Biology subjects

Livingstone, J.

Publications and source records attributed to Livingstone, J..

9 recordsLinked to original sources

bioRxiv2025

Somatic evolution of prostate cancer: mutation, selection, and epistasis across disease stages

BackgroundSomatic mutations involved in prostate cancer tumorigenesis and disease progression have been identified, but their evolutionary dynamics--including differential selective pressures across oncogenesis and metastatic spread--remain poorly understood. No prior study has systematically quantified the adaptive landscape from prostate organogenesis through tumor initiation and progression to metastatic castrate-resistant prostate cancer (mCRPC), nor characterized the selective epistatic interactions that structure this evolutionary trajectory. Methods and FindingsTo address this gap, we analyzed 2,704 low- and high-risk primary tumors and metastatic castration-resistant prostate cancers to quantify the mutation rates, mutational processes, and scaled selection coefficients of somatic mutations across disease stages. Trinucleotide mutational patterns were stable, but both mutation load and mutation rates increased with progression. In parallel, selective pressures on specific somatic mutations changed substantially, revealing a dynamic adaptive landscape. Stage-specific selective effects were associated with significant synergistic and antagonistic selective epistasis among key driver genes. Early selection on SPOP mutations in the BRD3 binding domain were under strong positive selection, and they increased selection for subsequent RHOA mutations while decreasing selection for TP53 mutations. Antagonistic selective epistasis was evident between mutations of CUL3 and both SPOP and PIK3CA. Mutations in KMT2C increased the selection for mutations in TP53, consistent with their frequent co-occurrence. Synergistic epistatic interactions between mutations of PTEN and both PIK3CA and AR support a strong therapeutic rationale for combined inhibition of PI3K/AR pathway in PTEN-deficient prostate cancers. ConclusionsThese findings provide a comprehensive map of the evolving selective and epistatic forces that shape prostate cancer progression across clinical stages. By distinguishing shifts in selection from changes in mutation rate and revealing the extents of cooperative and conflicting relationships among driver mutations, our work identifies critical points of vulnerability and informs that design of therapeutic strategies that anticipate and intercept the somatic evolutionary trajectory of prostate cancer.

cancer biology↗

bioRxiv2025

Structure-Function Mapping of Olfactory Bulb Circuits with Synchrotron X-ray Nanotomography

Information is routed between brain areas via parallel streams. Neurons may share common inputs yet convey distinct information to different downstream targets. Here, we leverage the anatomical organisation of the mouse olfactory bulb (OB), where dozens of projection neurons (mitral and tufted cells, M/TCs) affiliate with a single input unit, a glomerulus1-3. To link functional properties of M/TCs to their anatomical glomerular association at scale, we combine in vivo two-photon (2P) imaging with synchrotron {micro}CT4-6 anatomical analysis and targeted X- ray nano-holotomography (XNH)7,8. Improving XNH resolution for mm3 volumes enables us to reliably identify subcellular features, automatically segment >80,000 cell nuclei in individual experiments, and delineate several hundred functionally imaged projection neurons and their detailed morphology, including up to 20 M/TCs per individual glomerulus ("sister" cells). In over 2400 sister cell pairs, we consistently find that odour response amplitudes to a panel of 47 monomolecular odours are conserved between sister cells, with, however, distinct responses to individual odours. Responses correlated with anatomical features such as cell body position and lateral dendritic arborisation. Thus, sister cells neither simply relay glomerular inputs nor are they dominated by network activity. Instead, they show a "balanced diversity" in their responses, enabling efficient encoding of odour stimuli whilst retaining the overall structure of odour space. Thus, synchrotron X-ray tomography can reliably link subcellular anatomy to function in a non-destructive way across the mm3 scale. With recent advances in X-ray optics9 and the emergence of 4th generation synchrotrons10,11, it becomes conceivable to extend this highly accessible approach to entire brain regions with increasing resolution.

neuroscience↗

bioRxiv2025

The Landscape of Prostate Tumour Methylation

Prostate cancer is characterized by profound clinical and molecular heterogeneity. While its genomic heterogeneity is well-characterized, its epigenomic heterogeneity remains less understood. We therefore created a compendium of 3,001 multi-ancestry prostate methylomes spanning normal tissue through localized disease of all grades to poly-metastatic disease. A subset of 884 samples had multi-omic DNA and/or RNA characterization. We identify four epigenomic subtypes that risk-stratify patients and reflect distinct evolutionary trajectories. We demonstrate extensive regulatory interplay between DNA copy number and methylation, with transcriptional consequences that vary across genes and disease stages. We define epigenetic dysregulation signatures for 15 important clinico-molecular features, creating predictive models for each. For example, we identify specific epigenetic features that predict patient outcome and are synergistic with clinical prognostic features. These results define a complex interplay between tumour genetics and epigenetics that converges to modify gene-expression programs and clinical presentation, in part through modulation of epigenetic aging.

