase 1/2 Study, Mrinal M Patnaik, Haris Ali, Eunice S Wang, Abdulraheem Yacoub, James M Foran, Vikas Gupta, Gary J Schiller, Don Ambrose Stevens, Moshe Talpaz, Sarah Wall, Terra L Lasho, Abhishek A Mangaonkar, Talha Badar, Ross Lindsay, Antonio Galleu, Ira Gupta, Naveen Pemmaraju, Guillermo Garcia-Manero

Faculty, Staff and Student Publications

Chronic myelomonocytic leukemia (CMML) is an aggressive hematologic neoplasm characterized by an expansion of CD123+ monocytes and plasmacytoid dendritic cells (pDCs). pDC bone marrow clusters in CMML have been associated with higher rates of acute myeloid leukemia transformation. We evaluated tagraxofusp, a CD123-targeted therapy, in a phase 1/2 trial for patients with CMML. There were no dose-limiting toxicities. At the recommended phase 2 dose of 12 μg/kg per day, 37 patients were treated: 15 were treatment naïve; 22 had relapsed/refractory disease (median number of previous therapies, 1 [range, 1-7]). Common nonhematologic treatment-emergent adverse events (AEs) included fatigue (49%), hypoalbuminemia (46%), …

Meeting Report From The 2024 Symposium On Irak4 In Cancer: Highlights And Clinical Updates, Eric S Winer, Marina Konopleva, Han W Tun, Kian-Huat Lim, Bently Doonan, Klaus H Metzeler, Lakshmi Nayak, Andrés J M Ferreri, Christina Von Roemeling, Grzegorz S Nowakowski, Guillermo Garcia-Manero

Faculty, Staff and Student Publications

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a serine/threonine kinase that mediates interleukin-1 and Toll-like receptor (TLR) signaling. IRAK4 drives the activation of nuclear factor kappa B (NF-κB), which promotes cell survival, inflammation, and proliferation. Aberrant activation of IRAK4 and TLR signaling has been implicated in multiple malignancies. At the 3rd Annual IRAK4 in Cancer Symposium, experts discussed the role of IRAK4 in cancer biology, the potential for synergism between IRAK4 inhibition and other treatments to overcome resistance, and how IRAK4 inhibition may improve clinical outcomes. Preclinical data were presented demonstrating the activity of IRAK4 inhibition alone or in combination with …

Continuous Androgen Deprivation Therapy With Or Without Metastasis-Directed Therapy For Oligometastatic Prostate Cancer: The Multicenter Phase 2 Randomized Extend Trial, Alexander D Sherry, Bilal A Siddiqui, Cara Haymaker, Bryan M Fellman, Marina N Medina-Rosales, Tharakeswara K Bathala, Shuqi Wang, Suyu Liu, Aaron Seo, Kieko Hara, Hsinyi Lu, Patricia Troncoso, Stephen G Chun, Chul S Ha, Lauren L Mayo, Henry Mok, Ryan J Park, Brian F Chapin, Ryan M Phillips, Matthew P Deek, Craig A Kovitz, Ana Aparicio, Amado J Zurita, Patrick G Pilie, Lorenzo Cohen, Seungtaek L Choi, Alexandre Reuben, Phuoc T Tran, Paul G Corn, Sumit K Subudhi, Chad Tang

Faculty, Staff and Student Publications

Background and objective: Oligometastatic prostate cancer (omPC) is characterized by limited metastases. We hypothesized that metastasis-directed therapy (MDT) to all sites of omPC combined with androgen deprivation therapy (ADT) would improve clinical outcomes.

Methods: In the multicenter phase 2 EXTEND trial, patients with omPC were randomized 1:1 to ADT versus MDT + ADT in two independently powered and randomized baskets, one using intermittent ADT and one using continuous ADT. The primary endpoint was progression-free survival (PFS). The secondary endpoints included radiologic PFS (rPFS) and castration resistance-free survival (CRFS). Here, the primary results of the continuous ADT basket, the combined analysis …

Rank-Based Learning: A Novel High-Throughput Algorithm Resilient To Missing Data And Effective For Datasets With Small Sample Size, Lulu Song, Hamid Khoshfekr Rudsari, Johannes F Fahrmann, Jody Vykoukal, Sam Hanash, James P Long, Kim-Anh Do, Ehsan Irajizad

Faculty, Staff and Student Publications

High-throughput omics data present challenges for binary classification due to platform variability, batch effects, missing values, and high dimensionality. This study presents a novel Rank-Based Learning (RBL) method that leverages relative feature rankings to improve robustness and generalizability. We evaluated RBL against established methods like Logistic Regression (LR) and Random Forest (RF) using simulated data and two real-world plasma proteomics datasets: early-stage small cell lung cancer (SCLC) and duodenopancreatic neuroendocrine tumors (dpNET) in patients with Multiple Endocrine Neoplasia type 1 (MEN1). In simulation experiments, RBL outperformed LR under conditions involving batch effects, missing data, and varying numbers of true differential …

Corrigendum To "Single-Cell Proteomic Analysis Reveals Multiple Myeloma Heterogeneity And The Dynamics Of The Tumor Immune Microenvironment In Precursor And Advanced States" [Neoplasia 66 (2025) 1101189], Mohamed Kamal, Stephanie N Shishido, Jeremy Mason, Krina Patel, Elisabet E Manasanch, Robert Z Orlowski, Peter Kuhn

Faculty, Staff and Student Publications

No abstract provided.

