Łukasiewicz Marta, Pastuszak Krzysztof, Łapińska-Szumczyk Sylwia, Różański Robert, Veld Sjors G J G In 't, Bieńkowski Michał, Stokowy Tomasz, Ratajska Magdalena, Best Myron G, Würdinger Thomas, Żaczek Anna J, Supernat Anna, Jassem Jacek
Laboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, Medical University of Gdańsk, 80-211 Gdańsk, Poland.
Department of Algorithms and Systems Modelling, Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, Poland.
Cancers (Basel). 2021 Nov 16;13(22):5731. doi: 10.3390/cancers13225731.
Liquid biopsy is a minimally invasive collection of a patient body fluid sample. In oncology, they offer several advantages compared to traditional tissue biopsies. However, the potential of this method in endometrial cancer (EC) remains poorly explored. We studied the utility of tumor educated platelets (TEPs) and circulating tumor DNA (ctDNA) for preoperative EC diagnosis, including histology determination.
TEPs from 295 subjects (53 EC patients, 38 patients with benign gynecologic conditions, and 204 healthy women) were RNA-sequenced. DNA sequencing data were obtained for 519 primary tumor tissues and 16 plasma samples. Artificial intelligence was applied to sample classification.
Platelet-dedicated classifier yielded AUC of 97.5% in the test set when discriminating between healthy subjects and cancer patients. However, the discrimination between endometrial cancer and benign gynecologic conditions was more challenging, with AUC of 84.1%. ctDNA-dedicated classifier discriminated primary tumor tissue samples with AUC of 96% and ctDNA blood samples with AUC of 69.8%.
Liquid biopsies show potential in EC diagnosis. Both TEPs and ctDNA profiles coupled with artificial intelligence constitute a source of useful information. Further work involving more cases is warranted.
液体活检是对患者体液样本进行的微创采集。在肿瘤学领域，与传统组织活检相比，它具有多个优势。然而，该方法在子宫内膜癌（EC）中的潜力仍未得到充分探索。我们研究了肿瘤衍生血小板（TEP）和循环肿瘤DNA（ctDNA）在EC术前诊断中的效用，包括组织学判定。
对295名受试者（53例EC患者、38例患有良性妇科疾病的患者和204名健康女性）的TEP进行RNA测序。获取了519份原发性肿瘤组织和16份血浆样本的DNA测序数据。应用人工智能进行样本分类。
在区分健康受试者和癌症患者时，血小板专用分类器在测试集中的曲线下面积（AUC）为97.5%。然而，区分子宫内膜癌和良性妇科疾病更具挑战性，AUC为84.1%。ctDNA专用分类器区分原发性肿瘤组织样本的AUC为96%，区分ctDNA血液样本的AUC为69.8%。
液体活检在EC诊断中显示出潜力。TEP和ctDNA图谱与人工智能相结合构成了有用信息的来源。有必要开展涉及更多病例的进一步研究。
