Machine learning identifies signatures of macrophage reactivity and tolerance that predict disease outcomes

Linking signal input, cell state, and spatial context to inflammatory responses

Signal integration is central to a causal understanding of appropriately scaled inflammatory responses. Here, we discuss recent progress in our understanding of the stimulus-response linkages downstream of pro-inflammatory inputs, with special attention to (1) the impact of cell state on the specificity of evoked gene expression and (2) the critical role of the spatial context of stimulus exposure. Advances in these directions are emerging from new tools for inferring cell-cell interactions and the activities of cytokines and transcription factors in complex microenvironments, enabling analysis of signal integration in tissue settings. Building on data-driven elucidation of factors driving inflammatory outcomes, mechanistic modeling can then contribute to a quantitative understanding of regulatory events that balance protective versus pathological inflammation.

FORWARD: A Learning Framework for Logical Network Perturbations to Prioritize Targets for Drug Development

Despite advances in artificial intelligence (AI), target-based drug development remains a costly, complex and imprecise process. We introduce F.O.R.W.A.R.D [ Framework for Outcome-based Research and Drug Development ], a network-based target prioritization approach and test its utility in the challenging therapeutic area of Inflammatory Bowel Diseases (IBD), which is a chronic condition of multifactorial origin. F.O.R.W.A.R.D leverages real-world outcomes, using a machine-learning classifier trained on transcriptomic data from seven prospective randomized clinical trials involving four drugs. It establishes a molecular signature of remission as the therapeutic goal and computes, by integrating principles of network connectivity, the likelihood that a drug's action on its target(s) will induce the remission-associated genes. Benchmarking F.O.R.W.A.R.D against 210 completed clinical trials on 52 targets showed a perfect predictive accuracy of 100%. The success of F.O.R.W.A.R.D was achieved despite differences in targets, mechanisms, and trial designs. F.O.R.W.A.R.D-driven in-silico phase '0' trials revealed its potential to inform trial design, justify re-trialing failed drugs, and guide early terminations. With its extendable applications to other therapeutic areas and its iterative refinement with emerging trials, F.O.R.W.A.R.D holds the promise to transform drug discovery by generating foresight from hindsight and impacting research and development as well as human-in-the-loop clinical decision-making.

Liver macrophages revisited: The expanding universe of versatile responses in a spatiotemporal context

The liver is a vital organ that continuously adapts to a wide and dynamic diversity of self-antigens and xenobiotics. This involves the active contribution of immune cells, particularly by the liver-resident macrophages, the Kupffer cells (KCs), which exert a variety of central functions in liver homeostasis and disease. As such, KCs interact with their microenvironment to shape the hepatic cellular landscape, control gut-derived signal integration, and modulate metabolism. On injury, the rapid recruitment of bone marrow monocyte-derived macrophages alters this status quo and, when unrestrained, drastically compromises liver homeostasis, immune surveillance, and tissue organization. Several factors determine the functional roles of liver macrophages in these processes, such as their ontogeny, activation/polarization profile and, importantly, spatial distribution within the liver. Loss of tolerance and adaptability of the hepatic immune environment may result in persistent inflammation, hepatic fibrosis, cirrhosis, and a tumorigenic niche promoting liver cancer. In this review, we aim at providing the most recent breakthroughs in our understanding of liver macrophage biology, particularly their diversity and adaptability in the hepatic spatiotemporal context, as well as on potential therapeutic interventions that may hold the key to tackling remaining clinical challenges of varying etiologies in hepatology.

Immunoregulatory role of platelet derivatives in the macrophage-mediated immune response

Background

Macrophages are innate immune cells that display remarkable phenotypic heterogeneity and functional plasticity. Due to their involvement in the pathogenesis of several human conditions, macrophages are considered to be an attractive therapeutic target. In line with this, platelet derivatives have been successfully applied in many medical fields and as active participants in innate immunity, cooperation between platelets and macrophages is essential. In this context, the aim of this review is to compile the current evidence regarding the effects of platelet derivatives on the phenotype and functions of macrophages to identify the advantages and shortcomings for feasible future clinical applications.

Methods

A total of 669 articles were identified during the systematic literature search performed in PubMed and Web of Science databases.

Results

A total of 27 articles met the inclusion criteria. Based on published findings, platelet derivatives may play an important role in inducing a dynamic M1/M2 balance and promoting a timely M1-M2 shift. However, the differences in procedures regarding platelet derivatives and macrophages polarization and the occasional lack of information, makes reproducibility and comparison of results extremely challenging. Furthermore, understanding the differences between human macrophages and those derived from animal models, and taking into account the peculiarities of tissue resident macrophages and their ontogeny seem essential for the design of new therapeutic strategies.

