Digital Commons Network^™

A Machine Learning-Based Method For Automatically Identifying Novel Cells In Annotating Single-Cell Rna-Seq Data, Ziyi Li, Yizhuo Wang, Irene Ganan-Gomez, Simona Colla, Kim-Anh Do

Faculty, Staff and Student Publications

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) has been widely used to decompose complex tissues into functionally distinct cell types. The first and usually the most important step of scRNA-seq data analysis is to accurately annotate the cell labels. In recent years, many supervised annotation methods have been developed and shown to be more convenient and accurate than unsupervised cell clustering. One challenge faced by all the supervised annotation methods is the identification of the novel cell type, which is defined as the cell type that is not present in the training data, only exists in the testing data. Existing methods usually …

Quantification Of Pulmonary Artery Configuration After The Arterial Switch Operation: A Pilot Study, Thomas Martens, Gillian Claeys, Joachim De Groote, Meletios Kanakis, Martin Kostolny, Victor Tsang, Marina Hughes

Faculty, Staff and Student Publications

BACKGROUND: The arterial switch operation (ASO) is the preferred treatment for d-transposition of the great arteries (TGA). Freedom from reintervention is mainly determined by the performance of the arterial outflow tracts, with variable incidence of pulmonary artery stenosis (PAS), possibly related to aspects of surgical technique. This pilot study attempts to describe pulmonary artery (PA) configuration through several measurements using three-dimensional data from cardiac magnetic resonance (CMR) imaging and assesses whether PA configuration is associated with PAS.

METHODS: A retrospective, single-centre analysis of paediatric patients undergoing CMR after ASO. The geometry of the pulmonary arteries was compared between patients with …

Inhibition Of Colorectal Cancer Tumorigenesis By Ursolic Acid And Doxorubicin Is Mediated By Targeting The Akt Signaling Pathway And Activating The Hippo Signaling Pathway, Masashi Fujita, Mei-Ju May Chen, Doris Rieko Siwak, Shota Sasagawa, Ayako Oosawa-Tatsuguchi, Koji Arihiro, Atsushi Ono, Ryoichi Miura, Kazuhiro Maejima, Hiroshi Aikata, Masaki Ueno, Shinya Hayami, Hiroki Yamaue, Kazuaki Chayama, Ju-Seog Lee, Yiling Lu, Gordon B Mills, Han Liang, Satoshi S Nishizuka, Hidewaki Nakagawa

Faculty, Staff and Student Publications

Primary liver cancer is a heterogeneous disease in terms of its etiology, histology, and therapeutic response. Concurrent proteomic and genomic characterization of a large set of clinical liver cancer samples can help elucidate the molecular basis of heterogeneity and thus serve as a valuable resource for personalized liver cancer treatment. In this study, we perform proteomic profiling of ~300 proteins on 259 primary liver cancer tissues with reverse-phase protein arrays, mutational analysis using whole genome sequencing and transcriptional analysis with RNA-Seq. Patients are of Japanese ethnic background and mainly HBV or HCV positive, providing insight into this important liver cancer …

Proteo-Genomic Characterization Of Virus-Associated Liver Cancers Reveals Potential Subtypes And Therapeutic Targets, Masashi Fujita, Mei-Ju May Chen, Doris Rieko Siwak, Shota Sasagawa, Ayako Oosawa-Tatsuguchi, Koji Arihiro, Atsushi Ono, Ryoichi Miura, Kazuhiro Maejima, Hiroshi Aikata, Masaki Ueno, Shinya Hayami, Hiroki Yamaue, Kazuaki Chayama, Ju-Seog Lee, Yiling Lu, Gordon B Mills, Han Liang, Satoshi S Nishizuka, Hidewaki Nakagawa

Faculty, Staff and Student Publications

Primary liver cancer is a heterogeneous disease in terms of its etiology, histology, and therapeutic response. Concurrent proteomic and genomic characterization of a large set of clinical liver cancer samples can help elucidate the molecular basis of heterogeneity and thus serve as a valuable resource for personalized liver cancer treatment. In this study, we perform proteomic profiling of ~300 proteins on 259 primary liver cancer tissues with reverse-phase protein arrays, mutational analysis using whole genome sequencing and transcriptional analysis with RNA-Seq. Patients are of Japanese ethnic background and mainly HBV or HCV positive, providing insight into this important liver cancer …

