Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming and epithelial-mesenchymal transition (EMT) were investigated with explorative shotgun proteomics complemented by a Random Forest (RF) machine-learning approach. Deep and superficial tumor regions and distant-site non-tumor samples from the same patients (n = 16) were analyzed. Among the 2009 proteins analyzed, 91 proteins, including 23 novel potential CRC hallmarks, showed significant quantitative changes. In addition, a 98.4% accurate classification of the three analyzed tissues was obtained by RF using a set of 21 proteins. Subunit E1 of 2-oxoglutarate dehydrogenase (OGDH-E1) was the best classifying factor for the superficial tumor region, while sorting nexin-18 and coatomer-beta protein (beta-COP), implicated in protein trafficking, classified the deep region. Down- and up-regulations of metabolic checkpoints involved different proteins in superficial and deep tumors. Analogously to immune checkpoints affecting the TME, cytoskeleton and extracellular matrix (ECM) dynamics were crucial for EMT. Galectin-3, basigin, S100A9, and fibronectin involved in TME-CRC-ECM crosstalk were found to be differently variated in both tumor regions. Different metabolic strategies appeared to be adopted by the two CRC regions to uncouple the Krebs cycle and cytosolic glucose metabolism, promote lipogenesis, promote amino acid synthesis, down-regulate bioenergetics in mitochondria, and up-regulate oxidative stress. Finally, correlations with the Dukes stage and budding supported the finding of novel potential CRC hallmarks and therapeutic targets.

The calcium-binding protein S100A9 has emerged as a pivotal biomolecular actor in oncology, implicated in numerous malignancies. This comprehensive bioinformatics study transcends traditional boundaries, investigating the prognostic and therapeutic potential of S100A9 across diverse neoplastic entities. Leveraging a wide array of bioinformatics tools and publicly available cancer genomics databases, such as TCGA, we systematically examined the S100A9 gene. Our approach included differential expression analysis, mutational burden assessment, protein interaction networks, and survival analysis. This robust computational framework provided a high-resolution view of S100A9\'s role in cancer biology. The study meticulously explored S100A9\'s oncogenic facets, incorporating comprehensive analyses of its relationship with prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration across various tumor types. This study presents a panoramic view of S100A9 expression across a spectrum of human cancers, revealing a heterogeneous expression landscape. Elevated S100A9 expression was detected in malignancies such as BLCA (Bladder Urothelial Carcinoma), CESC (Cervical squamous cell carcinoma and endocervical adenocarcinoma), COAD (Colon adenocarcinoma), ESCA (Esophageal carcinoma), and GBM (Glioblastoma multiforme), while reduced expression was noted in BRCA (Breast invasive carcinoma), HNSC (Head and Neck squamous cell carcinoma), and KICH (Kidney Chromophobe). This disparate expression pattern suggests that S100A9\'s role in cancer biology is multifaceted and context-dependent. Prognostically, S100A9 expression correlates variably with patient outcomes across different cancer types. Furthermore, its expression is intricately associated with TMB and MSI in nine cancer types. Detailed examination of six selected tumors-BRCA, CESC, KIRC (Kidney renal clear cell carcinoma), LUSC (Lung squamous cell carcinoma), SKCM (Skin Cutaneous Melanoma); STAD (Stomach adenocarcinoma)-revealed a negative correlation of S100A9 expression with the infiltration of most immune cells, but a positive correlation with neutrophils, M1 macrophages, and activated NK cells, highlighting the complex interplay between S100A9 and the tumor immune environment. This bioinformatics synthesis posits S100A9 as a significant player in cancer progression, offering valuable prognostic insights. The data underscore the utility of S100A9 as a prognostic biomarker and its potential as a therapeutic target. The therapeutic implications are profound, suggesting that modulation of S100A9 activity could significantly impact cancer management strategies.

