Literature Curation Research Articles

The Animal Audiogram Database: A new resource for presenting and evaluating audiogram data on the web

Knowledge of hearing abilities, as represented in audiograms, is vital for understanding animal acoustic physiology, behaviour, and ecology. Additionally, such knowledge plays an important role for measuring, predicting, or counteracting effects of anthropogenic noise on the environment. Currently, audiogram data is usually only available embedded in individual scientific publications and in various unstandardized formats, which makes access to and analysis of audiograms across sources cumbersome. We established a newly database that presents audiograms along with data on the audio-physiological experiments and original publications in a structured and easily accessible way. The interface enables combination of audiogram data for comparative analysis of different species, experimental conditions or publications. Focusing currently on marine vertebrates its content is the result of an extensive survey of the scientific literature and manual curation of the contained audio-physiological data. The database is designed to accommodate audiogram data on any biological group and purposed to be extended and serve as a reference source for audiogram data. It is publicly accessible at https://animalaudiograms.museumfuernaturkunde.berlin. [The database was developed as part of the project “Hearing in Penguins” funded by the German Environment Agency (UBA) with means from the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU, FKZ3717182440).]

Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns.

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature

In spite of the efforts in developing and maintaining accurate variant databases, a large number of disease-associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an effort to extract this information is a challenging task due to: (i) the complexity of natural language processing, (ii) inconsistent use of standard recommendations for variant description, and (iii) the lack of clarity and consistency in describing the variant-genotype-phenotype associations in the biomedical literature. In this article, we employ text mining and word cloud analysis techniques to address these challenges. The proposed framework extracts the variant-gene-disease associations from the full-length biomedical literature and designs an evidence-based variant-driven gene panel for a given condition. We validate the identified genes by showing their diagnostic abilities to predict the patients’ clinical outcome on several independent validation cohorts. As representative examples, we present our results for acute myeloid leukemia (AML), breast cancer and prostate cancer. We compare these panels with other variant-driven gene panels obtained from Clinvar, Mastermind and others from literature, as well as with a panel identified with a classical differentially expressed genes (DEGs) approach. The results show that the panels obtained by the proposed framework yield better results than the other gene panels currently available in the literature.

Genome-wide Core Proteome Analysis of Brucella melitensis Strains for Potential Drug Target Prediction.

Brucella melitensis is a facultative intracellular bacterial pathogen that causes abortion in goats and sheep and Malta fever in humans. In humans, chronic infection occurs through contact with infected animals or their waste products. The subtractive genomic approach is considered as a powerful and useful method for the identification of potential drug and vaccine targets. In this study, an attempt has been made through a subtractive proteomic strategy to identify novel drug targets in Brucella melitensis strains. Total 2604 core proteins of 56 strains of B. melitensis were taken, of which 545 non-human homologs were found to be essential for pathogen growth. Metabolic pathway analysis of these essential proteins revealed that 129 proteins are exclusively involved in 21 unique metabolic pathways in B. melitensis reference strain. Of these, 31 proteins were found to be involved in 10 metabolic pathways that are unique to the pathogen. We selected Nitrate reductase subunit-β, Urease subunit α-2, Pantoate-β-alanine ligase, Isochorismatase, 2-dehydro-3-deoxyphosphooctonate aldolase and Serine O-acetyltransferase as drug targets in Brucella melitensis strains. Among these druggable targets, we selected only Pantoate-β- alanine ligase as high confidence target based on intensive literature curation, which is nonhomologous to the human gut metagenome involved in biosynthesis of secondary metabolites pathway. Pantothenate synthetase is the best chemotherapeutic target to combat Brucellulosis. Furthermore, in vitro and in vivo validation is needed for the evaluation of lead compounds against Brucella melitensis strains.

KURASI DIGITAL SASTRA SIBER: PERSPEKTIF SASTRA KONVENSIONAL

The last two decades signified the shift in the period of literary development. The emergence of various literary works that developed in the internet era succeeded in breaking the order of conventional literary publications which originally needed a layered process to be able to reach the readers. The rapid development of cyber literature produced many new literary works. Even though its quality is still being debated, it cannot eliminate its entity as a literary work and its role as a cultural product that must be preserved. That becomes a special aspect in this study, which aims to give consideration regarding preservation of cyber literary works in the form of digital curation of literature. This study considers the digital curation process of literature as the use of digital curation systems in the field of archives. This study uses descriptive qualitative methods to identify the urgency of digital curation of cyber literature. Furthermore, this analysis can be considered to produce collaboration between fields of literary, archival, and library science.