Pathologic Predictors Of Response To Treatment Of Immune Checkpoint Inhibitor-Induced Kidney Injury, Ala Abudayyeh, Liye Suo, Heather Lin, Omar Mamlouk, Noha Abdel-Wahab, Amanda Tchakarov

Faculty, Staff and Student Publications

Background: Immune-related adverse events are a management challenge in patients receiving immune checkpoint inhibitors (ICIs). The most common renal immune-related adverse event, acute interstitial nephritis (AIN), is associated with patient morbidity and mortality. AIN, characterized by infiltration of renal tissue with immune cells, may be analogous to kidney transplant rejection. We evaluated clinical variables and pathologic findings to identify predictors of renal response and overall survival (OS) in patients with ICI-induced AIN. Design, setting, participants, and measurements: We reviewed the records and biopsy specimens of all 35 patients treated for ICI-induced AIN at our institution, between August 2007 and August …

Summit: An Integrative Approach For Better Transcriptomic Data Imputation Improves Causal Gene Identification, Zichen Zhang, Ye Eun Bae, Jonathan R Bradley, Lang Wu, Chong Wu

Faculty, Staff and Student Publications

Genes with moderate to low expression heritability may explain a large proportion of complex trait etiology, but such genes cannot be sufficiently captured in conventional transcriptome-wide association studies (TWASs), partly due to the relatively small available reference datasets for developing expression genetic prediction models to capture the moderate to low genetically regulated components of gene expression. Here, we introduce a method, the Summary-level Unified Method for Modeling Integrated Transcriptome (SUMMIT), to improve the expression prediction model accuracy and the power of TWAS by using a large expression quantitative trait loci (eQTL) summary-level dataset. We apply SUMMIT to the eQTL summary-level …

Lenalidomide Promotes The Development Of Tp53-Mutated Therapy-Related Myeloid Neoplasms, Adam S Sperling, Veronica A Guerra, James A Kennedy, Yuanqing Yan, Joanne I Hsu, Feng Wang, Andrew T Nguyen, Peter G Miller, Marie E Mcconkey, Vanessa A Quevedo Barrios, Ken Furudate, Linda Zhang, Rashmi Kanagal-Shamanna, Jianhua Zhang, Latasha Little, Curtis Gumbs, Naval Daver, Courtney D Dinardo, Tapan Kadia, Farhad Ravandi, Hagop Kantarjian, Guillermo Garcia-Manero, P Andrew Futreal, Benjamin L Ebert, Koichi Takahashi

Faculty, Staff and Student Publications

There is a growing body of evidence that therapy-related myeloid neoplasms (t-MNs) with driver gene mutations arise in the background of clonal hematopoiesis (CH) under the positive selective pressure of chemo- and radiation therapies. Uncovering the exposure relationships that provide selective advantage to specific CH mutations is critical to understanding the pathogenesis and etiology of t-MNs. In a systematic analysis of 416 patients with t-MN and detailed prior exposure history, we found that TP53 mutations were significantly associated with prior treatment with thalidomide analogs, specifically lenalidomide. We demonstrated experimentally that lenalidomide treatment provides a selective advantage to Trp53-mutant hematopoietic stem …

Anterior Connectivity Critical For Recovery Of Connected Speech After Stroke, Junhua Ding, Tatiana T Schnur

Faculty, Staff and Student Publications

Connected speech recovers to different degrees across people after left hemisphere stroke, but white matter predictors of differential recovery from the acute stage of stroke are unknown. We assessed changes in lexical-syntactic aspects of connected speech in a longitudinal analysis of 40 individuals (18 females) from the acute stage of left hemisphere stroke (within an average of 4 days post-stroke) to subacute (within 2 months) and chronic stages (early: 6 months, late: 1 year) while measuring the extent of acute lesions on white matter tracts to identify tracts predictive of recovery. We found that acute damage to the frontal aslant …

