S100A14 promotes progression and gemcitabine resistance in pancreatic cancer

Identification and validation of three potential biomarkers and immune microenvironment for in severe asthma in microarray and single-cell datasets

Objective: The aim of this study was to identify genetic biomarkers and cellular communications associated with severe asthma in microarray data sets and single cell data sets. The potential gene expression levels were verified in a mouse model of asthma.Methods: We identified differentially expressed genes from the microarray datasets (GSE130499 and GSE63142) of severe asthma, and then constructed models to screen the most relevant biomarkers to severe asthma by machine learning algorithms (LASSO and SVM-RFE), with further validation of the results by GSE43696. Single-cell datasets (GSE193816 and GSE227744) were identified for potential biomarker-specific expression and intercellular communication. Finally, The expression levels of potential biomarkers were verified with a mouse model of asthma.Results: The 73 genes were differentially expressed between severe asthma and normal control. LASSO and SVM-RFE recognized three genes BCL3, DDIT4 and S100A14 as biomarkers of severe asthma and had good diagnostic effect. Among them, BCL3 transcript level was down-regulated in severe asthma, while S100A14 and DDIT4 transcript levels were up-regulated. The transcript levels of the three genes were confirmed in the mouse model. Infiltration of neutrophils and mast cells were found to be increased in severe asthma and may be associated with bronchial epithelial cells through BMP and NRG signalingConclusions: We identified three differentially expressed genes (BCL3, DDIT4 and S100A14) of diagnostic significance that may be involved in the development of severe asthma and these gene expressions could be serviced as biomarker of severe asthma and investigating the function roles could bring new insights into the underlying mechanisms.

The crucial prognostic signaling pathways of pancreatic ductal adenocarcinoma were identified by single-cell and bulk RNA sequencing data

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with poor prognosis and high mortality. Although a large number of studies have explored its potential prognostic markers using traditional RNA sequencing (RNA-Seq) data, they have not achieved good prediction effect. In order to explore the possible prognostic signaling pathways leading to the difference in prognosis, we identified differentially expressed genes from one scRNA-seq cohort and four GEO cohorts, respectively. Then Cox and Lasso regression analysis showed that 12 genes were independent prognostic factors for PDAC. AUC and calibration curve analysis showed that the prognostic model had good discrimination and calibration. Compared with the low-risk group, the high-risk group had a higher proportion of gene mutations than the low-risk group. Immune infiltration analysis revealed differences in macrophages and monocytes between the two groups. Prognosis related genes were mainly distributed in fibroblasts, macrophages and type 2 ducts. The results of cell communication analysis showed that there was a strong communication between cancer-associated fibroblasts (CAF) and type 2 ductal cells, and collagen formation was the main interaction pathway.

A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma

Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumor cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analyzed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms.

Mediation of circ_0007142 on miR-128-3p/S100A14 pathway to stimulate the progression of cervical cancer

A previous study has confirmed the upregulation of circ_0007142 expression in CC. Here, we aimed to investigate the effect and mechanism of circ_0007142 in CC progression. The expression of circ_0007142, microRNA-128-3p (miR-128-3p), S100 calcium-binding protein A14 (S100A14), and epithelial mesenchymal transition (EMT)-related markers was measured by qRT-PCR and Western blot. Cell proliferative, migratory, and invasion abilities were evaluated using cell counting Kit-8, cell colony formation, 5-ethynyl-2'-deoxyuridine, and transwell assays, respectively. The interaction among circ_0007142, miR-128-3p and S100A14 was identified by dual-luciferase reporter and RNA immunoprecipitation assays. In vivo experiment was implemented to investigate the effect of circ_0007142 on tumor growth. CC tissues and cells displayed high expression of circ_0007142 and S100A14, and low expression of miR-128-3p in comparison to the controls. Knockdown of circ_0007142 resulted in the inhibition of cell proliferation, migration invasion, and EMT in vitro. In support, circ_0007142 deficiency hindered tumor growth and EMT in vivo. In rescue experiments, downregulation of miR-128-3p relieved circ_0007142 absence-mediated anticancer impacts. MiR-128-3p overexpression-induced inhibitory effects on cell growth and metastasis were attenuated by S100A14 overexpression. Importantly, circ_0007142 regulated S100A14 expression by sponging miR-128-3p. Circ_0007142 knockdown suppressed CC cell malignant behaviors by miR-128-3p/S100A14 pathway, providing a possible circRNA-targeted therapy for CC.