Conclusion

Research on the combination of macrophages and platelet derivatives provides relevant information on the function and mechanisms of the immune response.

Molecular Signatures for Microbe-Associated Colorectal Cancers

Background

Genetic factors and microbial imbalances play crucial roles in colorectal cancers (CRCs), yet the impact of infections on cancer initiation remains poorly understood. While bioinformatic approaches offer valuable insights, the rising incidence of CRCs creates a pressing need to precisely identify early CRC events. We constructed a network model to identify continuum states during CRC initiation spanning normal colonic tissue to pre-cancer lesions (adenomatous polyps) and examined the influence of microbes and host genetics.

Methods

A Boolean network was built using a publicly available transcriptomic dataset from healthy and adenoma affected patients to identify an invariant Microbe-Associated Colorectal Cancer Signature (MACS). We focused on Fusobacterium nucleatum ( Fn ), a CRC-associated microbe, as a model bacterium. MACS-associated genes and proteins were validated by RT-qPCR, RNA seq, ELISA, IF and IHCs in tissues and colon-derived organoids from genetically predisposed mice ( CPC-APC Min+/- ) and patients (FAP, Lynch Syndrome, PJS, and JPS).

Results

The MACS that is upregulated in adenomas consists of four core genes/proteins: CLDN2/Claudin-2 (leakiness), LGR5/leucine-rich repeat-containing receptor (stemness), CEMIP/cell migration-inducing and hyaluronan-binding protein (epithelial-mesenchymal transition) and IL8/Interleukin-8 (inflammation). MACS was induced upon Fn infection, but not in response to infection with other enteric bacteria or probiotics. MACS induction upon Fn infection was higher in CPC-APC Min+/- organoids compared to WT controls. The degree of MACS expression in the patient-derived organoids (PDOs) generally corresponded with the known lifetime risk of CRCs.

Conclusions

Computational prediction followed by validation in the organoid-based disease model identified the early events in CRC initiation. MACS reveals that the CRC-associated microbes induce a greater risk in the genetically predisposed hosts, suggesting its potential use for risk prediction and targeted cancer prevention.

Costunolide mitigates inflammation and promotes extracellualr matrix integrity of thoracic aortic dissection by inhibiting NF-κB signaling

BACKGROUND

Thoracic aortic dissection (TAD) is one of the most fatal cardiovascular diseases. One of its important pathological characteristics is the local inflammatory response. Many studies have found that Macrophage polarization plays an extremely critical role in the inflammatory progression and tissue remodeling of TAD. Costunolide (CTD) has an improving effect on oxidative stress and inflammation in the body. However, whether it can promote the integrity of extracellular matrix in Aortic dissection and its mechanism are still unclear.

METHODS

The male C57BL/6J mice were used to construct an animal model of TAD with β-aminopropionitrile (BAPN) (100 mg/kg/day, lasting for 28 days), and then CTD (10 mg/kg or 100 mg/kg) was injected intraperitoneally for 28 days to check the survival rate, TAD incidence, aortic morphology and other indicators of the mice. Using hematoxylin-eosin (HE), Masson, Elastin van Gieson (EVG) staining, immunofluorescence (IF), and immunohistochemical staining, the study aimed to determine the therapeutic effects of CTD on an animal model with BAPN-induced TAD. To enhance the examination of the regulatory mechanism of CTD, we conducted transcriptome sequencing on arterial tissues of mice in both the BAPN group and the BAPN + CTD100 group. Next, ANG II were used to construct TAD model in vascular smooth muscle cells (VMSCs). The effects of CTD on the proliferation, migration, invasion, and apoptosis of ANG II-induced cells are to be detected. The expression of MMP2, MMP9, P65, and p-P65 in each group will be examined using Western blot. Finally, the overexpression of IκB kinaseβ (IKKβ) will be established in VMSCs cells to further explore the protective function of CTD.

RESULTS

The result showed that CTD significantly inhibited BAPN induced mortality and TAD incidence in the animal model, improved aortic vascular morphology, promoted the integrity of extracellular matrix in TAD, reduced tissue inflammation, reduced the accumulation of M1 macrophage, promoted M2 macrophage polarization, and reduced the expression of NF-κB pathway related proteins. Mechanistically, CTD significantly weakened the proliferation, migration, invasion, and apoptosis. p-P65 protein expression of TAD cells were induced by ANG II and IKK-β.

CONCLUSION

CTD has the potential to alleviate inflammation, VSMC apoptosis, MMP2/9 levels, and enhance extracellular matrix integrity in TAD by inhibiting the NF-κB signaling pathway.

