Biomedical Informatics Commons^™

Prevalence And Descriptive Epidemiology Of Turner Syndrome In The United States, 2000-2017: A Report From The National Birth Defects Prevention Network, Bailey A Martin-Giacalone, Angela E Lin, Sonja A Rasmussen, Russell S Kirby, Eirini Nestoridi, Rebecca F Liberman, A J Agopian, John C Carey, Janet D Cragan, Nina Forestieri, Vinita Leedom, Aubree Boyce, Wendy N Nembhard, Monika Piccardi, Theresa Sandidge, Xiaoyi Shan, Charles J Shumate, Erin B Stallings, Roger Stevenson, Philip J Lupo

Faculty, Staff and Students Publications

The lack of United States population-based data on Turner syndrome limits assessments of prevalence and associated characteristics for this sex chromosome abnormality. Therefore, we collated 2000-2017 data from seven birth defects surveillance programs within the National Birth Defects Prevention Network. We estimated the prevalence of karyotype-confirmed Turner syndrome diagnosed within the first year of life. We also calculated the proportion of cases with commonly ascertained birth defects, assessed associations with maternal and infant characteristics using prevalence ratios (PR) with 95% confidence intervals (CI), and estimated survival probability. The prevalence of Turner syndrome of any pregnancy outcome was 3.2 per 10,000 …

Epigenetic Age Acceleration Among Survivors Of Pediatric Medulloblastoma And Primitive Neuroectodermal Tumor, Rachel D Harris, Melissa A Richard, Maria Monica J Gramatges, Kevin Wilhelm, Michael E Scheurer, Philip J Lupo, Austin L Brown

Faculty, Staff and Students Publications

Survivors of childhood central nervous system (CNS) tumors experience early-onset aging-related phenotypes. DNA methylation (DNAm) age is an emerging epigenetic biomarker of physiologic age and may be predictive of chronic health conditions in long-term survivors. This report describes the course of epigenetic age acceleration using post-diagnosis blood samples (median: 3.9 years post-diagnosis; range: 0.04–15.96) from 83 survivors of pediatric CNS tumors. Epigenetic age acceleration was detected in 72% of patients, with an average difference between chronologic and dnam age of 2.58 years (95% Ci: 1.75–3.41, p < 0.001). Time from diagnosis to sample collection correlated with the magnitude of epigenetic age acceleration.

The Ratio Of Intratumour To Stromal Infiltrating Lymphocytes Better Predicts Prognosis In Breast Cancer, Baoyi Zhang, Xiang Wang, Chao Cheng

Faculty, Staff and Students Publications

No abstract provided.

Toward A Neural Semantic Parsing System For Ehr Question Answering, Sarvesh Soni, Kirk Roberts

Faculty, Staff and Student Publications

Clinical semantic parsing (SP) is an important step toward identifying the exact information need (as a machine-understandable logical form) from a natural language query aimed at retrieving information from electronic health records (EHRs). Current approaches to clinical SP are largely based on traditional machine learning and require hand-building a lexicon. The recent advancements in neural SP show a promise for building a robust and flexible semantic parser without much human effort. Thus, in this paper, we aim to systematically assess the performance of two such neural SP models for EHR question answering (QA). We found that the performance of these …

Specific Causes Of Excess Late Mortality And Association With Modifiable Risk Factors Among Survivors Of Childhood Cancer: A Report From The Childhood Cancer Survivor Study Cohort, Stephanie B Dixon, Qi Liu, Eric J Chow, Kevin C Oeffinger, Paul C Nathan, Rebecca M Howell, Wendy M Leisenring, Matthew J Ehrhardt, Kirsten K Ness, Kevin R Krull, Ann C Mertens, Melissa M Hudson, Leslie L Robison, Yutaka Yasui, Gregory T Armstrong

Faculty, Staff and Student Publications

Background: 5-year survival after childhood cancer does not fully describe life-years lost due to childhood cancer because there are a large number of deaths occurring beyond 5-years (late mortality) related to cancer and cancer treatment. Specific causes of health-related (non-recurrence, non-external) late mortality and risk reduction through modifiable lifestyle and cardiovascular risk factors are not well described. Through using a well-characterised cohort of 5-year survivors of the most common childhood cancers, we evaluated specific health-related causes of late mortality and excess deaths compared with the general US population and identified targets to reduce future risk.

