Medicine and Health Sciences Commons^™

Lefitolimod In Combination With Ipilimumab In Patients With Advanced Solid Tumors: A Phase I Trial, Mirella Nardo, Mohamed A Gouda, Matthew J Reilley, Amadeo B Biter, Joann Lim, Stacie A Bean, Ly M Nguyen, Priya R Bhosale, Casey R Ager, Coline A Couillault, Sarina A Piha-Paul, Siqing Fu, Apostolia M Tsimberidou, Timothy A Yap, Aung Naing, Jordi Rodon, Vivek Subbiah, Daniel D Karp, Michael A Curran, David S Hong

Faculty, Staff and Student Publications

Introduction: TLR9 agonists are immunomodulators that have been of interest for combined use with cancer immunotherapy. TLR9 agonists, such as lefitolimod (MGN1703), significantly increased Th1 response in preclinical models and have demonstrated efficacy in early clinical trials. This trial assessed the safety and preliminary efficacy of the combination of lefitolimod and ipilimumab in patients with advanced solid tumors.

Methods: This was a single-center, open-label, investigator-initiated phase I trial conducted at The University of Texas MD Anderson Cancer Center. Patients received leftolimod either subcutaneously (at escalating doses of 15-120 mg) or intratumorally (at the maximum feasible dose) in combination with ipilimumab …

Tumoral And Circulating Genomic Landscape Inform Survival Differences In Colorectal Carcinomatosis, Michael G White, Reed I Ayabe, Mohammad A Zeineddine, Fadl A Zeineddine, Abdelrahman M G Yousef, Mahmoud Yousef, Norman J Galbraith, J Bryan Iorgulescu, Christopher Scally, Keith Fournier, Timothy E Newhook, Nancy Y You, Jason Willis, Scott Kopetz, George J Chang, John Paul Shen, Abhineet Uppal

Faculty, Staff and Student Publications

Colorectal peritoneal metastases (CPM) are the third most common site of metastatic spread of colorectal cancer and are associated with worse survival than other sites of metastatic disease. In recent years tumoral circulating tumoral DNA (ctDNA) mutational status has been increasingly utilized in clinical decision making for metastatic colorectal cancer patients despite its utility in CPM being poorly understood. Here we describe standard of care performed mutational profiles and associated outcomes for unresectable CPM patients, with a contextual comparison to 160 unresected colorectal liver metastases (CLM) patients. Of 508 patients, 288 (57 %) had CPM alone and 220 (43 %) …

Unveiling The Intercompartmental Signaling Axis: Mitochondrial To Er Stress Response (Mersr) And Its Impact On Proteostasis, Jeson J Li, Nan Xin, Chunxia Yang, Bo G Kim, Larissa A Tavizon, Ruth Hong, Jina Park, Travis I Moore, Rebecca George Tharyan, Adam Antebi, Hyun-Eui Kim

Faculty, Staff and Student Publications

Maintaining protein homeostasis is essential for cellular health. Our previous research uncovered a cross-compartmental Mitochondrial to Cytosolic Stress Response, activated by the perturbation of mitochondrial proteostasis, which ultimately results in the improvement of proteostasis in the cytosol. Here, we found that this signaling axis also influences the unfolded protein response of the endoplasmic reticulum (UPRER), suggesting the presence of a Mitochondria to ER Stress Response (MERSR). During MERSR, the IRE1 branch of UPRER is inhibited, introducing a previously unknown regulatory component of MCSR. Moreover, proteostasis is enhanced through the upregulation of the PERK-eIF2α signaling pathway, increasing phosphorylation of eIF2α and …

Using A Surgical Risk Predictor To Estimate Percutaneous Cryoablation Adverse Event Risk: A Single Center Comparative Analysis, Prisha Patel, Koustav Pal, Hadi Ahmed, Bill Tang, Iwan Paolucci, Mohammad Khavandi, Peiman Habibollahi, Ketan Shah, Steven Y Huang, Bruno C Odisio, Sanjay Gupta, Kamran Ahrar, Steven Yevich, Joshua D Kuban, Alda Tam, Rahul A Sheth

Faculty, Staff and Student Publications

Objective: To evaluate the relevance of established surgical risk calculators for predicting complications in patients undergoing percutaneous lung cryoablation (PLC).

