Medical Specialties Commons^™

A Comparative Study Of Clinically Used Fast Monte Carlo Dose Engines For Proton Therapy, Sherif M Gadoue, Narayan Sahoo

Faculty, Staff and Student Publications

Background: Several fast Monte Carlo (MC) codes have been implemented and used to simulate proton transport and calculate patient doses in proton therapy. The resulting dose is typically compared to full MC codes, rather than other fast MC codes.

Purpose: The primary goal of this study was to compare the gamma pass rates (GPRs) of dose calculation from different fast MC codes to evaluate the accuracy of the computation and modeling among these codes.

Methods: Two GPU codes and one CPU MC code were commissioned to model our clinical proton beamline at University of Texas MD Anderson Cancer Center. The …

First Experience With Third-Party Validations: A Robust Calibration And Qa Procedure For Proton Flash Delivery, Chih-Chiang Chang, Balaji Selvaraj, Xingyi Zhao, Jacob Rembish, Paige A Taylor, Alexander Bookbinder, Chingyun Cheng, J Isabelle Choi, Charles B Simone, Haibo Lin, Minglei Kang

Faculty, Staff and Student Publications

Background: Proton FLASH radiotherapy, delivering ultra-high dose rates, shows promise in reducing normal tissue toxicity while maintaining tumor control. However, accurate dosimetry and quality assurance (QA) for FLASH remain challenging due to the extreme dose rates involved. Developing reliable calibration and QA procedures is crucial for advancing FLASH towards clinical implementation.

Purpose: To present an effective routine calibration and QA procedure for proton FLASH delivery to ensure high-quality dosimetry performance for preclinical and clinical delivery.

Methods: A high temporospatial resolution strip ionization chamber array (SICA) detector was mounted to the treatment nozzle, which was calibrated using an Advanced Markus ion …

Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, And Validation Study, Liwei Wang, Qiuhao Lu, Rui Li, Taylor B Harrison, Heling Jia, Ming Huang, Heidi Dowst, Rui Zhang, Hoda Badr, Jungwei W Fan, Hongfang Liu

Faculty, Staff and Students Publications

Background: Complementary therapies are being increasingly used by cancer survivors. As a channel for customers to share their feelings, outcomes, and perceived knowledge about the products purchased from e-commerce platforms, Amazon consumer reviews are a valuable real-world data source for understanding cancer survivorship care needs.

Objective: In this study, we aimed to highlight the potential of using Amazon consumer reviews as a novel source for identifying cancer survivorship care needs, particularly related to symptom self-management. Specifically, we present a publicly available, manually annotated corpus derived from Amazon reviews of health-related products and develop baseline natural language processing models using deep …

Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, And Validation Study, Liwei Wang, Qiuhao Lu, Rui Li, Taylor B. Harrison, Heling Jia, Ming Huang, Heidi Dowst, Rui Zhang, Hoda Badr, Jungwei W. Fan, Hongfang Liu

Department of Medical Oncology Faculty Papers

BACKGROUND: Complementary therapies are being increasingly used by cancer survivors. As a channel for customers to share their feelings, outcomes, and perceived knowledge about the products purchased from e-commerce platforms, Amazon consumer reviews are a valuable real-world data source for understanding cancer survivorship care needs.

OBJECTIVE: In this study, we aimed to highlight the potential of using Amazon consumer reviews as a novel source for identifying cancer survivorship care needs, particularly related to symptom self-management. Specifically, we present a publicly available, manually annotated corpus derived from Amazon reviews of health-related products and develop baseline natural language processing models using deep …

Next-Gen Tools In Cancer Neuroscience, Vera Thiel, Debpali Sur, Caroline C Picoli, Tamara Mcerlain, Katalina Couto, David J Simon, Yuan Pan, Karen Olivia Dixon, Rajan P Kulkarni, Sebastien Talbot, Alexander Birbrair

Faculty, Staff and Student Publications

The emerging field of cancer neuroscience is rapidly evolving, driven by novel technologies and tools. These include advances in single-cell and spatial transcriptomics; genetic mouse models paired with automated high-throughput; and innovative optical electrophysiological approaches, optogenetics, chemogenetics, engineered viruses, and new methods for visualizing neuronal activity. Collectively, these technologies are revolutionizing how we investigate, manipulate, and characterize distinct components that contribute to the nervous system-cancer interface. In the present review, we discuss the key technologies that are closing the gap between oncology and neuroscience, highlighting the innovations that are propelling the cancer neuroscience field forward.