Methods: In this multi-institutional, hospital-based, …

Genetic Loci Of Beta-Aminoisobutyric Acid Are Associated With Aging-Related Mild Cognitive Impairment, Einat Granot-Hershkovitz, Brian Spitzer, Yunju Yang, Wassim Tarraf, Bing Yu, Eric Boerwinkle, Myriam Fornage, Thomas H Mosley, Charles Decarli, Bruce S Kristal, Hector M González, Tamar Sofer

Faculty, Staff and Student Publications

We studied the genetic associations of a previously developed Metabolomic Risk Score (MRS) for Mild Cognitive Impairment (MCI) and beta-aminoisobutyric acid metabolite (BAIBA)-the metabolite highlighted by results from a genome-wide association study (GWAS) of the MCI-MRS, and assessed their association with MCI in datasets of diverse race/ethnicities. We first performed a GWAS for the MCI-MRS and BAIBA, in Hispanic/Latino adults (n = 3890) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We identified ten independent genome-wide significant (p value <5 × 10-8) variants associated with MCI-MRS or BAIBA. Variants associated with the MCI-MRS are located in the Alanine-Glyoxylate Aminotransferase 2 (AGXT2 gene), which is known to be associated with BAIBA metabolism. Variants associated with BAIBA are located in the AGXT2 gene and in the SLC6A13 gene. Next, we tested the variants' association with MCI in independent datasets of n = 3178 HCHS/SOL older individuals, n = 3775 European Americans, and n = 1032 African Americans from the Atherosclerosis Risk In Communities (ARIC) study. Variants were considered associated with MCI if their p value <0.05 in the meta-analysis of the three datasets and their direction of association was consistent with expectation. Rs16899972 and rs37369 from the AGXT2 region were associated with MCI. Mediation analysis supported the mediation effect of BAIBA between the two genetic variants and MCI (p value = 0.004 for causal mediated effect). In summary, genetic variants in the AGXT2 region are associated with MCI in Hispanic/Latino, African, and European American populations in the USA, and their effect is likely mediated by changes in BAIBA levels.

Alternative Splicing Of Gsdmb Modulates Killer Lymphocyte-Triggered Pyroptosis, Qing Kong, Shiyu Xia, Xingxin Pan, Kaixiong Ye, Zhouyihan Li, Haoyan Li, Xiaoqiang Tang, Nidhi Sahni, S Stephen Yi, Xing Liu, Hao Wu, Michael B Elowitz, Judy Lieberman, Zhibin Zhang

Faculty, Staff and Student Publications

Granzyme A from killer lymphocytes cleaves gasdermin B (GSDMB) and triggers pyroptosis in targeted human tumor cells, eliciting antitumor immunity. However, GSDMB has a controversial role in pyroptosis and has been linked to both anti- and protumor functions. Here, we found that GSDMB splicing variants are functionally distinct. Cleaved N-terminal (NT) fragments of GSDMB isoforms 3 and 4 caused pyroptosis, but isoforms 1, 2, and 5 did not. The nonfunctional isoforms have a deleted or modified exon 6 and therefore lack a stable belt motif. The belt likely contributes to the insertion of oligomeric GSDMB-NTs into the membrane. Consistently, noncytotoxic …

Cvam: Cna Profile Inference Of The Spatial Transcriptome Based On The Vgae And Hmm, Jian Ma, Jingjing Guo, Zhiwei Fan, Weiling Zhao, Xiaobo Zhou

Faculty, Staff and Student Publications

Tumors are often polyclonal due to copy number alteration (CNA) events. Through the CNA profile, we can understand the tumor heterogeneity and consistency. CNA information is usually obtained through DNA sequencing. However, many existing studies have shown a positive correlation between the gene expression and gene copy number identified from DNA sequencing. With the development of spatial transcriptome technologies, it is urgent to develop new tools to identify genomic variation from the spatial transcriptome. Therefore, in this study, we developed CVAM, a tool to infer the CNA profile from spatial transcriptome data. Compared with existing tools, CVAM integrates the spatial …

