Biology subjects

Aitken, S. J.

Publications and source records attributed to Aitken, S. J..

11 recordsLinked to original sources

bioRxiv2026

Explainable machine learning relates histological to genomic pathology

Background & AimsHaematoxylin and eosin (H&E) staining remains the diagnostic gold standard for solid cancers, including hepatocellular carcinoma, and is increasingly complemented by genomic profiling for precision medicine. Inferring genomic alterations directly from H&E images could streamline testing, but heterogeneity and biases in human training data limit interpretation of genotype-phenotype associations. Here, we aimed to relate histologic to genomic pathology to provide biological explainability for mutation prediction models and assess the impact of germline variation on model performance. MethodsWe analysed 597 murine liver tumours with matched whole-genome sequencing and histopathology (163,835 image tiles; 22.9 million nuclei). Our controlled in vivo design accounted for germline variation, biological sex, and causal mutagen (N-diethylnitrosamine), removing confounding factors present in human cohorts. We trained and evaluated deep learning and supervised machine learning models to predict germline variation and cancer driver alterations from H&E. ResultsModelling accurately predicted germline and somatic alterations from histology, at both locus-specific and genome-wide scales. Quantitative image analysis revealed an unexpected association between Egfr driver mutations and hepatic steatosis, linking genotype to an interpretable morphological phenotype. While model performance declined when applied to tumours from unrepresented genetic backgrounds, this limitation was biologically informative, revealing strain-dependent differences in tumour evolution, notably the prevalence of whole-genome duplication. ConclusionsMachine learning integration of histological and genomic pathology enables accurate, interpretable inference of genetic alterations from H&E, potentially reducing reliance on costly ancillary molecular assays. Our predictions are supported by human-interpretable biological features, addressing concerns around "black-box" technologies. However, caution is required when applying such methods to samples with a genetic background that, even if closely related, is beyond the genetic horizon of training data.

pathology↗

bioRxiv2026

Paired CRISPR screens identify mitochondrial metabolism and UBE2H as aneuploid-specific dependencies in human cancer cell lines

Aneuploidy is a hallmark of cancer and imposes widespread cellular stress, including proteotoxicity, transcriptional dysregulation, and increased metabolic demand. Although these stresses are predicted to create therapeutic vulnerabilities, the genetic dependencies of aneuploid cells remain incompletely characterized. Here, we performed paired CRISPR loss-of-function screens in isogenic aneuploid and near-euploid cancer cell line models to systematically identify aneuploidy-specific dependencies. Seven genome-wide paired screens identified ribosomes, rRNA processing, spliceosome-mediated RNA processing, proteasome subunits, and mitochondrial metabolism as top aneuploid-specific dependency gene groups. To identify therapeutically targetable aneuploid dependencies, we performed 18 additional paired CRISPR screens using a focused druggable genome library. This analysis identified the ubiquitin-conjugating enzyme UBE2H as a top aneuploid-selective dependency. Functional validation confirmed aneuploid cell dependency on UBE2H, and mechanistic analyses linked UBE2H to mitochondrial protein abundance, suggesting a role in maintaining mitochondrial proteostasis under aneuploid stress. Together, these findings define core cellular systems that support the viability of aneuploid cells and identify UBE2H as a potential therapeutic vulnerability connecting ubiquitin signaling to mitochondrial homeostasis.

cancer biology↗

bioRxiv2025

Mitochondrial Dysfunction in Endothelial Cells Drives Greater Vascular Impairment in Females with Diabetes-Associated Peripheral Artery Disease

