Biomedical Informatics Commons^™

The Nfib/Carm1 Partnership Is A Driver In Preclinical Models Of Small Cell Lung Cancer, Guozhen Gao, Simone Hausmann, Natasha M Flores, Ana Morales Benitez, Jianjun Shen, Xiaojie Yang, Maria D Person, Sitaram Gayatri, Donghang Cheng, Yue Lu, Bin Liu, Pawel K Mazur, Mark T Bedford

Faculty, Staff and Student Publications

The coactivator associated arginine methyltransferase (CARM1) promotes transcription, as its name implies. It does so by modifying histones and chromatin bound proteins. We identified nuclear factor I B (NFIB) as a CARM1 substrate and show that this transcription factor utilizes CARM1 as a coactivator. Biochemical studies reveal that tripartite motif 29 (TRIM29) is an effector molecule for methylated NFIB. Importantly, NFIB harbors both oncogenic and metastatic activities, and is often overexpressed in small cell lung cancer (SCLC). Here, we explore the possibility that CARM1 methylation of NFIB is important for its transforming activity. Using a SCLC mouse model, we show …

Mixcan: A Framework For Cell-Type-Aware Transcriptome-Wide Association Studies With An Application To Breast Cancer, Xiaoyu Song, Jiayi Ji, Joseph H Rothstein, Stacey E Alexeeff, Lori C Sakoda, Adriana Sistig, Ninah Achacoso, Eric Jorgenson, Alice S Whittemore, Robert J Klein, Laurel A Habel, Pei Wang, Weiva Sieh

Faculty, Staff and Student Publications

Human bulk tissue samples comprise multiple cell types with diverse roles in disease etiology. Conventional transcriptome-wide association study approaches predict genetically regulated gene expression at the tissue level, without considering cell-type heterogeneity, and test associations of predicted tissue-level expression with disease. Here we develop MiXcan, a cell-type-aware transcriptome-wide association study approach that predicts cell-type-level expression, identifies disease-associated genes via combination of cell-type-level association signals for multiple cell types, and provides insight into the disease-critical cell type. As a proof of concept, we conducted cell-type-aware analyses of breast cancer in 58,648 women and identified 12 transcriptome-wide significant genes using MiXcan compared …

Epigenomic Charting And Functional Annotation Of Risk Loci In Renal Cell Carcinomaepigenomic Charting And Functional Annotation Of Risk Loci In Renal Cell Carcinoma, Amin H Nassar, Sarah Abou Alaiwi, Sylvan C Baca, Elio Adib, Rosario I Corona, Ji-Heui Seo, Marcos A S Fonseca, Sandor Spisak, Talal El Zarif, Viktoria Tisza, David A Braun, Heng Du, Monica He, Abdallah Flaifel, Michel Alchoueiry, Thomas Denize, Sayed G Matar, Andres Acosta, Sachet Shukla, Yue Hou, John Steinharter, Gabrielle Bouchard, Jacob E Berchuck, Edward O'Connor, Connor Bell, Pier Vitale Nuzzo, Gwo-Shu Mary Lee, Sabina Signoretti, Michelle S Hirsch, Mark Pomerantz, Elizabeth Henske, Alexander Gusev, Kate Lawrenson, Toni K Choueiri, David J Kwiatkowski, Matthew L Freedman

Faculty, Staff and Student Publications

While the mutational and transcriptional landscapes of renal cell carcinoma (RCC) are well-known, the epigenome is poorly understood. We characterize the epigenome of clear cell (ccRCC), papillary (pRCC), and chromophobe RCC (chRCC) by using ChIP-seq, ATAC-Seq, RNA-seq, and SNP arrays. We integrate 153 individual data sets from 42 patients and nominate 50 histology-specific master transcription factors (MTF) to define RCC histologic subtypes, including EPAS1 and ETS-1 in ccRCC, HNF1B in pRCC, and FOXI1 in chRCC. We confirm histology-specific MTFs via immunohistochemistry including a ccRCC-specific TF, BHLHE41. FOXI1 overexpression with knock-down of EPAS1 in the 786-O ccRCC cell line induces transcriptional …

