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Biology subjects

Zaikova, E.

Publications and source records attributed to Zaikova, E..

5 recordsLinked to original sources

Chromosomal mutational signatures of DNA damaging agents at single cell resolution

The chromosomal-scale mutational spectrum of small molecules that interact with DNA has been hard to study at scale, as mutational events are distributed in location and occur in parallel in different cells. Here, we present a framework that pairs phylogenetic ancestry reconstruction with mutational signature decomposition to characterise recent, cell-private copy number alteration (CNA) mutational patterns at single-cell resolution. We used this framework to characterise the cell-wise mutational spectrum of contemporaneous CNAs generated by double-strand-break-inducing chemotherapeutic drugs. We demonstrate that platinum salts, G-quadruplex stabilizers and topoisomerase II inhibitors, although mechanistically distinct, converge on a mutational signature dominated by telomere-bounded copy-number gains and losses. This signature is observed in different genetic backgrounds and in vivo in drug-treated patient-derived xenografts. We also observe a high rate of endogenous telomere-bounded mutational foreground in BRCA1 deficient cells. We show that the single cell genome derived signature exposures are drug dose-dependent, and use this to identify the decay of mutational load after drug withdrawal. We observe that both cisplatin and a G4 binder molecule (CX5461) exhibit foreground mutational signature persistence for at least 3 weeks after drug withdrawal, suggesting that residual effects of exposure may last longer than anticipated. Finally, extending the framework to serially drug-treated patient-derived xenograft (PDX) models, we show that telomere-bounded CNA signature exposure is associated with tumoural response to drug, consistent with loss of mutational activity on the genome after acquired resistance emerges. Together, our results show that our framework applied on scWGS identifies contemporaneous chromosomal mutation patterns induced by small molecules in human tissues.

cancer biology↗

Minimally invasive monitoring of clonal evolution through integrated single cell and ctDNA analysis

Circulating cell-free DNA (cfDNA) offers a minimally invasive lens into tumor evolution. However, the accurate quantification of clonal composition from cfDNA remains challenging. Existing methods for clone tracking using liquid biopsies are constrained by issues such as their reliance on bulk tissue references, incomplete representations of clonal architecture or limited breadth of mutation panels. To address these limitations, we developed cfClone, a Bayesian framework that integrates single-cell whole-genome sequencing (scWGS) derived clonal structures with cfDNA whole-genome sequencing (cfDNA-WGS) data to enable high-resolution tissue-informed clonal tracking. By jointly modeling local copy-number alterations and haplotype-specific signals via Bayesian model selection and Markov chain Monte Carlo (MCMC) sampling, the algorithm yields uncertainty-aware estimates of clonal prevalence and tumour fraction (TF). Applied to longitudinal clinical cohorts, cfClone can be used to reconstruct evolutionary trajectories and uncovers clonal selection driving therapeutic resistance, including the de novo detection of emergent clonal populations. We demonstrate that cfClone achieves accurate TF estimates and circulating tumor DNA (ctDNA) detection in malignancies with varying degrees of copy-number variant (CNV) burden using semi-synthetic data. We then compare to the state of the art scWGS informed panel based approach, and demonstrate cfClone provides comparable accuracy while allowing for the tracking of more clones and detection of novel clones. Finally, we show how cfClone can be used to quantitatively track clonal dynamics in response to treatment in high grade serous ovarian cancer. Github link: https://github.com/Roth-Lab/cfclone

cancer biology↗

The UV potentiated mutational signature of clinical stage G-quadruplex binder CX5461.

Drug-related UVA-induced photoreactions have been reported for several therapeutic compounds, including fluoroquinolones. CX5461 is a clinically relevant quinolone-derived anti-cancer small molecule with documented UVA-sensitising activity. Here we compared, by bulk and clonal whole genome sequencing (WGS) under light-protected conditions, the mutational signatures in human retinal pigment epithelial cells (RPE1) exposed to UVA, CX5461, or co-exposed to UVA and CX5461. Treatment with CX5461 or UVA alone resulted in a low SNV burden and background-like mutational profiles. In contrast, bulk sequencing of human cells co-exposed to UVA and CX5461 had a markedly higher SNV burden characterized by T>A and T>C substitutions. Furthermore, single-cell clonal expansion and sequencing of CX5461 alone, UVA alone or CX5461+UVA treatments confirmed that the pattern was only observed when cells were exposed to both UVA and CX5461. The CX5461+UVA-associated SNV signature we report arises only when CX5461-treated cells are exposed to UVA, and is not observed when CX5461-treated cells are shielded from light. We do not observe strong single base mutagenic activity of CX5461 alone, under light protected conditions. Our data emphasise the need for appropriate controls and light-exposure precautions when studying base mutagenesis activity of known photosensitiser molecules.

