保存细胞学上清液中的 cfRNA,用于非小细胞肺癌患者的 cfDNA 和 cfRNA 双重检测。

IF 2.9 2区 医学 Q2 ONCOLOGY Cancer Medicine Pub Date : 2024-09-05 DOI:10.1002/cam4.70197
Yidan Ma, Yifei Wang, Lei He, Jun Du, Lin Li, Zhixin Bie, Yuanming Li, Xiaomao Xu, Wei Zhou, Xiaonan Wu, Li Yang, Jing Di, Chenyang Li, Xiaoguang Li, Dongge Liu, Zheng Wang
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引用次数: 0

摘要

背景:来自各种细胞学样本(包括体腔渗出液、痰液、支气管肺泡灌洗液(BALF)和针吸液)的上清液已通过验证,可用于使用无细胞DNA(cfDNA)检测非小细胞肺癌(NSCLC)患者的基因改变。然而,融合变异检测的灵敏度仍然具有挑战性。保护无细胞 RNA(cfRNA)对解决这一问题至关重要:方法:采用保护液(PS)保存细胞学上清液(CS)中的 cfRNA,并通过反转录定量聚合酶链反应(RT-qPCR)的周期阈值(CT)来评估受保护的 cfRNA 的质量。此外,我们还收集了一组来自84名NSCLC患者的恶性细胞学样本和匹配肿瘤样本,通过RT-qPCR的多基因突变检测验证了cfDNA和cfRNA的提取和驱动基因突变的双重检测:在最佳保护系统下,91.0%(101/111)的 cfRNA 得到了有效保护。在 84 份 NSCLC 患者样本中,有 7 份细胞学样本未通过检测。与肿瘤样本相比,上清液 cfDNA 和 cfRNA 检测驱动基因的总体灵敏度和特异性分别为 93.8%(74/77)和 100%(77/77)。值得注意的是,当只关注融合基因变化的患者时,EML4-ALK、ROS1、RET融合和MET ex14跳变的敏感性和特异性均达到100%(11/11):这些发现表明,本研究推荐的 cfDNA 和 cfRNA 提取及双重检测策略提高了驱动基因突变检测的准确性,尤其是基于 RNA 的检测。
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Preservation of cfRNA in cytological supernatants for cfDNA & cfRNA double detection in non-small cell lung cancer patients

Backgroud

Supernatants from various cytological samples, including body cavity effusion, sputum, bronchoalveolar lavage fluid (BALF), and needle aspiration, have been validated for detecting genetic alterations using cell-free DNA (cfDNA) in patients with non-small cell lung cancer (NSCLC). However, the sensitivity of fusion variations detection remains challenging. The protection of cell-free RNA (cfRNA) is critical for resolving the issue.

Methods

A protective solution (PS) was applied for preserving cfRNA in cytological supernatant (CS), and the quality of protected cfRNA was assessed by cycle threshold (CT) values from reverse transcription quantitative polymerase chain reaction (RT-qPCR). Furthermore, we collected an additional set of malignant cytological and matched tumor samples from 84 NSCLC patients, cfDNA & cfRNA extraction and double detection for driver gene mutations was validated using the multi-gene mutations detection by RT-qPCR.

Results

Under the optimal protection system, 91.0% (101/111) of cfRNA were protected effectively. Among the 84 NSCLC patient samples, seven cytological samples failed the tests. In comparison with tumor samples, the overall sensitivity and specificity of detecting driver genes of supernatant cfDNA and cfRNA were 93.8% (74/77) and 100% (77/77), respectively. Notably, when focusing exclusively on patients with fusion gene changes, both sensitivity and specificity reached 100% (11/11) for EML4-ALK, ROS1, RET fusions, and MET ex14 skipping.

Conclusion

These findings suggest that cfDNA & cfRNA extraction and double detection strategy recommended in this study improve the accuracy of driver genes mutations test, especially for RNA-based assay.

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来源期刊
Cancer Medicine
Cancer Medicine ONCOLOGY-
CiteScore
5.50
自引率
2.50%
发文量
907
审稿时长
19 weeks
期刊介绍: Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.
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