The Genomic Landscape Of Familial Glioma, Dong-Joo Choi, Georgina Armstrong, Brittney Lozzi, Prashanth Vijayaraghavan, Sharon E Plon, Terence C Wong, Eric Boerwinkle, Donna M Muzny, Hsiao-Chi Chen, Richard A Gibbs, Quinn T Ostrom, Beatrice Melin, Benjamin Deneen, Melissa L Bondy, Gliogene Consortium, Genomics England Research Consortium, Matthew N Bainbridge, Christopher I Amos, Jill S Barnholtz-Sloan, Jonine L Bernstein, Elizabeth B Claus, Richard S Houlston, Dora Il'yasova, Robert B Jenkins, Christoffer Johansen, Daniel Lachance, Rose Lai, Beatrice S Melin, Ryan T Merrell, Sara H Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, J C Ambrose, P Arumugam, R Bevers, M Bleda, F Boardman-Pretty, C R Boustred, H Brittain, M A Brown, M J Caulfield, G C Chan, A Giess, J N Griffin, A Hamblin, S Henderson, T J P Hubbard, R Jackson, L J Jones, D Kasperaviciute, M Kayikci, A Kousathanas, L Lahnstein, A Lakey, S E A Leigh, I U S Leong, F J Lopez, F Maleady-Crowe, M Mcentagart, F Minneci, J Mitchell, L Moutsianas, M Mueller, N Murugaesu, A C Need, P O'Donovan, C A Odhams, C Patch, D Perez-Gil, M B Pereira, J Pullinger, T Rahim, A Rendon, T Rogers, K Savage, K Sawant, R H Scott, A Siddiq, A Sieghart, S C Smith, A Sosinsky, A Stuckey, M Tanguy, A L Taylor Tavares, E R A Thomas, S R Thompson, A Tucci, M J Welland, E Williams, K Witkowska, S M Wood, M Zarowiecki

Faculty, Staff and Student Publications

Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 (P = 0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to …

Consensus Proposal For Revised International Working Group 2023 Response Criteria For Higher-Risk Myelodysplastic Syndromes, Amer M Zeidan, Uwe Platzbecker, Jan Philipp Bewersdorf, Maximilian Stahl, Lionel Adès, Uma Borate, David Bowen, Rena Buckstein, Andrew Brunner, Hetty E Carraway, Naval Daver, Maria Díez-Campelo, Theo De Witte, Amy E Dezern, Fabio Efficace, Guillermo Garcia-Manero, Jacqueline S Garcia, Ulrich Germing, Aristoteles Giagounidis, Elizabeth A Griffiths, Robert P Hasserjian, Eva Hellström-Lindberg, Marcelo Iastrebner, Rami Komrokji, Austin G Kulasekararaj, Luca Malcovati, Yasushi Miyazaki, Olatoyosi Odenike, Valeria Santini, Guillermo Sanz, Phillip Scheinberg, Reinhard Stauder, Arjan A Van De Loosdrecht, Andrew H Wei, Mikkael A Sekeres, Pierre Fenaux

Faculty, Staff and Student Publications

Myelodysplastic syndromes/myelodysplastic neoplasms (MDS) are associated with variable clinical presentations and outcomes. The initial response criteria developed by the International Working Group (IWG) in 2000 have been used in clinical practice, clinical trials, regulatory reviews, and drug labels. Although the IWG criteria were revised in 2006 and 2018 (the latter focusing on lower-risk disease), limitations persist in their application to higher-risk MDS (HR-MDS) and their ability to fully capture the clinical benefits of novel investigational drugs or serve as valid surrogates for longer-term clinical end points (eg, overall survival). Further, issues related to the ambiguity and practicality of some criteria …

Positive Selection Of Somatically Mutated Clones Identifies Adaptive Pathways In Metabolic Liver Disease, Zixi Wang, Shijia Zhu, Yuemeng Jia, Yunguan Wang, Naoto Kubota, Naoto Fujiwara, Ruth Gordillo, Cheryl Lewis, Min Zhu, Tripti Sharma, Lin Li, Qiyu Zeng, Yu-Hsuan Lin, Meng-Hsiung Hsieh, Purva Gopal, Tao Wang, Matt Hoare, Peter Campbell, Yujin Hoshida, Hao Zhu

