S100A13 is a new angiogenic marker in human melanoma

S-100 Proteins: Basics and Applications as Biomarkers in Animals with Special Focus on Calgranulins (S100A8, A9, and A12)

S100 proteins are a group of calcium-binding proteins which received this name because of their solubility in a 100% saturated solution of ammonium sulphate. They have a similar molecular mass of 10-12 KDa and share 25-65% similarity in their amino acid sequence. They are expressed in many tissues, and to date 25 different types of S100 proteins have been identified. This review aims to provide updated information about S100 proteins and their use as biomarkers in veterinary science, with special emphasis on the family of calgranulins that includes S100A8 (calgranulin A; myeloid-related protein 8, MRP8), S100A9 (calgranulin B; MRP14), and S100A12 (calgranulin C). The proteins SA100A8 and S100A9 can be linked, forming a heterodimer which is known as calprotectin. Calgranulins are related to the activation of inflammation and the immune system and increase in gastrointestinal diseases, inflammation and sepsis, immunomediated diseases, and obesity and endocrine disorders in different animal species. This review reflects the current knowledge about calgranulins in veterinary science, which should increase in the future to clarify their role in different diseases and potential as biomarkers and therapeutic targets, as well as the practical use of their measurement in non-invasive samples such as saliva or feces.

Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data

Introduction

Uveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.

Methods

Based on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.

Results

The immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.

Discussion

The immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.

The Interplay between Tumour Microenvironment Components in Malignant Melanoma

Malignant melanoma has shown an increasing incidence during the last two decades, exhibiting a large spectrum of locations and clinicopathological characteristics. Although current histopathological, biochemical, immunohistochemical, and molecular methods provide a deep insight into its biological behaviour and outcome, melanoma is still an unpredictable disease, with poor outcome. This review of the literature is aimed at updating the knowledge regarding melanoma’s clinicopathological and molecular hallmarks, including its heterogeneity and plasticity, involving cancer stem cells population. A special focus is given on the interplay between different cellular components and their secretion products in melanoma, considering its contribution to tumour progression, invasion, metastasis, recurrences, and resistance to classical therapy. Furthermore, the influences of the specific tumour microenvironment or “inflammasome”, its association with adipose tissue products, including the release of “extracellular vesicles”, and distinct microbiota are currently studied, considering their influences on diagnosis and prognosis. An insight into melanoma’s particular features may reveal new molecular pathways which may be exploited in order to develop innovative therapeutic approaches or tailored therapy.

Autocrine/Paracrine Loop Between SCF+/c-Kit+ Mast Cells Promotes Cutaneous Melanoma Progression

c-Kit, or mast/stem cell growth factor receptor Kit, is a tyrosine kinase receptor structurally analogous to the colony-stimulating factor-1 (CSF-1) and platelet-derived growth factor (PDGF) CSF-1/PDGF receptor Tyr-subfamily. It binds the cytokine KITLG/SCF to regulate cell survival and proliferation, hematopoiesis, stem cell maintenance, gametogenesis, mast cell development, migration and function, and it plays an essential role in melanogenesis. SCF and c-Kit are biologically active as membrane-bound and soluble forms. They can be expressed by tumor cells and cells of the microenvironment playing a crucial role in tumor development, progression, and relapses. To date, few investigations have concerned the role of SCF+/c-Kit+ mast cells in normal, premalignant, and malignant skin lesions that resemble steps of malignant melanoma progression. In this study, by immunolabeling reactions, we demonstrated that in melanoma lesions, SCF and c-Kit were expressed in mast cells and released by themselves, suggesting an autocrine/paracrine loop might be implicated in regulatory mechanisms of neoangiogenesis and tumor progression in human melanoma.

The Role of Calcium Signaling in Melanoma

Calcium signaling plays important roles in physiological and pathological conditions, including cutaneous melanoma, the most lethal type of skin cancer. Intracellular calcium concentration ([Ca²⁺]i), cell membrane calcium channels, calcium related proteins (S100 family, E-cadherin, and calpain), and Wnt/Ca²⁺ pathways are related to melanogenesis and melanoma tumorigenesis and progression. Calcium signaling influences the melanoma microenvironment, including immune cells, extracellular matrix (ECM), the vascular network, and chemical and physical surroundings. Other ionic channels, such as sodium and potassium channels, are engaged in calcium-mediated pathways in melanoma. Calcium signaling serves as a promising pharmacological target in melanoma treatment, and its dysregulation might serve as a marker for melanoma prediction. We documented calcium-dependent endoplasmic reticulum (ER) stress and mitochondria dysfunction, by targeting calcium channels and influencing [Ca²⁺]i and calcium homeostasis, and attenuated drug resistance in melanoma management.

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.

Integrated single-cell and bulk RNA sequencing analysis identifies a cancer associated fibroblast-related signature for predicting prognosis and therapeutic responses in colorectal cancer

Background

Cancer-associated fibroblasts (CAFs) contribute notably to colorectal cancer (CRC) tumorigenesis, stiffness, angiogenesis, immunosuppression and metastasis, and could serve as a promising therapeutic target. Our purpose was to construct CAF-related prognostic signature for CRC.

Methods

We performed bioinformatics analysis on single-cell transcriptome data derived from Gene Expression Omnibus (GEO) and identified 208 differentially expressed cell markers from fibroblasts cluster. Bulk gene expression data of CRC was obtained from The Cancer Genome Atlas (TCGA) and GEO databases. Univariate Cox regression and least absolute shrinkage operator (LASSO) analyses were performed on TCGA training cohort (n = 308) for model construction, and was validated in TCGA validation (n = 133), TCGA total (n = 441), GSE39582 (n = 470) and GSE17536 (n = 177) datasets. Microenvironment Cell Populations-counter (MCP-counter) and Estimate the Proportion of Immune and Cancer cells (EPIC) methods were applied to evaluated CAFs infiltrations from bulk gene expression data. Real-time polymerase chain reaction (qPCR) was performed in tissue microarrays containing 80 colon cancer samples to further validate the prognostic value of the CAF model. pRRophetic and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to predict chemosensitivity and immunotherapy response. Human Protein Atlas (HPA) databases and immunohistochemistry were used to evaluate the protein expressions.

Results

A nine-gene prognostic CAF-related signature was established in training cohort. Kaplan–Meier survival analyses revealed patients with higher CAF risk scores were correlated with adverse prognosis in each cohort. MCP-counter and EPIC results consistently revealed CAFs infiltrations were significantly higher in high CAF risk group. Patients with higher CAF risk scores were more prone to not respond to immunotherapy, but were more sensitive to several conventional chemotherapeutics, suggesting a potential strategy of combining chemotherapy with anti-CAF therapy to improve the efficacy of current T-cell based immunotherapies. Univariate and multivariate Cox regression analyses verified the CAF model was as an independent prognostic indicator in predicting overall survival, and a CAF-based nomogram was then built for clinical utility in predicting prognosis of CRC.