Connecting Innovation And Trust Through Translational Sciences – A Need For A Community Focus And Effective Education Strategiess, Filipa Godoy-Vitorino, Michelle Borrero, Josué Pérez-Santiago, Rubén García-García, Candelaria Gomez-Manzano

Faculty, Staff and Student Publications

Report of a conference held in Puerto Rico, this article highlights how interdisciplinary translational science-anchored in education, public trust, and equity-can accelerate innovation in cancer therapy while empowering underserved communities through inclusive training, collaboration, and research participation.

Loss Of Ptdss1 In Tumor Cells Improves Immunogenicity And Response To Anti-Pd-1 Therapy, Jielin Liu, Shelley Herbrich, Sreyashi Basu, Yulong Chen, Ashwat Nagarajan, Swetha Anandhan, Sangeeta Goswami, Liangwen Xiong, Baoxiang Guan, Padmanee Sharma

Faculty, Staff and Student Publications

PTDSS1 (phosphatidylserine synthase 1) encodes an enzyme that facilitates production of phosphatidylserine (PS), which mediates a global immunosuppressive signal. Here, based on in vivo CRISPR screen, we identified PTDSS1 as a target to improve anti-PD-1 therapy. Depletion of Ptdss1 in tumor cells increased expression of interferon-γ (IFN-γ)-regulated genes, including B2m, Cxcl9, Cxcl10, and Stat1, even in the absence of IFN-γ stimulation in vitro. Loss of Ptdss1 in tumor cells also led to increased expression of MHC-I, enhanced cytotoxicity of CD8+ T cells, and increased frequency of an iNOS+ myeloid subset. A gene signature derived from the …

Neurotransmitter Signaling In Molecular And Behavioral Immune Responses To Pathogens In C Elegans, Benson Otarigho, Alejandro Aballay

Faculty, Staff and Student Publications

Neurotransmitter signaling pathways play major roles in both molecular and behavioral defenses against pathogen invasion, shaping the ability of Caenorhabditis elegans to sense and respond to environmental challenges. Given the conservation of neurotransmitter signaling pathways, their understanding may not only provide insights into the neurobiology of C. elegans but also has broader implications for our understanding of neural-immune interactions and host defense mechanisms in higher organisms. In this review, we discussed the literature on various neurotransmitter signaling pathways, including serotonergic, dopaminergic/octopaminergic, GABAergic, and glutamatergic pathways, and how these pathways modulate molecular and behavioral immune defense against pathogens.

Innate And Adaptive Immune Features Associated With Immune-Related Adverse Events, Shaheen Khan, Venkat S Malladi, Mitchell S Von Itzstein, Hong Mu-Mosley, Farjana J Fattah, Yang Liu, Mary E Gwin, Jason Y Park, Suzanne M Cole, Sheena Bhalla, Jay Lohrey, David Hsiehchen, Angela Moses, Tao Wang, Yaming Xue, Angela B Mobley, J David Farrar, Marjaan Imam, Michelle Wu, Quan-Zhen Li, Edward K Wakeland, Yang Xie, Jeffrey A Sorelle, David E Gerber

Faculty, Staff and Student Publications

Background: While highly efficacious for numerous cancers, immune checkpoint inhibitors (ICIs) can cause unpredictable and potentially severe immune-related adverse events (irAEs), underscoring the need to understand irAE biology.

Methods: We used a multidimensional approach incorporating single-cell RNA sequencing, mass cytometry, multiplex cytokine assay, and antinuclear antibody (ANA) profiling to characterize the peripheral immune landscape of patients receiving ICI therapy according to irAE development.

