Even though we now know more about cancer than ever, it still outsmarts us and costs 10 million lives globally each year. Cancer occurs when mutated cells start growing uncontrollably and invade healthy tissues. In doing so, malignant cells develop mechanisms to evade the immune system and can even co-opt normal processes to their benefit. The difficulty in dealing with cancer is that, it is not one type of disease and it differs quite a lot from person to person.
A new class of drugs, called immunotherapy, emerged in the last decade and changed the outlook in cancer. Immunotherapy activates the immune system to combat malignant cells and it can lead to clearance of the tumor completely. However, this great new therapy works only for 20-60% of patients, prompting a wide scientific community to seek new approaches and clinical targets. Ultimately, we still don’t know why certain patients respond to treatment and others don’t. Thus, an increased understanding of the mechanisms of tumor immunity is critical for improving the cancer outcomes.
Our lab tries to figure out how noncoding RNAs fit in the picture of tumor immunology. Specifically, we study long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) functioning in tumor cells and in the immune cells. We also develop new algorithms and interfaces to facilitate highthrougput data analysis. The main themes of my lab include:
lncRNAs in tumor immunoevasion
- Using machine learning and data from The Cancer Genome Atlas, we identified lncRNAs whose expression correlates with various immune parameters within human tumors. We systematically manipulate these lncRNAs in melanoma cells (an aggressive form of skin cancer) and investigate their impact on the immunologic outcome.
miRNAs in antitumor T cell responses
- Using various bioinformatic approaches, we selected a set of miRNAs that have potential to regulate various aspects of killer T cell functions. We use state of the art genome editing tools such as CRISPR-Cas9 system to study the roles of specific miRNAs in controlling T cell infiltration into tumors and effector cytokine production.
Bioinformatics and computational biology
- Biological databases hold a massive amount of data that is open to public. Analysis of these data sets using novel computational methods can lead to new hypotheses on the mechanisms of disease. Our work tries to identify molecular signatures that predict immunotherapy responses and the clinical outcomes in cancer. We also develop user friendly analysis interfaces to remove the barriers for biologists to better utilize biological big data.
- We aim to generate chimeric antigen receptor (CAR) T cells in which specific specific noncoding RNAs are expressed. With this approach, we hope to increase the efficacy of CAR-T immunotherapy and obtain better tumor control.
Here are a few snapshots from our lab and the beautiful city of Izmir, where we are located.