Biology subjects

Broderick, J.

Publications and source records attributed to Broderick, J..

3 recordsLinked to original sources

bioRxiv2026

Profiling Siglec-7 and Siglec-9 ligands across the LuCaP PDX series: Implications for glyco-immune checkpoint inhibition in advanced prostate cancer

Advanced prostate cancer exhibits profound cellular and molecular heterogeneity, frequently becoming resistant to androgen receptor (AR) targeting through lineage plasticity and neuroendocrine differentiation. Immunotherapies have shown limited efficacy in prostate cancer, largely due to its immunosuppressive tumour microenvironment. Hypersialylation contributes to immune evasion by engaging sialic acid-binding immunoglobulin-like lectins (Siglecs) on immune cells, forming glyco-immune checkpoints. Although this pathway represents a promising therapeutic target, the distribution of Siglec ligands across diverse prostate cancer phenotypes and their response to standard-of-care hormone therapy remain poorly understood. Here, we utilised high-affinity engineered sialoglycan-binding reagents (HYDRA) to perform comprehensive immunohistochemical profiling of Siglec-7 and Siglec-9 ligands across a panel of 40 Washington Carcinoma of the Prostate (LuCaP) patient-derived xenograft (PDX) models. Ligand expression was evaluated in relation to AR status and neuroendocrine phenotype. To determine the impact of androgen deprivation on the tumour glycome, ligand expression was compared between matched PDX lines grown in intact and castrated mice. Our findings reveal widespread but heterogeneous expression of Siglec-7 and Siglec-9 ligands across the LuCaP cohort. Expression levels were comparable between AR-positive adenocarcinoma models and AR-negative neuroendocrine variants, demonstrating that this glyco-immune checkpoint is maintained across distinct prostate cancer lineages. Under castration conditions, glycan remodelling occurred in a model-dependent manner. A subset of PDX models exhibited reduced Siglec ligand expression following castration, suggesting partial AR dependence. In contrast, other models displayed increased ligand expression, consistent with adaptive immune evasion in response to therapeutic stress, while a third group remained largely unchanged. Collectively, our study demonstrates that the Siglec-7/9 glyco-immune checkpoint axis is broadly maintained across the spectrum of prostate cancer lineage plasticity but is dynamically remodelled by androgen deprivation in a patient-specific manner. These findings support the sialoglycan-Siglec axis as a lineage-independent immunotherapeutic target and suggest that strategies aimed at disrupting Siglec-mediated immune suppression, such as tumour desialylation, may be most effective when combined with androgen deprivation therapy to enhance anti-tumour immunity.

cancer biology↗

bioRxiv2021

Targeting cancer glycosylation repolarizes tumor-associated macrophages allowing effective immune checkpoint blockade

Immune checkpoint blockade (ICB) has significantly improved the prognosis of cancer patients, but the majority experience limited benefit, evidencing the need for new therapeutic approaches. Upregulation of sialic acid-containing glycans, termed hypersialylation, is a common feature of cancer-associated glycosylation, driving disease progression and immune escape via the engagement of Siglec-receptors on tumor-infiltrating immune cells. Here, we show that tumor sialylation correlates with distinct immune states and reduced survival in human cancers. The targeted removal of Siglec-ligands in the tumor microenvironment, using an antibody-sialidase conjugate, enhances anti-tumor immunity and halts tumor progression in several mouse tumor models. Using single-cell RNA sequencing, we reveal desialylation mechanistically to repolarize tumor-associated macrophages (TAMs) and identify Siglec-E on TAMs as the main receptor for hypersialylation. Finally, we show genetic and therapeutic desialylation, as well as loss of Siglec-E, to synergize with ICB. Thus, therapeutic desialylation represents a novel immunotherapeutic approach, shaping macrophage phenotypes and augmenting the adaptive anti-tumor immune response.

immunology↗

bioRxiv2020

The price of a bit: energetic costs and the evolution of cellular signaling

Recent experiments have uncovered a fundamental information scale for cellular signaling networks: the correlation between input and output concentrations of molecules in a signaling pathway corresponds to at most 1-3 bits of mutual information. Our understanding of the physical constraints and evolutionary pressures that determine this scale remains incomplete. By focusing on a basic element of signaling pathways, the kinase-phosphatase enzymatic push-pull loop, we highlight the pivotal role played by energy resources available for signaling and their expenditure: the chemical potential energy of ATP hydrolysis, and the rate of ATP consumption. Scanning a broad range of reaction parameters based on enzymatic databases, we find that ATP chemical potentials in modern organisms are just above the threshold necessary to achieve empirical mutual information values. We also derive an analytical relation for the minimum ATP consumption required to maintain a certain signal fidelity across a range of input frequencies, where we quantify fidelity either through instantaneous or time-delayed mutual information. Attempting to increase signal fidelity beyond a few bits lowers the bandwidth, the maximum characteristic signal frequency that the network can handle at a given energy cost. The observed information scale thus represents a balancing act between fidelity and the ability to process fast-changing environmental signals. Our analytical relation defines a performance limit for kinase-phosphatase networks, and we find evidence that a component of the yeast osmotic shock pathway may be close to the optimality line. By quantifying the evolutionary pressures that operate on these networks, we argue that this is not a coincidence: natural selection on energy expenditures is capable of pushing signaling systems toward optimality, particularly in unicellular organisms. Our theoretical framework is directly verifiable using existing experimental techniques, and predicts that more examples of such optimality should exist in nature.

systems biology↗