About our research
Tumour heterogeneity and recurrence
Preventing cancer relapse requires us to understand and target the cells that survive standard-of-care treatment. Tumors are composed of diverse cell populations shaped by genetic variation, their evolutionary histories and interactions with the surrounding tissue. This heterogeneity makes a cure difficult: treatment must eliminate the full diversity of cancer cells capable of sustaining the disease. Even a small number of cells surviving initial therapy can regenerate the tumor and give rise to disease that is more resistant to subsequent treatment. Our goal is to identify the populations most likely to persist, understand what protects them and develop treatments that eradicate them before relapse occurs.
Tumour profiling at the cellular and clonal level
We use patient-derived tumoroids, high-throughput drug and CRISPR screening, single-cell sequencing and molecular barcoding to study how heterogeneous cancer populations respond to therapy. Molecular barcodes allow us to follow thousands of cell lineages and determine which populations disappear, persist or expand during treatment. At the single-cell level, expressed barcodes can be captured together with each cell’s transcriptome, linking lineage identity with molecular phenotype. This allows survival to be examined as both an evolutionary and a cellular process: which lineages persist, which states they occupy and what distinguishes them from treatment-sensitive cells.
Precision lethality
A central concept in our research is precision lethality: designing treatments that eliminate the specific cell populations most likely to survive and cause relapse. Drug and CRISPR screens identify vulnerabilities across these populations and cell barcoding reveal complementary ways of targeting them. AI-based models complement this experimental work by integrating single-cell profiles with large-scale drug and genetic perturbation data to predict which targets and combinations are most likely to be effective. These predictions narrow the vast number of possible interventions and help prioritize the most promising strategies for testing in tumoroids.
Novel therapeutic strategies
We also develop new approaches for childhood cancer, including differentiation therapies that push aggressive neuroblastoma cells towards a more benign state, targeted radiopharmaceutical therapies and drugs that increase sensitivity to radiation.
Interdisciplinary approaches
Based at the Department of Oncology-Pathology at Karolinska Institutet and SciLifeLab, our group combines cancer biology, genomics, drug discovery and computational analysis. By resolving tumors at the level of individual cells and lineages, we aim to make treatment response more predictable and effective by developing therapies targeting tumor populations likely to be resistant to standard of care treatment.
