Calcium-Binding Protein S100P Promotes Tumor Progression but Enhances Chemosensitivity in Breast Cancer

Soluble form of tumor necrosis factor-related apoptosis-inducing ligand interacts with S100P protein

Tumor Necrosis Factor (TNF)-Related Apoptosis-Inducing Ligand (TRAIL) is a therapeutically relevant protein belonging to the TNF superfamily. Both membrane-bound and soluble (sTRAIL) forms of TRAIL affect innate and adaptive immune responses. We recently showed that soluble TNF binds specific members of the S100 family of multifunctional calcium-binding proteins, leading to suppression of its cytotoxic activity (Int. J. Mol. Sci. 2022, 23(24), 15,956). To test the ability of S100 proteins to affect sTRAIL functioning, we used surface plasmon resonance spectroscopy, intrinsic fluorescence, chemical crosslinking, molecular modeling, site-directed mutagenesis, cytotoxicity assay, and bioinformatics to study interaction of human sTRAIL with human non-fused S100 proteins. Of the 21 S100 proteins examined, only S100P protein showed specific interaction with sTRAIL characterized by equilibrium dissociation constant, Kd, reaching (0.16 ± 0.07) μM. sTRAIL monomer binds dimeric S100P strictly in the presence of Ca2+, while sTRAIL trimer interacts with S100P dimer regardless of Ca2+. Site-directed mutagenesis confirmed involvement of the 'hinge' and C-terminal regions of S100P in the sTRAIL recognition, consistent with the structural modeling results. Bioinformatic analysis indicates dysregulation of TRAIL and S100P in various neoplasms. S100P lowers cytotoxicity of sTRAIL against human fibrosarcoma HT-1080 cells. The suppression of proapoptotic sTRAIL signaling by S100P protein may contribute to oncogenic effects of the latter.

Integrative analysis of genetic variability and functional traits in lung adenocarcinoma epithelial cells via single-cell RNA sequencing, GWAS, bayesian deconvolution, and machine learning

BACKGROUND

Lung adenocarcinoma remains a leading cause of cancer-related mortality worldwide, characterized by high genetic and cellular heterogeneity, especially within the tumor microenvironment.

OBJECTIVE

This study integrates single-cell RNA sequencing (scRNA-seq) with genome-wide association studies (GWAS) using Bayesian deconvolution and machine learning techniques to unravel the genetic and functional complexity of lung adenocarcinoma epithelial cells.

METHODS

We performed scRNA-seq and GWAS analysis to identify critical cell populations affected by genetic variations. Bayesian deconvolution and machine learning techniques were applied to investigate tumor progression, prognosis, and immune-epithelial cell interactions, particularly focusing on immune checkpoint markers such as PD-L1 and CTLA-4.

RESULTS

Our analysis highlights the importance of genes like SLC2A1, which regulates glucose metabolism and correlates with tumor invasiveness and poor prognosis. Immune-epithelial interactions suggest a suppressive tumor microenvironment, potentially hindering immune responses. Additionally, machine learning models identify core prognostic genes such as F12, GOLM1, and S100P, which are significantly associated with patient survival.

CONCLUSIONS

This comprehensive approach provides novel insights into lung adenocarcinoma biology, emphasizing the role of genetic and immune factors in tumor progression. The findings support the development of personalized therapeutic strategies targeting both tumor cells and the immune microenvironment.

RAGE and its ligands in breast cancer progression and metastasis

Introduction

Breast cancer is the most common form of cancer diagnosed worldwide and the leading cause of death in women globally, according to Globocan 2020. Hence, investigating novel pathways implicated in cancer progression and metastasis could lead to the development of targeted therapies and new treatment strategies in breast cancer. Recent studies reported an interplay between the receptor for advanced glycation end products (RAGE) and its ligands, S100 protein group, advanced glycation end products (AGEs) and high-mobility group box 1 protein (HMGB1) and breast cancer growth and metastasis.

Materials and methods

We used articles available in the NCBI website database PubMed to write this scoping review. The search words used were 'RAGE receptor' AND/OR 'breast cancer, RAGE ligands, glycation end products'. A total of 90 articles were included. We conducted a meta-analysis to assess the relationship between the RAGE rs1800624 polymorphism and breast cancer risk using fixed-effect or random-effect models to calculate odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs).

