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The naphthalene diimide compound QN-302, designed to bind to G-quadruplex DNA sequences within the promoter regions of cancer-related genes, has high anti-proliferative activity in pancreatic cancer cell lines and anti-tumor activity in several experimental models for the disease. We show here that QN-302 also causes downregulation of the expression of the S100P gene and the S100P protein in cells and in vivo. This protein is well established as being involved in key proliferation and motility pathways in several human cancers and has been identified as a potential biomarker in pancreatic cancer. The S100P gene contains 60 putative quadruplex-forming sequences, one of which is in the promoter region, 48 nucleotides upstream from the transcription start site. We report biophysical and molecular modeling studies showing that this sequence forms a highly stable G-quadruplex in vitro, which is further stabilized by QN-302. We also report transcriptome analyses showing that S100P expression is highly upregulated in tissues from human pancreatic cancer tumors, compared to normal pancreas material. The extent of upregulation is dependent on the degree of differentiation of tumor cells, with the most poorly differentiated, from more advanced disease, having the highest level of S100P expression. The experimental drug QN-302 is currently in pre-IND development (as of Q1 2023), and its ability to downregulate S100P protein expression supports a role for this protein as a marker of therapeutic response in pancreatic cancer. These results are also consistent with the hypothesis that the S100P promoter G-quadruplex is a potential therapeutic target in pancreatic cancer at the transcriptional level for QN-302.

S100 proteins are multifunctional calcium-binding proteins of vertebrates that act intracellularly, extracellularly, or both, and are engaged in the progression of many socially significant diseases. Their extracellular action is typically mediated by the recognition of specific receptor proteins. Recent studies indicate the ability of some S100 proteins to affect cytokine signaling through direct interaction with cytokines. S100P was shown to be the S100 protein most actively involved in interactions with some four-helical cytokines. To assess the selectivity of the S100P protein binding to four-helical cytokines, we have probed the interaction of Ca2+-bound recombinant human S100P with a panel of 32 four-helical human cytokines covering all structural families of this fold, using surface plasmon resonance spectroscopy. A total of 22 cytokines from all families of four-helical cytokines are S100P binders with the equilibrium dissociation constants, Kd, ranging from 1 nM to 3 µM (below the Kd value for the S100P complex with the V domain of its conventional receptor, receptor for advanced glycation end products, RAGE). Molecular docking and mutagenesis studies revealed the presence in the S100P molecule of a cytokine-binding site, which overlaps with the RAGE-binding site. Since S100 binding to four-helical cytokines inhibits their signaling in some cases, the revealed ability of the S100P protein to interact with ca. 71% of the four-helical cytokines indicates that S100P may serve as a poorly selective inhibitor of their action.

Megakaryocytes (MKs) differentiate from hematopoietic stem cells and produce platelets at the final stage of differentiation. MKs directly interact with bone cells during bone remodeling. However, whether MKs are involved in regulating bone metabolism through indirect regulatory effects on bone cells is unclear. Here, we observed increased osteoclast differentiation of bone marrow-derived macrophages (BMMs) cultured in MK-cultured conditioned medium (MK CM), suggesting that this medium contains factors secreted from MKs that affect osteoclastogenesis. To identify the MK-secreted factor, DNA microarray analysis of the human leukemia cell line K562 and MKs was performed, and S100 calcium-binding protein P (S100P) was selected as a candidate gene affecting osteoclast differentiation. S100P was more highly expressed in MKs than in K562 cells, and showed higher levels in MK CM than in K562-cultured conditioned medium. In BMMs cultured in the presence of recombinant human S100P protein, osteoclast differentiation was promoted and marker gene expression was increased. The resorption area was significantly larger in S100P protein-treated osteoclasts, demonstrating enhanced resorption activity. Overall, S100P secreted from MKs promotes osteoclast differentiation and resorption activity, suggesting that MKs indirectly regulate osteoclast differentiation and activity through the paracrine action of S100P.

