Biology subjects

Tagal, V.

Publications and source records attributed to Tagal, V..

6 recordsLinked to original sources

bioRxiv2026

Resource limitation rewires chromosome instability and ploidy evolution across in vitro and in vivo cancer models

Whole-genome doubling (WGD) and elevated ploidy are pervasive features of cancer that shape chromosomal instability (CIN), therapeutic response, and metastatic fitness. Yet ploidy is strikingly context dependent: many tumors remain near diploid in vivo despite the frequent emergence of highly polyploid states in vitro. Here, we estimate ploidy dependent chromosome missegregation tolerance using a mathematical model calibrated to growth and chromosome number data from matched near diploid and near tetraploid breast cancer cultures and xenografts. The model architecture reflects a tug of war between two opposing selective forces acting on ploidy--resource limitation that caps high ploidy by imposing energetic and biosynthetic costs, and CIN that can favor higher ploidy by buffering the fitness impact of chromosome gains and losses. The fitted model reproduced chromosome losses in 4N cultures and WGD followed by chromosome losses in 2N cultures. In vivo, the strongest determinants of ploidy shifted from stress associated death at low oxygen to baseline missegregation at higher oxygen. Joint calibration to both in vivo and in vitro contexts assigned tumors lower proliferation, an approximately tenfold higher stress-associated death scale, and an 11-16 fold larger maximal stress induced missegregation increment than cultures. Simulating populations across combinations of constant oxygen levels and missegregation settings showed that ploidy increased with oxygen under conditions supporting population growth. In both culture and tumors, mean ploidy above tetraploidy was associated with population decline. Together, the framework predicts when resource constraints favor chromosome loss and when missegregation tolerance permits high ploidy expansion, providing testable expectations for how CIN perturbations reshape ploidy evolution in different resource environments.

cancer biology↗

bioRxiv2026

Ploidy shapes gemcitabine response through altered potency and delayed cell death

Aberrant tumor ploidy is a near-universal hallmark of cancer and increasingly recognized as a determinant of therapeutic response, but the mechanisms by which ploidy shapes sensitivity to specific cytotoxic agents remain unclear. Here, we investigated the relationship between ploidy and therapeutic response using pharmacogenomic reanalysis, isogenic cancer cell systems, live-cell imaging, intracellular pharmacokinetic/ pharmacodynamic (PK/PD) measurements, and mathematical modeling. Across public pharmacogenomic datasets, gemcitabine emerged as a low-ploidy-selective cytotoxic agent. In matched isogenic low- and high-ploidy cell systems, higher-ploidy cells were consistently less sensitive to gemcitabine across multiple lineages. Live-cell imaging and PK/PD measurements in near-diploid and near-tetraploid SUM-159 cells showed that both states formed intracellular dFdCTP, active form of gemcitabine; but, high-ploidy cells exhibited weaker and slower treatment responses, with delayed accumulation of cell death. To quantify these differences, we developed a delay-aware live/dead model driven by intracellular dFdCTP exposure. The model identified both reduced effective gemcitabine potency and a substantially longer delay from intracellular drug action to observed death in high-ploidy cells (17.5 hours in near-diploid cells versus 42.5 hours in near-tetraploid cells). Interpreting these fitted quantities alongside checkpoint signaling and metabolomic profiling suggests that high-ploidy cells convert intracellular gemcitabine exposure less efficiently into replication-stress signaling, nucleotide-metabolic disruption, and cytotoxic commitment. Together, these results establish ploidy as a determinant of both the magnitude and timing of gemcitabine response and provide a quantitative framework for linking intracellular drug exposure to delayed cytotoxic outcomes across ploidy states.

