Roles of S100 family members in drug resistance in tumors: Status and prospects

spatialGE: A user-friendly web application to democratize spatial transcriptomics analysis

Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.

S100A6 mediated epithelial-mesenchymal transition affects chemosensitivity of colorectal cancer to oxaliplatin

PURPOSE

To investigate the mechanism by which S100 calcium-binding protein A6 (S100A6) affects colorectal cancer (CRC) cells to oxaliplatin (L-OHP) chemotherapy, and to explore new strategies for CRC treatment.

METHODS

S100A6 expression was assessed in both parental and L-OHP-resistant CRC cells using western blotting, quantitative real-time polymerase chain reaction (qRT-PCR), and enzyme-linked immunosorbent assays (ELISA). Lentiviral vectors were utilized to induce the knockdown of S100A6 expression, followed by comprehensive evaluations of cell proliferation, apoptosis, and epithelial-mesenchymal transition (EMT). Additionally, RNA-seq analysis was conducted to identify genes associated with the knockdown of S100A6.

RESULTS

Elevated S100A6 expression in CRC tissues correlated with an adverse prognosis in patients with CRC. Higher expression of S100A6 was also observed in L-OHP-resistant CRC cells, which showed enhanced proliferation, migration, invasion, and antiapoptotic capabilities. Notably, the knockdown of S100A6 expression resulted in decreased proliferation, increased apoptosis, and suppression of EMT and tumorigenicity in L-OHP-resistant CRC cells. Transcriptome sequencing reveals a noteworthy association between S100A6 and vimentin expression. Application of the EMT agonist, transforming growth factor β (TGF-β), induces EMT in CRC cells. S100A6 expression positively correlates with TGF-β expression. TGF-β facilitated the expression of EMT-related molecules and reduced the chemosensitivity of L-OHP in S100A6-knockdown cells.

CONCLUSION

In conclusion, the knockdown of S100A6 may overcome the L-OHP resistance of CRC cells by modulating EMT.

Bidirectional relationship between pancreatic cancer and diabetes mellitus: a comprehensive literature review

Pancreatic cancer (PC) is a fatal malignant disease. It is well known that the relationship between PC and type 2 diabetes mellitus (T2DM) is a complicated bidirectional relationship. The most important factors causing increased risks of pancreatic cancer are hyperglycaemia, hyperinsulinemia, pancreatitis, and dyslipidemia. Genetics and the immune system also play an important role in the relationship between diabetes mellitus and pancreatic cancer. The primary contributors to this association involve insulin resistance and inflammatory processes within the tumour microenvironment. The combination of diabetes and obesity can contribute to PC by inducing hyperinsulinemia and influencing leptin and adiponectin levels. Given the heightened incidence of pancreatic cancer in diabetes patients compared to the general population, early screening for pancreatic cancer is recommended. Diabetes negatively impacts the survival of pancreatic cancer patients. Among patients receiving chemotherapy, it reduced their survival. The implementation of a healthy lifestyle, including weight management, serves as an initial preventive measure to mitigate the risk of disease development. The role of anti-diabetic drugs on survival is controversial; however, metformin may have a positive impact, especially in the early stages of cancer, while insulin therapy increases the risk of PC.

S100A6 could not promote the differentiation of Calu-6 lung cancer cell line

Background

Our previous study demonstrated that S100 calcium binding protein A6 (S100A6) impairs tumorigenesis by Calu-6 lung cancer cells, as well as inhibit their growth. However, the role that S100A6 plays in tumor cell differentiation has not been previously explored. This study aimed to confirm the effect of S100A6 on the direction of differentiation in the human lung cancer cell linem Calu-6m based on our previous published research.

Materials and methods

A S100A6-overexpressing lentiviral vector was successfully constructed in our previous study. Nude mouse tumorigenicity was then applied successfully, and 15 mice were divided into three groups (Calu-6, Calu-6/neo, Calu-6/S100A6). After 5 weeks, we detected lung cancer markers with immunohistochemistry in mice tumor tissues, including the adenocarcinoma markers, TTF-1 and NapsinA, the squamous cell carcinoma markers, P40, CK5/6 and P63, and the small cell lung cancer markers CD56, Syn, CgA, TTF-1, CK, and Ki-67. Differences among the three groups were statistically compared.

Results

All the above-mentioned markers were positive in the tumor tissues of all three groups, and there were no significant differences.

Conclusion

S100A6 cannot promote differentiation of the undifferentiated human lung cancer cell line, Calu-6, into adenocarcinoma, squamous, or small cell carcinoma cell lines.

Recognition of granulocyte-macrophage colony-stimulating factor by specific S100 proteins

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a pleiotropic myelopoietic growth factor and proinflammatory cytokine, clinically used for multiple indications and serving as a promising target for treatment of many disorders, including cancer, multiple sclerosis, rheumatoid arthritis, psoriasis, asthma, COVID-19. We have previously shown that dimeric Ca2+-bound forms of S100A6 and S100P proteins, members of the multifunctional S100 protein family, are specific to GM-CSF. To probe selectivity of these interactions, the affinity of recombinant human GM-CSF to dimeric Ca2+-loaded forms of 18 recombinant human S100 proteins was studied by surface plasmon resonance spectroscopy. Of them, only S100A4 protein specifically binds to GM-CSF with equilibrium dissociation constant, Kd, values of 0.3-2 μM, as confirmed by intrinsic fluorescence and chemical crosslinking data. Calcium removal prevents S100A4 binding to GM-CSF, whereas monomerization of S100A4/A6/P proteins disrupts S100A4/A6 interaction with GM-CSF and induces a slight decrease in S100P affinity for GM-CSF. Structural modelling indicates the presence in the GM-CSF molecule of a conserved S100A4/A6/P-binding site, consisting of the residues from its termini, helices I and III, some of which are involved in the interaction with GM-CSF receptors. The predicted involvement of the 'hinge' region and F89 residue of S100P in GM-CSF recognition was confirmed by mutagenesis. Examination of S100A4/A6/P ability to affect GM-CSF signaling showed that S100A4/A6 inhibit GM-CSF-induced suppression of viability of monocytic THP-1 cells. The ability of the S100 proteins to modulate GM-CSF activity is relevant to progression of various neoplasms and other diseases, according to bioinformatics analysis. The direct regulation of GM-CSF signaling by extracellular forms of the S100 proteins should be taken into account in the clinical use of GM-CSF and development of the therapeutic interventions targeting GM-CSF or its receptors.

