Biomedical Informatics Commons^™

Pspc1 Exerts An Oncogenic Role In Aml By Regulating A Leukemic Transcription Program In Cooperation With Pu1, Juyeong Hong, Pinpin Sui, Ying Li, Kerryn Y Xu, Ji-Hoon Lee, Juan Wang, Shi Chen, Peng Zhang, Noah Wingate, Asra Noor, Yaxia Yuan, Robert Hromas, Hongwei Zhou, Karina Hamamoto, Rui Su, C Cameron Yin, Fengxi Ye, Andrés E Quesada, Jianjun Chen, Suming Huang, Daohong Zhou, M James You, Feng-Chun Yang, Jianlong Wang, Mingjiang Xu

Faculty, Staff and Student Publications

Acute myeloid leukemia (AML) is an aggressive hematopoietic malignancy characterized by the blockage of myeloid cell differentiation and uncontrolled proliferation of immature myeloid cells. Here, we show that paraspeckle component 1 (PSPC1) is aberrantly overexpressed and associated with poor survival in AML patients. Using human AML cells and mouse models, we demonstrate that PSPC1 is not required for normal hematopoiesis, but it is critical and essential for AML cells to maintain their leukemic characteristics. PSPC1 loss induces robust differentiation, suppresses proliferation, and abolishes leukemogenesis in diverse AML cells. Mechanistically, PSPC1 exerts a pro-leukemia effect by regulating a unique leukemic transcription …

Drbioright 20: An Llm-Powered Bioinformatics Chatbot For Large-Scale Cancer Functional Proteomics Analysis, Wei Liu, Jun Li, Yitao Tang, Yining Zhao, Chaozhong Liu, Meiyi Song, Zhenlin Ju, Shwetha V Kumar, Yiling Lu, Rehan Akbani, Gordon B Mills, Han Liang

Faculty, Staff and Student Publications

Functional proteomics provides critical insights into cancer mechanisms, facilitating the discovery of novel biomarkers and therapeutic targets. We have developed a comprehensive cancer functional proteomics resource using reverse phase protein arrays, incorporating data from nearly 8000 patient samples from The Cancer Genome Atlas and approximately 900 samples from the Cancer Cell Line Encyclopedia. Our dataset includes a curated panel of nearly 500 high-quality antibodies, covering all major cancer hallmark pathways. To enhance the accessibility and analytic power of this resource, we introduce DrBioRight 2.0 ( https://drbioright.org ), an intuitive bioinformatic platform powered by state-of-the-art large language models. DrBioRight enables researchers …

Photoacoustic Imaging For Image-Guided Gastric Tube Placement: Ex Vivo Characterization, Samuel John, Yeidi Yuja Vaquiz, Nikhila Nyayapathi, Loay Kabbani, Anoop Nilam, Jonathan F Lovell, Nicole A Wilson, Yan Yan, Mohammad Mehrmohammadi

Faculty, Staff and Student Publications

Over 250,000 gastrostomy tubes (G-tubes) are placed annually in the United States. Percutaneous endoscopic gastrostomy (PEG) is the most widely used clinical method for placing G-tubes within the stomach. However, endoscope detectability is limited due to the scattering of light by tissues. Poor organ visibility and low sensitivity of the palpation techniques cause blind needle insertions, which cause colon/liver perforations, abdominal bleeding, and gastric resections. Additionally, imaging artifacts and the poor distinguishability between water-filled tissues make ultrasound (US) imaging-based techniques incompatible with G-tube placement. The risk of ionizing radiation exposure and the confinement of fluoroscopy to radiology suites limits its …

Learning Directed Acyclic Graphs For Ligands And Receptors Based On Spatially Resolved Transcriptomic Data Of Ovarian Cancer, Shrabanti Chowdhury, Sammy Ferri-Borgogno, Peng Yang, Wenyi Wang, Jie Peng, Samuel C Mok, Pei Wang

Faculty, Staff and Student Publications

To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancements in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that power cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and immune/stroma cells based on ST …

Addressing Health Disparities In Hematologic Malignancies: From Genes To Outreach, Christopher R Flowers, Rachel W Anantha, Veronica Leautaud, Pinkal Desai, Chancellor E Donald, Michelle A T Hildebrandt, Jean L Koff, Rulla M Tamimi, Wendy Cozen, Chijioke Nze, Ari M Melnick

Faculty, Staff and Student Publications

This review underscores our shared responsibility to champion multidimensional strategies rooted in basic and translational science, community involvement, and societal responsiveness for a meaningful impact. Unifying themes include the need to enhance collaborative infrastructure to engage laboratory researchers, epidemiologists, data scientists, clinicians, patients, community leaders, and policymakers; patient-level support services; outreach, education, and navigation for patients at the community level; recruitment and retention of underrepresented groups in the healthcare and research workforce; and funding for these efforts.