BackgroundWomen with peripheral artery disease (PAD) experience poorer clinical outcomes than men, particularly in the setting of diabetes. However, the mechanistic basis for these sex- specific disparities remains unclear. MethodsHere, we investigated endothelial cell (EC) function(s) in diabetes-associated PAD, with a focus on sex differences. Limb tissues from patients with diabetes and chronic limb-threatening ischemia (CLTI) undergoing amputation, and a diabetes mouse model of hindlimb ischemia (HLI), were assessed for vasodilatory capacity, angiogenesis, oxidative stress and changes to expression of mitochondrial complex genes. ECs exposed to a hyperglycemic environment in vitro were assessed for mitochondrial function. The therapeutic potential of the mitochondrial-targeted antioxidant MitoQ was investigated. ResultsECs from females with diabetes-associated PAD have altered responses compared to males. Specifically, limb vessels and skeletal muscle from females exhibit reduced arterial relaxation, angiogenesis and increased oxidative stress in response to HLI in mice, and in tissues from patients. Single-cell RNA sequencing of murine limbs revealed marked suppression of EC mitochondrial complex genes in females with diabetes. Female human ECs exposed to high glucose had reduced respiration, reduced expression of mitochondrial genes and increased oxidative stress. Remarkably, MitoQ restored arterial relaxation and the angiogenic response in female diabetes- associated PAD. ConclusionOur findings uncover a striking sex-specific vulnerability involving oxidative stress and mitochondrial dysfunction in EC health in diabetes-associated PAD. These results highlight the need for sex-specific therapeutic strategies in diabetic PAD, which might include mitochondrial targeted antioxidant strategies.

pathology↗

bioRxiv2025

A scalable approach for tissue microarray profiling using spatial single cell transcriptomics

Spatially resolved transcriptomics was named Method of the Year 20201 and has continued to evolve rapidly since then, providing novel insights in development, physiology, and disease processes. Many approaches now offer excellent performance in formalin-fixed paraffin embedded tissue, opening up a wealth of archived clinical samples to these high-throughput spatial biology modalities. In this Chapter, we introduce a methodology to apply 10x Xenium In Situ to FFPE tissue microarrays. Using this method we have achieved a cost-effective approach to profile hundreds of genes with subcellular resolution in over a hundred human liver samples. Our method can easily be adapted to other tumour types, diseases, or model systems.

pathology↗

bioRxiv2025

Germline and somatic variation influence nuclear-mitochondrial crosstalk in tumourigenesis

Hepatocellular carcinoma is the most prevalent primary liver cancer and arises from hepatocytes, which are very metabolically active and contain abundant mitochondria. Despite extensive characterisation of nuclear driver genes and pathways, the role of crosstalk between the mitochondrial and nuclear genomes in mitochondrial mutagenesis remains poorly understood. To address this, we leveraged a chemical carcinogenesis model of liver cancer in four mouse strains. We analysed hundreds of tumours with paired whole-genome sequencing and total RNA sequencing to comprehensively characterise mitochondrial mutations and expression. Following de novo assembly of strain-specific mitochondrial genomes, we devised an accurate and efficient heteroplasmy detection approach and analysed mitochondrial DNA (mtDNA) content and transcription. Across strains, there was high concordance of the number of heteroplasmies, mutation signatures, and variant allele frequencies. In contrast, the heteroplasmy rate and genic locations differed between strains, suggesting strain-specificity in DNA repair mechanisms in early tumour development. Independent of age or environmental factors, tumours had lower mtDNA content than adjacent normal liver, suggesting mitochondrial loss during tumourigenesis. Additionally, within individual strains, mtDNA content differences were associated with nuclear driver gene choice. Our comprehensive characterisation of mitochondrial genomes and expression patterns demonstrates that both germline and somatic genetic variation influence tumour mtDNA content, mutation patterns, and gene expression.

