Neoplasms Commons^™

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 …

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 …

Evolution Of Esophageal Adenocarcinoma From Precursor Lesion Stem Cells, Wa Xian, Shan Wang, Jingzhong Xie, Yusuke Yamamoto, Melina Khorrami, Yanting Zhang, Raul Caballero Montes, Caycel Desales, Melika Khorrami, Zaal Mory, Ashley Hoffman, Amber Su, Crystal Nguyen, Peter J A Davies, Clifford Stephan, Shuang Pan, Wengen Wu, Yuxin Liu, Jeremy Siegelman, Rebecca E Waters, William A Ross, Shumei Song, Mark Metersky, David G Beer, Christopher P Crum, Alexander J Stewart, Matthew Vincent, Richard Russell, Robert A Izard, Khek Yu Ho, Jack Hung-Sen Lai, William W Bachovchin, Jaffer A Ajani, Frank D Mckeon

Faculty, Staff and Student Publications

Background & aims: Metastatic cancers arise from a decades-long succession of increasingly virulent precursor lesions, each of which represents prospective targets for therapeutic intervention. This evolutionary process has been particularly vivid in esophageal adenocarcinoma (EAC), as this cancer and associated precursor lesions, including Barrett's esophagus (BE), low-grade dysplasia (LGD), and high-grade dysplasia (HGD), coexist in an accessible, 2-dimensional pattern in esophageal mucosa. Given the durability of these precursor lesions, it is likely that they, like EAC, rely on stem cells for their regenerative growth. To assess the role of stem cells in the evolution of EAC, we apply technology that …

An Integrative Genomics Approach For The Discovery Of Potential Clinically Actionable Diagnostic And Prognostic Biomarkers In Colorectal Cancer, Mark Fertel, Duaa Mohammad Alawad, Chindo Hicks

School of Graduate Studies Faculty Publications

Background: Despite remarkable progress in clinical management of patients and intensified screening, colorectal cancer remains the second most common cause of cancer-related death in the United States. The recent surge of next generation sequencing has enabled genomic analysis of colorectal cancer genomes. However, to date, there is little information about leveraging gene expression data and integrating it with somatic mutation information to discover potential biomarkers and therapeutic targets. Here, we integrated gene expression data with somatic mutation information to discover potential diagnostic and prognostic biomarkers and molecular drivers of colorectal cancer. Methods: We used publicly available gene expression and somatic …

Impacts Of Radiation On Metabolism And Vascular Cell Senescence, Junichi Abe, Khanh Chau, Anahita Mojiri, Guangyu Wang, Masayoshi Oikawa, Venkata S K Samanthapudi, Abigail M Osborn, Keila C Ostos-Mendoza, Karla N Mariscal-Reyes, Tammay Mathur, Abhishek Jain, Joerg Herrmann, Syed Wamique Yusuf, Sunil Krishnan, Anita Deswal, Steven H Lin, Sivareddy Kotla, John P Cooke, Nhat-Tu Le

Faculty, Staff and Student Publications

Significance: This review investigates how radiation therapy (RT) increases the risk of delayed cardiovascular disease (CVD) in cancer survivors. Understanding the mechanisms underlying radiation-induced CVD is essential for developing targeted therapies to mitigate these effects and improve long-term outcomes for patients with cancer.

Recent Advances: Recent studies have primarily focused on metabolic alterations induced by irradiation in various cancer cell types. However, there remains a significant knowledge gap regarding the role of chronic metabolic alterations in normal cells, particularly vascular cells, in the progression of CVD after RT.

Critical Issues: This review centers on RT-induced metabolic alterations in vascular cells …

