Diagnostic importance of S100A9 and S100A12 in breast cancer

Elucidating the pan-oncologic landscape of S100A9: prognostic and therapeutic corollaries from an integrative bioinformatics and Mendelian randomization analysis

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

Serum protein profiling reveals an inflammation signature as a predictor of early breast cancer survival

BACKGROUND

Breast cancers exhibit considerable heterogeneity in their biology, immunology, and prognosis. Currently, no validated, serum protein-based tools are available to evaluate the prognosis of patients with early breast cancer.

METHODS

The study population consisted of 521 early-stage breast cancer patients with a median follow-up of 8.9 years. Additionally, 61 patients with breast fibroadenoma or atypical ductal hyperplasia were included as controls. We used a proximity extension assay to measure the preoperative serum levels of 92 proteins associated with inflammatory and immune response processes. The invasive cancers were randomly split into discovery (n = 413) and validation (n = 108) cohorts for the statistical analyses.

RESULTS

Using LASSO regression, we identified a nine-protein signature (CCL8, CCL23, CCL28, CSCL10, S100A12, IL10, IL10RB, STAMPB2, and TNFβ) that predicted various survival endpoints more accurately than traditional prognostic factors. In the time-dependent analyses, the prognostic power of the model remained rather stable over time. We also developed and validated a 17-protein model with the potential to differentiate benign breast lesions from malignant lesions (Wilcoxon p < 2.2*10- 16; AUC 0.94).

CONCLUSIONS

Inflammation and immunity-related serum proteins have the potential to rise above the classical prognostic factors of early-stage breast cancer. They may also help to distinguish benign from malignant breast lesions.

The role of surgical tissue injury and intraoperative sympathetic activation in postoperative immunosuppression after breast-conserving surgery versus mastectomy: a prospective observational study

BACKGROUND

Breast cancer is the second most common cause of death from cancer in women worldwide. Counterintuitively, large population-based retrospective trials report better survival after breast-conserving surgery (BCS) compared to mastectomy, corrected for tumour- and patient variables. More extensive surgical tissue injury and activation of the sympathetic nervous system by nociceptive stimuli are associated with immune suppression. We hypothesized that mastectomy causes a higher expression of plasma damage associated molecular patterns (DAMPs) and more intraoperative sympathetic activation which induce postoperative immune dysregulation. Immune suppression can lead to postoperative complications and affect tumour-free survival.

METHODS

In this prospective observational study, plasma DAMPs (HMGB1, HSP70, S100A8/A9 and S100A12), intraoperative sympathetic activation (Nociception Level (NOL) index from 0 to 100), and postoperative immune function (plasma cytokine concentrations and ex vivo cytokine production capacity) were compared in patients undergoing elective BCS (n = 20) versus mastectomy (n = 20).

RESULTS

Ex vivo cytokine production capacity of TNF, IL-6 and IL-1β was nearly absent in both groups one hour after surgery. Levels appeared recovered on postoperative day 3 (POD3), with significantly higher ex vivo production capacity of IL-1β after BCS (p = .041) compared to mastectomy. Plasma concentration of IL-6 was higher one hour after mastectomy (p = .045). Concentrations of plasma alarmins S100A8/A9 and S100A12 were significantly higher on POD3 after mastectomy (p = .003 and p = .041, respectively). Regression analysis showed a significantly lower percentage of NOL measurements ≤ 8 (absence of nociception) during mastectomy when corrected for norepinephrine equivalents (36% versus 45% respectively, p = .038). Percentage of NOL measurements ≤ 8 of all patients correlated with ex vivo cytokine production capacity of IL-1β and TNF on POD3 (r = .408; p = .011 and r = .500; p = .001, respectively).

CONCLUSIONS

This pilot study revealed substantial early postoperative immune suppression after BCS and mastectomy that appears to recover in the following days. Differences between BCS and mastectomy in release of DAMPs and intraoperative sympathetic activation could affect postoperative immune homeostasis and thereby contribute to the better survival reported after BCS in previous large population-based retrospective trials. These results endorse further exploration of (1) S100 alarmins as potential therapeutic targets in breast cancer surgery and (2) suppression of intraoperative sympathetic activation to substantiate the observed association with postoperative immune dysregulation.

