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A New Registry for Genetic Diagnosis of Inborn Errors of Immunity within the Military Health System Nathan A. Boggs1,2, Brandon J. Schornack1, Janet A. Brunader3, Ahlea A. Rutt3, Maria Leondaridis4,5, Kip R. Hartman1, Lydia D. Hellwig5,6, Gauthaman Sukumar5,6, Xijun Zhang5,6, Joaquin Villar5,6, Clifton L. Dalgard5,7, Andrew L. Snow4 1Allergy and Immunology Service, Walter Reed National Military Medical Center, Bethesda, MD, 2Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA, 3Defense Health Agency Immunization Healthcare Division, Falls Church, VA, USA, 4Department of Pharmacology & Molecular Therapeutics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA, 5Henry M Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA, 6Center for Military Precision Health, Uniformed Services University of the Health Sciences, Bethesda, MD, USA, 7 Department of Anatomy, Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA Genotypic definition of monogenic inborn errors of immunity (IEIs) continues to accelerate with broader access to next generation sequencing, underscoring this aggregated group of disorders as a major health burden impacting both civilian and military populations. At an estimated prevalence of 1 in 1200 individuals, IEIs affect ~8,000 patients within the Military Health System (MHS). Despite access to targeted gene/exome panels at military treatment facilities, most affected patients never receive a definitive genetic diagnosis that would significantly improve clinical care. To address this gap, we established the first registry of IEI patients within the MHS with the goal of identifying known and novel pathogenic genetic defects to increase diagnosis rates and enhance clinical care. Using the registry, a research protocol was opened in July 2022. Since July we have enrolled 75 IEI patients encompassing a breadth of phenotypes inclu, RITM0037649, Genotypic definition of monogenic inborn errors of immunity (IEIs) continues to accelerate with broader access to next generation sequencing, underscoring this aggregated group of disorders as a major health burden impacting both civilian and military populations. At an estimated prevalence of 1 in 1200 individuals, IEIs affect ~8,000 patients within the Military Health System (MHS). Despite access to targeted gene/exome panels at military treatment facilities, most affected patients never receive a definitive genetic diagnosis that would significantly improve clinical care. To address this gap, we established the first registry of IEI patients within the MHS with the goal of identifying known and novel pathogenic genetic defects to increase diagnosis rates and enhance clinical care. Using the registry, a research protocol was opened in July 2022. Since July we have enrolled 75 IEI patients encompassing a breadth of phenotypes including severe and recurrent infections, bone marrow failure, autoimmunity/autoinflammation, atopic disease, and malignancy. Enrolled patients provide blood and bone marrow samples for whole genome, ultra-deep targeted panel and comprehensive transcriptome sequencing, plus cryopreservation of peripheral blood mononuclear cells for future functional studies. We are also implementing and developing analytical methods for identifying and interrogating non-coding and structural variants. Suspected pathogenic variants are adjudicated by a clinical molecular geneticist using state-of-the-art analysis pipelines. These analyses subsequently inform in vitro experiments to validate causative mutations using cell reporter systems and primary patient cells. Clinical variant validation and return of genetic results are planned with genetic counseling provided. As a proof of principle, this integrated genetic evaluation pipeline revealed a novel, candidate TLR7 nonsense variant in two adolescent brothers who both endured critical COVID-19 pneumonia, requi

A New Registry for Genetic Diagnosis of Inborn Errors of Immunity within the Military Health System Nathan A. Boggs1,2, Brandon J. Schornack1, Janet A. Brunader3, Ahlea A. Rutt3, Maria Leondaridis4,5, Kip R. Hartman1, Lydia D. Hellwig5,6, Gauthaman Sukumar5,6, Xijun Zhang5,6, Joaquin Villar5,6, Clifton L. Dalgard5,7, Andrew L. Snow4 1Allergy and Immunology Service, Walter Reed National Military Medical Center, Bethesda, MD, 2Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA, 3Defense Health Agency Immunization Healthcare Division, Falls Church, VA, USA, 4Department of Pharmacology & Molecular Therapeutics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA, 5Henry M Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA, 6Center for Military Precision Health, Uniformed Services University of the Health Sciences, Bethesda, MD, USA, 7 Department of Anatomy, Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA Genotypic definition of monogenic inborn errors of immunity (IEIs) continues to accelerate with broader access to next generation sequencing, underscoring this aggregated group of disorders as a major health burden impacting both civilian and military populations. At an estimated prevalence of 1 in 1200 individuals, IEIs affect ~8,000 patients within the Military Health System (MHS). Despite access to targeted gene/exome panels at military treatment facilities, most affected patients never receive a definitive genetic diagnosis that would significantly improve clinical care. To address this gap, we established the first registry of IEI patients