Results

RAGE upon activation by its ligands enhances downstream signaling pathways, contributing to breast cancer cells migration, growth, angiogenesis, metastasis, and drug resistance. In addition, studies have shown that RAGE and its ligands influence the way breast cancer cells interact with immune cells present in the tumor microenvironment (macrophages, fibroblasts), thus regulating it to promote tumor growth and metastasis.

Conclusion

Breast cancers with a high expression of RAGE are associated with poor prognosis. Targeting RAGE and its ligands impairs cell invasion and metastasis, showing promising potential for further research as potential prognostic biomarkers or targeted onco-therapeutics.

Breaking Barriers: Nucleic Acid Aptamers in Gastrointestinal (GI) Cancers Therapy

Conventional cancer therapies can have significant adverse effects as they are not targeted to cancer cells and may damage healthy cells. Single-stranded oligonucleotides assembled in a particular architecture, known as aptamers, enable them to attach selectively to target areas. Usually, they are created by Systematic Evolution of Ligand by Exponential enrichment (SELEX), and they go through a rigorous pharmacological revision process to change their therapeutic half-life, affinity, and specificity. They could thus offer a viable substitute for antibodies in the targeted cancer treatment market. Although aptamers can be a better choice in some situations, antibodies are still appropriate for many other uses. The technique of delivering aptamers is simple and reasonable, and the time needed to manufacture them is relatively brief. Aptamers do not require animals or an immune response to be produced, in contrast to antibodies. When used as a medication, aptamers can directly suppress tumor cells. As an alternative, they can be included in systems for targeted drug delivery that administer medications specifically to tumor cells while reducing toxicity to healthy cells. The most recent and cutting-edge methods for treating gastrointestinal (GI) tract cancer with aptamers will be covered in this review, with a focus on targeted therapy as a means of conquering resistance to traditional medicines.

Prognostic Value of S100 Family mRNA Expression in Hepatocellular Carcinoma

BACKGROUND/AIMS

 The S100 family contains more than 20 Ca2+-binding proteins that participate in numerous cellular biological processes. However, the prognostic value of individual S100s in hepatocellular carcinoma (HCC) remains unclear. Therefore, we comprehensively assessed the prognostic value of S100s in HCC.

MATERIALS AND METHODS

 The mRNA level of S100s in distinct types of cancer was analyzed through Oncomine. The clinical prognostic significance of each S100 was evaluated using Kaplan-Meier plotter and OncoLnc. The expression and mutation of S100s were determined through cBioPortal. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to predict the functions and pathways of S100s.

RESULTS

 The analyses revealed that, relative to normal tissues, liver cancer tissues showed aberrant mRNA expression of most S100s. In the survival analysis with Kaplan-Meier plotter, elevated expression levels of S100PBP, S100A2, S100A7, S100A10, and S100A13 were related to shorter overall survival (OS), whereas increased S100A5 expression was associated with longer OS. Moreover, results obtained using OncoLnc showed that increased expression levels of S100P, S100PBP, S100A13, S100A11, S100A10, and S100A2 were related to shorter OS. Thus, S100PBP, S100A13, S100A10, and S100A2 exhibited the same prognostic trend in the 2 databases. However, all S100 member gene mutational changes had no considerable prognostic value in OS and disease-free survival of HCC patients.

CONCLUSION

 Although the findings need to be further confirmed by experiments, they provide new evidence for the prognostic significance of the S100s in HCC.

Endogenous S100P-mediated autophagy regulates the chemosensitivity of leukemia cells through the p53/AMPK/mTOR pathway