Measuring cancer driving force of chromosomal aberrations through multi-layer Boolean implication networks

Multi-layer Complex networks are commonly used for modeling and analysing biological entities. This paper presents the advantage of using COMBO (Combining Multi Bio Omics) to suggest a new role of the chromosomal aberration as a cancer driver factor. Exploiting the heterogeneous multi-layer networks, COMBO integrates gene expression and DNA-methylation data in order to identify complex bilateral relationships between transcriptome and epigenome. We evaluated the multi-layer networks generated by COMBO on different TCGA cancer datasets (COAD, BLCA, BRCA, CESC, STAD) focusing on the effect of a specific chromosomal numerical aberration, broad gain in chromosome 20, on different cancer histotypes. In addition, the effect of chromosome 8q amplification was tested in the same TCGA cancer dataset. The results demonstrate the ability of COMBO to identify the chromosome 20 amplification cancer driver force in the different TCGA Pan Cancer project datasets.

The phenotype and related gene expressions of macrophages in adipose tissue of T2D mice following MSCs infusion

BACKGROUND

Infusion of mesenchymal stem cells (MSCs) induces polarization of M2 macrophages in adipose tissue of type 2 diabetes (T2D) mice. Studies have shown that M2 macrophages were divided into four sub-phenotypes (M2a, M2b, M2c and M2d) with different functions, and manuscripts have also confirmed that macrophages co-cultured with MSCs were not matched with known four phenotype macrophages. Therefore, our study explored the phenotype and related gene expressions of macrophages in the adipose tissue of T2D mice with/without MSCs infusion.

METHODS

We induced a T2D mouse model by using high-fat diets and streptozotocin (STZ) injection. The mice were divided into three groups: the control group, the T2D group, and the MSCs group. MSCs were systemically injected once a week for 6 weeks. The phenotype of macrophages in adipose tissue was detected via flow cytometric analysis. We also investigated the gene expression of macrophages in different groups via SMART-RNA-sequencing and quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR).

RESULTS

The present study found that the macrophages of adipose tissue in the MSCs group were polarized to the M2 phenotype mixed with four sub-phenotypes. Besides, M2a and M2c held a dominant position, while M2b and M2d (tumor-associated macrophages, TAMs) exhibited a decreasing trend after infusion of MSCs. Moreover, the MSCs group did not appear to express higher levels of tumor-associated, inflammation-associated, or fibrosis-associated genes in comparison to the T2D group.

CONCLUSION

The present results unveiled that the macrophage phenotype was inclined to be present in a hybridity state of four M2 sub-phenotypes and the genes related to tumor-promoting, pro-inflammation and pro-fibrosis were not increased after MSCs injection.

Macrophage Polarizations in the Placenta and Lung are Associated with Bronchopulmonary Dysplasia

The intricate interplay between macrophage polarization and placenta vascular dysfunction has garnered increasing attention in the context of placental inflammatory diseases. This study delves into the complex relationship between macrophage polarization within the placenta and its potential impact on the development of vascular dysfunction and inflammatory conditions. The placenta, a crucial organ in fetal development, relies on a finely tuned balance of immune responses for proper functioning. Disruptions in this delicate equilibrium can lead to pathological conditions, including inflammatory diseases affecting the fetus and newborn infant. We explored the interconnectedness between placental macrophage polarization and its relevance to lung macrophages, particularly in the context of early life lung development. Bronchopulmonary dysplasia (BPD), the most common chronic lung disease of prematurity, has been associated with abnormal immune responses, and understanding the role of macrophages in this context is pivotal. The investigation aims to shed light on how alterations in placental macrophage polarization may contribute to lung macrophage behavior and, consequently, influence the development of BPD. By unraveling the intricate mechanisms linking macrophage polarization, placental dysfunction and BPD, this research seeks to provide insights that could pave the way for targeted therapeutic interventions. The findings may offer novel perspectives on preventing and managing placental and lung-related pathologies, ultimately contributing to improved maternal and neonatal health outcomes.

C1QA is an invariant biomarker for tissue macrophages

Macrophages play a pivotal role in immune responses, particularly in the context of combating microbial threats within tissues. The identification of reliable biomarkers associated with macrophage function is essential for understanding their diverse roles in host defense. This study investigates the potential of C1QA as an invariant biomarker for tissue macrophages, focusing on its correlation with the anti-microbial pathway. C1QA, a component of the complement system, has been previously implicated in various immune functions. Our research delves into the specific association of C1QA with tissue-resident macrophages and its implications in the context of anti-microbial responses. Through comprehensive systems biology and Boolean analysis of gene expression, we aim to establish C1QA as a consistent and reliable marker for identifying tissue macrophages. Furthermore, we explore the functional significance of C1QA in the anti-microbial pathway. This research seeks to provide valuable insights into the molecular mechanisms underlying the anti-microbial functions of tissue macrophages, with C1QA emerging as a potential key player in this intricate regulatory network. Understanding the relationship between C1QA, tissue macrophages, and the anti-microbial pathway could pave the way for the development of targeted therapeutic strategies aimed at enhancing the host's ability to combat infections. Ultimately, our findings contribute to the expanding knowledge of macrophage biology and may have implications for the diagnosis and treatment of infectious diseases.