Results: Analysis of 162 patients revealed that individuals who developed clinically significant irAEs exhibited a baseline proinflammatory, autoimmune-like state characterized by a significantly higher abundance of CD57+ T and natural killer (NK) T cells, plasmablasts, proliferating and …

Gene Context Drift Identifies Drug Targets To Mitigate Cancer Treatment Resistance, Amir Jassim, Birgit V Nimmervoll, Sabrina Terranova, Erica Nathan, Linda Hu, Jessica T Taylor, Katherine E Masih, Lisa Ruff, Matilde Duarte, Elizabeth Cooper, Gunjan Katyal, Melika Akhbari, Reuben J Gilbertson, Jennifer C Coleman, Joseph S Toker, Colton Terhune, Gabriel Balmus, Stephen P Jackson, Hailong Liu, Tao Jiang, Michael D Taylor, Kui Hua, Jean E Abraham, Mariella G Filbin, Anthony Hill, Anarita Patrizi, Neil Dani, Aviv Regev, Maria K Lehtinen, Richard J Gilbertson

Faculty, Staff and Students Publications

Cancer treatment often fails because combinations of different therapies evoke complex resistance mechanisms that are hard to predict. We introduce REsistance through COntext DRift (RECODR): a computational pipeline that combines co-expression graph networks of single-cell RNA sequencing profiles with a graph-embedding approach to measure changes in gene co-expression context during cancer treatment. RECODR is based on the idea that gene co-expression context, rather than expression level alone, reveals important information about treatment resistance. Analysis of tumors treated in preclinical and clinical trials using RECODR unmasked resistance mechanisms -invisible to existing computational approaches- enabling the design of highly effective combination treatments …

Detection Of Cancers Three Years Prior To Diagnosis Using Plasma Cell-Free Dna, Yuxuan Wang, Corinne E Joshu, Samuel D Curtis, Christopher Douville, Vernon A Burk, Meng Ru, Maria Popoli, Janine Ptak, Lisa Dobbyn, Natalie Silliman, Josef Coresh, Eric Boerwinkle, Anna Prizment, Chetan Bettegowda, Kenneth W Kinzler, Nickolas Papadopoulos, Elizabeth A Platz, Bert Vogelstein

Faculty, Staff and Student Publications

To explore how early can cancers be detected prior to clinical signs or symptoms, we assessed prospectively collected serial plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) test. All eight participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six …

Efficacy Of Atr Kinase Inhibitor Elimusertib Monotherapy Or Combination In Tumors With Dna Damage Response Pathway And Other Genomic Alterations, Kaushik Varadarajan, Christian X Cruz Pico, Kurt W Evans, Maria Gabriela Raso, Yasmeen Qamar Rizvi, Xiaofeng Zheng, Dhruv Chachad, Timothy P Diperi, Bailiang Wang, Stephen M Scott, Ming Zhao, Argun Akcakanat, Antje M Wengner, Timothy A Yap, Funda Meric-Bernstam

Faculty, Staff and Student Publications

The ataxia telangiectasia and RAD3-related (ATR) kinase functions with ataxia telangiectasia-mutated (ATM) kinase as a modulator of DNA damage response (DDR). We assessed the antitumor effects of the ATR inhibitor elimusertib (BAY-1895344) in patient-derived xenograft (PDX) models with DDR alterations. Antitumor activity was assessed by change in tumor volume (TV) from baseline. Responses were categorized as follows: partial response (PR), ≥30% decrease in TV; ≥20% increase in TV, progressive disease; and non-PR/progressive disease, stable disease (SD). Event-free survival was defined as time for tumor doubling (EFS-2). Of 21 PDX models tested, 11 had significant prolongation of EFS-2 with elimusertib monotherapy. …

Contemporary Characteristics And Outcomes Of Pediatric Oncology Patients Participating In Early Phase Clinical Trials., Avina Rami, Kira Bona, Suzanne Shusterman, Karen Wright, Andrew E. Place, Puja J. Umaretiya, Ketki Bhushan, Steven G. Dubois, Kevin Campbell

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: Phase 1 or phase 1/2 trials are a first step in pediatric cancer drug development. Currently, there is a paucity of information regarding contemporary outcomes for pediatric patients enrolled in these trials. We describe characteristics and outcomes of patients enrolled in pediatric phase 1 clinical trials over a 9-year period at a single institution.

