Potential prognostic biomarkers of pancreatic cancer

Preoperative Prognostic Factors in Resectable Pancreatic Cancer: State of the Art and Prospects

BACKGROUND

Only 15% to 20% of patients with pancreatic ductal adenocarcinoma (PDAC) have access to surgical resection, which represents the only chance of curative treatment. Current resection classifications are almost exclusively anatomic and do not correlate sufficiently with patient survival. It is essential to develop preoperative prognostic factors to distinguish patients at high risk of early postoperative recurrence from those who will have prolonged survival after surgery. In some cases, PDACs may present biomolecular differences reflecting their aggressiveness that are not yet assessable by the current clinical-biologic assessment. This study aimed to assess the preoperative prognostic factors that are already available and the future perspectives being developed.

METHOD

This study reviewed the literature using the PubMed public database for preoperative prognostic factors for resectable PDAC.

CONCLUSION

Validated preoperative prognostic factors, whether clinical, biologic, radiologic, or histologic, are very important in anticipating the course of each patient's disease. The identification of potential new prognostic biomarkers such as genomic, transcriptomic, and proteomic analyses and the dosage of circulating tumor DNA are very serious avenues to be developed, but the extraction and analysis techniques as well as the interpretation of their results need to be standardized in prospective studies.

Multi-omic biomarker panel in pancreatic cyst fluid and serum predicts patients at a high risk of pancreatic cancer development

Integration of multi-omic data for the purposes of biomarker discovery can provide novel and robust panels across multiple biological compartments. Appropriate analytical methods are key to ensuring accurate and meaningful outputs in the multi-omic setting. Here, we extensively profile the proteome and transcriptome of patient pancreatic cyst fluid (PCF) (n = 32) and serum (n = 68), before integrating matched omic and biofluid data, to identify biomarkers of pancreatic cancer risk. Differential expression analysis, feature reduction, multi-omic data integration, unsupervised hierarchical clustering, principal component analysis, spearman correlations and leave-one-out cross-validation were performed using RStudio and CombiROC software. An 11-feature multi-omic panel in PCF [PIGR, S100A8, REG1A, LGALS3, TCN1, LCN2, PRSS8, MUC6, SNORA66, miR-216a-5p, miR-216b-5p] generated an AUC = 0.806. A 13-feature multi-omic panel in serum [SHROOM3, IGHV3-72, IGJ, IGHA1, PPBP, APOD, SFN, IGHG1, miR-197-5p, miR-6741-5p, miR-3180, miR-3180-3p, miR-6782-5p] produced an AUC = 0.824. Integration of the strongest performing biomarkers generated a 10-feature cross-biofluid multi-omic panel [S100A8, LGALS3, SNORA66, miR-216b-5p, IGHV3-72, IGJ, IGHA1, PPBP, miR-3180, miR-3180-3p] with an AUC = 0.970. Multi-omic profiling provides an abundance of potential biomarkers. Integration of data from different omic compartments, and across biofluids, produced a biomarker panel that performs with high accuracy, showing promise for the risk stratification of patients with pancreatic cystic lesions.

Proteomic profiling of small extracellular vesicles derived from mouse pancreatic cancer and stellate cells: Role in pancreatic cancer

Small extracellular vesicles (sEVs) are cell-derived vesicles evolving as important elements involved in all stages of cancers. sEVs bear unique protein signatures that may serve as biomarkers. Pancreatic cancer (PC) records a very poor survival rate owing to its late diagnosis and several cancer cell-derived proteins have been reported as candidate biomarkers. However, given the pivotal role played by stellate cells (PSCs, which produce the collagenous stroma in PC), it is essential to also assess PSC-sEV cargo in biomarker discovery. Thus, this study aimed to isolate and characterise sEVs from mouse PC cells and PSCs cultured alone or as co-cultures and performed proteomic profiling and pathway analysis. Proteomics confirmed the enrichment of specific markers in the sEVs compared to their cells of origin as well as the proteins that are known to express in each of the culture types. Most importantly, for the first time it was revealed that PSC-sEVs are enriched in proteins (including G6PI, PGAM1, ENO1, ENO3, and LDHA) that mediate pathways related to development of diabetes, such as glucose metabolism and gluconeogenesis revealing a potential role of PSCs in pancreatic cancer-related diabetes (PCRD). PCRD is now considered a harbinger of PC and further research will enable to identify the role of these components in PCRD and may develop as novel candidate biomarkers of PC.

