PhD defence by Camilla Koldbæk Lemvigh

On Friday 1 December 2023, Camilla Koldbæk Lemvigh will defend her PhD thesis "Dissecting tumor microenvironments of blood cancers using single-cell expression data".

Time: 13:00

Place: Building 101, Meeting Room 1 & zoom: https://dtudk.zoom.us/meeting/register/u5Aqf-ispjMvEtCFwjCnLqGkIVnsw0auI6-C

Please be aware that the PhD defense may be recorded - This will also be informed at the beginning of the PhD defense.

Supervisor: Associate Professor Lars Rønn Olsen

Co-supervisor: Professor Catherine J. Wu, Dana-Farber Cancer Institute

Assessment committee:
Associate Professor Kedar Natarajan, DTU Bioengineering
Professor Joel Stern, Hofstra University
Head of bioinformatics Nicolas Rapin, National Genome Center

Chairperson:
Professor Ole Lund, DTU Health Technology

Abstract:
Cancer is one of the leading causes of deaths worldwide, and the cancer burden is continuously growing globally despite massive amounts of new discoveries, therapies, and general research. Conventional cancer therapies include radiation and chemotherapy; however, these are associated with severe side effects including damages to healthy cells. Introducing immunotherapies as a novel strategy towards combatting cancer has revolutionized treatments of several cancer types. Immunotherapies aim at harnessing the body’s own immune system to eradicate the cancer cells in a tumor-specific way, thus minimizing side effects. Specifically, immune checkpoint blockade (CPB) therapies have shown great clinical responses. Cancers can create an immunosuppressive environment, where CPB sets out to reverse this and thus unleash the potential of effector immune cells. A lot of efforts have been put into predictions of responders to these treatments and the mechanisms underlying, but for many cancer types this is still unknown.

The interplay between cancer cells, immune cells and immunotherapies is extremely complex and continuous. This thesis presents and discusses aspects of the bioinformatic analysis within this interplay. The results of four studies are presented and discussed: firstly, a study profiling the immune cells using single-cell expression. The immune cells originate from cancer patients enrolled in a clinical trial receiving to identify novel biomarkers of response. This highlights the importance of profiling such heterogenous systems at single-cell resolution. Next, a case example of how immune cells in cancer patients diverge from healthy immune cells is shown along with a discussion of the importance of sample handling. Moreover, two studies profiling the cancer cells are presented.

Finally, the learnings on profiling immune and cancer cells with bioinformatic tools along with suggestions for future directions is proposed.