A programmed cell death-related gene signature to predict prognosis and therapeutic responses in liver hepatocellular carcinoma

BACKGROUND

Programmed cell death (PCD) functions critically in cancers and PCD-related genes are associated with tumor microenvironment (TME), prognosis and therapeutic responses of cancer patients. This study stratified hepatocellular carcinoma (HCC) patients and develop a prognostic model for predicting prognosis and therapeutic responses.

METHODS

Consensus clustering analysis was performed to subtype HCC patients in The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) among the subtypes were filtered and subjected to the least absolute shrinkage and selection operator (LASSO) regression analysis and univariate Cox regression analysis to filter prognostic genes. A PCD-related prognostic gene signature in TCGA was constructed and validated in ICGC-LIRI-JP and GSE14520 datasets. TME was analyzed using CIBERSORT, MCP-counter, TIMER and EPIC algorithms. Drug sensitivity was predicted by oncoPredict package. Spearman analysis was used to detect correlation.

RESULTS

Four molecular subtypes were categorized based on PCD-related genes. Subtype C1 showed the poorest prognosis, the most infiltration of Fibroblasts, dentritic cell (DC) and cancer-associated fibroblasts (CAFs), and the highest TIDE score. C4 had a better prognosis survival outcome, and lowest immune cell infiltration. The survival outcomes of C2 and C3 were intermediate. Next, a total of 69 co-DEGs were screened among the four subtypes and subsequently we identified five prognostic genes (MCM2, SPP1, S100A9, MSC and EPO) for developing the prognostic model. High-risk patients not only had unfavorable prognosis, higher clinical stage and grade, and more inflammatory pathway enrichment, but also possessed higher possibility of immune escape and were more sensitive to Cisplatin and 5. Fluorouracil. The robustness of the prognostic model was validated in external datasets.

CONCLUSION

This study provides new insights into clinical subtyping and the PCD-related prognostic signature may serve as a useful tool to predict prognosis and guide treatments for patients with HCC.

S-100 and MATH-1 Protein Expressions Can Be Useful for the Prediction of Clinical Outcome in Neuroblastoma Patients

Neuroblastoma (NB) is the most frequent extracranial solid tumor of childhood, remarkable for its broad spectrum of clinical behavior. This diversity in behavior correlates closely with defined clinical and biological features and combinations of prognostic variables are used for risk-group assignment. S-100 proteins have roles in differentiation and were shown to be frequently dysregulated in NB. MATH-1 protein plays role in neuronal cell differentiation through development. However, up to date, there are no studies evaluating the relationship between MATH-1 and NB. Grb2-associated binding (Gab) proteins have roles in the regulation of cell growth and differentiation. Gab1 was reported to be related to poor survival of high-risk NB patients. The aim of this study was to investigate the relationship between differentiation-related S-100, MATH-1, and Gab1 proteins and risk group and/or stages of NB. A significant relation was found between S-100 and early stages of NB. This study also revealed a significant association between MATH-1 and low-risk groups. S-100 and MATH-1 were also shown to provide survival advantages among stages and risk groups. The findings of this study support the assumption that S-100 and MATH-1 can be potential prognostic biomarkers for staging and risk-group assignment of NB patients. These proteins can be useful tools for clinicians to guide through treatment options, especially for the evaluation of tumor differentiation.

Exploring the prognostic value of S100A11 and its association with immune infiltration in breast cancer

Breast cancer (BC) is a severe danger to women's lives and health globally. S100A11 is aberrantly expressed in many carcinomas and serves a crucial function in cancer development. However, the role of S100A11 in BC is unclear. In this study, we utilized multiple databases and online tools, including the TCGA database, cBioPortal, and STRING, to evaluate the significance of S100A11 in BC prognosis and immune infiltration. We found that S100A11 was considerably more abundant in BC tissues. Survival analysis indicated that individuals with S100A11 high expression of BC had shorter overall survival. Multivariate Cox regression analysis revealed that high S100A11 expression independently influenced the poor outcome of patients with BC (HR = 1.738, 95%CI 1.197-2.524). Our nomogram incorporating five factors, including S100A11, age, clinical stage, N, and M, was developed to anticipate the survival probability in BC prognosis. The model demonstrated good consistency and accuracy. Furthermore, the mutation rete of S100A11 was 14%. Survival analysis suggested that breast cancer patients with S100A11 mutation had a worse prognosis. KEGG pathway enrichment analysis revealed that S100A11 may be mainly involved in the IL-17 signaling pathway. Finally, we discovered a correlation between S100A11 expression and immune cell infiltration on BC. S100A11 expression was positively associated with 17 immune checkpoint-related genes. In conclusion, this study indicates that S100A11 may contribute to a worse prognosis for BC and potentially has a significant impact through its influence on immune cell infiltration and the IL-17 signaling pathway.