Association Of Mrna Vaccination With Clinical And Virologic Features Of Covid-19 Among Us Essential And Frontline Workers, The Heroes-Recover Network, Mark G Thompson, Sarang K Yoon, Allison L Naleway, Jennifer Meece, Thomas P Fabrizio, Alberto J Caban-Martinez, Jefferey L Burgess, Manjusha Gaglani, Lauren E W Olsho, Allen Bateman, Jessica Lundgren, Lauren Grant, Andrew L Phillips, Holly C Groom, Elisha Stefanski, Natasha Schaefer Solle, Katherine Ellingson, Karen Lutrick, Kayan Dunnigan, Meredith G Wesley, Kyley Guenther, Angela Hunt, Josephine Mak, Kurt T Hegmann, Jennifer L Kuntz, Adam Bissonnette, James Hollister, Spencer Rose, Tyler C Morrill, Karley Respet, Ashley L Fowlkes, Matthew S Thiese, Patrick Rivers, Meghan K Herring, Marilyn J Odean, Young M Yoo, Matthew Brunner, Edward J Bedrick, Deanna E Fleary, John T Jones, Jenna Praggastis, James Romine, Monica Dickerson, Sana M Khan, Julie Mayo Lamberte, Shawn Beitel, Richard J Webby, Harmony L Tyner

Faculty, Staff and Student Publications

IMPORTANCE: Data on the epidemiology of mild to moderately severe COVID-19 are needed to inform public health guidance.

OBJECTIVE: To evaluate associations between 2 or 3 doses of mRNA COVID-19 vaccine and attenuation of symptoms and viral RNA load across SARS-CoV-2 viral lineages.

DESIGN, SETTING, AND PARTICIPANTS: A prospective cohort study of essential and frontline workers in Arizona, Florida, Minnesota, Oregon, Texas, and Utah with COVID-19 infection confirmed by reverse transcriptase-polymerase chain reaction testing and lineage classified by whole genome sequencing of specimens self-collected weekly and at COVID-19 illness symptom onset. This analysis was conducted among 1199 participants with SARS-CoV-2 …

Scgwas: Landscape Of Trait-Cell Type Associations By Integrating Single-Cell Transcriptomics-Wide And Genome-Wide Association Studies, Peilin Jia, Ruifeng Hu, Fangfang Yan, Yulin Dai, Zhongming Zhao

Faculty, Staff and Student Publications

BACKGROUND: The rapid accumulation of single-cell RNA sequencing (scRNA-seq) data presents unique opportunities to decode the genetically mediated cell-type specificity in complex diseases. Here, we develop a new method, scGWAS, which effectively leverages scRNA-seq data to achieve two goals: (1) to infer the cell types in which the disease-associated genes manifest and (2) to construct cellular modules which imply disease-specific activation of different processes.

RESULTS: scGWAS only utilizes the average gene expression for each cell type followed by virtual search processes to construct the null distributions of module scores, making it scalable to large scRNA-seq datasets. We demonstrated scGWAS in …

Tumor Microenvironment: Barrier Or Opportunity Towards Effective Cancer Therapy, Aadhya Tiwari, Rakesh Trivedi, Shiaw-Yih Lin

Faculty, Staff and Student Publications

Tumor microenvironment (TME) is a specialized ecosystem of host components, designed by tumor cells for successful development and metastasis of tumor. With the advent of 3D culture and advanced bioinformatic methodologies, it is now possible to study TME's individual components and their interplay at higher resolution. Deeper understanding of the immune cell's diversity, stromal constituents, repertoire profiling, neoantigen prediction of TMEs has provided the opportunity to explore the spatial and temporal regulation of immune therapeutic interventions. The variation of TME composition among patients plays an important role in determining responders and non-responders towards cancer immunotherapy. Therefore, there could be a …

Federated Learning Algorithms For Generalized Mixed-Effects Model (Glmm) On Horizontally Partitioned Data From Distributed Sources, Wentao Li, Jiayi Tong, Md Monowar Anjum, Noman Mohammed, Yong Chen, Xiaoqian Jiang

Faculty, Staff and Student Publications

OBJECTIVES: This paper developed federated solutions based on two approximation algorithms to achieve federated generalized linear mixed effect models (GLMM). The paper also proposed a solution for numerical errors and singularity issues. And showed the two proposed methods can perform well in revealing the significance of parameter in distributed datasets, comparing to a centralized GLMM algorithm from R package ('lme4') as the baseline model.