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. …

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 …

Global And Regional Disparities In Access To Specialist Sarcoma Services, Tomas Zamora, Eduardo Botello, Thomas Jenkins, Charlotte Jeys, Minna Laitinen, Ajay Puri, Lee Jeys, Boom Consensus Meeting Participants, Santiago Abad Repiso, Hesham Abdelbary, Alejandro Abiad Mejia, Ahmed Abood, Juan C Abril Martin, Adesegun Abudu, Ayman Abu Elhamd, Marthelena Acosta, Keisuke Ae, Manish Agarwal, Vivek Ajit Singh, Toru Akiyama, Ibrahim Alshaygy, Jose I Albergo, John Alexander, Patricio A Alfaro, Bugra Alpan, Jose Amaya-Valero, Megan Anderson, Dimosthenis Andreou, Lucas Annabell, Christopher Anthony, Ahmed Aoude, William Aston, Libe Asua Mentxaka, Christine Azzopardi, Thomas Baad-Hansen, Ismail T Badr, Francisco Baixauli-Garcia, Gavin Baker, Tessa Balach, Giacomo G Baldi, Janie Barry, Georges Basile, Stefano Bastoni, Mohammad H Basuki, Henrik Bauer, Lee Bayliss, Ricardo G Becker, Angad Bedi, Joseph Benevenia, Francisco Bengoa, Peter Bergh, Marko Bergovec, Nicholas Bernthal, Odion Binitie, David Boddie, Michele Boffano, Patricia Bonilla Huertas, Anna B Borgognoni, Rajesh Botchu, Richard A Boyle, Jos Bramer, Rahat Brar, Harriet Branford-White, Demien Broekhuis, Samuel E Broida, Tymoteusz Budny, Zachary D Burke, Jorge Cabrolier, Jose A Calvo-Haro, Jorge R Calvo-Tapies, Domenico A Campanacci, Rodrigo Cardoso, Richard Carey Smith, Pedro I Carvallo, Nicolas Casales Fresenga, Jose M Casanova, Oscar Ceballos, Juan L Cebrian Parra, Laura K Certain, Sara Chancon Cartaya, Chung M Chan, Yoon Joo Cho, Peter Choong, Yang-Guk Chung, David Ciechanowicz, David Clever, Sebastian Colina, Luis Consuegra, Cory Couch, Gillian Cribb, Carlos Cuervo, Laurence A Cusick, Solomon Dadia, Tanios Dagher, Dietmar Dammerer, Mark Davies, Nerys Davies, Luis P De La Rosa Martino, Francisco J De Santos De La Fuente, Marieke De Vaal, Claudia Deckers, Javier Delgado Obando, Shaneel Deo, Niklas Deventer, Claudia Di Bella, Gregory Domson, Davide M Donati, Desiree M Dorleijn, Jacques Du Toit, Debra Dunne, Rodolfo Duran Ciarrochi, Walid Ebeid, Elina Ekman, Ahmed M El Ghoneimy, Makoto Endo, Levent Eralp, Mahmoud Etaiwi, Scott Evans, Robin Evrard, Will Eward, Alberto Farese, Peter C Ferguson, Pedro F Ferreira Cardoso, Fabrice Fiorenza, Michael Flint, Hector Flores, Joao Freitas, Bruno Fuchs, Tomohiro Fujiwara, Philipp T Funovics, Marcos Galli Serra, Zakareya Gamie, Carlos Garces-Zarzalejo, Aaron Gazendam, Carsten Gebert, Jasper G Gerbers, Craig Gerrand, Ghaith Abou-Nouar, Michelle Ghert, Kanishka M Ghosh, Max Gibbons, Luis C Gomez-Mier, Jesus Gomez-Vallejo, Anne Gomez-Mascard, Marcos R Gonzalez, Fausto Gonzalez-Lizan, Georg Gosheger, Stuart Goudie, Krista Goulding, Stavros D Goumenos, Anthony Griffin, Ashish Gulia, Sanjay Gupta, Amit Gupta, Maurice Guzman, Mohammed Haitham, Jendrik Hardes, Francisco Hardoy, Yusuf Hasan, Georg Hauer, Helard Havard, Rex Haydon, John Healey, Nerea Hernandez Gonzalez, Adriana Hernandez-Lopez, Asle Hesla, Matthew Hess, Chindanai Hongsaprabhas, Francis Hornicek, Keith Hosking, Matthew T Houdek, Eleanor Houghton, Oluwaseyi K Idowu, Joseph Ippolito, Marc Isler, Shintaro Iwata, Jake Jagiello, Neil Jenkins, Tom Jeys, Luke Johnson, Andy Johnston, Min Wook Joo, Paul C Jutte, Kadri Kaldas, Amar Kamat, Sudhir Kannan, Bilal Kapanci, Zeeshan Khan, Hiroshi Kobayashi, Yehuda Kollender, Sebastian Koob, Daniel Kotrych, Vineet Kurisunkal, Richard Kyte, Jose M Lamo De Espinosa, Alexander L Lazarides, Louis-Romee Le Nail, Pawel Legosz, Burkhard Lehner, Andreas Leithner, Maryse Lejoly, Valerae O Lewis, Peng Lin, Francisco Linares, Santiago A Lozano-Calderon, Ashish Mahendra, Ferdiansyah Mahyudin, Fermin J Mandia Mancebo, Sara Martos Torrejon, Christian Marx, Eric Mascard, Jean-Camille Mattei, Louise Mccullough, Sam Mcmahon, Manuel R Medellin Rincon, Benjamin Miller, Shinji Miwa, Gustavo Molina Uribe, Bryan Moon, Thomas Hilton, Diego J Moriel Garcesco, Carol Morris, Guy Morris, Steward Morrison, Sophie Mottard, Marcio Moura, Linde Muster, Robert Nakayama, Prashant Narhari, Ana Navas, Prakash Nayak, Johannes Neugebauer, Erik T Newman, Jyrki Nieminen, Emmy Nyqvist, Lukas Nystrom, Sarah O'Reilly-Harbidge, Gary O'Toole, Vania Oliveira, André Olivier, Mohamed Omar, Eduardo J Ortiz-Cruz, Harzem Ozger, Korhan Ozkan, Elisa Pala, Emanuela Palmerini, Grant Pang, Panayiotis Papagelopoulos, Giovanni Paraliticci, Michael C Parry, Sam Patton, David Peake, Ana Peiro Ibanez, Israel Perez Munoz, Ganapathy R Perianayagam, Michael M Petersen, Joris Ploegmakers, Robin Pollock, Gerard Powell, Juan Pretell, Jan Puetzler, Faisal Qamar, Anand Raja, Raja B Rajasekaran, Dipak Ramkumar, R L Randall, Kenneth Rankin, Kevin A Raskin, Kumaran Rassppan, Lauris Repsa, Mickael Ropars, Peter Rose, Pietro Ruggieri, Wael Sadek, German Salcedo, Aasim Saleemi, Andrea Sambri, Hartej Sar, Roberto Scanferla, Thomas Schubert, Jan Schwarze, Guido Scoccianti, Ashley Scrimshire, Tetsuya Sekita, Ahmad Shehadeh, Ahmed Shoaib, Bhim Shreemal, Felix Shumelinsky, Geoffrey Siegel, Claudio Silveri, Robert Silverwood, Friedl Sinnaeve, Jerome Sison, Andrea Slade, Maria A Smolle, Franz Snyman, Scott Sommerville, Sahil Sood, Andre Spiguel, Hugo St-Yves, Eric L Staals, Silvia Stacchiotti, Nikolas Stavropoulos, Peter Steadman, Jonathan D Stevenson, Mikaela Sullivan, Gwen Sys, Bartlomiej Szostakowski, Angela Tamburini, Yuta Taniguchi, Thomas Temple, Christoph Theil, Joachim Thorkildsen, Meagan Tibbo, Roger Tillman, Yu Toda, Kaspar Tootsi, Ferran Torner-Rubies, Frank Traub, Ioannis Trikoupis, Panagiotis Tsagkozis, Kim Tsoi, Hiroyuki Tsuchiya, Veli-Matti Vainio, Antonio Valcarcel, Juan Valencia, Annelies Van Beeck, Michiel Van De Sande, Thomas Van Den Berghe, Ingrid Van Der Geest, Lizz Van Der Heijden, Robert Van Der Wal, Kirsten Van Langevelde, Gualter Vaz, Roberto Velez Villa, Floortje Verspoor, Koenraad Verstraete, Julia Visgauss, Oleg Vyrva, Hazem Wafa, Sebastian Walter, Wan F Wan Ismail, Edward Wang, Patrick Q Wang, David Warnock, Joel Werier, Wolfram Weschenfelder, Kwok-Chuen Wong, Marjan Wouthuyzen-Bakker, Jay Wunder, Indica Wysinghe, Norio Yamamoto, Zhaoming Ye, Seung-Jae Yoon, Suraya Zainul Abidin, Pierluca Zecchetto, Liuzhe Zhang, Juan P Zumarraga, Miguel A Clara-Altamirano