Mass spectrometry–based proteomics technology in pancreatic cancer research

Pancreatic ductal adenocarcinoma (PDAC) has become a significant health concern with increasing incidence and mortality rates over the past few decades. Researchers have turned their attention to cutting-edge mass spectrometry (MS) technology due to its high-throughput and accurate detection capacity, which plays a vital role in understanding the mechanisms and discovering biomarkers for pancreatic diseases. In this review, we comprehensively investigate various methodologies of quantitative and qualitative proteomics MS technologies, alongside bioinformatical platforms employed in pancreatic cancer research. The integration of these optimized approaches provides novel insights into the molecular mechanisms underlying tumorigenesis and disease progression, ultimately facilitating the discovery of potential diagnostic, prognostic biomarkers, and therapeutic targets. The robust MS-based strategy shows promise in paving the way for early diagnosis and personalized medicine for pancreatic cancer patients.

S100A8/A9 as a risk factor for breast cancer negatively regulated by DACH1

BACKGROUND

S100A8 and S100A9 are members of Ca2+-binding EF-hand superfamily, mainly expressed by macrophages and neutrophils. Limited by the poor stability of homodimers, they commonly exist as heterodimers. Beyond acting as antibacterial cytokines, S100A8/A9 is also associated with metabolic and autoimmune diseases such as obesity, diabetes, and rheumatoid arthritis. While the involvement of S100A8/A9 in breast cancer development has been documented, its prognostic significance and the precise regulatory mechanisms remain unclear.

METHODS

S100A8/A9 protein in breast cancer samples was evaluated by immunohistochemistry staining with tumor tissue microarrays. The serum S100A8 concentration in patients was measured by enzyme-linked immunosorbent assay (ELISA). The S100A8 secreted by breast cancer cells was detected by ELISA as well. Pooled analyses were conducted to explore the relationships between S100A8/A9 mRNA level and clinicopathological features of breast cancer patients. Besides, the effects of S100A8/A9 and DACH1 on patient outcomes were analyzed by tissue assays. Finally, xenograft tumor assays were adopted to validate the effects of DACH1 on tumor growth and S100A8/A9 expression.

RESULTS

The level of S100A8/A9 was higher in breast cancer, relative to normal tissue. Increased S100A8/A9 was related to poor differentiation grade, loss of hormone receptors, and Her2 positive. Moreover, elevated S100A8/A9 predicted a worse prognosis for breast cancer patients. Meanwhile, serum S100A8 concentration was upregulated in Grade 3, basal-like, and Her2-overexpressed subtypes. Additionally, the results of public databases showed S100A8/A9 mRNA level was negatively correlated to DACH1. Stable overexpressing DACH1 in breast cancer cells significantly decreased the generation of S100A8. The survival analysis demonstrated that patients with high S100A8/A9 and low DACH1 achieved the shortest overall survival. The xenograft models indicated that DACH1 expression significantly retarded tumor growth and downregulated S100A8/A9 protein abundance.

CONCLUSION

S100A8/A9 is remarkedly increased in basal-like and Her2-overexpressed subtypes, predicting poor prognosis of breast cancer patients. Tumor suppressor DACH1 inhibits S100A8/A9 expression. The combination of S100A8/A9 and DACH1 predicted the overall survival of breast cancer patients more preciously.