Methods: The institution's database was queried for PLC procedures from March 2015 to May 2024, excluding those patients with concomitant local therapies or five or more lesions treated in a single setting. Demographics, frailty metrics as defined by the surgical literature, and procedural variables were collected. To evaluate the suitability of surgical risk estimate calculators, the requisite demographic data were input into the American College of Surgery surgical risk calculator; estimates for length of stay (LOS), serious complications, 30-day readmission, …

Natural History Models For Lung Cancer: A Scoping Review, Renu Sara Nargund, Sayaka Ishizawa, Maryam Eghbalizarch, Paul Yeh, Seyyed Mostafa Mousavi Janbeh Saray, Sara Nofal, Yimin Geng, Pianpian Cao, Edwin J Ostrin, Rafael Meza, Martin C Tammemägi, Robert J Volk, Maria A Lopez-Olivo, Iakovos Toumazis

Faculty, Staff and Student Publications

Introduction: Natural history models (NHMs) of lung cancer (LC) simulate the disease's natural progression providing a baseline for assessing the impact of interventions. NHMs have been increasingly used to inform public health policies, highlighting their utility. The objective of this scoping review was to summarize existing LC NHMs, identify their limitations, and propose a framework for future NHM development.

Methods: We searched MEDLINE, Embase, Web of Science, and IEEE Xplore from their inception to October 5, 2023, for peer-reviewed, full-length articles with an LC NHM. Model characteristics, their applications, data sources used, and limitations were extracted and narratively synthesized.

Results: …

Dose Prediction Via Deep Learning To Enhance Treatment Planning Of Lung Radiotherapy Including Simultaneous Integrated Boost Techniques, Wenhua Cao, Mary Gronberg, Stephen Bilton, Hana Baroudi, Skylar Gay, Christopher Peeler, Zhongxing Liao, Thomas J Whitaker, Karen Hoffman, Laurence E Court

Faculty, Staff and Student Publications

Background: Recent studies have shown deep learning techniques are able to predict three-dimensional (3D) dose distributions of radiotherapy treatment plans. However, their use in dose prediction for treatments with varied prescription doses including simultaneous integrated boost (SIB), that is, using multiple prescription doses within the same plan, and benefit in improving plan quality should be validated.

Purpose: To investigate the feasibility and potential benefit of using deep learning to predict dose distribution of volumetric modulated arc therapy (VMAT) including SIB techniques and improve treatment planning for patients with lung cancer.

Methods: The dose prediction model was trained with 93 retrospective …

Prevalence And Patterns Of Opioid Use In Chronic Pancreatitis, Anna Evans Phillips, Darwin L Conwell, Shuang Li, Jami L Saloman, Phil A Hart, Evan L Fogel, Santhi Swaroop Vege, Dana K Andersen, William E Fisher, Christopher E Forsmark, Stephen Pandol, Walter G Park, Mark D Topazian, Stephen K Van Den Eeden, Jose Serrano, Liang Li, Dhiraj Yadav

Faculty, Staff and Student Publications

Introduction: Opioids are used to treat pain in chronic pancreatitis (CP), but little is known about current use patterns. The aim of this study was to characterize the utilization of opioids and associations with clinical characteristics in adult patients with CP.

Methods: This cross-sectional analysis used baseline data from participants with definite CP enrolled in a cohort study in the United States (PROspective Evaluation of CP for EpidEmiologic and Translational StuDies). Data on demographics, pain medication use, healthcare utilization, disability, and pain patterns were systematically collected in case report forms while quality of life was assessed with patient-reported outcome instruments. …

Chemotherapy-Free Treatment With Radiotherapy And Immunotherapy For Locally Advanced Non-Small Cell Lung Cancer, M Zeeshan Ozair, Balazs Halmos, Angelica D'Aiello, Jaewon Yun, Andrea R Filippi, Andreas Rimner, Steven H Lin, Charles B Simone, Nitin Ohri

Faculty, Staff and Student Publications

Background: Concurrent chemoradiotherapy (CRT) followed by immunotherapy is a standard treatment for locally advanced non-small cell lung cancer (LA-NSCLC), yet many patients are ineligible due to treatment-related toxicity or poor functional status. Chemotherapy-free approaches using radiotherapy (RT) and immunotherapy may offer a safer and equally effective alternative in select patient populations.

