Prediction and prioritization of neoantigens: integration of RNA sequencing data with whole-exome sequencing.
Prediction and prioritization of neoantigens: integration of RNA sequencing data with whole-exome sequencing.
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新抗原的预测和优先排序：RNA 测序数据与全外显子组测序的整合。
DOI：
10.1111/cas.13131
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发表时间：
2017-02
期刊：
影响因子：
5.7
通讯作者：
Kakimi K
中科院分区：
文献类型：
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作者：
Karasaki T;Nagayama K;Kuwano H;Nitadori JI;Sato M;Anraku M;Hosoi A;Matsushita H;Takazawa M;Ohara O;Nakajima J;Kakimi K
新抗原对癌症免疫的重要性现在已得到公认。然而，存在用于预测和优先化候选新抗原的不同策略，因此报告的新抗原负荷变化很大。为了澄清这个问题，我们比较了目前使用的四种策略预测的新抗原候选物的数量。对四名非小细胞肺癌患者进行全外显子组测序和RNA测序（RNA-Seq）。我们鉴定了361个体细胞错义突变，其中使用MHC I类结合亲和力预测软件（策略I）预测了224个候选新抗原。其中，207个超过了基因表达的设定阈值（每百万个片段映射的转录物的每个酶的片段≥1），产生了124个候选新抗原（策略II）。为了验证突变体mRNA表达，对来自肿瘤cDNA的扩增子（包括每种突变）进行测序; 207个突变中的204个成功测序，产生121个突变体mRNA序列，产生75个候选新抗原（策略III）。从RNA-Seq中提取序列信息，以确认突变mRNA的存在。对于207个突变中的117个，在RNA-Seq中发现变异等位基因频率≥0.04，并认为在肿瘤中表达，最终预测了72个候选新抗原（策略IV）。在没有额外的cDNA扩增子测序的情况下，策略IV与策略III相当。因此，我们提出策略IV作为一种实用和适当的策略，充分利用目前可用的信息来预测候选新抗原。值得注意的是，根据所应用的策略，从相同的肿瘤推导出不同的新抗原负荷。
The importance of neoantigens for cancer immunity is now well‐acknowledged. However, there are diverse strategies for predicting and prioritizing candidate neoantigens, and thus reported neoantigen loads vary a great deal. To clarify this issue, we compared the numbers of neoantigen candidates predicted by four currently utilized strategies. Whole‐exome sequencing and RNA sequencing (RNA‐Seq) of four non‐small‐cell lung cancer patients was carried out. We identified 361 somatic missense mutations from which 224 candidate neoantigens were predicted using MHC class I binding affinity prediction software (strategy I). Of these, 207 exceeded the set threshold of gene expression (fragments per kilobase of transcript per million fragments mapped ≥1), resulting in 124 candidate neoantigens (strategy II). To verify mutant mRNA expression, sequencing of amplicons from tumor cDNA including each mutation was undertaken; 204 of the 207 mutations were successfully sequenced, yielding 121 mutant mRNA sequences, resulting in 75 candidate neoantigens (strategy III). Sequence information was extracted from RNA‐Seq to confirm the presence of mutated mRNA. Variant allele frequencies ≥0.04 in RNA‐Seq were found for 117 of the 207 mutations and regarded as expressed in the tumor, and finally, 72 candidate neoantigens were predicted (strategy IV). Without additional amplicon sequencing of cDNA, strategy IV was comparable to strategy III. We therefore propose strategy IV as a practical and appropriate strategy to predict candidate neoantigens fully utilizing currently available information. It is of note that different neoantigen loads were deduced from the same tumors depending on the strategies applied.