Abstract PHB03: A hierarchical model of DNA repair inferred from omics-scale genetic interaction data reveals the dynamics of DNA damage induction

Abstract Deficiency in one or more subsystems of the DNA damage response and repair system hierarchy is a hallmark of cancer and makes DNA repair an attractive target for physical or chemical therapies. An accurate, complete, yet parsimonious model of the systems and pathways comprising the hierarchy of DNA repair mechanisms can be expected to further our understanding of cancer genesis and progression and to facilitate the development of improved cancer therapies. Previous attempts in building a hierarchical model of DNA repair include methods based on literature curation (Gene Ontology [1]) and expert consensus (2). However, as these models rely on manual curation, rapid integration of novel omics-scale experimental data sets is not practicable. Moreover, Gene Ontology is by its definition only concerned with the modeling of pathways in the healthy cell and does not aim to reflect cancer-specific aspects. To bridge this gap, we here describe the generation of an entirely data-driven model of DNA repair, inferred from a large meta-compendium describing the physical interactions between proteins based on an integration of over 110 experimental data sets from different omics levels (genome, transcriptome, proteome). Augmenting a technique that we developed earlier, Active Interaction Mapping (AIM) (3), we define a hierarchical model of DNA repair consisting of 293 genes organized in 40 systems. Briefly, we integrate the interaction evidence using a random forest regressor to generate a weighted, integrated network; we then transform the network into a consensus matrix and feed this into an algorithm based on previous work (4) to identify the hierarchical structure embedded in the network. The hierarchical model takes the form of a directed acyclic graph (DAG), which allows us to model pleiotropic aspects of molecular systems, as some proteins and systems play functional roles in different ancestor systems. Using a network biology approach, we suggest a list of 293 genes playing central roles in DNA repair and find evidence that genome replication and RNA splicing processes are more intimately connected to DNA repair than previously appreciated. We find novel roles for about one third of the genes in our model, identify novel subsystems of already known systems in DNA repair, and can describe novel interactions between already known DNA repair systems. Finally, we perform perturbations of the DNA repair hierarchy in different cell lines, measure the impact on the protein-protein and genetic interaction networks, and use the identified interactions to search for impacted connections within and between systems of the DNA repair model.

DbPSP 2.0, an updated database of protein phosphorylation sites in prokaryotes

In prokaryotes, protein phosphorylation plays a critical role in regulating a broad spectrum of biological processes and occurs mainly on various amino acids, including serine (S), threonine (T), tyrosine (Y), arginine (R), aspartic acid (D), histidine (H) and cysteine (C) residues of protein substrates. Through literature curation and public database integration, here we reported an updated database of phosphorylation sites (p-sites) in prokaryotes (dbPSP 2.0) that contains 19,296 experimentally identified p-sites in 8,586 proteins from 200 prokaryotic organisms, which belong to 12 phyla of two kingdoms, bacteria and archaea. To carefully annotate these phosphoproteins and p-sites, we integrated the knowledge from 88 publicly available resources that covers 9 aspects, namely, taxonomy annotation, genome annotation, function annotation, transcriptional regulation, sequence and structure information, family and domain annotation, interaction, orthologous information and biological pathway. In contrast to version 1.0 (~30 MB), dbPSP 2.0 contains ~9 GB of data, with a 300-fold increased volume. We anticipate that dbPSP 2.0 can serve as a useful data resource for further investigating phosphorylation events in prokaryotes. dbPSP 2.0 is free for all users to access at: http://dbpsp.biocuckoo.cn.

Data libraries - the missing element for modeling biological systems.

The primary bottleneck in understanding and modeling biological systems is shifting from data collection to data analysis and integration. This process critically depends on data being available in an organized form, so that they can be accessed, understood, and reused by a broad community of scientists. A proven solution for organizing data is literature curation, which extracts, aggregates, and distributes findings from publications. Here, I describe the benefits of extending curation practices to datasets, especially those that are not deposited in centralized databases. I argue that dataset curation (or ‘data librarianship’ as I suggest we call it) will overcome many barriers in data visibility and reusability and make a unique contribution to integration and modeling.

Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex

Structural rules underlying functional properties ofcortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified rules governing cell-class-specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single-cell abstraction, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community.