Dual impacts of mesenchymal stem cell-derived exosomes on cancer cells: unravelling complex interactions

Mesenchymal stem cells (MSCs) are multipotent, self-renewing stromal cells found in a variety of adult tissues. MSCs possess a remarkable ability to migrate towards tumor sites, known as homing. This homing process is mediated by various factors, including chemokines, growth factors, and extracellular matrix components present in the tumor microenvironment. MSCs release extracellular vesicles known as exosomes (MSC-Exos), which have been suggested to serve a key role in mediating a wide variety of MSC activities. Through cell-cell communication, MSC-Exos have been shown to alter recipient cell phenotype or function and play as a novel cell-free alternative for MSC-based cell therapy. However, MSC recruitment to tumors allows for their interaction with cancer cells and subsequent regulation of tumor behavior. MSC-Exos act as tumor niche modulators via transferring exosomal contents, such as specific proteins or genetic materials, to the nearby cancer cells, leading to either promotion or suppression of tumorigenesis, angiogenesis, and metastasis, depending on the specific microenvironmental cues and recipient cell characteristics. Consequently, there is still a debate about the precise relationship between tumor cells and MSC-Exos, and it is unclear how MSC-Exos impacts tumor cells. Although the dysregulation of miRNAs is caused by the progression of cancer, they also play a direct role in either promoting or inhibiting tumor growth as they act as either oncogenes or tumor suppressors. The utilization of MSC-Exos may prove to be an effective method for restoring miRNA as a means of treating cancer. This review aimed to present the existing understanding of the impact that MSC-Exos could have on cancer. To begin with, we presented a brief explanation of exosomes, MSCs, and MSC-Exos. Following this, we delved into the impact of MSC-Exos on cancer growth, EMT, metastasis, angiogenesis, resistance to chemotherapy and radiotherapy, and modulation of the immune system. Opposing effects of mesenchymal stem cells-derived exosomes on cancer cells.

S100A6 is a potential diagnostic and prognostic biomarker for human glioma

S100 calcium-binding protein A6 (S100A6) is a protein that belongs to the S100 family. The present study aimed to investigate the function of S100A6 in the diagnosis and survival prediction of glioma and elucidated the potential processes affecting glioma development. The Cancer Genome Atlas database was searched to identify the relationship among S100A6 expression, immune cell infiltration, clinicopathological parameters and glioma prognosis. Several clinical cases were used to verify these findings. S100A6 gene expression was high in glioma tissues, suggesting its diagnostic significance. In particular, S100A6 upregulation in glioma tissues exhibited a significant and positive correlation with the World Health Organization (WHO) grade, histological type, age, sex, primary treatment outcomes, 1p/19q codeletion, isocitrate dehydrogenase (IDH) status, overall survival (OS), progression-free interval and disease-specific survival. Kaplan-Meier and Cox regression analyses revealed that S100A6 gene expression can independently function as a risk factor affecting the prognosis of patients with glioma. Furthermore, Gene Ontology functional enrichment analysis revealed that S100A6 is implicated in immune responses and that the expression profiles of S100A6 are linked to the immune microenvironment. Furthermore, immunohistochemistry revealed that increased S100A6 protein levels are correlated with age, 1p/19q codeletion, IDH status, WHO grade and OS. The present findings suggest that increased S100A6 expression is an indicator of the dismal prognosis of patients with glioma and that it can be used as a potential diagnostic biomarker for this condition.

Recent Advances in Molecular and Cellular Functions of S100A10

S100A10 (p11, annexin II light chain, calpactin light chain) is a multifunctional protein with a wide range of physiological activity. S100A10 is unique among the S100 family members of proteins since it does not bind to Ca2+, despite its sequence and structural similarity. This review focuses on studies highlighting the structure, regulation, and binding partners of S100A10. The binding partners of S100A10 were collated and summarized.

Gene Regulatory Network-Classifier: Gene Regulatory Network-Based Classifier and Its Applications to Gastric Cancer Drug (5-Fluorouracil) Marker Identification

The complex mechanisms of diseases involve the disturbance of the molecular network, rather than disorder in a single gene, implying that single gene-based analysis is insufficient to understand these mechanisms. Gene regulatory networks (GRNs) have attracted a lot of interest and various approaches have been developed for their statistical inference and gene network-based analysis. Although various computational methods have been developed, relatively little attention has been paid to incorporation of biological knowledge into the computational approaches. Furthermore, existing studies on network-based analysis perform prediction/classification of status of cell lines based on preconstructed GRNs, implying that we cannot extract prediction/classification-specific gene networks, leading to difficulty in interpretation of biological mechanisms and marker identification related to the status of cancer cell lines. We developed a novel strategy to build a GRN-based classifier, called a GRN-classifier. The proposed GRN-classifier estimates GRNs and classifies cell lines simultaneously, where the gene network is estimated to minimize error in gene network estimation and the negative log-likelihood for classifying cell lines. Thus, we can identify biological status-specific gene regulatory systems, enabling us to achieve biologically reliable interpretation of the classification. We also propose an algorithm to implement the GRN-classifier based on coordinate descent update. Monte Carlo simulations were conducted to examine performance of the GRN-classifier. Results: Our strategy provides effective results in feature selection in the classification model and edge selection in gene network estimation. The GRN-classifier also shows outstanding classification accuracy. We apply the GRN-classifier to classify cancer cell lines into anticancer drug-related status, that is, 5-fluorouracil (5-FU)-sensitive/resistant and 5-FU target/nontarget cancer cell lines. We then identified 5-FU markers based on 5-FU-related status classification-specific gene networks. The mechanisms of the identified markers were verified through literature survey. Our results suggest that the molecular interplay between MYOF and AHNAK2 may play a crucial role in drug resistance and can provide information on the chemotherapy efficiency of 5-FU. It is also suggested that suppression of the identified 5-FU markers, including MYOF/AHNAK2 and AKR1C1/AKR1C3 may improve 5-FU resistance of cancer cell lines.