Conclusion

To conclude, the CAF-related signature could serve as a robust prognostic indicator in CRC, which provides novel genomics evidence for anti-CAF immunotherapeutic strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02252-9.

S100 Calcium Binding Protein Family Members Associate With Poor Patient Outcome and Response to Proteasome Inhibition in Multiple Myeloma

Despite several new therapeutic options, multiple myeloma (MM) patients experience multiple relapses and inevitably become refractory to treatment. Insights into drug resistance mechanisms may lead to the development of novel treatment strategies. The S100 family is comprised of 21 calcium binding protein members with 17 S100 genes located in the 1q21 region, which is commonly amplified in MM. Dysregulated expression of S100 family members is associated with tumor initiation, progression and inflammation. However, the relationship between the S100 family and MM pathogenesis and drug response is unknown. In this study, the roles of S100 members were systematically studied at the copy number, transcriptional and protein level with patients’ survival and drug response. Copy number analysis revealed a predominant pattern of gains occurring in S100 genes clustering in the 1q21 locus. In general, gains of genes encoding S100 family members associated with worse patient survival. However, S100 gene copy number and S100 gene expression did not necessarily correlate, and high expression of S100A4 associated with poor patient survival. Furthermore, integrated analysis of S100 gene expression and ex vivo drug sensitivity data showed significant negative correlation between expression of S100 family members (S100A8, S100A9, and S100A12) and sensitivity to some drugs used in current MM treatment, including proteasome inhibitors (bortezomib, carfilzomib, and ixazomib) and histone deacetylase inhibitor panobinostat. Combined proteomic and pharmacological data exhibited significant negative association of S100 members (S100A4, S100A8, and S100A9) with proteasome inhibitors and panobinostat. Clinically, the higher expression of S100A4 and S100A10 were significantly linked to shorter progression free survival in patients receiving carfilzomib-based therapy. The results indicate an association and highlight the potential functional importance of S100 members on chromosome 1q21 in the development of MM and resistance to established myeloma drugs, including proteasome inhibitors.

The S100 Protein Family as Players and Therapeutic Targets in Pulmonary Diseases

The S100 protein family consists of over 20 members in humans that are involved in many intracellular and extracellular processes, including proliferation, differentiation, apoptosis, Ca₂⁺ homeostasis, energy metabolism, inflammation, tissue repair, and migration/invasion. Although there are structural similarities between each member, they are not functionally interchangeable. The S100 proteins function both as intracellular Ca²⁺ sensors and as extracellular factors. Dysregulated responses of multiple members of the S100 family are observed in several diseases, including the lungs (asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, cystic fibrosis, pulmonary hypertension, and lung cancer). To this degree, extensive research was undertaken to identify their roles in pulmonary disease pathogenesis and the identification of inhibitors for several S100 family members that have progressed to clinical trials in patients for nonpulmonary conditions. This review outlines the potential role of each S100 protein in pulmonary diseases, details the possible mechanisms observed in diseases, and outlines potential therapeutic strategies for treatment.

Comparative analysis of triple-negative breast cancer transcriptomics of Kenyan, African American and Caucasian Women

•

The current study determined the molecular fingerprints of TNBCs of women from kenya (KE) and compared them with those of African–American (AA) and Caucasian (CA) women.

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RNA sequencing analysis highlights the role of molecular alterations in TNBCs and the potential benefit of targeting pathways in this disease for the KE population as compared to AAs and CAs.

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The dysregulated genes and signaling pathways could contributes to the aggressive phenotypes of TNBCs of KE women.

Purpose

: Triple-negative breast cancer (TNBC) patients of various ethnic groups often have discrete clinical presentations and outcomes. Women of African descent have a disproportionately higher chance of developing TNBCs. The aim of the current study was to establish the transcriptome of TNBCs from Kenyan (KE) women of Bantu origin and compare it to those TNBCs of African-Americans (AA) and Caucasians (CA) for identifying KE TNBC-specific molecular determinants of cancer progression and potential biomarkers of clinical outcomes.

Patients and Methods

: Pathology-confirmed TNBC tissues from Kenyan women of Bantu origin (n = 15) and age and stage range matched AA (n = 19) and CA (n = 23) TNBCs of patients from Alabama were included in this study. RNA was isolated from paraffin-embedded tissues, and expression was analyzed by RNA sequencing.

Results

: At clinical presentation, young KE TNBC patients have tumors of higher stages. Differential expression analysis identified 160 up-regulated and 178 down-regulated genes in KE TNBCs compared to AA and CA TNBCs. Validation analyses of the TCGA breast cancer data identified 45 KE TNBC-specific genes that are involved in the apoptosis (ACTC1, ERCC6 and CD14), cell proliferation (UHRF2, KDM4C, UHMK1, KCNH5, KRT18, CSF1R and S100A13), and Wnt signaling (BCL9L) pathways.

Conclusions

: In this study, we identified biomarkers that are specific for KE TNBC patients of Bantu origin. Further study with a larger sample size of matched tumors could confirm our findings. If biologically confirmed, these molecular determinants could have clinical and biological implications and serve as targets for development of personalized therapeutics for KE TNBC patients.

Comprehensive Analysis of the Prognosis and Correlations With Immune Infiltration of S100 Protein Family Members in Hepatocellular Carcinoma

S100 protein family members (S100s) are commonly dysregulated in various tumors including hepatocellular carcinoma (HCC). However, the diverse expression, mutation, prognosis and associations with immune infiltration of S100s in HCC have yet to be analyzed. Herein we investigated the roles of S100s in HCC from the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas, Kaplan-Meier Plotter, cBioPortal and TIMER databases. Compared with para-cancer tissues, the expression levels of S100A4/S100A6/S100A10/S100A11/S100A13/S100A14/S100P were higher in HCC tissues, while the expression levels of S100A8/S100A9/S100A12 were decreased in tumor tissues. The mRNA levels of S100A2/S100A7/S100A7A/S100A8/S100A9/S100A11 were correlated with advanced tumor stage. Besides, higher mRNA expressions of S100A6/S100A10/S100A11/S100A13/S100A14/S100P were shown to have shorter overall survival (OS), while higher expression of S100A12 was associated with favorable OS. Further, the mutation rate of S100s was investigated, and the high mutation rate (53%) was associated with shorter OS. Additionally, the expressions of S100s were found to be significantly associated with various immune infiltrating cells. Hence, our results showed that S100A6/S100A10/S100A11/S10012/S100A13/S100A14/S100P may be regarded as new prognostic or therapeutic markers and S100s inhibitors may be helpful in the combination of immunotherapies.