Gain-Of-Function Chromatin Remodeling Activity Of Oncogenic Foxl2c134w Reprograms Glucocorticoid Receptor Occupancy To Drive Granulosa Cell Tumors, Thomas Welte, Veena K Vuttaradhi, Eleonora Y Khlebus, Allison Brodsky, Alejandra Flores Legarreta, Joseph Celestino, Reid T Powell, Clifford C Stephan, Nghi Nguyen, Jian Li, Shiro Takamatsu, Katherine Calzoncinth, Anil K Sood, David M Gershenson, P Andrew Futreal, Barrett Lawson, R Tyler Hillman

Faculty, Staff and Student Publications

Adult type ovarian granulosa cell tumors (AGCT) are rare malignancies with the near universal c.C402G (p.Cys134Trp) somatic mutation in FOXL2, a forkhead box family transcription factor important for ovarian function. Relapsed AGCT is incurable, but the mechanism of the unique FOXL2 mutation could confer therapeutic vulnerabilities. To identify FOXL2C134W-dependent pharmacologic synergies, we created and characterized endogenous FOXL2 isogenic AGCT cells and an AGCT tumoroid biobank. A drug screen identified that glucocorticoids promote FOXL2C134W-dependent AGCT growth. Epigenetic investigation revealed that the Cys134Trp mutation exposes latent DNA sequence-specific chromatin remodeling activity in FOXL2. FOXL2C134W-dependent chromatin remodeling activity redirected glucocorticoid receptor chromatin occupancy …

First-In-Human Clinical Trial Of A Small-Molecule Ebna1 Inhibitor, Vk-2019, In Patients With Epstein-Barr-Positive Nasopharyngeal Cancer, With Pharmacokinetic And Pharmacodynamic Studies, A Dimitrios Colevas, Zahra Talebi, Elizabeth Winters, Caroline Even, Victor Ho-Fun Lee, Maura L Gillison, Saad A Khan, Rong Lu, Benjamin A Pinsky, Samantha S Soldan, Olga Vladmirova, Paul M Lieberman, Troy E Messick

Faculty, Staff and Student Publications

Purpose: A first-in-human phase I study was conducted in patients with nasopharyngeal carcinoma to assess the safety and tolerability of VK-2019, a small-molecule selective inhibitor of Epstein-Barr virus (EBV) nuclear antigen 1 (EBNA1).

Patients and methods: Pharmacokinetic and pharmacodynamic studies were performed, including the measurement of EBV DNA plasma levels. Twenty-three patients received VK-2019 orally once daily at doses ranging from 60 to 1,800 mg using an accelerated titration design, with cohort expansion at 1,800 mg. EBV genome copy number and spatial transcriptomic analyses were conducted on biopsies collected from three patients at baseline and after treatment.

Results: VK-2019 was …

Ancestral Differences In Anticancer Treatment Efficacy And Their Underlying Genomic And Molecular Alterations, Mei Luo, Jingwen Yang, Alejandro A Schäffer, Chengxuan Chen, Yuan Liu, Yamei Chen, Chunru Lin, Lixia Diao, Yong Zang, Yanyan Lou, Huda Salman, Gordon B Mills, Eytan Ruppin, Leng Han

Faculty, Staff and Student Publications

Systematic multi-omics analysis revealed ancestry-dependent molecular alterations, but their impact on the efficacy of anti-cancer treatment is yet largely unknown. Here, we analyzed clinical trials from ClinicalTrials.gov and found that only 8,779/102,721 (8.5%) oncology clinical trials posted information on enrollment by race/ethnicity. The underrepresentation of non-White populations suggests that it remains challenging to determine differences in the efficacy of anti-tumor treatments among different racial groups. Through a comprehensive analysis of clinically actionable genes, imputed drug responses, and immune features, we identified potential differences in treatment response to targeted, chemo and immunotherapies between different ancestral populations. Further analysis of multiple independent …

A Novel Sensitivity Maximization At A Given Specificity Method For Binary Classifications, Seyyed Mahmood Ghasemi, Chunhui Gu, Johannes F Fahrmann, Samir Hanash, Kim-Anh Do, James P Long, Ehsan Irajizad