cancer biology↗

bioRxiv2025

Self-supervised image restoration in coherent X-rayneuronal microscopy

Coherent X-ray microscopy is emerging as a transformative technology for neuronal imaging, with the potential to offer a scalable solution for reconstruction of neural circuits in millimeter sized tissue volumes. Specifically, X-ray holographic nanoto-mography (XNH) brings together outstanding capabilities in terms of contrast, spatial resolution and data acquisition speed. While recent XNH developments already enabled generating valuable datasets for neuro-sciences, a major challenge for reconstruction of neural circuits remained overcoming resolving power limits to distinguish smaller neurites and synapses in the reconstructed volumes. Here we present a self-supervised image restoration approach that simultaneously improves spatial resolution, contrast, and data acquisition speed. This enables revealing synapses with XNH, marking a major milestone in the quest for generating connectomes of full mammalian brains. We demonstrate that this method is effective for various types of neuronal tissues and acquisition schemes. We propose a scalable implementation compatible with multi-terabyte image volumes. Altogether, this work brings large-scale X-ray nanotomography to a new precision level.

neuroscience↗

bioRxiv2024

Metapipeline-DNA: A Comprehensive Germline & Somatic Genomics Nextflow Pipeline

SummaryThe price, quality and throughout of DNA sequencing continue to improve. Algorithmic innovations have allowed inference of a growing range of features from DNA sequencing data, quantifying nuclear, mitochondrial and evolutionary aspects of both germline and somatic genomes. To automate analyses of the full range of genomic characteristics, we created an extensible Nextflow meta-pipeline called metapipeline-DNA. Metapipeline-DNA analyzes targeted and whole-genome sequencing data from raw reads through pre-processing, feature detection by multiple algorithms, quality-control and data- visualization. Each step can be run independently and is supported robust software engineering including automated failure-recovery, robust testing and consistent verifications of inputs, outputs and parameters. Metapipeline-DNA is cloud-compatible and highly configurable, with options to subset and optimize each analysis. Metapipeline-DNA facilitates high-scale, comprehensive analysis of DNA sequencing data. AvailabilityMetapipeline-DNA is an open-source Nextflow pipeline under the GPLv2 license and is available at https://github.com/uclahs-cds/metapipeline-DNA.

bioinformatics↗

bioRxiv2024

moPepGen: Rapid and Comprehensive Proteoform Identification

Proteogenomics is limited by challenges of modeling the complexities of gene expression. We create moPepGen, a graph-based algorithm that comprehensively generates non-canonical peptides in linear time. moPepGen works with multiple technologies, in multiple species and on all types of genetic and transcriptomic data. In human cancer proteomes, it enumerates previously unobservable noncanonical peptides arising from germline and somatic genomic variants, noncoding open reading frames, RNA fusions and RNA circularization.

bioinformatics↗

bioRxiv2022

Germline determinants of the prostate tumor genome

A persons germline genome strongly influences their risk of developing cancer. Yet the molecular mechanisms linking the host genome to the specific somatic molecular phenotypes of individual cancers are largely unknown. We quantified the relationships between germline polymorphisms and somatic mutational features in prostate cancer. Across 1,991 prostate tumors, we identified 23 co-occurring germline and somatic events in close 2D or 3D spatial genomic proximity, affecting 10 cancer driver genes. These driver quantitative trait loci (dQTLs) overlap active regulatory regions, and shape the tumor epigenome, transcriptome and proteome. Some dQTLs are active in multiple cancer types, and information content analyses imply hundreds of undiscovered dQTLs. Specific dQTLs explain at least 16.7% ancestry-biases in rates of TMPRSS2-ERG gene fusions and 67.3% of ancestry-biases in rates of FOXA1 point mutations. These data reveal extensive influences of common germline variation on somatic mutational landscapes.

cancer biology↗

bioRxiv2021

The Telomere Length Landscape of Localized Prostate Cancer

Replicative immortality is a hallmark of cancer, and can be achieved through telomere lengthening and maintenance. We report telomere lengths (TLs) of 392 localized prostate cancer tumours and characterize their relationship to genomic, transcriptomic and proteomic features. Shorter tumour TLs were associated with elevated genomic instability, including single-nucleotide variants, indels and structural variants. Genes involved in cell proliferation and signaling were correlated with tumour TL at all levels of the central dogma. TL was also associated with multiple clinical features of a tumour. Longer TLs in non-tumour samples were associated with a lower rate of biochemical relapse after definitive local therapy. Our analysis integrates multi-omics data to illuminate the relationship of specific genomic alterations in a tumour and TL in prostate cancer. Although the role of telomere length in cancer has been well studied, its association to genomic features is less well known. We describe the multi-level integration of telomere length, genomics, transcriptomics and proteomics in localized prostate cancer. Patient Summary We examined the association between telomere length and multiple omics-level data in prostate cancer. We observed that traditional telomere mutations are rare in prostate cancer and that telomere length is associated with multiple measure of genomic instability.

genomics↗

bioRxiv2020

Differing total mRNA expression shapes the molecular and clinical phenotype of cancer

Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, differences in tumor cell total mRNA content have not been comprehensively assessed. Technical and analytical challenges have impeded examination of total mRNA expression at scale across cancers. To address this, we developed a model for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data, which performs transcriptomic deconvolution while adjusting for mixed genomes. We used single-cell RNA sequencing data to demonstrate total mRNA expression as a feature of tumor phenotype. We estimated and validated TmS in 5,015 patients across 15 cancer types identifying significant inter-individual variability. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Cancer type-specific patterns of genetic alterations, intra-tumor genetic heterogeneity, as well as pan-cancer trends in metabolic dysregulation and hypoxia contribute to TmS. Taken together, our results suggest that measuring cell-type specific total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important biological and clinical implications.

genomics↗