Investigation of the landscape of immunosequencing and its clinical relevance through novel immunoinformatic approaches
通过新型免疫信息学方法研究免疫测序的前景及其临床相关性
基本信息
- 批准号:10446946
- 负责人:
- 金额:$ 35.24万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-07-01 至 2026-03-31
- 项目状态:未结题
- 来源:
- 关键词:2019-nCoVAdaptive Immune SystemAgonistAntibodiesAntigensArchitectureB cell repertoireB-Cell Antigen ReceptorB-LymphocytesBar CodesBioinformaticsBloodCOVID-19 patientCancer PatientCellsCharacteristicsClinicalComputational TechniqueComputer AnalysisComputer softwareCoronavirusCustomDataDevelopmentDiseaseEnvironmentEpitopesEsophagogastric JunctionEsophagusEvaluationEvolutionFutureGene ExpressionGenerationsGenetic HeterogeneityGoalsGrowthImmuneImmune responseImmunodiagnosticsImmunoglobulinsImmunologic ReceptorsImmunotherapeutic agentImmunotherapyInfectionInvestigationJointsLeadMachine LearningMalignant NeoplasmsMalignant neoplasm of lungMalignant neoplasm of prostateMeasuresMethodsModalityModelingMolecularNatureOutcomePathway AnalysisPatternProbabilityProcessPropertyProvengePythonsResolutionRoleSpecificitySpecimenStatistical MethodsT cell responseT-Cell ReceptorT-LymphocyteTNFRSF5 geneTechniquesTimeTumor ImmunityVirus DiseasesVisualizationVisualization softwareadaptive immune responseanalysis pipelineanalytical toolantigen antibody bindingbasebioinformatics toolbiomarker discoverycancer immunotherapycancer typecell typeclinical prognosticclinically relevantfeature selectionflexibilitygenetic signaturehigh dimensionalityimmunogenicimprovedindividual responsenetwork architecturenext generation sequencingnovelopen sourcepredictive modelingprognosticpublic repositoryreceptorrespiratoryresponders and non-respondersresponsesingle-cell RNA sequencingtooltranscriptometumoruser-friendlyvaccine discovery
项目摘要
PROJECT SUMMARY
The adaptive immune system is responsible for the specific recognition and elimination of antigens originating
from infection and disease. It recognizes antigens via an immense array of antigen-binding antibodies (B-cell
receptors, BCRs) and T-cell receptors (TCRs), the immune repertoire. Because of the enormous breadth of
epitopes recognized by immune repertoires, immune repertoires are extremely diverse and dynamic. Advances
in immune receptor sequencing (Rep-seq), such as next generation sequencing, have driven the quantitative
and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the
immune receptor sequence landscape. However, the current analysis tools lack the ability to track and examine
the dynamic nature of the repertoire across serial time points or correlate with clinical outcomes. We propose to
use network analysis and formulate a novel ensemble feature selection approach, along with other
advanced machine learning techniques and statistical approaches (e.g., Bayesian nonparametric approach
and shrinkage estimation method), to interrogate and measure immune repertoire architecture longitudinally
and in a clinical context. Network analysis is a powerful approach that can help us identify TCRs sharing antigen
specificity and highly mutable BCR, which can help to develop or improve existing immunotherapeutics and
immunodiagnostics. To integrate gene expression data and scRep-seq data in single-cell setting, we propose to
apply the multitable mixed-membership approach to construct a network to increase the resolution of T and
B cell clusters. In addition, we assess the importance of shared clusters by introducing Bayes factor to
incorporate clonal generation probability and real data abundance. B and T cell responses develop in parallel
and influence one another, thus we will further study how BCR/TCR network properties interact, in addition to
assessing their individual response separately. We will implement the proposed methods on multiple studies to
better illustrate the diversity and richness of the data to demonstrate the flexibility and power of the proposed
tools. These studies are unique and generalizable, because they include three cancer types spanning from
immunogenic to non-immunogenic in both metastatic and localized settings with different
immunotherapeutic modalities. In addition, the proposed methods can be used to study immune response to
diseases besides cancer, including respiratory coronaviruses, such as SARS-CoV-2. Therefore, first, we will
investigate the landscape of bulk Rep-seq changes over serial timepoints for prostate cancer patients who
received Sipuleucel-T and COVID-19 patients. We will develop prognostic/prediction model based on network
properties with clinical outcome/characteristics for durvalumab-treated lung cancer patients to elucidate the
clinically prognostic features of the network as well classify SARS-CoV-2 infected patients from healthy donors.
Moreover, based on unique features of single-cell RNA sequencing, we will classify the immune cells and study
the T and B cell responses to immunotherapy (CD40 agonist antibody) for esophageal and gastroesophageal
junction cancer patients. Furthermore, we will develop bioinformatics software by incorporating the proposed
methods and techniques to tackle the complexity of the immunosequencing data in a translational fashion and
provide a comprehensive platform with user-friendly visualization tools.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Li Zhang其他文献
Ramanujan-type congruences for overpartitions modulo 3
模 3 过度划分的拉马努金型同余
- DOI:
10.1216/rmj.2020.50.2257 - 发表时间:
2020 - 期刊:
- 影响因子:0.8
- 作者:
Li Zhang - 通讯作者:
Li Zhang
Li Zhang的其他文献
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{{ truncateString('Li Zhang', 18)}}的其他基金
Investigation of the landscape of immunosequencing and its clinical relevance through novel immunoinformatic approaches
通过新型免疫信息学方法研究免疫测序的前景及其临床相关性
- 批准号:
10651683 - 财政年份:2022
- 资助金额:
$ 35.24万 - 项目类别:
Computational approaches to unravel immune receptor sequencing for cancer immunotherapy
揭示癌症免疫治疗免疫受体测序的计算方法
- 批准号:
10490312 - 财政年份:2021
- 资助金额:
$ 35.24万 - 项目类别:
Computational approaches to unravel immune receptor sequencing for cancer immunotherapy
揭示癌症免疫治疗免疫受体测序的计算方法
- 批准号:
10305538 - 财政年份:2021
- 资助金额:
$ 35.24万 - 项目类别:
Molecular Mechanism Governing Oxygen Signaling and Heme Regulation by Gis1
Gis1 控制氧信号传导和血红素调节的分子机制
- 批准号:
8770294 - 财政年份:2014
- 资助金额:
$ 35.24万 - 项目类别:
Molecular Mechanism Governing Oxygen Signaling and Heme Regulation by Gis1
Gis1 控制氧信号传导和血红素调节的分子机制
- 批准号:
9059941 - 财政年份:2014
- 资助金额:
$ 35.24万 - 项目类别:
Molecular Mechanism Governing Oxygen Signaling and Heme Regulation by Gis1
Gis1 控制氧信号传导和血红素调节的分子机制
- 批准号:
9072488 - 财政年份:2014
- 资助金额:
$ 35.24万 - 项目类别:
An Oxygen-Sensing Network Involving Heme and Chaperones
涉及血红素和伴侣的氧传感网络
- 批准号:
7901855 - 财政年份:2009
- 资助金额:
$ 35.24万 - 项目类别:
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