Synthesize Heterogeneous Biological Knowledge Via Representation Learning For Alzheimer’S Disease Drug Repurposing, Kang-Lin Hsieh, German Plascencia-Villa, Ko-Hong Lin, George Perry, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Developing drugs for treating Alzheimer's disease has been extremely challenging and costly due to limited knowledge of underlying mechanisms and therapeutic targets. To address the challenge in AD drug development, we developed a multi-task deep learning pipeline that learns biological interactions and AD risk genes, then utilizes multi-level evidence on drug efficacy to identify repurposable drug candidates. Using the embedding derived from the model, we ranked drug candidates based on evidence from post-treatment transcriptomic patterns, efficacy in preclinical models, population-based treatment effects, and clinical trials. We mechanistically validated the top-ranked candidates in neuronal cells, identifying drug combinations with efficacy in …

Outcomes Of Surgical Treatment For Extradural Benign Primary Spinal Tumors In Patients Younger Than 25 Years: An Ambispective International Multicenter Study, Alexander C Disch, Stefano Boriani, Aron Lazary, Laurence D Rhines, Alessandro Luzzati, Ziya L Gokaslan, Charles G Fisher, Michael G Fehlings, Michelle J Clarke, Dean Chou, Nicole M Germscheid, Klaus-Dieter Schaser, Jeremy J Reynolds, The Ao Spine Knowledge Forum Tumor

Faculty, Staff and Student Publications

Extradural primary spinal tumors were retrospectively analyzed from a prospective database of 1495 cases. All subjects with benign primary tumors under the age of 25 years, who were enrolled between 1990 and 2012 (Median FU was 2.4 years), were identified. Patient- and case-related characteristics were collected and statistically analyzed. Results: 161 patients (66f;95m; age 17.0 ± 4.7 years at time of diagnosis) were identified. The most common tumors were osteoblastomas n = 53 (32.9%), osteoid osteomas n = 45 (28.0%), and aneurysmal bone cysts n = 32 (19.9%). The tumor grade, according to the Enneking Classification S1/S2/S3, was 14/73/74 (8.7/45.3/46.0%), …

Acquired Genomic Alterations On First-Line Chemotherapy With Cetuximab In Advanced Colorectal Cancer: Circulating Tumor Dna Analysis Of The Calgb/Swog-80405 Trial (Alliance), Kanwal Raghav, Fang-Shu Ou, Alan P Venook, Federico Innocenti, Ryan Sun, Heinz-Josef Lenz, Scott Kopetz

Faculty, Staff and Student Publications

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.Acquired genomic alterations (Acq-GAs), specifically RAS, BRAF, and EGFR-ectodomain mutations and ERBB2 and MET amplifications, are recognized as major mechanisms of resistance to later-line anti-EGFR-antibody therapy in metastatic colorectal cancer (mCRC). However, data regarding …

Resistance Mechanisms To Anti–Epidermal Growth Factor Receptor Therapy In Ras/Raf Wild-Type Colorectal Cancer Vary By Regimen And Line Of Therapy, Christine M Parseghian, Ryan Sun, Melanie Woods, Stefania Napolitano, Hey Min Lee, Jumanah Alshenaifi, Jason Willis, Shakayla Nunez, Kanwal P Raghav, Van K Morris, John P Shen, Madhulika Eluri, Alexey Sorokin, Preeti Kanikarla, Eduardo Vilar, Marko Rehn, Agnes Ang, Teresa Troiani, Scott Kopetz

Faculty, Staff and Student Publications

Purpose: Acquired resistance to anti-epidermal growth factor receptor (EGFR) inhibitor (EGFRi) therapy in colorectal cancer (CRC) has previously been explained by the model of acquiring new mutations in KRAS/NRAS/EGFR, among other MAPK-pathway members. However, this was primarily on the basis of single-agent EGFRi trials and little is known about the resistance mechanisms of EGFRi combined with effective cytotoxic chemotherapy in previously untreated patients.

