Biology subjects

Bravo, R.

Publications and source records attributed to Bravo, R..

9 recordsLinked to original sources

bioRxiv2026

Lipid acyl chain remodeling governs KRAS nanoclustering and oncogenic functions through membrane composition control

KRAS signaling is spatially organized within the dynamic proteolipid nanoclusters on the plasma membrane (PM) that selectively concentrate anionic phospholipids, yet the molecular determinants governing this lipid sorting remain incompletely defined. Here we identify phospholipid acyl chain composition as a critical regulator of KRAS spatial organization and signal output. Using genetic and pharmacological perturbation of lysophosphatidylcholine acyltransferase 3 (LPCAT3), a key enzyme that incorporates polyunsaturated fatty acids into phospholipids, we demonstrate that remodeling of membrane acyl chain unsaturation alters the phosphatidylserine (PS) lipidome without changing total PS abundance. Loss of LPCAT3 depletes polyunsaturated PS species, disrupts KRAS PM association and nanoclustering, and attenuates downstream MAPK signaling and oncogenic activity across multiple KRAS mutant contexts. Acute restoration of polyunsaturated, but not saturated, lipids rescue KRAS nanoclustering, establishing a direct requirement for lipid unsaturation in sustaining signaling-competent assemblies. Mechanistically, these findings define membrane acyl chain composition as a determinant of proteolipid organization that encodes KRAS signaling capacity. Consistent with this model, LPCAT3 inhibition selectively impairs KRAS-dependent proliferation and sensitizes tumor cells to direct KRAS inhibition. Together, this work uncovers lipid acyl chain remodeling as a fundamental regulator of membrane-associated signaling and identifies membrane composition as an exploitable vulnerability in oncogenic KRAS systems.

cancer biology↗

bioRxiv2024

Spatial interactions modulate tumor growth and immune infiltration

Direct observation of immune cell trafficking patterns and tumor-immune interactions is unlikely in human tumors with currently available technology, but computational simulations based on clinical data can provide insight to test hypotheses. It is hypothesized that patterns of collagen formation evolve as a mechanism of immune escape, but the exact nature of the interaction between immune cells and collagen is poorly understood. Spatial data quantifying the degree of collagen fiber alignment in squamous cell carcinomas indicates that late stage disease is associated with highly aligned fibers. Here, we introduce a computational modeling framework (called Lenia) to discriminate between two hypotheses: immune cell migration that moves 1) parallel or 2) perpendicular to collagen fiber orientation. The modeling recapitulates immune-ECM interactions where collagen patterns provide immune protection, leading to an emergent inverse relationship between disease stage and immune coverage. We also illustrate the capabilities of Lenia to model the evolution of tumor progression and immune predation. Lenia provides a flexible framework for considering a spectrum of local (cell-scale) to global (tumor-scale) dynamics by defining a kernel cell-cell interaction function that governs tumor growth dynamics under immune predation with immune cell migration. Mathematical modeling provides important mechanistic insights into cell interactions. Short-range interaction kernels provide a mechanism for tumor cell survival under conditions with strong Allee effects, while asymmetric tumor-immune interaction kernels lead to poor immune response. Thus, the length scale of tumor-immune interactions drives tumor growth and infiltration.

cancer biology↗

bioRxiv2023

Bibliometric analysis on cannibalism/infanticide and maternal aggression towards pups in laboratory animals

