Defining the landscape of noncoding driver mutations in 24 cancer types

• Applicant: Dr. Lino Möhrmann
• Subject Area: Hematology, Oncology ; General Genetics and Functional Genome Biology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 551924272

Background: Cancer genomics has primarily focused on the coding 2% of the genome so far. The remaining 98% of the genome, the noncoding part, plays a crucial role in gene regulation and mutations in these noncoding regions can significantly influence cancer development and progression, such as TERT promoter mutations in melanoma. Despite their potential significance, systematic insights into the landscape of noncoding mutations are lacking, particularly in rare cancers, which represent ~25% of all cases. Mutational signatures, characteristic patterns of DNA alterations, can provide insights into the underlying processes driving cancer development. Objectives: This project will systematically identify and characterize noncoding genomic drivers in whole-genome sequencing data of 2,826 cancer patients from the German NCT/DKFZ MASTER program. This unique cohort includes 24 cancer types of which ~75% are rare cancers that are not part of existing sequencing cohorts, such as PCAWG or Genomics England (Horak et al. Cancer Discovery 2021, Möhrmann et al. Nature Communications 2022). My aims are to 1) Define the landscape of noncoding driver mutations in 24 cancer types, and 2) Quantify mutational signatures in 24 cancers and link them to clinical outcomes. These aims will test my hypothesis that the noncoding genome harbors several driver mutations, particularly in the substantial part of rare cancers that do not have any clear driver mutation in the coding genome. Together, they will systematically characterize driver and passenger mutation patterns in the noncoding genome. Methods: This project represents a collaborative effort between NCT/DKFZ in Germany and my host lab at Harvard Medical School in the US, which developed an innovative computational approaches to identify driver mutations in the noncoding genome (Dietlein et al. Science 2022) and quantify extended nucleotide contexts around mutation signatures (Dietlein et al. Nature Genetics 2020). Under the guidance of Dr. Dietlein, I will devise a sliding-window approach that pinpoints mutations across regulatory and non-protein-coding regions of the genome (Aim 1) and link extended nucleotide contexts in mutational signatures to a wide range of clinical outcome parameters (Aim 2). In both Aims, I will leverage multi-omics data (transcriptome and methylome) to validate my findings. Anticipated Impact: This research will bridge a crucial gap in cancer genomics by shifting the focus from coding toward noncoding regions, paving the way for new genome-based drug targets and diagnostic markers. It will significantly advance our understanding of the genomic landscape that drives cancer, including rare cancer types. It will also provide a critical foundation for clinical follow-up studies, aiming to identify genome-based drug targets in precision medicine. Ultimately, it will help me to establish my independent research lab focusing on translational cancer genomics at a German university hospital.

• DFG Programme: WBP Fellowship
• International Connection: USA
• Host: Felix Dietlein, Ph.D.