Faculty, Staff and Student Publications

In the cancer early detection field, logistic regression (LR) is a frequently used approach to establish a combination rule that differentiates cancer from noncancer. However, the application of LR relies on a maximum likelihood approach, which may not yield optimal combination rules for maximizing sensitivity at a clinically desirable specificity and vice versa. In this article, we have developed an improved regression framework, sensitivity maximization at a given specificity (SMAGS), for binary classification that finds the linear decision rule, yielding the maximum sensitivity for a given specificity or the maximum specificity for a given sensitivity. We additionally expand the framework …

Safety And Efficacy Of Dtx401, An Aav8-Mediated Liver-Directed Gene Therapy, In Adults With Glycogen Storage Disease Type I A (Gsdia), David A Weinstein, Terry G Derks, David F Rodriguez-Buritica, Ayesha Ahmad, María-Luz Couce, John J Mitchell, Rebecca Riba-Wolman, Malaya Mount, Julieta Bonvin Sallago, Katalin M Ross, Melanie M Van Der Klauw, Foekje De Boer, Caroline Van Der Schaaf, Heather Saavedra, Miguel Martínez-Olmos, Elvis Atanga, Asad Hosseini, Deepali Mitragotri, Eric Crombez

Faculty, Staff and Student Publications

Glycogen storage disease type Ia (GSDIa) is a rare, life‐threatening, inherited carbohydrate metabolism disorder caused by glucose‐6‐phosphatase (G6Pase) deficiency, which is essential for glycogenolysis and gluconeogenesis. GSDIa management includes a strict medically prescribed diet that typically includes daily uncooked cornstarch doses, including overnight, to maintain euglycemia. DTX401 is an investigational adeno‐associated virus serotype 8 vector expressing the human G6PC1 gene that encodes G6Pase. This open‐label, phase 1/2, dose‐escalation, 52‐week gene therapy trial evaluated the safety and efficacy of a single DTX401 infusion in 12 adults with GSDIa (ClinicalTrials.gov Identifier: NCT03517085). Three participants in Cohort 1 received DTX401 2.0 × …

Bevacizumab Beyond Progression: Impact Of Subsequent Bevacizumab Re-Treatment In Patients With Ovarian, Fallopian Tube, And Peritoneal Cancer After Progression, Amma Asare, Rebecca Ann Previs, Daniel Spinosa, Bryan Fellman, Amelia L Scott, Isabelle Mulder, May Mahmoud, Ahmed Enbaya, Jean Hansen Siedel, Lauren Cobb, Pamela T Soliman, Anil K Sood, Robert L Coleman, Angeles Alvarez Secord, Shannon N Westin

Faculty, Staff and Student Publications

Background: This study evaluated whether patients with epithelial ovarian, fallopian tube, and primary peritoneal carcinoma (OC) who are immediately re-treated with bevacizumab derive benefit after disease progression on a bevacizumab-containing regimen.

Methods: This multi-institutional, retrospective study compared patients with high grade non-mucinous epithelial OC who received bevacizumab followed directly by another bevacizumab-containing treatment regimen to patients who received bevacizumab followed by a regimen that did not contain bevacizumab (or received no further treatment). Progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan Meier product-limit estimator and modeled via Cox proportional hazards regression.

Results: Among 226 patients with OC …

A Neoantigen Vaccine Generates Antitumour Immunity In Renal Cell Carcinoma, David A Braun, Giorgia Moranzoni, Vipheaviny Chea, Bradley A Mcgregor, Eryn Blass, Chloe R Tu, Allison P Vanasse, Cleo Forman, Juliet Forman, Alexander B Afeyan, Nicholas R Schindler, Yiwen Liu, Shuqiang Li, Jackson Southard, Steven L Chang, Michelle S Hirsch, Nicole R Leboeuf, Oriol Olive, Ambica Mehndiratta, Haley Greenslade, Keerthi Shetty, Susan Klaeger, Siranush Sarkizova, Christina B Pedersen, Matthew Mossanen, Isabel Carulli, Anna Tarren, Joseph Duke-Cohan, Alexis A Howard, J Bryan Iorgulescu, Bohoon Shim, Jeremy M Simon, Sabina Signoretti, Jon C Aster, Liudmila Elagina, Steven A Carr, Ignaty Leshchiner, Gad Getz, Stacey Gabriel, Nir Hacohen, Lars R Olsen, Giacomo Oliveira, Donna S Neuberg, Kenneth J Livak, Sachet A Shukla, Edward F Fritsch, Catherine J Wu, Derin B Keskin, Patrick A Ott, Toni K Choueiri