TAF2, within the TFIID complex, regulates the expression of a subset of protein-coding genes

TFIID, one of the general transcription factor (GTF), regulates transcriptional initiation of protein-coding genes through direct binding to promoter elements and subsequent recruitment of other GTFs and RNA polymerase II. Although generally required for most protein-coding genes, accumulated studies have also demonstrated promoter-specific functions for several TFIID subunits in gene activation. Here, we report that TBP-associated factor 2 (TAF2) specifically regulates TFIID binding to a small subset of protein-coding genes and is essential for cell growth of multiple cancer lines. Co-immunoprecipitation assays revealed that TAF2 may be sub-stoichiometrically associated with the TFIID complex, thus indicating a minor fraction of TAF2-containing TFIID in cells. Consistently, integrated genome-wide profiles show that TAF2 binds to and regulates only a small subset of protein-coding genes. Furthermore, through the use of an inducible TAF2 degradation system, our results reveal a reduction of TBP/TFIID binding to several ribosomal genes upon selective ablation of TAF2. In addition, depletion of TAF2, as well as the TAF2-regulated ribosomal protein genes RPL30 and RPL39, decreases ribosome assembly and global protein translation. Collectively, this study suggests that TAF2 within the TFIID complex is of functional importance for TBP/TFIID binding to and expression of a small subset of protein-coding genes, thus establishing a previously unappreciated promoter-selective function for TAF2.

Filter and Wrapper Stacking Ensemble (FWSE): a robust approach for reliable biomarker discovery in high-dimensional omics data

Selecting informative features, such as accurate biomarkers for disease diagnosis, prognosis and response to treatment, is an essential task in the field of bioinformatics. Medical data often contain thousands of features and identifying potential biomarkers is challenging due to small number of samples in the data, method dependence and non-reproducibility. This paper proposes a novel ensemble feature selection method, named Filter and Wrapper Stacking Ensemble (FWSE), to identify reproducible biomarkers from high-dimensional omics data. In FWSE, filter feature selection methods are run on numerous subsets of the data to eliminate irrelevant features, and then wrapper feature selection methods are applied to rank the top features. The method was validated on four high-dimensional medical datasets related to mental illnesses and cancer. The results indicate that the features selected by FWSE are stable and statistically more significant than the ones obtained by existing methods while also demonstrating biological relevance. Furthermore, FWSE is a generic method, applicable to various high-dimensional datasets in the fields of machine intelligence and bioinformatics.

The bioengineered and multifunctional nanoparticles in pancreatic cancer therapy: Bioresponisive nanostructures, phototherapy and targeted drug delivery

The multidisciplinary approaches in treatment of cancer appear to be essential in term of bringing benefits of several disciplines and their coordination in tumor elimination. Because of the biological and malignant features of cancer cells, they have ability of developing resistance to conventional therapies such as chemo- and radio-therapy. Pancreatic cancer (PC) is a malignant disease of gastrointestinal tract in which chemotherapy and radiotherapy are main tools in its treatment, and recently, nanocarriers have been emerged as promising structures in its therapy. The bioresponsive nanocarriers are able to respond to pH and redox, among others, in targeted delivery of cargo for specific treatment of PC. The loading drugs on the nanoparticles that can be synthetic or natural compounds, can help in more reduction in progression of PC through enhancing their intracellular accumulation in cancer cells. The encapsulation of genes in the nanoparticles can protect against degradation and promotes intracellular accumulation in tumor suppression. A new kind of therapy for cancer is phototherapy in which nanoparticles can stimulate both photothermal therapy and photodynamic therapy through hyperthermia and ROS overgeneration to trigger cell death in PC. Therefore, synergistic therapy of phototherapy with chemotherapy is performed in accelerating tumor suppression. One of the important functions of nanotechnology is selective targeting of PC cells in reducing side effects on normal cells. The nanostructures are capable of being surface functionalized with aptamers, proteins and antibodies to specifically target PC cells in suppressing their progression. Therefore, a specific therapy for PC is provided and future implications for diagnosis of PC is suggested.