Background In allergic asthma, a detrimental cycle of epithelial barrier destruction, driven predominantly by type 2 inflammation, facilitates allergen exposure to deeper tissues. However, the precise mechanisms underlying this process remain poorly understood. Methods A bioinformatics analysis was performed using public datasets and an independent cohort of asthma patients. Single-cell profiling further elucidated the role of S100 calcium-binding protein P (S100P) in this condition. To investigate the impact of S100P on barrier integrity, human bronchial epithelial cells (16HBE) were stimulated with interleukin-13 (IL-13). The functional interaction between S100P and potential therapeutic compounds was evaluated by molecular docking and dynamics simulation. Results Our findings revealed significant alterations in the transcriptional regulation of the S100P, with protein levels correlating closely with lung function and eosinophilic inflammation. S100P was predominantly localized in airway epithelial cells (AECs), particularly in the goblet and club cells. It acts as a pivotal signal in maintaining epithelial barrier integrity by regulating tight junction proteins, such as ZO-1 and occludin, and altering transepithelial electrical resistance. Mechanistically, IL-13 markedly upregulated S100P expression in AECs, likely via activation of transcription factor 4 (ATF4). Molecular docking and dynamics simulations demonstrated that S100P interacts with the clinically established antihistamine astemizole and the immunosuppressant celastrol, both of which protect against S100P-induced barrier disruption. Conclusions Our work identified S100P as a key mediator of airway epithelial barrier dysfunction in asthma, shedding light on the crucial signaling of the IL-13/ATF4/S100P axis. These findings highlight the dual potential of S100P as both a biomarker and a therapeutic target, offering promising strategies for barrier protection in clinical asthma management.

Sepsis, characterized as a severe systemic inflammatory response syndrome, typically originates from an exaggerated immune response to infection that gives rise to organ dysfunction. Serving as one of the predominant causes of death among critically ill patients, it’s pressing to acquire an in-depth understanding of its intricate pathological mechanisms to strengthen diagnostic and therapeutic strategies. By integrating genomic, transcriptomic, proteomic, and metabolomic data across multiple biological levels, multi-omics research analysis has emerged as a crucial tool for unveiling the complex interactions within biological systems and unraveling disease mechanisms in recent years. Samples were collected from 23 cases of sepsis patients and 10 healthy volunteers from January 2019 to December 2020. The protein components in the samples were explored by independent data acquisition (DIA) analysis method, while Circular RNA (circRNA) categories were usually identified by RNA sequencing (RNA-seq) technology. Subsequent to the above steps, data quality monitoring was performed by employing software, and unqualified sequences were excluded, and conditions were set for differential expression network analysis (protein group and circRNA group were separately used log 2 |FC|≥ 1 and log 2 |FC|≥ 2, P < 0.050). Gene Ontology (GO) enrichment analysis and gene set enrichment analysis (GSEA) analysis were performed on common differentially expressed proteins, followed by protein–protein interaction between common differentially expressed genes and cytoscape software enrichment analysis, and subsequently its association with associated diseases (Disease Ontology (DO)) was investigated in an all-round manner. Afterwards, the distribution distinction of common differentially expressed genes in sepsis group and healthy volunteer group was displayed by heat map after Meta-analysis. Subsequent to the above procedures, pivotal targets with noticeable survival curve distinctions in two states were screened out after Meta-analysis. At last, their potential value was verified by in vitro cell experiment, which provided reference for further discussion of the diagnostic value and prognostic effect of target gene. A total of 174 DEPs and 308 DEcircRNAs were identified in the proteomics analysis, while a total of 12 common differentially expressed genes were identified after joint analysis. The protein–protein interaction (PPI) network suggested the degree of interaction between the dissimilar genes, and the heat map demonstrated their specific distribution in distinct groups. Through enrichment analysis, these proteins predominantly participated in a sequence of crucial processes such as intracellular material synthesis and secretion, changes in inflammatory receptors and immune inflammatory response. The meta-analysis identified that S100P is highly expressed in sepsis. As illustrated by the ROC curve, this gene has high clinical diagnostic value, and utimately confirmed its expression in sepsis through in vitro cell experiments. In these two groups of healthy people and septic patients, S100P demonstrated a more obvious trend of differential expression; Cell experiments also proved its value in diagnosis and prognosis judgment in sepsis; As a result, they may become diagnostic and prognostic markers for sepsis in clinical practice.

