Whole-Blood Gene Expression Profiles Correlate with Response to Immune Checkpoint Inhibitors in Patients with Metastatic Renal Cell Carcinoma.
Whole-Blood Gene Expression Profiles Correlate with Response to Immune Checkpoint Inhibitors in Patients with Metastatic Renal Cell Carcinoma.
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DOI：
10.3390/cancers14246207
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发表时间：
2022-12-15
期刊：
影响因子：
5.2
通讯作者：
Nishiyama, Hiroyuki
中科院分区：
文献类型：
--
作者：
Nagumo, Yoshiyuki;Kandori, Shuya;Kojima, Takahiro;Hamada, Kazuki;Nitta, Satoshi;Chihara, Ichiro;Shiga, Masanobu;Negoro, Hiromitsu;Mathis, Bryan J.;Nishiyama, Hiroyuki
一些转移性肾细胞癌(MRCC)患者对免疫检查点抑制物(ICI)治疗无效。然而，由于预测谁的反应不佳是困难的，迫切需要一种非侵入性的、高分辨率的基因组生物标记物来准确预测ICIS的临床反应。我们发现至少有14个基因会随着治疗而改变，这个小组可以用来准确地对有反应的患者进行分类。我们的结果表明，全血转录组方法确定的基因特征是预测肾细胞癌患者ICI反应的临床有用的生物标记物。在转移性肾细胞癌(MRCC)中，临床对免疫检查点抑制剂(ICIS)的反应仅限于一小部分患者，因此需要确定非侵入性的、基于血液的、可预测的反应生物标志物。在使用ipilimumab(IPI)和/或nivolumab(Nivo)之前，我们对49名mRCC患者的前瞻性全血样本进行了RNA测序，以确定基因表达谱是否与疗效相关。对33例完全缓解(n=5)、部分缓解(n=14)和进展(n=14)的肾细胞癌患者的分析表明，与免疫应答相关的460个差异表达基因(Deg)在应答组和无应答组之间有显著差异。从最初的460个DEG中产生的一组14个基因准确地对应答者进行了分类(敏感度94.7%和特异度50.0%)，而共识聚类定义了具有显著不同应答率的簇(92.3%和35.0%)。这些分组结果在包括另外16名SD患者(49名患者)的队列中重复：应答率分别为95.8%和48.0%。总的来说，来自接受ICIS治疗的mRCC患者的全血基因表达谱在反应和使用免疫反应度对应答患者进行准确分类的分级聚类方面明显不同。这些结果表明，这种筛查可以作为预测肾细胞癌患者ICI反应的指标。
Some metastatic renal cell carcinoma (mRCC) patients do not respond to immune checkpoint inhibitor (ICI) therapy. However, since predicting who will be a poor responder is difficult, a non-invasive, high-resolution genomic biomarker to accurately predict clinical responses to ICIs is urgently required. We found a minimum set of 14 genes that change in response to treatment and this panel can be used to accurately classify responder patients. Our results suggest that the gene signatures identified from a whole-blood transcriptome approach are clinically useful biomarkers for predicting ICI responses in patients with mRCC. In metastatic renal cell carcinoma (mRCC), the clinical response to immune checkpoint inhibitors (ICIs) is limited in a subset of patients and the need exists to identify non-invasive, blood-based, predictive biomarkers for responses. We performed RNA sequencing using whole-blood samples prospectively collected from 49 patients with mRCC prior to the administration of ipilimumab (IPI) and/or nivolumab (NIVO) to determine whether gene expression profiles were associated with responses. An analysis from 33 mRCC patients with complete responses (n = 5), partial responses (n = 14), and progressive disease (n = 14) showed 460 differentially expressed genes (DEGs) related to immune responses between the responder and non-responder groups with significant differences. A set of 14 genes generated from the initial 460 DEGs accurately classified responders (sensitivity 94.7% and specificity 50.0%) while consensus clustering defined clusters with significantly differing response rates (92.3% and 35.0%). These clustering results were replicated in a cohort featuring 16 additional SD patients (49 total patients): response rates were 95.8% and 48.0%. Collectively, whole-blood gene expression profiles derived from mRCC patients treated with ICIs clearly differed by response and hierarchical clustering using immune response DEGs accurately classified responder patients. These results suggest that such screening may serve as a predictor for ICI responses in mRCC patients.
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