Autophagy, a highly regulated lysosome-dependent catabolic pathway, has garnered increasing attention because of its role in leukemia resistance. Among the S100 family of small calcium-binding proteins, S100P is differentially expressed in various tumor cell lines, thereby influencing tumor occurrence, invasion, metastasis, and drug resistance. However, the relationship between S100P and autophagy in determining chemosensitivity in leukemia cells remains unexplored. Our investigation revealed a negative correlation between S100P expression and the clinical status in childhood leukemia, with its presence observed in HL-60 and Jurkat cell lines. Suppression of S100P expression resulted in increased cell proliferation and decreased chemosensitivity in leukemia cells, whereas enhancement of S100P expression inhibited cell proliferation and increased chemosensitivity. Additionally, S100P knockdown drastically promoted autophagy, which was subsequently suppressed by S100P upregulation. Moreover, the p53/AMP-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) pathway was found to be functionally associated with S100P-mediated autophagy. Knockdown of S100P expression led to a decrease in p53 and p-mTOR levels and an increase in p-AMPK expression, ultimately promoting autophagy. This effect was reversed by administration of Tenovin-6 (a p53 activator) and Compound C (an AMPK inhibitor). The findings of our in vivo experiments provide additional evidence supporting the aforementioned data. Specifically, S100P inhibition significantly enhanced the growth of HL-60 tumor xenografts and increased the expression of microtubule-associated protein 1 light chain 3 and p-AMPK in nude mice. Consequently, it can be concluded that S100P plays a regulatory role in the chemosensitivity of leukemia cells by modulating the p53/AMPK/mTOR pathway, which controls autophagy in leukemia cells.

Unveiling Gene Regulatory Networks That Characterize Difference of Molecular Interplays Between Gastric Cancer Drug Sensitive and Resistance Cell Lines

Gastric cancer is a leading cause of cancer-related deaths globally and chemotherapy is widely accepted as the standard treatment for gastric cancer. However, drug resistance in cancer cells poses a significant obstacle to the success of chemotherapy, limiting its effectiveness in treating gastric cancer. Although many studies have been conducted to unravel the mechanisms of acquired drug resistance, the existing studies were based on abnormalities of a single gene, that is, differential gene expression (DGE) analysis. Single gene-based analysis alone is insufficient to comprehensively understand the mechanisms of drug resistance in cancer cells, because the underlying processes of the mechanism involve perturbations of the molecular interactions. To uncover the mechanism of acquired gastric cancer drug resistance, we perform for identification of differentially regulated gene networks between drug-sensitive and drug-resistant cell lines. We develop a computational strategy for identifying phenotype-specific gene networks by extending the existing method, CIdrgn, that quantifies the dissimilarity of gene networks based on comprehensive information of network structure, that is, regulatory effect between genes, structure of edge, and expression levels of genes. To enhance the efficiency of identifying differentially regulated gene networks and improve the biological relevance of our findings, we integrate additional information and incorporate knowledge of network biology, such as hubness of genes and weighted adjacency matrices. The outstanding capabilities of the developed strategy are validated through Monte Carlo simulations. By using our strategy, we uncover gene regulatory networks that specifically capture the molecular interplays distinguishing drug-sensitive and drug-resistant profiles in gastric cancer. The reliability and significance of the identified drug-sensitive and resistance-specific gene networks, as well as their related markers, are verified through literature. Our analysis for differentially regulated gene network identification has the capacity to characterize the drug-sensitive and resistance-specific molecular interplays related to mechanisms of acquired drug resistance that cannot be revealed by analysis based solely on abnormalities of a single gene, for example, DGE analysis. Through our analysis and comprehensive examination of relevant literature, we suggest that targeting the suppressors of the identified drug-resistant markers, such as the Melanoma Antigen (MAGE) family, Trefoil Factor (TFF) family, and Ras-Associated Binding 25 (RAB25), while enhancing the expression of inducers of the drug sensitivity markers [e.g., Serum Amyloid A (SAA) family], could potentially reduce drug resistance and enhance the effectiveness of chemotherapy for gastric cancer. We expect that the developed strategy will serve as a useful tool for uncovering cancer-related phenotype-specific gene regulatory networks that provide essential clues for uncovering not only drug resistance mechanisms but also complex biological systems of cancer.