Faculty, Staff and Student Publications

Personalized cancer vaccines (PCVs) can generate circulating immune responses against predicted neoantigens1-6. However, whether such responses can target cancer driver mutations, lead to immune recognition of a patient's tumour and result in clinical activity are largely unknown. These questions are of particular interest for patients who have tumours with a low mutational burden. Here we conducted a phase I trial (ClinicalTrials.gov identifier NCT02950766) to test a neoantigen-targeting PCV in patients with high-risk, fully resected clear cell renal cell carcinoma (RCC; stage III or IV) with or without ipilimumab administered adjacent to the vaccine. At a median follow-up of 40.2 …

Exome Sequencing Identifies Helb As A Novel Susceptibility Gene For Non-Mucinous, Non-High-Grade-Serous Epithelial Ovarian Cancer, Ed M Dicks, Jonthan P Tyrer, Suzana Ezquina, Michelle Jones, John Baierl, Pei-Chen Peng, Michael Diaz, Ellen Goode, Stacey J Winham, Thilo Dörk, Toon Van Gorp, Anna De Fazio, David D L Bowtell, Dale W Garsed, Kunle Odunsi, Kirsten Moysich, Marina Pavanello, Florentia Fostira, Penelope M Webb, Jana Soukupová, Paul A Cohen, Weiva Sieh, Renée Turzanski Fortner, Charite Ricker, Beth Karlan, Ian Campbell, James D Brenton, Susan J Ramus, Simon A Gayther, Paul D P Pharoah

Faculty, Staff and Student Publications

Rare, germline loss-of-function variants in a handful of DNA repair genes are associated with epithelial ovarian cancer. The aim of this study was to evaluate the role of rare, coding, loss-of-function variants across the genome in epithelial ovarian cancer. We carried out a gene-by-gene burden test with various histotypes using data from 2573 non-mucinous cases and 13,923 controls. Twelve genes were associated at a False Discovery Rate of less than 0.1 of which seven were the known ovarian cancer susceptibility genes BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, MSH6 and PALB2. The other five genes were OR2T35, HELB, MYO1A and GABRP which …

Immunelens Characterizes Systemic Immune Dysregulation In Aging And Cancer, Robert Bentham, Thomas P Jones, James R M Black, Carlos Martinez-Ruiz, Michelle Dietzen, Maria Litovchenko, Kerstin Thol, Thomas B K Watkins, Chris Bailey, Oriol Pich, Zhihui Zhang, Peter Van Loo, Genomics England Consortium, Tracerx Consortium, Charles Swanton, Nicholas Mcgranahan

Faculty, Staff and Student Publications

Recognition and elimination of pathogens and cancer cells depend on the adaptive immune system. Thus, accurate quantification of immune subsets is vital for precision medicine. We present immune lymphocyte estimation from nucleotide sequencing (ImmuneLENS), which estimates T cell and B cell fractions, class switching and clonotype diversity from whole-genome sequencing data at depths as low as 5× coverage. By applying ImmuneLENS to the 100,000 Genomes Project, we identify genes enriched with somatic mutations in T cell-rich tumors, significant sex-based differences in circulating T cell fraction and demonstrated that the circulating T cell fraction in patients with cancer is significantly lower …

Diet-Enhanced Lrg1 Expression Promotes Insulin Hypersecretion And Er Stress In Pancreatic Beta Cells, Desirae D Morales, Jiyoon Ryu, Cong Wei, Jason T Hadley, Maia R Smith, Juli Bai, Juan C Lopez-Alvarenga, Srinivas Mummidi, Ravindranath Duggirala, Jane L Lynch, Feng Liu, Lily Q Dong

Faculty, Staff and Student Publications

Aims/hypothesis: Upregulation of serum leucine-rich α-2-glycoprotein 1 (LRG1) has been implicated in diet-induced obesity and metabolic disorders. However, its specific hormonal actions remain unclear. This study aimed to determine whether diet-enhanced serum LRG1 levels promote hyperinsulinaemia by directly stimulating insulin secretion from pancreatic beta cells.

Methods: Human serum samples were obtained from individuals (both male and female) undergoing plastic surgery. Male C57BL/6 wild-type and Lrg1 whole-body knockout (Lrg1KO) mice were fed a 45% high-fat diet, with serum samples collected every 2 weeks to monitor LRG1 and insulin levels throughout diet-induced obesity. MIN6 beta cells were used to investigate the effects …

Histology-Grounded Automated Plaque Subtype Segmentation In Intravascular Optical Coherence Tomography, Paul Young, Drew Nolen, Thomas E Milner, Alexandra Gruslova, Deborah Vela, Louis Maximilian Buja, Luis A Diaz Sanmartin, Paul Rad, Marc D Feldman

Faculty, Staff and Student Publications

Background: Intravascular optical coherence tomography (IVOCT) adoption has been limited by the complexity of image interpretation. The interpretation of histologic subtypes beyond lipid, calcium, and fibrous is challenging to human readers. To assist and standardize IVOCT image analysis, we demonstrate an artificial intelligence algorithm based on a histology data set that identifies lipid pools, fibrofatty, calcified lipid, and calcified fibrous in human coronary arteries for the first time.

