Okan Gültekin

My research is driven by a global vision to outsmart advanced gynecological cancers—including High-Grade Serous Carcinoma (HGSC), uterine sarcomas, and cervical cancers—by decoding the complex dialogue within the tumor microenvironment (TME). Based at the Department of Women’s and Children’s Health (KBH), I lead an initiative to transform multi-dimensional biological data into a roadmap for personalized patient care.

For many patients, the path to recovery is complicated by the disease’s ability to adapt and resist treatment. Traditional models often miss the "big picture"—the silent interactions between the tumor, the patient’s own response to surgical trauma, and the unique environment in which the cancer grows. My work addresses this by building an AI-powered framework that understands these hidden patterns. Instead of looking at a single factor, this endeavor synthesizes clinical history with the molecular changes that occur during the critical window of surgical treatment.

With "full-stack" expertise in spatial functional mapping, my methodological approach bridges clinical sample acquisition with advanced bioengineering and computational analysis:

• Functional Modeling: I utilize 3D ex vivo explants and biomimetic "multi-organ on a chip" microfluidic systems to investigate how malignant fluids, such as ascites, act as a "schooling medium" that amplifies tumor malignancy.
• Spatial Functional Mapping: I leverage high-plex spatial biology, including CODEX (PhenoCycler) and Multiplex Immunofluorescence, to map complex immune neighborhoods and tissue responses.
• AI & Bio-imaging: I develop machine-learning-based pipelines to translate systems-level biological data into clinically relevant tools, specifically investigating how inflammation and wound healing triggered by surgery affect cancer invasion and chemoresistance.

This undertaking is built on the belief that solving a global problem requires a global team. My research journey involves a cross-border collaboration between Karolinska Institutet, the University of Helsinki, and Queen Mary University of London, working toward a future where every patient receives a treatment plan as unique as they are.

*2019-23 * Lecturer for tumor image analysis, PhD/MSc course “Tumor
microenvironment communication” Karolinska Institutet, Stockholm, SE
*2020- 23 *Supervisor to 5 biomedical students for Bachelor thesis, 5
biomedical student Master thesis