Most of us know someone who has suffered from cancer, making it a deeply personal issue for many. As one of the most significant clinical challenges of our time, cancer's complexity and heterogeneity complicate efforts to develop effective treatments and cures. By unraveling these complexities, we can pave the way for more targeted and effective interventions, ultimately improving patient outcomes and striving toward a future where cancer is not just manageable but curable.

Clonal evolution and epigenetic plasticity represent significant challenges in achieving a cure for cancer. As tumors develop, they undergo genetic changes that lead to clonal diversity, allowing the emergence of resistant malignant cells, which can survive treatment. Concurrently, epigenetic modifications can alter gene expression without changing the DNA sequence, enabling cancer cells to evade therapeutic interventions. We believe that by measuring these phenomena directly in cancer patients through advanced single-cell sequencing technologies, we can gain valuable insights into therapy resistance mechanisms. This understanding can pave the way for more effective, personalized treatment strategies aimed at overcoming the dynamic nature of cancer.

We integrate single-cell multi-modal sequencing and advanced computational biology to elucidate malignant cell phenotypes directly from patient samples. This approach captures cancer heterogeneity at an unprecedented resolution, revealing insights into tumorigenesis, drug resistance, and progression. By analyzing single cells, we assess multiple layers of information (genetic, transcriptomic, epigenetic, or proteomic) simultaneously, identifying molecular signatures. Our computational frameworks uncover patterns crucial for understanding clonal evolution and epigenetic changes in response to treatment. Ultimately, these insights will inform targeted therapies and personalized medicine, enhancing patient outcomes by reflecting the unique cellular makeup of tumors.

Our goal is to measure and counteract clonal evolution and epigenetic plasticity in cancer, by translating our findings into new or combined therapies that enhance treatment efficacy improving patient outcomes.