Biology subjects

Roberts, M. G.

Publications and source records attributed to Roberts, M. G..

2 recordsLinked to original sources

bioRxiv2025

Glucocorticoids unleash immune-dependent melanoma control through inhibition of the GARP/TGF-β axis

Half of advanced melanoma patients fail to benefit from immune checkpoint blockade and novel treatments are urgently required. Testing topical medications used in other skin diseases for anti-cancer activity in an immunotherapy-resistant murine melanoma model, we counterintuitively found that glucocorticoids elicit rapid cytotoxic T lymphocyte (CTL)-dependent tumor control. Genetic ablation of the glucocorticoid receptor in different cellular compartments revealed glucocorticoids acted not on immune cells but directly on tumor cells to downregulate expression of GARP (glycoprotein A repetitions predominant). This inhibited TGF-{beta} signaling and unleashed CTL killing. In agreement, glucocorticoids stimulated tumor control in multiple cancer models, but only if the tumors also responded to pharmacological inhibition of TGF-{beta} signaling. Furthermore, melanoma patients with high glucocorticoid receptor expression or signaling showed improved prognosis and lower TGF-{beta} signaling in tumor-infiltrating CTLs. Additionally, elevated GARP expression correlated with reduced survival, including in immunotherapy-treated patients. Thus, the GARP/TGF-{beta} axis emerges as a glucocorticoid-sensitive cancer cell-intrinsic immune evasive mechanism. SignificanceScreening widely used topical treatments in a melanoma model, this study uncovers a surprising role for glucocorticoids in triggering CD8+ T cell-dependent tumor control through downregulation of GARP and thus TGF-{beta} signaling. Melanoma patient sample analysis supported these findings suggesting GARP/TGF-{beta} activity functions as a tumor cell-intrinsic immune evasive mechanism, and GARP expression may serve as both a biomarker of poor antitumor immunity and a therapeutic target to improve the response to immunotherapy.

cancer biology↗

bioRxiv2020

Reproducibility in systems biology modelling

The reproducibility crisis has emerged as an important concern across many fields of science including life science, since many published results failed to reproduce. Systems biology modelling, which involves mathematical representation of biological processes to study complex system behaviour, was expected to be least affected by this crisis. While lack of reproducibility of experimental results and computational analysis could be a repercussion of several compounded factors, it was not fully understood why systems biology models with well-defined mathematical expressions fail to reproduce and how prevalent it is. Hence, we systematically attempted to reproduce 455 kinetic models of biological processes published in peer-reviewed research articles from 152 journals; which is collectively a work of about 1400 scientists from 49 countries. Our investigation revealed that about half (49%) of the models could not be reproduced using the information provided in the published manuscripts. With further effort, an additional 12% of the models could be reproduced either by empirical correction or support from authors. The other 37% remained non-reproducible models due to missing parameter values, missing initial concentration, inconsistent model structure, or a combination of these factors. Among the corresponding authors of the non-reproducible model we contacted, less than 30% responded. Our analysis revealed that models published in journals across several fields of life science failed to reproduce, revealing a common problem in the peer-review process. Hence, we propose an 8-point reproducibility scorecard that can be used by authors, reviewers and journal editors to assess each model and address the reproducibility crisis.

systems biology↗