Methods: We analyzed paired plasma samples from patients with RAS/BRAF/EGFR wild-type metastatic CRC enrolled in three large randomized trials evaluating EGFRi in the first line in combination with chemotherapy and as a single agent in third …

Prediction Of Pathologic Complete Response To Neoadjuvant Systemic Therapy In Triple Negative Breast Cancer Using Deep Learning On Multiparametric Mri, Zijian Zhou, Beatriz E Adrada, Rosalind P Candelaria, Nabil A Elshafeey, Medine Boge, Rania M Mohamed, Sanaz Pashapoor, Jia Sun, Zhan Xu, Bikash Panthi, Jong Bum Son, Mary S Guirguis, Miral M Patel, Gary J Whitman, Tanya W Moseley, Marion E Scoggins, Jason B White, Jennifer K Litton, Vicente Valero, Kelly K Hunt, Debu Tripathy, Wei Yang, Peng Wei, Clinton Yam, Mark D Pagel, Gaiane M Rauch, Jingfei Ma

Faculty, Staff and Student Publications

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic therapy (NAST) followed by surgery are currently standard of care for TNBC with 50-60% of patients achieving pathologic complete response (pCR). We investigated ability of deep learning (DL) on dynamic contrast enhanced (DCE) MRI and diffusion weighted imaging acquired early during NAST to predict TNBC patients' pCR status in the breast. During the development phase using the images of 130 TNBC patients, the DL model achieved areas under the receiver operating characteristic curves (AUCs) of 0.97 ± 0.04 and 0.82 ± 0.10 for the training and the …

Svhound: Detection Of Regions That Harbor Yet Undetected Structural Variation, Luis F Paulin, Muthuswamy Raveendran, R Alan Harris, Jeffrey Rogers, Arndt Von Haeseler, Fritz J Sedlazeck

Faculty, Staff and Students Publications

BACKGROUND: Recent population studies are ever growing in number of samples to investigate the diversity of a population or species. These studies reveal new polymorphism that lead to important insights into the mechanisms of evolution, but are also important for the interpretation of these variations. Nevertheless, while the full catalog of variations across entire species remains unknown, we can predict which regions harbor additional not yet detected variations and investigate their properties, thereby enhancing the analysis for potentially missed variants.

RESULTS: To achieve this we developed SVhound ( https://github.com/lfpaulin/SVhound ), which based on a population level SVs dataset can predict …

Hypoxia Truncates And Constitutively Activates The Key Cholesterol Synthesis Enzyme Squalene Monooxygenase, Hudson W Coates, Isabelle M Capell-Hattam, Ellen M Olzomer, Ximing Du, Rhonda Farrell, Hongyuan Yang, Frances L Byrne, Andrew J Brown

Faculty, Staff and Student Publications

Cholesterol synthesis is both energy- and oxygen-intensive, yet relatively little is known of the regulatory effects of hypoxia on pathway enzymes. We previously showed that the rate-limiting and first oxygen-dependent enzyme of the committed cholesterol synthesis pathway, squalene monooxygenase (SM), can undergo partial proteasomal degradation that renders it constitutively active. Here, we show hypoxia is a physiological trigger for this truncation, which occurs through a two-part mechanism: (1) increased targeting of SM to the proteasome via stabilization of the E3 ubiquitin ligase MARCHF6 and (2) accumulation of the SM substrate, squalene, which impedes the complete degradation of SM and liberates …

Integrated Mrna Sequence Optimization Using Deep Learning, Haoran Gong, Jianguo Wen, Ruihan Luo, Yuzhou Feng, Jingjing Guo, Hongguang Fu, Xiaobo Zhou

Faculty, Staff and Student Publications

The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a critical challenge. A new algorithm, iDRO (integrated deep-learning-based mRNA optimization), is developed to optimize multiple components of mRNA sequences based on given amino acid sequences of target protein. Considering the biological constraints, we divided iDRO into two steps: open reading frame (ORF) optimization and 5' untranslated region (UTR) and 3'UTR generation. In ORF optimization, BiLSTM-CRF (bidirectional long-short-term memory with conditional random …

Ontologies Applied In Clinical Decision Support System Rules: Systematic Review, Xia Jing, Hua Min, Yang Gong, Paul Biondich, David Robinson, Timothy Law, Christian Nohr, Arild Faxvaag, Lior Rennert, Nina Hubig, Ronald Gimbel

Faculty, Staff and Student Publications

BACKGROUND: Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused.