Background Immunosuppression is a significant factor contributing to the poor prognosis of cancer. S100P , a member of the S100 protein family, has been implicated in various cancers. However, its role in the tumor microenvironment (TME) of pancreatic cancer remains unclear. This study aimed to investigate the potential impact of S100P on TME characteristics in patients with pancreatic cancer. Methods Multiple data (including microarray, RNA-Seq, and scRNA-Seq) were obtained from public databases. The expression pattern of S100P was comprehensively evaluated in RNA-Seq data and validated in four different microarray datasets. Prognostic value was assessed through Kaplan-Meier plotter and Cox regression analyses. Immune infiltration levels were determined using the ESTIMATE and ssGSEA algorithms and validated at the single-cell level. Spearman correlation test was used to examine the correlation between S100P expression and immune checkpoint genes, and tumor mutation burden (TMB). DNA methylation analysis was performed to investigate the change in mRNA expression. Reverse transcription PCR (RT-PCR) and immunohistochemical (IHC) were utilized to validate the expression using five cell lines and 60 pancreatic cancer tissues. Results This study found that S100P was differentially expressed in pancreatic cancer and was associated with poor prognosis ( P  < 0.05). Notably, S100P exhibited a significant negative-correlation with immune cell infiltration, particularly CD8 + T cells. Furthermore, a close association between S100P and immunotherapy was observed, as it strongly correlated with TMB and the expression levels of TIGIT , HAVCR2 , CTLA4 , and BTLA ( P  < 0.05). Intriguingly, higher S100P expression demonstrated a negative correlation with methylation levels (cg14323984, cg27027375, cg14900031, cg14140379, cg25083732, cg07210669, cg26233331, and cg22266967), which were associated with CD8 + T cells. In vitro RT-PCR validated upregulated S100P expression across all five pancreatic cancer cell lines, and IHC confirmed high S100P levels in pancreatic cancer tissues ( P  < 0.05). Conclusion These findings suggest that S100P could serve as a promising biomarker for immunosuppressive microenvironment, which may provide a novel therapeutic way for pancreatic cancer.

Background The gonadotropin-releasing hormone (GnRH) antagonist protocol for in vitro fertilization (IVF) often leads to lower pregnancy rates compared to the GnRH agonist protocol. Decreased endometrial receptivity is one reason for the lower success rate, but the mechanisms underlying this phenomenon remain poorly understood. The S100 calcium protein P (S100P) is a biomarker for endometrial receptivity. Both GnRH antagonist and S100P are involved in mediating cell apoptosis. However, the involvement of S100P in reduced endometrial receptivity during the GnRH antagonist protocol remains unclear. Methods Endometrial tissue was collected at the time of implantation window from patients undergoing the GnRH agonist (GnRH-a) or GnRH antagonist (GnRH-ant) protocols, as well as from patients on their natural cycles. Endometrial cell apoptosis and expression levels of S100P, HOXA10, Bax, and Bcl-2 were assessed. Ishikawa cells were cultured to evaluate the effects that GnRH antagonist exposure or S100P up- or down- regulation had on apoptosis. Results Endometrial tissue from patients in the GnRH-ant group showed elevated apoptosis and decreased expression of the anti-apoptotic marker Bcl-2. In addition, endometrial expression of S100P was significantly reduced in the GnRH-ant group, and expression of HOXA10 was lower. Immunofluorescence colocalization analysis revealed that S100P was mainly distributed in the epithelium. In vitro experiments showed that knockdown of S100P in Ishikawa cells induced apoptosis, decreased expression of Bcl-2, while overexpression of S100P caused the opposite effects and decreased expression of Bax. Furthermore, endometrial epithelial cells exposed to GnRH antagonist expressed lower levels of S100P and Bcl-2, increased expression of Bax, and had higher rates of apoptosis. The increased apoptosis induced by GnRH antagonist treatment could be rescued by overexpression of S100P. Conclusions We found that GnRH antagonist treatment induced endometrial epithelial cell apoptosis by down-regulating S100P, which was detrimental to endometrial receptivity. These results further define a mechanistic role for S100P in contributing to endometrial apoptosis during GnRH antagonist treatment, and suggest that S100P is a potential clinical target to improve the success of IVF using the GnRH antagonist protocol.