Faculty, Staff and Student Publications

Aims: Cancer care guidelines have been developed in many subspecialities, usually in advanced health systems. However, there are notable global disparities in healthcare access, which can impact sarcoma care. Unfortunately, there is a lack of global data on this subject. Our aim was to describe access to sarcoma care based on a comprehensive global survey among orthopaedic oncologists, and assess for global as well as regional differences.

Methods: A 25-question survey was emailed to the attendees of the 2024 Birmingham Orthopaedic Oncology Meeting and included questions about the respondents' training and practice, access to sarcoma centres, and specific items for …

The Tumor Microenvironment Is An Ecosystem Sustained By Metabolic Interactions, Emily Jane Kay, Sara Zanivan

Faculty, Staff and Student Publications

Cancer-associated fibroblasts (CAFs) and immune cells make up two major components of the tumor microenvironment (TME), contributing to an ecosystem that can either support or restrain cancer progression. Metabolism is a key regulator of the TME, providing a means for cells to communicate with and influence each other, modulating tumor progression and anti-tumor immunity. Cells of the TME can metabolically interact directly through metabolite secretion and consumption or by influencing other aspects of the TME that, in turn, stimulate metabolic rewiring in target cells. Recent advances in understanding the subtypes and plasticity of cells in the TME both open up …

Single-Cell Rna Sequencing Identifies Molecular Biomarkers Predicting Late Progression To Cdk4/6 Inhibition In Patients With Hr+/Her2- Metastatic Breast Cancer, Linjie Luo, Peng Yang, Sofia Mastoraki, Xiayu Rao, Yan Wang, Nicole M Kettner, Akshara Singareeka Raghavendra, Debasish Tripathy, Senthil Damodaran, Kelly K Hunt, Jing Wang, Ziyi Li, Khandan Keyomarsi

Faculty, Staff and Student Publications

Background: Cyclin-dependent kinase 4/6 inhibitors (CDK4/6is) in combination with endocrine therapy are the standard treatment for patients with hormone receptor-positive, HER2-negative metastatic breast cancer (mBC). Despite the efficacy of CDK4/6is, intrinsic resistance occurs in approximately one-third of patients, highlighting the need for reliable predictive biomarkers.

