Thesis Format
Integrated Article
Degree
Master of Science
Program
Pathology and Laboratory Medicine
Supervisor
Cecchini, Matthew
2nd Supervisor
Brackstone, Muriel
Co-Supervisor
Abstract
Digital pathology holds promise to transform biomarker analysis by improving accuracy, efficiency, and reducing turnaround times with image analysis and artificial intelligence tools. This thesis focuses on the development and utilization of image analysis tools on mismatch repair (MMR) protein in colorectal cancer and tumour infiltrating lymphocytes (TILs) in breast cancer (BC). Using a semi-automated image analysis workflow, we utilize a novel means, tumour to stroma ratio, to objectively classify MMR status. We deployed a similar semi-automated workflow to enumerate TILs. We utilized this to quantify TILs in BC cases treated with neoadjuvant chemotherapy or chemoradiation to explore potential predictors of response to therapy. We identified significance between chemotherapy and high TILs in patients achieving a pathological complete response (pCR). Chemoradiation resulted in increased TILs among patients achieving a pCR. Utilizing semi-automated workflows, it’s possible to augment existing biomarker workflows and novel markers to better prognostication and guide treatment decisions.
Summary for Lay Audience
Our healthcare system is currently under significant strain, with doctors and healthcare professionals managing heavy workloads. Transitioning to digital pathology could help ease this burden by allowing tissues to be assessed more efficiently using automated or semi- automated processes. In this study we focused on two common cancers: colorectal and breast cancer. Both have specific biomarkers—unique characteristics of each cancer—that can guide treatment decisions. For colorectal cancer, one key biomarker is mismatch repair (MMR) status, which can determine the type of treatment a patient will receive. However, the traditional methods for assessing MMR can sometimes be inconsistent, leading to less reliable results. Our research developed a semi-automated method to make this assessment faster and more reliable.
For breast cancer, we’re exploring how the immune system interacts with cancer cells. A new biomarker, called tumour-infiltrating lymphocytes (TILs), is being studied to understand this interaction better. TILs represent immune cells that have entered the tumour area, and they might help us predict how well a patient will respond to treatment. In this study, we developed a digital method to assess TILs more efficiently and compared their levels in patients who received chemotherapy alone versus chemotherapy and radiotherapy. This is the first time TILs have been studied in the context of combined chemoradiotherapy.
We have shown that digital assessments can be used on both biomarkers for accurate and successful semi-automation. We demonstrated that patients with high TILs in their tumour before receiving chemotherapy were more likely to have a complete response to treatment with no cancer cells left at time of surgery. Additionally, in patients who received chemoradiotherapy, we observed even higher levels of TILs in the area where the tumour had been, suggesting that radiotherapy might further enhance the immune system’s response.
Breast and colorectal cancers are among the most common cancers in Canada. The biomarkers we studied have the potential to significantly impact how treatment decisions are made for each patient, possibly leading to better outcomes. Improving the accuracy and efficiency of the assessment of these biomarkers will help clarify the role of these in determining patient treatment and outcomes.
Recommended Citation
Grindrod, Natalie, "The Digital Assessment of Biomarkers in Breast and Colorectal Cancer" (2024). Electronic Thesis and Dissertation Repository. 10659.
https://ir.lib.uwo.ca/etd/10659
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.