The focus of this work is toward the development of a point-of-care (POC) handheld technology for the noninvasive early detection of salivary biomarkers. The initial of focus was the detection and quantification of S100 calcium-binding protein P (S100P) mRNA found in whole saliva for use as a potential biomarker for oral cancer. Specifically, a surface-enhanced Raman spectroscopy (SERS)-based approach and assay were designed, developed, and tested for sensitive and rapid detection of S100P mRNA. Gold nanoparticles (AuNPs) were conjugated with oligonucleotides and malachite green isothiocyanate was then used as a Raman reporter molecule. The hybridization of S100P target to DNA-conjugated AuNPs in sandwich assay format in both free solution and a vertical flow chip (VFC) was confirmed using a handheld SERS system. The detection limit of the SERS-based assay in free solution was determined to be 1.1 nM, whereas on the VFC the detection limit was observed to be 10 nM. SERS-based VFCs were also used to quantify the S100P mRNA from saliva samples of oral cancer patients and a healthy group. The result indicated that the amount of S100P mRNA detected for the oral cancer patients is three times higher than that of a healthy group.

This article examines the multifaceted roles of the S100P gene in pan-cancer, with the aim of exploring its biological functions and related mechanisms in depth. S100P is a small calcium-binding protein that recent studies have identified as playing a significant role in the occurrence and progression of various cancers. As research on cancer biomarkers advances, the relationship between S100P expression levels and cancer prognosis, metastasis and invasiveness has garnered increasing attention. However, the specific mechanisms underlying the role of S100P in different cancer types remain elusive and related research is still in the exploratory phase. Therefore, this review systematically summarizes the biological functions of S100P, clarifying its signaling pathways and regulatory mechanisms. This work provides new insights and strategies for targeted therapy and establishes a theoretical basis for subsequent clinical applications. Through this summary, the present review aims to enhance personalized treatment approaches for S100P-related cancers and strengthen future explorations of S100P.

Breast cancer is still the most significant contributor to morbidity and mortality among women in China. Despite advances in imaging and molecular testing, few reliable biomarkers exist for early detection and disease characterization. The identification of new marker genes related to breast carcinogenesis could greatly improve diagnostic accuracy, and potentially influence treatment decisions. In this study, machine learning algorithms were implemented using the R programming environment to evaluate three publicly available breast cancer datasets included in the Gene Expression Omnibus (GEO) database. We screened differentially expressed genes and then selected the best feature genes using a machine learning cased feature selection model. Finally, we experimentally validated these genes by performing quantitative polymerase chain reaction (qPCR), Western blots, and immunohistochemistry (IHC). By intersecting the top 10 signature genes from each dataset, we were able to identify two consistently diagnostic gene candidates; S100P and COL10A1. Both genes were discovered to exhibit significantly greater expression in the tissues of breast cancer vs. normal controls, across all experimental validation. Our results suggest that S100P and COL10A1 may be appropriate as adjunct molecular biomarkers for improved early and accurate breast cancer diagnosis and could be especially helpful in cases with indeterminate morphological features to improve detection rates and decrease cancer related.