Methods: Sixty-seven human coronary arteries were imaged with IVOCT within 24 hours after death and then underwent histologic examination. IVOCT images were coregistered and segmented into histologic subtypes: lipid pools, fibrofatty tissue, …

Author Correction: Ctla4 Blockade Abrogates Keap1/Stk11-Related Resistance To Pd-(L)1 Inhibitors, Ferdinandos Skoulidis, Haniel A Araujo, Minh Truong Do, Yu Qian, Xin Sun, Ana Galan Cobo, John T Le, Meagan Montesion, Rachael Palmer, Nadine Jahchan, Joseph M Juan, Chengyin Min, Yi Yu, Xuewen Pan, Kathryn C Arbour, Natalie Vokes, Stephanie T Schmidt, David Molkentine, Dwight H Owen, Regan Memmott, Pradnya D Patil, Melina E Marmarelis, Mark M Awad, Joseph C Murray, Jessica A Hellyer, Justin F Gainor, Anastasios Dimou, Christine M Bestvina, Catherine A Shu, Jonathan W Riess, Collin M Blakely, Chad V Pecot, Laura Mezquita, Fabrizio Tabbó, Matthias Scheffler, Subba Digumarthy, Meghan J Mooradian, Adrian G Sacher, Sally C M Lau, Andreas N Saltos, Julia Rotow, Rocio Perez Johnson, Corinne Liu, Tyler Stewart, Sarah B Goldberg, Jonathan Killam, Zenta Walther, Kurt Schalper, Kurtis D Davies, Mark G Woodcock, Valsamo Anagnostou, Kristen A Marrone, Patrick M Forde, Biagio Ricciuti, Deepti Venkatraman, Eliezer M Van Allen, Amy L Cummings, Jonathan W Goldman, Hiram Shaish, Melanie Kier, Sharyn Katz, Charu Aggarwal, Ying Ni, Joseph T Azok, Jeremy Segal, Lauren Ritterhouse, Joel W Neal, Ludovic Lacroix, Yasir Y Elamin, Marcelo V Negrao, Xiuning Le, Vincent K Lam, Whitney E Lewis, Haley N Kemp, Brett Carter, Jack A Roth, Stephen Swisher, Richard Lee, Teng Zhou, Alissa Poteete, Yifan Kong, Tomohiro Takehara, Alvaro Guimaraes Paula, Edwin R Parra Cuentas, Carmen Behrens, Ignacio I Wistuba, Jianjun Zhang, George R Blumenschein, Carl Gay, Lauren A Byers, Don L Gibbons, Anne Tsao, J Jack Lee, Trever G Bivona, D Ross Camidge, Jhannelle E Gray, Natasha B Leighl, Benjamin Levy, Julie R Brahmer, Marina C Garassino, David R Gandara, Edward B Garon, Naiyer A Rizvi, Giorgio Vittorio Scagliotti, Jürgen Wolf, David Planchard, Benjamin Besse, Roy S Herbst, Heather A Wakelee, Nathan A Pennell, Alice T Shaw, Pasi A Jänne, David P Carbone, Matthew D Hellmann, Charles M Rudin, Lee Albacker, Helen Mann, Zhou Zhu, Zhongwu Lai, Ross Stewart, Solange Peters, Melissa L Johnson, Kwok K Wong, Alan Huang, Monte M Winslow, Michael J Rosen, Ian P Winters, Vassiliki A Papadimitrakopoulou, Tina Cascone, Philip Jewsbury, John V Heymach

Faculty, Staff and Student Publications

No abstract provided.

Predicting Chemotherapy Responsiveness In Gastric Cancer Through Machine Learning Analysis Of Genome, Immune, And Neutrophil Signatures, Shota Sasagawa, Yoshitaka Honma, Xinxin Peng, Kazuhiro Maejima, Koji Nagaoka, Yukari Kobayashi, Ayako Oosawa, Todd A Johnson, Yuki Okawa, Han Liang, Kazuhiro Kakimi, Yasuhide Yamada, Hidewaki Nakagawa

Faculty, Staff and Student Publications

Background: Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-related mortality worldwide. This study was initiated to address the variability in patient responses to combination chemotherapy, highlighting the need for personalized treatment strategies based on genomic data.

Methods: We analyzed whole-genome and RNA sequences from biopsy specimens of 65 advanced gastric cancer patients before their chemotherapy treatment. Using machine learning techniques, we developed a model with 123 omics features, such as immune signatures and copy number variations, to predict their chemotherapy outcomes.

