Biology subjects

Ross, A. M.

Publications and source records attributed to Ross, A. M..

4 recordsLinked to original sources

bioRxiv2026

Pre-existing levels of pro-survival proteins and induction of BCL-XL dictate cell fate after p53 activation

TP53 (also called TRP53 or p53) is a critical tumour suppressor that prevents cancer development by inducing a transcriptional program which can lead to diverse cellular responses, most prominently, cell proliferation arrest/senescence with survival of cells or cell death by apoptosis. Why distinct cell types undergo different outcomes after p53 activation remains unclear. Using integrated RNA-sequencing, proteomic and functional analyses across a diverse range of murine primary cell types, we demonstrate that cell fate is governed by the balance between pro-survival BCL-2 and pro-apoptotic BH3-only proteins. Cells resistant to apoptosis displays a higher starting ratio of pro-survival BCL-2 to pro-apoptotic BH3-only proteins, along with transcriptional upregulation of the pro-survival gene Bcl2l1, encoding BCL-XL. This control of cell fate is also seen in human wild-type p53 cancer cell lines. These findings reveal the mechanism for understanding p53-driven cell fate decisions, suggest therapeutic strategies to shift p53-induced cell proliferation arrest/senescence toward apoptotic cell death and allowed generation of an RNAseq data-based predictor of outcome for cancer cells after p53 activation.

cancer biology↗

bioRxiv2026

Loss of systemic anti-viral immunity and LMP1-driven suppressive myeloid tumour niches converge to shape the immunobiology of EBV+ diffuse large B-cell lymphoma

Epstein-Barr virus (EBV)-positive diffuse large B-cell lymphoma (EBVDLBCL) is an aggressive lymphoma with poor outcomes and an incompletely understood pathogenesis, frequently attributed to immunosenescence. However, its occurrence across all age groups suggests alternative mechanisms. Here, we integrate functional profiling of peripheral antiviral T-cell immunity with high-dimensional spatial proteomics and mechanistic in vitro modelling to define the immunological landscape of EBVDLBCL. We show that both EBV and EBV-DLBCL patients exhibit broad impairments in antiviral T-cell responses compared with healthy controls, affecting latent and lytic EBV antigens as well as non-EBV viral targets, with deficits most pronounced in EBV patients. Spatial proteomic analysis revealed that EBVDLBCL harbours a profoundly immunosuppressive tumour microenvironment characterised by relative loss of intratumoural CD8 T cells, expansion of PD-1 regulatory and exhausted T-cell populations, and dense aggregates of PD-L1/IDO1 macrophages. Compared with EBV classical Hodgkin lymphoma and infectious mononucleosis, EBV DLBCL displayed the most marked macrophage-associated immunosuppressive signature and the lowest T-cell density. Suppressive myeloid niches were preferentially enriched around LMP1-expressing tumour cells, a feature not observed in the other EBV-associated conditions. Together, these findings indicate that EBVDLBCL is driven by the convergence of systemic antiviral immune dysfunction and an LMP1-dependent suppressive tumour microenvironment.

cancer biology↗

bioRxiv2025

CellMAPS: A no-code model-based customisable multiplex image analysis workflow

Although multiplex imaging allows simultaneous mapping of complex tissue architectures and cellular phenotypes, the dearth of user-friendly robust image analysis workflows remains a significant limitation to its widespread use, restricting multiplex imaging to laboratories with image analysis expertise. Here, we introduce a no-code model-based customisable suite, CellMAPS, which allows both image processing and spatial analyses by non-specialists. We also developed new tools for tissue de-arraying, image normalisation and cell segmentation to increase usability and reduce analysis subjectivity. We have also introduce new spatial analysis tools for the partition of tissue architectures and cellular microenvironments. We demonstrate the capabilities of CellMAPS in various diseases captured using different multiplex imaging platforms. Overall, CellMAPS provides a platform for inexperienced laboratories to implement multiplex imaging and complex spatial analyses, which ultimately should lead to the broader adoption of these technologies in the biomedical field.

bioinformatics↗

bioRxiv2023

Accurate Automated Segmentation of Autophagic Bodies in Yeast Vacuoles Using Cellpose 2.0

Segmenting autophagic bodies in yeast TEM images is a key technique for measuring changes in autophagosome size and number in order to better understand autophagy. Manual segmentation of these images can be very time consuming, particularly since hundreds of images are needed for accurate measurements. Here we describe a validated Cellpose 2.0 model that can segment these images with accuracy comparable to that of human experts. This model can be used for fully automated segmentation, eliminating the need for manual body outlining, or for model-assisted segmentation, which allows human oversight but is still five times as fast as the current manual method. The model and instructions for its use are presented here for the autophagy community.

cell biology↗