Modeling colorectal cancer: A bio-resource of 50 patient-derived organoid lines

结直肠癌建模:50 个患者来源的类器官系的生物资源

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作者:Rebekah M Engel, Thierry Jardé, Karen Oliva, Genevieve Kerr, Wing Hei Chan, Sara Hlavca, David Nickless, Stuart K Archer, Raymond Yap, Pravin Ranchod, Stephen Bell, Ann Niap, Christine Koulis, Ashley Chong, Simon Wilkins, Trevor C Dale, Andrew J Hollins, Paul J McMurrick, Helen E Abud

Aim

Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. To improve outcomes for these patients, we need to develop new treatment strategies. Personalized cancer medicine, where patients are treated based on the characteristics of their own tumor, has gained significant interest for its promise to improve outcomes and reduce unnecessary side effects. The purpose of this study was to examine the potential utility of patient-derived colorectal cancer organoids (PDCOs) in a personalized cancer medicine setting.

Conclusions

Patient-derived colorectal cancer organoids recapitulate characteristics of the tissue from which they are derived and are a powerful tool for cancer research. Further research will determine their utility for predicting patient outcomes in a personalized cancer medicine setting.

Methods

Patient-derived colorectal cancer organoids were derived from tissue obtained from treatment-naïve patients undergoing surgical resection for the treatment of CRC. We examined the recapitulation of key histopathological, molecular, and phenotypic characteristics of the primary tumor.

Results

We created a bio-resource of PDCOs from primary and metastatic CRCs. Key histopathological features were retained in PDCOs when compared with the primary tumor. Additionally, a cohort of 12 PDCOs, and their corresponding primary tumors and normal sample, were characterized through whole exome sequencing and somatic variant calling. These PDCOs exhibited a high level of concordance in key driver mutations when compared with the primary tumor. Conclusions: Patient-derived colorectal cancer organoids recapitulate characteristics of the tissue from which they are derived and are a powerful tool for cancer research. Further research will determine their utility for predicting patient outcomes in a personalized cancer medicine setting.

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