Methods: A comprehensive literature review was conducted using PubMed, Google Scholar, and relevant conference proceedings focusing on trials between 2000 and 2024. Studies investigating chemotherapy-free regimens combining RT and immunotherapy in LA-NSCLC were analyzed, with emphasis on clinical outcomes, biomarker use, treatment sequencing, radiation dose/fractionation, and safety.

Results: Multiple …

Neurotransmitter Power Plays: The Synaptic Communication Nexus Shaping Brain Cancer, Jayanta Mondal, Jason T Huse

Faculty, Staff and Student Publications

Gliomas and brain metastases are notorious for their dismal prognosis and low survival rates, a challenge exacerbated by our incomplete grasp of the complex dynamics that govern brain cancers. Recently, a groundbreaking paradigm shift has emerged, highlighting the crucial role of synaptic communication between neurons and brain tumor cells in reshaping neuronal signaling to favor tumor growth. This review delves into the pivotal interplay of synaptic mechanisms, focusing on excitatory glutamatergic and inhibitory GABAergic pathways. Glutamatergic synapses utilize glutamate to propagate excitatory signals, while GABAergic synapses employ gamma-aminobutyric acid (GABA) to inhibit neuronal firing. Glutamatergic signaling can be broadly classified …

Use Of Natural Language Processing To Identify Patients With Inflammatory Breast Cancer Across A Health-Care System, Ramez Kouzy, Megumi Kai, Huong T Le-Petross, Sadia Saleem, Wendy A Woodward

Faculty, Staff and Student Publications

Early identification and referral of inflammatory breast cancer remains challenging within large health-care systems, limiting access to specialized care. We developed and evaluated an artificial intelligence-driven platform integrating natural language processing (NLP) with electronic health records to systematically identify potential inflammatory breast cancer patients across 5 campuses. Our platform analyzed 8 623 494 clinical notes, implementing a sequential review process: NLP screening followed by human validation and multidisciplinary confirmation. Initial NLP screening achieved 55.4% positive predictive value, improving to 78.4% with human-in-the-loop review. Notably, among 255 confirmed patients with inflammatory breast cancer, our system demonstrated 92.2% sensitivity, identifying 57 patients …

Bilateral Germ Cell Tumor Of The Testis: Biological And Clinical Implications For A Stem Versus Genetic Origin Of Cancers, Jamaal C Jackson, Darren Sanchez, Aron Y Joon, Marcos R Estecio, Andrew C Johns, Amishi Y Shah, Matthew Campbell, John F Ward, Louis L Pisters, Charles C Guo, Miao Zhang, Niki M Zacharias, Shi-Ming Tu

Faculty, Staff and Student Publications

Germ cell tumors of the testis (GCTs) provide an ideal tumor model to investigate the cellular versus genetic origin of cancers. In this single institutional study, we evaluated 38 patients with bilateral GCT, including tumors that occurred simultaneously (synchronous) and those occurring at different times (metachronous). For nine of these patients, DNA was isolated from the right and left GCT to determine the genomic and epigenetic differences between tissues using whole-exome sequencing (WES) and reduced representation bisulfite sequencing (RRBS). We found that seminomas and non-seminomas are molecularly distinct based on DNA methylation and not due to synchronous or metachronous disease. …

Cognitive Outcomes In Prostate Cancer Treatment: Insights From The Odenza Trial And Future Considerations, Bryan J Neth, Jeffrey S Wefel, Kevin T Nead

Faculty, Staff and Student Publications

No abstract provided.