Faculty, Staff and Student Publications

Somatic mutations in nonmalignant tissues accumulate with age and injury, but whether these mutations are adaptive on the cellular or organismal levels is unclear. To interrogate genes in human metabolic disease, we performed lineage tracing in mice harboring somatic mosaicism subjected to nonalcoholic steatohepatitis (NASH). Proof-of-concept studies with mosaic loss of Mboat7, a membrane lipid acyltransferase, showed that increased steatosis accelerated clonal disappearance. Next, we induced pooled mosaicism in 63 known NASH genes, allowing us to trace mutant clones side by side. This in vivo tracing platform, which we coined MOSAICS, selected for mutations that ameliorate lipotoxicity, including mutant genes …

Mapping The Functional Interactions At The Tumor-Immune Checkpoint Interface, Behnaz Bozorgui, Elisabeth K Kong, Augustin Luna, Anil Korkut

Faculty, Staff and Student Publications

The interactions between tumor intrinsic processes and immune checkpoints can mediate immune evasion by cancer cells and responses to immunotherapy. It is, however, challenging to identify functional interactions due to the prohibitively complex molecular landscape of the tumor-immune interfaces. We address this challenge with a statistical analysis framework, immuno-oncology gene interaction maps (ImogiMap). ImogiMap quantifies and statistically validates tumor-immune checkpoint interactions based on their co-associations with immune-associated phenotypes. The outcome is a catalog of tumor-immune checkpoint interaction maps for diverse immune-associated phenotypes. Applications of ImogiMap recapitulate the interaction of SERPINB9 and immune checkpoints with interferon gamma (IFNγ) expression. Our analyses …

Increased Risk Of Dementia In Patients With Atopic Dermatitis: A Nationwide Population-Based Cohort Study, Yu Ri Woo, Minah Cho, Kyung Do Han, Sang Hyun Cho, Ji Hyun Lee

Faculty, Staff and Student Publications

Atopic dermatitis (AD) is a chronic inflammatory skin disorder with bimodal incidence peaks in early childhood and middle-aged and older adults. Few studies have focused on the risk of dementia in AD. The aims of this study were to analyse the incidence, and risk factors for dementia in patients with AD. This nationwide population-based retrospective cohort study enrolled 38,391 adults ≥ 40 years of age with AD and 2,643,602 controls without AD from the Korean National Health Insurance System (NHIS) database from 2009 to 2016. The cumulative incidence probability of all-cause dementia, Alzheimer's disease, or vascular dementia at 8 years …

Hica Toxin-Based Counterselection Marker For Allelic Exchange Mutations In Fusobacterium Nucleatum, Bibek Gc, Peng Zhou, Chenggang Wu

Faculty, Staff and Student Publications

The study of fusobacterial virulence factors has dramatically benefited from the creation of various genetic tools for DNA manipulation, including galK-based counterselection for in-frame deletion mutagenesis in Fusobacterium nucleatum, which was recently developed. However, this method requires a host lacking the galK gene, which is an inherent limitation. To circumvent this limitation, we explored the possibility of using the hicA gene that encodes a toxin consisting of a HicAB toxin-antitoxin module in Fusobacterium periodonticum as a new counterselective marker. Interestingly, the full-length hicA gene is not toxic in F. nucleatum, but a truncated hicA gene version lacking the first …

Overcoming Adaptive Resistance To Anti-Vegf Therapy By Targeting Cd5l, Christopher J Lafargue, Paola Amero, Kyunghee Noh, Lingegowda S Mangala, Yunfei Wen, Emine Bayraktar, Sujanitha Umamaheswaran, Elaine Stur, Santosh K Dasari, Cristina Ivan, Sunila Pradeep, Wonbeak Yoo, Chunhua Lu, Nicholas B Jennings, Vinod Vathipadiekal, Wei Hu, Anca Chelariu-Raicu, Zhiqiang Ku, Hui Deng, Wei Xiong, Hyun-Jin Choi, Min Hu, Takae Kiyama, Chai-An Mao, Rouba Ali-Fehmi, Michael J Birrer, Jinsong Liu, Ningyan Zhang, Gabriel Lopez-Berestein, Vittorio De Franciscis, Zhiqiang An, Anil K Sood