Animal welfare has evolved during the past decades to improve not only the quality of life of laboratory animals but also the quality and reproducibility of scientific investigations. Bibliometric analysis has become an important tool to complete the current knowledge with academic databases. Our objective was to investigate whether scientific research on cannibalism/infanticide is connected with maternal aggression towards the offspring in laboratory animals. To carry out our research, we performed a specific search for published articles on each concept. Results were analyzed in the opensource environment RStudio with the package Bibliometrix. We obtained 228 and 134 articles for the first search (cannibalism/infanticide) and the second search (maternal aggression towards the pups) respectively. We observed that the interest in infanticide cannibalism started in the 1950s, while researchers started showing interest in maternal aggression towards the pups 30 years later. Our analyses indicated that maternal aggression had better citations in scientific literature. In addition, although our results showed some common features (e.g., oxytocin or medial preoptic area in the brain), we observed a gap between cannibalism/infanticide and maternal aggression towards the pups with only 18 published articles in common for both the searches. Therefore, we recommend researchers to combine both concepts in further investigations in the context of cannibalism for better dissemination and higher impact in laboratory animals welfare research. Highlights- Cannibalism/Infanticide and maternal aggression have been investigated separately. - Maternal aggression has a higher impact on scientific literature. - Combining both topics may increase cannibalism/infanticide impact.

animal behavior and cognition↗

bioRxiv2022

Tumor-immune metaphenotypes orchestrate an evolutionary bottleneck that promotes metabolic transformation

Metabolism plays a complex role in the evolution of cancerous tumors, including inducing a multifaceted effect on the immune system to aid immune escape. Immune escape is, by definition, a collective phenomenon by requiring the presence of two cell types interacting in close proximity: tumor and immune. The microenvironmental context of these interactions is influenced by the dynamic process of blood vessel growth and remodelling, creating heterogeneous patches of well-vascularized tumor or acidic niches. We present a multiscale mathematical model that captures the phenotypic, vascular, microenvironmental, and spatial heterogeneity which shapes acid-mediated invasion and immune escape over a biologically-realistic time scale. We model immune escape mechanisms such as i) acid inactivation of immune cells, ii) competition for glucose, and iii) inhibitory immune checkpoint receptor expression (PD-L1) under anti-PD-L1 and sodium bicarbonate buffer therapies. To aid in understanding immune escape as a collective cellular phenomenon, we define immune escape in the context of six collective phenotypes (termed "meta-phenotypes"): Self-Acidify, Mooch Acid, PD-L1 Attack, Mooch PD-L1, Proliferate Fast, and Starve Glucose. Fomenting a stronger immune response leads to initial benefits but this advantage is offset by increased cell turnover that accelerates the emergence of aggressive phenotypes by inducing an evolutionary bottleneck. This model helps to untangle the key constraints on evolutionary costs and benefits of three key phenotypic axes on tumor invasion and treatment: acid-resistance, glycolysis, and PD-L1 expression. The benefits of concomitant anti-PD-L1 and buffer treatments is a promising treatment strategy to limit the adverse effects of immune escape. O_TEXTBOXSignificance statement In this work, we present a multi-scale mathematical model that captures the phenotypic, vascular, microenvironmental, and spatial heterogeneity which shapes acid-mediated invasion and immune escape over a biologically-realistic time scale. To aid in understanding immune escape as a collective cellular phenomenon, we introduce the concept of metaphenotypes: immune escape mechanisms that account for cellular phenotype and surrounding context. Metaphenotypes are defined by accounting for the following: cellular phenotype, microenvironmental factors, neighboring cell types, and immune-tumor interactions. These metaphenotypes provide insight into why targeting intratumoral pH with bicarbonate buffer is a synergistic combination treatment when paired with immune checkpoint blockade. C_TEXTBOX

cancer biology↗

bioRxiv2019

Modeling adaptive therapy in non-muscle invasive bladder cancer

Bladder cancer is the 9th most commonly diagnosed cancer. Nearly half of patients with early stage bladder cancer treated with the immune-stimulating agent BCG have disease recurrence, while 13% progress to invasive bladder cancer. Here we explored the potential of tumor mutational heterogeneity and the role of pro- and anti-inflammatory cytokines to identify different subtypes of bladder cancer that may predict therapeutic response to BCG. Further, we used mathematical modeling of dosing strategies to infer tumor response to varying doses and time schedules f BCG administration. As a proof-of-concept, present adaptive therapy scheduling of BCG as a viable strategy to control tumor size and minimize recurrence.

