Understanding resistance and sensitivity to improve cancer treatment

Abstract

Improving cancer therapy requires detailed understanding of factors that are involved in sensitivity and resistance to the treatment. For example, if a specific mutation leads to resistance, we can use it as a biomarker to predict response and stratify patients for specific treatments. This knowledge can be used to design combination therapies that prevent resistance. To find new biomarkers and combination therapies we use functional genetic screens, where we investigate every gene in the genome simultaneously. In this thesis, we use genetic screens to study sensitivity and resistance of cancer cells to different cancer treatments. In chapter 2 we investigated indisulam, a compound which has been tested in clinical trials but abandoned due to low response rates. Indisulam works as a molecular glue, degrading splicing factor RBM39. We show that loss of SRPK1 sensitizes cancer cells to indisulam through accumulation of splicing errors. We also show that loss of CAND1 prevents RBM39 degradation and leads to resistance. Factors such as SRPK1 and CAND1 can be used as potential biomarkers to stratify patients for indisulam treatment. Furthermore, combining indisulam with SRPK1 inhibitors or BCL-xL inhibitors might be a possible therapeutic strategy. In chapter 3 we combined indisulam with CDK4/6 inhibitor palbociclib to induce cancer cell senescence. We performed genetic screens for palbociclib enhancers and validated CDK2 as a top hit. CDK2 knock-out cells treated with palbociclib show markers of senescence. We use indisulam as an indirect CDK2 inhibitor and show induction of senescence in cells treated with palbociclib and indisulam. When testing the combination in mice, a reduction of tumor growth was observed compared to single treatments. We showed that indisulam prevents activation of CDK2 through CCNH downregulation. Induction of senescence could be a new strategy in cancer treatment, as senescent cells gain vulnerabilities that can be targeted. We showed that senescent cells are sensitive to the senolytic ABT-263. Taken together, we showed that palbociclib based senescence induction can be improved by combining it with indisulam. In chapter 4 we investigated factors leading to acquired resistance to immunotherapy. Immune checkpoint blockade (ICB) has gained a lot of attention due to long lasting responses in melanoma patients. However, there is still a large subset of patients that do not benefit from this therapy. We investigated a cohort of melanoma patients treated with anti PD-1, and compared DNA sequences from biopsies at baseline and after relapse. We compiled a list of candidate genes that could be involved in resistance to ICB. Next, we performed a genetic screen using a custom library targeting the candidate genes in melanoma cells co-cultured with T lymphocytes. We showed that loss of antigen presentation due to disruption of B2M leads to resistance to T-cell killing. To further improve the understanding of the interaction of tumor cells and the immune system new models are needed. We show examples of genetic screens that uncovered new factors of sensitivity and resistance to various types of cancer treatments which can lead to biomarkers and combination treatment strategies and improve precision oncology.