This research focused on how upregulation of S100A9 contributed to the pathogenesis of the dry eye disease (DED) and whether S100A9 served as a promising therapeutic target in DED. Public single-cell RNA sequencing (scRNA-seq) data of a lacrimal gland excision (LGE) murine DED model was analyzed. LGE model was established and expression of protein was measured through immunofluorescence and Western blot. DED-related signs were evaluated through tear secretion and fluorescent staining. TUNEL was performed to detect the level of cell death. Briefly, S100A9 was recognized as a highly variable gene in the DED group. LGE model was successfully established, and S100A9 showed a time-dependent increase in the corneal epithelia. Autophagic blockage was predicted by the scRNA-seq data in DED, and further verified by decrease of LC3B-II/LC3B-I and increase of SQSTM1 and p-mTOR/mTOR, while S100A9 inhibitor paquinimod (PAQ) reversed the changes. PAQ also downregulated TLR4, and inhibition of TLR4 also alleviated autophagic blockage in DED. Finally, signs of DED, chronic corneal inflammation and cell death got a remission after either inhibition of S100A9 or TLR4. In general, we deduced a S100A9-TLR4-Autophagic blockage pathway in the pathogenesis of DED.

Juvenile myelomonocytic leukemia (JMML), a clonal hematologic malignancy, originates from mutated hematopoietic stem cells (HSCs). The mechanism sustaining the persistence of mutant stem cells, leading to leukemia development, remains elusive. In this study, we conducted comprehensive examination of gene expression profiles, transcriptional factor regulons, and cell compositions/interactions throughout various stages of tumor cell development in Ptpn11 mutation-associated JMML. Our analyses revealed that leukemia-initiating Ptpn11 E76K/+ mutant stem cells exhibited de novo activation of the myeloid transcriptional program and aberrant developmental trajectories. These mutant stem cells displayed significantly elevated expression of innate immunity-associated anti-microbial peptides and pro-inflammatory proteins, particularly S100a9 and S100a8. Biological experiments confirmed that S100a9/S100a8 conferred a selective advantage to the leukemia-initiating cells through autocrine effects and facilitated immune evasion by recruiting and promoting immune suppressive myeloid-derived suppressor cells (MDSCs) in the microenvironment. Importantly, pharmacological inhibition of S100a9/S100a8 signaling effectively impeded leukemia development from Ptpn11 E76K/+ mutant stem cells. These findings collectively suggest that JMML tumor-initiating cells exploit evolutionarily conserved innate immune and inflammatory mechanisms to establish clonal dominance.

In the past decades, the therapeutic effect of glioblastoma (GBM) has not been significantly improved. Generous evidence indicates that S100A9 has a wide range of functions in tumors, but its exploration in GBM is less. The purpose of this study is to conduct a comprehensive bioinformatics analysis and cytological experiment on S100A9 in GBM. The expression data and clinical data of GBM samples were downloaded from the public database, and comprehensive bioinformatics analysis was performed on S100A9 in GBM using R software. Wound healing assay and transwell assay were used to detect the migration activity of cells, and colony formation assay, EdU staining, and CCK-8 assay were used to detect the proliferation activity of cells. The effect of S100A9 on the migration activity of M2 macrophages was verified by the cell co-culture method. The protein expression was detected by western blotting and immunohistochemical staining. S100A9 is an independent prognostic factor in GBM patients and is related to poor prognosis. It can be used as an effective tool to predict the response of GBM patients to immune checkpoint inhibitors (ICIs). In addition, S100A9 can promote the malignant progression of GBM and the migration of M2 macrophages. On the whole, our study highlights the potential value of S100A9 in predicting prognosis and immunotherapeutic response in GBM patients. More importantly, S100A9 may promote the malignant progress of GBM by involving in some carcinogenic pathways and remodeling the tumor microenvironment (TME).

Glioblastoma (GBM) is a highly heterogeneous disease with poor clinical outcomes. To comprehensively dissect the molecular landscape of GBM and heterogeneous macrophage clusters in the progression of GBM, this study integrates single-cell and bulk transcriptome data to recognize a distinct pro-tumor macrophage cluster significantly associated with the prognosis of GBM and develop a GBM prognostic signature to facilitate prior subtypes. Leveraging glioma single-cell sequencing data, we identified a novel pro-tumor macrophage subgroup, marked by S100A9, which might interact with endothelial cells to facilitate tumor progression via angiogenesis. To further benefit clinical application, a prognostic signature was established with the genes associated with pro-tumor macrophages. Patients classified within the high-risk group characterized with enrichment in functions related to tumor progression, including epithelial-mesenchymal transition and hypoxia, displays elevated mutations in the TERT promoter region, reduced methylation in the MGMT promoter region, poorer prognoses, and diminished responses to temozolomide therapy, thus effectively discriminating between the prognostic outcomes of GBM patients. Our research sheds light on the intricate microenvironment of gliomas and identifies potential molecular targets for the development of novel therapeutic approaches.