OBJECTIVE: Ontologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers …

Impact Of Adherence To Procalcitonin Antibiotic Prescribing Guideline Recommendations For Low Procalcitonin Levels On Antibiotic Use, Brian E Malley, Jonathan G Yabes, Elizabeth Gimbel, Chung-Chou H Chang, Donald M Yealy, Michael J Fine, Derek C Angus, David T Huang, Proact Investigators

Faculty, Staff and Student Publications

BACKGROUND: The Procalcitonin Antibiotic Consensus Trial (ProACT) found provision of a procalcitonin antibiotic prescribing guideline to hospital-based clinicians did not reduce antibiotic use. Possible reasons include clinician reluctance to follow the guideline, with an observed 64.8% adherence rate. In this study we sought to determine the threshold adherence rate for reduction in antibiotic use, and to explore opportunities to increase adherence.

METHODS: This study is a retrospective analysis of ProACT data. ProACT randomized 1656 patients presenting to 14 U.S. hospitals with suspected lower respiratory tract infection to usual care or provision of procalcitonin assay results and an antibiotic prescribing guideline …

Control Of Craniofacial Development By The Collagen Receptor, Discoidin Domain Receptor 2, Fatma F Mohamed, Chunxi Ge, Shawn A Hallett, Alec C Bancroft, Randy T Cowling, Noriaki Ono, Abdul-Aziz Binrayes, Barry Greenberg, Benjamin Levi, Vesa M Kaartinen, Renny T Franceschi

Faculty, Staff and Student Publications

Development of the craniofacial skeleton requires interactions between progenitor cells and the collagen-rich extracellular matrix (ECM). The mediators of these interactions are not well-defined. Mutations in the discoidin domain receptor 2 gene (DDR2), which encodes a non-integrin collagen receptor, are associated with human craniofacial abnormalities, such as midface hypoplasia and open fontanels. However, the exact role of this gene in craniofacial morphogenesis is not known. As will be shown, Ddr2-deficient mice exhibit defects in craniofacial bones including impaired calvarial growth and frontal suture formation, cranial base hypoplasia due to aberrant chondrogenesis and delayed ossification at growth plate …

Circadian Rhythms As Modulators Of Brain Health During Development And Throughout Aging, Rachel Van Drunen, Kristin Eckel-Mahan

Faculty, Staff and Student Publications

The circadian clock plays a prominent role in neurons during development and throughout aging. This review covers topics pertinent to the role of 24-h rhythms in neuronal development and function, and their tendency to decline with aging. Pharmacological or behavioral modification that augment the function of our internal clock may be central to decline of cognitive disease and to future chronotherapy for aging-related diseases of the central nervous system.

Long-Term Bidirectional Association Between Asthma And Attention Deficit Hyperactivity Disorder: A Big Data Cohort Study, Hye Jin Park, Young Hyeon Kim, Da Ye Na, Seong Won Jeong, Min Gyu Lee, Jong-Hwan Lee, Yun Na Yang, Min Gu Kang, Sang Woo Yeom, Jong Seung Kim

Faculty, Staff and Student Publications

BACKGROUND: Previous studies have argued that attention deficit hyperactivity disorder (ADHD) is associated with asthma. However, reliable evidence to verify this association has not yet been reported.

OBJECTIVES: To investigate the bidirectional association between asthma and ADHD through a 12-year big data cohort study.

