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肿瘤及相邻正常组织的综合HLA分型能够揭示肿瘤免疫反应的相关见解。

Integrative HLA typing of tumor and adjacent normal tissue can reveal insights into the tumor immune response.

作者信息

Sverchkova Angelina, Burkholz Scott, Rubsamen Reid, Stratford Richard, Clancy Trevor

机构信息

NEC OncoImmunity, Oslo Cancer Cluster, Innovation Park, Oslo, Norway.

Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

出版信息

BMC Med Genomics. 2024 Jan 27;17(1):37. doi: 10.1186/s12920-024-01808-8.

Abstract

BACKGROUND

The HLA complex is the most polymorphic region of the human genome, and its improved characterization can help us understand the genetics of human disease as well as the interplay between cancer and the immune system. The main function of HLA genes is to recognize "non-self" antigens and to present them on the cell surface to T cells, which instigate an immune response toward infected or transformed cells. While sequence variation in the antigen-binding groove of HLA may modulate the repertoire of immunogenic antigens presented to T cells, alterations in HLA expression can significantly influence the immune response to pathogens and cancer.

METHODS

RNA sequencing was used here to accurately genotype the HLA region and quantify and compare the level of allele-specific HLA expression in tumors and patient-matched adjacent normal tissue. The computational approach utilized in the study types classical and non-classical Class I and Class II HLA alleles from RNA-seq while simultaneously quantifying allele-specific or personalized HLA expression. The strategy also uses RNA-seq data to infer immune cell infiltration into tumors and the corresponding immune cell composition of matched normal tissue, to reveal potential insights related to T cell and NK cell interactions with tumor HLA alleles.

RESULTS

The genotyping method outperforms existing RNA-seq-based HLA typing tools for Class II HLA genotyping. Further, we demonstrate its potential for studying tumor-immune interactions by applying the method to tumor samples from two different subtypes of breast cancer and their matched normal breast tissue controls.

CONCLUSIONS

The integrative RNA-seq-based HLA typing approach described in the study, coupled with HLA expression analysis, neoantigen prediction and immune cell infiltration, may help increase our understanding of the interplay between a patient's tumor and immune system; and provide further insights into the immune mechanisms that determine a positive or negative outcome following treatment with immunotherapy such as checkpoint blockade.

摘要

背景

HLA复合体是人类基因组中多态性最高的区域,对其特征的深入了解有助于我们理解人类疾病的遗传学以及癌症与免疫系统之间的相互作用。HLA基因的主要功能是识别“非自身”抗原,并将其呈递至细胞表面供T细胞识别,从而引发针对受感染或转化细胞的免疫反应。虽然HLA抗原结合槽中的序列变异可能会调节呈递给T细胞的免疫原性抗原库,但HLA表达的改变会显著影响对病原体和癌症的免疫反应。

方法

本研究采用RNA测序技术对HLA区域进行精确基因分型,并对肿瘤组织及与之匹配的癌旁正常组织中等位基因特异性HLA表达水平进行定量和比较。该研究中使用的计算方法可从RNA测序数据中识别出经典和非经典的I类和II类HLA等位基因,同时对等位基因特异性或个性化的HLA表达进行定量。该策略还利用RNA测序数据推断免疫细胞向肿瘤组织的浸润情况以及匹配正常组织的相应免疫细胞组成,以揭示与T细胞和NK细胞与肿瘤HLA等位基因相互作用相关的潜在见解。

结果

该基因分型方法在II类HLA基因分型方面优于现有的基于RNA测序的HLA分型工具。此外,我们通过将该方法应用于两种不同亚型乳腺癌的肿瘤样本及其匹配的正常乳腺组织对照,证明了其在研究肿瘤-免疫相互作用方面的潜力。

结论

本研究中描述的基于RNA测序的综合HLA分型方法,结合HLA表达分析、新抗原预测和免疫细胞浸润分析,可能有助于加深我们对患者肿瘤与免疫系统之间相互作用的理解;并为确定免疫治疗(如检查点阻断)治疗后阳性或阴性结果的免疫机制提供进一步的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafa/10821267/f546d7c172cf/12920_2024_1808_Fig1_HTML.jpg

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