Trends In Medicare Payments Within The First Year Of Cervical Cancer Diagnosis, 2010–2019, Mohammad A Karim, Ning Zhang, Hui Zhao, Ya-Chen Tina Shih, Lakshmi S M Kodali, Sharon H Giordano, Sanjay Shete

Faculty, Staff and Student Publications

Assessing Medicare payment trends for cervical cancer care is important to mitigate the financial impact on Medicare. This multiyear cross-sectional study included 65 years and older cervical cancer patients in SEER registries diagnosed between 2010 and 2019 who had continuous Part A and B Medicare coverage at least 6 months before diagnosis and at least within the first year of diagnosis and were not enrolled in any Health Maintenance Organization (HMO) in this duration. The main outcomes were trends in total and service-specific mean monthly Medicare payments within the first year of a cervical cancer diagnosis. This study included 2147 …

Network-Based Clustering Unveils Interconnected Landscapes Of Genomic And Clinical Features Across Myeloid Malignancies, Fritz Bayer, Marco Roncador, Giusi Moffa, Kiyomi Morita, Koichi Takahashi, Niko Beerenwinkel, Jack Kuipers

Faculty, Staff and Student Publications

Myeloid malignancies exhibit considerable heterogeneity with overlapping clinical and genetic features among subtypes. We present a data-driven approach that integrates mutational features and clinical covariates at diagnosis within networks of their probabilistic relationships, enabling the discovery of patient subgroups. A key strength is its ability to include presumed causal directions in the edges linking clinical and mutational features, and account for them aptly in the clustering. In a cohort of 1323 patients, we identify subgroups that outperform established risk classifications in prognostic accuracy. Our approach generalises well to unseen cohorts with classification based on our subgroups similarly offering advantages in …

The Effects Of Prescribed Medications On Depressive Symptoms And Neurocognitive Performance In People With Hiv, Asante R Kamkwalala, Avery Matthews, Ankita Garg, Upal Roy, Qing Ma, Maile Karris, Erin Sundermann, Ronald J Ellis, Patricia K Riggs, Mattia Trunfio, Jennifer Blanchard, David J Moore, Leah H Rubin, Scott L Letendre

Faculty, Staff and Student Publications

Background: Alterations in brain function and structure, such as depression and neurocognitive impairment, continue to occur in people with human immunodeficiency virus (HIV, PWH) taking suppressive antiretroviral therapy (ART). The lifespan of PWH has improved but the healthspan remains worse than people without HIV, in part because of aging-related diseases. As a result, polypharmacy is common and increases the risk of drug-drug interactions and adverse reactions.

Methods: This cross-sectional project investigated the relationship between 7 medication-related metrics (including anticholinergic burden), depressive symptoms, and neurocognitive performance in 491 PWH at a single center in the United States. All participants were taking …

Enhanced And Interpretable Prediction Of Multiple Cancer Types Using A Stacking Ensemble Approach With Shap Analysis, Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao

Faculty, Staff and Student Publications

Background: Cancer is a leading cause of death worldwide, and its early detection is crucial for improving patient outcomes. This study aimed to develop and evaluate ensemble learning models, specifically stacking, for the accurate prediction of lung, breast, and cervical cancers using lifestyle and clinical data.

Methods: 12 base learners were trained on datasets for lung, breast, and cervical cancer. Stacking ensemble models were then developed using these base learners. The models were evaluated for accuracy, precision, recall, F1-score, AUC-ROC, MCC, and kappa. An explainable AI technique, SHAP, was used to interpret model predictions.

Results: The stacking …

Lung Cancer Risk Prediction In Patients With Persistent Pulmonary Nodules Using The Brock Model And Sybil Model, Hui Li, Morteza Salehjahromi, Myrna C B Godoy, Kang Qin, Courtney M Plummer, Zheng Zhang, Lingzhi Hong, Simon Heeke, Xiuning Le, Natalie Vokes, Bingnan Zhang, Haniel A Araujo, Mehmet Altan, Carol C Wu, Mara B Antonoff, Edwin J Ostrin, Don L Gibbons, John V Heymach, J Jack Lee, David E Gerber, Jia Wu, Jianjun Zhang

Faculty, Staff and Student Publications

Background/objectives: Persistent pulmonary nodules are at higher risk of developing into lung cancers. Assessing their future cancer risk is essential for successful interception. We evaluated the performance of two risk prediction models for persistent nodules in hospital-based cohorts: the Brock model, based on clinical and radiological characteristics, and the Sybil model, a novel deep learning model for lung cancer risk prediction.

