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用于神经内分泌肿瘤诊断的即用型 PCR 系统的实用性。

Utility of a ready-to-use PCR system for neuroendocrine tumor diagnosis.

机构信息

Wren Laboratories, Branford, Connecticut, United States of America.

Sarah Cannon Molecular Diagnostics, London, United Kingdom.

出版信息

PLoS One. 2019 Jun 27;14(6):e0218592. doi: 10.1371/journal.pone.0218592. eCollection 2019.

Abstract

BACKGROUND

Multigene-based PCR tests are time-consuming and limiting aspects of the protocol include increased risk of operator-based variation. In addition, such protocols are complex to transfer and reproduce between laboratories.

AIMS

Evaluate the clinical utility of a pre-spotted PCR plate (PSP) for a novel multigene (n = 51) blood-based gene expression diagnostic assay for neuroendocrine tumors (NETs).

METHODS

A pilot study (n = 44; 8 controls and 36 NETs) was undertaken to compare CQ, normalized gene expression and algorithm-based output (NETest score). Gene expression was then evaluated between matched blood:tumor tissue samples (n = 7). Thereafter, two prospective sets (diagnostic: n = 167; clinical validation: n = 48, respectively) were evaluated for diagnostic and clinical utility value. Two independent molecular diagnostics facilities were used to assess assay reproducibility and inter-laboratory metrics. Samples were collected (per CLIA protocol) processed to mRNA and cDNA and then either run per standard assay (liquid primers) or on PSPs. Separately, matching plasma samples were analyzed for chromogranin A (CgA). Statistics included non-parametric testing, Pearson-concordance, Predictive Modeling and AUROC analyses.

RESULTS

In the pilot study (n = 44), CQ values were highly concordant (r: 0.82, p<0.0001) and normalized gene expression data significantly related (p<0.0001) (Pearson-pairwise correlation). NETest values were not different (49.7±33 standard vs. 48.5±31.5 PSP) and the overall concordance in output 96%. Predictive modelling confirmed this concordance (F1 score = 0.95). Gene expression levels were highly correlated between blood and tumor tissue (R: 0.71-0.83). In the diagnostic cohort (n = 30 controls, n = 87 non-NET controls, n = 50 NET), NETest was significantly lower (p<0.0001) in controls (11±6.5) and non-NET controls (13±18) than NETs (61±31). The AUROCs were 0.93-0.97 and the diagnostic accuracy was 90-97.5%. As a diagnostic, the PSP-NETest was significantly better than CgA (accuracy: 56%, p<0.0001). For clinical samples, the PSP generated robust and accurate (>96%) scores and was significantly better (p<0.0001) than CgA. The assay protocol was consistent (r: 0.97) and reproducible (co-efficient of variation: 1.3-4.2%) across the two facilities.

CONCLUSION

The PSP protocol for the NETest has been established and prospectively tested in clinical samples. It is highly reproducible, has similar metrics (CV, categorization by control or NET) to the standard PCR assay and generates clinically concordant (>96%) NETest results. Moreover, it functions significantly more accurately than CgA.

摘要

背景

基于多基因的 PCR 检测耗时,且协议限制方面包括增加了基于操作人员的差异风险。此外,此类协议在实验室之间的转移和复制较为复杂。

目的

评估新型多基因(n=51)基于血液的基因表达诊断检测用于神经内分泌肿瘤(NETs)的预点 PCR 板(PSP)的临床实用性。

方法

进行了一项初步研究(n=44;8 个对照和 36 个 NETs),以比较 CQ、归一化基因表达和基于算法的输出(NETest 评分)。然后在匹配的血液:肿瘤组织样本之间评估基因表达(n=7)。此后,分别评估了两个前瞻性组(诊断:n=167;临床验证:n=48)的诊断和临床效用价值。使用两个独立的分子诊断设施来评估检测的重现性和实验室间指标。根据 CLIA 协议采集样本,进行 mRNA 和 cDNA 处理,然后按标准检测(液体引物)或 PSP 运行。此外,分别分析匹配的血浆样本中的嗜铬粒蛋白 A(CgA)。统计分析包括非参数检验、Pearson 一致性、预测建模和 AUROC 分析。

结果

在初步研究(n=44)中,CQ 值高度一致(r:0.82,p<0.0001),归一化基因表达数据显著相关(p<0.0001)(Pearson 成对相关性)。NETest 值没有差异(49.7±33 标准与 48.5±31.5 PSP),输出总体一致性为 96%。预测模型证实了这种一致性(F1 评分=0.95)。血液和肿瘤组织之间的基因表达水平高度相关(R:0.71-0.83)。在诊断队列(n=30 个对照,n=87 个非 NET 对照,n=50 个 NET)中,NETest 在对照组(11±6.5)和非 NET 对照组(13±18)中显著低于 NETs(61±31)(p<0.0001)。AUROCs 为 0.93-0.97,诊断准确性为 90-97.5%。作为诊断,PSP-NETest 明显优于 CgA(准确性:56%,p<0.0001)。对于临床样本,PSP 生成了可靠且准确(>96%)的分数,并且明显优于 CgA(p<0.0001)。该检测方案在两个设施中均具有一致性(r:0.97)和可重复性(变异系数:1.3-4.2%)。

结论

已经建立了用于 NETest 的 PSP 协议,并在临床样本中进行了前瞻性测试。它具有高度的可重复性,具有与标准 PCR 检测相似的指标(CV、通过对照或 NET 分类),并产生临床上一致(>96%)的 NETest 结果。此外,它的功能明显比 CgA 更准确。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2ae/6597157/b55358e9638c/pone.0218592.g001.jpg

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