New insight in urological cancer therapy: From epithelial-mesenchymal transition (EMT) to application of nano-biomaterials

A high number of cancer-related deaths (up to 90) are due to metastasis and simple definition of metastasis is new colony formation of tumor cells in a secondary site. In tumor cells, epithelial-mesenchymal transition (EMT) stimulates metastasis and invasion, and it is a common characteristic of malignant tumors. Prostate cancer, bladder cancer and renal cancer are three main types of urological tumors that their malignant and aggressive behaviors are due to abnormal proliferation and metastasis. EMT has been well-documented as a mechanism for promoting invasion of tumor cells and in the current review, a special attention is directed towards understanding role of EMT in malignancy, metastasis and therapy response of urological cancers. The invasion and metastatic characteristics of urological tumors enhance due to EMT induction and this is essential for ensuring survival and ability in developing new colonies in neighboring and distant tissues and organs. When EMT induction occurs, malignant behavior of tumor cells enhances and their tend in developing therapy resistance especially chemoresistance promotes that is one of the underlying reasons for therapy failure and patient death. The lncRNAs, microRNAs, eIF5A2, Notch-4 and hypoxia are among common modulators of EMT mechanism in urological tumors. Moreover, anti-tumor compounds such as metformin can be utilized in suppressing malignancy of urological tumors. Besides, genes and epigenetic factors modulating EMT mechanism can be therapeutically targeted for interfering malignancy of urological tumors. Nanomaterials are new emerging agents in urological cancer therapy that they can improve potential of current therapeutics by their targeted delivery to tumor site. The important hallmarks of urological cancers including growth, invasion and angiogenesis can be suppressed by cargo-loaded nanomaterials. Moreover, nanomaterials can improve chemotherapy potential in urological cancer elimination and by providing phototherapy, they mediate synergistic tumor suppression. The clinical application depends on development of biocompatible nanomaterials.

Comprehensive analysis of the prognosis of S100 family members and their relationship with tumor-infiltrating immune cells in human pancreatic adenocarcinoma

S100 family members (S100s) are small molecular EF hand calcium binding proteins and widely expressed in many tissues and organs. S100s are shown to be biomarkers of disease progression and prognosis in various types of cancers. Nevertheless, the expression patterns, function, and prognostic values of S100s and its association with tumor-infiltrating immune cells in pancreatic adenocarcinoma (PAAD) patients have not been systematically clarified. We explored the expression and roles of the entire 20 S100s in PAAD patients by using the following public databases: Oncomine, gene expression profiling interactive analysis, cBioPortal, Metascape, search tool for recurring instances of neighboring genes, Tumor IMmune Estimation Resource, and GeneMANIA. The S100A2/A3/A4/A6/A8/A9/A10/A11/A13/A14/A16/B/P mRNA expressions were significantly upregulated in PAAD patients. The mRNA expression of S100A3/A4/A5/A6/A10/A11/A14/A16/Z were significantly negatively related with the tumor stage in PAAD patients. We found that the S100A2/A3/A5/A10/A11/A14/A16 were significantly correlated with poor overall survival, whereas the increased levels of S100A1/B/G/Z were strongly associated with good overall survival. We found significant correlations among S100s and tumor-infiltrating immune cells. Cox proportional risk models revealed that B cells, Dendritic cells and S100A1/A5/A6/A8/A9/A13/A14 were significantly related with outcomes in PAAD patients. These results suggest that S100A2/A3/A10/A11/A14/A16 may serve as new diagnostic and prognostic biomarkers for PAAD patients and provide new clues for immunotherapy in PAAD patients.

Developing and validating a survival prediction model based on blood exosomal ceRNA network in patients with PAAD

BACKGROUND

Among the most lethal cancers, pancreatic adenocarcinoma (PAAD) is an essential component of digestive system malignancies that still lacks effective diagnosis and treatment methods. As exosomes and competing endogenous RNA (ceRNA) regulatory networks in tumors go deeper, we expect to construct a ceRNA regulatory network derived from blood exosomes of PAAD patients by bioinformatics methods and develop a survival prediction model based on it.

METHODS

Blood exosome sequencing data of PAAD patients and normal controls were downloaded from the exoRbase database, and the expression profiles of exosomal mRNA, lncRNA, and circRNA were differentially analyzed by R. The related mRNA, circRNA, lncRNA, and their corresponding miRNA prediction data were imported into Cytoscape software to visualize the ceRNA network. Then, we conducted GO and KEGG enrichment analysis of mRNA in the ceRNA network. Genes that express differently in pancreatic cancer tissues compared with normal tissues and associate with survival (P < 0.05) were determined as Hub genes by GEPIA. We identified optimal prognosis-related differentially expressed mRNAs (DEmRNAs) and generated a risk score model by performing univariate and multivariate Cox regression analyses.