Thyroid Carcinoma: Phenotypic Features, Underlying Biology and Potential Relevance for Targeting Therapy

Thyroid carcinoma consists a group of phenotypically heterogeneous cancers. Recent advances in biological technologies have been advancing the delineation of genetic, epigenetic, and non-genetic factors that contribute to the heterogeneities of these cancers. In this review article, we discuss new findings that are greatly improving the understanding of thyroid cancer biology and facilitating the identification of novel targets for therapeutic intervention. We review the phenotypic features of different subtypes of thyroid cancers and their underlying biology. We discuss recent discoveries in thyroid cancer heterogeneities and the critical mechanisms contributing to the heterogeneity with emphases on genetic and epigenetic factors, cancer stemness traits, and tumor microenvironments. We also discuss the potential relevance of the intratumor heterogeneity in understanding therapeutic resistance and how new findings in tumor biology can facilitate designing novel targeting therapies for thyroid cancer.

Development of a prognostic model based on an immunogenomic landscape analysis of medulloblastoma

Medulloblastoma (MB) is one of the most common central nervous system tumors in children. At present, the vital role of immune abnormalities has been proved in tumorigenesis and progression. However, the immune mechanism in MB is still poorly understood. In the present study, 51 differentially expressed immune-related genes (DE-IRGs) and 226 survival associated immune-related genes (Sur-IRGs) were screened by an integrated analysis of multi-array. Moreover, the potential pathways were enriched by functional analysis, such as ‘cytokine–cytokine receptor interaction’, ‘Ras signaling pathway’, ‘PI3K-Akt signaling pathway’ and ‘pathways in cancer’. Furthermore, 10 core IRGs were identified from DE-IRGs and Sur-IRGs. And the potential regulatory mechanisms of core IRGs were also explored. Additionally, a new prognostic model, including 7 genes (HDGF, CSK, PNOC, S100A13, RORB, FPR1, and ICAM2) based on IRGs, was established by multivariable COX analysis. In summary, our study revealed the underlying immune mechanism of MB. Moreover, we developed a prognostic model associated with clinical characteristics and could reflect the infiltration of immune cells.

An Integrated Bioinformatic Analysis of the S100 Gene Family for the Prognosis of Colorectal Cancer

Background

S100 family genes exclusively encode at least 20 calcium-binding proteins, which possess a wide spectrum of intracellular and extracellular functions in vertebrates. Multiple lines of evidences suggest that dysregulated S100 proteins are associated with human malignancies including colorectal cancer (CRC). However, the diverse expression patterns and prognostic roles of distinct S100 genes in CRC have not been fully elucidated.

Methods

In the current study, we analyzed the mRNA expression levels of S100 family genes and proteins and their associations with the survival of CRC patients using the Oncomine analysis and GEPIA databases. Expressions and mutations of S100 family genes were analyzed using the cBioPortal, and protein-protein interaction (PPI) networks of S100 proteins and their mutation-related coexpressed genes were analyzed using STRING and Cytoscape.

Results

We observed that the mRNA expression levels of S100A2, S100A3, S100A9, S100A11, and S100P were higher and the level of S100B was lower in CRC tissues than those in normal colon mucosa. A high S100A10 levels was associated with advanced-stage CRC. Results from GEPIA database showed that highly expressed S100A1 was correlated with worse overall survival (OS) and disease-free survival (DFS) and that overexpressions of S100A2 and S100A11 were associated with poor DFS of CRC, indicating that S100A1, S100A2, and S100A11 are potential prognostic markers. Unexpectedly, most of S100 family genes showed no significant prognostic values in CRC.

Conclusions

Our findings, though still need to be ascertained, offer novel insights into the prognostic implications of the S100 family in CRC and will inspire more clinical trials to explore potential S100-targeted inhibitors for the treatment of CRC.

RAGE Signaling in Melanoma Tumors

Despite recent progresses in its treatment, malignant cutaneous melanoma remains a cancer with very poor prognosis. Emerging evidences suggest that the receptor for advance glycation end products (RAGE) plays a key role in melanoma progression through its activation in both cancer and stromal cells. In tumors, RAGE activation is fueled by numerous ligands, S100B and HMGB1 being the most notable, but the role of many other ligands is not well understood and should not be underappreciated. Here, we provide a review of the current role of RAGE in melanoma and conclude that targeting RAGE in melanoma could be an approach to improve the outcomes of melanoma patients.

Cisplatin-Induced Giant Cells Formation Is Involved in Chemoresistance of Melanoma Cells

Melanoma is notoriously resistant to current cancer therapy. However, the chemoresistance mechanism of melanoma remains unclear. The present study unveiled that chemotherapy drug cisplatin induced the formation of giant cells, which exhibited enlargement in cell diameter and nucleus in mice and human melanoma cells. Giant cells were positive with melanoma maker S100 and cancer stem cell markers including ABCB5 and CD133 in vitro and in vivo. Moreover, giant cells retained the mitotic ability with expression of proliferation marker Ki-67 and exhibited multiple drug resistance to doxorubicin and actinomycin D. The mitochondria genesis/activities and cellular ATP level were significantly elevated in giant cells, implicating the demand for energy supply. Application of metabolic blockers such as sodium azide or 2-deoxy glucose abolished the cisplatin-induced giant cells formation and expression of cancer stemness markers. The present study unveils a novel chemoresistance mechanism of melanoma cells via size alteration and the anti-neoplastic strategy by targeting giant cells.

Prognostic alternative splicing signature reveals the landscape of immune infiltration in Pancreatic Cancer

Background: Pancreatic cancer (PC) is an aggressive cancer with worse survival in the world. Emerging evidence suggested that the imbalance of alternative splicing (AS) is a hallmark of cancer and indicated poor prognosis of patients. Genes-derived splicing events can produce neoepitopes for immunotherapy. However, the profound study of splicing profiling in PC is still elusive. We aimed to identification of novel prognostic signature across a comprehensive splicing landscape and reveal their relationship with tumor-infiltrating immune cells in pancreatic cancer microenvironment.