Faculty, Staff and Student Publications

Antiangiogenic treatment targeting the vascular endothelial growth factor (VEGF) pathway is a powerful tool to combat tumor growth and progression; however, drug resistance frequently emerges. We identify CD5L (CD5 antigen-like precursor) as an important gene upregulated in response to antiangiogenic therapy leading to the emergence of adaptive resistance. By using both an RNA-aptamer and a monoclonal antibody targeting CD5L, we are able to abate the pro-angiogenic effects of CD5L overexpression in both in vitro and in vivo settings. In addition, we find that increased expression of vascular CD5L in cancer patients is associated with bevacizumab resistance and worse overall survival. …

Bridging Clinic And Wildlife Care With Ai-Powered Pan-Species Computational Pathology, Khalid Abduljabbar, Simon P Castillo, Katherine Hughes, Hannah Davidson, Amy M Boddy, Lisa M Abegglen, Lucia Minoli, Selina Iussich, Elizabeth P Murchison, Trevor A Graham, Simon Spiro, Carlo C Maley, Luca Aresu, Chiara Palmieri, Yinyin Yuan

Faculty, Staff and Student Publications

Cancers occur across species. Understanding what is consistent and varies across species can provide new insights into cancer initiation and evolution, with significant implications for animal welfare and wildlife conservation. We build a pan-species cancer digital pathology atlas (panspecies.ai) and conduct a pan-species study of computational comparative pathology using a supervised convolutional neural network algorithm trained on human samples. The artificial intelligence algorithm achieves high accuracy in measuring immune response through single-cell classification for two transmissible cancers (canine transmissible venereal tumour, 0.94; Tasmanian devil facial tumour disease, 0.88). In 18 other vertebrate species (mammalia = 11, reptilia = 4, aves …

Modelling Radiation Cancer Treatment With A Death-Rate Term In Ordinary And Fractional Differential Equations, Nicole Wilson, Corina S Drapaca, Heiko Enderling, Jimmy J Caudell, Kathleen P Wilkie

Faculty, Staff and Student Publications

Fractional calculus has recently been applied to the mathematical modelling of tumour growth, but its use introduces complexities that may not be warranted. Mathematical modelling with differential equations is a standard approach to study and predict treatment outcomes for population-level and patient-specific responses. Here, we use patient data of radiation-treated tumours to discuss the benefits and limitations of introducing fractional derivatives into three standard models of tumour growth. The fractional derivative introduces a history-dependence into the growth function, which requires a continuous death-rate term for radiation treatment. This newly proposed radiation-induced death-rate term improves computational efficiency in both ordinary and …

Cdk5-Prmt1-Wdr24 Signaling Cascade Promotes Mtorc1 Signaling And Tumor Growth, Shasha Yin, Liu Liu, Lauren E Ball, Yalong Wang, Mark T Bedford, Stephen A Duncan, Haizhen Wang, Wenjian Gan

Faculty, Staff and Student Publications

The mammalian target of rapamycin complex1 (mTORC1) is a central regulator of metabolism and cell growth by sensing diverse environmental signals, including amino acids. The GATOR2 complex is a key component linking amino acid signals to mTORC1. Here, we identify protein arginine methyltransferase 1 (PRMT1) as a critical regulator of GATOR2. In response to amino acids, cyclin-dependent kinase 5 (CDK5) phosphorylates PRMT1 at S307 to promote PRMT1 translocation from nucleus to cytoplasm and lysosome, which in turn methylates WDR24, an essential component of GATOR2, to activate the mTORC1 pathway. Disruption of the CDK5-PRMT1-WDR24 axis suppresses hepatocellular carcinoma (HCC) cell proliferation …

Immune Cellular Patterns Of Distribution Affect Outcomes Of Patients With Non-Small Cell Lung Cancer, Edwin Roger Parra, Jiexin Zhang, Mei Jiang, Auriole Tamegnon, Renganayaki Krishna Pandurengan, Carmen Behrens, Luisa Solis, Cara Haymaker, John Victor Heymach, Cesar Moran, Jack J Lee, Don Gibbons, Ignacio Ivan Wistuba