within the MHS with the goal of identifying known and novel pathogenic genetic defects to increase diagnosis rates and enhance clinical care. Using the registry, a research protocol was opened in July 2022. Since July we have enrolled 75 IEI patients encompassing a breadth of phenotypes inclu, RITM0037463, Genotypic definition of monogenic inborn errors of immunity (IEIs) continues to accelerate with broader access to next generation sequencing, underscoring this aggregated group of disorders as a major health burden impacting both civilian and military populations. At an estimated prevalence of 1 in 1200 individuals, IEIs affect ~8,000 patients within the Military Health System (MHS). Despite access to targeted gene/exome panels at military treatment facilities, most affected patients never receive a definitive genetic diagnosis that would significantly improve clinical care. To address this gap, we established the first registry of IEI patients within the MHS with the goal of identifying known and novel pathogenic genetic defects to increase diagnosis rates and enhance clinical care. Using the registry, a research protocol was opened in July 2022. Since July we have enrolled 75 IEI patients encompassing a breadth of phenotypes including severe and recurrent infections, bone marrow failure, autoimmunity/autoinflammation, atopic disease, and malignancy. Enrolled patients provide blood and bone marrow samples for whole genome, ultra-deep targeted panel and comprehensive transcriptome sequencing, plus cryopreservation of peripheral blood mononuclear cells for future functional studies. We are also implementing and developing analytical methods for identifying and interrogating non-coding and structural variants. Suspected pathogenic variants are adjudicated by a clinical molecular geneticist using state-of-the-art analysis pipelines. These analyses subsequently inform in vitro experiments to validate causative mutations using cell reporter systems and primary patient cells. Clinical variant validation and return of genetic results are planned with genetic counseling provided. As a proof of principle, this integrated genetic evaluation pipeline revealed a novel, candidate TLR7 nonsense variant in two adolescent brothers who both endured critical COVID-19 pneumonia, requi

Introduction Workflow Summary Detecting differentially expressed genes under different biological conditions is crucial to characterize mechanisms of cancer development and identifying determinants of patient outcome. High throughput technologies such as RNA sequencing and mass spectrometry-based proteomics have been widely used to identify differentially expressed genes (DEG), on a transcript and on a peptide basis, respectively. However, both transcription and translation of genes provide information about gene expression. Thus, leveraging both RNA and protein expression data could potentially produce more accurate results. Various statistical tools have been developed to tackle the differential expression problem for a single platform, such as edgeR, DESeq2, etc. However, a tool that integrates both transcriptome and proteomics data for differential expression analysis has not yet been developed. Meta-analysis can potentially increase statistical power and identify new cancer genes in large sample cohorts and potentially also in small sample cohorts. Here we present DE-Meta, a new tool developed using R, which performs combined meta-analysis of RNA-seq and MS-based proteomics on matched tumor specimens. Lung adenocarcinoma (LUAD) is a primary cause of cancer-related deaths worldwide, despite advances in somatically targeted therapeutics and immune checkpoint therapies. The diagnosis and treatment of LUAD patients pose significant challenges due to the vast morphological and molecular heterogeneity observed both within and between tumors. Two published lung adenocarcinoma datasets were used in this study: APOLLO11,7 and CPTAC2. APOLLO7 is a proteogenomic study seeking to describe the major genome, transcriptome, proteome and phosphoproteome alterations, subtypes, and molecular predictors of patient outcomes. Stratifying LUAD patients using expression subtypes can enhance prediction of clinical outcomes. Expression subtype status of these two cohorts were predicted, RITM0035818, Detecting differentially expressed genes under different biological conditions is crucial to characterize mechanisms of cancer development and identifying determinants of patient outcome. High throughput technologies such as RNA sequencing and mass spectrometrybased proteomics have been widely used to identify differentially expressed genes (DEG), on a transcript and on a peptide basis, respectively. However, both transcription and translation of genes provide information about gene expression. Thus, leveraging both RNA and protein expression data could potentially produce more accurate results. Various statistical tools have been developed to tackle the differential expression problem for a single platform, such as edgeR, DESeq2, etc. However, a tool that integrates both transcriptome and proteomics data for differential expression analysis has not yet been developed. Meta-analysis can potentially increase statistical power and identify new cancer genes in large sample cohorts and potentially also in small sample cohorts. Here we present DE-Meta, a new tool developed using R, which performs combined meta-analysis of RNA-seq and MS-based proteomics on matched tumor specimens.