METHODS: The independent variable group was extracted from 3.5 million individuals randomly sampled by the National Health Insurance Service (NHIS). In Study 1, the incidence of ADHD according to asthma was evaluated, while in Study 2, the incidence of asthma according to ADHD was analyzed. Propensity score (PS) matching with several variables was used to obtain …

A Comprehensive Assessment Of Cell Type-Specific Differential Expression Methods In Bulk Data, Guanqun Meng, Wen Tang, Emina Huang, Ziyi Li, Hao Feng

Faculty, Staff and Student Publications

Accounting for cell type compositions has been very successful at analyzing high-throughput data from heterogeneous tissues. Differential gene expression analysis at cell type level is becoming increasingly popular, yielding biomarker discovery in a finer granularity within a particular cell type. Although several computational methods have been developed to identify cell type-specific differentially expressed genes (csDEG) from RNA-seq data, a systematic evaluation is yet to be performed. Here, we thoroughly benchmark six recently published methods: CellDMC, CARseq, TOAST, LRCDE, CeDAR and TCA, together with two classical methods, csSAM and DESeq2, for a comprehensive comparison. We aim to systematically evaluate the performance …

Ccsynergy: An Integrative Deep-Learning Framework Enabling Context-Aware Prediction Of Anti-Cancer Drug Synergy, Sayed-Rzgar Hosseini, Xiaobo Zhou

Faculty, Staff and Student Publications

Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug synergy are much needed for narrowing down this space, especially when examining new cellular contexts. Here, we thus introduce CCSynergy, a flexible, context aware and integrative deep-learning framework that we have established to unleash the potential of the Chemical Checker extended drug bioactivity profiles for the purpose of drug synergy prediction. We have shown that CCSynergy enables predictions of superior accuracy, remarkable robustness and improved context generalizability …

Dynamic Imine Bonding Facilitates Mannan Release From A Nanofibrous Peptide Hydrogel, Brett H Pogostin, Gabriel Saenz, Carson C Cole, Erin M Euliano, Jeffrey D Hartgerink, Kevin J Mchugh

Faculty, Staff and Student Publications

Recently, there has been increased interest in using mannan as an immunomodulatory bioconjugate. Despite notable immunological and functional differences between the reduced (R-Man) and oxidized (O-Man) forms of mannan, little is known about the impact of mannan oxidation state on its in vivo persistence or its potential controlled release from biomaterials that may improve immunotherapeutic or prophylactic efficacy. Here, we investigate the impact of oxidation state on the in vitro and in vivo release of mannan from a biocompatible and immunostimulatory multidomain peptide hydrogel, K2(SL)6K2 (abbreviated as K2), that has been previously used for the controlled release of protein and …

Multimodality Annotated Hepatocellular Carcinoma Data Set Including Pre- And Post-Tace With Imaging Segmentation, Ahmed W Moawad, Ali Morshid, Ahmed M Khalaf, Mohab M Elmohr, John D Hazle, David Fuentes, Mohamed Badawy, Ahmed O Kaseb, Manal Hassan, Armeen Mahvash, Janio Szklaruk, Aliyya Qayyum, Abdelrahman Abusaif, William C Bennett, Tracy S Nolan, Brittney Camp, Khaled M Elsayes

Faculty, Staff and Student Publications

Hepatocellular carcinoma (HCC) is the most common primary liver neoplasm, and its incidence has doubled over the past two decades owing to increasing risk factors. Despite surveillance, most HCC cases are diagnosed at advanced stages and can only be treated using transarterial chemo-embolization (TACE) or systemic therapy. TACE failure may occur with incidence reaching up to 60% of cases, leaving patients with a financial and emotional burden. Radiomics has emerged as a new tool capable of predicting tumor response to TACE from pre-procedural computed tomography (CT) studies. This data report defines the HCC-TACE data collection of confirmed HCC patients who …

Met Amplification As A Resistance Driver To Tki Therapies In Lung Cancer: Clinical Challenges And Opportunities, Kang Qin, Lingzhi Hong, Jianjun Zhang, Xiuning Le

Faculty, Staff and Student Publications

Targeted therapy has emerged as an important pillar for the standard of care in oncogene-driven non-small cell lung cancer (NSCLC), which significantly improved outcomes of patients whose tumors harbor oncogenic driver mutations. However, tumors eventually develop resistance to targeted drugs, and mechanisms of resistance can be diverse.