Methods: Based on integrated analysis of splicing profiling and clinical data, differentially splicing events were filtered out. Then, stepwise Cox regression analysis was applied to identify survival-related splicing events and construct prognostic signature. Functional enrichment analysis was performed to explore biology function. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were performed to validate the predictive effect of predictive signature. We also verified the clinical value of prognostic signature under the influence of different clinical parameters. For deeper analysis, we evaluated the correlation between prognostic signature and infiltrating immune cells by CIBERSORT.

Results: According to systematic analyzing, a final six splicing events were identified and validated the good prognostic capability in entire TCGA dataset, validation set 1 and validation set 2 by Kaplan-Meier curves (P < 0.0001). The area under the curve (AUC) of ROC curves were also confirmed the high predictive efficiency of the prognostic signature in these three cohorts (AUC = 0.857, 0.895 and 0.788). In order to validate whether prognostic signature highlights a correlation between AS and immune contexture, CIBERSORT was performed to analyze the proportion of tumor-infiltrating immune cells in PC. Based on prognostic signature, we identified survival-related immune cells including CD8 T cells (P = 0.0111), activated CD4 memory T cells (P = 0.0329) and resting mast cells (P = 0.0352).

Conclusion: In conclusion, our study contribute to provide a promising prognostic signature based on six splicing events and revealed prognosis-related immune cells which indeed represented novel tumor drivers and provide potential targets for personalized therapeutic.

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.

Intracellular partners of fibroblast growth factors 1 and 2 - implications for functions

Fibroblast growth factors 1 and 2 (FGF1 and FGF2) are mainly considered as ligands of surface receptors through which they regulate a broad spectrum of biological processes. They are secreted in non-canonical way and, unlike other growth factors, they are able to translocate from the endosome to the cell interior. These unique features, as well as the role of the intracellular pool of FGF1 and FGF2, are far from being fully understood. An increasing number of reports address this problem, focusing on the intracellular interactions of FGF1 and 2. Here, we summarize the current state of knowledge of the FGF1 and FGF2 binding partners inside the cell and the possible role of these interactions. The partner proteins are grouped according to their function, including proteins involved in secretion, cell signaling, nucleocytoplasmic transport, binding and processing of nucleic acids, ATP binding, and cytoskeleton assembly. An in-depth analysis of the network of these binding partners could indicate novel, non-classical functions of FGF1 and FGF2 and uncover an additional level of a fine control of the well-known FGF-regulated cellular processes.

Prognostic values of S100 family mRNA expression in ovarian cancer

S100 family is made up of at least 20 calcium-binding proteins which are involved in many cellular processes. The prognostic values of individual S100 member in ovarian cancer patients are still unknown. In this study, we performed a detailed prognostic values of S100 in ovarian cancer. The mRNA expression levels of S100 family in various cancers were analyzed via the Oncomine, and the protein-protein interaction network of S100 family was analyzed via String. The prognostic values of individual S100 member were evaluated via Kaplan-Meier Plotter. The S100 family genes expression and mutation were analyzed via cBioProtal. We observed that the mRNA expression of most S100 family were overexpressed in ovarian cancer compared with normal tissues. In survival analysis in Kaplan-Meier Plotter, 10 members of S100 family showed significant correlation with overall survival in ovarian cancer patients. The trends of high expression of individual S100 members were nearly the same in different subtype and pathological grades. However, the S100 family genes expression and mutation showed no significant prognostic values in overall survival and disease free survival in ovarian cancer patients. Although, the results need more verification both in clinical trials and fundamental experiments, our study provide new insights for the prognostic function of S100 family in ovarian cancer and might promote development of S100 targeted inhibitors for the new treatment of ovarian cancer.

Identification of Prognostic Signatures for Predicting the Overall Survival of Uveal Melanoma Patients

Uveal melanoma (UM) is an aggressive cancer which has a high percentage of metastasis and with a poor prognosis. Identifying the potential prognostic markers of uveal melanoma may provide information for early detection of metastasis and treatment. In this work, we analyzed 80 uveal melanoma samples from The Cancer Genome Atlas (TCGA). We developed an 18-gene signature which can significantly predict the prognosis of UM patients. Firstly, we performed a univariate Cox regression analysis to identify significantly prognostic genes in uveal melanoma (P<0.01). Then the glmnet Cox analysis was used to generate a powerful prognostic gene model. Further, we established a risk score formula for every patient based on the 18-gene prognostic model with multivariate Cox regression. We stratified patients into high- and low-risk subtypes with median risk score and found that patients in high-risk group had worse prognosis than patients in low-risk group. Multivariate Cox regression analysis demonstrated that 18-gene model risk score was independent of clinical prognostic factors. We identified four genes whose mutations were closely to UM patients' prognosis or risk score. We also explored the relationship between copy number variation and risk score and found that high risk group showed more chromosome aberrations than low risk group. Gene Set Enrichment Analysis (GSEA) analysis showed that the different biological pathways and functions between low and high risk group. In summary, our findings constructed an 18-gene signature for estimating overall survival (OS) of UM. Patients were categorized into two subtypes based on the risk score and we found that high risk group showed more chromosome aberrations than low risk group.

Expression and clinical significance of S100 family genes in patients with melanoma

Genes in the S100 family are abnormally expressed in a variety of tumor cells and are associated with clinical pathology, but their prognostic value in melanoma patients has not yet been fully elucidated. In this study, we extracted and profiled S100 family mRNA expression data and corresponding clinical data from the Gene Expression Omnibus database to analyze how expression of these genes correlates with clinical pathology. Compared with normal skin, S100A1, S100A13, and S100B were expressed at significantly higher levels in melanoma samples. S100A2, S100A7, S100A8, S100A9, S100A10, S100A11, and S100P were all highly expressed in primary melanoma samples but were expressed at low levels in metastatic melanoma, and all of these genes were strongly correlated with each other (P<0.001). We found the expression of these S100 family genes to be significantly correlated with both lymphatic and distant melanoma metastasis, as well as with American Joint Committee on Cancer grade but not with Clark’s grade, age, or sex. This suggests that expression of these genes may be related to the degree of tumor invasion. Although further validation through basic and clinical trials is needed, our results suggest that the S100 family genes have the potential to play an important role in the diagnosis of melanoma. S100 expression may be related to tumor invasion and may facilitate the early diagnosis of melanoma, allowing for a more accurate prognosis. Targeted S100 therapies are also potentially viable strategies in the context of melanoma.

Prognostic values of S100 family members in ovarian cancer patients

Objective

Exhibiting high consistence in sequence and structure, S100 family members are interchangeable in function and they show a wide spectrum of biological processes, including proliferation, apoptosis, migration, inflammation and differentiation and the like. While the prognostic value of each individual S100 in ovarian cancer is still elusive. In current study, we investigated the prognostic value of S100 family members in the ovarian cancer.