METHODS: The log-likelihood function of GLMM is approximated by two numerical methods (Laplace approximation and Gaussian Hermite approximation, abbreviated as LA and GH), which supports federated decomposition of GLMM to bring computation to data. To solve …

Machine Learning On Syngeneic Mouse Tumor Profiles To Model Clinical Immunotherapy Response, Zexian Zeng, Shengqing Stan Gu, Cheryl J Wong, Lin Yang, Nofal Ouardaoui, Dian Li, Wubing Zhang, Myles Brown, X Shirley Liu

Faculty, Staff and Student Publications

Most patients with cancer are refractory to immune checkpoint blockade (ICB) therapy, and proper patient stratification remains an open question. Primary patient data suffer from high heterogeneity, low accessibility, and lack of proper controls. In contrast, syngeneic mouse tumor models enable controlled experiments with ICB treatments. Using transcriptomic and experimental variables from >700 ICB-treated/control syngeneic mouse tumors, we developed a machine learning framework to model tumor immunity and identify factors influencing ICB response. Projected on human immunotherapy trial data, we found that the model can predict clinical ICB response. We further applied the model to predicting ICB-responsive/resistant cancer types in …

Combined Trip13 And Aurora Kinase Inhibition Induces Apoptosis In Human Papillomavirus-Driven Cancers, Soma Ghosh, Tuhina Mazumdar, Wei Xu, Reid T Powell, Clifford Stephan, Li Shen, Pooja A Shah, Curtis R Pickering, Jeffery N Myers, Jing Wang, Mitchell J Frederick, Faye M Johnson

Faculty, Staff and Student Publications

PURPOSE: Human papillomavirus (HPV) causes >5% of cancers, but no therapies uniquely target HPV-driven cancers.

EXPERIMENTAL DESIGN: We tested the cytotoxic effect of 864 drugs in 16 HPV-positive and 17 HPV-negative human squamous cancer cell lines. We confirmed apoptosis in vitro and in vivo using patient-derived xenografts. Mitotic pathway components were manipulated with drugs, knockdown, and overexpression.

RESULTS: Aurora kinase inhibitors were more effective in vitro and in vivo in HPV-positive than in HPV-negative models. We hypothesized that the mechanism of sensitivity involves retinoblastoma (Rb) expression because the viral oncoprotein E7 leads to Rb protein degradation, and basal Rb protein …

Prevalence Of Polypharmacy And Associated Adverse Outcomes And Risk Factors Among Children With Asthma In The Usa: A Cross-Sectional Study, Luyu Xie, Andrew Gelfand, Caitlin C Murphy, M Sunil Mathew, Folefac Atem, George L Delclos, Sarah Messiah

Faculty, Staff and Student Publications

OBJECTIVE: to estimate the prevalence of polypharmacy, identify risk factors and examine related adverse outcomes in the US children with asthma.

DESIGN, SETTING AND PARTICIPANTS: This population-based, cross-sectional study included 1776 children with asthma from the 2011-2020 National Health and Nutrition Examination Surveys.

EXPOSURES: Polypharmacy is defined as taking ≥2 medications concurrently for ≥1 day over the past 30 days.

MAIN OUTCOMES AND MEASURES: (1) Weighted prevalence estimates of polypharmacy in children with asthma; (2) asthma attacks and emergency department (ED) visits.

RESULTS: The estimated prevalence of polypharmacy in the US children with asthma was 33.49% (95% CI 31.81% to …

Structural And Functional Diversity Of Type Iv Secretion Systems, Melissa R Cruz, Shane Cristy, Shantanu Guha, Giuseppe Buda De Cesare, Elena Evdokimova, Hiram Sanchez, Dominika Borek, Pedro Miramón, Junko Yano, Paul L Fidel, Alexei Savchenko, David R Andes, Peter J Stogios, Michael C Lorenz, Danielle A Garsin