Results: The model demonstrated a prediction accuracy of 70-80% in forecasting chemotherapy responses in …

Guidelines For Minimal Reporting Requirements, Design And Interpretation Of Experiments Involving The Use Of Eukaryotic Dual Gene Expression Reporters (Mindr), Gary Loughran, Dmitry E Andreev, Ilya M Terenin, Olivier Namy, Martin Mikl, Martina M Yordanova, C Joel Mcmanus, Andrew E Firth, John F Atkins, Christopher S Fraser, Zoya Ignatova, Shintaro Iwasaki, Joanna Kufel, Ola Larsson, Sebastian A Leidel, Alexander S Mankin, Marco Mariotti, Marvin E Tanenbaum, Ivan Topisirovic, Nora Vázquez-Laslop, Gabriela Viero, Neva Caliskan, Yiwen Chen, Patricia L Clark, Jonathan D Dinman, Philip J Farabaugh, Wendy V Gilbert, Pavel Ivanov, Jeffrey S Kieft, Oliver Mühlemann, Matthew S Sachs, Ivan N Shatsky, Nahum Sonenberg, Anna-Lena Steckelberg, Anne E Willis, Michael T Woodside, Leos Shivaya Valasek, Sergey E Dmitriev, Pavel V Baranov

Faculty, Staff and Student Publications

Dual reporters encoding two distinct proteins within the same mRNA have had a crucial role in identifying and characterizing unconventional mechanisms of eukaryotic translation. These mechanisms include initiation via internal ribosomal entry sites (IRESs), ribosomal frameshifting, stop codon readthrough and reinitiation. This design enables the expression of one reporter to be influenced by the specific mechanism under investigation, while the other reporter serves as an internal control. However, challenges arise when intervening test sequences are placed between these two reporters. Such sequences can inadvertently impact the expression or function of either reporter, independent of translation-related changes, potentially biasing the results. …

Monte Carlo Modeling Of An Experimental Benchtop L-Shell X-Ray Fluorescence Imaging/Ct System Adopting Two Silicone Drift Detectors, Neerajan Nepal, Amrit Kaphle, Sandun Jayarathna, Sang Hyun Cho

Faculty, Staff and Student Publications

L-shell x-ray fluorescence (XRF) photons induced from gold nanoparticles (GNPs) after being irradiated by an x-ray beam allow for highly sensitive XRF imaging/computed tomography (XFCT) of biological samples containing GNPs at low concentrations on the order of parts-per-million (ppm). The primary goal of this Monte Carlo (MC) study was to investigate the feasibility of upgrading an existing experimental benchtop XRF/XFCT imaging setup adopting a single silicon drift detector (SDD), developed based on the aforementioned concept (often known as L-shell XFCT), by deploying another SDD within the same setup. Specifically, an MC model of the original single SDD L-shell XFCT setup, …

Proceedings Of The National Cancer Institute Workshop On Combining Immunotherapy With Radiotherapy: Challenges And Opportunities For Clinical Translation, Zachary S Morris, Sandra Demaria, Arta M Monjazeb, Silvia C Formenti, Ralph R Weichselbaum, James Welsh, Heiko Enderling, Jonathan D Schoenfeld, Joshua D Brody, Heather M Mcgee, Michele Mondini, Michael S Kent, Kristina H Young, Lorenzo Galluzzi, Sana D Karam, Willemijn S M E Theelen, Joe Y Chang, Mai Anh Huynh, Adi Daib, Sean Pitroda, Caroline Chung, Raphael Serre, Clemens Grassberger, Jie Deng, Quaovi H Sodji, Anthony T Nguyen, Ravi B Patel, Simone Krebs, Anusha Kalbasi, Caroline Kerr, Claire Vanpouille-Box, Logan Vick, Todd A Aguilera, Irene M Ong, Fernanda Herrera, Hari Menon, Deedee Smart, Jalal Ahmed, Robyn D Gartrell, Christina L Roland, Fatemeh Fekrmandi, Binita Chakraborty, Eric H Bent, Tracy J Berg, Alan Hutson, Samir Khleif, Andrew G Sikora, Lawrence Fong

Faculty, Staff and Student Publications

Radiotherapy both promotes and antagonises tumour immune recognition. Some clinical studies show improved patient outcomes when immunotherapies are integrated with radiotherapy. Safe, greater than additive, clinical response to the combination is limited to a subset of patients, however, and how radiotherapy can best be combined with immunotherapies remains unclear. The National Cancer Institute-Immuno-Oncology Translational Network-Society for Immunotherapy of Cancer-American Association of Immunology Workshop on Combining Immunotherapy with Radiotherapy was convened to identify and prioritise opportunities and challenges for radiotherapy and immunotherapy combinations. Sessions examined the immune effects of radiation, barriers to anti-tumour immune response, previous clinical trial data, immunological and …

