Classical Dichotomy of Macrophages and Alternative Activation Models Proposed with Technological Progress

Quantitative systems pharmacology modeling of macrophage-targeted therapy combined with PD-L1 inhibition in advanced NSCLC

Immune checkpoint inhibitors remained the standard-of-care treatment for advanced non-small cell lung cancer (NSCLC) for the past decade. In unselected patients, anti-PD-(L)1 monotherapy achieved an overall response rate of about 20%. In this analysis, we developed a pharmacokinetic and pharmacodynamic module for our previously calibrated quantitative systems pharmacology model (QSP) to simulate the effectiveness of macrophage-targeted therapies in combination with PD-L1 inhibition in advanced NSCLC. By conducting in silico clinical trials, the model confirmed that anti-CD47 treatment is not an optimal option of second- and later-line treatment for advanced NSCLC resistant to PD-(L)1 blockade. Furthermore, the model predicted that inhibition of macrophage recruitment, such as using CCR2 inhibitors, can potentially improve tumor size reduction when combined with anti-PD-(L)1 therapy, especially in patients who are likely to respond to anti-PD-(L)1 monotherapy and those with a high level of tumor-associated macrophages. Here, we demonstrate the application of the QSP platform on predicting the effectiveness of novel drug combinations involving immune checkpoint inhibitors based on preclinical or early-stage clinical trial data.

Role of macrophage polarisation in skin wound healing

Skin wound healing is a complex pathophysiological change that is driven by macrophages and their secreted related factors. Depending on the stimuli, macrophages can be polarised into two subtypes of macrophages with completely different phenotypes and functions, namely M1 and M2. The aim of this study was to explore the role of M1 and M2 macrophages in skin healing in order to develop new drugs for the treatment of refractory wounds. Primary bone marrow-derived macrophages (BMDMs) were isolated from rats and expanded in vitro using macrophage colony stimulating factor. In addition, the BMDMs were polarised into the M1 and M2 subtypes using lipopolysaccharides (LPS) and interleukin-4 (IL-4), respectively. Cytokine levels in the culture supernatants were measured by an enzyme linked immunosorbent assay. Epidermal wounds were made on the dorsal surface of rats, and treated with M1 or M2 cell suspensions or phosphate buffered saline. Wound healing was recorded on days 1, 3, 7, 10, and 14 after stamping, and the wound healing rate was measured by haematoxylin-eosin and Masson staining. A total of 3 to 4 × 107 bone marrow cells were extracted from each rat femur. The BMDM culture had 87.1% CD45+ cells, 89.2% CD68+ cells, and 86.5% CD45+ CD68+ cells. Furthermore, IL-12 (P < .05) and IL-10 (P ≥ .05) levels, respectively, increased and decreased in the culture supernatants of the M1 cells after LPS stimulation compared with those in the M0 (unstimulated) group. Likewise, IL-4 stimulation led to a significant increase in IL-10 levels (P < .01) in the conditioned media of M2 cells, while that of IL-12 decreased slightly (P ≥ .05). In the rat model, the infusion of M2 cells accelerated wound healing and tissue regeneration, whereas the M1 cells delayed the recruitment of inflammatory cells, granulation growth, and collagen deposition, which impaired wound healing. Macrophage polarisation and activation are critical for skin wound healing. While exogenous M1 cell infusion delayed wound healing, the M2 cells promoted wound healing in a rat model.

Dynamics of tumor-associated macrophages in a quantitative systems pharmacology model of immunotherapy in triple-negative breast cancer

Quantitative systems pharmacology (QSP) modeling is an emerging mechanistic computational approach that couples drug pharmacokinetics/pharmacodynamics and the course of disease progression. It has begun to play important roles in drug development for complex diseases such as cancer, including triple-negative breast cancer (TNBC). The combination of the anti-PD-L1 antibody atezolizumab and nab-paclitaxel has shown clinical activity in advanced TNBC with PD-L1-positive tumor-infiltrating immune cells. As tumor-associated macrophages (TAMs) serve as major contributors to the immuno-suppressive tumor microenvironment, we incorporated the dynamics of TAMs into our previously published QSP model to investigate their impact on cancer treatment. We show that through proper calibration, the model captures the macrophage heterogeneity in the tumor microenvironment while maintaining its predictive power of the trial results at the population level. Despite its high mechanistic complexity, the modularized QSP platform can be readily reproduced, expanded for new species of interest, and applied in clinical trial simulation.

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A mechanistic model of quantitative systems pharmacology in immuno-oncology

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Dynamics of tumor-associated macrophages are integrated into our previous work

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Conducting in silico clinical trials to predict clinical response to cancer therapy