Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Clin Transl Med. 2024 Aug;14(8):e1778. doi: 10.1002/ctm2.1778.
Recent advances in molecular analyses of ovarian cancer have revealed a wealth of promising tumour-specific biomarkers, including protein, DNA mutations and methylation; however, reliably detecting such alterations at satisfactorily high sensitivity and specificity through low-cost methods remains challenging, especially in early-stage diseases. Here we present PapDREAM, a new approach that enables detection of rare, ovarian-cancer-specific aberrations of DNA methylation from routinely-collected cervical Pap specimens. The PapDREAM approach employs a microfluidic platform that performs highly parallelized digital high-resolution melt to analyze locus-specific DNA methylation patterns on a molecule-by-molecule basis at or near single CpG-site resolution at a fraction (< 1/10th) of the cost of next-generation sequencing techniques. We demonstrate the feasibility of the platform by assessing intermolecular heterogeneity of DNA methylation in a panel of methylation biomarker loci using DNA derived from Pap specimens obtained from a cohort of 43 women, including 18 cases with ovarian cancer and 25 cancer-free controls. PapDREAM leverages systematic multidimensional bioinformatic analyses of locus-specific methylation heterogeneity to improve upon Pap-specimen-based detection of ovarian cancer, demonstrating a clinical sensitivity of 50% at 99% specificity in detecting ovarian cancer cases with an area under the receiver operator curve of 0.90. We then establish a logistic regression model that could be used to identify high-risk patients for subsequent clinical follow-up and monitoring. The results of this study support the utility of PapDREAM as a simple, low-cost screening method with the potential to integrate with existing clinical workflows for early detection of ovarian cancer. KEY POINTS: We present a microfluidic platform for detection and analysis of rare, heterogeneously methylated DNA within Pap specimens towards detection of ovarian cancer. The platform achieves high sensitivity (fractions <0.00005%) at a suitably low cost (∼$25) for routine screening applications. Furthermore, it provides molecule-by-molecule quantitative analysis to facilitate further study on the effect of heterogeneous methylation on cancer development.
最近在卵巢癌的分子分析方面取得了进展,揭示了丰富的有前途的肿瘤特异性生物标志物,包括蛋白质、DNA 突变和甲基化;然而,通过低成本的方法可靠地以令人满意的高灵敏度和特异性检测到这些改变仍然具有挑战性,尤其是在早期疾病中。在这里,我们提出了 PapDREAM,这是一种新方法,能够从常规收集的宫颈 Pap 标本中检测到罕见的卵巢癌特异性 DNA 甲基化异常。PapDREAM 方法采用微流控平台,通过高度并行化的数字高分辨率熔解,以分子为基础,在接近单个 CpG 位点的分辨率(<1/10 成本)分析分子特异性 DNA 甲基化模式。我们通过使用来自 43 名女性队列的 Pap 标本中获得的 DNA 评估了一组甲基化生物标志物基因座的分子间 DNA 甲基化异质性,证明了该平台的可行性,其中包括 18 例卵巢癌病例和 25 例无癌对照。PapDREAM 利用系统的多维生物信息学分析来改善基于 Pap 标本的卵巢癌检测,在以 99%特异性检测卵巢癌病例时,灵敏度为 50%,接收器操作曲线下的面积为 0.90。然后,我们建立了一个逻辑回归模型,可以用于识别高危患者进行后续的临床随访和监测。这项研究的结果支持 PapDREAM 作为一种简单、低成本的筛查方法的实用性,它有可能与现有的临床工作流程相结合,用于早期发现卵巢癌。关键点:我们提出了一种用于检测和分析 Pap 标本中罕见的、异质性甲基化 DNA 的微流控平台,以检测卵巢癌。该平台以合适的低成本(约 25 美元)实现了高灵敏度(<0.00005%),适用于常规筛查应用。此外,它提供了分子水平的定量分析,有助于进一步研究异质性甲基化对癌症发展的影响。