Outcomes Of Standard-Risk Multiple Myeloma Patients Who Undergo Upfront Autologous Hematopoietic Stem Cell Transplantation, Oren Pasvolsky, Curtis Marcoux, Zhongya Wang, Denái R Milton, Babar Pal, Mark R Tanner, Qaiser Bashir, Samer Srour, Neeraj Saini, Paul Lin, Jeremy Ramdial, Yago Nieto, Guilin Tang, Naureen Syed, Yosra Aljawai, Hans C Lee, Krina K Patel, Melody R Becnel, Christine Ye, Partow Kebriaei, Sheeba K Thomas, Robert Z Orlowski, Richard E Champlin, Elizabeth J Shpall, Muzaffar H Qazilbash

Faculty, Staff and Student Publications

Patients with multiple myeloma (MM) without high-risk cytogenetic abnormalities are classified as having standard-risk MM (SRMM), and data focusing on their outcomes after autologous hematopoietic stem cell transplantation (autoHCT) are limited. We sought to evaluate survival outcomes for patients with SRMM receiving autoHCT, and to elucidate factors that impact these outcomes. This was a single-center retrospective analysis that included consecutive MM patients who received upfront autoHCT between 2013 and 2021, had available cytogenetic information and had no high-risk chromosomal abnormalities on fluorescence in situ hybridization, defined as t(4;14), t(14;16), del(17p) or 1q21 gain or amplification. A total of 1000 SRMM …

In Pursuit Of Ki-Rads: Toward A Single, Evidence-Based Imaging Classification Of Renal Masses, Stuart G Silverman, Ivan Pedrosa, Nicola Schieda, Vitaly Margulis, Payal Kapur, Matthew S Davenport

Faculty, Staff and Student Publications

Despite the successful application of Imaging Reporting and Data Systems to improve the radiologic description and management of disease in many organs, one does not yet exist for the kidney. Instead, the radiologic approach to the kidney has focused on the Bosniak classification system, which is based on imaging characteristics for cystic renal masses, and detecting macroscopic fat within solid renal masses. Radiologically, cystic and solid renal masses are categorized and evaluated separately because of historical precedent, differences in appearance at imaging, and differences in biologic behavior. However, the World Health Organization classification of renal neoplasms does not support such …

Proteasome Augmentation Mitigates Age-Related Cognitive Decline In Mice, Danitra Parker, Kanisa Davidson, Pawel A Osmulski, Maria Gaczynska, Andrew M Pickering

Faculty, Staff and Student Publications

The aging brain experiences a significant decline in proteasome function. The proteasome is critical for many key neuronal functions including neuronal plasticity, and memory formation/retention. Treatment with proteasome inhibitors impairs these processes. Our study reveals a marked reduction in 20S and 26S proteasome activities in aged mice brains, including in the hippocampus, this is driven by reduced functionality of aged proteasome. The decline in proteasome activity is matched by a decline in 20S proteasome assembly. In contrast, 26S proteasome assembly was found to increase with age, though 26S proteasome activity was still found to decline. Our data suggests that age-related …

Medical Image Segmentation Assisted With Clinical Inputs Via Language Encoder In A Deep Learning Framework, Hengrui Zhao, Biling Wang, Deepkumar Mistry, Jing Wang, Michael Dohopolski, Daniel Yang, Weiguo Lu, Steve Jiang, Dan Nguyen

Faculty, Staff and Student Publications

Introduction: Auto-segmentation of tumor volumes and organs at risk (OARs) is a critical step in cancer radiotherapy treatment planning, where rapid, precise adjustments to treatment plans are required to match the patient anatomy. Although auto-segmentation has been clinically accepted for most OARs, auto-segmentation of tumor volumes, particularly clinical target volumes (CTVs), remains a challenge. This difficulty arises because images alone are often insufficient to capture the necessary information for accurate delineation of microscopic tumor invasion invisible on the image itself.