Transcriptomics of Canine Inflammatory Mammary Cancer Treated with Empty Cowpea Mosaic Virus Implicates Neutrophils in Anti-Tumor Immunity

Canine inflammatory mammary cancer (IMC) is a highly aggressive and lethal cancer in dogs serving as a valuable animal model for its human counterpart, inflammatory breast cancer (IBC), both lacking effective therapies. Intratumoral immunotherapy (IT-IT) with empty cowpea mosaic virus (eCPMV) nanoparticles has shown promising results, demonstrating a reduction in tumor size, longer survival rates, and improved quality of life. This study compares the transcriptomic profiles of tumor samples from female dogs with IMC receiving eCPMV IT-IT and medical therapy (MT) versus MT alone. Transcriptomic analyses, gene expression profiles, signaling pathways, and cell type profiling of immune cell populations in samples from four eCPMV-treated dogs with IMC and four dogs with IMC treated with MT were evaluated using NanoString Technologies using a canine immune-oncology panel. Comparative analyses revealed 34 differentially expressed genes between treated and untreated samples. Five genes (CXCL8, S100A9, CCL20, IL6, and PTGS2) involved in neutrophil recruitment and activation were upregulated in the treated samples, linked to the IL17-signaling pathway. Cell type profiling showed a significant increase in neutrophil populations in the tumor microenvironment after eCPMV treatment. These findings highlight the role of neutrophils in the anti-tumor response mediated by eCPMV IT-IT and suggest eCPMV as a novel therapeutic approach for IBC/IMC.

Differential plasma proteomes of the patients with Opisthorchiasis viverrini and cholangiocarcinoma identify a polymeric immunoglobulin receptor as a potential biomarker

In Southeast Asian countries, nitrosamine compounds and the liver fluke Opisthorchis viverrini have long been identified as carcinogens for cholangiocarcinoma (CHCA). In order to effectively treat O. viverrini infections and prevent the development of CHCA, methods for disease detection are needed. This study aims to identify biomarkers for O. viverrini infection and CHCA. In the discovery phase, technical triplicates of five pooled plasma pools (10 plasma each) of healthy control subjects (noOVCCA), O. viverrini subjects (OV), and cholangiocarcinoma subjects (CCA), underwent solution-based digestion, with the label-free method, using a Thermo Scientific™ Q Exactive™ HF hybrid quadrupole-Orbitrap mass spectrometer and UltiMate 300 LC systems. The noOVCCA, OV, and CCA groups demonstrated different profiles and were clustered, as illustrated by PCA and heat map analysis. The STRING and reactome analysis showed that both OV and CCA groups up-regulated proteins targeting immune system-related proteins. Differential proteomic profiles, S100A9, and polymeric immunoglobulin receptor (PIGR) were specifically expressed in the CCA group. During the validation phase, another 50 plasma samples were validated via the PIGR sandwich ELISA. Using PIGR >1.559 ng/ml as a cut-off point, 78.00% sensitivity, 71.00% specificity, and AUC = 0.8216, were obtained. It is sufficient to differentially diagnose cholangiocarcinoma patients from healthy patients and those with Opisthorchiasis viverrini. Hence, in this study, PIGR was identified and validated as a potential biomarker for CHCA. Plasma PIGR is suggested for screening CHCA, especially in an endemic region of O. viverrini infection.