METHODS: We queried our clinical trials management system to generate a list of patients enrolled and treated on pediatric phase 1 or phase 1/2 trials from 2011 to 2019. We collected baseline demographics, clinical data, efficacy, and safety endpoints post-enrollment including: time to death, objective …

Mucinous Cystic Neoplasms Of The Pancreas And Liver Share A Similar Dna Methylation Profile With Mucinous Ovarian Tumors, Zoe Leoni, Teodor G Calina, Tobias Janik, Elena Grafenhorst, Eliane T Taube, Christopher Cm Neumann, Baoqing Chen, Elena I Braicu, Jalid Sehouli, Thomas Malinka, Wenzel Schöning, Johann Pratschke, George A Calin, David S Klimstra, Jamal K Benhamida, Irene Esposito, Markus Möbs, David Horst, Simon Schallenberg, David Capper, Mihnea P Dragomir

Faculty, Staff and Student Publications

The origin of mucinous cystic neoplasms (MCNs) remains a major challenge in hepato-pancreato-biliary pathology. These cystic tumors are defined by their mucinous epithelium and ovarian-like stroma, with an estimated 10% risk of progression to invasive carcinoma. The origin of the ovarian-like stroma remains a subject of debate. In this study, we conducted immunohistochemical profiling, targeted DNA sequencing, and genome-wide DNA methylation analysis on a cohort of 15 pancreatic MCNs (MCN-P) and six hepatic MCNs (MCN-L). Using immunohistochemistry and targeted DNA sequencing, we unequivocally established the diagnosis of MCN. Unsupervised DNA methylation profile analysis of reference classes of pancreatic neoplasms (11 …

Systematic Literature Review Of Intravenous Versus Subcutaneous Administration Of Oncology Therapies: A Clinical, Economic And Patient Perspective, Saby George, Maria T Bourlon, Michael J Overman, Matt Dixon, Karishma Shelley, Kristen J Markus, Rachel M Kewley, Sophie I Pope, Laurence Albigès

Faculty, Staff and Student Publications

Subcutaneous (SC) formulations of oncology therapies offer a potentially less time-consuming and more convenient alternative to intravenous (IV) administration. However, exploring the potential benefits of SC over IV administration from a broader perspective is necessary to understand the larger-scale impact. In this systematic literature review (SLR), we evaluated the efficacy, pharmacokinetics/pharmacodynamics (PK/PD), safety, and patient and healthcare provider (HCP) preference for SC/IV oncology therapies, along with differences in patient outcomes, costs, and time requirements. The SLR was conducted in January 2019 and updated in May 2023, and included 169 publications. Studies providing comparative results between IV and SC formulations regarding …

Risk Of Second Primary Lung Cancer Among Cancer Survivors Stratified By The Site Of First Primary Cancer And The Lung Cancer Screening Eligibility Status, Sara Nofal, Edwin J Ostrin, Jianjun Zhang, Jia Wu, Paul Scheet, Mara B Antonoff, John V Heymach, Iakovos Toumazis

Faculty, Staff and Student Publications

Personal history of cancer is an independent risk factor for developing lung cancer. However, it is not considered in the current US lung cancer screening (LCS) guidelines. In this study, we assessed the risk of developing lung cancer among cancer survivors across 24 different sites of first primary cancer stratified by their LCS eligibility status. Using data from the Patient History Database at the University of Texas MD Anderson Cancer Center, we calculated and compared the cumulative incidence of second primary lung cancer, the overall and the LCS eligibility status-specific, stratified by the site of first primary cancer among cancer …