Methods: Patients with persistent pulmonary nodules-defined as nodules detected on at least two computed tomography (CT) scans, three months apart, without evidence of shrinkage-were included in the retrospective (n = 130) and prospective (n = 301) cohorts. …

Investigative Needle Core Biopsies Support Multimodal Deep-Data Generation In Glioblastoma, Kenny K H Yu, Sreyashi Basu, Gerard Baquer, Ryuhjin Ahn, Jennifer Gantchev, Sonali Jindal, Michael S Regan, Zaki Abou-Mrad, Michael C Prabhu, Marc J Williams, Alicia D D'Souza, Seth W Malinowski, Kelsey Hopland, Yuval Elhanati, Sylwia A Stopka, Alexei Stortchevoi, Charles Couturier, Zhong He, Jingjing Sun, Yulong Chen, Alexsandra B Espejo, Kin Hoe Chow, Smitha Yerrum, Pei-Lun Kao, Brittany Parker Kerrigan, Lisa Norberg, Douglas Nielsen, Vinay K Puduvalli, Jason Huse, Rameen Beroukhim, Betty Y S Kim, Sangeeta Goswami, Adrienne Boire, Sarah Frisken, Michael J Cima, Matthias Holdhoff, Calixto-Hope G Lucas, Chetan Bettegowda, Stuart S Levine, Tejus A Bale, Cameron Brennan, David A Reardon, Frederick F Lang, E Antonio Chiocca, Keith L Ligon, Forest M White, Padmanee Sharma, Viviane Tabar, Nathalie Y R Agar

Faculty, Staff and Student Publications

Glioblastoma (GBM) is an aggressive primary brain cancer with few effective therapies. Stereotactic needle biopsies are routinely used for diagnosis; however, the feasibility and utility of investigative biopsies to monitor treatment response remains ill-defined. Here, we demonstrate the depth of data generation possible from routine stereotactic needle core biopsies and perform highly resolved multi-omics analyses, including single-cell RNA sequencing, spatial transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics on standard biopsy tissue obtained intra-operatively. We also examine biopsies taken from different locations and provide a framework for measuring spatial and genomic heterogeneity. Finally, we investigate the …

Improved Overall Survival In An Anti-Pd-L1 Treated Cohort Of Newly Diagnosed Glioblastoma Patients Is Associated With Distinct Immune, Mutation, And Gut Microbiome Features: A Single Arm Prospective Phase I/Ii Trial, Shiao-Pei Weathers, Xiqi Li, Haifeng Zhu, Ashish V Damania, Mark Knafl, Brian Mckinley, Heather Lin, Rebecca A Harrison, Nazanin K Majd, Barbara J O'Brien, Marta Penas-Prado, Monica Loghin, Carlos Kamiya-Matsuoka, W K Alfred Yung, Luisa M Solis Soto, Dipen M Maru, Ignacio Wistuba, Edwin R Parra Cuentas, Sharia Hernandez, Andrew Futreal, Jennifer A Wargo, Katja Schulze, Walter C Darbonne, Nadim J Ajami, Scott E Woodman, John F De Groot

Faculty, Staff and Student Publications

This phase I/II trial aims to evaluate the efficacy of concurrent atezolizumab with radiation therapy and temozolomide (TMZ) followed by adjuvant atezolizumab and TMZ in newly diagnosed glioblastoma (GBM) patients and to identify pre-treatment correlates with outcome (N = 60). Trial number: NCT03174197. The primary outcome was overall survival (OS) whereas secondary outcomes were retrospective global-omics analyses to identify pre-treatment immune and genetic tumor features that correlated with survival. Concurrent use of atezolizumab with radiation and TMZ demonstrated OS in line with published trials for newly diagnosed GBM. Tumor genomic (WES and/or targeted NGS panel), transcriptomic (RNAseq) and tissue microenvironment …