Wrapper-Based Deep Feature Optimization For Activity Recognition In The Wearable Sensor Networks Of Healthcare Systems, Karam Kumar Sahoo, Raghunath Ghosh, Saurav Mallik, Arup Roy, Pawan Kumar Singh, Zhongming Zhao

Faculty, Staff and Student Publications

The Human Activity Recognition (HAR) problem leverages pattern recognition to classify physical human activities as they are captured by several sensor modalities. Remote monitoring of an individual's activities has gained importance due to the reduction in travel and physical activities during the pandemic. Research on HAR enables one person to either remotely monitor or recognize another person's activity via the ubiquitous mobile device or by using sensor-based Internet of Things (IoT). Our proposed work focuses on the accurate classification of daily human activities from both accelerometer and gyroscope sensor data after converting into spectrogram images. The feature extraction process follows …

Scalable Causal Structure Learning: Scoping Review Of Traditional And Deep Learning Algorithms And New Opportunities In Biomedicine, Pulakesh Upadhyaya, Kai Zhang, Can Li, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

BACKGROUND: Causal structure learning refers to a process of identifying causal structures from observational data, and it can have multiple applications in biomedicine and health care.

OBJECTIVE: This paper provides a practical review and tutorial on scalable causal structure learning models with examples of real-world data to help health care audiences understand and apply them.

METHODS: We reviewed traditional (combinatorial and score-based) methods for causal structure discovery and machine learning-based schemes. Various traditional approaches have been studied to tackle this problem, the most important among these being the Peter Spirtes and Clark Glymour algorithms. This was followed by analyzing the …

Harnessing The Therapeutic Vulnerability Of Mmr Heterogeneity In Colorectal Cancer, Gayathri Anandappa, Michael J Overman

Faculty, Staff and Student Publications

In a recent issue of Cancer Cell, Amodio and colleagues report an interesting method of modulating immunosurveillance in colorectal tumors with DNA mismatch repair (MMR) heterogeneity.1 By pharmacologically enriching the MMR deficient (MMRd) component using 6-thioguanine, they demonstrate improved tumor control in murine models.

Examining Stripes On A Herd Of Zebras: Impact Of Genomic Matching For Ultrarare Sarcomas In Phase 1 Clinical Trials (Samba 102), Justin T Moyers, Roberto Carmagnani Pestana, Jason Roszik, David S Hong, Aung Naing, Siqing Fu, Sarina Piha-Paul, Timothy A Yap, Daniel Karp, Jordi Rodon, Andy Livingston, Maria Alejandra Zarzour, Vinod Ravi, Shreyaskumar Patel, Robert S Benjamin, Joseph Ludwig, Cynthia Herzog, Ravin Ratan, Neeta Somaiah, Anthony Conley, Richard Gorlick, Funda Meric-Bernstam, Vivek Subbiah

Faculty, Staff and Student Publications

Purpose: Recently, the Connective Tissue Oncology Society published consensus guidelines for recognizing ultrarare sarcomas (URS), defined as sarcomas with an incidence ≤1 per 1,000,000. We assessed the outcomes of 56 patients with soft tissue, and 21 with bone sarcomas, enrolled in Phase 1 trials.

Experimental design: In this Sarcoma-Matched Biomarker Analysis (SAMBA-102 study), we reviewed records from patients on Phase 1 trials at the University of Texas MD Anderson Cancer Center between January 2013 and June 2021.

Results: Among 587 sarcomas, 106 (18.1%) were classified as URS. Fifty (47%) were male, and the median age was 44.3 years (range, 19-82). …

Computational Simulations Of Fabrication Of Aluminum-Based Josephson Junctions: Topological Aspects Of The Barrier Structure, Chuanbing Han, Huihui Sun, Fudong Liu, Xiangju Zhao, Zheng Shan

Faculty, Staff and Student Publications

Although the performance of qubits has been improved in recent years, the differences in the microscopic atomic structure of the Josephson junctions, the core devices prepared under different preparation conditions, are still underexplored. In this paper, the effects of the oxygen temperature and upper aluminum deposition rate on the topology of the barrier layer in the aluminum-based Josephson junctions have been presented by classical molecular dynamics simulations. We apply a Voronoi tessellation method to characterize the topology of the interface and central regions of the barrier layers. We find that when the oxygen temperature is 573 K and the upper …