Faculty, Staff and Student Publications

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns-an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular …

Bone Marrow Endosteal Stem Cells Dictate Active Osteogenesis And Aggressive Tumorigenesis, Yuki Matsushita, Jialin Liu, Angel Ka Yan Chu, Chiaki Tsutsumi-Arai, Mizuki Nagata, Yuki Arai, Wanida Ono, Kouhei Yamamoto, Thomas L Saunders, Joshua D Welch, Noriaki Ono

Faculty, Staff and Student Publications

The bone marrow contains various populations of skeletal stem cells (SSCs) in the stromal compartment, which are important regulators of bone formation. It is well-described that leptin receptor (LepR)+ perivascular stromal cells provide a major source of bone-forming osteoblasts in adult and aged bone marrow. However, the identity of SSCs in young bone marrow and how they coordinate active bone formation remains unclear. Here we show that bone marrow endosteal SSCs are defined by fibroblast growth factor receptor 3 (Fgfr3) and osteoblast-chondrocyte transitional (OCT) identities with some characteristics of bone osteoblasts and chondrocytes. These Fgfr3-creER-marked endosteal stromal cells contribute to …

Armo: Automated And Reliable Multi-Objective Model For Lymph Node Metastasis Prediction In Head And Neck Cancer, Zhiguo Zhou, Liyuan Chen, Michael Dohopolski, David Sher, Jing Wang

Faculty, Staff and Student Publications

Objective:

Accurate diagnosis of lymph node metastasis (LNM) is critical in treatment management for patients with head & neck cancer. Positron emission tomography (PET) and computed tomography (CT) are routinely used for identifying LNM status. However, for small or less fluorodeoxyglucose (FDG) avid nodes, there are always uncertainties in LNM diagnosis. We are aiming to develop a reliable prediction model is for identifying LNM.

Approach:

In this study, a new automated and reliable multi-objective learning model (ARMO) is proposed. In ARMO, a multi-objective model is introduced to obtain balanced sensitivity and specificity. Meanwhile, confidence is calibrated by introducing individual reliability, …

Machine Learning Models For The Identification Of Prognostic And Predictive Cancer Biomarkers: A Systematic Review, Qasem Al-Tashi, Maliazurina B Saad, Amgad Muneer, Rizwan Qureshi, Seyedali Mirjalili, Ajay Sheshadri, Xiuning Le, Natalie I Vokes, Jianjun Zhang, Jia Wu

Faculty, Staff and Student Publications

The identification of biomarkers plays a crucial role in personalized medicine, both in the clinical and research settings. However, the contrast between predictive and prognostic biomarkers can be challenging due to the overlap between the two. A prognostic biomarker predicts the future outcome of cancer, regardless of treatment, and a predictive biomarker predicts the effectiveness of a therapeutic intervention. Misclassifying a prognostic biomarker as predictive (or vice versa) can have serious financial and personal consequences for patients. To address this issue, various statistical and machine learning approaches have been developed. The aim of this study is to present an in-depth …

Increased Breast And Colorectal Cancer Risk In Type 2 Diabetes: Awareness Among Adults With And Without Diabetes And Information Provision On Diabetes Websites, Laura Ashley, Kathryn A Robb, Daryl B O'Connor, Rebecca Platt, Mollie Price, Olivia Robinson, Elizabeth Travis, Lorraine Lipscombe, Ramzi Ajjan, Rebecca Birch

Faculty, Staff and Student Publications

BACKGROUND: People with type 2 diabetes mellitus (T2DM) have a higher risk of developing breast and bowel cancers but are less likely to participate in cancer screening.

PURPOSE: Two interlinked studies examined public awareness of the fact that T2DM increases breast and bowel cancer risk, and provision of this information on diabetes websites.