Methods: Single-cell RNA sequencing analyzed metastatic tumors from HR+/HER2- mBC patients pre-CDK4/6i treatment at baseline (BL) and/or at disease progression. BL samples were from CDK4/6i responders (median progression-free survival [mPFS] = 25.5 months), while progressors were categorized as early-progressors (EP, mPFS = 3 months) and late-progressors (LP, mPFS = 11 months). Metastatic sites included liver, …

Genetics And Biology Of Pancreatic Ductal Adenocarcinoma, Haoqiang Ying, Alec C Kimmelman, Nabeel Bardeesy, Raghu Kalluri, Anirban Maitra, Ronald A Depinho

Faculty, Staff and Student Publications

Pancreatic ductal adenocarcinoma (PDAC) poses a grim prognosis for patients. Recent multidisciplinary research efforts have provided critical insights into its genetics and tumor biology, creating the foundation for rational development of targeted and immune therapies. Here, we review the PDAC genomic landscape and the role of specific oncogenic events in tumor initiation and progression, as well as their contributions to shaping its tumor biology. We further summarize and synthesize breakthroughs in single-cell and metabolic profiling technologies that have illuminated the complex cellular composition and heterotypic interactions of the PDAC tumor microenvironment, with an emphasis on metabolic cross-talk across cancer and …

Targeted Inhibition Of Aurora Kinase A Promotes Immune Checkpoint Inhibition Efficacy In Human Papillomavirus-Driven Cancers, Soma Ghosh, Madison P O'Hara, Pragya Sinha, Tuhina Mazumdar, Lacin Yapindi, Jagannadha K Sastry, Faye M Johnson

Faculty, Staff and Student Publications

Background: Human papillomavirus (HPV)-driven cancers include head and neck squamous cell carcinoma and cervical cancer and represent approximately 5% of all cancer cases worldwide. Standard-of-care chemotherapy, radiotherapy, and immune checkpoint inhibitors (ICIs) are associated with adverse effects and limited responses in patients with HPV-driven cancers. The integration of targeted therapies with ICIs may improve outcomes. In a previous study, we demonstrated that Aurora kinase A (AURKA, Aurora A) inhibitors lead to apoptosis of human HPV-positive cancer cells in vitro and in vivo. Here, we explored the potential of Aurora A inhibition to enhance response to ICIs in immune-competent …

Utility Of Pre-Procedural [99mtc]Tcmaa Spect/Ct Multicompartment Dosimetry For Treatment Planning Of 90y Glass Microspheres In Patients With Hepatocellular Carcinoma: Comparison Of Anatomic Versus [99mtc]Tcmaa-Based Segmentation, Marnix Lam, Etienne Garin, Paul Haste, Alban Denys, Brian Geller, S Cheenu Kappadath, Cuneyt Turkmen, Daniel Y Sze, Hamad Saleh Alsuhaibani, Ken Herrmann, Marco Maccauro, Murat Cantasdemir, Matthew Dreher, Kirk D Fowers, Vanessa Gates, Riad Salem

Faculty, Staff and Student Publications

Purpose: Pre-treatment [99mTc]TcMAA-based radioembolization treatment planning using multicompartment dosimetry involves the definition of the tumor and normal tissue compartments and calculation of the prescribed absorbed doses. The aim was to compare the real-world utility of anatomic and [99mTc]TcMAA-based segmentation of tumor and normal tissue compartments.

Materials and methods: Included patients had HCC treated by glass [90Y]yttrium microspheres, ≥ 1 tumor, ≥ 3 cm diameter and [99mTc]TcMAA SPECT/CT imaging before treatment. Segmentation was performed retrospectively using dedicated dosimetry software: (1) anatomic (diagnostic CT/MRI-based), and (2) [99mTc]TcMAA threshold-based (i.e., using an activity-isocontour threshold). CT/MRI was co-registered with [99mTc]TcMAA SPECT/CT. Logistic regression and …

Psychometric Properties And Meaningful Change Thresholds For The Qol-E Instrument In Patients With Myelodysplastic Neoplasms, Esther Natalie Oliva, Shien Guo, Jennifer Lord-Bessen, Aylin Yucel, Roberto Latagliata, Massimo Breccia, Giuseppe A Palumbo, Grazia Sanpaolo, Marta Riva, Valeria Santini, Uwe Platzbecker, Guillermo Garcia-Manero, Pierre Fenaux, Christopher G Pelligra

Faculty, Staff and Student Publications

peripheral blood cytopenias, and an increased risk of progression to acute myeloid leukemia. One of the main treatment goals is improving quality of life (QoL), particularly for patients with lower-risk MDS (LR-MDS) who may live longer with compromised QoL. The QOL-E© is a patient-reported outcome (PRO) measure specifically developed to address the lack of a health-related QoL questionnaire for patients with MDS. The objective of this study was to evaluate the psychometric performance of the QOL-E in patients with LR-MDS.