Quantitative Proteomics of Tissue-Infiltrating T Cells From CRC Patients Identified Lipocalin-2 Induces T-Cell Apoptosis and Promotes Tumor Cell Proliferation by Iron Efflux

T cells play the most pivotal roles in antitumor immunity; the T-cell proteome and the differentially expressed proteins in the tumor immune microenvironment have rarely been identified directly from the clinical samples, especially for tumors that lack effective immunotherapy targets, such as colorectal cancer (CRC). In this study, we analyzed the protein expression pattern of the infiltrating T cells isolated from CRC patients using quantitative proteomics. CD4+ and CD8+ T cells were isolated from clinical samples and labeled by tandem mass tag reagents, and the differentially expressed proteins were quantified by mass spectrometry. The T-cell proteome profiling revealed dysfunctions in these tumor-infiltrating T cells. Specifically, antitumor immunity was suppressed because of differentially expressed metal ion transporters and immunity regulators. For the first time, lipocalin-2 (LCN2) was shown to be significantly upregulated in CD4+ T cells. Quantitative proteomic analysis of LCN2-overexpressed Jurkat cells showed that LCN2 damaged T cells by changes in iron transport. LCN2 induced T-cell apoptosis by reducing cellular iron concentration; moreover, the iron that was transported to the tumor microenvironment aided tumor cell proliferation, promoting tumor development. Meanwhile, LCN2 also influenced tumor progression through immune cytokines and cholesterol metabolism. Our results demonstrated that LCN2 has immunosuppressive functions that can promote tumor development; therefore, it is a potential immunotherapy target for CRC.

Single-cell RNA-sequencing uncovers the dynamic changes of tumour immune microenvironment in advanced lung adenocarcinoma

BACKGROUND

The heterogeneity of lung adenocarcinoma (LUAD) plays a vital role in determining the development of cancer and therapeutic sensitivity and significantly hinders the clinical treatment of LUAD.

OBJECTIVE

To elucidate the cellular composition and reveal previously uncharacterised tumour microenvironment in LUAD using single-cell RNA-sequencing (scRNA-seq).

METHODS

Two scRNA-seq datasets with 106 829 high-quality cells from 34 patients including 11 normal, 9 early (stage I and II) and 14 advanced (stage III and IV) LUAD were integrated and clustered to explore diagnostic and therapeutic cell populations and their biomarkers for diverse stages of LUAD. Three independent bulk RNA-seq datasets were used to validate the results from scRNA-seq analysis. The expression of marker genes for specific cell types in early and advanced LUAD was verified by immunohistochemistry (IHC).

RESULTS

Comprehensive cluster analysis identified that S100P+ epithelial and SPP1+ macrophage, positively related to poor outcomes, were preferentially enriched in advanced stage. Although the accumulation of KLRB1+CD8+ T cell and IGHA1+/IGHG1+ plasma cell both significantly associated the favourable prognosis, we also found KLRB1+CD8+ T cell decreased in advanced stage while IGHA1+/IGHG1+ plasma cells were increased. Cell-cell communication analysis showed that SPP1+ macrophage could interact with most of CD8+ subclusters through SPP1-CD44 axis. Furthermore, based on three independent bulk RNA-seq datasets, we built risk model with nine marker genes for specific cell subtypes and conducted deconvolution analysis, both supporting our results from scRNA-seq data. We finally validated the expression of four marker genes in early and advanced LUAD by IHC.

CONCLUSION

Our analyses highlight the molecular dynamics of LUAD epithelial and microenvironment and provide new targets to improve LUAD therapy.

Breast cancer in young Indian women: factors, challenges in screening, and upcoming diagnostics

Breast cancer management for young Indian women are full of challenges. The National Cancer Registry Programme (NCRP) has predicted that nearly 2,30,000 cases of breast cancer will be reported annually by 2025; with a steady increase in cases of young women (< 45 years of age) with breast cancer. In this review, the available literature is evaluated to understand the various risk factors contributing to the rise in cases of breast cancer in young women in India. Further, the challenges that are faced by the technicians in early diagnosis (e.g., physiology of young breasts, limited trained professionals, and awareness among patients, and cost of the treatment) of breast cancer. This review also focuses on the upcoming diagnostics like serum biomarkers and nanosensors for the early identification of the disease. For better prognosis and to reduce the chances of disease reoccurrence and metastasis, it is important that the disease has to be identified at an early stage.

S100P as a potential biomarker for immunosuppressive microenvironment in pancreatic cancer: a bioinformatics analysis and in vitro study

BACKGROUND

Immunosuppression is a significant factor contributing to the poor prognosis of cancer. S100P, a member of the S100 protein family, has been implicated in various cancers. However, its role in the tumor microenvironment (TME) of pancreatic cancer remains unclear. This study aimed to investigate the potential impact of S100P on TME characteristics in patients with pancreatic cancer.

