Abstract
During my PhD, we investigated different methods of personalised treatment for patients with metastatic colorectal cancer. The challenge is to use treatment in the most precise manner possible to improve life expectancy and quality of life. Currently, it is difficult to predict which treatment is best for an individual patient.
Patients with mismatch repair deficient (dMMR) tumours respond very well to immunotherapy. Further improvements can be achieved by understanding why these patients do not benefit from chemotherapy and targeted treatment. Our results show that there is insufficient clinical evidence that any particular type of chemotherapy or targeted treatment is more effective in these patients. Moreover, dMMR organoids had similar sensitivity to these treatments as other organoids. This suggests that environmental factors play a role in insensitivity to treatment.
Organoids may offer a tailored treatment strategy for patients with cancer. We evaluated previous studies and confirmed that organoids predict treatment response in patients. In our study with colorectal cancer organoids, we were able to predict patient response to chemotherapy through organoid response with a high sensitivity and specificity.
Prediction models can provide information about an expected treatment outcome. Our results show that existing prediction models for patients receiving treatment for liver metastases or who received trifluridine/tipiracil should be improved. We developed a new prediction model for patients undergoing treatment for liver metastases to estimate the likelihood of disease recurrence outside the liver.
These results will contribute to more personalised treatment for patients with colorectal cancer.
Patients with mismatch repair deficient (dMMR) tumours respond very well to immunotherapy. Further improvements can be achieved by understanding why these patients do not benefit from chemotherapy and targeted treatment. Our results show that there is insufficient clinical evidence that any particular type of chemotherapy or targeted treatment is more effective in these patients. Moreover, dMMR organoids had similar sensitivity to these treatments as other organoids. This suggests that environmental factors play a role in insensitivity to treatment.
Organoids may offer a tailored treatment strategy for patients with cancer. We evaluated previous studies and confirmed that organoids predict treatment response in patients. In our study with colorectal cancer organoids, we were able to predict patient response to chemotherapy through organoid response with a high sensitivity and specificity.
Prediction models can provide information about an expected treatment outcome. Our results show that existing prediction models for patients receiving treatment for liver metastases or who received trifluridine/tipiracil should be improved. We developed a new prediction model for patients undergoing treatment for liver metastases to estimate the likelihood of disease recurrence outside the liver.
These results will contribute to more personalised treatment for patients with colorectal cancer.
| Original language | English |
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| Award date | 22 Dec 2022 |
| Place of Publication | Utrecht |
| Publisher | |
| Print ISBNs | 978-94-6458-660-2 |
| DOIs | |
| Publication status | Published - 22 Dec 2022 |
Keywords
- colorectal cancer
- metastatic
- treatment
- personalized
- organoids
- prediction models