BACKGROUND: The pathogenesis of biliary atresia (BA) remains elusive. We aimed to investigate the role of long noncoding RNA (lncRNA) MEG9 in BA.
METHODS: LncRNA microarray was conducted to identify differentially expressed lncRNAs in three BA and three para-hepatoblastoma liver tissues. RT-qPCR validated the results. Human intrahepatic bile duct epithelial cells (HIBECs) were stably transfected with lncRNA MEG9 knockdown/overexpression to investigate its cellular localization and function. RNA sequencing (RNA-seq), differentially expressed genes (DEGs) analysis and gene set enrichment analysis were applied to MEG9-overexpresed HIBECs. RNA pull-down and mass spectrometry explored the interacting protein of MEG9, while clinical information was reviewed.
RESULTS: 436 differentially expressed lncRNAs were identified, with MEG9 highly upregulated in BA. RT-qPCR further confirmed MEG9\'s overexpression in BA and diagnostic potential (AUC = 0.9691). MEG9 was predominantly located in the nucleus and significantly promoted cell proliferation and migration. RNA-seq revealed inflammation- and extracellular matrix-related pathways enriched in MEG9-overexpressing HIBECs, with upregulated cytokine genes like CXCL6 and IL6. MMP-7 and collagen I were also overexpressed. Furthermore, 38 proteins were identified to specifically interact with MEG9, and S100A9 was highly expressed in cell models. S100A9 was also significantly upregulated in BA liver tissue and correlated with MEG9 expression (r = 0.313, p < 0.05), albumin level (r = -0.349, p < 0.05), and platelet level (r = -0.324, p < 0.05).
CONCLUSIONS: MEG9 influences cholangiocyte proliferation, migration, and cytokine production, potentially regulating BA inflammation and fibrosis via S100A9 interaction.

BACKGROUND: Microglia and infiltrated macrophages (M/M) are integral components of the innate immune system that play a critical role in facilitating brain repair after ischemic stroke (IS) by clearing cell debris. Novel therapeutic strategies for IS therapy involve modulating M/M phenotype shifting. This study aims to elucidate the pivotal role of S100A9 in M/M and its downstream STAT6/PPARγ signaling pathway in neuroinflammation and phagocytosis after IS.
METHODS: In the clinical study, we initially detected the expression pattern of S100A9 in monocytes from patients with acute IS and investigated its association with the long-term prognosis. In the in vivo study, we generated the S100A9 conditional knockout (CKO) mice and compared the stroke outcomes with the control group. We further tested the S100A9-specific inhibitor paqunimod (PQD), for its pharmaceutical effects on stroke outcomes. Transcriptomics and in vitro studies were adopted to explore the mechanism of S100A9 in modulating the M/M phenotype, which involves the regulation of the STAT6/PPARγ signaling pathway.
RESULTS: S100A9 was predominantly expressed in classical monocytes and was correlated with unfavorable outcomes in patients of IS. S100A9 CKO mitigated infarction volume and white matter injury, enhanced cerebral blood flow and functional recovery, and prompted anti-inflammation phenotype and efferocytosis after tMCAO. The STAT6/PPARγ pathway, an essential signaling cascade involved in immune response and inflammation, might be the downstream target mediated by S100A9 deletion, as evidenced by the STAT6 phosphorylation inhibitor AS1517499 abolishing the beneficial effect of S100A9 inhibition in tMCAO mice and cell lines. Moreover, S100A9 inhibition by PQD treatment protected against neuronal death in vitro and brain injuries in vivo.
CONCLUSIONS: This study provides evidence for the first time that S100A9 in classical monocytes could potentially be a biomarker for predicting IS prognosis and reveals a novel therapeutic strategy for IS. By demonstrating that S100A9-mediated M/M polarization and phagocytosis can be reversed by S100A9 inhibition in a STAT6/PPARγ pathway-dependent manner, this study opens up new avenues for drug development in the field.

