将热点突变与甲基化和片段组图谱相结合,提高多发性癌症的早期检测能力

Thi Hue Hanh Nguyen, Giang Hoang Vu, Tu Thi Nguyen, Tuan Anh Nguyen, Vu Uyen Tran, Luyen Thi Vu, Giang Thi Huong Nguyen, Nhat Duy Nguyen, Trung Hieu Tran, Van Thien Chi Nguyen, Thanh Dat Nguyen, Trong Hieu Nguyen, Dac Ho Vo, Thi Tuong Vi Van, Thanh Thi Do, Minh Phong Le, Le Anh Khoa Huynh, Duy Sinh Nguyen, Hung Sang Tang, Hoai-Nghia Nguyen, Minh-Duy Phan, Hoa Giang, Lan N Tu, Le Son Tran
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引用次数: 0

摘要

背景通过单次血液检测进行多种癌症早期检测(MCED)可大大推进癌症诊断。然而,大多数 MCED 检测都依赖于单一类型的生物标志物,导致灵敏度有限,尤其是对早期癌症而言。我们之前开发了 SPOT-MAS,这是一种基于 ctDNA 的多模态检测方法,通过分析甲基化和片段组图谱来检测五种常见癌症。尽管 SPOT-MAS 很有潜力,但它对早期癌症的灵敏度一般。本研究探讨了将热点突变整合到 SPOT-MAS 中是否能提高其检测率。方法开发了一种靶向扩增子测序方法,用于分析无细胞DNA中的700个热点突变,并将其整合到SPOT-MAS检测中,创建了一个单次抽血工作流程。该工作流程(即 SPOT-MAS Plus)在 255 名非转移性癌症患者(乳腺癌、结直肠癌、胃癌、肝癌和肺癌)和 304 名健康人中进行了回顾性验证。结果255名癌症患者中有131人(51.4%)检出了热点突变,其中肝癌的检出率最高(96.5%),其次是结直肠癌(59.3%)和肺癌(53.7%)。肿瘤突变负荷低的癌症检出率较低,如乳腺癌(31.3%)和胃癌(41.9%)。相比之下,SPOT-MAS 对这些癌症的敏感度更高(乳腺癌为 51.6%,胃癌为 62.9%)。将热点突变与 SPOT-MAS 预测相结合可提高早期癌症检测率,总体灵敏度为 78.5%,特异性为 97.7%。结直肠癌(81.36%)和肺癌(82.9%)的灵敏度有所提高。结论将基因和表观遗传学改变整合到多模式检测中可显著提高各种癌症的早期检测率。为了支持更广泛的临床应用,有必要在更大的队列中进行进一步验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combination of hotspot mutations with methylation and fragmentomic profiles to enhance Multi-Cancer Early Detection
Background Multi-cancer early detection (MCED) through a single blood test significantly advances cancer diagnosis. However, most MCED tests rely on a single type of biomarkers, leading to limited sensitivity, particularly for early-stage cancers. We previously developed SPOT-MAS, a multimodal ctDNA-based assay analyzing methylation and fragmentomic profiles to detect five common cancers. Despite its potential, SPOT-MAS exhibited moderate sensitivities for early-stage cancers. This study investigated whether integrating hotspot mutations into SPOT-MAS could enhance its detection rates. Method A targeted amplicon sequencing approach was developed to profile 700 hotspot mutations in cell-free DNA and integrated into the SPOT-MAS assay, creating a single-blood draw workflow. This workflow, namely SPOT-MAS Plus was retrospectively validated in a cohort of 255 non-metastatic cancer patients (breast, colorectal, gastric, liver, and lung) and 304 healthy individuals. Results Hotspot mutations were detected in 131 of 255 (51.4%) cancer patients, with the highest rates in liver cancer (96.5%), followed by colorectal (59.3%) and lung cancer (53.7%). Lower detection rates were found for cancers with low tumor mutational burden, such as breast (31.3%) and gastric (41.9%) cancers. In contrast, SPOT-MAS demonstrated higher sensitivities for these cancers (51.6% for breast and 62.9% for gastric). The combination of hotspot mutations with SPOT-MAS predictions improved early-stage cancer detection, achieving an overall sensitivity of 78.5% at a specificity of 97.7%. Enhanced sensitivities were observed for colorectal (81.36%) and lung cancer (82.9%). Conclusion The integration of genetic and epigenetic alterations into a multimodal assay significantly enhances the early detection of various cancers. Further validation in larger cohorts is necessary to support broader clinical applications.
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