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Cerda, V.

Publications and source records attributed to Cerda, V..

4 recordsLinked to original sources

G4SCOPE identifies sequence features and epigenetic contexts of chromatin G-quadruplexes

Cancer-associated epigenetic remodeling involves a complex interplay between DNA secondary structures and covalent cytosine modifications, yet predicting endogenously folded, chromatin-constrained G-quadruplex (G4) dynamics remains challenging. Here, we develop G4SCOPE, a multi-task deep learning framework that models chromatin-associated G4 occupancy and reconstructs quantitative high-resolution CUT&Tag profiles directly from primary DNA sequence alone. We initially trained G4SCOPE on genotype-stratified G4 enriched cut&tag landscapes generated across an isogenic series of human breast epithelial cells (WT, TP53-/-, TP53-/-;BRCA1-/-, and TP53-/-;BRCA2-/-). G4SCOPE integrates convolutional motif learning with transformer self-attention to decode long-range sequence contexts. The model robustly distinguishes chromatin-associated G4s from GC-matched loci with intrinsic in vitro folding potential, generalizes across distinct breast lineages, and transfers accurately to an independent K562 cellular context. Strikingly, genotype-resolved mapping reveals a profound divergence in genome maintenance states: BRCA1 deficiency indicated a global inflation of chromatin-embedded G4 density, whereas BRCA2 loss was associated with systemic, chromosome-wide structural depletion. Furthermore, unsupervised clustering of model-derived latent sequence representations identified distinct biological G4 subclasses that occupy unique regulatory class genomic environments associated with distinct local 5-methylcytosine and 5-hydroxymethylcytosine landscapes. Together, our framework decodes the primary sequence grammar governing cell-based G4 occupancy and demonstrates that sequence-defined G4 topologies harbor intrinsic and distinct local epigenetic features.

bioinformatics↗

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↗