Lee Taehee, Rawding Piper A, Bu Jiyoon, Hyun Sunghee, Rou Woosun, Jeon Hongjae, Kim Seokhyun, Lee Byungseok, Kubiatowicz Luke J, Kim Dawon, Hong Seungpyo, Eun Hyuksoo
Department of Biomedical Laboratory Science, Daegu Health College, Daegu 41453, Korea.
Department of Senior Healthcare, Graduate School, Eulji University, Uijeongbu-si 11759, Korea.
Cancers (Basel). 2022 Apr 20;14(9):2061. doi: 10.3390/cancers14092061.
(1) Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Although various serum enzymes have been utilized for the diagnosis and prognosis of HCC, the currently available biomarkers lack the sensitivity needed to detect HCC at early stages and accurately predict treatment responses. (2) Methods: We utilized our highly sensitive cell-free DNA (cfDNA) detection system, in combination with a machine learning algorithm, to provide a platform for improved diagnosis and prognosis of HCC. (3) Results: cfDNA, specifically alpha-fetoprotein (AFP) expression in captured cfDNA, demonstrated the highest accuracy for diagnosing malignancies among the serum/plasma biomarkers used in this study, including AFP, aspartate aminotransferase, alanine aminotransferase, albumin, alkaline phosphatase, and bilirubin. The diagnostic/prognostic capability of cfDNA was further improved by establishing a cfDNA score (cfD), which integrated the total plasma cfDNA levels and cfAFP-DNA expression into a single score using machine learning algorithms. (4) Conclusion: The cfD score demonstrated significantly improved accuracy in determining the pathological features of HCC and predicting patients' survival outcomes compared to the other biomarkers. The results presented herein reveal that our cfDNA capture/analysis platform is a promising approach to effectively utilize cfDNA as a biomarker for the diagnosis and prognosis of HCC.
(1) 背景：肝细胞癌（HCC）是全球癌症相关死亡的主要原因之一。尽管多种血清酶已被用于HCC的诊断和预后评估，但目前可用的生物标志物缺乏早期检测HCC以及准确预测治疗反应所需的敏感性。(2) 方法：我们利用高灵敏度的游离DNA（cfDNA）检测系统，结合机器学习算法，为改善HCC的诊断和预后提供一个平台。(3) 结果：cfDNA，特别是捕获的cfDNA中的甲胎蛋白（AFP）表达，在本研究使用的血清/血浆生物标志物（包括AFP、天冬氨酸转氨酶、丙氨酸转氨酶、白蛋白、碱性磷酸酶和胆红素）中，对诊断恶性肿瘤具有最高的准确性。通过建立cfDNA评分（cfD）进一步提高了cfDNA的诊断/预后能力，该评分使用机器学习算法将血浆总cfDNA水平和cfAFP-DNA表达整合为一个单一分数。(4) 结论：与其他生物标志物相比，cfD评分在确定HCC病理特征和预测患者生存结果方面显示出显著提高的准确性。本文给出的结果表明，我们的cfDNA捕获/分析平台是有效利用cfDNA作为HCC诊断和预后生物标志物的一种有前景的方法。