Methods: Data from four clinical trials in MDS (MEDALIST, DARB-MDS, EQoL-MDS, and RevMDS trials) were used to assess construct validity, …

Predicting Sinonasal Inverted Papilloma Attachment Using Machine Learning: Current Lessons And Future Directions, Sean P Mckee, Xiaomin Liang, William C Yao, Brady Anderson, Jumah G Ahmad, David Z Allen, Salman Hasan, Andy J Chua, Chinmay Mokashi, Samia Islam, Amber U Luong, Martin J Citardi, Luca Giancardo

Faculty, Staff and Student Publications

Background: Hyperostosis is a common radiographic feature of inverted papilloma (IP) tumor origin on computed tomography (CT). Herein, we developed a machine learning (ML) model capable of analyzing CT images and identifying IP attachment sites.

Methods: A retrospective review of patients treated for IP at our institution was performed. The tumor attachment site was manually segmented on CT scans by the operating surgeon. We used a nnU-Net model, a state-of-the-art deep learning-based segmentation algorithm that automatically configures image preprocessing, network architecture, training, and post-processing to identify the IP attachment site. The model was trained and evaluated using a 5-fold cross …

Tissue And Imaging Biomarkers Of Response To Neoadjuvant Nivolumab Or Nivolumab Plus Ipilimumab In Patients With Resectable Hepatocellular Carcinoma, Michael Lapelusa, Shadi Chamseddine, Hop Sanderson Tran Cao, Lianchun Xiao, Elshad Hasanov, Priya Bhosale, Hesham M Amin, Yehia I Mohamed, Betul Gok Yavuz, Yara Sakr, Li Xu, Ian Hu, Sunyoung S Lee, Divya Sakamuri, Sonali Jindal, Van Nguyen, Michael A Curran, Ryan Sun, Asif Rashid, Dan Gabriel Duda, Padmanee Sharma, Aliya Qayyum, Ahmed Omar Kaseb

Faculty, Staff and Student Publications

Introduction: Perioperative immunotherapy has shown promise in some patients with early-stage hepatocellular carcinoma (HCC). This study examined tissue and imaging biomarkers associated with pathologic response in a phase II clinical trial in patients with resectable HCC.

Methods: Analysis included 18 patients with biopsy-proven resectable HCC treated with neoadjuvant nivolumab plus ipilimumab or nivolumab alone in a phase II clinical trial at MD Anderson Cancer Center (NCT03222076). Liver MRE (to measure tissue fibrosis) and biopsies (to evaluate immune activation markers) were obtained serially pretreatment and after completing neoadjuvant immunotherapy. A major pathologic response (MPR) was defined as tumor necrosis …

Knowledge-Based Planning For Fully Automated Radiation Therapy Treatment Planning Of 10 Different Cancer Sites, Christine V Chung, Meena S Khan, Adenike Olanrewaju, Mary Pham, Quyen T Nguyen, Tina Patel, Prajnan Das, Michael S O'Reilly, Valerie K Reed, Anuja Jhingran, Hannah Simonds, Ethan B Ludmir, Karen E Hoffman, Komeela Naidoo, Jeannette Parkes, Ajay Aggarwal, Lauren L Mayo, Shalin J Shah, Chad Tang, Beth M Beadle, Julie Wetter, Gary Walker, Simon Hughes, Vinod Mullassery, Stephen Skett, Christopher Thomas, Lifei Zhang, Son Nguyen, Raymond P Mumme, Raphael J Douglas, Hana Baroudi, Laurence E Court

Faculty, Staff and Student Publications

Purpose: Radiation treatment planning is highly complex and can have significant inter- and intra-planner inconsistency, as well as variability in planning time and plan quality. Knowledge-based planning (KBP) is a tool that can be used to efficiently produce high-quality, consistent, clinically acceptable plans, independent of planner skills and experience. In this study, we created and validated multiple clinically acceptable and fully automatable KBP models, with the goal of creating VMAT plans without user intervention.

Methods: Ten KBP models were configured using high quality clinical plans from a single institution. They were then honed to be part of a fully automatable …

Comparison Of Vendor-Pretrained And Custom-Trained Deep Learning Segmentation Models For Head-And-Neck, Breast, And Prostate Cancers, Xinru Chen, Yao Zhao, Hana Baroudi, Mohammad D El Basha, Aji Daniel, Skylar S Gay, Cenji Yu, He Wang, Jack Phan, Seungtaek L Choi, Chelain R Goodman, Xiaodong Zhang, Joshua S Niedzielski, Sanjay S Shete, Laurence E Court, Zhongxing Liao, Fredrik Löfman, Peter A Balter, Jinzhong Yang

Faculty, Staff and Student Publications

Background/objectives: We assessed the influence of local patients and clinical characteristics on the performance of commercial deep learning (DL) segmentation models for head-and-neck (HN), breast, and prostate cancers.