Faculty, Staff and Student Publications

Fungal pathogens are a continuing challenge due to few effective antifungals and a rise in resistance. In previous work, we described the inhibition of Candida albicans virulence following exposure to the 68 amino acid bacteriocin, EntV, secreted by Enterococcus faecalis. Here, to optimize EntV as a potential therapeutic and better understand its antifungal features, an X-ray structure is obtained. The structure consists of six alpha helices enclosing a seventh 16 amino acid helix (α7). The individual helices are tested for antifungal activity using in vitro and nematode infection assays. Interestingly, α7 retains antifungal, but not antibacterial activity and is also …

Deep Learning Models For Automated Assessment Of Breast Density Using Multiple Mammographic Image Types, Bastien Rigaud, Olena O Weaver, Jennifer B Dennison, Muhammad Awais, Brian M Anderson, Ting-Yu D Chiang, Wei T Yang, Jessica W T Leung, Samir M Hanash, Kristy K Brock

Faculty, Staff and Student Publications

Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investigate pre-trained EfficientNetB0 deep learning (DL) models for automated assessment of breast density using multiple mammographic types with and without clinical information to improve reliability and versatility of reporting. 120,000 for-processing and for-presentation full-field digital mammograms (FFDM), digital breast tomosynthesis (DBT), and synthesized 2D images from 5032 women were retrospectively analyzed. …

2022 Practice Recommendation Updates From The World Consensus Conference On Bia-Alcl, Fabio Santanelli Di Pompeo, Mark W Clemens, Michael Atlan, Giovanni Botti, Peter G Cordeiro, Daphne De Jong, Arianna Di Napoli, Dennis Hammond, Cara L Haymaker, Steven M Horwitz, Kelly Hunt, Peter Lennox, Patrick Mallucci, Roberto N Miranda, Alexandre M Munhoz, Eric Swanson, Suzanne D Turner, Guido Firmani, Michail Sorotos

Faculty, Staff and Student Publications

BACKGROUND: Laboratory and clinical research on breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is rapidly evolving. Changes in standard of care and insights into best practice were recently presented at the 3rd World Consensus Conference on BIA-ALCL.

OBJECTIVES: The authors sought to provide practice recommendations from a consensus of experts, supplemented with a literature review regarding epidemiology, etiology, pathogenesis, diagnosis, treatment, socio-psychological aspects, and international authority guidance.

METHODS: A literature search of all manuscripts between 1997 and August 2021 for the above areas of BIA-ALCL was conducted with the PubMed database. Manuscripts in different languages, on non-human subjects, and/or discussing …

Whole Genome Sequence Analysis Of Blood Lipid Levels In >66,000 Individuals, Margaret Sunitha Selvaraj, Xihao Li, Zilin Li, Akhil Pampana, David Y Zhang, Joseph Park, Stella Aslibekyan, Joshua C Bis, Jennifer A Brody, Brian E Cade, Lee-Ming Chuang, Ren-Hua Chung, Joanne E Curran, Lisa De Las Fuentes, Paul S De Vries, Ravindranath Duggirala, Barry I Freedman, Mariaelisa Graff, Xiuqing Guo, Nancy Heard-Costa, Bertha Hidalgo, Chii-Min Hwu, Marguerite R Irvin, Tanika N Kelly, Brian G Kral, Leslie Lange, Xiaohui Li, Martin Lisa, Steven A Lubitz, Ani W Manichaikul, Preuss Michael, May E Montasser, Alanna C Morrison, Take Naseri, Jeffrey R O'Connell, Nicholette D Palmer, Patricia A Peyser, Muagututia S Reupena, Jennifer A Smith, Xiao Sun, Kent D Taylor, Russell P Tracy, Michael Y Tsai, Zhe Wang, Yuxuan Wang, Wei Bao, John T Wilkins, Lisa R Yanek, Wei Zhao, Donna K Arnett, John Blangero, Eric Boerwinkle, Donald W Bowden, Yii-Der Ida Chen, Adolfo Correa, L Adrienne Cupples, Susan K Dutcher, Patrick T Ellinor, Myriam Fornage, Stacey Gabriel, Soren Germer, Richard Gibbs, Jiang He, Robert C Kaplan, Sharon L R Kardia, Ryan Kim, Charles Kooperberg, Ruth J F Loos, Karine A Viaud-Martinez, Rasika A Mathias, Stephen T Mcgarvey, Braxton D Mitchell, Deborah Nickerson, Kari E North, Bruce M Psaty, Susan Redline, Alexander P Reiner, Ramachandran S Vasan, Stephen S Rich, Cristen Willer, Jerome I Rotter, Daniel J Rader, Xihong Lin, Gina M Peloso, Pradeep Natarajan