RESULTS

205 DEmRNAs, 118 differentially expressed lncRNAs (DElncRNAs), and 98 differentially expressed circRNAs (DEcircRNAs) were screened out. We constructed the ceRNA network, and a total of 26 mRNA nodes, 7 lncRNA nodes, 6 circRNA nodes, and 16 miRNA nodes were identified. KEGG enrichment analysis showed that the DEmRNAs in the regulatory network were mainly enriched in Human papillomavirus infection, PI3K-Akt signaling pathway, Osteoclast differentiation, and ECM-receptor interaction. Next, six hub genes (S100A14, KRT8, KRT19, MAL2, MYO5B, PSCA) were determined through GEPIA. They all showed significantly increased expression in cancer tissues compared with control groups, and their high expression pointed to adverse survival. Two optimal prognostic-related DEmRNAs, MYO5B (HR = 1.41, P < 0.05) and PSCA (HR = 1.10, P < 0.05) were included to construct the survival prediction model.

CONCLUSION

In this study, we successfully constructed a ceRNA regulatory network in blood exosomes from PAAD patients and developed a two-gene survival prediction model that provided new targets which shall aid in diagnosing and treating PAAD.

Morphological and Molecular Responses of Lateolabrax maculatus Skeletal Muscle Cells to Different Temperatures

Temperature strongly modulates muscle development and growth in ectothermic teleosts; however, the underlying mechanisms remain largely unknown. In this study, primary cultures of skeletal muscle cells of Lateolabrax maculatus were conducted and reared at different temperatures (21, 25, and 28 °C) in both the proliferation and differentiation stages. CCK-8, EdU, wound scratch and nuclear fusion index assays revealed that the proliferation, myogenic differentiation, and migration processes of skeletal muscle cells were significantly accelerated as the temperature raises. Based on the GO, GSEA, and WGCNA, higher temperature (28 °C) induced genes involved in HSF1 activation, DNA replication, and ECM organization processes at the proliferation stage, as well as HSF1 activation, calcium activity regulation, myogenic differentiation, and myoblast fusion, and sarcomere assembly processes at the differentiation stage. In contrast, lower temperature (21 °C) increased the expression levels of genes associated with DNA damage, DNA repair and apoptosis processes at the proliferation stage, and cytokine signaling and neutrophil degranulation processes at the differentiation stage. Additionally, we screened several hub genes regulating myogenesis processes. Our results could facilitate the understanding of the regulatory mechanism of temperature on fish skeletal muscle growth and further contribute to utilizing rational management strategies and promoting organism growth and development.

Construction of immune-related signature and identification of S100A14 determining immune-suppressive microenvironment in pancreatic cancer

Pancreatic cancer (PC) is a highly lethal and aggressive disease with its incidence and mortality quite discouraging. A robust prognostic signature and novel biomarkers are urgently needed for accurate stratification of the patients and optimization of clinical decision-making. Since the critical role of immune microenvironment in the progression of PC, a prognostic signature based on seven immune-related genes was established, which was validated in The Cancer Genome Atlas (TCGA) training set, TCGA testing set, TCGA entire set and GSE71729 set. Furthermore, S100A14 (S100 Calcium Binding Protein A14) was identified as the gene occupying the most paramount position in risk signature. According to the GSEA, CIBERSORT and ESTIMATE algorithm, S100A14 was mainly associated with lower proportion of CD8 + T cells and higher proportion of M0 macrophages in PC tissue. Meanwhile, analysis of single-cell dataset CRA001160 revealed a significant negative correlation between S100A14 expression in PC cells and CD8 + T cell infiltration, which was further confirmed by tissue microenvironment landscape imaging and machine learning-based analysis in our own PUMCH cohort. Additionally, analysis of a pan-pancreatic cancer cell line illustrated that S100A14 might inhibit CD8 + T cell activation via the upregulation of PD-L1 expression in PC cells, which was also verified by the immunohistochemical results of PUMCH cohort. Finally, tumor mutation burden analysis and immunophenoscore algorithm revealed that patients with high S100A14 expression had a higher probability of responding to immunotherapy. In conclusion, our study established an efficient immune-related prediction model and identified the potential role of S100A14 in regulating the immune microenvironment and serving as a biomarker for immunotherapy efficacy prediction.

S100A14: A novel negative regulator of cancer stemness and immune evasion by inhibiting STAT3-mediated programmed death-ligand 1 expression in colorectal cancer

BACKGROUND

Programmed death-ligand 1 (PD-L1) has functional roles in cancer stem-like cell (CSC) phenotypes and chemoresistance besides immune evasion. Chemotherapy is a common treatment choice for colorectal cancer (CRC) patients; however, chemoresistance limits its effectiveness of treatment.