METHODS

Multiple data (including microarray, RNA-Seq, and scRNA-Seq) were obtained from public databases. The expression pattern of S100P was comprehensively evaluated in RNA-Seq data and validated in four different microarray datasets. Prognostic value was assessed through Kaplan-Meier plotter and Cox regression analyses. Immune infiltration levels were determined using the ESTIMATE and ssGSEA algorithms and validated at the single-cell level. Spearman correlation test was used to examine the correlation between S100P expression and immune checkpoint genes, and tumor mutation burden (TMB). DNA methylation analysis was performed to investigate the change in mRNA expression. Reverse transcription PCR (RT-PCR) and immunohistochemical (IHC) were utilized to validate the expression using five cell lines and 60 pancreatic cancer tissues.

RESULTS

This study found that S100P was differentially expressed in pancreatic cancer and was associated with poor prognosis (P < 0.05). Notably, S100P exhibited a significant negative-correlation with immune cell infiltration, particularly CD8 + T cells. Furthermore, a close association between S100P and immunotherapy was observed, as it strongly correlated with TMB and the expression levels of TIGIT, HAVCR2, CTLA4, and BTLA (P < 0.05). Intriguingly, higher S100P expression demonstrated a negative correlation with methylation levels (cg14323984, cg27027375, cg14900031, cg14140379, cg25083732, cg07210669, cg26233331, and cg22266967), which were associated with CD8 + T cells. In vitro RT-PCR validated upregulated S100P expression across all five pancreatic cancer cell lines, and IHC confirmed high S100P levels in pancreatic cancer tissues (P < 0.05).

CONCLUSION

These findings suggest that S100P could serve as a promising biomarker for immunosuppressive microenvironment, which may provide a novel therapeutic way for pancreatic cancer.

Recent Advances of Proteomics in Management of Acute Kidney Injury

Acute Kidney Injury (AKI) is currently recognized as a life-threatening disease, leading to an exponential increase in morbidity and mortality worldwide. At present, AKI is characterized by a significant increase in serum creatinine (SCr) levels, typically followed by a sudden drop in glomerulus filtration rate (GFR). Changes in urine output are usually associated with the renal inability to excrete urea and other nitrogenous waste products, causing extracellular volume and electrolyte imbalances. Several molecular mechanisms were proposed to be affiliated with AKI development and progression, ultimately involving renal epithelium tubular cell-cycle arrest, inflammation, mitochondrial dysfunction, the inability to recover and regenerate proximal tubules, and impaired endothelial function. Diagnosis and prognosis using state-of-the-art clinical markers are often late and provide poor outcomes at disease onset. Inappropriate clinical assessment is a strong disease contributor, actively driving progression towards end stage renal disease (ESRD). Proteins, as the main functional and structural unit of the cell, provide the opportunity to monitor the disease on a molecular level. Changes in the proteomic profiles are pivotal for the expression of molecular pathways and disease pathogenesis. Introduction of highly-sensitive and innovative technology enabled the discovery of novel biomarkers for improved risk stratification, better and more cost-effective medical care for the ill patients and advanced personalized medicine. In line with those strategies, this review provides and discusses the latest findings of proteomic-based biomarkers and their prospective clinical application for AKI management.

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Spatially resolved transcriptomics (SRT) enable the comprehensive characterization of transcriptomic profiles in the context of tissue microenvironments. Unveiling spatial transcriptional heterogeneity needs to effectively incorporate spatial information accounting for the substantial spatial correlation of expression measurements. Here, we develop a computational method, SpaSRL (spatially aware self-representation learning), which flexibly enhances and decodes spatial transcriptional signals to simultaneously achieve spatial domain detection and spatial functional genes identification. This novel tunable spatially aware strategy of SpaSRL not only balances spatial and transcriptional coherence for the two tasks, but also can transfer spatial correlation constraint between them based on a unified model. In addition, this joint analysis by SpaSRL deciphers accurate and fine-grained tissue structures and ensures the effective extraction of biologically informative genes underlying spatial architecture. We verified the superiority of SpaSRL on spatial domain detection, spatial functional genes identification and data denoising using multiple SRT datasets obtained by different platforms and tissue sections. Our results illustrate SpaSRL's utility in flexible integration of spatial information and novel discovery of biological insights from spatial transcriptomic datasets.

