The Analysis of Platelet-Derived circRNA Repertoire as Potential Diagnostic Biomarker for Non-Small Cell Lung Cancer.
The Analysis of Platelet-Derived circRNA Repertoire as Potential Diagnostic Biomarker for Non-Small Cell Lung Cancer.
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DOI：
10.3390/cancers13184644
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发表时间：
2021-09-16
期刊：
影响因子：
5.2
通讯作者：
Würdinger T
中科院分区：
文献类型：
--
作者：
D'Ambrosi S;Visser A;Antunes-Ferreira M;Poutsma A;Giannoukakos S;Sol N;Sabrkhany S;Bahce I;Kuijpers MJE;Oude Egbrink MGA;Griffioen AW;Best MG;Koppers-Lalic D;Oudejans C;Würdinger T
血小板和癌细胞之间的相互作用在癌症发展和进展的各个步骤中起着重要作用。这些相互作用导致血小板RNA含量的变化，导致肿瘤介导的血小板“教育”。肿瘤训练血小板（TEP）可用作癌症检测和进展监测的非侵入性生物标志物来源。我们的实验室以前已经确定，剪接的mRNA TEP签名提供了关于癌症的存在，位置和分子特征的特定信息。除了mRNA，血小板中还存在其他RNA类型，它们的库可能会受到癌症介导的改变。尽管有证据表明circRNA可能是一种有前途的癌症生物标志物，但它们尚未在癌症患者的血小板中进行分析。在这项概念验证研究中，我们的目标是评估血小板的circRNA签名是否可以用作癌症检测和进展的生物标志物。肿瘤训练的血小板（TEP）已经成为适用于癌症检测的液体活检中癌症相关RNA谱的丰富生物标志物。尽管已经发现人类血小板富含环状RNA（circRNA），但没有研究调查circRNA作为血小板衍生的癌症生物标志物的潜力。在这项概念验证研究中，我们研究了血小板的circRNA签名是否可以用作检测非小细胞肺癌（NSCLC）的液体活检生物标志物。我们使用RNA测序（RNA-Seq）分析了从NSCLC患者和无症状个体收集的血小板样本中提取的总RNA。使用精确的CircRNA finder套件（ACFS）进行已知和新型circRNA的鉴定和定量，然后使用我们的thromboSeq软件的修改版本进行差异转录表达分析。在4732个检测到的circRNA中，我们鉴定出411个circRNA在无症状个体和NSCLC患者之间显著（p值<0.05）差异表达。使用0.05的错误发现率（FDR）作为截止值，我们选择核受体相互作用蛋白1（NRIP1）circRNA（circNRIP1）作为潜在的生物标志物候选物，以通过逆转录-定量PCR（RT-qPCR）进行进一步验证。该分析是在一个独立的血小板样本队列中进行的。RT-qPCR结果证实了RNA-Seq数据分析，NSCLC患者血小板中circNRIP1显著下调。我们的研究结果表明，在血小板中发现的circRNA可能具有使用液体活检检测NSCLC的诊断生物标志物的潜力。
Interaction between blood platelets and cancer cells play an important role in various steps of cancer development and progression. These interactions lead to changes in the platelets’ RNA content, resulting in tumor-mediated “education” of platelets. Tumor-educated platelets (TEPs) can be used as a non-invasive biomarker source for cancer detection and progression monitoring. Our lab has previously identified that spliced mRNA TEP signatures provide specific information on the presence, location, and molecular features of cancers. Next to mRNA, other RNA types are present in platelets, and their repertoire can potentially be subjected to cancer-mediated alterations. Despite the evidence that circRNA could be a promising cancer biomarker, they have not yet been analyzed in blood platelets of cancer patients. In this proof-of-concept study, we aim to evaluate whether platelets’ circRNA signature could be used as a biomarker for cancer detection and progression. Tumor-educated Platelets (TEPs) have emerged as rich biosources of cancer-related RNA profiles in liquid biopsies applicable for cancer detection. Although human blood platelets have been found to be enriched in circular RNA (circRNA), no studies have investigated the potential of circRNA as platelet-derived biomarkers for cancer. In this proof-of-concept study, we examine whether the circRNA signature of blood platelets can be used as a liquid biopsy biomarker for the detection of non-small cell lung cancer (NSCLC). We analyzed the total RNA, extracted from the platelet samples collected from NSCLC patients and asymptomatic individuals, using RNA sequencing (RNA-Seq). Identification and quantification of known and novel circRNAs were performed using the accurate CircRNA finder suite (ACFS), followed by the differential transcript expression analysis using a modified version of our thromboSeq software. Out of 4732 detected circRNAs, we identified 411 circRNAs that are significantly (p-value < 0.05) differentially expressed between asymptomatic individuals and NSCLC patients. Using the false discovery rate (FDR) of 0.05 as cutoff, we selected the nuclear receptor-interacting protein 1 (NRIP1) circRNA (circNRIP1) as a potential biomarker candidate for further validation by reverse transcription–quantitative PCR (RT-qPCR). This analysis was performed on an independent cohort of platelet samples. The RT-qPCR results confirmed the RNA-Seq data analysis, with significant downregulation of circNRIP1 in platelets derived from NSCLC patients. Our findings suggest that circRNAs found in blood platelets may hold diagnostic biomarkers potential for the detection of NSCLC using liquid biopsies.
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影响因子：
14.9
作者：
Enuka Y;Lauriola M;Feldman ME;Sas-Chen A;Ulitsky I;Yarden Y
通讯作者：
Yarden Y
影响因子：
3.3
作者：
Li M;Cai J;Han X;Ren Y
通讯作者：
Ren Y
影响因子：
5.8
作者：
Blandin Knight S;Crosbie PA;Balata H;Chudziak J;Hussell T;Dive C
通讯作者：
Dive C
影响因子：
4
作者：
Hang D;Zhou J;Qin N;Zhou W;Ma H;Jin G;Hu Z;Dai J;Shen H
通讯作者：
Shen H
DOI：
10.1016/j.bbrc.2018.07.164
发表时间：
2018-09-10
影响因子：
3.1
作者：
Li, Yongsheng;Hu, Jiahang;Dong, Xiangmei
通讯作者：
Dong, Xiangmei