Methods: Clinical computed tomography (CT) scans and clinically approved contours of 210 patients (53 HN, 49 left breast, 55 right breast, and 53 prostate cancer) were used to train and validate segmentation models integrated within a vendor-supplied DL training toolkit and to assess the performance of both vendor-pretrained and custom-trained models. Four custom models (HN, left breast, right breast, and prostate) were trained and validated with 30 (training)/5 (validation) HN, 34/5 left …

Nuclear Expression Of Dynamin 2 Is Associated With Tumor Aggressiveness In Bladder Cancer Patients: A Bioinformatics And Experimental Approach, Mahdieh Razmi, Leili Saeednejad Zanjani, Mandana Rahimi, Roya Sajed, Sadegh Safaei, Zahra Madjd, Roya Ghods

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

BACKGROUND: Dynamin 2 (DNM2) is aberrantly expressed in different malignancies and exerts a function in tumor progression.

AIMS: This study, for the first time, aimed to evaluate the clinical and prognostic value of DNM2 in the pathophysiology of bladder cancer using bioinformatics analysis and experimental evaluation.

METHODS AND RESULTS: We analyzed gene expression of DNM2 in bladder tumor by GEPIA2 and GENT2 platforms. Cluster subnetworks were recognized from the protein-protein interaction (PPI) network using the MCODE plugin to screen the key genes. Subsequently, the pathway enrichment analysis was evaluated. Then, the immunohistochemical examination was conducted on 209 paraffin-embedded bladder cancer …

What Do Cancer Genetic Providers Want Us To Know About Variant Reclassification And Recontact That We Are Not Asking? A Thematic Analysis Of Open-Ended Survey Responses, Kerri Brown, Marisel Ponton, Elenita Davidson, Banu Arun, Robert J Volk, Sanjay Shete, Susan K Peterson, Sukh Makhnoon

Faculty, Staff and Student Publications

BACKGROUND: Accurate variant classification and relaying reclassified results to patients is critical for hereditary cancer care delivery. Over a 5- to 10-year period, 6%-15% of variants undergo reclassification. As the frequency of reclassifications increases, the issue of whether, how, when, and which providers should recontact patients becomes important but remains contentious.

METHODS: The authors used inductive thematic analysis to analyze open-ended comments offered by oncologists and genetic counselors (GCs) from a large national survey.

RESULTS: Of the 634 oncologists and cancer GCs, 126 (20%) offered substantive free-text comments. Four thematic areas emerged: 1) ambiguity over professional responsibility to recontact, 2) …

Micrornas Are Enriched At Covid-19 Genomic Risk Regions, And Their Blood Levels Correlate With The Covid-19 Prognosis Of Cancer Patients Infected By Sars-Cov-2, Simone Anfossi, Faezeh Darbaniyan, Joseph Quinlan, Steliana Calin, Masayoshi Shimizu, Meng Chen, Paola Rausseo, Michael Winters, Elena Bogatenkova, Kim-Anh Do, Ivan Martinez, Ziyi Li, Loredana Antal, Tudor Rares Olariu, Ignacio Wistuba, George A Calin

Faculty, Staff and Student Publications

Background: Cancer patients are more susceptible to an aggressive course of COVID-19. Developing biomarkers identifying cancer patients at high risk of COVID-19-related death could help determine who needs early clinical intervention. The miRNAs hosted in the genomic regions associated with the risk of aggressive COVID-19 could represent potential biomarkers for clinical outcomes.

Patients and methods: Plasma samples were collected at The University of Texas MD Anderson Cancer Center from cancer patients (N = 128) affected by COVID-19. Serum samples were collected from vaccinated healthy individuals (n = 23) at the Municipal Clinical Emergency Teaching Hospital in Timisoara, Romania. An in …

Molecular And Clinical Features Of Pancreatic Acinar Cell Carcinoma: A Single-Institution Case Series, Ashwathy Balachandran Pillai, Mahmoud Yousef, Abdelrahman Yousef, Kristin D Alfaro-Munoz, Brandon G Smaglo, Jason Willis, Robert A Wolff, Shubham Pant, Mark W Hurd, Anirban Maitra, Huamin Wang, Matthew Harold G Katz, Laura R Prakash, Ching-Wei D Tzeng, Rebecca Snyder, Luca F Castelnovo, Anthony Chen, Andrey Kravets, Kseniia Kudriavtseva, Artem Tarasov, Kirill Kryukov, Haoqiang Ying, John Paul Shen, Dan Zhao

Faculty, Staff and Student Publications

Objectives: Acinar cell carcinoma (ACC) accounts for about 1% of pancreatic cancers. The molecular and clinical features of ACC are less characterized than those of pancreatic ductal adenocarcinoma. Methods: We retrospectively evaluated the clinical and molecular features of ACC patients who underwent germline and/or somatic molecular testing at The University of Texas MD Anderson Cancer Center from 2008 to 2022 and two cases from 2023-2024 who underwent RNA and TME analysis by Boston Gene. Patient information was extracted from our institutional database with the approval of the Institutional Review Board. Results: We identified 16 patients with available molecular testing …