Identification of a minimum number of genes to predict triple-negative breast cancer subgroups from gene expression profiles

BACKGROUND

Triple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them.

METHODS

Lehman's TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set.

RESULTS

We identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug-target interactions were found among the upregulated genes in the M, IM and MSL subsets.

CONCLUSIONS

Our study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amount of information from several data sets has allowed us to identify a well-determined minimal number of genes that may help in the recognition of TNBC subtypes. These genes, most of which have been previously found to be associated with breast cancer, have the potential to become novel diagnostic markers and/or therapeutic targets for specific TNBC subsets.

S100 Proteins in Fatty Liver Disease and Hepatocellular Carcinoma

Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent and slow progressing hepatic pathology characterized by different stages of increasing severity which can ultimately give rise to the development of hepatocellular carcinoma (HCC). Besides drastic lifestyle changes, few drugs are effective to some extent alleviate NAFLD and HCC remains a poorly curable cancer. Among the deregulated molecular mechanisms promoting NAFLD and HCC, several members of the S100 proteins family appear to play an important role in the development of hepatic steatosis, non-alcoholic steatohepatitis (NASH) and HCC. Specific members of this Ca²⁺-binding protein family are indeed significantly overexpressed in either parenchymal or non-parenchymal liver cells, where they exert pleiotropic pathological functions driving NAFLD/NASH to severe stages and/or cancer development. The aberrant activity of S100 specific isoforms has also been reported to drive malignancy in liver cancers. Herein, we discuss the implication of several key members of this family, e.g., S100A4, S100A6, S100A8, S100A9 and S100A11, in NAFLD and HCC, with a particular focus on their intracellular versus extracellular functions in different hepatic cell types. Their clinical relevance as non-invasive diagnostic/prognostic biomarkers for the different stages of NAFLD and HCC, or their pharmacological targeting for therapeutic purpose, is further debated.

All-trans retinoic acid enhanced the antileukemic efficacy of ABT-199 in acute myeloid leukemia by downregulating the expression of S100A8

Acute myeloid leukemia (AML) is prone to relapse. Targeted therapy with a specific inhibitor of the anti-apoptotic protein Bcl-2 ABT-199 is an effective method for relapsed and refractory patients, but drug resistance is likely, which is primarily related to high Mcl-1 and S100A8 expression. All-trans retinoic acid (ATRA) can inhibit Bcl-2 and Mcl-1 expression. The study purpose was to determine whether ATRA can enhance the antileukemia effect of ABT-199 on AML cells. Our data showed that ATRA combined with ABT-199 exerts a synergistic antileukemic effect by inducing apoptosis and cell cycle arrest in AML. In vivo, combination therapy prolonged the survival of AML xenograft mice. The possible mechanism involves promoting apoptosis through downregulation of S100A8 expression by inhibiting the PI3K/AKT signaling pathway. This study provides a potential treatment strategy and theoretical support for overcoming the clinical ABT-199 resistance problem in AML patients.

Relationships Between Serum Cortisol, RAGE-Associated s100A8/A9 Levels, and Self-Reported Cancer-Related Distress in Women With Nonmetastatic Breast Cancer

OBJECTIVE

Elevated inflammation and psychological distress in patients with breast cancer (BCa) have been related to poorer health outcomes. Regulation of the hypothalamic-pituitary-adrenal axis and signaling of the receptor for advanced glycation end products (RAGE) are important in the inflammatory response and have been associated with increased stress and poorer health outcomes in patients with cancer. This study examined relationships among circulating cortisol, a measure of hypothalamic-pituitary-adrenal axis activity and physiological stress; s100A8/A9, a RAGE ligand and emerging cancer-related biological measure; and self-reported cancer-related distress.

METHODS

Patients with BCa ( N = 183, stages 0-IIIb) were recruited 2 to 10 weeks after surgery but before receiving adjuvant therapies. Participants provided blood samples, from which serum cortisol and s100A8/A9 levels were determined, and completed a psychosocial questionnaire. Regression analyses, adjusting for age, cancer stage, time since surgery, race, and menopausal status, were conducted examining the relationships between cortisol, s100A8/A9, and cancer-related distress (Impact of Event Scale [IES]-Revised).

RESULTS

Cortisol and s100A8/A9 levels were positively related ( β = 0.218, t (112) = 2.332, p = .021), although the overall model was not significant. Cortisol levels were also positively associated with IES-Intrusions ( β = 0.192, t (163) = 2.659, p = .009) and IES-Hyperarousal subscale scores ( β = 0.171, t (163) = 2.304, p = .022).

CONCLUSIONS

Patients with higher cortisol levels also reported higher s100A8/A9 levels and more cancer-related distress. The relationship between cortisol and s100A8/A9 supports a link between the stress response and proinflammatory physiological processes known to predict a greater metastatic risk in BCa. Stress processes implicated in cancer biology are complex, and replication and extension of these initial findings are important.