Integrative systems and functional analyses reveal a role of dopaminergic signaling in myelin pathogenesis

BackgroundMyelin sheaths surrounding axons are critical for electrical signal transmission in the central nervous system (CNS). Diseases with myelin defects such as multiple sclerosis (MS) are devastating neurological conditions for which few effective treatments are available. Dysfunction of the dopaminergic system has been observed in multiple neurological disorders. Its role in myelin pathogenesis, however, is unclear.MethodsThis work used a combination of literature curation, bioinformatics, pharmacological and genetic manipulation, as well as confocal imaging techniques. Literature search was used to establish a complete set of genes which is associated with MS in humans. Bioinformatics analyses include pathway enrichment and crosstalk analyses with human genetic association studies as well as gene set enrichment and causal relationship analyses with transcriptome data. Pharmacological and CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) genetic manipulation were applied to inhibit the dopaminergic signaling in zebrafish. Imaging techniques were used to visualize myelin formation in vivo.ResultsSystematic analysis of human genetic association studies revealed that the dopaminergic synapse signaling pathway is enriched in candidate gene sets. Transcriptome analysis confirmed that expression of multiple dopaminergic gene sets was significantly altered in patients with MS. Pathway crosstalk analysis and gene set causal relationship analysis reveal that the dopaminergic synapse signaling pathway interacts with or is associated with other critical pathways involved in MS. We also found that disruption of the dopaminergic system leads to myelin deficiency in zebrafish.ConclusionsDopaminergic signaling may be involved in myelin pathogenesis. This study may offer a novel molecular mechanism of demyelination in the nervous system.

A structured model for immune exposures.

An Immune Exposure is the process by which components of the immune system first encounter a potential trigger. The ability to describe consistently the details of the Immune Exposure process was needed for data resources responsible for housing scientific data related to the immune response. This need was met through the development of a structured model for Immune Exposures. This model was created during curation of the immunology literature, resulting in a robust model capable of meeting the requirements of such data. We present this model with the hope that overlapping projects will adopt and or contribute to this work.

A Quantitative Systems Pharmacology Model for the Key Interleukins Involved in Crohn's Disease.

Crohn's disease (CD) is a complex inflammatory bowel disease whose pathogenesis appears to involve several immunologic defects causing functional impairment of the gut. Its complexity and the reported loss of effectiveness over time of standard of care together with the increase in its worldwide incidence require the application of techniques aiming to find new therapeutic strategies. Currently, systems pharmacology modeling has been gaining importance as it integrates the available knowledge of the system into a single computational model. In this work, the following workflow for robust application of systems pharmacology modeling was followed: 1) scope definition; 2) species selection and circulating plasma levels based on a search in the literature; 3) representation of model topology and parametrization of the interactions, after literature data extraction and curation, and the implementation of ordinary differential equations in SimBiology (MATLAB version R2018b); and 4) model curation and evaluation by visual comparison of simulated interleukin (IL) concentrations with the reported levels in plasma, and sensitivity analysis performed to confirm model robustness and identify the most influential parameters. Finally, 5) exposure to two dose levels of recombinant human IL10 was evaluated by simulation and comparison with reported clinical study results. In summary, we present a quantitative systems pharmacology model for the main ILs involved in CD developed using a standardized methodology and supported by a comprehensive repository summarizing the most relevant literature in the field. However, it has to be taken into account that external validation is still pending as available clinical data were primarily used for model training. SIGNIFICANCE STATEMENT: Crohn's disease (CD) is a complex heterogeneous inflammatory bowel disorder. Systems pharmacology modeling offers a great opportunity for integration of the available knowledge on the disease using a computational framework. As a result of this work, a comprehensive repository along with a quantitative systems pharmacology model for the main interleukins involved in CD is provided. This model is useful for the in silico evaluation of biomarkers and potential therapeutic targets and can be adapted to address research gaps regarding CD.

Impact of Automatic Query Generation and Quality Recognition Using Deep Learning to Curate Evidence From Biomedical Literature: Empirical Study.

