BMC Medical GenomicsBioinformaticsPeer-reviewed journal article
A Novel Neoantigen Discovery Approach based on Chromatin High Order Conformation
Yi Y. ShiiD, Mingxuan ZhangiD, Luming MengiD, Xianbin SuiD, Xueying ShangiD, Zehua GuoiD, Qingjiao LiiD, Mengna Lin, Xin ZouiD, Qing LuoiD, Yaoliang Yu, Yanting WuiD, Lin‐Tai DaiD, Tom Weidong Cai, Guang HeiD, Ze‐Guang HaniD
Abstract
The high-throughput sequencing technology has yielded reliable and ultra-fast sequencing for DNA and RNA. For tumor cells of cancer patients, when combining the results of DNA and RNA sequencing, one can identify potential neoantigens that stimulate immune response of the T cells. However, when the somatic mutations are abundant, it is computationally challenging to efficiently prioritize the identified neoantigen candidates according to their ability of activating the T cell immuno-response. Numerous prioritization or prediction approaches have been proposed to address this issue but none of them considers the original DNA loci of the neoantigens from the perspective of 3D genome. Here we retrospect the DNA origins of the immune-positive and non-negative neoantigens in the context of 3D genome and discovered that 1) DNA loci of the immuno-positive neoantigens tend to cluster genome-wise. 2) DNA loci of the immuno-positive neoantigens tend to belong to active chromosomal compartment (compartment A) in some chromosomes. 3). DNA loci of the immuno-positive neoantigens tend to locate at specific regions in the 3D genome. We believe that the 3D genome information will help more precise neoantigen prioritization and discovery and eventually benefit precision and personalized medicine in cancer immunotherapy.
- organism: human
- assay: whole-genome sequencing
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: variant effect prediction
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 4
- FWCI
- 0.18
- Field percentile
- 50th percentile
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