Biology subjects

Humphreys, L.

Publications and source records attributed to Humphreys, L..

3 recordsLinked to original sources

bioRxiv2026

A comprehensive atlas of somatic mutation rates and mutational signatures in normal human cells

Over the course of a lifetime, somatic mutations accrue in normal human cells, causing variation in cell phenotype and engendering somatic evolution with outcomes ranging from the adaptive immune system to cancer. To inform understanding of somatic evolution in the human body we report the mutation rates and mutational signatures of 53 normal cell types. Most show evidence of linear mutation accumulation over time with single base substitution mutation rates ranging from ~3.5/year/diploid genome in spermatogonia and sperm, to ~20/year in postmitotic neurons, ~50/year in mitotically active colorectal epithelial cells, ~60/year in kidney proximal tubule cells and hepatocytes, 100s/year in sun-exposed skin epidermal cells and 10-50/year in the remainder. Certain cell types, including skin epidermis, cardiac myocytes, bladder urothelium, kidney proximal tubule cells, and hepatocytes, show substantial variability in mutation burdens around the linear age trend, indicating the influence of additional factors which differ between individuals and modulate mutation accumulation, including exogenous mutagen exposures. At least 18 single-base substitution and nine small insertion and deletion mutational signatures are present, some in all cell types, some in a subset and others in a single cell type. Known exogenous mutagen exposures and endogenous mutational processes account for some mutational signatures, but the origins and mechanisms underlying many are uncertain. This comprehensive survey of mutagenesis provides a foundation for understanding somatic evolution of human cell populations in health and disease.

genomics↗

bioRxiv2024

The long-term effects of chemotherapy on normal blood cells

In developed countries, [~]10% of individuals are exposed to systemic chemotherapy for cancer and other diseases. Many chemotherapeutic agents act by increasing DNA damage in cancer cells, triggering cell death. However, there is limited understanding of the extent and long-term consequences of collateral DNA damage to normal tissues. To investigate the impact of chemotherapy on mutation burdens and cell population structure of a normal tissue we sequenced blood cell genomes from 23 individuals, aged 3-80 years, treated with a range of chemotherapy regimens. Substantial additional mutation loads with characteristic mutational signatures were imposed by some chemotherapeutic agents, but there were differences in burden between different classes of agent, different agents of the same class and different blood cell types. Chemotherapy also induced premature changes in the cell population structure of normal blood, similar to those of normal ageing. The results constitute an initial survey of the long-term biological consequences of cytotoxic agents to which a substantial fraction of the population is exposed during the course of their disease management, raising mechanistic questions and highlighting opportunities for mitigation of adverse effects.

cell biology↗

bioRxiv2020

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in genomic studies surveying cancer and normal somatic tissues. Here we present SigProfilerExtractor, an automated tool for accurate de novo extraction of mutational signatures for all types of somatic mutations. Benchmarking with a total of 34 distinct scenarios encompassing 2,500 simulated signatures operative in more than 60,000 unique synthetic genomes and 20,000 synthetic exomes demonstrates that SigProfilerExtractor outperforms thirteen other tools across all datasets with and without noise. For genome simulations with 5% noise, reflecting high-quality genomic datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true positive signatures while yielding more than 5-fold less false positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome sequenced and 19,184 whole-exome sequenced cancers reveals four previously missed mutational signatures. Two of the signatures are confirmed in independent cohorts with one of these signatures associating with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting mutational signatures, and several novel mutational signatures including a signature putatively attributed to direct tobacco smoking mutagenesis in bladder cancer and in normal bladder epithelium.

bioinformatics↗