Scientific Context of the Project

Immunotherapy has changed the outlook in advanced cancers, but not all patients benefit from the treatment. Although the correlates of a productive antitumor immune response have been recently reported, ultimately it remains unknown why some patients fail to respond immunotherapeutics, suggesting key regulatory mechanisms within the tumor immune microenvironment remains to be determined. This project will focus on long non-coding RNAs (lncRNAs), a major component of human transcriptome, as predictors of immunotherapy response and clinical outcome in cancer. By using large amounts of publicly available data and various machine learning algorithms, we will investigate molecular patterns that are strongly associated with clinically relevant parameters in human cancers of various origins, and experimentally study particular lncRNA candidates in order to reveal novel mechanisms of antitumor immunity. This work will advance our knowledge of how the immune system responds to cancer and it will have applications in predictive biomarker development and therapeutic target discovery in cancer. Importantly, trainees participating into this project will strongly enhance their professional competitiveness by gaining essential skills at the intersection of tumor biology, immunology, and computational biology, and they will be able to prepare themselves for a successful career in science. Excellent mentors and the advanced infrastructures of two collaborating biomedical research institutions will optimally position trainees to investigate clinically important mechanisms while residing in a vibrant city that offers many exciting opportunities for extracurricular activities.

Innovative Aspects of the Project

This project brings together experts in multiple disciplines: noncoding RNA biology, immunology, and bioinformatics. The multifaceted research design involves state of the art methodologies and will generate impactful findings. We propose an innovative approach that is powered by big biological data analysis followed by rigorous validation studies and mechanistic characterization. In that sense, this project will integrate cutting-edge innovations across multiple disciplines to address important questions in biomedical cancer research.

Research Environment and Infrastructure

Host institution Izmir Institute of Technology (IZTECH) and participating institution Izmir Biomedicine and Genome Center (IBG) offer excellent infrastructures to perform cutting edge scientific research and world-class graduate training programs. Multinational faculty in these institutions carry out highly collaborative research spanning a wide range of disciplines including cancer biology, immunology, bioinformatics, and therapeutics development. Laboratories in both institutions are fully equipped with basic molecular biology equipment and there are advanced core facilities with expert staff including small animal and zebrafish vivaria, flow cytometry and sorting, cell imaging, bioinformatics, and structural protein biochemistry cores. IZTECH and IBG have been beneficiaries of multiple national and international grants including the TUBITAK, TUBA, TUSEB, ERC, EMBO Installation Grants, Marie Curie Sklodowska Action Grants. Thus, this proposal will be carried out at institutions that are fully integrated with the research circles of the EU at the highest standards. Importantly, the faculty in the participating institutions have a wide range of scientific research interests and areas of expertise which will allow pursuing science in every direction as well as generating new collaborative projects (https://www.atakanekiz.com/en/lab/).

Preferred Academic Background

Molecular Biology, Bioinformatics, Computational Biology, Biochemistry

Required GRE Score

GRE Quantitative 157.00