Inflammatory bowel disease (IBD), including Crohn\'s disease (CD) and ulcerative colitis (UC), is associated with a loss or an imbalance of host-microorganism interactions. However, such interactions at protein levels remain largely unknown. Here, we applied a depletion-assisted metaproteomics approach to obtain in-depth host-microbiome association networks of IBD, where the core host proteins shifted from those maintaining mucosal homeostasis in controls to those involved in inflammation, proteolysis, and intestinal barrier in IBD. Microbial nodes such as short-chain fatty-acid producer-related host-microbial crosstalk were lost or suppressed by inflammatory proteins in IBD. Guided by protein-protein association networks, we employed proteomics and lipidomics to investigate the effects of UC-related core proteins S100A8, S100A9, and cytokines (IL-1β, IL-6, and TNF-α) on gut bacteria. These proteins suppressed purine nucleotide biosynthesis in stool-derived in vitro communities, which was also reduced in IBD stool samples. Single species study revealed that S100A8, S100A9, and cytokines can synergistically or antagonistically alter gut bacteria intracellular and secreted proteome, with combined S100A8 and S100A9 potently inhibiting beneficial Bifidobacterium adolescentis. Furthermore, these inflammatory proteins only altered the extracellular but not intracellular proteins of Ruminococcus gnavus. Generally, S100A8 induced more significant bacterial proteome changes than S100A9, IL-1β, IL-6, and TNF-α but gut bacteria degrade significantly more S100A8 than S100A9 in the presence of both proteins. Among the investigated species, distinct lipid alterations were only observed in Bacteroides vulgatus treated with combined S100A8, S100A9, and cytokines. These results provided a valuable resource of inflammatory protein-centric host-microbial molecular interactions.

Alzheimer\'s disease (AD) leads to progressive neurodegeneration and dementia. AD primarily affects older adults with neuropathological changes including amyloid-beta (Aβ) deposition, neuroinflammation, and neurodegeneration. We have previously demonstrated that systemic treatment with combined stem cell factor (SCF) and granulocyte colony-stimulating factor (G-CSF) (SCF+G-CSF) reduces the Aβ load, increases Aβ uptake by activated microglia and macrophages, reduces neuroinflammation, and restores dendrites and synapses in the brains of aged APPswe/PS1dE9 (APP/PS1) mice. However, the mechanisms underlying SCF+G-CSF-enhanced brain repair in aged APP/PS1 mice remain unclear. This study used a transcriptomic approach to identify the potential mechanisms by which SCF+G-CSF treatment modulates microglia and peripheral myeloid cells to mitigate AD pathology in the aged brain. After injections of SCF+G-CSF for 5 consecutive days, single-cell RNA sequencing was performed on CD11b+ cells isolated from the brains of 28-month-old APP/PS1 mice. The vast majority of cell clusters aligned with transcriptional profiles of microglia in various activation states. However, SCF+G-CSF treatment dramatically increased a cell population showing upregulation of marker genes related to peripheral myeloid cells. Flow cytometry data also revealed an SCF+G-CSF-induced increase of cerebral CD45high/CD11b+ active phagocytes. SCF+G-CSF treatment robustly increased the transcription of genes implicated in immune cell activation, including gene sets that regulate inflammatory processes and cell migration. The expression of S100a8 and S100a9 was robustly enhanced following SCF+G-CSF treatment in all CD11b+ cell clusters. Moreover, the topmost genes differentially expressed with SCF+G-CSF treatment were largely upregulated in S100a8/9-positive cells, suggesting a well-conserved transcriptional profile related to SCF+G-CSF treatment in resident and peripherally derived CD11b+ immune cells. This S100a8/9-associated transcriptional profile contained notable genes related to pro-inflammatory and anti-inflammatory responses, neuroprotection, and Aβ plaque inhibition or clearance. Altogether, this study reveals the immunomodulatory effects of SCF+G-CSF treatment in the aged brain with AD pathology, which will guide future studies to further uncover the therapeutic mechanisms.