Patient‐derived organoids as a preclinical platform for precision medicine in colorectal cancer

类有机物 结直肠癌 医学 精密医学 个性化医疗 内科学 药品 肿瘤科 癌症 生物信息学 药理学 病理 生物 遗传学
作者
Young-Won Cho,Dong‐Wook Min,Hwang-Phill Kim,Yohan An,Sheehyun Kim,Jeonghwan Youk,Jaeyoung Chun,Jong Pil Im,Sang‐Hyun Song,Young Seok Ju,Sae‐Won Han,Kyu Joo Park,Tae-You Kim
出处
期刊:Molecular Oncology [Elsevier BV]
卷期号:16 (12): 2396-2412 被引量:16
标识
DOI:10.1002/1878-0261.13144
摘要

Patient‐derived organoids are being considered as models that can help guide personalized therapy through in vitro anticancer drug response evaluation. However, attempts to quantify in vitro drug responses in organoids and compare them with responses in matched patients remain inadequate. In this study, we investigated whether drug responses of organoids correlate with clinical responses of matched patients and disease progression of patients. Organoids were established from 54 patients with colorectal cancer who (except for one patient) did not receive any form of therapy before, and tumor organoids were assessed through whole‐exome sequencing. For comparisons of in vitro drug responses in matched patients, we developed an ‘organoid score’ based on the variable anticancer treatment responses observed in organoids. Very interestingly, a higher organoid score was significantly correlated with a lower tumor regression rate after the standard‐of‐care treatment in matched patients. Additionally, we confirmed that patients with a higher organoid score (≥ 2.5) had poorer progression‐free survival compared with those with a lower organoid score (< 2.5). Furthermore, to assess potential drug repurposing using an FDA‐approved drug library, ten tumor organoids derived from patients with disease progression were applied to a simulation platform. Taken together, organoids and organoid scores can facilitate the prediction of anticancer therapy efficacy, and they can be used as a simulation model to determine the next therapeutic options through drug screening. Organoids will be an attractive platform to enable the implementation of personalized therapy for colorectal cancer patients.

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