cancer biology↗

Somatic copy number mutations contribute to fitness in transplantation models of spontaneous human breast cancer metastasis

The contribution of somatic gene dosage mutations (CNA) to breast cancer metastasis remains poorly defined. Using 9 transplantable human neoadjuvant-naive triple-negative breast cancer xenografts, we studied the fitness of copy number clones in spontaneous metastasis from orthotopic transplant sites. Metastatic site preference was strongly patient-dependent, and the emergence of metastases exhibited a general trend toward slower growth at the orthotopic site. In our models, single-cell whole-genome sequencing of primary and metastatic sites showed that distant metastases were most often the result of minor prevalence clones at the orthotopic site, suggesting that some metastatic phenotypes may be weakly negatively fit at the primary site. We validated the existence of a fitness hierarchy of copy number clones using a previously established paradigm of remixing and retransplanting clones. Single-cell clone analysis of competitive repopulation and re-emergence of metastases showed that CNAs arising in cancer evolution can mediate metastatic fitness. Moreover, some clones displaying strong metastatic tendency exhibited weaker survival at the primary site, consistent with the notion that metastatic phenotypes could have a fitness cost at the primary site. Finally, we conducted RNA-seq analysis combined with DriverNet analysis to dissect the contribution of CNA-mediated versus genome-independent transcriptional states. CNA mutations appeared to contribute strongly to transcriptional differences between clones. Among clones of high metastatic potential, we observed CNA-mediated and CNA-independent convergence on pathways such as epithelial-mesenchymal transition (EMT), established as mediators of metastatic cell survival at distant sites. Taken together, our data point to a contribution of CNA-mediated cancer evolution to metastatic states and identify distant-site context as a key determinant of CNA-mediated fitness.

cancer biology↗

Single cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BackgroundThe encoding of cell intrinsic resistance states in breast cancer reflects the contributions of genomic and non-genomic variation. However, identifying the potential contributions of each requires accurate measurement and subtraction of the contribution of clonal fitness from co-measurement of transcriptional states. Somatic genomic variation in gene dosage, copy number variation, is the dominant mutational mechanism in breast cancer contributing to transcriptional variation and has recently been shown to contribute to platinum chemotherapy resistance states. Here we deploy time series measurements of triple negative breast cancer single cell transcriptomes in conjunction with co-measured single cell copy number associated clonal fitness to identify the contributions of genomic and non-genomic mechanisms to drug associated transcription states. ResultsWe generated serial scRNA-seq data (126,556 cells) from triple negative breast cancer (TNBC) patient-derived xenograft (PDX) experiments over 2.5 years in duration, and matched it against genomic copy number single cell data from the same biological samples. We show that the cell memory of transcriptional states of TNBC tumors serially exposed to platinum identifies distinct clonal responses within individual tumours. Copy-number clones with high drug fitness leading to clonal sweeps exhibit less transcriptional reversion, whereas clones with weak drug fitness exhibit highly dynamic transcription on drug withdrawal. Pathway analysis shows that copy number associated and copy number independent transcripts converge on epithelial-mesenchymal transition (EMT) and cytokine signaling states associated with resistance. We show from trajectory analysis that transcriptional reversion exhibits hysteresis, indicating that new intermediate transcriptional states are generated by platinum exposure. ConclusionsWe discovered that copy number clones with strong genotype associated fitness under platinum became fixed in their states, resulting in minimal transcriptional reversion on drug withdrawal. In contrast clones with weaker fitness undergo non-genomic transcriptional plasticity and these distinct responses co-exist within single tumours. Together the data suggest that copy number associated and copy number independent transcriptional states may contribute to platinum drug resistance within individual tumours. The dominance of genomic or non-genomic mechanisms within individual polyclonal tumours has implications for approaches to restoration of drug sensitivity and re-treatment strategies. Data availabilityUploaded Data URL: https://ega-archive.org/studies/EGAS00001007242 Github manuscript: https://github.com/molonc/drug_resistant_material/

genomics↗