Dissecting tumor microenvironments of blood cancers using single-cell expression data

Cancer is a major global issue claiming the lives of millions every year. It is an extremely complex and diverse disease spanning numerous cancer types, however, they are all defined by one specific hallmark: abnormal cell growth. Historically, researchers have focused on the cancer itself, but it is now apparent that several other factors contribute to the disease. Cancer cells and immune cells constantly exert mutual selective pressure on each other during cancer development. Immune cells posses the ability to kill cancer cells, nevertheless cancer cells can escape this by creating immunosuppressive environments. The introduction of immunotherapies has changed the cancer treatment paradigm. Instead of using highly toxic treatment options such as chemotherapy and radiation, immunotherapies aim at unleashing the potential of immune cells to eliminate the cancer cells. Due to varying response rates, there is a strong need for patient stratification in order to determine who will benefit from treatment.
With the advances of single-cell technologies such single-cell RNA (scRNA) sequencing, dissection of heterogeneous cell systems such as the tumor microenvironment is now widely adopted. This thesis is comprised of four studies with a common goal of elucidating various aspects of the tumor microenvironment primarily employing scRNA sequencing. The first study presented highlights transcriptional differences between healthy immune cells and cancer patients with either chronic lymphocytic leukemia (CLL) or the precursor stage thereof.
Secondly, a study seeking to discover the determinants of response in Richter’s syndrome (RS) patients following PD1 checkpoint blockade is presented. This showed that response associated with a CD8+ T cell population marked by the expression of the transcription factor ZNF683 that appeared to regulate key pathways of T cell activation and differentiation.
The third included in this thesis observes no transcriptional changes of the tumor cells of CLL patients going from precursor stage to disease. This is in concordance with the DNA methylation patterns presented in this study, that is detected already at the precursor stage and is persistent through the disease course. Finally, scRNA sequencing was utilized to detect clonal evolution of CLL cells transforming into an aggressive secondary lymphoma, RS. The findings of this study also includes molecular events driving this transformation.