Leveraging Existing Cohort Studies Of Mexican Women To Better Understand Hispanic Health And Cancer Risk, Dalia Stern, Liliana Gomez-Flores-Ramos, Britton Trabert, V Wendy Setiawan, Loïc Le Marchand, Henry Gomez, Paul A Scheet, Humberto Parada, Amber Pirzada, Martin Lajous, Leslie V Farland

Faculty, Staff and Student Publications

Background: Hispanics have been historically underrepresented in epidemiologic cancer research. Existing cohort studies focused on recruiting Hispanic participants have been relatively small, making studying cancer outcomes challenging. Therefore, we aimed to compare the distribution of cancer risk factors among Hispanic women of Mexican heritage (HWMH) participating in existing cohorts to explore the possibility of future data pooling efforts.

Methods: We used baseline data of HWMH from three US-based studies, the Mexican American Cohort (MAC; n = 19,797; 2001-2017), the Multiethnic Cohort (MEC; n = 18,007; 1993-1996), and the Hispanic Community Health Study/Study of Latinos (HCHS/SOL; n = 4,022; 2008-2011), and …

Expression Graph Network Framework For Biomarker Discovery, Yang Liu, Jason Huse, Kasthuri Kannan

Faculty, Staff and Student Publications

Biomarker discovery for complex diseases, such as cancer, hinges on uncovering molecular signatures that capture intricate, interconnected relationships within biological data-a challenge that traditional statistical and machine learning methods often fail to meet due to the complexity of high-dimensional gene expression profiles. To overcome this, we introduce the expression graph network framework (EGNF). This cutting-edge graph-based approach integrates graph neural networks with network-based feature engineering to enhance the predictive identification of biomarkers. EGNF constructs biologically informed networks by combining gene expression data and clinical attributes within a graph database, utilizing hierarchical clustering to generate dynamic, patient-specific representations of molecular interactions. …

The Role Of Recruited Adipose Stromal Cells And Their Fibroblastic Differentiation In Cancer, Lingyi Cai, Mikhail G Kolonin, Dimitris Anastassiou

Faculty, Staff and Student Publications

Adipose stromal cells (ASCs) are perivascular mesenchymal progenitors of adipose tissue. In cancer patients, ASCs can mobilize and migrate to the tumor, where they subsequently play an important role in cancer progression. This biological process involves the conversion of recruited ASCs into cancer-associated fibroblasts (CAFs). ASC-derived CAFs influence the tumor microenvironment through extracellular matrix remodeling, vascularization, and immunomodulation. These and other processes mediated by secreted paracrine factors also affect gene expression in carcinoma cells to promote the epithelial-mesenchymal transition (EMT), metabolic adaptation, survival, and invasiveness of cancer cells. ASC-derived CAFs can enhance tumor aggressiveness, accounting in part for the link …

Reproducibility Of Statistically Significant Phase Iii Oncology Trials: An In Silico Meta-Epidemiological Analysis, Alexander D Sherry, Pavlos Msaouel, Avital M Miller, Timothy A Lin, Joseph Abi Jaoude, Ramez Kouzy, Adina H Passy, Tomer Meirson, Nikolaos Ignatiadis, Zachary R Mccaw, Erik Van Zwet, Ethan B Ludmir

Faculty, Staff and Student Publications

Purpose: The conventional assumption that P values ≤ 0.05 imply reproducible effects has come under recent criticism. This concern is particularly relevant in oncology, as phase III oncology trials, which directly inform practice, are usually not repeated. Using advanced modeling techniques, we investigated the relationship between P values and reproducibility in oncology.