BRCA mutational status shapes the stromal microenvironment of pancreatic cancer linking clusterin expression in cancer associated fibroblasts with HSF1 signaling

Tumors initiate by mutations in cancer cells, and progress through interactions of the cancer cells with non-malignant cells of the tumor microenvironment. Major players in the tumor microenvironment are cancer-associated fibroblasts (CAFs), which support tumor malignancy, and comprise up to 90% of the tumor mass in pancreatic cancer. CAFs are transcriptionally rewired by cancer cells. Whether this rewiring is differentially affected by different mutations in cancer cells is largely unknown. Here we address this question by dissecting the stromal landscape of BRCA-mutated and BRCA Wild-type pancreatic ductal adenocarcinoma. We comprehensively analyze pancreatic cancer samples from 42 patients, revealing different CAF subtype compositions in germline BRCA-mutated vs. BRCA Wild-type tumors. In particular, we detect an increase in a subset of immune-regulatory clusterin-positive CAFs in BRCA-mutated tumors. Using cancer organoids and mouse models we show that this process is mediated through activation of heat-shock factor 1, the transcriptional regulator of clusterin. Our findings unravel a dimension of stromal heterogeneity influenced by germline mutations in cancer cells, with direct implications for clinical research.

Identification S100A9 as a potential biomarker in neuroblastoma

BACKGROUND

More than half of Neuroblastoma (NB) patients presented with distant metastases and the relapse of metastatic patients was up to 90%. It is urgent to explore a biomarker that could facilitate the prediction of metastasis in NB patients.

METHODS AND RESULTS

In the present study, we systematically analyzed Gene Expression Omnibus datasets and focused on identifying the critical molecular networks and novel key hub genes implicated in NB metastasis. In total, 176 up-regulated and 19 down-regulated differentially expressed genes (DEGs) were identified. Based on these DEGs, a PPI network composed of 150 nodes and 452 interactions was established. Through PPI network identification combined with qRT-PCR, ELISA and IHC, S100A9 was screened as an outstanding gene. Furthermore, in vitro tumorigenesis assays demonstrated that S100A9 overexpression enhanced the proliferation, migration and invasion of NB cells.

CONCLUSIONS

Taken together, our findings suggested that S100A9 could participate in NB tumorigenesis and progression. In addition, S100A9 has the potential to be used as a promising clinical biomarker in the prediction of NB metastasis.

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished 'classical' from 'basal-like' tumors with more aggressive clinical behavior. We derive PDAC organoids from 18 primary tumors and two matched liver metastases, and show that 'classical' and 'basal-like' cells coexist in individual organoids. By single-cell transcriptome analysis of PDAC organoids and primary PDAC, we identify distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. Cell states are connected by a differentiation hierarchy, with 'classical' cells concentrated at the endpoint. In an imaging-based drug screen, expression of 'classical' subtype genes correlates with better drug response. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity.

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.

Pancreatic ductal deletion of S100A9 alleviates acute pancreatitis by targeting VNN1-mediated ROS release to inhibit NLRP3 activation

Recent studies have proven that the overall pathophysiology of pancreatitis involves not only the pancreatic acinar cells but also duct cells, however, pancreatic duct contribution in acinar cells homeostasis is poorly known and the molecular mechanisms leading to acinar insult and acute pancreatitis (AP) are unclear. Our previous work also showed that S100A9 protein level was notably increased in AP rat pancreas through iTRAQ-based quantitative proteomic analysis. Therefore, we investigated the actions of injured duct cells on acinar cells and the S100A9-related effects and mechanisms underlying AP pathology in the present paper. Methods: In this study, we constructed S100A9 knockout (s100a9-/-) mice and an in vitro coculture system for pancreatic duct cells and acinar cells. Moreover, a variety of small molecular inhibitors of S100A9 were screened from ChemDiv through molecular docking and virtual screening methods. Results: We found that the upregulation of S100A9 induces cell injury and inflammatory response via NLRP3 activation by targeting VNN1-mediated ROS release; and loss of S100A9 decreases AP injury in vitro and in vivo. Moreover, molecular docking and mutant plasmid experiments proved that S100A9 has a direct interaction with VNN1 through the salt bridges formation of Lys57 and Glu92 residues in S100A9 protein. We further found that compounds C42H60N4O6 and C28H29F3N4O5S can significantly improve AP injury in vitro and in vivo through inhibiting S100A9-VNN1 interaction. Conclusions: Our study showed the important regulatory effect of S100A9 on pancreatic duct injury during AP and revealed that inhibition of the S100A9-VNN1 interaction may be a key therapeutic target for this disease.

Current State of "Omics" Biomarkers in Pancreatic Cancer

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.