Methods

We used the Kaplan Meier plotter (KM plotter) database, in which updated gene expression data and survival information are from 1657 ovarian cancer patients, to assess the relevance of individual S100 family mRNA expression to overall survival in various ovarian cancer subtypes and different clinicopathological features.

Results

It was found that high expression of S100A2 (HR = 1.18, 95%CI: 1.04–1.34, P = 0.012), S100A7A (HR = 1.3, 95%CI: 1.04–1.63, P = 0.02),S100A10 (HR = 1.2, 95%CI: 1.05–1.38, P = 0.0087),and S100A16 (HR = 1.23, 95%CI: 1–1.51, P = 0.052) were significantly correlated with worse OS in all ovarian cancer patients, while the expression of S100A1 (HR = 0.87, 95%CI: 0.77–0.99, P = 0.039), S100A3 (HR = 0.83, 95%CI: 0.71–0.96, P = 0.0011), S100A5 (HR = 0.84, 95%CI: 0.73–0.97, P = 0.017), S100A6 (HR = 0.84, 95%CI: 0.72–0.98, P = 0.024), S100A13 (HR = 0.85, 95%CI:0.75–0.97, P = 0.014) and S100G (HR = 0.86, 95%CI: 0.74–0.99, P = 0.041) were associated with better prognosis. Furthermore, we assessed the prognostic value of S100 expression in different subtypes and the clinicopathological features, including pathological grades, clinical stages and TP53 mutation status, of ovarian cancer patients.

Conclusion

Comprehensive understanding of the S100 family members may have guiding significance for the diagnosis and outcome of ovarian cancer patients.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5170-3) contains supplementary material, which is available to authorized users.

Overexpression of S100A13 protein is associated with tumor angiogenesis and poor survival in patients with early-stage non-small cell lung cancer

Background

S100A13 plays a key role in tumor growth and metastasis. The purpose of this study was to investigate the prognostic significance of S100A13 expression, microvessel density (MVD), and survival in early stage non‐small cell lung cancer (NSCLC).

Methods

In silico analysis was performed to determine the associations between S100A13 and NSCLC. The data of 82 patients with early‐stage NSCLC who underwent radical resection were evaluated. Paraffin‐embedded tumor specimens were stained with S100A13 and CD31 (a specific endothelial marker) using immunohistochemical methods. Prognostic significance was assessed by univariate and multivariate analyses.

Results

S100A13 messenger RNA was overexpressed in NSCLC, especially in advanced stage. Of the 82 NSCLC specimens examined, 37 (45.1%) cases exhibited S100A13 overexpression and 31 (37.8%) showed high MVD. Univariate analysis indicated that gender, age, smoking status, histology type, tumor differentiation, and T stage were not significantly associated with prognosis. However, the overall and disease‐free survival rates of patients with S100A13 overexpression and high MVD were significantly lower than in the remaining cases. Multivariate analysis demonstrated that only S100A13 overexpression was an independent factor for poor prognosis in early‐stage NSCLC. Statistical analysis demonstrated that the MVD was significantly higher in tumors with high (67.6%, 25/37) compared to low S100A13 expression (13.3%, 6/45) (P < 0.01).

Conclusions

High S100A13 expression is closely associated with high intratumoral angiogenesis and poor prognosis in patients with stage I NSCLC. Immunohistochemical evaluation of S100A13 expression, along with an examination of the perioperative extent of angiolymphatic invasion, has value for predicting prognosis.

Thrombus Formation and Propagation in the Onset of Cardiovascular Events

Ischemic cardiovascular disease is a major cause of morbidity and mortality worldwide and thrombus formation on disrupted atherosclerotic plaques is considered to trigger its onset. Although the activation of platelets and coagulation pathways has been investigated intensively, the mechanisms of thrombus formation on disrupted plaques have not been understood in detail. Platelets are thought to play a central role in the formation of arterial thrombus because of rapid flow conditions; however, thrombus that develops on disrupted plaques consistently includes large amounts of fibrin in addition to aggregated platelets. While, thrombus does not always become large enough to completely occlude the vascular lumen, indicating that the propagation of thrombus is also critical for the onset of cardiovascular events. Various factors, such as vascular wall thrombogenicity, altered blood flow and imbalanced blood hemostasis, modulate thrombus formation and propagation on disrupted plaques. Pathological findings derived from humans and experimental animal models of atherothrombosis have identified important factors that affect thrombus formation and propagation, namely platelets, extrinsic and intrinsic coagulation factors, proinflammatory factors, plaque hypoxia and blood flow alteration. These findings might provide insight into the mechanisms of thrombus formation and propagation on disrupted plaques that lead to the onset of cardiovascular events.

Generation of a double binary transgenic zebrafish model to study myeloid gene regulation in response to oncogene activation in melanocytes

A complex network of inflammatory genes is closely linked to somatic cell transformation and malignant disease. Immune cells and their associated molecules are responsible for detecting and eliminating cancer cells as they establish themselves as the precursors of a tumour. By the time a patient has a detectable solid tumour, cancer cells have escaped the initial immune response mechanisms. Here, we describe the development of a double binary zebrafish model that enables regulatory programming of the myeloid cells as they respond to oncogene-activated melanocytes to be explored, focussing on the initial phase when cells become the precursors of cancer. A hormone-inducible binary system allows for temporal control of expression of different Ras oncogenes (NRasQ61K, HRasG12V and KRasG12V) in melanocytes, leading to proliferation and changes in morphology of the melanocytes. This model was coupled to binary cell-specific biotagging models allowing in vivo biotinylation and subsequent isolation of macrophage or neutrophil nuclei for regulatory profiling of their active transcriptomes. Nuclear transcriptional profiling of neutrophils, performed as they respond to the earliest precursors of melanoma in vivo, revealed an intricate landscape of regulatory factors that may promote progression to melanoma, including Serpinb1l4, Fgf1, Fgf6, Cathepsin H, Galectin 1 and Galectin 3. The model presented here provides a powerful platform to study the myeloid response to the earliest precursors of melanoma.