Methods: We obtained the signal-to-noise ratio distribution in phase III oncology using outcomes from 632 two-arm superiority trials enrolling 496,219 patients. With this distribution, we estimated successful replication probability as the probability that a replicate trial, having the same design, effect size, and standard error, would have a …

Human Interpretable Grammar Encodes Multicellular Systems Biology Models To Democratize Virtual Cell Laboratories, Jeanette A I Johnson, Daniel R Bergman, Heber L Rocha, David L Zhou, Eric Cramer, Ian C Mclean, Yoseph W Dance, Max Booth, Zachary Nicholas, Tamara Lopez-Vidal, Atul Deshpande, Randy Heiland, Elmar Bucher, Fatemeh Shojaeian, Matthew Dunworth, André Forjaz, Michael Getz, Inês Godet, Furkan Kurtoglu, Melissa Lyman, John Metzcar, Jacob T Mitchell, Andrew Raddatz, Jacobo Solorzano, Aneequa Sundus, Yafei Wang, David G Denardo, Andrew J Ewald, Daniele M Gilkes, Luciane T Kagohara, Ashley L Kiemen, Elizabeth D Thompson, Denis Wirtz, Laura D Wood, Pei-Hsun Wu, Neeha Zaidi, Lei Zheng, Jacquelyn W Zimmerman, Jude M Phillip, Elizabeth M Jaffee, Joe W Gray, Lisa M Coussens, Young Hwan Chang, Laura M Heiser, Genevieve L Stein-O'Brien, Elana J Fertig, Paul Macklin

Faculty, Staff and Student Publications

Cells interact as dynamically evolving ecosystems. While recent single-cell and spatial multi-omics technologies quantify individual cell characteristics, predicting their evolution requires mathematical modeling. We propose a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This enables systematic integration of biological knowledge and multi-omics data to generate in silico models, enabling virtual "thought experiments" that test and expand our understanding of multicellular systems and generate new testable hypotheses. This paper motivates and describes the grammar, offers a reference implementation, and demonstrates its use in developing both de novo mechanistic models and those informed …

Mathematical Modeling And Association Analysis Decipher The Impact Of The Gut Microbiome On Cancer Immunotherapy, Andreas G Hadjigeorgiou, Constantinos Harkos, Aditya K Mishra, Golnaz Morad, Sarah B Johnson, Nadim J Ajami, Jennifer A Wargo, Lance L Munn, Triantafyllos Stylianopoulos, Rakesh K Jain

Faculty, Staff and Student Publications

The gut microbiome has emerged as a key regulator of response to cancer immunotherapy. However, a better understanding of the underlying mechanisms by which the microbiome influences immunotherapy is needed to identify strategies to optimize outcomes. To this end, we developed a mathematical model to obtain insights into the effect of the microbiome on the immune system and immunotherapy response. This model was based on (i) gut microbiome data derived from preclinical studies, (ii) mathematical modeling of the antitumor immune response, (iii) association analysis of microbiome profiles with model-predicted immune profiles, and (iv) statistical models that correlate model parameters with …

Hippocampal Avoidance During Prophylactic Cranial Irradiation For Patients With Small Cell Lung Cancer: Randomized Phase Ii/Iii Trial Nrg-Cc003, Vinai Gondi, Stephanie L Pugh, Minesh P Mehta, Jeffrey S Wefel, Wolfgang A Tomé, Alexander Y Sun, John Grecula, Kristin J Redmond, Shannon Fogh, Laurie Gaspar, Andre Konski, Joseph Bovi, Clifford G Robinson, Benjamin Corn, Gregory M Videtic, Benjamin H Lok, Harold A Yoon, John H Heinzerling, Albert S Denittis, Ronald C Mcgarry, Kiran Devisetty, Vijayananda Kundapur, Abraham J Wu, Edward C Mccarron, Isabelle Thibault, Edmund L Simon, Andrew M Baschnagel, Samir Narayan, Jondavid Pollock, Rebecca Paulus, Lisa A Kachnic

Faculty, Staff and Student Publications

Purpose: Hippocampal avoidance (HA) during therapeutic whole-brain radiotherapy reduces the risk of neurocognitive function (NCF) toxicity in patients with brain metastasis. This trial hypothesized that HA during prophylactic cranial irradiation (PCI) in patients with small cell lung cancer (SCLC) leads to noninferior intracranial relapse (ICR) and reduction in NCF toxicity.