S100 Proteins as Novel Therapeutic Targets in Psoriasis and Other Autoimmune Diseases

Psoriasis is one of the most common inflammatory skin diseases affecting about 1-3% of the population. One of the characteristic abnormalities in psoriasis is the excessive production of antimicrobial peptides and proteins, which play an essential role in the pathogenesis of the disease. Antimicrobial peptides and proteins can be expressed differently in normal and diseased skin, reflecting their usefulness as diagnostic biomarkers. Moreover, due to their very important functions in innate immunity, members of host defense peptides and proteins are currently considered to be promising new therapeutic targets for many inflammatory diseases. Koebnerisin (S100A15) belongs to an S100 family of antimicrobial proteins, which constitute the multigenetic group of calcium-binding proteins involved in ion-dependent cellular functions and regulation of immune mechanisms. S100A15 was first discovered to be overexpressed in 'koebnerized' psoriatic skin, indicating its involvement in the disease phenotype and the same promising potential as a new therapeutic target. This review describes the involvement of antimicrobial peptides and proteins in inflammatory diseases' development and therapy. The discussion focuses on S100 proteins, especially koebnerisin, which may be involved in the underlying mechanism of the Köebner phenomenon in psoriasis, as well as other immune-mediated inflammatory diseases described in the last decade.

High-Throughput In Vitro Gene Expression Profile to Screen of Natural Herbals for Breast Cancer Treatment

Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer in women worldwide. Some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in breast cancer. However, the chemical composition and underlying anti-tumor mechanisms of TCM still need to be investigated. The primary aim of this study is to provide unique insights to screen the natural components for breast cancer therapy using high-throughput transcriptome analysis. Differentially expressed genes were identified based on two conditions: single samples and groups were classified according to their pharmaceutical effect. Subsequently, the sample treated with E. cochinchinensis Lour. generated the most significant DEGs set, including 1,459 DEGs, 805 upregulated and 654 downregulated. Similarly, group 3 treatment contained the most DEGs (414 DEGs, 311 upregulated and 103 downregulated). KEGG pathway analyses showed five significant pathways associated with the inflammatory and metastasis processes in cancer, which include the TNF, IL−17, NF-kappa B, MAPK signaling pathways, and transcriptional misregulation in cancer. Samples were classified into 13 groups based on their pharmaceutical effects. The results of the KEGG pathway analyses remained consistent with signal samples; group 3 presents a high significance. A total of 21 genes were significantly regulated in these five pathways, interestingly, IL6, TNFAIP3, and BRIC3 were enriched on at least two pathways, seven genes (FOSL1, S100A9, CXCL12, ID2, PRS6KA3, AREG, and DUSP6) have been reported as the target biomarkers and even the diagnostic tools in cancer therapy. In addition, weighted correlation network analysis (WGCNA) was used to identify 18 modules. Among them, blue and thistle2 were the most relevant modules. A total of 26 hub genes in blue and thistle2 modules were identified as the hub genes. In conclusion, we screened out three new TCM (R. communis L., E. cochinchinensis Lour., and B. fruticosa) that have the potential to develop natural drugs for breast cancer therapy, and obtained the therapeutic targets.

Comprehensive Profiling Reveals Distinct Microenvironment and Metabolism Characterization of Lung Adenocarcinoma