Emerging Biomarkers in Cutaneous Melanoma

Earlier identification of aggressive melanoma remains a goal in the field of melanoma research. With new targeted and immune therapies that have revolutionized the care of patients with melanoma, the ability to predict progression and monitor or predict response to therapy has become the new focus of research into biomarkers in melanoma. In this review, promising biomarkers are highlighted. These biomarkers have been used to diagnose melanoma as well as predict progression to advanced disease and response to therapy. The biomarkers take various forms, including protein expression at the level of tissue, genetic mutations of cancer cells, and detection of circulating DNA. First, a brief description is provided about the conventional tissue markers used to stage melanoma, including tumor depth. Next, protein biomarkers, which provide both diagnostic and prognostic information, are described. This is followed by a discussion of important genetic mutations, microRNA, and epigenetic modifications that can provide therapeutic and prognostic material. Finally, emerging serologic biomarkers are reviewed, including circulating melanoma cells and exosomes. Overall the goal is to identify biomarkers that aid in the earlier identification and improved treatment of aggressive melanoma.

Retrospective Proteomic Screening of 100 Breast Cancer Tissues

The present investigation has been conducted on one hundred tissue fragments of breast cancer, collected and immediately cryopreserved following the surgical resection. The specimens were selected from patients with invasive ductal carcinoma of the breast, the most frequent and potentially aggressive type of mammary cancer, with the objective to increase the knowledge of breast cancer molecular markers potentially useful for clinical applications. The proteomic screening; by 2D-IPG and mass spectrometry; allowed us to identify two main classes of protein clusters: proteins expressed ubiquitously at high levels in all patients; and proteins expressed sporadically among the same patients. Within the group of ubiquitous proteins, glycolytic enzymes and proteins with anti-apoptotic activity were predominant. Among the sporadic ones, proteins involved in cell motility, molecular chaperones and proteins involved in the detoxification appeared prevalent. The data of the present study indicates that the primary tumor growth is reasonably supported by concurrent events: the inhibition of apoptosis and stimulation of cellular proliferation, and the increased expression of glycolytic enzymes with multiple functions. The second phase of the evolution of the tumor can be prematurely scheduled by the occasional presence of proteins involved in cell motility and in the defenses of the oxidative stress. We suggest that this approach on large-scale 2D-IPG proteomics of breast cancer is currently a valid tool that offers the opportunity to evaluate on the same assay the presence and recurrence of individual proteins, their isoforms and short forms, to be proposed as prognostic indicators and susceptibility to metastasis in patients operated on for invasive ductal carcinoma of the breast.

The association between S100A13 and HMGA1 in the modulation of thyroid cancer proliferation and invasion

BACKGROUND

S100A13 and high mobility group A (HMGA1) are known to play essential roles in the carcinogenesis and progression of cancer. However, the correlation between S100A13 and HMGA1 during cancer progression is not yet well understood. In this study, we determined the effects of S100A13 on HMGA1 expression in thyroid cancer cells and examined the role of HMGA1 in thyroid cancer progression.

METHODS

Stable ectopic S100A13 expression TT cellular proliferation was evaluated by nude mice xenografts assays. The effect of lentivirus-mediated S100A13 knockdown on thyroid cancer cellular oncogenic properties were evaluated by MTT, colony formation assays and transwell assays in TPC1 and SW579 cells. The effect of siRNA-mediated HMGA1 knockdown on thyroid cancer cellular proliferation and invasion were evaluated by MTT, colony formation assays and transwell assays. The tissue microarray was performed to investigate the correlation between S100A13 and HMGA1 expression in tumor tissues.

RESULTS

The ectopic expression of S100A13 could increase tumor growth in a TT cell xenograft mouse model. Moreover, lentivirus-mediated S100A13 knockdown led to the inhibition of cellular oncogenic properties in thyroid cancer cells, and HMGA1 was found to be involved in the effect of S100A13 on thyroid cancer growth and invasion. Furthermore, siRNA-mediated HMGA1 knockdown was proved to inhibit the growth of TPC1 cells and invasive abilities of SW579 cells. Clinically, it was revealed that both S100A13 and HMGA1 showed a higher expression levels in thyroid cancer cases compared with those in matched normal thyroid cases (P = 0.007 and P = 0.000); S100A13 and HMGA1 expressions were identified to be positively correlated (P = 0.004, R = 0.316) when analyzed regardless of thyroid cancer types.

CONCLUSIONS

This is the first report for the association between HMGA1 and S100A13 expression in the modulation of thyroid cancer growth and invasion. Those results would provide an essential insight into the effect of S100A13 on carcinogenesis of thyroid tumor, rending S100A13 to be potential biological marker for the diagnosis of thyroid cancer.

Vascular Smooth Muscle Cells Stimulate Platelets and Facilitate Thrombus Formation through Platelet CLEC-2: Implications in Atherothrombosis

The platelet receptor CLEC-2 is involved in thrombosis/hemostasis, but its ligand, podoplanin, is expressed only in advanced atherosclerotic lesions. We investigated CLEC-2 ligands in vessel walls. Recombinant CLEC-2 bound to early atherosclerotic lesions and normal arterial walls, co-localizing with vascular smooth muscle cells (VSMCs). Flow cytometry and immunocytochemistry showed that recombinant CLEC-2, but not an anti-podoplanin antibody, bound to VSMCs, suggesting that CLEC-2 ligands other than podoplanin are present in VSMCs. VSMCs stimulated platelet granule release and supported thrombus formation under flow, dependent on CLEC-2. The time to occlusion in a FeCl3-induced animal thrombosis model was significantly prolonged in the absence of CLEC-2. Because the internal elastic lamina was lacerated in our FeCl3-induced model, we assume that the interaction between CLEC-2 and its ligands in VSMCs induces thrombus formation. Protein arrays and Biacore analysis were used to identify S100A13 as a CLEC-2 ligand in VSMCs. However, S100A13 is not responsible for the above-described VSMC-induced platelet activation, because S100A13 is not expressed on the surface of normal VSMCs. S100A13 was released upon oxidative stress and expressed in the luminal area of atherosclerotic lesions. Suspended S100A13 did not activate platelets, but immobilized S100A13 significantly increased thrombus formation on collagen-coated surfaces. Taken together, we proposed that VSMCs stimulate platelets through CLEC-2, possibly leading to thrombus formation after plaque erosion and stent implantation, where VSMCs are exposed to blood flow. Furthermore, we identified S100A13 as one of the ligands on VSMCs.

The S100 proteins in epidermis: Topology and function

BACKGROUND

S100 proteins are small calcium binding proteins encoded by genes located in the epidermal differentiation complex (EDC). Differently to other proteins encoded by EDC genes, which are indispensable for normal epidermal differentiation, the role of S100 proteins in the epidermis remains largely unknown.

SCOPE OF REVIEW

Particular S100 proteins differ in their distribution in epidermal layers, skin appendages, melanocytes and Langerhans cells. Taking into account that each epidermal component consists of specialized cells with well-defined functions, such differential distribution may be indicative of the function of a given S100 protein. We used this criterion together with the survey of the current experimental data pertinent to epidermis to provide a fairly comprehensive view on the possible function of individual S100 proteins in this tissue.