Methods: This randomized phase II/III trial enrolled patients with SCLC, no brain metastases, and response to chemotherapy. The primary end points were 12-month ICR (noninferiority design, randomized phase II) and 6-month Hopkins Verbal Learning Test-Revised (HVLT-R) Delayed Recall (DR) failure (phase III). Secondary end points were failure in any NCF …

Histologic And Immune Characterization Of Cutaneous Immune-Related Adverse Events Induced By Immune Checkpoint Inhibitors, Omar Pacha, Anisha B Patel, Jonathan L Curry, Cara L Haymaker, Nejla Ozirmak Lermi, Dzifa Yawa Duose, Ken Chen, Joud Hajjar, Aung Naing

Faculty, Staff and Student Publications

Background: Although immune checkpoint inhibitors (ICIs) are efficacious, they often cause immune-related adverse events (irAEs), most commonly cutaneous irAEs (CirAEs). The mechanisms underlying CirAEs remain unclear.

Methods: Attempting to better understand their mechanisms and histology we conducted a prospective study of 15 patients with advanced cancers treated with ICIs who developed grade 2 or higher CirAEs. Clinical and histologic characterization of biopsy specimens of CirAEs was performed. Histologic analysis of patient biopsy specimens were subdivided by epidermal reaction patterns that included spongiotic, lichenoid, and interface dermatitis patterns. A targeted RNA expression assay was used to identify immune markers in CirAE …

Development And Validation Of Venous Thromboembolism-Bidirectional Encoder Representations From Transformers (Vte-Bert) Natural Language Processing Model, Omid Jafari, Shengling Ma, Barbara D Lam, Jun Y Jiang, Emily Zhou, Mrinal Ranjan, Justine Ryu, Raka Bandyo, Arash Maghsoudi, Bo Peng, Christopher I Amos, Abiodun Oluyomi, Nathanael R Fillmore, Jennifer La, Ang Li

Faculty, Staff and Students Publications

Background: Accurate and rapid phenotyping of venous thromboembolism (VTE) in longitudinal studies is important. A natural language processing (NLP) tool externally validated in representative patients is lacking.

Objectives: To train and validate an efficient NLP model to detect incident VTE event.

Methods: We designed a novel NLP platform, NLPMed, to assist thrombosis researchers with data preprocessing, phenotype annotation, language model finetuning, and NLP application. Using clinical notes, discharge summaries, and radiology reports from patients with cancer at 2 healthcare institutions, we finetuned Bio_Clinical Bidirectional Encoder Representations from Transformers (BERT) to develop VTE-BERT. The new model was trained to detect acute …

Enhancing Patient Positioning Accuracy: Evaluating Daily Cone Beam Computed Tomography In The Halcyon System., Duong Thanh Tai, Luong Tien Phat, Tran Trung Kien, Nguyen Ngoc Anh, Nguyen Xuan Hai, Peter Sandwall, David Bradley, James C L Chow

Oncology Articles

BACKGROUND: Precise patient positioning is crucial for successful radiotherapy, ensuring accurate delivery of radiation to tumors while minimizing exposure to healthy tissues. Positional errors can significantly impact treatment efficacy and increase side effects. This study evaluates the effectiveness of daily cone beam computed tomography (CBCT) imaging in the Halcyon system for detecting and correcting patient misalignments across various cancer types and treatment sites.

METHODS: A retrospective analysis was conducted on 411 patients treated with the Varian Halcyon linear accelerator from August 2022 to August 2024. Patients were grouped based on tumor location: Head and Neck (118 patients), Chest (188 patients), …

Rna Sequencing And Immunohistochemistry Jointly Improve Tumor Biomarker Interpretation, Vladimir Kushnarev, Danil Stupichev, Suren Davitavyan, Kirill Kriukov, Basavaraja U Shanthappa, Anna Butusova, Sofia Menshikova, Anna Belozerova, Anastasia Shvyrkova, Arina Tkachuk, Olga Khatenkova, Linda Balabanian, Ekaterina Postovalova, Jochen K Lennerz, Funda Meric-Bernstam, Alexander Bagaev