Features Of Tumor-Microenvironment Images Predict Targeted Therapy Survival Benefit In Patients With Egfr-Mutant Lung Cancer, Shidan Wang, Ruichen Rong, Donghan M Yang, Junya Fujimoto, Justin A Bishop, Shirley Yan, Ling Cai, Carmen Behrens, Lynne D Berry, Clare Wilhelm, Dara Aisner, Lynette Sholl, Bruce E Johnson, David J Kwiatkowski, Ignacio I Wistuba, Paul A Bunn, John Minna, Guanghua Xiao, Mark G Kris, Yang Xie

Faculty, Staff and Student Publications

Tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR) are effective for many patients with lung cancer with EGFR mutations. However, not all patients are responsive to EGFR TKIs, including even those harboring EGFR-sensitizing mutations. In this study, we quantified the cells and cellular interaction features of the tumor microenvironment (TME) using routine H&E-stained biopsy sections. These TME features were used to develop a prediction model for survival benefit from EGFR TKI therapy in patients with lung adenocarcinoma and EGFR-sensitizing mutations in the Lung Cancer Mutation Consortium 1 (LCMC1) and validated in an independent LCMC2 cohort. In the validation …

Mechanisms Of Mcl-1 Protein Stability Induced By Mcl-1 Antagonists In B-Cell Malignancies, Shady I Tantawy, Aloke Sarkar, Stefan Hubner, Zhi Tan, William G Wierda, Abdelraouf Eldeib, Shuxing Zhang, Steven Kornblau, Varsha Gandhi

Faculty, Staff and Student Publications

PURPOSE: Several MCL-1 inhibitors (MCL-1i), including AMG-176 and AZD5991, have shown promise in preclinical studies and are being tested for the treatment of hematologic malignancies. A unique feature of these agents is induction and stability of Mcl-1 protein; however, the precise mechanism is unknown. We aim to study the mechanism of MCL-1i-induced Mcl-1 protein stability.

EXPERIMENTAL DESIGN: Using several B-cell leukemia and lymphoma cell lines and primary chronic lymphocytic leukemia (CLL) lymphocytes, we evaluated molecular events associated with Mcl-1 protein stability including protein half-life, reverse-phase protein array, protein-protein interaction, phosphorylation, ubiquitination, and de-ubiquitination, followed by molecular simulation and modeling.

RESULTS: …

Planarians To Schistosomes: An Overview Of Flatworm Cell-Types And Regulators, J Lee

Faculty, Staff and Student Publications

Schistosomiasis remains a major neglected tropical disease that afflicts over 200 million people globally. Schistosomes, the aetiological agent of schistosomiasis, are parasitic flatworms that propagate between molluscan and mammalian hosts. Inside the mammalian host, schistosomes rapidly grow over 100-fold in size and develop into a sexually mature male or female that thrives in the bloodstream for several decades. Recent work has identified schistosome stem cells as the source that drives parasite transmission, reproduction and longevity. Moreover, studies have begun to uncover molecular programmes deployed by stem cells that are essential for tissue development and maintenance, parasite survival and immune evasion. …

Exploring Therapeutic Strategies For Infantile Neuronal Axonal Dystrophy (Inad/Park14), Guang Lin, Burak Tepe, Geoff Mcgrane, Regine C Tipon, Gist Croft, Leena Panwala, Amanda Hope, Agnes J H Liang, Zhongyuan Zuo, Seul Kee Byeon, Lily Wang, Akhilesh Pandey, Hugo J Bellen

Faculty, Staff and Students Publications

Infantile neuroaxonal dystrophy (INAD) is caused by recessive variants in PLA2G6 and is a lethal pediatric neurodegenerative disorder. Loss of the Drosophila homolog of PLA2G6, leads to ceramide accumulation, lysosome expansion, and mitochondrial defects. Here, we report that retromer function, ceramide metabolism, the endolysosomal pathway, and mitochondrial morphology are affected in INAD patient-derived neurons. We show that in INAD mouse models, the same features are affected in Purkinje cells, arguing that the neuropathological mechanisms are evolutionary conserved and that these features can be used as biomarkers. We tested 20 drugs that target these pathways and found that Ambroxol, Desipramine, …