Methods: We propose a deep learning-based medical image segmentation framework designed to mimic the clinical process of delineating CTVs and …

Elder Mistreatment Within Stroke Family Caregiving, Carina Katigbak, Wesley R Browning, Sean Savitz, Carolyn E Z Pickering

Faculty, Staff and Student Publications

This secondary data analysis sought to identify characteristics associated with mistreatment among chronic stroke survivors who transition to dementia. We examined baseline data from a multi-time series survey study (n = 453; where caregivers of those with stroke n = 107, and those without stroke, n = 346) on caregiving experiences influencing dementia family caregivers’ abusive or neglectful behaviors. Inferential statistical analysis indicated that baseline mistreatment rates were similar across stroke and non-stroke subgroups, though this finding was not significant. Caregiver depression was significantly associated with mistreatment. Multi-morbidity, prescription medication use, and limited mobility were more common among stroke …

Difference-Makers For Collecting Sexual Orientation And Gender Identity Data In Oncology Settings, Mandi L Pratt-Chapman, Edward J Miech, Megan A Mullins, Shine Chang, Gwendolyn P Quinn, Shail Maingi, Matthew B Schabath, Charles Kamen

Faculty, Staff and Student Publications

Purpose: The purpose of this analysis was to identify key difference-making conditions that distinguish oncology institutions that collect sexual orientation and gender identity (SOGI) data across a sample of American Society of Clinical Oncology (ASCO) members.

Methods: From October to November 2020, an anonymous 54-item web-based survey was distributed to ASCO members. Coincidence analysis was used to identify difference-making conditions for the collection of SOGI data.

Results: ASCO members' responses to just three items consistently distinguished practices that reported collecting both SO and GI data (n = 25) from those who did not (n = 20): (1)."Do you ask your …

An Automated Treatment Planning Portfolio For Whole Breast Radiotherapy, Hana Baroudi, Leonard Che Fru, Deborah Schofield, Dominique L Roniger, Callistus Nguyen, Donald Hancock, Christine Chung, Beth M Beadle, Kent A Gifford, Tucker Netherton, Joshua S Niedzielski, Adam Melancon, Manickam Muruganandham, Meena Khan, Simona F Shaitelman, Sanjay Shete, Patricia Murina, Daniel Venencia, Sheeba Thengumpallil, Conny Vrieling, Joy Zhang, Melissa P Mitchell, Laurence E Court

Faculty, Staff and Student Publications

Background: Automation in radiotherapy presents a promising solution to the increasing cancer burden and workforce shortages. However, existing automated methods for breast radiotherapy lack a comprehensive, end-to-end solution that meets varying standards of care.

Purpose: This study aims to develop a complete portfolio of automated radiotherapy treatment planning for intact breasts, tailored to individual patient factors, clinical approaches, and available resources.

Methods: We developed five automated conventional treatment approaches and utilized an established RapidPlan model for volumetric arc therapy. These approaches include conventional tangents for whole breast treatment, two variants for supraclavicular nodes (SCLV) treatment with/without axillary nodes, and two …

Combining Radioembolization And Immune Checkpoint Inhibitors For The Treatment Of Hepatocellular Carcinoma: The Quest For Synergy, Christopher D Malone, Suryansh Bajaj, Aiwu He, Kabir Mody, Ryan M Hickey, Ammar Sarwar, Sunil Krishnan, Tushar C Patel, Beau B Toskich

Faculty, Staff and Student Publications

Hepatocellular carcinoma is a leading and increasing contributor to cancer-related death worldwide. Recent advancements in both liver-directed therapies in the form of yttrium-90 (90Y) radioembolization (RE) and systemic therapy in the form of immune checkpoint inhibitors (ICI) have expanded treatment options for patients with an otherwise poor prognosis. Despite these gains, ICIs and 90Y-RE each have key limitations with low objective response rates and persistent hazard of out-of-field recurrence, respectively, and overall survival remains low. However, each therapy's strength may mitigate the other's weakness, making them potentially ideal partners for combination treatment strategies. This review discusses the scientific and clinical …

Qsp Modeling Shows Pathological Synergism Between Insulin Resistance And Amyloid-Beta Exposure In Upregulating Vcam1 Expression At The Bbb Endothelium, Zengtao Wang, Vaishnavi Veerareddy, Xiaojiao Tang, Kevin J Thompson, Sunil Krishnan, Krishna R Kalari, Karunya K Kandimalla

Faculty, Staff and Student Publications

Type 2 diabetes mellitus (T2DM), characterized by insulin resistance, is closely associated with Alzheimer's disease (AD). Cerebrovascular dysfunction is manifested in both T2DM and AD, and is often considered as a pathological link between the two diseases. Insulin signaling regulates critical functions of the blood-brain barrier (BBB), and endothelial insulin resistance could lead to BBB dysfunction, aggravating AD pathology. However, insulin signaling is intrinsically dynamic and involves interactions among numerous molecular mediators. Hence, a mechanistic systems biology model is needed to understand how insulin regulates BBB physiology and the consequences of its impairment in T2DM and AD. In this study, …