METHODS

We examined the role of S100A14 (SA14) in CRC by adopting PD-L1high subpopulations within CRC cell lines and patient tumours, by establishing PD-L1high chemoresistant CRC sublines through prolonged exposure to 5-fluorouracil/oxaliplatin-based chemotherapy in vitro and in vivo, and by analysing a public database.

RESULTS

We identified a novel function of SA14 as a regulator of immune surveillance, major CSC phenotypes, and survival capacity under hostile microenvironments, including those harbouring chemotherapeutics, and as a prognostic biomarker in CRC. Mechanistically, SA14 inhibits PD-L1 expression by directly interacting with signal transducer and activator of transcription 3 (STAT3) and inducing its proteasome-mediated degradation. While gain-of-SA14 causes loss of PD-L1 expression and tumourigenic potential and sensitisation to chemotherapy-induced apoptosis in chemoresistant CRC cells, loss-of-SA14 causes increases in PD-L1 expression, tumourigenic potential, and chemoresistance in vitro and in vivo. We further show that a combinatorial treatment with chemotherapy and recombinant SA14 protein effectively induces apoptosis in PD-L1high chemoresistant CRC cells.

CONCLUSIONS

Our results suggest that SA14-based therapy is an effective strategy to prevent tumour progression and that SA14 is a predictive biomarker for anti-PD-L1 immunotherapy and chemotherapy in combination.

Circ_0003221 Downregulation Restrains Cervical Cancer Cell Growth, Metastasis and Angiogenesis by Governing the miR-139-3p/S100A14 Pathway

Circular RNA (circRNA) has considerable potency in carcinogenesis, which has aroused much attention. The objective of our study was to disclose the role of circ_0003221 in cervical cancer. Circ_0003221, miR-139-3p, and S100 calcium-binding protein A14 (S100A14) mRNA were quantified by quantitative real-time PCR (qPCR). The proliferation of cancer cells was checked by CCK-8 assay and EdU assay. The migration and invasion of cancer cells were checked by transwell assay. Angiogenesis was determined by tube formation assay. The protein levels of epithelial-mesenchymal transition (EMT)-related markers, angiogenesis-related markers, and S100A14 protein were measured by western blot. The interplays between miR-139-3p and circ_0003221 or S100A14 were ensured by RIP assay and dual-luciferase reporter assay. Further animal study was conducted to verify the role of circ_0003221 in vivo. Circ_0003221 was highly expressed in cancer tissues and cells, and its downregulation suppressed cancer cell proliferation, migration, invasion, and angiogenesis and also delayed tumor growth in vivo. Circ_0003221 bound to miR-139-3p and sequestered miR-139-3p expression. The inhibitory cancer cell biological behaviors by circ_0003221 downregulation were recovered by miR-139-3p suppression. S100A14 was a target gene of miR-139-3p. MiR-139-3p upregulation repressed cancer cell malignant phenotypes by depleting S100A14. Importantly, circ_0003221 positively regulated S100A14 expression by targeting miR-139-3p. Circ_0003221 downregulation restrains cervical cancer cell growth, metastasis, and angiogenesis by governing the miR-139-3p/S100A14 pathway.

S100A2 Is a Prognostic Biomarker Involved in Immune Infiltration and Predict Immunotherapy Response in Pancreatic Cancer

Pancreatic cancer (PC) is a highly fatal and aggressive disease with its incidence and mortality quite discouraging. It is of great significance to construct an effective prognostic signature of PC and find the novel biomarker for the optimization of the clinical decision-making. Due to the crucial role of immunity in tumor development, a prognostic model based on nine immune-related genes was constructed, which was proved to be effective in The Cancer Genome Atlas (TCGA) training set, TCGA testing set, TCGA entire set, GSE78229 set, and GSE62452 set. Furthermore, S100A2 (S100 Calcium Binding Protein A2) was identified as the gene occupying the most paramount position in risk model. Gene set enrichment analysis (GSEA), ESTIMATE and CIBERSORT algorithm revealed that S100A2 was closely associated with the immune status in PC microenvironment, mainly related to lower proportion of CD8+T cells and activated NK cells and higher proportion of M0 macrophages. Meanwhile, patients with high S100A2 expression might get more benefit from immunotherapy according to immunophenoscore algorithm. Afterwards, our independent cohort was also used to demonstrate S100A2 was an unfavorable marker of PC, as well as its remarkably positive correlation with the expression of PD-L1. In conclusion, our results demonstrate S100A2 might be responsible for the preservation of immune-suppressive status in PC microenvironment, which was identified with significant potentiality in predicting prognosis and immunotherapy response in PC patients.