Lung adenocarcinoma has entered into an era of immunotherapy with the development of immune checkpoint inhibitors (ICIs). The identification of immune subtype is crucial to prolonging survival in patients. The tumor microenvironment (TME) and metabolism have a profound impact on prognosis and therapy. The majority of previous studies focused on only one aspect, while both of them are essential to the understanding of tumorigenesis and development. We hypothesized that lung adenocarcinoma can be stratified into immune subgroups with alterations in the TME infiltration. We aimed to explore the "TME-Metabolism-Risk" patterns in each subtypes and the mechanism behind. Glycolysis and cholesterol were selected for the analysis of metabolic states based on the first half of the study. Bioinformatic analysis was performed to investigate the transcriptomic and clinical data integrated by three lung adenocarcinoma cohorts (GSE30219, GSE31210, GSE37745, N = 415). The results were validated in an independent cohort (GSE50081, N = 127). In total, 415 lung adenocarcinoma samples were integrated and analyzed. Four major immune subtypes were indentified using bioinformatic analysis. Subtype NC1, characterized by a high level of glycolysis, with extremely low microenvironment cell infiltration. Subtype NC2, characterized by the "Silence" and "Cholesterol biosynthesis Predominant" metabolic states, with a middle degree infiltration of microenvironment cell. Subtype NC3, characterized by the lack of "Cholesterol biosynthesis Predominant" metabolic state, with abundant microenvironment cell infiltration. Subtype NC4, characterized by "Mixed" metabolic state, with a relatively low microenvironment cell infiltration. Least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were performed to calculate the risk of each sample, and we attempted to find out the potential immune escape mechanism in different subtypes. The result revealed that the lack of immune cells infiltration might contribute to the immune escape in subtypes NC1 and NC4. NC3 was characterized by the high expression of immune checkpoint molecules and fibroblasts. NC2 had defects in activation of innate immune cells. There existed an obviously survival advantage in subtype NC2. Gene set enrichment analysis (GSEA) and Gene Ontology analysis indicated that the PI3K-AKT-mTOR, TGF-β, MYC-related pathways might be correlated with this phenomenon. In addition, some differentially expressed genes (DEGs) were indentified in subtype NC3, which might be potential targets for survival phenotype transformation.

Identification of the prognostic value of immune gene signature and infiltrating immune cells for esophageal cancer patients

BACKGROUND

Esophageal cancer (ESCA) is one of the deadliest solid malignancies with worse survival rate worldwide. Here, we aimed to establish an immune-gene prognostic signature for predicting patients' survival and providing accurate targets for personalized therapy or immunotherapy.

METHODS

Gene expression profile of patients with ESCA were download from The Cancer Genome Atlas (TCGA) database (dataset 1: n = 159) and immune-related genes from the ImmPORT database. Dataset 1 was subdivided into two groups (dataset 2: n = 80; dataset 3: n = 79). Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature on the three datasets. TIMER and CIBERSORT analysis were used to evaluate the correlation between the prognostic signature and infiltrating immune cells.

RESULTS

We constructed a prognostic signature composed of six immune genes (HSPA6, S100A12, FABP3, DKK1, OSM and NR2F2). Kaplan-Meier curves validated the good predictive ability of the prognostic signature in datasets 1, 2 and 3 (P = 0.0034, P = 0.0081, and P = 0.0363, respectively). The area under the curve (AUC) of the ROC curves validated the predictive accuracy of the immune signature (AUCs = 0.757, 0.800, and 0.701, respectively). We also revealed the good prognostic value of the immune cells, including activated memory CD4 T cells, T follicular helper cells and monocytes. Potential target drugs, including Olopatadine and Amlexanox, were identified for clinical therapies to improve patients' survival outcomes.

CONCLUSION

Our study indicated that the immune-related prognostic signature could serve as a novel biomarker for predicting patients' prognosis and providing new immunotherapy targets in ESCA.

Clinical importance of S100A9 in osteosarcoma development and as a diagnostic marker and therapeutic target

Objective: S100A9 is a calcium- and zinc-binding molecule of S100 family. The aim of the study was to evaluate the role of S100A9 in osteosarcoma (OS) and its value as a diagnostic and therapeutic target in OS. Methods: Quantitative real-time polymerase chain reaction (qRT-PCR), immunohistochemistry and microdissection-based mRNA analysis were used to detect S100A9 mRNA and protein expression in OS and normal bone tissues and its potential as a diagnostic marker in OS. In vitro experiments with RNA interference were performed to evaluate the functional role of S100A9 and its potential as a therapeutic target in OS. Results: S100A9 mRNA levels were significantly higher in OS tissues than that of in normal bone tissues. Receiver operating characteristic curves showed that S100A9 could be a useful diagnostic marker in OS. In vitro data showed that inhibition of S100A9 decreased the proliferation and invasiveness of OS cells, and these findings were supported by microarray data. Conclusions: Assessment of S100A9 mRNA expression is a promising tool for the diagnosis of OS, and S100A9 may be a promising therapeutic target in OS.

