Dr. Bogdan A Czerniak's lab focuses on understanding bladder cancer, a common and deadly disease. The research aims to identify how bladder cancer develops and evolves, particularly looking at the cellular changes that contribute to its severity and resistance to treatment. By characterizing the molecular mechanisms involved, the lab aims to develop new therapies to improve early detection and treatment outcomes for bladder cancer patients.

Dr. Ronald Anthony Depinho's lab at the University of Texas MD Anderson Cancer Center focuses on understanding how specific gene deletions in cancer cells can create unique vulnerabilities. By identifying these weak spots, the lab aims to develop precision cancer therapies that target only cancer cells while sparing normal ones. They utilize advanced techniques such as CRISPR to explore these genetic interactions and aim to improve treatment outcomes for cancer patients.

Dr. Raghu Kalluri's lab focuses on understanding exosomes, tiny particles that cells release into the bloodstream, and their roles in cancer, particularly pancreatic cancer. They investigate how these exosomes contribute to cancer progression and explore innovative ways to use engineered exosomes as potential therapies. The lab aims to uncover the mysteries of exosome biology and harness their properties for improving cancer diagnosis and treatment.

Dr. Lawrence Kwong's lab studies cholangiocarcinoma, a serious form of bile duct cancer. The lab focuses on understanding how cancer cells change their identities, a process known as lineage plasticity, which can affect how aggressive the cancer is and how well it responds to treatment. By exploring the genetic and molecular underpinnings of this plasticity, the lab aims to identify new biomarkers and treatment strategies to improve patient outcomes.

Dr. Subrata Sen's lab focuses on advancing the early detection of pancreatic cancer, a particularly aggressive form of cancer. The researchers are developing and validating blood-based biomarkers and advanced imaging techniques to identify the disease at an earlier stage, using both machine learning and multiple biological analyses. Their work aims to improve risk assessment and provide better options for patients at high risk of developing pancreatic cancer.