cancer biology↗

bioRxiv2019

Clonal Architecture of the Epidermis: Homeostasis Limits Keratinocyte Evolution

The skin is the largest human organ, functioning to serve as the protective barrier to the harsh, outside world. Recent studies have revealed that large numbers of somatic mutations accumulate in normal tissue, which can be used to infer skin cell dynamics1-5. Here we present the first realistic, cell-genome mechanistic epidermal model that shows homeostasis imposes a characteristic log-linear subclone size distribution for both neutral and oncogenic driver mutations, where the largest skin subclones are the oldest subclones. Because homeostasis inherently limits proliferation and therefore clonal sweeps, selection for driver mutations (NOTCH1 and TP53) in normal epidermis is instead conferred by greater persistence, which leads to larger subclone sizes. These results highlight how the integration of mechanistic modeling with genomic data provide novel insights into the evolutionary cell dynamics of normal human homeostatic tissues.

evolutionary biology↗

bioRxiv2018

Acidity promotes tumor progression by altering macrophage phenotype in prostate cancer

Tumors rapidly ferment glucose to lactic acid even in the presence of oxygen, and coupling high glycolysis with poor perfusion leads to extracellular acidification. Here we demonstrate that acidity, independent from lactate, augments the pro-tumor phenotype of macrophages. We used zwitterionic buffers to show that activating macrophages at pH 6.8 in vitro enhanced an IL-4-driven phenotype as measured by gene expression, cytokine profiling, and functional assays. These results were recapitulated in vivo wherein neutralizing intratumoral acidity reduced the pro-tumor phenotype of macrophages, while also decreasing tumor incidence and invasion in the TRAMP model of prostate cancer. These results were recapitulated using an in silico mathematical model that simulate macrophage responses to environmental signals. By turning off acid-induced cellular responses, our in silico mathematical modeling shows that acid-resistant macrophages can limit tumor progression. In summary, this study suggests that tumor acidity contributes to prostate carcinogenesis by altering the state of macrophage activation.

immunology↗

bioRxiv2018

Evolutionary exploitation of PD-L1 expression in hormone receptor positive breast cancer

Based on clinical data from hormone positive breast cancer patients, we determined that there is a potential tradeoff between reducing tumor burden and altering metastatic potential when administering combination therapy of aromatase inhibitors and immune checkpoint inhibitors. While hormone-deprivation therapies serve to reduce tumor size in the neoadjuvant setting pre-surgery, they may induce tumors to change expression patterns towards a metastatic phenotype. We used mathematical modeling to explore how the timing of the therapies affects tumor burden and metastatic potential with an eye toward developing a dynamic prognostic score and reducing both tumor size and risk of metastasis.

cancer biology↗

bioRxiv2017

Combining radiomics and mathematical modeling to elucidate mechanisms of resistance to immune checkpoint blockade in non-small cell lung cancer

Immune therapies have shown promise in a number of cancers, and clinical trials using the anti-PD-L1/PD-1 checkpoint inhibitor in lung cancer have been successful for a number of patients. However, some patients either do not respond to the treatment or have cancer recurrence after an initial response. It is not clear which patients might fall into these categories or what mechanisms are responsible for treatment failure. To explore the different underlying biological mechanisms of resistance, we created a spatially explicit mathematical model with a modular framework. This construction enables different potential mechanisms to be turned on and off in order to adjust specific tumor and tissue interactions to match a specific patient's disease. In parallel, we developed a software suite to identify significant computed tomography (CT) imaging features correlated with outcome using data from an anti-PDL-1 checkpoint inhibitor clinical trial for lung cancer and a tool that extracts these features from both patient CT images and \"virtual CT\" images created from the cellular density profile of the model. The combination of our two toolkits provides a framework that feeds patient data through an iterative pipeline to identify predictive imaging features associated with outcome, whilst at the same time proposing hypotheses about the underlying resistance mechanisms.

cancer biology↗