A Systematic Review On The Techniques, Long-Term Outcomes, And Complications Of Partial Breast Irradiation After Breast-Conserving Surgery For Early-Stage Breast Cancer, Jing Ning, Guanghui Cheng, Ning Wu

Faculty, Staff and Student Publications

To evaluate the efficacy and safety of four techniques of partial breast irradiation (PBI) including interstitial brachytherapy (ISBT), balloon-based brachytherapy (BBT), Intraoperative radiotherapy (IORT) and three-dimensional conformal radiotherapy (3DCRT) in the treatment for early-stage breast cancer patients after breast-conserving surgery. A systematic search was performed according to the Preferred Reporting Items of Systematic Reviews and Meta-analyses (PRISMA) guidelines using the PubMed, Embase, Cochrane Library and Web of Science databases. The inclusion criteria were clinical trials and observational studies that reported on outcome measures of principal PBI techniques. The methodological quality of the included research data was assessed using bias risk …

The P-Myh9/Usp22/Hif-1Α Axis Promotes Lenvatinib Resistance And Cancer Stemness In Hepatocellular Carcinoma, Qiaonan Shan, Lu Yin, Qifan Zhan, Jiongjie Yu, Sheng Pan, Jianyong Zhuo, Wei Zhou, Jiaqi Bao, Lincheng Zhang, Jiachen Hong, Jianan Xiang, Qingyang Que, Kangchen Chen, Shengjun Xu, Jingrui Wang, Yangbo Zhu, Bin He, Jingbang Wu, Haiyang Xie, Shusen Zheng, Tingting Feng, Sunbin Ling, Xiao Xu

Faculty, Staff and Student Publications

Lenvatinib is a targeted drug used for first-line treatment of hepatocellular carcinoma (HCC). A deeper insight into the resistance mechanism of HCC against lenvatinib is urgently needed. In this study, we aimed to dissect the underlying mechanism of lenvatinib resistance (LR) and provide effective treatment strategies. We established an HCC model of acquired LR. Cell counting, migration, self-renewal ability, chemoresistance and expression of stemness genes were used to detect the stemness of HCC cells. Molecular and biochemical strategies such as RNA-sequencing, immunoprecipitation, mass spectrometry and ubiquitination assays were used to explore the underlying mechanisms. Patient-derived HCC models and HCC samples …

Targeting Igf2 To Reprogram The Tumor Microenvironment For Enhanced Viro-Immunotherapy, Min Hye Noh, Jin Muk Kang, Alexandra A Miller, Grace Nguyen, Minxin Huang, Ji Seon Shim, Alberto J Bueso-Perez, Sara A Murphy, Kimberly A Rivera-Caraballo, Yoshihiro Otani, Eunju Kim, Seung-Hee Yoo, Yuanqing Yan, Yeshavanth Banasavadi-Siddegowda, Hiroshi Nakashima, E Antonio Chiocca, Balveen Kaur, Zhongming Zhao, Tae Jin Lee, Ji Young Yoo

Faculty, Staff and Student Publications

BACKGROUND: The FDA approval of oncolytic herpes simplex-1 virus (oHSV) therapy underscores its therapeutic promise and safety as a cancer immunotherapy. Despite this promise, the current efficacy of oHSV is significantly limited to a small subset of patients largely due to the resistance in tumor and tumor microenvironment (TME).

METHODS: RNA sequencing (RNA-Seq) was used to identify molecular targets of oHSV resistance. Intracranial human and murine glioma or breast cancer brain metastasis (BCBM) tumor-bearing mouse models were employed to elucidate the mechanism underlying oHSV therapy-induced resistance.

RESULTS: Transcriptome analysis identified IGF2 as one of the top-secreted proteins following oHSV treatment. …

Neoadjuvant Parpi Or Chemotherapy In Ovarian Cancer Informs Targeting Effector Treg Cells For Homologous-Recombination-Deficient Tumors, Yikai Luo, Yu Xia, Dan Liu, Xiong Li, Huayi Li, Jiahao Liu, Dongchen Zhou, Yu Dong, Xin Li, Yiyu Qian, Cheng Xu, Kangjia Tao, Guannan Li, Wen Pan, Qing Zhong, Xingzhe Liu, Sen Xu, Zhi Wang, Ronghua Liu, Wei Zhang, Wanying Shan, Tian Fang, Siyuan Wang, Zikun Peng, Ping Jin, Ning Jin, Shennan Shi, Yuxin Chen, Mengjie Wang, Xiaofei Jiao, Mengshi Luo, Wenjian Gong, Ya Wang, Yue Yao, Yi Zhao, Xinlin Huang, Xuwo Ji, Zhaoren He, Guangnian Zhao, Rong Liu, Mingfu Wu, Gang Chen, Li Hong, Cocpo Consortium, Ding Ma, Yong Fang, Han Liang, Qinglei Gao