Biliary Tract Carcinogenesis Model Based on Bile Metaproteomics

Purpose: To analyze human and bacteria proteomic profiles in bile, exposed to a tumor vs. non-tumor microenvironment, in order to identify differences between these conditions, which may contribute to a better understanding of pancreatic carcinogenesis.

Patients and Methods: Using liquid chromatography and mass spectrometry, human and bacterial proteomic profiles of a total of 20 bile samples (7 from gallstone (GS) patients, and 13 from pancreatic head ductal adenocarcinoma (PDAC) patients) that were collected during surgery and taken directly from the gallbladder, were compared. g:Profiler and KEGG (Kyoto Encyclopedia of Genes and Genomes) Mapper Reconstruct Pathway were used as the main comparative platform focusing on over-represented biological pathways among human proteins and interaction pathways among bacterial proteins.

Results: Three bacterial infection pathways were over-represented in the human PDAC group of proteins. IL-8 is the only human protein that coincides in the three pathways and this protein is only present in the PDAC group. Quantitative and qualitative differences in bacterial proteins suggest a dysbiotic microenvironment in the PDAC group, supported by significant participation of antibiotic biosynthesis enzymes. Prokaryotes interaction signaling pathways highlight the presence of zeatin in the GS group and surfactin in the PDAC group, the former in the metabolism of terpenoids and polyketides, and the latter in both metabolisms of terpenoids, polyketides and quorum sensing. Based on our findings, we propose a bacterial-induced carcinogenesis model for the biliary tract.

Conclusion: To the best of our knowledge this is the first study with the aim of comparing human and bacterial bile proteins in a tumor vs. non-tumor microenvironment. We proposed a new carcinogenesis model for the biliary tract based on bile metaproteomic findings. Our results suggest that bacteria may be key players in biliary tract carcinogenesis, in a long-lasting dysbiotic and epithelially harmful microenvironment, in which specific bacterial species' biofilm formation is of utmost importance. Our finding should be further explored in future using in vitro and in vivo investigations.

An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

Calprotectin and Calgranulin C as Biomarkers of Pancreatic Tumors: Baseline Levels and Level Changes after Surgery

Pancreatic tumors and their surgical resection are associated with significant morbidity and mortality, and the biomarkers currently used for these conditions have limited sensitivity and specificity. Because calprotectin and calgranulin C serum levels have been demonstrated to be potential biomarkers of certain cancers and complications of major surgery, the levels of both proteins were tested in the current study in patients with benign and malignant pancreatic tumors that were surgically removed. The baseline serum levels and kinetics of calprotectin and calgranulin C during the 7-day postoperative period were evaluated with immunoassays in 98 adult patients who underwent pancreatic surgery. The baseline serum levels of calprotectin and calgranulin C in patients with malignant (n = 84) and benign tumors (n = 14) were significantly higher (p < 0.01) when compared to those in the healthy controls (n = 26). The serum levels of both proteins were also significantly (p < 0.05) higher in patients with benign tumors than in those with malignant tumors. After surgery, the serum levels of calprotectin and calgranulin C were significantly (p < 0.01) higher than their baseline values, and this elevation persisted throughout the seven days of the follow-up period. Interestingly, starting on day 1 of the postoperative period, the serum levels of both proteins were significantly (p < 0.05) higher in the 37 patients who developed postoperative pancreatic fistulas (POPFs) than in the patients who had uneventful recoveries (n = 61). Moreover, the serum levels of calprotectin and calgranulin C demonstrated a significant predictive value for the development of POPF; the predictive values of these two proteins were better than those of the serum level of C-reactive protein and the white blood cell count. Taken together, the results of this study suggest that calprotectin and calgranulin C serum levels are potential biomarkers for pancreatic tumors, surgical injury to the pancreatic tissue and the development of POPFs.