Faculty, Staff and Student Publications

This study aimed to assess the correlation between RNA sequencing (RNA-seq) and immunohistochemistry (IHC) in detecting key cancer biomarkers across solid tumors, and then, to establish RNA-seq thresholds that accurately reflect clinical IHC classifications. Expression levels of nine biomarkers-ESR1, PGR, AR, MKI67, ERBB2, CD274, CDX2, KRT7, and KRT20-were analyzed in 365 formalin-fixed, paraffin-embedded samples from breast, lung, gastrointestinal, and other solid carcinomas. Correlations between RNA-seq data and IHC scores were determined using Spearman's correlation coefficients, with RNA-seq cut-offs established to distinguish positive from negative IHC scores. The results revealed strong correlations for most biomarkers, with coefficients ranging from 0.53 to …

Gastrointestinal Infection Before Immune Checkpoint Inhibition Hinders Treatment Efficacy And Increases The Risk Of Colitis, Malek Shatila, Kian Abdul-Baki, Andres Urias Rivera, Kei Takigawa, Irene Jeong-Ah Lee, Andrew Sullivan, Tanvi Gupta, Linfeng Lu, Raakhi Menon, Ayesha Khan, Hamza Salim, Elliot Baerman, Carolina Colli Cruz, Cristina Natha, Varun Vemulapalli, Garrett Coleman, Krishnavathana Varatharajalu, Christopher Fan, Pablo Okhuysen, Anthony J Olszanski, Yan Zhou, Hao Chi Zhang, Mehnaz Shafi, Yinghong Wang

Faculty, Staff and Students Publications

Background: Gastrointestinal (GI) infections, which often result in or stem from intestinal dysbiosis, can affect the efficacy of immune checkpoint inhibitors (ICIs) and increase the risk of adverse effects, such as colitis. In this study, we explored the impact of GI infections before initiation of ICI therapy on the incidence and severity of immune-mediated colitis (IMC) and survival.

Methods: A single-center, retrospective review including all patients who received ICIs from January 2010 to February 2024 and subsequently developed IMC. Patients were screened for IMC and prior GI infections based on symptoms and stool tests. Patients' demographic, IMC, and GI infection-related …

Racial And Ethnic Disparity For Cancer Mortality In General And Single-Payer Healthcare Systems In The United States, Rock Bum Kim, Emily Zhou, Kaitlin N Swinnerton, Jennifer La, Shengling Ma, Mrinal Ranjan, Nhan V Do, Mary T Brophy, Nathanael R Fillmore, Ang Li

Faculty, Staff and Students Publications

Background: It remains unclear what factors significantly drive racial disparity in cancer survival in the United States (US). We compared adjusted mortality outcomes in cancer patients from different racial and ethnic groups on a population level in the US and a single-payer healthcare system.

Patients and methods: We selected adult patients with incident solid and hematologic malignancies from the Surveillance, Epidemiology, and End Results (SEER) 2011-2020 and Veteran Affairs national healthcare system (VA) 2011-2021. We classified the self-reported NIH race and ethnicity into non-Hispanic White (NHW), non-Hispanic Black (NHB), non-Hispanic Asian Pacific Islander (API), and Hispanic. Cox regression models for …

Patient, Physician, And Assessor Blinding In Phase Iii Randomized Trials In Oncology: A Meta-Epidemiological Analysis, Gabrielle Brown, Pavlos Msaouel, Avital M Miller, Ramez Kouzy, Timothy A Lin, Joseph Abi Jaoude, Ethan B Ludmir, Alexander D Sherry

Faculty, Staff and Student Publications

Background: Blinding mitigates bias in randomized trials and may be especially crucial for surrogate endpoints, such as progression-free survival (PFS). Here, we characterize utilization of and factors associated with blinding in Phase III oncology trials with PFS primary endpoints.

Methods: Two-arm, superiority-design trials investigating systemic therapy were identified in May 2024 from ClinicalTrials.gov with no date limitation. Trials were required to have a PFS primary endpoint. The study outcomes were the presence of double-blind designs and blinded independent central review (BICR) for the primary endpoint. Ninety-five percent credible intervals for binary outcomes were estimated from beta distributions, and multivariable logistic …