Faculty, Staff and Student Publications

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid …

Evolution And Modulation Of Antigen-Specific T Cell Responses In Melanoma Patients, Jani Huuhtanen, Liang Chen, Emmi Jokinen, Henna Kasanen, Tapio Lönnberg, Anna Kreutzman, Katriina Peltola, Micaela Hernberg, Chunlin Wang, Cassian Yee, Harri Lähdesmäki, Mark M Davis, Satu Mustjoki

Faculty, Staff and Student Publications

Analyzing antigen-specific T cell responses at scale has been challenging. Here, we analyze three types of T cell receptor (TCR) repertoire data (antigen-specific TCRs, TCR-repertoire, and single-cell RNA + TCRαβ-sequencing data) from 515 patients with primary or metastatic melanoma and compare it to 783 healthy controls. Although melanoma-associated antigen (MAA) -specific TCRs are restricted to individuals, they share sequence similarities that allow us to build classifiers for predicting anti-MAA T cells. The frequency of anti-MAA T cells distinguishes melanoma patients from healthy and predicts metastatic recurrence from primary melanoma. Anti-MAA T cells have stem-like properties and frequent interactions with regulatory …

Cue-Induced Cocaine Craving Enhances Psychosocial Stress And Vice Versa In Chronic Cocaine Users, Ann-Kathrin Kexel, Bruno Kluwe-Schiavon, Markus R Baumgartner, Etna J E Engeli, Monika Visentini, Clemens Kirschbaum, Erich Seifritz, Beate Ditzen, Leila M Soravia, Boris B Quednow

Faculty, Staff and Student Publications

Stress and craving, it has been found, contribute to the development and maintenance of and relapse in cocaine use disorder. Chronic cocaine users (CU), previous research has shown, display altered physiological responses to psychosocial stress and increased vegetative responding to substance-related cues. However, how psychosocial stress and cue-induced craving interact in relation to the CU's physiological responses remains largely unknown. We thus investigated the interaction between acute psychosocial stress and cocaine-cue-related reactivity in 47 CU and 38 controls. In a crossed and balanced design, the participants were randomly exposed to a video-based cocaine-cue paradigm and the Trier Social Stress Test …

Tntdetectai: A Deep Learning Model For Automated Detection And Counting Of Tunneling Nanotubes In Microscopy Images, Yasin Ceran, Hamza Ergüder, Katherine Ladner, Sophie Korenfeld, Karina Deniz, Sanyukta Padmanabhan, Phillip Wong, Murat Baday, Thomas Pengo, Emil Lou, Chirag B Patel

Faculty, Staff and Student Publications

BACKGROUND: Tunneling nanotubes (TNTs) are cellular structures connecting cell membranes and mediating intercellular communication. TNTs are manually identified and counted by a trained investigator; however, this process is time-intensive. We therefore sought to develop an automated approach for quantitative analysis of TNTs.

METHODS: We used a convolutional neural network (U-Net) deep learning model to segment phase contrast microscopy images of both cancer and non-cancer cells. Our method was composed of preprocessing and model development. We developed a new preprocessing method to label TNTs on a pixel-wise basis. Two sequential models were employed to detect TNTs. First, we identified the regions …

Metarnn: Differentiating Rare Pathogenic And Rare Benign Missense Snvs And Indels Using Deep Learning, Chang Li, Degui Zhi, Kai Wang, Xiaoming Liu

Faculty, Staff and Student Publications

Multiple computational approaches have been developed to improve our understanding of genetic variants. However, their ability to identify rare pathogenic variants from rare benign ones is still lacking. Using context annotations and deep learning methods, we present pathogenicity prediction models, MetaRNN and MetaRNN-indel, to help identify and prioritize rare nonsynonymous single nucleotide variants (nsSNVs) and non-frameshift insertion/deletions (nfINDELs). We use independent test sets to demonstrate that these new models outperform state-of-the-art competitors and achieve a more interpretable score distribution. Importantly, prediction scores from both models are comparable, enabling easy adoption of integrated genotype-phenotype association analysis methods. All pre-computed nsSNV scores …

Clinical Decision Support Malfunctions Related To Medication Routes: A Case Series, Adam Wright, Scott Nelson, David Rubins, Richard Schreiber, Dean F Sittig

Faculty, Staff and Student Publications

OBJECTIVE: To identify common medication route-related causes of clinical decision support (CDS) malfunctions and best practices for avoiding them.