Systematic review of comparative transcriptomic studies of cellular resistance to genotoxic stress

The development of resistance by tumor cells to various types of therapy is a significant problem that decreases the effectiveness of oncology treatments. For more than two decades, comparative transcriptomic studies of tumor cells with different sensitivities to ionizing radiation and chemotherapeutic agents have been conducted in order to identify the causes and mechanisms underlying this phenomenon. However, the results of such studies have little in common and often contradict each other. We have assumed that a systematic analysis of a large number of such studies will provide new knowledge about the mechanisms of development of therapeutic resistance in tumor cells. Our comparison of 123 differentially expressed gene (DEG) lists published in 98 papers suggests a very low degree of consistency between the study results. Grouping the data by type of genotoxic agent and tumor type did not increase the similarity. The most frequently overexpressed genes were found to be those encoding the transport protein ABCB1 and the antiviral defense protein IFITM1. We put forward a hypothesis that the role played by the overexpression of the latter in the development of resistance may be associated not only with the stimulation of proliferation, but also with the limitation of exosomal communication and, as a result, with a decrease in the bystander effect. Among down regulated DEGs, BNIP3 was observed most frequently. The expression of BNIP3, together with BNIP3L, is often suppressed in cells resistant to non-platinum genotoxic chemotherapeutic agents, whereas it is increased in cells resistant to ionizing radiation. These observations are likely to be mediated by the binary effects of these gene products on survival, and regulation of apoptosis and autophagy. The combined data also show that even such obvious mechanisms as inhibition of apoptosis and increase of proliferation are not universal but show multidirectional changes.

Cromolyn chitosan nanoparticles reverse the DNA methylation of RASSF1A and p16 genes and mitigate DNMT1 and METTL3 expression in breast cancer cell line and tumor xenograft model in mice

BACKGROUND

Developing epigenetic drugs for breast cancer (BC) remains a novel therapeutic approach. Cromolyn is a mast cell stabilizer emerging as an anticancer drug; its encapsulation in chitosan nanoparticles (CSNPs) improves its effect and bioavailability. However, its effect on DNA and RNA methylation machineries has not been previously tackled.

METHODS

The possible anticancer effect of cromolyn CSNPs and its potential as an epigenetic drug was investigated in vitro using MCF-7 human BC cell line and in vivo using Ehrlich ascites carcinoma-xenograft model in mice symbolizing murine mammary adenocarcinoma. Mice were injected with a single dose of Ehrlich ascites carcinoma cells subcutaneously for the induction of tumor mass, and then randomized into three groups: control, cromolyn CSNPs (equivalent to 5 mg cromolyn/kg, i.p.) and plain CSNPs twice/week for 2 weeks.

RESULTS

Cromolyn CSNPs showed prominent anticancer effect in MCF-7 cells by reducing the cell viability percent and enhancing DNA damage in the comet assay demonstrating its apoptotic actions. Mechanistically, cromolyn CSNPs influenced potential epigenetic processes through mitigating DNA methyltransferase 1 (DNMT1) expression, reversing the hypermethylation pattern of the tumor suppressor RASSF1A and p16 genes and attenuating the expression of the RNA N⁶-methyladenosine writer, methyltransferase-like 3 (METTL3). Cromolyn CSNPs diminished ERK1/2 phosphorylation, a possible arm influencing DNMT1 expression. In vivo, cromolyn CSNPs lessened the tumor volume and halted DNMT1 and METTL3 expression in Ehrlich carcinoma mice.

CONCLUSIONS

Cromolyn CSNPs have the premise as an epigenetic drug through inhibiting ERK1/2 phosphorylation/DNMT1/DNA methylation and possibly impacting the RNA methylation machinery via mitigating METTL3 expression.