Faculty, Staff and Student Publications

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD …

Artificial Intelligence-Based Segmentation Of Residual Pancreatic Cancer In Resection Specimens Following Neoadjuvant Treatment (Isgpp-2): International Improvement And Validation Study, Boris V Janssen, Bart Oteman, Mahsoem Ali, Pieter A Valkema, Volkan Adsay, Olca Basturk, Deyali Chatterjee, Angela Chou, Stijn Crobach, Michael Doukas, Paul Drillenburg, Irene Esposito, Anthony J Gill, Seung-Mo Hong, Casper Jansen, Mike Kliffen, Anubhav Mittal, Jas Samra, Marie-Louise F Van Velthuysen, Aslihan Yavas, Geert Kazemier, Joanne Verheij, Ewout Steyerberg, Marc G Besselink, Huamin Wang, Caroline Verbeke, Arantza Fariña, Onno J De Boer, Pancreatobiliary And Hepatic Artificial Intelligence Research (Phair) Consortium, International Study Group Of Pancreatic Pathologists (Isgpp);

Faculty, Staff and Student Publications

Neoadjuvant therapy (NAT) has become routine in patients with borderline resectable pancreatic cancer. Pathologists examine pancreatic cancer resection specimens to evaluate the effect of NAT. However, an automated scoring system to objectively quantify residual pancreatic cancer (RPC) is currently lacking. Herein, we developed and validated the first automated segmentation model using artificial intelligence techniques to objectively quantify RPC. Digitized histopathological tissue slides were included from resected pancreatic cancer specimens from 14 centers in 7 countries in Europe, North America, Australia, and Asia. Four different scanner types were used: Philips (56%), Hamamatsu (27%), 3DHistech (10%), and Leica (7%). Regions of interest …

Landmark-Based Auto-Contouring Of Clinical Target Volumes For Radiotherapy Of Nasopharyngeal Cancer, Carlos Sjogreen, Tucker J Netherton, Anna Lee, Moaaz Soliman, Skylar S Gay, Callistus Nguyen, Raymond Mumme, Ivan Vazquez, Dong Joo Rhee, Carlos E Cardenas, Mary K Martel, Beth M Beadle, Laurence Edward Court

Faculty, Staff and Student Publications

Background: The delineation of clinical target volumes (CTVs) for radiotherapy for nasopharyngeal cancer is complex and varies based on the location and extent of disease.

Purpose: The current study aimed to develop an auto-contouring solution following one protocol guidelines (NRG-HN001) that can be adjusted to meet other guidelines, such as RTOG-0225 and the 2018 International guidelines.

Methods: The study used 2-channel 3-dimensional U-Net and nnU-Net framework to auto-contour 27 normal structures in the head and neck (H&N) region that are used to define CTVs in the protocol. To define the CTV-Expansion (CTV1 and CTV2) and CTV-Overall (the outer envelope of …

In Silico Modelling And Docking Simulation Of Egfr-Targeted Diphtheria Toxin Chimera With Various Targeting Moieties, Muhammad Afif Naufal Bmed, Benedictus Ansell Susanto Bmed, Talitha Dinda Gunawan Bmed, Azhar Ridha Lukman Bmed, Alifa Rahma Rizqina Bmed, Muhammad Misbahul Fuad Bmed

Indonesian Journal of Medical Chemistry and Bioinformatics

Introduction: Cancer is a major etiology of death worldwide due to high mortality and suboptimal medicine. However, an emerging field, targeted therapy enabled a more selective and effective therapeutic action. This article aims to analyze in-silico the hypothetical targeted therapy agent that is combinations of conjugate consisting of EGFR targeting moieties and diphtheria toxin (DT-390).

Method: Our novel peptide is a conjugate of a novel EGFR targeting peptide and DT-390, forming a chimera. The tertiary structure was predicted using AlphaFold 2.0. The best IDDT scoring and stereochemistry profiles were utilized. The HADDOCK2.4 webserver modelled the docking between our …

Whole Genome And Reverse Protein Phase Array Landscapes Of Patient Derived Osteosarcoma Xenograft Models, Chia-Chin Wu, Licai Huang, Zhongting Zhang, Zhenlin Ju, Xingzhi Song, E Anders Kolb, Wendong Zhang, Jonathan Gill, Min Ha, Malcolm A Smith, Peter Houghton, Christopher L Morton, Raushan Kurmasheva, John Maris, Yael Mosse, Yiling Lu, Richard Gorlick, P Andrew Futreal, Hannah C Beird

Faculty, Staff and Student Publications

Osteosarcoma is the most common primary bone malignancy in children and young adults, and it has few treatment options. As a result, there has been little improvement in survival outcomes in the past few decades. The need for models to test novel therapies is especially great in this disease since it is both rare and does not respond to most therapies. To address this, an NCI-funded consortium has characterized and utilized a panel of patient-derived xenograft models of osteosarcoma for drug testing. The exomes, transcriptomes, and copy number landscapes of these models have been presented previously. This study now adds …