MATERIALS AND METHODS: Case series of medication route-related CDS malfunctions from diverse healthcare provider organizations.

RESULTS: Nine cases were identified and described, including both false-positive and false-negative alert scenarios. A common cause was the inclusion of nonsystemically available medication routes in value sets (eg, eye drops, ear drops, or topical preparations) when only systemically available routes were appropriate.

DISCUSSION: These value set errors are common, occur across healthcare provider organizations and electronic health record (EHR) systems, affect many different types of …

Lineage-Coupled Clonal Capture Identifies Clonal Evolution Mechanisms And Vulnerabilities Of Brafv600e Inhibition Resistance In Melanoma, Ze-Yan Zhang, Yingwen Ding, Ravesanker Ezhilarasan, Tenzin Lhakhang, Qianghu Wang, Jie Yang, Aram S Modrek, Hua Zhang, Aristotelis Tsirigos, Andrew Futreal, Giulio F Draetta, Roel G W Verhaak, Erik P Sulman

Faculty, Staff and Student Publications

Targeted cancer therapies have revolutionized treatment but their efficacies are limited by the development of resistance driven by clonal evolution within tumors. We developed "CAPTURE", a single-cell barcoding approach to comprehensively trace clonal dynamics and capture live lineage-coupled resistant cells for in-depth multi-omics analysis and functional exploration. We demonstrate that heterogeneous clones, either preexisting or emerging from drug-tolerant persister cells, dominated resistance to vemurafenib in BRAF

Lineage-Coupled Clonal Capture Identifies Clonal Evolution Mechanisms And Vulnerabilities Of Braf V600e Inhibition Resistance In Melanoma, Ze-Yan Zhang, Yingwen Ding, Ravesanker Ezhilarasan, Tenzin Lhakhang, Qianghu Wang, Jie Yang, Aram S Modrek, Hua Zhang, Aristotelis Tsirigos, Andrew Futreal, Giulio F Draetta, Roel G W Verhaak, Erik P Sulman

Faculty, Staff and Student Publications

Targeted cancer therapies have revolutionized treatment but their efficacies are limited by the development of resistance driven by clonal evolution within tumors. We developed "CAPTURE", a single-cell barcoding approach to comprehensively trace clonal dynamics and capture live lineage-coupled resistant cells for in-depth multi-omics analysis and functional exploration. We demonstrate that heterogeneous clones, either preexisting or emerging from drug-tolerant persister cells, dominated resistance to vemurafenib in BRAFV600E melanoma. Further integrative studies uncovered diverse resistance mechanisms. This includes a previously unrecognized and clinically relevant mechanism, chromosome 18q21 gain, which leads to vulnerability of the cells to BCL2 inhibitor. We also identified targetable …

Feasibility Of A Novel Non-Invasive Swab Technique For Serial Whole-Exome Sequencing Of Cervical Tumors During Chemoradiation Therapy, Julianna K Bronk, Chiraag Kapadia, Xiaogang Wu, Bhavana V Chapman, Rui Wang, Tatiana V Karpinets, Xingzhi Song, Andrew M Futreal, Jianhua Zhang, Ann H Klopp, Lauren E Colbert

Faculty, Staff and Student Publications

BACKGROUND: Clinically relevant genetic predictors of radiation response for cervical cancer are understudied due to the morbidity of repeat invasive biopsies required to obtain genetic material. Thus, we aimed to demonstrate the feasibility of a novel noninvasive cervical swab technique to (1) collect tumor DNA with adequate throughput to (2) perform whole-exome sequencing (WES) at serial time points over the course of chemoradiation therapy (CRT).