Whole Genome Sequence Analysis of Candidate Genes Identified Three Loci Potentially Related to Mefloquine Side Effects Monique Hollis-Perry1, Joshua Gray1, Dutchabong Shaw1,2, Daniel Hupalo1,2, Heidi Adams1,2, Xijun Zhang1,2, Matthew D. Wilkerson1, Lydia D. Hellwig1,2, Clifton Dalgard1, Jeffrey Livezey1, David Saunders1 1Uniformed Services University of Health Sciences Bethesda, MD; 2Henry Jackson Foundation for the Advancement of Military Medicine Bethesda, MD Gene Provided Data RSID Chr loc hg38 Site 1 ref/alt Site 2 ref/alt Site details ORM1 S rs17650,rs1126801 chr9 114323246. ; 114325132 G,G G,G ARG(CGG)20,VAL(GTG)156 ORM1 F1 rs17650,rs1126801 chr9 114323246. ; 114325132 G,A G,G GLN(CAG)20,VAL(GTG)156 ORM1 F2 rs17650,rs1126801 chr9 114323246. ; 114325132 G,A G,A GLN(CAG)20 MET(ATG)156 MTHFR A1298C rs1801131 chr1 11794419 A C p.Glu429Ala MTHFR C677T rs1801133 chr1 11796321 C T p.Ala222Val MDR1 C1236T rs1128503 chr7 87550285 A G p.Gly412Gly MDR1 G2677T rs2032582 chr7 87531302 A C p.Ala893Ser MDR1 C3435T rs1045642 chr7 87509329 A G p.Ile1145Ile PYK2 rs2883490 rs28834970 chr8 27337604 T C intronic HT2A rs7997012 rs7997012 chr13 46837850 A G intronic HT2A rs1928040 rs1928040 chr13 46873101 G A intronic HT2A rs6311 rs6311 chr13 46897343 C T intronic HT2A rs6313 rs6313 chr13 46895805 G A p.Ser34Ser ADA G22A rs73598374 chr20 44651586 C T p.Asp8Tyr ADORA2A (A2A) T1976C rs5751876 chr22 24441333 T C p.Tyr361Tyr ADORA2A (A2A) C2592T rs35320474 chr22 24441942 - T 3' UTR variant METHODS Volunteers with a history of exposure to mefloquine with or without adverse neuropsychiatric symptoms were invited to participate in this case-control cross-sectional study after interviews and medical records review. Investigators searched for potential associations within 7 candidate genes and 16 associated variants for study. Blood samples were collected in Paxgene RNA tubes from 50 volunteers. Mefloquine exposure was defined as: travel to an area with malaria prophylaxis recommendations; w, RITM0040216, Although mefloquine provides effective once-weekly antimalarial prophylaxis, this medication has fallen out of favor due to the risk of neuropsychiatric effects. These can appear after one or two doses, may be mild or severe and commonly include headaches, memory impairment, anxiety or depression, hallucinations, insomnia, and psychosis. Adverse events typically resolve after drug discontinuation, but some patients report long-term complications. While genetic susceptibilities have been identified, pharmacogenomic testing guidance for mefloquine use is not currently available.

