Rate My Professor Erik Larsson Lekholm

Erik Larsson Lekholm is Professor of Bioinformatics at the Institute of Biomedicine, Department of Medical Biochemistry and Cell Biology, University of Gothenburg, within the Sahlgrenska Academy. His research group specializes in human computational genomics, with a primary emphasis on basic cancer science. They investigate the origins and distribution of somatic mutations across cancer genomes, developing computational models to detect signals of positive selection indicative of driver alterations. Key research areas include non-coding alterations in cancer, mitochondrial DNA changes, and the creation of bioinformatics tools for analyzing large-scale genomics data. The group operates a wet laboratory employing high-throughput sequencing to map DNA damage from ultraviolet light at base resolution, yielding insights into mutational signatures in skin tumors such as melanoma. Translational efforts involve collaborations with clinicians at Sahlgrenska University Hospital.

Larsson Lekholm's influential publications appear in leading journals, including 'Non-coding driver mutations in human cancer' (Nature Reviews Cancer, 2021), 'Independent somatic evolution underlies clustered neuroendocrine tumors in the human small intestine' (Nature Communications, 2021), 'Somatic mutation distribution across tumour cohorts provides a signal for positive selection in cancer' (Nature Communications, 2022), 'Base-resolution UV footprinting by sequencing reveals distinctive damage signatures for DNA-binding proteins' (Nature Communications, 2023), 'Mechanistic basis of atypical TERT promoter mutations' (Nature Communications, 2024), and 'Ribonucleotide incorporation into mitochondrial DNA drives inflammation' (Nature, 2025). He received the Wallenberg Academy Fellow prolongation grant in 2020, supporting establishment of his wet lab and subprojects on skin cancer mutations, and the Eric K. Fernström Prize for young researchers in 2018 for groundbreaking work combining bioinformatics and experimental approaches to understand cancer mutation processes. His contributions advance cancer genomics by enhancing interpretation of DNA sequencing data and identification of clinically relevant changes.