METHODS: Study-1: phase-1 surveyed awareness of T2DM-increased cancer risk in a nationally-representative British sample aged 50-74 (N = 1,458) and compared respondents with and without T2DM (n = 125 vs. n = 1,305); phase-2 surveyed an additional exclusively T2DM sample (N = 319). Study-2: High-ranking diabetes websites …

Neoadjuvant Pembrolizumab In Localized Microsatellite Instability High/Deficient Mismatch Repair Solid Tumors, Kaysia Ludford, Won Jin Ho, Jane V Thomas, Kanwal P S Raghav, Mariela Blum Murphy, Nicole D Fleming, Michael S Lee, Brandon G Smaglo, Y Nancy You, Matthew M Tillman, Carlos Kamiya-Matsuoka, Selvi Thirumurthi, Craig Messick, Benny Johnson, Eduardo Vilar, Arvind Dasari, Sarah Shin, Alexei Hernandez, Xuan Yuan, Hongqui Yang, Wai Chin Foo, Wei Qiao, Dipen Maru, Scott Kopetz, Michael J Overman

Faculty, Staff and Student Publications

PURPOSE: Pembrolizumab significantly improves clinical outcomes in advanced/metastatic microsatellite instability high (MSI-H)/deficient mismatch repair (dMMR) solid tumors but is not well studied in the neoadjuvant space.

METHODS: This is a phase II open-label, single-center trial of localized unresectable or high-risk resectable MSI-H/dMMR tumors. Treatment is pembrolizumab 200 mg once every 3 weeks for 6 months followed by surgical resection with an option to continue therapy for 1 year followed by observation. To continue on study, patients are required to have radiographic or clinical benefit. The coprimary end points are safety and pathologic complete response. Key secondary end points are response …

Nivolumab Plus Ipilimumab Versus Extreme Regimen As First-Line Treatment For Recurrent/Metastatic Squamous Cell Carcinoma Of The Head And Neck: The Final Results Of Checkmate 651, Robert I Haddad, Kevin Harrington, Makoto Tahara, Robert L Ferris, Maura Gillison, Jerome Fayette, Amaury Daste, Piotr Koralewski, Bogdan Zurawski, Miren Taberna, Nabil F Saba, Milena Mak, Andrzej Kawecki, Gustavo Girotto, Miguel Angel Alvarez Avitia, Caroline Even, Joaquin Gabriel Reinoso Toledo, Alexander Guminski, Urs Müller-Richter, Naomi Kiyota, Mustimbo Roberts, Tariq Aziz Khan, Karen Miller-Moslin, Li Wei, Athanassios Argiris

Faculty, Staff and Student Publications

PURPOSE: CheckMate 651 (ClinicalTrials.gov identifier: NCT02741570) evaluated first-line nivolumab plus ipilimumab versus EXTREME (cetuximab plus cisplatin/carboplatin plus fluorouracil ≤ six cycles, then cetuximab maintenance) in recurrent/metastatic squamous cell carcinoma of the head and neck (R/M SCCHN).

METHODS: Patients without prior systemic therapy for R/M SCCHN were randomly assigned 1:1 to nivolumab plus ipilimumab or EXTREME. Primary end points were overall survival (OS) in the all randomly assigned and programmed death-ligand 1 combined positive score (CPS) ≥ 20 populations. Secondary end points included OS in the programmed death-ligand 1 CPS ≥ 1 population, and progression-free survival, objective response rate, and duration …

Development And Validation Of A Prediction Model For Kidney Failure In Long-Term Survivors Of Childhood Cancer, Natalie L Wu, Yan Chen, Bryan V Dieffenbach, Matthew J Ehrhardt, Sangeeta Hingorani, Rebecca M Howell, John L Jefferies, Daniel A Mulrooney, Kevin C Oeffinger, Leslie L Robison, Brent R Weil, Yan Yuan, Yutaka Yasui, Melissa M Hudson, Wendy M Leisenring, Gregory T Armstrong, Eric J Chow

Faculty, Staff and Student Publications

Purpose: Kidney failure is a rare but serious late effect following treatment for childhood cancer. We developed a model using demographic and treatment characteristics to predict individual risk of kidney failure among 5-year survivors of childhood cancer.