Ca2+-Binding Proteins of the EF-Hand Superfamily: Diagnostic and Prognostic Biomarkers and Novel Therapeutic Targets

A multitude of Ca²⁺-sensor proteins containing the specific Ca²⁺-binding motif (helix-loop-helix, called EF-hand) are of major clinical relevance in a many human diseases. Measurements of troponin, the first intracellular Ca-sensor protein to be discovered, is nowadays the "gold standard" in the diagnosis of patients with acute coronary syndrome (ACS). Mutations have been identified in calmodulin and linked to inherited ventricular tachycardia and in patients affected by severe cardiac arrhythmias. Parvalbumin, when introduced into the diseased heart by gene therapy to increase contraction and relaxation speed, is considered to be a novel therapeutic strategy to combat heart failure. S100 proteins, the largest subgroup with the EF-hand protein family, are closely associated with cardiovascular diseases, various types of cancer, inflammation, and autoimmune pathologies. The intention of this review is to summarize the clinical importance of this protein family and their use as biomarkers and potential drug targets, which could help to improve the diagnosis of human diseases and identification of more selective therapeutic interventions.

Identification of an eight-gene signature for survival prediction for patients with hepatocellular carcinoma based on integrated bioinformatics analysis

Background

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related death worldwide. Despite recent advances in imaging techniques and therapeutic intervention for HCC, the low overall 5-year survival rate of HCC patients remains unsatisfactory. This study aims to find a gene signature to predict clinical outcomes in HCC.

Methods

Bioinformatics analysis including Cox’s regression analysis, Kaplan-Meier (KM) and receiver operating characteristic curve (ROC) analysis and the random survival forest algorithm were performed to mine the expression profiles of 553 hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public database.

Results

We selected a signature comprising eight protein-coding genes (DCAF13, FAM163A, GPR18, LRP10, PVRIG, S100A9, SGCB, and TNNI3K) in the training dataset (AUC = 0.77 at five years, n = 332). The signature stratified patients into high- and low-risk groups with significantly different survival in the training dataset (median 2.20 vs. 8.93 years, log-rank test P < 0.001) and in the test dataset (median 2.68 vs. 4.24 years, log-rank test P = 0.004, n = 221, GSE14520). Further multivariate Cox regression analysis showed that the signature was an independent prognostic factor for patients with HCC. Compared with TNM stage and another reported three-gene model, the signature displayed improved survival prediction power in entire dataset (AUC signature = 0.66 vs. AUC TNM = 0.64 vs. AUC gene model = 0.60, n = 553). Stratification analysis shows that it can be used as an auxiliary marker for many traditional staging models.

Conclusions

We constructed an eight-gene signature that can be a novel prognostic marker to predict the survival of HCC patients.

Isolation and Characterization of Serum Extracellular Vesicles (EVs) from Atlantic Salmon Infected with Piscirickettsia Salmonis

Secretion of extracellular vesicles (EVs) is a common feature of both eukaryotic and prokaryotic cells. Isolated EVs have been shown to contain different types of molecules, including proteins and nucleic acids, and are reported to be key players in intercellular communication. Little is known, however, of EV secretion in fish, or the effect of infection on EV release and content. In the present study, EVs were isolated from the serum of healthy and Piscirickettsia salmonis infected Atlantic salmon in order to evaluate the effect of infection on EV secretion. P. salmonis is facultative intracellular bacterium that causes a systemic infection disease in farmed salmonids. EVs isolated from both infected and non-infected fish had an average diameter of 230–300 nm, as confirmed by transmission electron microscopy, nanoparticle tracking, and flow cytometry. Mass spectrometry identified 180 proteins in serum EVs from both groups of fish. Interestingly, 35 unique proteins were identified in serum EVs isolated from the fish infected with P. salmonis. These unique proteins included proteasomes subunits, granulins, and major histocompatibility class I and II. Our results suggest that EV release could be part of a mechanism in which host stimulatory molecules are released from infected cells to promote an immune response.