Integration Of Genetic And Imaging Data For Alzheimer's Disease Diagnosis And Interpretation, Yanfei Wang, Qing Wang, Minghao Zhou, Jialu Liang, Lei You, Breton Asken, Xiaobo Zhou, Qianqian Song

Faculty, Staff and Student Publications

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by complex interactions between genetic risk factors and structural brain changes. Traditional diagnostic approaches that rely on single-modality data, such as imaging or genomics alone, often fall short in both predictive accuracy and biological interpretability. To address these limitations, AlzCLIP, a novel contrastive learning framework that integrates single nucleotide polymorphism (SNP) profiles and MRI-derived imaging features into a unified embedding space is introduced. This joint representation captures disease-relevant interactions between genetic variation and brain structure, enabling both accurate diagnosis and mechanistic insight into AD. AlzCLIP is trained and evaluated on two …

Diffuse Cutaneous Alk-Immunoreactive Histiocytosis With Mef2c::Flt3 Fusion, Sanjana Likki, Kevin Lee, Fiorinda Muhaj, Wei Wang, Pei Lin, Woo Cheal Cho, Doina Ivan, Carlos A Torres-Cabala, Luis Fayad, Jonathan L Curry

Faculty, Staff and Student Publications

No abstract provided.

Data-Driven Abdominal Phenotypes Of Type 2 Diabetes In Lean, Overweight, And Obese Cohorts From Computed Tomography, Lucas W Remedios, Chloe Cho, Trent M Schwartz, Dingjie Su, Gaurav Rudravaram, Chenyu Gao, Aravind R Krishnan, Adam M Saunders, Michael E Kim, Shunxing Bao, Alvin C Powers, Bennett A Landman, John Virostko

Faculty, Staff and Student Publications

Purpose: Although elevated body mass index (BMI) is a well-known risk factor for type 2 diabetes, the disease's presence in some lean adults and absence in others with obesity suggests that more detailed measurements of body composition may uncover abdominal phenotypes of type 2 diabetes. With artificial intelligence (AI) and computed tomography (CT), we can now leverage robust image segmentation to extract detailed measurements of size, shape, and tissue composition from abdominal organs, abdominal muscle, and abdominal fat depots in 3D clinical imaging at scale. This creates an opportunity to empirically define body composition signatures linked to type 2 diabetes …

Basal Cell Carcinoma Risk Prediction In Survivors Of Childhood Cancer, Cindy Im, Christina Boull, Zhe Lu, Kenneth Liao, Hasibul Hasan, Linwan Xu, Yadav Sapkota, Rebecca M Howell, Michael A Arnold, Miriam R Conces, Ashley J Housten, Judith Gebauer, Thorsten Langer, Jop C Teepen, Leontien C M Kremer, Louis S Constine, Yutaka Yasui, Melissa M Hudson, Kirsten K Ness, Gregory T Armstrong, Joseph P Neglia, Yan Yuan, Lucie M Turcotte

Faculty, Staff and Student Publications

Background: Survivors of childhood cancer face excess risk of developing basal cell carcinoma. Age-specific basal cell carcinoma risk prediction models for survivors may support targeted screening recommendations.

Methods: We developed models predicting basal cell carcinoma risk by ages 40 and 50 years featuring detailed cancer treatment predictors, utilizing statistical and machine-learning algorithms and data from 23 166 five-year survivors in the Childhood Cancer Survivor Study, a multi-institutional retrospective cohort study. Selected models were externally validated in 5314 survivors in the St Jude Lifetime Cohort. Model discrimination and precision were evaluated using the area under the receiver operating characteristic curve (AUROC) …

Study Of 18 F-Fluciclovine Pet For Serial Assessment Of Glioblastoma Tumor Volumes During Surgery And Radiotherapy, Samir A Dagher, Jason M Johnson, Rania M M Mohamed, Shehbaz Ansari, Osama Mawlawi, Ho-Ling Liu, Max Wintermark, Dawid Schellingerhout, Lesley Flynt, Debra N Yeboa, Jeffrey S Weinberg, Sherise D Ferguson, Maria K Gule-Monroe

Faculty, Staff and Student Publications

PURPOSE: Recent evidence supports incorporating 18 F-Fluciclovine PET for glioblastoma treatment planning and monitoring, as it better captures tumor infiltration compared to conventional MRI. However, the relationship between PET- and MRI-defined tumor volumes remains unclear, particularly in the post-treatment setting. This study prospectively compares tumor volumes on MRI and PET at multiple timepoints throughout the treatment course and evaluates volumetric changes with therapy.

METHODS: We prospectively enrolled 8 adults with IDH-wildtype glioblastoma treated with surgery and chemoradiation between September 2019 and 2021. Participants underwent paired 18 F-Fluciclovine PET/CT and conventional MRI at four timepoints: preoperatively, pre-radiation, and at one- and …

B-Cell-Specific Wwox Deletion Promotes Plasmablastic Tumor Development And Proinflammatory Signatures In Myeloma Model, Tabish Hussain, Matthew D Bramble, Bin Liu, Martin C Abba, Marta Chesi, C Marcelo Aldaz

Faculty, Staff and Student Publications

Deletions and translocations affecting WWOX accompanied by loss of expression are frequently observed in B-cell neoplasms and are linked to poor prognosis. Our previous research showed that Wwox deletion early in B-cell development induces genomic instability, neoplastic transformation, and monoclonal gammopathies in mice. In this study, by crossing Cd19 Wwox knockout (KO) with Vk^∗MYC myeloma model mice, we generated a model with concurrent Wwox deletion and MYC activation, reproducing 2 common oncogenic alterations in B- and plasma-cell cancers. We observed that Vk^∗MYC:Wwox KO mice exhibited significantly reduced survival rates primarily due to the development of plasmablastic …