Low social and family well-being is associated with greater RAGE ligand s100A8/A9 and interleukin-1 beta levels in metastatic breast cancer patients

Greater inflammatory signaling has been shown to promote breast cancer disease progression and poorer clinical outcomes. Lower social support and social well-being have been related to greater inflammatory signaling and poorer clinical outcomes in women with non-metastatic breast cancer, and this appears to be independent of depression. However, little is known about these associations in women with metastatic disease. s100A8/A9 and interleukin 1 beta (IL-1β) proteins are widely studied in breast cancer and are considered as biomarkers of cancer progression or as having a causal role in carcinogenesis and cancer progression and metastasis via inflammatory signaling. The aim of this study was to examine the associations between less social/family well-being (SWB) and S100A8/A9 and IL-1β levels in women diagnosed with metastatic breast cancer. Sixty women (Mean age 58.95 ​± ​1.49) with a diagnosis of metastatic breast cancer participated in the study. The Functional Assessment of Cancer Therapy (FACT) social and family well-being (SWB) subscale and the Hospital Anxiety Depression Scale (HADS) were administered to patients undergoing a first- or second-line endocrine or oral chemotherapy treatment and who were not experiencing brain metastasis or visceral crisis. Salivary s100A8/A9 and IL-1β levels were assessed at 5PM on two consecutive days and averaged. Multiple regression tested the independent contribution of SWB on s100 A8/A9 and IL-1b while controlling for depression. Lower levels of SWB were associated with greater S100A8/A9 (ß ​= ​-0.345, p ​= ​0.007) and IL-1β (ß ​= ​-0.286, p ​= ​0.027) levels and these associations remained significant after controlling for depression. This work provides new evidence for the role of decreased SWB and greater s100A8/A9 and IL-1b levels in patients diagnosed with metastatic breast cancer. Psychosocial interventions that promote social support and positive social interactions through interpersonal skills may help metastatic breast cancer patients to improve their SWB. This may have salutary effects on cancer-promoting processes, which could provide psychological and physical health benefits.

Identification of the Shared Gene Signatures and Biological Mechanism in Type 2 Diabetes and Pancreatic Cancer

Background

The relationship between pancreatic cancer (PC) and type 2 diabetes mellitus (T2DM) has long been widely recognized, but the interaction mechanisms are still unknown. This study was aimed to investigate the shared gene signatures and molecular processes between PC and T2DM.

Methods

The Gene Expression Omnibus (GEO) database was used to retrieve the RNA sequence and patient information of PC and T2DM. Weighted gene co-expression network analysis (WGCNA) was performed to discover a co-expression network associated with PC and T2DM. Enrichment analysis of shared genes present in PC and T2DM was performed by ClueGO software. These results were validated in the other four cohorts based on differential gene analysis. The predictive significance of S100A6 in PC was evaluated using univariate and multivariate Cox analyses, as well as Kaplan-Meier plots. The biological process of S100A6 enrichment in PC was detected using Gene Set Enrichment Analysis (GSEA). The involvement of S100A6 in the tumor immune microenvironment (TIME) was assessed by CIBERSORT. In vitro assays were used to further confirm the function of S100A6 in PC.

Results

WGCNA recognized three major modules for T2DM and two major modules for PC. There were 44 shared genes identified for PC and T2DM, and Gene Ontology (GO) analysis showed that regulation of endodermal cell fate specification was primarily enriched. In addition, a key shared gene S100A6 was derived in the validation tests. S100A6 was shown to be highly expressed in PC compared to non-tumor tissues. PC patients with high S100A6 expression had worse overall survival (OS) than those with low expression. GSEA revealed that S100A6 is involved in cancer-related pathways and glycometabolism-related pathways. There is a strong relationship between S100A6 and TIME. In vitro functional assays showed that S100A6 helped to induce the PC cells' proliferation and migration. We also proposed a diagram of common mechanisms of PC and T2DM.

Conclusions

This study firstly revealed that the regulation of endodermal cell fate specification may be common pathogenesis of PC and T2DM and identified S100A6 as a possible biomarker and therapeutic target for PC and T2DM patients.

Quantitative Proteomic Analysis of Cervical Cancer Tissues Identifies Proteins Associated With Cancer Progression

BACKGROUND/AIM

To date, several proteomics studies in cervical cancer (CC) have focused mainly on squamous cervical cancer (SCC). Our study aimed to discover and clarify differences in SCC and CAD that may provide valuable information for the identification of proteins involved in tumor progression, in CC as a whole, or specific for SCC or CAD.

MATERIALS AND METHODS

Total protein extracts from 15 individual samples corresponding to 5 different CC tissue types were compared with a non-cancerous control group using bidimensional liquid chromatography-mass spectrometry (2D LC-MS/MS), isobaric tags for relative and absolute quantitation (ITRAQ), principal component analysis (PCA) and gene set enrichment analysis (GSEA).

RESULTS

A total of 622 statistically significant different proteins were detected. Exocytosis-related proteins were the most over-represented, accounting for 25% of the identified and quantified proteins. Based on the experimental results, reticulocalbin 3 (RCN3) and Ras-related protein Rab-14 (RAB14) were chosen for further downstream in vitro and vivo analyses. RCN3 was overexpressed in all CC tissues compared to the control and RAB14 was overexpressed in squamous cervical cancer (SCC) compared to invasive cervical adenocarcinoma (CAD). In the tumor xenograft experiment, RAB14 protein expression was positively correlated with increased tumor size. In addition, RCN3-expressing HeLa cells induced a discrete size increment compared to control, at day 47 after inoculation.

CONCLUSION

RAB14 and RCN3 are suggested as potential biomarkers and therapeutic targets in the treatment of CC.