BackgroundThe quality of health care is continuously improving and is expected to improve further because of the advancement of machine learning and knowledge-based techniques along with innovation and availability of wearable sensors. With these advancements, health care professionals are now becoming more interested and involved in seeking scientific research evidence from external sources for decision making relevant to medical diagnosis, treatments, and prognosis. Not much work has been done to develop methods for unobtrusive and seamless curation of data from the biomedical literature.ObjectiveThis study aimed to design a framework that can enable bringing quality publications intelligently to the users’ desk to assist medical practitioners in answering clinical questions and fulfilling their informational needs.MethodsThe proposed framework consists of methods for efficient biomedical literature curation, including the automatic construction of a well-built question, the recognition of evidence quality by proposing extended quality recognition model (E-QRM), and the ranking and summarization of the extracted evidence.ResultsUnlike previous works, the proposed framework systematically integrates the echelons of biomedical literature curation by including methods for searching queries, content quality assessments, and ranking and summarization. Using an ensemble approach, our high-impact classifier E-QRM obtained significantly improved accuracy than the existing quality recognition model (1723/1894, 90.97% vs 1462/1894, 77.21%).ConclusionsOur proposed methods and evaluation demonstrate the validity and rigorousness of the results, which can be used in different applications, including evidence-based medicine, precision medicine, and medical education.

Quantitative Investigation of Pharmacologically Modulated Signaling and Efficacy in ABC DLBCL Using a Systems Pharmacology Model

Introduction The activated B cell like (ABC) subtype of DLBCL has a 40% cure rate with currently available therapies [1] - worse than the rate for germinal center B-cell like (GCB) DLBCL, which highlights the need for ABC subtype-specific treatment strategies. Bruton's tyrosine kinase (BTK) links the activity of the B cell receptor (BCR) to NF-κB and is essential for the survival of ABC cell lines with chronic active BCR signaling. BTK selective covalent inhibitors such as ibrutinib and acalabrutinib are effective in blocking BTK activation and reducing downstream NF-κB pathway activity. However, in ABC DLBCL patients, the observed response rate to ibrutinib is 37% (14/38) and the median PFS is only about 2 months [1]. Many patients show primary resistance to the drug or develop secondary resistance. To improve patient outcomes, a number of combination treatments along with BTK inhibition may be considered. The goal of this work is to integrate data on ABC DLBCL signaling and tumor effect, as well as its pharmacological modulation into one common quantitative systems pharmacology (QSP) modeling framework, to better understand potential efficacy benefits when adding combination partners to a BTK inhibitor. Methods A fit-for-purpose mechanistic model of ABC DLBCL signaling linked to cell cycle and cell death was developed, based on literature curation and in vitro and in vivo data in TMD8 cell lines. TMD8 cells carry activating mutations in the BCR adaptor protein CD79B and in the TLR adaptor protein MYD88. Chronic BCR signaling in ABC DLBCL activates downstream NF-κB through signaling of the BTK as well as the PI3K/AKT/mTOR pathways (Fig. 1). The L265P mutated isoform of MYD88 spontaneously activates NF-κB in a BCR-independent manner. In the cell cycle / cell death part of the model, transition rates were regulated by relevant model variables of signaling pathways (NF-κB, AKT, mTOR activation). Efficacy (tumor size modulation) was implemented through quantitative PK/PD data obtained from TMD8 xenograft studies in CB.17 SCID mice treated with acalabrutinib, as well as mTOR and AKT inhibitors. Results Individual animal tumor size dynamics were studied in control and treatment groups: BTKi (acalabrutinib), AKTi (AZD5363), mTORi (everolimus and AZD2014), as monotherapies and in combinations with acalabrutinib. Interestingly, there was no statistically significant difference in tumor size dynamics, between the control arm and the AKTi monotherapy group. Acalabrutinib monotherapy showed only a moderate decrease in tumor size, with no observation of full tumor rejection. However, acalabrutinib combined with mTORi or AKTi achieved 100% tumor rejection. The model adequately described tumor size dynamics with acalabrutinib and mTORi/AKTi combinations. In order to improve model fitting, we are now taking enhanced activation of the PI3K/AKT/mTOR pathway into consideration, to further evaluate the underlying mechanism for synergy between acalabrutinib and AKTi. Discussion Enhanced AKT activation induction has been observed in BTKi treatment refractory cell lines [2] and may explain primary resistance to, or limited efficacy of BTK inhibitors in some ABC DLBCL patients (while other mechanisms of primary resistance are known). This mechanism may help lymphoma cells to strive, chronically, under BTK inhibitor treatment, while at the same time increase the probability of gaining mutations such as BTK C481S [3], which may further lead to secondary resistance. Combination of an AKT inhibitor with acalabrutinib may help circumvent both primary and secondary (acquired) resistance in ABC-DLBCL.