MAJOR CONCLUSIONS

S100 proteins are differently expressed and, despite extensive structural homology, perform diverse functions in the epidermis. Certain S100 proteins probably ensure constant epidermal renewal and support wound healing while others act in epidermal differentiation or have a protective role. As their expression is differently affected in various skin pathologies, particular S100 proteins could be valuable diagnostic markers.

GENERAL SIGNIFICANCE

S100 proteins seem to be important although not yet fully recognized epidermal constituents. Better understanding of their role in the epidermis might be helpful in designing therapies to various skin diseases.

A multiplexed, targeted mass spectrometry assay of the S100 protein family uncovers the isoform-specific expression in thyroid tumours

Background

Mounting evidence demonstrates a causal role for S100 proteins in tumourigenesis and several S100 isoforms have shown utility as biomarkers of several types of cancer. The S100 family is comprised of 21 small isoforms, many of them implicated in important cellular functions such as proliferation, motility and survival. Furthermore, in vivo experiments have proven the role of S100 proteins in tumour growth and disease progression, while other studies have shown their prognostic value and involvement in resistance to chemotherapy drugs. Taken together, all these aspects highlight S100 proteins as potential therapeutic targets and as a promising panel of cancer biomarkers. In this work, we have developed a mass spectrometry (MS)-based method for the multiplexed and specific analysis of the entire S100 protein family in tumour tissues and have applied it to investigate the expression of S100 isoforms in the context of thyroid cancer, the main endocrine malignancy.

Methods

Selected Reaction Monitoring (SRM)-MS and stable isotope labelling/label-free analysis were employed to investigate the expression of the 21 S100 protein isoforms in thyroid tissue samples. Specimens included 9 normal thyroid tissues and 27 tumour tissues consisting of 9 follicular adenomas (FA), 8 follicular carcinomas (FTC) and 10 papillary carcinomas (PTC).

Results

The multiplexed and targeted mass spectrometry method led to the detection of eleven S100 protein isoforms across all tissues. Label- and label-free analyses showed the same significant differences and results were confirmed by western blot. S100A6, S100A11 and its putative interaction partner annexin A1 showed the highest overexpression in PTC compared to normal thyroid. S100A13 was also elevated in PTC. Reduced S100A4 expression was observed in FA compared to all other tissues. FA and FTC showed reduction of S100A10 and annexin A2 expression.

Conclusions

Targeted mass spectrometry allows the multiplexed and specific analysis of S100 protein isoforms in tumour tissue specimens. It revealed S100A13 as a novel candidate PTC biomarker. Results show that S100A6, S100A11 and Annexin A1 could help discriminate follicular and papillary tumours. The diagnostic and functional significance of S100A4 and S100A10 reduction in follicular tumours requires further investigation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1217-x) contains supplementary material, which is available to authorized users.

Microvessel density, lymphovascular density, and lymphovascular invasion in primary cutaneous melanoma-correlation with histopathologic prognosticators and BRAF status

The relationship between microvessel density (MVD), lymphovascular density (LVD), and lymphovascular invasion (LVI) in primary cutaneous melanoma (PCM) remains unclear. Given this, a total of 102 PCMs were assessed for MVD (vascular endothelial growth factor receptor 2 and Endocan), LVD (D2-40), and LVI (immunostaining with D2-40/S-100 and hematoxylin and eosin); tumoral S-100A13, vascular endothelial growth factor receptor 2, and Endocan; and BRAF status. LVD was associated with MVD (P = .01). MVD was higher in PCMs with depth greater than or equal to 2 mm and ulceration (P = .04, .05), whereas LVD was higher in PCMs with depth greater than or equal to 2 mm and mitoses (P = .03, .02). After adjusting for MVD and LVD, only ulceration was associated with LVI (P < .02). A BRAF mutation was seen in 30.4% cases, and when present, both LVD and host response (P = .0008 and .04, respectively) were significantly associated with MVD. Immunostaining with S-100A13 was noted in 99% of cases and a significant association noted only with ulceration (P = .05). Immunostaining increased LVI positivity (46.5% versus 4.9% by hematoxylin and eosin, P < .0001). MVD and LVD are not associated with LVI, appear to be closely related with each other, and are associated with select markers of poor prognosticative value. The association between a host response and LVD and MVD in PCMs with a BRAF mutation suggests that they exhibit potential for strategizing immunotherapies.

Detection of recurrent alternative splicing switches in tumor samples reveals novel signatures of cancer

The determination of the alternative splicing isoforms expressed in cancer is fundamental for the development of tumor-specific molecular targets for prognosis and therapy, but it is hindered by the heterogeneity of tumors and the variability across patients. We developed a new computational method, robust to biological and technical variability, which identifies significant transcript isoform changes across multiple samples. We applied this method to more than 4000 samples from the The Cancer Genome Atlas project to obtain novel splicing signatures that are predictive for nine different cancer types, and find a specific signature for basal-like breast tumors involving the tumor-driver CTNND1. Additionally, our method identifies 244 isoform switches, for which the change occurs in the most abundant transcript. Some of these switches occur in known tumor drivers, including PPARG, CCND3, RALGDS, MITF, PRDM1, ABI1 and MYH11, for which the switch implies a change in the protein product. Moreover, some of the switches cannot be described with simple splicing events. Surprisingly, isoform switches are independent of somatic mutations, except for the tumor-suppressor FBLN2 and the oncogene MYH11. Our method reveals novel signatures of cancer in terms of transcript isoforms specifically expressed in tumors, providing novel potential molecular targets for prognosis and therapy. Data and software are available at: http://dx.doi.org/10.6084/m9.figshare.1061917 and https://bitbucket.org/regulatorygenomicsupf/iso-ktsp.

The receptor for advanced glycation end products influences the expression of its S100 protein ligands in melanoma tumors

Recent studies have suggested that the receptor for advanced glycation end products (RAGE) participates in melanoma progression by promoting tumor growth. However, the mechanisms of RAGE activation in melanoma tumors are not clearly understood. To get deeper insights into these mechanisms, we transfected a melanoma cell line, which was established from a human melanoma primary tumor, with RAGE, and studied the effect of RAGE overexpression on cell proliferation and migration in vitro. We observed that overexpression of RAGE in these cells not only resulted in significantly increased migration rates compared to control cells, but also in decreased proliferation rates (Meghnani et al., 2014). In the present study, we compared the growth of xenograft tumors established from RAGE overexpressing WM115 cells, to that of control cells. We observed that when implanted in mice, RAGE overexpressing cells generated tumors faster than control cells. Analysis of protein tumor extracts showed increased levels of the RAGE ligands S100B, S100A2, S100A4, S100A6 and S100A10 in RAGE overexpressing tumors compared to control tumors. We show that the tumor growth was significantly reduced when the mice were treated with anti-RAGE antibodies, suggesting that RAGE, and probably several S100 proteins, were involved in tumor growth. We further demonstrate that the anti-RAGE antibody treatment significantly enhanced the efficacy of the alkylating drug dacarbazine in reducing the growth rate of RAGE overexpressing tumors.