Erythropoietin Interacts with Specific S100 Proteins

Erythropoietin (EPO) is a clinically significant four-helical cytokine, exhibiting erythropoietic, cytoprotective, immunomodulatory, and cancer-promoting activities. Despite vast knowledge on its signaling pathways and physiological effects, extracellular factors regulating EPO activity remain underexplored. Here we show by surface plasmon resonance spectroscopy, that among eighteen members of Ca2+-binding proteins of the S100 protein family studied, only S100A2, S100A6 and S100P proteins specifically recognize EPO with equilibrium dissociation constants ranging from 81 nM to 0.5 µM. The interactions occur exclusively under calcium excess. Bioinformatics analysis showed that the EPO-S100 interactions could be relevant to progression of neoplastic diseases, including cancer, and other diseases. The detailed knowledge of distinct physiological effects of the EPO-S100 interactions could favor development of more efficient clinical implications of EPO. Summing up our data with previous findings, we conclude that S100 proteins are potentially able to directly affect functional activities of specific members of all families of four-helical cytokines, and cytokines of other structural superfamilies.

Deregulated calcium signaling in blood cancer: Underlying mechanisms and therapeutic potential

Intracellular calcium signaling regulates diverse physiological and pathological processes. In solid tumors, changes to calcium channels and effectors via mutations or changes in expression affect all cancer hallmarks. Such changes often disrupt transport of calcium ions (Ca²⁺) in the endoplasmic reticulum (ER) or mitochondria, impacting apoptosis. Evidence rapidly accumulates that this is similar in blood cancer. Principles of intracellular Ca²⁺ signaling are outlined in the introduction. We describe different Ca²⁺-toolkit components and summarize the unique relationship between extracellular Ca²⁺ in the endosteal niche and hematopoietic stem cells. The foundational data on Ca²⁺ homeostasis in red blood cells is discussed, with the demonstration of changes in red blood cell disorders. This leads to the role of Ca²⁺ in neoplastic erythropoiesis. Then we expand onto the neoplastic impact of deregulated plasma membrane Ca²⁺ channels, ER Ca²⁺ channels, Ca²⁺ pumps and exchangers, as well as Ca²⁺ sensor and effector proteins across all types of hematologic neoplasms. This includes an overview of genetic variants in the Ca²⁺-toolkit encoding genes in lymphoid and myeloid cancers as recorded in publically available cancer databases. The data we compiled demonstrate that multiple Ca²⁺ homeostatic mechanisms and Ca²⁺ responsive pathways are altered in hematologic cancers. Some of these alterations may have genetic basis but this requires further investigation. Most changes in the Ca²⁺-toolkit do not appear to define/associate with specific disease entities but may influence disease grade, prognosis, treatment response, and certain complications. Further elucidation of the underlying mechanisms may lead to novel treatments, with the aim to tailor drugs to different patterns of deregulation. To our knowledge this is the first review of its type in the published literature. We hope that the evidence we compiled increases awareness of the calcium signaling deregulation in hematologic neoplasms and triggers more clinical studies to help advance this field.

A Novel S100 Family-Based Signature Associated with Prognosis and Immune Microenvironment in Glioma

Background

Glioma is the most common central nervous system (CNS) cancer with a short survival period and a poor prognosis. The S100 family gene, comprising 25 members, relates to diverse biological processes of human malignancies. Nonetheless, the significance of S100 genes in predicting the prognosis of glioma remains largely unclear. We aimed to build an S100 family-based signature for glioma prognosis.

Methods

We downloaded 665 and 313 glioma patients, respectively, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database with RNAseq data and clinical information. This study established a prognostic signature based on the S100 family genes through multivariate COX and LASSO regression. The Kaplan-Meier curve was plotted to compare overall survival (OS) among groups, whereas Receiver Operating Characteristic (ROC) analysis was performed to evaluate model accuracy. A representative gene S100B was further verified by in vitro experiments.

Results

An S100 family-based signature comprising 5 genes was constructed to predict the glioma that stratified TCGA-derived cases as a low- or high-risk group, whereas the significance of prognosis was verified based on CGGA-derived cases. Kaplan-Meier analysis revealed that the high-risk group was associated with the dismal prognosis. Furthermore, the S100 family-based signature was proved to be closely related to immune microenvironment. In vitro analysis showed S100B gene in the signature promoted glioblastoma (GBM) cell proliferation and migration.

Conclusions

We constructed and verified a novel S100 family-based signature associated with tumor immune microenvironment (TIME), which may shed novel light on the glioma diagnosis and treatment.

Studying the Structures of Relaxed and Fuzzy Interactions: The Diverse World of S100 Complexes

S100 proteins are small, dimeric, Ca²⁺-binding proteins of considerable interest due to their associations with cancer and rheumatic and neurodegenerative diseases. They control the functions of numerous proteins by forming protein–protein complexes with them. Several of these complexes were found to display “fuzzy” properties. Examining these highly flexible interactions, however, is a difficult task, especially from a structural biology point of view. Here, we summarize the available in vitro techniques that can be deployed to obtain structural information about these dynamic complexes. We also review the current state of knowledge about the structures of S100 complexes, focusing on their often-asymmetric nature.

Comprehensive analysis of the transcriptional expressions and prognostic value of S100A family in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory malignancy with poor prognosis. It is urgent to identify novel and valid biomarkers to predict the progress and prognosis of PDAC. The S100A family have been identified as being involved in cell proliferation, migration and differentiation progression of various cancer types. However, the expression patterns and prognostic values of S100As in PDAC remain to be analyzed.