Aberrant calcium signalling downstream of mutations in TP53 and the PI3K/AKT pathway genes promotes disease progression and therapy resistance in triple negative breast cancer

Triple-negative breast cancer (TNBC) is characterized as an aggressive form of breast cancer (BC) associated with poor patient outcomes. For the majority of patients, there is a lack of approved targeted therapies. Therefore, chemotherapy remains a key treatment option for these patients, but significant issues around acquired resistance limit its efficacy. Thus, TNBC has an unmet need for new targeted personalized medicine approaches. Calcium (Ca²⁺) is a ubiquitous second messenger that is known to control a range of key cellular processes by mediating signalling transduction and gene transcription. Changes in Ca²⁺ through altered calcium channel expression or activity are known to promote tumorigenesis and treatment resistance in a range of cancers including BC. Emerging evidence shows that this is mediated by Ca²⁺ modulation, supporting the function of tumour suppressor genes (TSGs) and oncogenes. This review provides insight into the underlying alterations in calcium signalling and how it plays a key role in promoting disease progression and therapy resistance in TNBC which harbours mutations in tumour protein p53 (TP53) and the PI3K/AKT pathway.

Calcium-binding protein S100P is a new target gene of MACC1, drives colorectal cancer metastasis and serves as a prognostic biomarker

Background

The metastasis inducing gene MACC1 is a prognostic and predictive biomarker for metastasis in several cancers. Its mechanism of inducing metastasis includes the transcriptional control of other cancer-related target genes. Here, we investigate the interplay with the metastasis driver S100P in CRC progression.

Methods

MACC1-dependent S100P expression was analysed by qRT-PCR. The binding of MACC1 to the S100P promoter was determined by ChIP. Alterations in cell proliferation and motility were determined by functional in vitro assays. In vivo metastasis after intrasplenic transplantation was assessed by bioluminescence imaging and evaluation of tumour growth and liver metastasis. The prognostic value of S100P was determined in CRC patients by ROC-based Kaplan–Meier analyses.

Results

Expression of S100P and MACC1 correlated positively in CRC cells and colorectal tumours. MACC1 was found binding to the S100P promoter and induces its expression. The overexpression of S100P increased proliferation, migration and invasion in vitro and significantly induced liver metastasis in vivo. S100P expression was significantly elevated in metachronously metastasising CRC and was associated with shorter metastasis-free survival.

Conclusions

We identified S100P as a transcriptional target gene of MACC1. Expression of S100P increases the metastatic potential of CRC cells in vitro and in vivo, and serves as a prognostic biomarker for metastasis-free survival of CRC patients, emphasising novel therapeutic interventions targeting S100P.

S100A16 promotes acute kidney injury by activating HRD1-induced ubiquitination and degradation of GSK3β and CK1α

The pathogenesis of acute kidney injury (AKI) is associated with the activation of multiple signaling pathways, including Wnt/β-catenin signaling. However, the mechanism of Wnt/β-catenin pathway activation in renal interstitial fibroblasts during AKI is unclear. S100 calcium-binding protein A16 (S100A16), a new member of calcium-binding protein S100 family, is a multi-functional signaling factor involved in various pathogenies, including tumors, glycolipid metabolism disorder, and chronic kidney disease (CKD). We investigated the potential participation of S100A16 in Wnt/β-catenin pathway activation during AKI by subjecting wild-type (WT) and S100A16 knockout (S100A16+/−) mice to the ischemia–reperfusion injury (IRI), and revealed S100A16 upregulation in this model, in which knockout of S100A16 impeded the Wnt/β-catenin signaling pathway activation and recovered the expression of downstream hepatocyte growth factor (HGF). We also found that S100A16 was highly expressed in Platelet-derived growth factor receptor beta (PDGFRβ) positive renal fibroblasts in vivo. Consistently, in rat renal interstitial fibroblasts (NRK-49F cells), both hypoxia/reoxygenation and S100A16 overexpression exacerbated fibroblasts apoptosis and inhibited HGF secretion; whereas S100A16 knockdown or Wnt/β-catenin pathway inhibitor ICG-001 reversed these changes. Mechanistically, we showed that S100A16 promoted Wnt/β-catenin signaling activation via the ubiquitylation and degradation of β-catenin complex members, glycogen synthase kinase 3β (GSK3β) and casein kinase 1α (CK1α), mediated by E3 ubiquitin ligase, the HMG-CoA reductase degradation protein 1 (HRD1). Our study identified the S100A16 as a key regulator in the activation of Wnt/β-catenin signaling pathway in AKI.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

S100 Calcium-Binding Protein P Secreted from Megakaryocytes Promotes Osteoclast Maturation

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