Building A Pre-Surgical Multiparametric-Mri-Based Morphologic, Qualitative, Semiquantitative, First And High-Order Radiomic Predictive Treatment Response Model For Undifferentiated Pleomorphic Sarcoma To Replace Recist, Raul F Valenzuela, Elvis Duran-Sierra, Mathew Antony, Behrang Amini, Sam Lo, Keila E Torres, Robert S Benjamin, Jingfei Ma, Ken-Pin Hwang, R Jason Stafford, Dejka Araujo, Andrew J Bishop, Ravin Ratan, Wei-Lien Wang, Jossue Espinoza, Pia V Valenzuela, Chengyue Wu, John E Madewell, William A Murphy, Colleen M Costelloe

Faculty, Staff and Student Publications

Background: Undifferentiated pleomorphic sarcoma (UPS) is the largest subgroup of soft-tissue sarcomas. It demonstrates post-therapeutic hemosiderin deposition, granulation tissue formation, fibrosis, and calcification. Our research aims to establish the multiparametric MRI (mp-MRI) value for predicting UPS treatment response.

Methods: An IRB-approved retrospective study included 33 extremity UPS patients with pre-operative mp-MRI, including diffusion-weighted imaging (DWI), contrast-enhanced susceptibility-weighted imaging (CE-SWI), and perfusion-weighted imaging with dynamic contrast-enhancement (PWI/DCE), and surgical resection between February 2021 and May 2023. Lesions were visually classified on CE-SWI into one of 6 morphology patterns. On PWI/DCE, lesions were classified into one of 6 patterns, and time-intensity curves …

Acute Brcaness Induction And Ar Pathway Blockage Through Cdk12/7/9 Degradation Enhances Parp Inhibitor Sensitivity In Prostate Cancer, Fu Gui, Baishan Jiang, Jie Jiang, Zhixiang He, Takuya Tsujino, Tomoaki Takai, Seiji Arai, Celine Pana, Jens Köllermann, Gary Andrew Bradshaw, Robyn Eisert, Marian Kalocsay, Anne Fassl, Steven P Balk, Adam S Kibel, Li Jia

Faculty, Staff and Student Publications

Current treatments for advanced prostate cancer (PCa) primarily target the androgen receptor (AR) pathway. However, the emergence of castration-resistant prostate cancer (CRPC) and resistance to AR pathway inhibitors (APPIs) remains ongoing challenges. Here, we present BSJ-5-63, a proteolysis-targeting chimera (PROTAC) targeting cyclin-dependent kinases (CDKs) CDK12, CDK7, and CDK9, offering a multipronged approach to CRPC therapy. BSJ-5-63 degrades CDK12, diminishing BRCA1 and BRCA2 expression and inducing a sustained "BRCAness" state. This sensitizes cancer cells to PARP inhibitors (PARPis) regardless of their homologous recombination repair (HRR) status. Furthermore, CDK7 and CDK9 degradation attenuates AR signaling, enhancing its therapeutic efficacy. Preclinical studies, including …

A Pioneering Artificial Intelligence Tool To Predict Treatment Outcomes In Ovarian Cancer Via Diagnostic Laparoscopy, Xiaotian Ma, Yu-Chun Hsu, Amma Asare, Kai Zhang, Deanna Glassman, Katelyn F Handley, Katherine Foster, Khwahish Sharma, Shannon Westin, Amir Jazaeri, Nicole D Fleming, Pratip K Bhattacharya, Xiaoqian Jiang, Anil K Sood, Shayan Shams