METHODS

We investigated the transcriptional expressions, methylation level and prognostic value of S100As in PDAC patients from the Oncomine, GEPIA2, Linkedomics and cBioPortal databases. Real-time PCR was used to detect the expressions of S100A2/4/6/10/14/16 in four pancreatic cancer cell lines and pancreatic cancer tissues from PDAC patients undergoing surgery. To verify the results further, immunohistochemistry was used to measure the expression of S100A2/4/6/10/14/16 in 43 PDAC patients' tissue samples. The drug relations of S100As were analyzed by using the Drugbank database.

RESULTS

The results suggested that, the expression levels of S100A2/4/6/10/14/16 were elevated to PDAC tissues than in normal pancreatic tissues, and the promoter methylation levels of S100A S100A2/4/6/10/14/16 in PDAC (n = 10) were lower compared with normal tissue (n = 184) (P < 0.05). In addition, their expressions were negatively correlated with PDAC patient survival.

CONCLUSIONS

Taken together, these results suggest that S100A2/4/6/10/14/16 might be served as prognostic biomarkers for survivals of PDAC patients.

Calcium signaling in cancer progression and therapy

The old Greek aphorism 'Panta Rhei' ('everything flows') is true for all living things in general. As a dynamic process, calcium signaling plays fundamental roles in cellular activities under both normal and pathological conditions, with recent researches uncovering its involvement in cell proliferation, migration, survival, gene expression, and more. The major question we address here is how calcium signaling affects cancer progression and whether it could be targeted to combine with classic chemotherapeutics or emerging immunotherapies to improve their efficacy.

YAP inactivation in estrogen receptor alpha-positive hepatocellular carcinoma with less aggressive behavior

The expression of estrogen receptor alpha (ERα, encoded by ESR1) has been shown to be associated with the prognostic outcomes of patients in various cancers; however, its prognostic and mechanistic significance in hepatocellular carcinoma (HCC) remain unclear. Here, we evaluated the expression of ERα and its association with clinicopathological features in 339 HCC patients. ERα was expressed in 9.4% (32/339) of HCCs and was related to better overall survival (OS; hazard ratio [HR] = 0.11, p = 0.009, 95% C.I. = 0.016–0.82) and disease-free survival (DFS, HR = 0.4, p = 0.013, 95% C.I. = 0.18–0.85). ERα expression was also associated with features related to more favorable prognosis, such as older age, lower serum alpha-fetoprotein level, and less microvascular invasion (p < 0.05). In addition, to obtain mechanistic insights into the role of ERα in HCC progression, we performed integrative transcriptome data analyses, which revealed that yes-associated protein (YAP) pathway was significantly suppressed in ESR1-expressing HCCs. By performing cell culture experiments, we validated that ERα expression enhanced YAP phosphorylation, attenuating its nuclear translocation, which in turn suppressed the downstream signaling pathways and cancer cell growth. In conclusion, we suggest that ERα expression is an indicator of more favorable prognosis in HCC and that this effect is mediated by inactivation of YAP signaling. Our results provide new clinical and pathobiological insights into ERα and YAP signaling in HCC.

Estrogen receptor signaling can act as a brake preventing the progression of an often deadly form of liver cancer. Studies have shown that women are at a lower risk of developing and succumbing to hepatocellular carcinoma (HCC) than men, suggesting a potential role for sex hormones. Researchers in South Korea led by Hyun Goo Woo of the Ajou University School of Medicine, Suwon, and Young Nyun Park of Yonsei University College of Medicine, Seoul, have now shown that expression of the estrogen receptor α is a strong prognostic predictor for HCC. In a survey of patient tumor samples, they found that expression of this hormone receptor is associated with nearly a tenfold increased likelihood of survival. The researchers identified a mechanism by which estrogen receptor α signaling impedes cancerous growth, revealing potential new drug targets.

The S100 protein family in lung cancer

The S100 protein family is involved in the pathogenesis of several malignancies including lung cancer. Recent studies have shown that one member, S100A2, was over-expressed in advanced stage non-small cell lung cancer (NSCLC). Another, S100A6, demonstrated variable expression in different lung cancer subtypes. Research using NSCLC cell lines reported that SIX3 inhibited cell metastasis and proliferation via S100P down-regulation. This review represents an update on S100 proteins in lung cancer from 2017 to 2021 and includes the aforementioned as well as S100A4, S100A7, and S100B. Inconsistencies in mechanisms of action for S100A8/S100A9 are highlighted and a comprehensive evaluation of the most recent evidence for the S100 proteins in lung cancer is presented.

Synergistic Combination of Bioactive Hydroxyapatite Nanoparticles and the Chemotherapeutic Doxorubicin to Overcome Tumor Multidrug Resistance

Multidrug resistance (MDR) is one of the biggest obstacles in cancer chemotherapy. Here, a remarkable reversal of MDR in breast cancer through the synergistic effects of bioactive hydroxyapatite nanoparticles (HAPNs) and doxorubicin (DOX) is shown. DOX loaded HAPNs (DHAPNs) exhibit a 150-fold reduction in IC₅₀ compared with free DOX for human MDR breast cancer MCF-7/ADR cells, and lead to almost complete inhibition of tumor growth in vivo without obvious side effects of free DOX. This high efficacy and specificity could be attributed to multiple action mechanisms of HAPNs. In addition to acting as the conventional nanocarriers to facilitate the cellular uptake and retention of DOX in MCF-7/ADR cells, more importantly, drug-free HAPNs themselves are able to prevent drug being pumped out of MDR cells through targeting mitochondria to induce mitochondrial damage and inhibit ATP production and to trigger sustained mitochondrial calcium overload and apoptosis in MDR cancer cells while not affecting normal cells. The results demonstrate that this simple but versatile bioactive nanoparticle provides a practical approach to effectively overcome MDR.