cancer biology↗

bioRxiv2025

Genetic background sets the trajectory of cancer evolution

Human cancers are heterogeneous. Their genomes evolve from genetically diverse germlines in complex and dynamic environments, including exposure to potential carcinogens. This heterogeneity of humans, our environmental exposures, and subsequent tumours makes it challenging to understand the extent to which cancer evolution is predictable. Addressing this limitation, we re-ran early tumour evolution hundreds of times in diverse, inbred mouse strains, capturing genetic variation comparable to and beyond that found in human populations. The sex, environment, and carcinogenic exposures were all controlled and tumours comprehensively profiled with whole genome and transcriptome sequencing. Within a strain, there was a high degree of consistency in the mutational landscape, a limited range of driver mutations, and all strains converged on the acquisition of a MAPK activating mutation with similar transcriptional disruption of that pathway. Despite these similarities in the phenotypic state of tumours, different strains took markedly divergent paths to reach that state. This included pronounced biases in the precise driver mutations, the strain specific occurrence of whole genome duplication, and differences in subclonal selection that reflected both cancer susceptibility and tumour growth rate. These results show that interactions between the germline genome and the environment are highly deterministic for the trajectory of tumour genome evolution, and even modest genetic divergence can substantially alter selection pressures during cancer development, influencing both cancer risk and the biology of the tumour that develops.

genomics↗

bioRxiv2022

LGR5 targeting molecules as therapeutic agents for multiple cancer types

Leucine-rich repeat-containing G-protein receptor 5 (LGR5) has been characterised as a stem cell and cancer stem cell marker. Previous analyses of LGR5 transcript levels indicate high level expression discriminates malignancies such as colorectal cancer (CRC) and pre-B acute lymphoblastic leukaemia (pre-B ALL) from healthy tissues suggesting LGR5 protein expression may provide a molecular handle for prognosis and treatment. We have developed highly specific, high affinity antibodies to the extracellular domain of human LGR5 (-LGR5) that detect high LGR5 protein levels in colorectal cancer (CRC), hepatocellular carcinoma (HCC), and pre-B ALL. In contrast, there is low to undetectable levels of LGR5 protein in normal colon and rectal epithelia, liver, ovarian tissues, brain and immune cell types. LGR5 is rapidly internalised from the plasma membrane and trafficked to intracellular vesicular compartments including lysosomes. Treatment of high LGR5-expressing CRC and pre-B ALL cancer cell lines with an antibody-drug conjugate version of -LGR5 (-LGR5-ADC) lead to effective cell killing at nanomolar concentrations. Interventional treatment of pre-B ALL tumours with -LGR5-ADC in vivo led to rapid tumour attrition. We further demonstrated the therapeutic utility of humanised -LGR5 by using the corresponding scFv fragment for the generation of -LGR5 chimeric antigen receptors (CARs) and a Bispecific T cell Engager (BiTE). -LGR5-CAR-NK cells were effective at killing LGR5-expressing cells while -LGR5/-CD3 BiTEs induce T cell activation and killing of NALM6 cells by cytotoxic CD8+ T cells. Taken together, this study establishes -LGR5-based therapeutic modalities that effectively discriminate and target CRC, HCC and pre-B ALL tumour cells. One Sentence SummaryWe generated novel antibodies against the cancer cell marker LGR5, validated diagnostic use in prioritizing specific cancer types for targeting, and developed antibody-based therapeutics.

cell biology↗

bioRxiv2022

Strand-resolved mutagenicity of DNA damage and repair

DNA base damage is a major source of oncogenic mutations1. Such damage can produce strand-phased mutation patterns and multiallelic variation through the process of lesion segregation2. Here, we exploited these properties to reveal how strand-asymmetric processes, such as replication and transcription, shape DNA damage and repair. Despite distinct mechanisms of leading and lagging strand replication3,4, we observe identical fidelity and damage tolerance for both strands. For small DNA adducts, our results support a model in which the same translesion polymerase is recruited on-the-fly to both replication strands, starkly contrasting the strand asymmetric tolerance of bulky adducts5. We find that DNA damage tolerance is also common during transcription, where RNA-polymerases frequently bypass lesions without triggering repair. At multiple genomic scales, we show the pattern of DNA damage induced mutations is largely shaped by the influence of DNA accessibility on repair efficiency, rather than gradients of DNA damage. Finally, we reveal specific genomic conditions that can corrupt the fidelity of nucleotide excision repair and actively drive oncogenic mutagenesis. These results provide insight into how strand-asymmetric mechanisms underlie the formation, tolerance, and repair of DNA damage, thereby shaping cancer genome evolution.