METHODS: Cervical cancer tumor samples from patients undergoing chemoradiation were collected at baseline, at week 1, week 3, and at the completion of CRT (week 5) using a noninvasive swab-based biopsy technique. Swab samples were …

Complement Component C4 Structural Variation And Quantitative Traits Contribute To Sex-Biased Vulnerability In Systemic Sclerosis, Martin Kerick, Marialbert Acosta-Herrera, Carmen Pilar Simeón-Aznar, José Luis Callejas, Shervin Assassi, Susanna M Proudman, Mandana Nikpour, Nicolas Hunzelmann, Gianluca Moroncini, Jeska K De Vries-Bouwstra, Gisela Orozco, Anne Barton, Ariane L Herrick, Chikashi Terao, Yannick Allanore, Carmen Fonseca, Marta Eugenia Alarcón-Riquelme, Timothy R D J Radstake, Lorenzo Beretta, Christopher P Denton, Maureen D Mayes, Javier Martin

Faculty, Staff and Student Publications

Copy number (CN) polymorphisms of complement C4 play distinct roles in many conditions, including immune-mediated diseases. We investigated the association of C4 CN with systemic sclerosis (SSc) risk. Imputed total C4, C4A, C4B, and HERV-K CN were analyzed in 26,633 individuals and validated in an independent cohort. Our results showed that higher C4 CN confers protection to SSc, and deviations from CN parity of C4A and C4B augmented risk. The protection contributed per copy of C4A and C4B differed by sex. Stronger protection was afforded by C4A in men and by C4B in women. C4 CN correlated well with its …

Single-Cell Sequencing Reveals Trajectory Of Tumor-Infiltrating Lymphocyte States In Pancreatic Cancer, Aislyn Schalck, Donastas Sakellariou-Thompson, Marie-Andrée Forget, Emi Sei, Tara G Hughes, Alexandre Reuben, Shanshan Bai, Min Hu, Tapsi Kumar, Mark W Hurd, Matthew H G Katz, Ching-Wei D Tzeng, Shubham Pant, Milind Javle, David R Fogelman, Anirban Maitra, Cara L Haymaker, Michael P Kim, Nicholas E Navin, Chantale Bernatchez

Faculty, Staff and Student Publications

Pancreatic ductal adenocarcinoma (PDAC) has few effective treatments. Immunotherapy, an attractive alternative strategy, remains challenging with the lack of knowledge on the tumor-infiltrating lymphocyte (TIL) landscape in PDAC. To generate a reference of T-cell subpopulations, we profiled 80,000 T cells from 57 PDAC samples, 22 uninvolved/normal samples, and cultured TIL using single-cell transcriptomic and T-cell receptor analysis. These data revealed 20 cell states and heterogeneous distributions of TIL populations. The CD8+ TIL contained a putative transitional GZMK+ population based on T-cell receptor clonotype sharing, and cell-state trajectory analysis showed similarity to a GZMB+PRF1+ cytotoxic and a CXCL13+ dysfunctional population. Statistical …

Single-Cell Transcriptomic Profiling Reveals The Tumor Heterogeneity Of Small-Cell Lung Cancer, Yanhua Tian, Qingqing Li, Zhenlin Yang, Shu Zhang, Jiachen Xu, Zhijie Wang, Hua Bai, Jianchun Duan, Bo Zheng, Wen Li, Yueli Cui, Xin Wang, Rui Wan, Kailun Fei, Jia Zhong, Shugeng Gao, Jie He, Carl M Gay, Jianjun Zhang, Jie Wang, Fuchou Tang

Faculty, Staff and Student Publications

Small-cell lung cancer (SCLC) is the most aggressive and lethal subtype of lung cancer, for which, better understandings of its biology are urgently needed. Single-cell sequencing technologies provide an opportunity to profile individual cells within the tumor microenvironment (TME) and investigate their roles in tumorigenic processes. Here, we performed high-precision single-cell transcriptomic analysis of ~5000 individual cells from primary tumors (PTs) and matched normal adjacent tissues (NATs) from 11 SCLC patients, including one patient with both PT and relapsed tumor (RT). The comparison revealed an immunosuppressive landscape of human SCLC. Malignant cells in SCLC tumors exhibited diverse states mainly related …