Pathogenic Roles of S100A8 and S100A9 Proteins in Acute Myeloid and Lymphoid Leukemia: Clinical and Therapeutic Impacts

Deregulations of the expression of the S100A8 and S100A9 genes and/or proteins, as well as changes in their plasma levels or their levels of secretion in the bone marrow microenvironment, are frequently observed in acute myeloblastic leukemias (AML) and acute lymphoblastic leukemias (ALL). These deregulations impact the prognosis of patients through various mechanisms of cellular or extracellular regulation of the viability of leukemic cells. In particular, S100A8 and S100A9 in monomeric, homodimeric, or heterodimeric forms are able to modulate the survival and the sensitivity to chemotherapy of leukemic clones through their action on the regulation of intracellular calcium, on oxidative stress, on the activation of apoptosis, and thanks to their implications, on cell death regulation by autophagy and pyroptosis. Moreover, biologic effects of S100A8/9 via both TLR4 and RAGE on hematopoietic stem cells contribute to the selection and expansion of leukemic clones by excretion of proinflammatory cytokines and/or immune regulation. Hence, the therapeutic targeting of S100A8 and S100A9 appears to be a promising way to improve treatment efficiency in acute leukemias.

Targeting the IRAK1-S100A9 Axis Overcomes Resistance to Paclitaxel in Nasopharyngeal Carcinoma

Novel strategies to treat late-stage nasopharyngeal carcinoma that often develop resistance to chemotherapy remains an unmet clinical demand. In this study, we identify the multi-kinase inhibitor pacritinib as capable of resensitizing the response to paclitaxel in an acquired resistance model. Transcriptome analysis of paclitaxel-sensitive and -resistant cell lines, as well as chemorefractory clinical samples, identified S100A9 as the top candidate gene suppressed by pacritinib and whose overexpression was significantly associated with paclitaxel resistance and poor clinical outcome. Moreover, both paclitaxel-resistant nasopharyngeal carcinoma cells and relapsed/metastatic clinical samples exhibited increased IRAK1 phosphorylation and demonstrated that pacritinib could abolish the IRAK1 phosphorylation to suppress S100A9 expression. Functional studies in both in vitro and in vivo models showed that genetic or pharmacologic blockade of IRAK1 overcame the resistance to paclitaxel, and combined treatment of pacritinib with paclitaxel exhibited superior antitumor effect. Together, these findings demonstrate an important role for the IRAK1-S100A9 axis in mediating resistance to paclitaxel. Furthermore, targeting of IRAK1 by pacritinib may provide a novel therapeutic strategy to overcome chemoresistance in nasopharyngeal carcinoma. SIGNIFICANCE: Deregulation of the IRAK1-S100A9 axis correlates with poor prognosis, contributes to chemoresistance in nasopharyngeal carcinoma, and can be targeted by pacritinib to overcome chemoresistance in nasopharyngeal carcinoma.

Damage-Associated Molecular Patterns and Their Signaling Pathways in Primary Blast Lung Injury: New Research Progress and Future Directions

Primary blast lung injury (PBLI) is a common cause of casualties in wars, terrorist attacks, and explosions. It can exist in the absence of any other outward signs of trauma, and further develop into acute lung injury (ALI) or a more severe acute respiratory distress syndrome (ARDS). The pathogenesis of PBLI at the cellular and molecular level has not been clear. Damage-associated molecular pattern (DAMP) is a general term for endogenous danger signals released by the body after injury, including intracellular protein molecules (HMGB1, histones, s100s, heat shock proteins, eCIRP, etc.), secretory protein factors (IL-1β, IL-6, IL-10, TNF-α, VEGF, complements, etc.), purines and pyrimidines and their derived degradation products (nucleic acids, ATP, ADP, UDPG, uric acid, etc.), and extracellular matrix components (hyaluronic acid, fibronectin, heparin sulfate, biglycan, etc.). DAMPs can be detected by multiple receptors including pattern recognition receptors (PRRs). The study of DAMPs and their related signaling pathways, such as the mtDNA-triggered cGAS-YAP pathway, contributes to revealing the molecular mechanism of PBLI, and provides new therapeutic targets for controlling inflammatory diseases and alleviating their symptoms. In this review, we focus on the recent progress of research on DAMPs and their signaling pathways, as well as the potential therapeutic targets and future research directions in PBLI.

Friend or Foe: S100 Proteins in Cancer

S100 proteins are widely expressed small molecular EF-hand calcium-binding proteins of vertebrates, which are involved in numerous cellular processes, such as Ca²⁺ homeostasis, proliferation, apoptosis, differentiation, and inflammation. Although the complex network of S100 signalling is by far not fully deciphered, several S100 family members could be linked to a variety of diseases, such as inflammatory disorders, neurological diseases, and also cancer. The research of the past decades revealed that S100 proteins play a crucial role in the development and progression of many cancer types, such as breast cancer, lung cancer, and melanoma. Hence, S100 family members have also been shown to be promising diagnostic markers and possible novel targets for therapy. However, the current knowledge of S100 proteins is limited and more attention to this unique group of proteins is needed. Therefore, this review article summarises S100 proteins and their relation in different cancer types, while also providing an overview of novel therapeutic strategies for targeting S100 proteins for cancer treatment.