Faculty, Staff and Student Publications

Ovarian cancer is associated with high rates of patient mortality and morbidity. Laparoscopic assessment of tumor localization can be used for treatment planning in newly diagnosed high-grade serous ovarian carcinoma (HGSOC). While spread to multiple intra-abdominal areas is correlated with worse outcomes, whether other morphological tumor differences are also associated with patient outcomes is unknown. Given the large volume of visual information in laparoscopic videos, we investigated whether deep-learning models can capture implicit features and predict treatment outcomes. We developed a novel deep-learning framework using pre-treatment laparoscopic images to assess clinical outcomes following upfront standard treatment, defined as short progression-free …

The Dynamic Immune Behavior Of Primary And Metastatic Ovarian Carcinoma, Elaine Stur, Fuduan Peng, Pang-Ning Teng, Emine Bayraktar, Min Hu, Sara Corvigno, David J Brown, Sanghoon Lee, Kathleen N Moore, Nicholas W Bateman, Kathleen M Darcy, George L Maxwell, Thomas P Conrads, Nidhi Sahni, Ignacio Vázquez-García, Sohrab P Shah, Joseph Celestino, Nicole D Fleming, Nicholas E Navin, Linghua Wang, Anil K Sood

Faculty, Staff and Student Publications

Patients with high-grade serous ovarian carcinoma (HGSC) are usually diagnosed with advanced-stage disease, and the tumors often have immunosuppressive characteristics. Together, these factors are important for disease progression, drug resistance, and mortality. In this study, we used a combination of single-cell sequencing and spatial transcriptomics to identify the molecular mechanisms that lead to immunosuppression in HGSC. Primary tumors consistently showed a more active immune microenvironment than did omental tumors. In addition, we found that untreated primary tumors were mostly populated by dysfunctional CD4 and CD8 T cells in later stages of differentiation; this, in turn, was correlated with expression changes …

Idh Status Dictates Ohsv Mediated Metabolic Reprogramming Affecting Anti-Tumor Immunity, Upasana Sahu, Matthew P Mullarkey, Sara A Murphy, Joshua C Anderson, Vasanta Putluri, Abu Hena Mostafa Kamal, Jun Hyoung Park, Tae Jin Lee, Alexander L Ling, Benny A Kaipparettu, Ashok Sharma, Nagireddy Putluri, Pamela L Wenzel, Christopher D Willey, E Antonio Chiocca, James M Markert, Balveen Kaur

Faculty, Staff and Student Publications

Identification of isocitrate dehydrogenase (IDH) mutations has uncovered the crucial role of metabolism in gliomagenesis. Oncolytic herpes virus (oHSV) initiates direct tumor debulking by tumor lysis and activates anti-tumor immunity, however, little is known about the role of glioma metabolism in determining oHSV efficacy. Here we identify that oHSV rewires central carbon metabolism increasing glucose utilization towards oxidative phosphorylation and shuttling glutamine towards reductive carboxylation in IDH wildtype glioma. The switch in metabolism results in increased lipid synthesis and cellular ROS. PKC induces ACSL4 in oHSV treated cells leading to lipid peroxidation and ferroptosis. Ferroptosis is critical to launch an …

High-Grade Astrocytoma With Piloid Features: A Single-Institution Case Series And Literature Review, Eric A Goethe, Subhiksha Srinivasan, Swaminathan Kumar, Sujit S Prabhu, Maria A Gubbiotti, Sherise D Ferguson

Faculty, Staff and Student Publications

High-grade astrocytoma with piloid features (HGAP) is a recently described primary brain tumor and the first requiring a specific methylation pattern for diagnosis, as its histologic features are often compatible with other tumors such as glioblastoma (GBM). Characterized by molecular alterations in CDKN2A/B, NF1, BRAF, FGFR1, and ATRX, they may be located anywhere in the CNS but show a predilection for the posterior fossa. Reports are limited to retrospective case series, and the standard of care is not yet established. We performed a retrospective review of electronic medical records of all patients with HGAP at our institution. Records were queried …

Dual Targeting Of Ezh2 And Ezh1 Drives Exit Of Leukemia Stem Cells From Quiescence And Potentiates Chemotherapy In Acute Myeloid Leukemia, Hiroki Akiyama, Yuki Nishida, Kyung Hee Chang, Andrea D Bedoy, Muharrem Muftuoglu, Wencai Ma, Mahesh Basyal, Zoe Hirschi, Daisuke Honma, Shinji Tsutsumi, Jing Wang, Weiguo Zhang, Xuelin Huang, Raajit K Rampal, Olalekan O Oluwole, Dale Lee Bixby, Naval G Daver, Michael Andreeff

Faculty, Staff and Student Publications

No abstract provided.