WormBase: a modern Model Organism Information Resource.

WormBase (https://wormbase.org/) is a mature Model Organism Information Resource supporting researchers using the nematode Caenorhabditis elegans as a model system for studies across a broad range of basic biological processes. Toward this mission, WormBase efforts are arranged in three primary facets: curation, user interface and architecture. In this update, we describe progress in each of these three areas. In particular, we discuss the status of literature curation and recently added data, detail new features of the web interface and options for users wishing to conduct data mining workflows, and discuss our efforts to build a robust and scalable architecture by leveraging commercial cloud offerings. We conclude with a description of WormBase's role as a founding member of the nascent Alliance of Genome Resources.

Blinded Testing of Function Annotation for uPE1 Proteins by I-TASSER/COFACTOR Pipeline Using the 2018-2019 Additions to neXtProt and the CAFA3 Challenge.

In 2018, we reported a hybrid pipeline that predicts protein structures with I-TASSER and function with COFACTOR. I-TASSER/COFACTOR achieved Gene Ontology (GO) high prediction accuracies of Fmax = 0.69 and 0.57 for molecular function (MF) and biological process (BP), respectively, on 100 comprehensively annotated proteins. Now we report blinded analyses of newly annotated proteins in the critical assessment of function annotation (CAFA) three function prediction challenge and in neXtProt. For CAFA3 results released in May 2019, our predictions on 267 and 912 human proteins with newly annotated MF and BP terms achieved Fmax = 0.50 and 0.42, respectively, on "No Knowledge" proteins, and 0.51 and 0.74, respectively, on "Limited Knowledge" proteins. While COFACTOR consistently outperforms simple homology-based analysis, its accuracy still depends on template availability. Meanwhile, in neXtProt 2019-01, 25 proteins acquired new function annotation through literature curation at UniProt/Swiss-Prot. Before the release of these curated results, we submitted to neXtProt blinded predictions of free-text function annotation based on predicted GO terms. For 10 of the 25, a good match of free-text or GO term annotation was obtained. These blind tests represent rigorous assessments of I-TASSER/COFACTOR. neXtProt now provides links to precomputed I-TASSER/COFACTOR predictions for proteins without function annotation to facilitate experimental planning on "dark proteins".

A machine-compiled database of genome-wide association studies

Tens of thousands of genotype-phenotype associations have been discovered to date, yet not all of them are easily accessible to scientists. Here, we describe GWASkb, a machine-compiled knowledge base of genetic associations collected from the scientific literature using automated information extraction algorithms. Our information extraction system helps curators by automatically collecting over 6,000 associations from open-access publications with an estimated recall of 60–80% and with an estimated precision of 78–94% (measured relative to existing manually curated knowledge bases). This system represents a fully automated GWAS curation effort and is made possible by a paradigm for constructing machine learning systems called data programming. Our work represents a step towards making the curation of scientific literature more efficient using automated systems.

Comparative Analysis of Public Knowledge Bases for Precision Oncology.

Precision oncology depends on the availability of up-to-date, comprehensive, and accurate information about associations between genetic variants and therapeutic options. Recently, a number of knowledge bases (KBs) have been developed that gather such information on the basis of expert curation of the scientific literature. We performed a quantitative and qualitative comparison of Clinical Interpretations of Variants in Cancer, OncoKB, Cancer Gene Census, Database of Curated Mutations, CGI Biomarkers (the cancer genome interpreter biomarker database), Tumor Alterations Relevant for Genomics-Driven Therapy, and the Precision Medicine Knowledge Base. We downloaded each KB and restructured their content to describe variants, genes, drugs, and gene-drug associations in a common format. We normalized gene names to Entrez Gene IDs and drug names to ChEMBL and DrugBank IDs. For the analysis of clinically relevant gene-drug associations, we obtained lists of genes affected by genetic alterations and putative drug therapies for 113 patients with cancer whose cases were presented at the Molecular Tumor Board (MTB) of the Charité Comprehensive Cancer Center. Our analysis revealed that the KBs are largely overlapping but also that each source harbors a notable amount of unique information. Although some KBs cover more genes, others contain more data about gene-drug associations. Retrospective comparisons with findings of the Charitè MTB at the gene level showed that use of multiple KBs may considerably improve retrieval results. The relative importance of a KB in terms of cancer genes was assessed in more detail by logistic regression, which revealed that all but one source had a notable impact on result quality. We confirmed these findings using a second data set obtained from an independent MTB. To date, none of the existing publicly available KBs on gene-drug associations in precision oncology fully subsumes the others, but all of them exhibit specific strengths and weaknesses. Consideration of multiple KBs, therefore, is essential to obtain comprehensive results.

