Bioinformatics Technology to Characterize Tumor Infiltrating Immune Repertoires

项目总结 肿瘤浸润性T细胞和B细胞是肿瘤免疫信息的丰富来源 并提供对癌症免疫治疗靶点的见解。已经做出了努力来描述B/T 在实体肿瘤中使用细胞分选和定向深度测序的细胞谱。然而，这些 方法可能会在组织解聚过程中产生有偏见的估计，并且当应用于 大样本队列。大规模并行mna测序(rna-seq)技术已成为主流。 基因表达谱方法和数以千计的实体肿瘤rna-seq谱在公众中可用。 域。丰富的肿瘤rna-seq数据集为研究肿瘤的浸润性提供了另一种方法。 实体瘤中的B/T细胞亚群。我们团队最近开发了一种用于去卷积的统计方法定时器 肿瘤微环境中的不同免疫成分，以及推断高变量的可信度 肿瘤浸润性T细胞受体(TCR)谱系的互补决定区(CDR) 公共领域的肿瘤RNA-seq数据。 我们的初步分析表明，大约有十倍于B细胞受体(BCR)的读数 和TCR读数，这表明从大宗肿瘤RNA-SEQ中提取BCR谱系可能揭示出重要的 关于B细胞介导的肿瘤免疫的见解。该方案的目的是：将我们的信任算法扩展到 从肿瘤RNA-seq数据中提取B细胞受体(BCR)谱系，并鉴定体细胞超突变和 免疫球蛋白类开关(目标1)：系统分析大型肿瘤的TCR和BCR谱系 Rna-seq队列，并开发用户友好的Web界面，以允许癌症免疫学家或免疫肿瘤学家 研究肿瘤免疫相关性(目标2)；通过以下途径促进肿瘤免疫资源的利用 协作、云共享和扩展(目标3)。 我们将提供一种稳健的生物信息学算法来系统地从实体肿瘤中识别BCR/TCR谱系 RNA-SEQ数据和用户友好的资源，供癌症免疫学家或免疫肿瘤学家探索肿瘤- 来自公众的大型肿瘤特征队列及其未发表数据的免疫相互作用。这个 这项提议的成功执行有可能为癌症免疫疗法的临床实践提供信息， 包括过继T细胞转移、治疗性癌症疫苗或抗体。我们提议的癌症免疫学 算法和资源将是Information开发的一系列生物信息学工具的独特补充 美国国家癌症研究所癌症研究技术中心。

PROJECT SUMMARY The repertoires of tumor-infiltrating T cells and B cells are rich sources of information about cancer-immune interactions and provide insights on cancer immunotherapy targets. Efforts have been made to characterize B/T cell repertoires in solid tumors using cell sorting followed by targeted deep sequencing. However, these approaches may produce biased estimates during tissue disaggregation and can be expensive when applied to large sample cohorts. Massively parallel mRNA sequencing (RNA-seq) technology has become the mainstream method to profile gene expression and thousands of solid tumor RNA-seq profiles are available in the public domain. The rich collection of tumor RNA-seq datasets provides an alternative approach to study tumor-infiltrating B/T cell repertoires in solid tumors. Our team has recently developed a statistical method TIMER for deconvolving different immune components in the tumor microenvironment, and TRUST for inferring the hypervariable complementarity determining regions (CDRs) of the tumor infiltrating T cell receptor (TCR) repertoire from bulk tumor RNA-seq data in the public domain. Our preliminary analysis indicated that there are approximately ten times as many B cell receptor (BCR) reads and TCR reads, suggesting that extracting the BCR repertoires from bulk tumor RNA-seq could reveal important insights on B cell mediated tumor immunity. The aims of this proposal are: to extend our TRUST algorithm to extract B cell receptor (BCR) repertoires from tumor RNA-seq data, and identify somatic hypermutations and immunoglobin class switches (Aim 1); to systematically analyze TCR and BCR repertoires from large scale tumor RNA-seq cohorts, and develop a user friendly web interface to allow cancer immunologists or immuno-oncologists to investigate tumor-immune associations (Aim 2); to promote the utility of our tumor immune resource through collaborations, cloud sharing, and outreach (Aim 3). We will deliver a robust bioinformatics algorithm to systematically identify BCR / TCR repertoires from bulk tumor RNA-seq data and a user-friendly resource for cancer immunologists or immuno-oncologists to explore tumor- immune interactions from large tumor profiling cohorts in the public as well as their unpublished data. The successful execution of this proposal has the potential to inform clinical practice of cancer immunotherapies, including adoptive T cell transfer, therapeutic cancer vaccines or antibodies. Our proposed cancer immunology algorithm and resource will be a unique addition to the array of bioinformatics tools developed by the Information Technology for Cancer Research at the National Cancer Institute.