Analysis Of Differentially Expressed Genes (Deg) And Upstream Regulator Proteins Indicates That Inhibition Of Transforming Growth Factor Beta 1 (Tgfb1) Is A Potential Target For Acne Inversa, Weri Veranita, Siva Fauziah, Siti Nurbaya

Indonesian Journal of Medical Chemistry and Bioinformatics

Acne inversa (AI) is a chronic inflammatory skin disease characterized by painful nodules, abscesses, and scarring, primarily in intertriginous areas. This study aims to identify potential therapeutic targets for managing acne inversa based on the analysis of differentially expressed genes (DEG). The expression targets of these genes were then validated for their potential as biomarkers, and upstream regulator proteins (URPs) were identified from the resulting DEG. DEG analysis on the GEO dataset GSE122592 (acne inversa vs. healthy donor skin) revealed five DEG that can serve as biomarkers for acne inversa, with a sensitivity and specificity of (100%). These DEG—IL10, GZMB, …

Retrospective Analysis Of Cement Extravasation Rates In Vertebroplasty, Kyphoplasty, And Bone Tumor Radiofrequency Ablation, Soun Sheen, Prit Hasan, Xiaowen Sun, Jian Wang, Claudio Tatsui, Kent Nouri, Saba Javed

Faculty, Staff and Student Publications

Background: Percutaneous vertebral augmentation techniques, including vertebroplasty, kyphoplasty, and bone tumor radiofrequency ablation (BT-RFA), are commonly used to treat painful vertebral compression fractures (VCFs). While generally safe and effective, they carry risks, including cement extravasation, which can lead to pulmonary embolism or spinal cord compression. This study aims to compare the rate of cement extravasation across different vertebral augmentation techniques and identify potential risk factors.

Methods: A retrospective cohort study was conducted at a comprehensive cancer center on 1002 procedure encounters in 888 patients who underwent vertebral augmentation for painful VCFs. Data were collected on patient demographics, fracture pathology, procedure …

Development And Validation Of A Dynamic Real-Time Risk Prediction Model For Intensive Care Units Patients Based On Longitudinal Irregular Data: Multicenter Retrospective Study, Zhuo Zheng, Jiawei Luo, Yingchao Zhu, Lei Du, Lan Lan, Xiaobo Zhou, Xiaoyan Yang, Shixin Huang

Faculty, Staff and Student Publications

Background: Timely and accurate prediction of short-term mortality is critical in intensive care units (ICUs), where patients' conditions change rapidly. Traditional scoring systems, such as the Simplified Acute Physiology Score and Acute Physiology and Chronic Health Evaluation, rely on static variables collected within the first 24 hours of admission and do not account for continuously evolving clinical states. These systems lack real-time adaptability, interpretability, and generalizability. With the increasing availability of high-frequency electronic medical record (EMR) data, machine learning (ML) approaches have emerged as powerful tools to model complex temporal patterns and support dynamic clinical decision-making. However, existing models are …

Ensemble Learning With Explainable Ai For Improved Heart Disease Prediction Based On Multiple Datasets, Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao

Faculty, Staff and Student Publications

Heart disease is one of the leading causes of death worldwide. Predicting and detecting heart disease early is crucial, as it allows medical professionals to take appropriate and necessary actions at earlier stages. Healthcare professionals can diagnose cardiac conditions more accurately by applying machine learning technology. This study aimed to enhance heart disease prediction using stacking and voting ensemble methods. Fifteen base models were trained on two different heart disease datasets. After evaluating various combinations, six base models were pipelined to develop ensemble models employing a meta-model (stacking) and a majority vote (voting). The performance of the stacking and voting …