cancer biology↗

bioRxiv2025

CLONEID: A Framework for Monitoring and Steering Subclonal Dynamics

Molecular assays can resolve clonal structure, but they are expensive and typically sparse in time, whereas phenotypic observations such as imaging can be collected frequently but often are not preserved in the context needed for later interpretation. We present CLONEID, an event-based framework for organizing clone-resolved phenotypic, molecular, and specimen-context records so that genotype-to-phenotype interpretation can be maintained across time. CLONEID links time-stamped Events, assay-specific Perspectives, and reconciled Identities through structured ingestion, provenance-aware retrieval, and reproducible export, complementing upstream clone-calling methods. In a long-term gastric cancer density-selection experiment, CLONEID linked repeated culture events, growth measurements, and late karyotypic profiling within a shared record, supporting longitudinal interpretation of phenotypic adaptation together with underlying chromosomal state.

bioinformatics↗

bioRxiv2024

Cell identity revealed by precise cell cycle state mapping links data modalities

Several methods for cell cycle inference from sequencing data exist and are widely adopted. In contrast, methods for classification of cell cycle state from imaging data are scarce. We have for the first time integrated sequencing and imaging derived cell cycle pseudo-times for assigning 449 imaged cells to 693 sequenced cells at an average resolution of 3.4 and 2.4 cells for sequencing and imaging data respectively. Data integration revealed thousands of pathways and organelle features that are correlated with each other, including several previously known interactions and novel associations. The ability to assign the transcriptome state of a profiled cell to its closest living relative, which is still actively growing and expanding opens the door for genotype-phenotype mapping at single cell resolution forward in time.

bioinformatics↗

bioRxiv2023

Interactions between ploidy and resource availability shape clonal interference at initiation and recurrence of glioblastoma

Glioblastoma (GBM) is the most aggressive form of primary brain tumor. Complete surgical resection of GBM is almost impossible due to the infiltrative nature of the cancer. While no evidence for recent selection events have been found after diagnosis, the selective forces that govern gliomagenesis are strong, shaping the tumors cell composition during the initial progression to malignancy with late consequences for invasiveness and therapy response. We present a mathematical model that simulates the growth and invasion of a glioma, given its ploidy level and the nature of its brain tissue micro-environment (TME), and use it to make inferences about GBM initiation and response to standard-of-care treatment. We approximate the spatial distribution of resource access in the TME through integration of in-silico modelling, multi-omics data and image analysis of primary and recurrent GBM. In the pre-malignant setting, our in-silico results suggest that low ploidy cancer cells are more resistant to starvation-induced cell death. In the malignant setting, between first and second surgery, simulated tumors with different ploidy compositions progressed at different rates. Whether higher ploidy predicted fast recurrence, however, depended on the TME. Historical data supports this dependence on TME resources, as shown by a significant correlation between the median glucose uptake rates in human tissues and the median ploidy of cancer types that arise in the respective tissues (Spearman r = -0.70; P = 0.026). Taken together our findings suggest that availability of metabolic substrates in the TME drives different cell fate decisions for cancer cells with different ploidy and shapes GBM disease initiation and relapse characteristics.

cancer biology↗

bioRxiv2019

Loss of Aurora kinase signaling allows lung cancer cells to adopt an alternative cell cycle and resist anti-mitotic drugs

Polyploid multinucleated (PP/MN) giant cancer cells are common in tumors and have been associated with resistance to cancer therapy, tumor relapse, malignancy, immunosuppression, metastasis, cancer stem cell production and modulation of the tumor microenvironment. However, the molecular mechanisms that cause these cells to form are yet known. In this study, we discover that Aurora kinases are synergistic determinants of a switch from the proliferative cell cycle to polyploid growth and multinucleation in lung cancer cell lines. When Aurora kinases are inhibited together, lung cancer cells uniformly grow into PP/MN giant cells. These cells have adopted an endocycle in which the genome replicates, mitosis is omitted and cells grow in size. Consequently, such cells continue to safely grow in the presence of antimitotic agents. These polyploid multinucleated cancer cells can re-enter the proliferative cell cycle and grow in cell number when the treatment is terminated.

cancer biology↗