Biology subjects

Casanova, R.

Publications and source records attributed to Casanova, R..

5 recordsLinked to original sources

bioRxiv2024

Transposable element methylation state predicts age and disease

Transposable elements (TEs) are DNA sequences that expand selfishly in the genome, possibly causing severe cellular damage. While normally silenced, TEs have been shown to activate during aging. DNA methylation is one of the main mechanisms by which TEs are silenced and has been used to train highly accurate age predictors. Yet, one common criticism of such predictors is that they lack interpretability. In this study, we investigate the changes in TE methylation that occur during human aging. We find that evolutionarily young LINE1s (L1s), the only known TEs capable of autonomous transposition in humans, undergo the fastest loss of methylation, suggesting an active mechanism of de-repression. We then show that accurate age predictors can be trained on both methylation of individual TE copies and average methylation of TE families genome wide. Lastly, we show that while old L1s gradually lose methylation during the entire lifespan, demethylation of young L1s only happens late in life and is associated with cancer.

genomics↗

bioRxiv2024

SMAC mimetics overcome apoptotic resistance in ovarian cancer through MSLN-TNF alpha axis

Resistance to chemotherapy and PARPi inhibitors remains a critical challenge in the treatment of epithelial ovarian cancer, mainly due to disabled apoptotic responses in tumor cells. Given mesothelins pivotal role in ovarian cancer and its restricted expression in healthy tissues, we conducted a drug-screening discovery analysis across a range of genetically modified cancer cells to unveil mesothelins therapeutic impact. We observed enhanced cell death in cancer cells with low mesothelin expression when exposed to a second mitochondria-derived activator of caspases (SMAC) mimetics, and demonstrated a compelling synergy when combined with chemotherapy in ex vivo patient-derived cultures and zebrafish tumor xenografts. Mechanistically, the addition of the SMAC mimetics drug birinapant to either carboplatin or paclitaxel triggered the activation of the Caspase 8-dependent apoptotic program facilitated by TNFLJ signaling. Multimodal analysis of neoadjuvant-treated patient samples further revealed an association between tumor-associated macrophages and the activation of TNFLJ-related pathways. Our proposed bimodal treatment shows promise in enhancing the clinical management of patients by harnessing the potential of SMAC mimetics alongside conventional chemotherapy.

cancer biology↗

bioRxiv2023

Systems Age: A single blood methylation test to quantify aging heterogeneity across 11 physiological systems

Individuals, organs, tissues, and cells age in diverse ways throughout the lifespan. Epigenetic clocks attempt to quantify differential aging between individuals, but they typically summarize aging as a single measure, ignoring within-person heterogeneity. Our aim was to develop novel systems-based methylation clocks that, when assessed in blood, capture aging in distinct physiological systems. We combined supervised and unsupervised machine learning methods to link DNA methylation, system-specific clinical chemistry and functional measures, and mortality risk. This yielded a panel of 11 system-specific scores- Heart, Lung, Kidney, Liver, Brain, Immune, Inflammatory, Blood, Musculoskeletal, Hormone, and Metabolic. Each system score predicted a wide variety of outcomes, aging phenotypes, and conditions specific to the respective system. We also combined the system scores into a composite Systems Age clock that is predictive of aging across physiological systems in an unbiased manner. Finally, we showed that the system scores clustered individuals into unique aging subtypes that had different patterns of age-related disease and decline. Overall, our biological systems based epigenetic framework captures aging in multiple physiological systems using a single blood draw and assay and may inform the development of more personalized clinical approaches for improving age-related quality of life.

systems biology↗

bioRxiv2023

Standardization of suspension and imaging mass cytometry readouts for clinical decision making

Suspension and imaging mass cytometry are single-cell, proteomic-based methods used to characterize tissue composition and structure. Data assessing the consistency of these methods over an extended period of time are still sparse and are needed if mass cytometry-based methods are to be used clinically. Here, we present experimental and computational pipelines developed within the Tumor Profiler clinical study, an observational clinical trial assessing the relevance of cutting-edge technologies in guiding treatment decisions for advanced cancer patients. By using aliquots of frozen antibody panels, batch effects between independent experiments performed within a time frame of one year were minimized. The inclusion of well-characterized reference samples allowed us to assess and correct for batch effects. A systematic evaluation of a test tumor sample analyzed in each run showed that our batch correction approach consistently reduced signal variations. We provide an exemplary analysis of a representative patient sample including an overview of data provided to clinicians and potential treatment suggestions. This study demonstrates that standardized suspension and imaging mass cytometry measurements generate robust data that meet clinical requirements for reproducibility and provide oncologists with valuable insights on the biology of patient tumors.

cancer biology↗

bioRxiv2023

Statistical modeling and analysis of multiplexed imaging data

The rapid development of multiplexed imaging technologies has enabled the spatial cartography of various healthy and tumor tissues. However, the lack of adequate statistical models has hampered the use of multiplexed imaging to efficiently compare tissue composition across sample groups, for instance between healthy and tumor tissue samples. Here, we developed two statistical models that accurately describe the distribution of cell counts observed in a given field of view in an imaging experiment. The parameters of these distributions are directly linked to the field of view size and also to properties of the studied cell type such as cellular density and spatial aggregation. Using these models, we identified statistical tests that have improved statistical power for differential abundance testing of tissue composition compared to the commonly used rank-based test. Our analysis revealed that spatial aggregation is the main determinant of statistical power and that to have sufficient power to detect differences in cell counts when cells are highly aggregated may require sampling of hundreds of fields of view. To overcome this challenge, we provide a new stratified sampling strategy that might significantly reduce the number of required samples.

bioinformatics↗