Interaction of S100A13 with C2 domain of receptor for advanced glycation end products (RAGE)

S100A13 is involved in several key biological functions like angiogenesis, tumor formation and cell apoptosis. It is a homodimeric protein that belongs to the S100 protein family. S100A13 is co-expressed with acidic fibroblast growth factor (FGF1) and interleukin-1α which are key angiogenesis inducers. The S100 proteins have been shown to be involved in several cellular functions such as calcium homeostasis, cell growth and differentiation dynamic of cytoskeleton. Its biological functions are mainly mediated through the receptor for advanced glycation end products (RAGE) signaling. RAGE is involved in inflammatory processes and is associated with diabetic complications, tumor outgrowth, and neurodegenerative disorders. RAGE induces cellular signaling upon binding of different ligands, such as S100 proteins, glycated proteins, and HMGB1. RAGE signaling is complex, and it depends on the cell type and concentration of the ligand. Molecular level interactions of RAGE and S100 proteins are useful to understand the RAGE signaling diversity. In this report we focus on the molecular level interactions of S100A13 and RAGE C2 domain. The binding between RAGE C2 and S100A13 is moderately strong (Kd~1.3μM). We have solved the solution structure of the S100A13-RAGE C2 complex and pronounce the interface regions in S100A13-RAGE C2 complex which are helpful for drug development of RAGE induced diseases.

Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance

BACKGROUND

Disseminated cutaneous malignant melanoma (CMM) is commonly unresponsive to standard chemotherapies, and there are as yet no predictive markers of therapy response.

METHODS

In the present study we collected fresh-frozen pretreatment lymph-node metastasis samples (n=14) from melanoma patients with differential response to dacarbazine (DTIC) or temozolomide (TMZ) chemotherapy, to identify proteins with an impact on treatment response. We performed quantitative protein profiling using tandem mass spectrometry and compared the proteome differences between responders (R) and non-responders (NR), matched for age, gender and histopathological type of CMM.

RESULTS

Biological pathway analyses showed several signalling pathways differing between R vs NR, including Rho signalling. Gene expression profiling data was available for a subset of the samples, and the results were compared with the proteomics data. Four proteins with differential expression between R and NR were selected for technical validation by immunoblotting (ISYNA1, F13A1, CSTB and S100A13), and CSTB and S100A13 were further validated on a larger sample set by immunohistochemistry (n=48). The calcium binding protein S100A13 was found to be significantly overexpressed in NR compared with R in all analyses performed.

CONCLUSIONS

Our results suggest that S100A13 is involved in CMM resistance to DTIC/TMZ.

S100 protein family in human cancer

S100 protein family has been implicated in multiple stages of tumorigenesis and progression. Among the S100 genes, 22 are clustered at chromosome locus 1q21, a region frequently rearranged in cancers. S100 protein possesses a wide range of intracellular and extracellular functions such as regulation of calcium homeostasis, cell proliferation, apoptosis, cell invasion and motility, cytoskeleton interactions, protein phosphorylation, regulation of transcriptional factors, autoimmunity, chemotaxis, inflammation and pluripotency. Many lines of evidence suggest that altered expression of S100 proteins was associated with tumor progression and prognosis. Therefore, S100 proteins might also represent potential tumor biomarkers and therapeutic targets. In this review, we summarize the evidence connecting S100 protein family and cancer and discuss the mechanisms by which S100 exerts its diverse functions.

Feasibility study on measuring selected proteins in malignant melanoma tissue by SRM quantification

Currently there are no clinically recognized molecular biomarkers for malignant melanoma (MM) for either diagnosing disease stage or measuring response to therapy. The aim of this feasibility study was to develop targeted selected reaction monitoring (SRM) assays for identifying candidate protein biomarkers in metastatic melanoma tissue lysate. In a pilot study applying the SRM assay, the tissue expression of nine selected proteins [complement 3 (C3), T-cell surface glycoprotein CD3 epsilon chain E (CD3E), dermatopontin, minichromosome maintenance complex component (MCM4), premelanosome protein (PMEL), S100 calcium binding protein A8 (S100A8), S100 calcium binding protein A13 (S100A13), transgelin-2 and S100B] was quantified in a small cohort of metastatic malignant melanoma patients. The SRM assay was developed using a TSQ Vantage triple quadrupole mass spectrometer that generated highly accurate peptide quantification. Repeated injection of internal standards spiked into matrix showed relative standard deviation (RSD) from 6% to 15%. All nine target proteins were identified in tumor lysate digests spiked with heavy peptide standards. The multiplex SRM peptide assay panel was then measured and quantified on a set of frozen MM tissue samples obtained from the Malignant Melanoma Biobank collected in Lund, Sweden. All nine proteins could be accurately quantified using the new SRM assay format. This study provides preliminary data on the heterogeneity of biomarker expression within MM patients. The S100B protein, which is clinically used as the pathology identifier of MM, was identified in 9 out of 10 MM tissue lysates. The use of the targeted SRM assay provides potential advancements in the diagnosis of MM that can aid in future assessments of disease in melanoma patients.

The immune system--a hidden treasure for biomarker discovery in cutaneous melanoma

This chapter describes how skin immune system (SIS) is specifically involved in the development of cutaneous melanoma. Local immune surveillance is presented as a complex process that comprises markers to be monitored in disease's evolution and in therapy. The ranking of tissue or soluble immune markers in a future panel of diagnostic/prognostic panel are evaluated. Taking into account the difficulties of cutaneous melanoma patients' management, this chapter shows the immune surveillance at the skin level, the conditions that favor the tumor escape from the immunological arm, the immune pattern of skin melanoma with diagnostic/prognostic relevance, the circulatory immune markers, and, last but not least, how immune markers are used in immune-therapy monitoring. The chapter cannot be exhaustive but will give the reader a glimpse of the complex immune network that lies within tumor escape and where to search for immune-therapeutical targets in skin melanoma.