One Sentence Summary

C1QA is a fundamental biomarker of tissue macrophages.

Large-scale computational modelling of the M1 and M2 synovial macrophages in rheumatoid arthritis

Macrophages play an essential role in rheumatoid arthritis. Depending on their phenotype (M1 or M2), they can play a role in the initiation or resolution of inflammation. The M1/M2 ratio in rheumatoid arthritis is higher than in healthy controls. Despite this, no treatment targeting specifically macrophages is currently used in clinics. Thus, devising strategies to selectively deplete proinflammatory macrophages and promote anti-inflammatory macrophages could be a promising therapeutic approach. State-of-the-art molecular interaction maps of M1 and M2 macrophages in rheumatoid arthritis are available and represent a dense source of knowledge; however, these maps remain limited by their static nature. Discrete dynamic modelling can be employed to study the emergent behaviours of these systems. Nevertheless, handling such large-scale models is challenging. Due to their massive size, it is computationally demanding to identify biologically relevant states in a cell- and disease-specific context. In this work, we developed an efficient computational framework that converts molecular interaction maps into Boolean models using the CaSQ tool. Next, we used a newly developed version of the BMA tool deployed to a high-performance computing cluster to identify the models' steady states. The identified attractors are then validated using gene expression data sets and prior knowledge. We successfully applied our framework to generate and calibrate the M1 and M2 macrophage Boolean models for rheumatoid arthritis. Using KO simulations, we identified NFkB, JAK1/JAK2, and ERK1/Notch1 as potential targets that could selectively suppress proinflammatory macrophages and GSK3B as a promising target that could promote anti-inflammatory macrophages in rheumatoid arthritis.

Macrophage states: there's a method in the madness

Single-cell approaches have shone a spotlight on discrete context-specific tissue macrophage states, deconstructed to their most minute details. Machine-learning (ML) approaches have recently challenged that dogma by revealing a context-agnostic continuum of states shared across tissues. Both approaches agree that 'brake' and 'accelerator' macrophage subpopulations must be balanced to achieve homeostasis. Both approaches also highlight the importance of ensemble fluidity as subpopulations switch between wide ranges of accelerator and brake phenotypes to mount the most optimal wholistic response to any threat. A full comprehension of the rules that govern these brake and accelerator states is a promising avenue because it can help formulate precise macrophage re-education therapeutic strategies that might selectively boost or suppress disease-associated states and phenotypes across various tissues.

Reframing macrophage diversity with network motifs

A binary classification of macrophage activation as inflammatory or resolving does not capture the diversity of macrophage states observed in tissues. However, framing macrophage activation as a continuous spectrum of states overlooks the intracellular and extracellular networks that regulate and coordinate macrophage responses. Here, we suggest that the systems biology concept of network motifs, which incorporate rules of local molecular interactions, is useful for reframing macrophage activation. Because network motifs can be used to regulate distinct biological functions, they offer a simplified unit that can be compared across organismal, tissue, and disease contexts. Moreover, defining macrophage states as combinations of functional modules regulated by network motifs offers a framework to ultimately predict and target macrophage responses arising in complex environments.

An AI-assisted Investigation of Tumor-Associated Macrophages and their Polarization in Colorectal Cancer

Tumor-associated Macrophages (or TAMs) are amongst the most common cells that play a significant role in the initiation and progression of colorectal cancer (CRC). Recently, Ghosh et al. proposed distinguishing signatures for identifying macrophage polarization states, namely, immuno-reactive and immuno-tolerant, using the concept of Boolean implications and Boolean networks. Their signature, called the Signature of Macrophage Reactivity and Tolerance (SMaRT), comprises of 338 human genes (equivalently, 298 mouse genes). However, SMaRT was constructed using datasets that were not specialized towards any particular disease. In this paper, (a) we perform a comprehensive analysis of the SMaRT signature on single-cell human and mouse colorectal cancer RNA-seq datasets; (b) we then adopt a technique akin to transfer learning to construct a "refined" SMaRT signature for investigating TAMs and their polarization in the CRC tumor microenvironment. Towards validation of our refined gene signature, we use (a) 5 pseudo-bulk RNA-seq datasets derived from single-cell human datasets; and (b) 5 large-cohort microarray datasets from humans. Furthermore, we investigate the translational potential of our refined gene signature in problems related to MSS/MSI (4 datasets) and CIMP+/CIMP- status (4 datasets). Overall, our refined gene signature and its extensive validation provide a path for its adoption in clinical practice in diagnosing colorectal cancer and associated attributes.