Prognostic Values and Clinical Significance of S100 Family Member's Individualized mRNA Expression in Pancreatic Adenocarcinoma

Objective: Pancreatic adenocarcinoma (PAAD) is a common malignant tumor worldwide. S100 family (S100s) is wildly involved in regulating the occurrence, development, invasion, metastasis, apoptosis, and drug resistance of many malignant tumors. However, the expression pattern, prognostic value, and oncological role of individual S100s members in PAAD need to be elucidated.

Methods: The transcriptional expression levels of S100s were analyzed through the Oncomine and GEPIA, respectively. The protein levels of S100s members in PAAD were studied by Human Protein Atlas. The correlation between S100 mRNA expression and overall survival and tumor stage in PAAD patients was studied by GEPIA. The transcriptional expression correlation and gene mutation rate of S100s members in PAAD patients were explored by cBioPortal. The co-expression networks of S100s are identified using STRING and Gene MANIA to predict their potential functions. The correlation of S100s expression and tumor-infiltrating immune cells was tested by TIMER. Pathway activity and drug target analyzed by GSCALite.

Results: 13 S100s members were upregulated in PAAD tissues. 15 S100s members were associated with TP53 mutation. Expression levels of S100A3/A5/A6/A10/A11/A14/A16/B/P/Z were significantly correlated with the pathological stage. Prognosis analysis demonstrated that PAAD patients with low mRNA levels of S100A1/B/Z or high levels of S100A2/A3/A5/A10/A11/A14/A16 had a poor prognosis. Immuno-infiltration analysis showed that the mRNA levels of S100A10/A11/A14/A16 were correlated with the infiltration degree of macrophages in PAAD. Drug sensitivity analysis showed that PAAD expressing high levels of S100A2/A6/A10/A11/A13/A14/A16 maybe resistant to small molecule drugs.

Conclusion: This study identifies the clinical significance and biological functions of the S100s in PAAD, which may provide novel insights for the selection of prognostic biomarkers.

S100 Proteins in Pancreatic Cancer: Current Knowledge and Future Perspectives

Pancreatic cancer (PC) is a highly malignant tumor occurring in the digestive system. Currently, there is a lack of specific and effective interventions for PC; thus, further exploration regarding the pathogenesis of this malignancy is warranted. The S100 protein family, a collection of calcium-binding proteins expressed only in vertebrates, comprises 25 members with high sequence and structural similarity. Dysregulated expression of S100 proteins is a biomarker of cancer progression and prognosis. Functionally, these proteins are associated with the regulation of multiple cellular processes, including proliferation, apoptosis, growth, differentiation, enzyme activation, migration/invasion, Ca2+ homeostasis, and energy metabolism. This review highlights the significance of the S100 family in the diagnosis and prognosis of PC and its vital functions in tumor cell metastasis, invasion and proliferation. A further understanding of S100 proteins will provide potential therapeutic targets for preventing or treating PC.

Ca2+ Signaling and Its Potential Targeting in Pancreatic Ductal Carcinoma

Pancreatic cancer (PC) is a major cause of cancer-associated mortality in Western countries (and estimated to be the second cause of cancer deaths by 2030). The main form of PC is pancreatic adenocarcinoma, which is the fourth most common cause of cancer-related death, and this situation has remained virtually unchanged for several decades. Pancreatic ductal adenocarcinoma (PDAC) is inherently linked to the unique physiology and microenvironment of the exocrine pancreas, such as pH, mechanical stress, and hypoxia. Of them, calcium (Ca2+) signals, being pivotal molecular devices in sensing and integrating signals from the microenvironment, are emerging to be particularly relevant in cancer. Mutations or aberrant expression of key proteins that control Ca2+ levels can cause deregulation of Ca2+-dependent effectors that control signaling pathways determining the cells' behavior in a way that promotes pathophysiological cancer hallmarks, such as enhanced proliferation, survival and invasion. So far, it is essentially unknown how the cancer-associated Ca2+ signaling is regulated within the characteristic landscape of PDAC. This work provides a complete overview of the Ca2+ signaling and its main players in PDAC. Special consideration is given to the Ca2+ signaling as a potential target in PDAC treatment and its role in drug resistance.