A Protein Expression Signature of TMPRSS2-ERG Gene Fusion and ERG Protein Overexpression in Prostate Cancer Nicholas W. Bateman1-3, Tamara S. Abulez1-3, Cara C. Schafer3,4, Kelly A. Conrads1-3, Brian L. Hood1-3, Xijun Zhang5, Isabell A. Sesterhenn7, Clifton Dalgard5, Matthew Wilkerson5, Albert Dobi3,4, Gyorgy Petrovics3,4, Craig D. Shriver2, Gregory T. Chesnut2,4,8, Thomas P. Conrads1,2,6, Shyh-Han Tan3,4 1) Gynecologic Cancer Center of Excellence, Department of Gynecologic Surgery and Obstetrics, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, Maryland, 20889, USA. 2) Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Bethesda, Maryland, 20889, USA. 3) The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, Maryland, 20817, USA. 4) Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, Maryland, 20817, USA. 5) The American Genome Center, Collaborative Health Initiative Research Program, Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, 20814, USA. 6) Women’s Health Integrated Research Center, Women’s Service Line, Inova Health System, Falls Church, Virginia, 22042, USA. 7) Joint Pathology Center, Silver Spring, Maryland, 20906, USA. 8) Urology Service, Walter Reed National Military Medical Center, Bethesda, Maryland, 20814, USA. Background Methods Results Conclusions Prostate cancer is the third most common cancer type diagnosed in active-duty service members (ADSM), an incidence rate that is higher relative to the US population. Several poorly understood racial disparities are prevalent in the prostate cancer population, where African Americans (AA) are more frequently diagnosed with, RITM0040134, Prostate cancer is the third most common cancer type diagnosed in active-duty service members (ADSM), an incidence rate that is higher relative to the US population. Several poorly understood racial disparities are prevalent in the prostate cancer population, where African Americans (AA) are more frequently diagnosed with this disease and present more often with distant metastasis compared to European Americans (EA). Common molecular characteristics in prostate cancer include a gene fusion involving transmembrane protease, serine 2 and ETS-related gene (TMPRSS2-ERG) that results in elevated ERG protein abundance that is more common in men of EA ancestry. TMPRSS2-ERG fusion event occur early in tumorigenesis and play a critical role in the clonal selection of prostate tumors. Assessment of ERG overexpression by clinical diagnostic testing has prompted the development of ERG-based therapies that include small molecule inhibitors targeting ERG, e.g., ERGi-USU. Knowledge of transcript and protein abundance changes correlating with TMPRSS2-ERG fusion status could provide further insights into the functional activity of the ERG signaling pathway. Our team conducted a proteogenomic analysis of prostate cancer tissues collected within a cohort of AA and EA ADSM as part of the Cancer Moonshot, Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network, which included assessment of protein expression changes in prostate cancer tissues harboring TMPRSS2-ERG fusion and ERG protein overexpression.

Anthony R. Soltis1,3, Nicholas W. Bateman2,3, Jianfang Liu4, Trinh Nguyen5, Teri J. Franks5, Xijun Zhang1,3, Clifton L. Dalgard1, Coralie Violet 1,3 , Stella Somiari4, Chunhua Yan6, Karen Zeman7,8, William J. Skinner7,8, Jerry S. H. Lee9, Harvey B. Pollard1, Clesson Turner8, Emanuel F. Petricoin10, Daoud Meerzaman5, Thomas P. Conrads2, Hai Hu4,8, APOLLO Research Network, Craig D. Shriver8*, Christopher A. Moskaluk11*, Robert F. Browning7,8*, Matthew D. Wilkerson1*^ 1 The American Genome Center, Collaborative Health Initiative Research Program, Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA 2 Women’s Health Integrated Research Center, Inova Women’s Service Line, Inova Fairfax Medical Campus, Falls Church, VA, USA; Gynecologic Cancer Center of Excellence, Murtha Cancer Center Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD, USA . 3 The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda MD, USA. 4 Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA. 5Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, USA 6 Pulmonary and Mediastinal Pathology, Department of Defense, Joint Pathology Center, Silver Spring, MD, USA. 7 Department of Medicine, Walter Reed National Military Medical Center, Bethesda, MD, USA 8 Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA 9 Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, CA, USA 10 Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA, USA 11 Department of Pathology, University of Virginia, Charlottesville, VA, USA Proteogenomic analysis of lung adenocarcinoma reveals tumor heterogeneity, survival determinants and therapeutically-relevant pathways Backgrou, RITM0028776, Lung cancer is a leading cause of cancer incidence and deaths in the U.S. Military and impairs readiness of the armed forces. Lung adenocarcinoma is a common histological variant; however, these tumors result from different patient exposures, have different presentations, and display vastly different responses to treatment. This wide-ranging heterogeneity in lung adenocarcinoma complicates individualizing patient treatment and prognosis. National efforts directed towards cataloging DNA and RNA alterations have significantly improved the understanding of lung adenocarcinoma and its molecular heterogeneity; however, there is a gap in identifying the critical molecular alterations in all lung adenocarcinomas and distinguishing which are relevant for patient outcome and treatment. To address this gap, mass-spectrometry-based proteomic profiling has been recently conducted to reveal proteomic alterations in lung adenocarcinoma and other tumor types. To date, these efforts have been focused on tumors from East Asian countries and with EGFR mutation, which is an important but incomplete segment of this disease. We sought to characterize the proteogenomic etiology of lung adenocarcinoma and develop improved molecular predictors of patient outcome in a cohort of lung adenocarcinomas from the U.S., as part of the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) Research Network.