Trajectories in Argentine Children's Literature: Constancio C. Vigil and Horacio Quiroga

Children's author and publishing entrepreneur Constancio C. Vigil was a Uruguayan who spent most of his working life in Argentina. He was best known for his children's magazine Billiken (1919 to present). Vigil's contemporary and compatriot Horacio Quiroga also made the move across the River Plate and went on to have a transformative impact on Argentine literary culture, in part through his Jungle Tales for Children (1924). Both Quiroga and Vigil aspired to have their works for children accepted as school reading books, recognising the role of school authorities in the formation of the national canon. Vigil and Quiroga's trajectories of inclusion and exclusion, and their extraordinary contribution to the Argentine and Latin American cultural landscape in the first half of the twentieth century, provide a window onto the curation of an Argentine national children's literature at the same time as challenging the very nature of such a category.

Abstract 4158: Dissecting the role of zygosity and lineage in Lynch Syndrome-associated microsatellite Instability

Abstract Lynch syndrome (LS) is an inherited condition leading to an increased risk of developing colorectal cancer and other select malignancies. LS patients have germline alterations in mismatch repair (MMR) genes and their tumors often demonstrate microsatellite instability (MSI). With the advent of immune checkpoint blockade, this is of both prognostic and therapeutic significance. Nevertheless, the factors that dictate the presence of the MSI phenotype in tumors diagnosed in LS patients are poorly understood. We integrated germline pathogenicity with somatic alterations in 17,152 prospectively sequenced advanced cancer patients to determine how zygosity and lineage shape the presence and intensity of the somatic MSI phenotype in LS patients. Overall, we identified 117 LS patients (0.68%) with one of 46 distinct cancer types, 111 of which had sufficient purity for somatic assessment. The tumors of 72% (80/111) of these patients had biallelic inactivation of the germline allele as assessed by integrating high-precision mutant allele fractions with allele-specific DNA copy number analysis or, in select low purity tumors, confirmatory immunohistochemistry. Among patients with biallelic inactivation, 73% (58/80) had MSI positive tumors whereas, only 1/31 (3%) of heterozygous tumors were MSI positive, indicating that biallelic inactivation of the germline allele was obligate to drive the somatic MSI phenotype (p-value=5.4e-12). Lineage appears, however, to condition this dependence of MSI status on biallelic inactivation. Leveraging the prevalence of germline MMR mutations in our cohort, zygosity enrichment, and literature curation of MMR penetrance, we classified cancer types as either conventionally Lynch-associated or not. Notably, despite the presence of biallelic inactivation, MSI was not seen in LS patients whose cancers were not conventionally Lynch-associated such as breast, lung, and thyroid cancers among others. The nature and degree of the MSI phenotype also varied as a function of underlying genotype in these patients. Despite comparable mutational burdens, MSH6 germline carriers that were somatic biallelic had lower MSI scores, lower rates of frameshift indels and higher rates of missense mutations than patients with biallelic mutations in other MMR genes. Collectively, these data suggest that the presence of MSI is dictated by lineage-dependent selection for biallelic inactivation in LS tumors, and emerges to differing degrees driven by the underlying genotype, which together has implications for the immunogenicity of resulting tumors and the biomarker of greatest response to immune checkpoint blockade. By expanding our prospective cohort to >30,000 patients with advanced cancer and integrating clinical response to immunotherapy, we will further explore gene-specific variability in MSI patterns observed in LS patients and its effects on outcome and therapeutic response. Citation Format: Preethi Srinivasan, Chaitanya Bandlamudi, Jinru Shia, Alicia S. Latham, Philip Jonsson, Alexander Penson, Sumit Middha, Jackie Hechtman, Ahmet Zehir, Allison Richards, Shweta Chawan, Yelena Kemel, Diana Mandelker, Liying Zhang, David Hyman, Marc Ladanyi, Mark Robson, Kenneth Offit, David Solit, Barry Taylor, Michael Berger, Zsofia Stadler. Dissecting the role of zygosity and lineage in Lynch Syndrome-associated microsatellite Instability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4158.