Biology subjects

Koerber, J. T.

Publications and source records attributed to Koerber, J. T..

4 recordsLinked to original sources

bioRxiv2026

Inhibition of integrin αvβ8-mediated TGFβ activation and active-TGFβ blockade promote anti-tumor immunity through distinct biological mechanisms

Transforming Growth Factor {beta} (TGF{beta}) is a potent immunosuppressor and a primary driver of resistance to cancer immunotherapy. While preclinical models have long suggested that TGF{beta} inhibition could synergize with immune checkpoint inhibitors, these effects have proven difficult to replicate in clinical settings. The highly regulated TGF{beta} pathway can be inhibited through various mechanisms, including neutralizing activated ligands or inhibiting upstream activators, such as integrins. Recent structural data demonstrated that integrin v{beta}8 can enable TGF{beta}1/3 signaling without releasing the active cytokines from their Latency-Associated Peptides, suggesting that ligand-blocking antibodies may have limited access to their epitopes. Here, we show that integrin v{beta}8 blockade, while achieving anti-tumor responses similar to those of anti-TGF{beta} antibodies, does so through a distinct mechanism of action. Anti-v{beta}8 is 3 orders of magnitude more potent at inhibiting v{beta}8-mediated TGF{beta} activity than a commonly used antibody against the mature form of the cytokine. Whereas TGF{beta} ligand inhibition has little effect on TGF{beta} signaling in tumor-draining lymph nodes (tdLN) and requires IFN{gamma} for its anti-tumor effects, v{beta}8 blockade strongly inhibits TGF{beta} signaling in tdLN and, in combination with PD-L1 blockade, drives tumor control through an IFN{gamma} -independent mechanism that strictly requires T cell egress from tdLN. Combined v{beta}8 and anti-PD-L1 blockade enhances antigen presentation in dendritic cells (DCs) and, unlike TGF{beta} ligand blockade, improves the efficiency of DC-induced T cell activation in response to cross-presented antigen. These findings suggest that v{beta}8 blockade can disable an immunologically critical source of TGF{beta} signaling that is not addressed by antibodies targeting TGF{beta} ligands, suggesting a promising new approach to TGF{beta} pathway modulation. One Sentence SummaryUnlike ligand-neutralizing antibodies, v{beta}8 blockade suppresses TGF{beta} in tdLN and boosts DC-T cell activation, a differentiated immunotherapy strategy.

immunology↗

bioRxiv2025

Property Enhancer - a data efficient multi-objective approach for functional antibody optimization

In-silico antibody lead optimization remains challenging due to scarce high-quality data, costly experimental validation, and the need to jointly optimize multiple developability properties. Discovery workflows often rely on high-throughput phage, ribosome or yeast display experiments, which yield large but noisy datasets; as leads emerge, strategies shift to low-throughput assays which are precise, yet unscalable. Deep-learning and language-model approaches are hindered by such limited, unreliable measurements. We introduce Property Enhancer (PropEn), a data-efficient framework for low-data, heterogeneous regimes that can simultaneously optimize multiple antibody properties. PropEn proposes a matching-based augmentation that expands the training data with sequence pairs differing by only a few mutations; within each pair the second sequence improves the target value, providing an implicit optimization signal. Extensive in silico and in vitro tests show 10-39x affinity gains across four targets and nine leads, and enable joint multi-property optimization, positioning PropEn as a scalable, general solution.

molecular biology↗

bioRxiv2025

Lab-in-the-loop therapeutic antibody design with deep learning

Therapeutic antibody design is a complex multi-property optimization problem with substantial promise for improvement with the application of machine-learning methods. Towards realizing that promise, we introduce "Lab-in-the-loop," a new approach that orchestrates state-of-the-art repertoire mining methods, generative machine learning models, multi-task property predictors, active learning ranking and selection, and in vitro experimentation in a semi-autonomous, iterative optimization loop. By automating the design of antibody variants, property prediction, ranking and selection of designs to assay in the lab, and ingestion of in vitro data, we enable an end-to-end approach to developing computationally-informed therapeutic antibody design pipelines. We apply lab-in-the-loop to eleven seed antibodies obtained via animal immunization with four clinically relevant antigen targets: EGFR, IL-6, HER2, and OSM. Over 1,800 unique antibody variants are tested throughout four rounds of iterative optimization identifying 3-100x better binding variants for all targets and 10/11 seeds, with the best binders exceeding 100 pM affinity, demonstrating a process by which end-to-end machine learning can be developed for therapeutic antibody development.

bioengineering↗

bioRxiv2022

Loss of the intracellular enzyme QPCTL limits chemokine function and reshapes myeloid infiltration to augment tumor immunity

Tumor-associated macrophages are composed of distinct populations arising from monocytes or tissue macrophages, with a poorly understood link to disease pathogenesis. Here, we demonstrate that mouse monocyte migration was supported by glutaminyl-peptide cyclotransferase-like (QPCTL), an enzyme that mediates N-terminal modification of several subtrates, including the monocyte-chemoattractants CCL2 and CCL7, protecting them from proteolytic inactivation. Knockout of Qpctl disrupted monocyte homeostasis, attenuated tumor growth and reshaped myeloid cell infiltration, with loss of monocyte-derived populations with immunosuppressive and pro-angiogenic profiles. Antibody blockade of the receptor CSF1R, which more broadly eliminates tissue macrophages, reversed tumor growth inhibition in Qpctl-/- mice, and prevented lymphocyte infiltration. Modulation of QPCTL synergized with anti-PD-L1 to expand CD8+ T cells and limit tumor growth. QPCTL inhibition constitutes an effective approach for myeloid cell-targeted cancer immunotherapy.

immunology↗