Methods: Five-year survivors from the Childhood Cancer Survivor Study (CCSS) without history of kidney failure (n = 25,483) were assessed for subsequent kidney failure (ie, dialysis, kidney transplantation, or kidney-related death) by age 40 years. Outcomes were identified by self-report and linkage with the Organ Procurement and Transplantation Network and the National Death Index. A sibling cohort (n = 5,045) served as a …

An Altered Extracellular Matrix-Integrin Interface Contributes To Huntington’S Disease-Associated Cns Dysfunction In Glial And Vascular Cells, Sarah J Hernandez, Ryan G Lim, Tarik Onur, Mark A Dane, Rebecca Smith, Keona Wang, Grace En-Hway Jean, Andrea Reyes-Ortiz, Kaylyn Devlin, Ricardo Miramontes, Jie Wu, Malcolm Casale, David Kilburn, Laura M Heiser, James E Korkola, David Van Vactor, Juan Botas, Katherine L Thompson-Peer, Leslie M Thompson

Faculty, Staff and Students Publications

Astrocytes and brain endothelial cells are components of the neurovascular unit that comprises the blood-brain barrier (BBB) and their dysfunction contributes to pathogenesis in Huntington's disease (HD). Defining the contribution of these cells to disease can inform cell-type-specific effects and uncover new disease-modifying therapeutic targets. These cells express integrin (ITG) adhesion receptors that anchor the cells to the extracellular matrix (ECM) to maintain the integrity of the BBB. We used HD patient-derived induced pluripotent stem cell (iPSC) modeling to study the ECM-ITG interface in astrocytes and brain microvascular endothelial cells and found ECM-ITG dysregulation in human iPSC-derived cells that may …

A Multi-Site Randomized Trial Of A Clinical Decision Support Intervention To Improve Problem List Completeness, Adam Wright, Richard Schreiber, David W Bates, Skye Aaron, Angela Ai, Raja Arul Cholan, Akshay Desai, Miguel Divo, David A Dorr, Thu-Trang Hickman, Salman Hussain, Shari Just, Brian Koh, Stuart Lipsitz, Dustin Mcevoy, Trent Rosenbloom, Elise Russo, David Yut-Chee Ting, Asli Weitkamp, Dean F Sittig

Faculty, Staff and Student Publications

OBJECTIVE: To improve problem list documentation and care quality.

MATERIALS AND METHODS: We developed algorithms to infer clinical problems a patient has that are not recorded on the coded problem list using structured data in the electronic health record (EHR) for 12 clinically significant heart, lung, and blood diseases. We also developed a clinical decision support (CDS) intervention which suggests adding missing problems to the problem list. We evaluated the intervention at 4 diverse healthcare systems using 3 different EHRs in a randomized trial using 3 predetermined outcome measures: alert acceptance, problem addition, and National Committee for Quality Assurance Healthcare …

Assessment And Prediction Of Glioblastoma Therapy Response: Challenges And Opportunities, Dan Qi, Jing Li, C Chad Quarles, Ekokobe Fonkem, Erxi Wu

Faculty, Staff and Student Publications

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is < 10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

Modeling Collective Cell Behavior In Cancer: Perspectives From An Interdisciplinary Conversation, Frederick R Adler, Alexander R A Anderson, Abhinav Bhushan, Paul Bogdan, Jose Javier Bravo-Cordero, Amy Brock, Yun Chen, Edna Cukierman, Kathleen E Delgiorno, Gerald V Denis, Meghan C Ferrall-Fairbanks, Zev Jordan Gartner, Ronald N Germain, Deborah M Gordon, Ginger Hunter, Mohit Kumar Jolly, Loukia Georgiou Karacosta, Karthikeyan Mythreye, Parag Katira, Rajan P Kulkarni, Matthew L Kutys, Arthur D Lander, Ashley M Laughney, Herbert Levine, Emil Lou, Pedro R Lowenstein, Kristyn S Masters, Dana Pe'er, Shelly R Peyton, Manu O Platt, Jeremy E Purvis, Gerald Quon, Jennifer K Richer, Nicole C Riddle, Analiz Rodriguez, Joshua C Snyder, Gregory Lee Szeto, Claire J Tomlin, Itai Yanai, Ioannis K Zervantonakis, Hannah Dueck

Faculty, Staff and Student Publications

Collective cell behavior contributes to all stages of cancer progression. Understanding how collective behavior emerges through cell-cell interactions and decision-making will advance our understanding of cancer biology and provide new therapeutic approaches. Here, we summarize an interdisciplinary discussion on multicellular behavior in cancer, draw lessons from other scientific disciplines, and identify future directions.