genomics↗

bioRxiv2019

Pervasive lesion segregation shapes cancer genome evolution

Cancers arise through the acquisition of oncogenic mutations and grow through clonal expansion1, 2. Here we reveal that most mutagenic DNA lesions are not resolved as mutations within a single cell-cycle. Instead, DNA lesions segregate unrepaired into daughter cells for multiple cell generations, resulting in the chromosome-scale phasing of subsequent mutations. We characterise this process in mutagen-induced mouse liver tumours and show that DNA replication across persisting lesions can generate multiple alternative alleles in successive cell divisions, thereby increasing both multi-allelic and combinatorial genetic diversity. The phasing of lesions enables the accurate measurement of strand biased repair processes, the quantification of oncogenic selection, and the fine mapping of sister chromatid exchange events. Finally, we demonstrate that lesion segregation is a unifying property of exogenous mutagens, including UV light and chemotherapy agents in human cells and tumours, which has profound implications for the evolution and adaptation of cancer genomes.

cancer biology↗

bioRxiv2019

Clustered CTCF binding is an evolutionary mechanism to maintain topologically associating domains

CTCF binding contributes to the establishment of higher order genome structure by demarcating the boundaries of large-scale topologically associating domains (TADs). We have carried out an experimental and computational study that exploits the natural genetic variation across five closely related species to assess how CTCF binding patterns stably fixed by evolution in each species contribute to the establishment and evolutionary dynamics of TAD boundaries. We performed CTCF ChIP-seq in multiple mouse species to create genome-wide binding profiles and associated them with TAD boundaries. Our analyses reveal that CTCF binding is maintained at TAD boundaries by an equilibrium of selective constraints and dynamic evolutionary processes. Regardless of their conservation across species, CTCF binding sites at TAD boundaries are subject to stronger sequence and functional constraints compared to other CTCF sites. TAD boundaries frequently harbor rapidly evolving clusters containing both evolutionary old and young CTCF sites as a result of repeated acquisition of new species-specific sites close to conserved ones. The overwhelming majority of clustered CTCF sites colocalize with cohesin and are significantly closer to gene transcription start sites than nonclustered CTCF sites, suggesting that CTCF clusters particularly contribute to cohesin stabilization and transcriptional regulation. Overall, CTCF site clusters are an apparently important feature of CTCF binding evolution that are critical the functional stability of higher order chromatin structure.

genomics↗

bioRxiv2018

Mutational landscape of a chemically-induced mouse model of liver cancer

Carcinogen-induced mouse models of liver cancer are used extensively to study the pathogenesis of the disease and have a critical role in validating candidate therapeutics. These models can recapitulate molecular and histological features of human disease. However, it is not known if the spectra of genomic alterations driving these mouse tumour genomes are comparable to those found in humans. Here, we provide a detailed characterisation of the exome-wide pattern of mutations in tumours from mice exposed to diethylnitrosamine (DEN), a commonly used model of hepatocellular carcinoma (HCC). DEN-initiated tumours had a high, uniform number of somatic single nucleotide variants (SNVs), with very few insertions, deletions or copy number alterations, consistent with the known genotoxic action of DEN. Exposure of hepatocytes to DEN left a reproducible mutational imprint in resulting tumour exomes which we could computationally reconstruct using six known COSMIC mutational signatures. The tumours carried a high diversity of low-incidence, non-synonymous point mutations in many oncogenes and tumour suppressors, reflecting the stochastic introduction of SNVs into the hepatocyte genome by the carcinogen. We identified four recurrently mutated genes that were putative oncogenic drivers of HCC in this model. Every neoplasm carried activating hotspot mutations either in codon 61 of Hras, in codon 584 of Braf or in codon 254 of Egfr. Truncating mutations of Apc occurred in 21% of neoplasms, which were exclusively carcinomas supporting a role for deregulation of Wnt/{beta}-catenin signalling in cancer progression. Conclusion: Our study provides detailed insight into the mutational landscape of tumours arising in a commonly-used carcinogen model of hepatocellular carcinoma, facilitating the future use of this model to understand the human disease.

cancer biology↗