Proteomic and genomic profiling of pancreatic cancer

Pancreatic cancer remains the most fatal human tumor type. The aggressive tumor biology coupled with the lack of early detection strategies and effective treatment are major reasons for the poor survival rate. Collaborative research efforts have been devoted to understand pancreatic cancer at the molecular level. Large-scale genomic studies have generated important insights into the genetic drivers of pancreatic cancer. In the post-genomic era, protein sequencing of tumor tissue, cell lines, pancreatic juice, and blood from patients with pancreatic cancer has provided a fundament for the development of new diagnostic and prognostic biomarkers. The integration of mass spectrometry and genomic sequencing strategies may help characterize protein identities and post-translational modifications that relate to a specific mutation. Consequently, proteomic and genomic techniques have become a compulsory requirement in modern medicine and health care. These types of proteogenomic studies may usher in a new era of precision diagnostics and treatment in patients with pancreatic cancer.

S100A9 promotes the proliferation and migration of cervical cancer cells by inducing epithelial‑mesenchymal transition and activating the Wnt/β‑catenin pathway

S100 calcium-binding protein A9 (S100A9), a member of the S100 protein family, is often upregulated in various cancers, including cervical cancer. Elevated S100A9 expression is thought to serve an important role in tumorigenesis; however, the exact role of S100A9 in the modulation of cervical cancer and the underlying molecular mechanism remain unknown. In the present study, we aimed to investigate the effects of S100A9 on the proliferation and migration of cervical cancer cells, as well as the molecular mechanisms underlying these effects. Our results demonstrated that endogenous expression of S100A9 in SiHa and CaSki cell lines was significantly higher than in the HeLa cell line. As expected, overexpression of S100A9 enhanced the proliferation and migration of cervical cancer cells. In addition, S100A9 overexpression induced epithelial-mesenchymal transition (EMT) as determined by reduced expression levels of the epithelial marker E-cadherin, whereas the expression levels of the mesenchymal marker vimentin were upregulated. Furthermore, it was reported that the effects of S100A9 in the modulation of cervical cancer cells were mediated through the Wnt/β-catenin signaling pathway as β-catenin knockdown significantly suppressed the ability of S100A9 to enhance the proliferation and migration of cervical cancer cells. Collectively, these findings suggest that S100A9 promoted the proliferation and migration of cervical cancer cell lines. Furthermore, the underlying molecular mechanisms may be partially attributed to the induction of EMT and activation of the Wnt/β-catenin signaling pathway.

Extracellular S100A11 Plays a Critical Role in Spread of the Fibroblast Population in Pancreatic Cancers

The fertile stroma in pancreatic ductal adenocarcinomas (PDACs) has been suspected to greatly contribute to PDAC progression. Since the main cell constituents of the stroma are fibroblasts, there is crosstalking(s) between PDAC cells and surrounding fibroblasts in the stroma, which induces a fibroblast proliferation burst. We have reported that several malignant cancer cells including PDAC cells secrete a pronounced level of S100A11, which in turn stimulates proliferation of cancer cells via the receptor for advanced glycation end products (RAGE) in an autocrine manner. Owing to the RAGE⁺ expression in fibroblasts, the extracellular abundant S100A11 will affect adjacent fibroblasts. In this study, we investigated the significance of the paracrine axis of S100A11-RAGE in fibroblasts for their proliferation activity. In in vitro settings, extracellular S100A11 induced upregulation of fibroblast proliferation. Our mechanistic studies revealed that the induction is through RAGE-MyD88-mTOR-p70 S6 kinase upon S100A11 stimulation. The paracrine effect on fibroblasts is linked mainly to triggering growth but not cellular motility. Thus, the identified pathway might become a potential therapeutic target to suppress PDAC progression through preventing PDAC-associated fibroblast proliferation.

Proteomic biomarkers in body fluids associated with pancreatic cancer

Pancreatic cancer (PC) is a highly malignant disease that represents the fourth leading cancer-related death worldwide. There has been very little improvement in survival rates over recent years, and surgical resection remains the only reliable curative approach. Factors that contribute to this dismal prognosis for PC include its rapid progression and invasion, the absence of specific symptoms, and the little impact of available chemotherapy. Importantly, the management of this malignancy is also limited by the lack of highly specific and sensitive biomarkers for its diagnosis and follow-up, and their identification is therefore considered a promising strategy to improve outcomes in these patients. Numerous translational studies have explored the usefulness of body fluids as a non-invasive source of PC-specific biomarkers, and innovations in proteomic methods and technologies have provided a myriad of protein biomarkers for different cancers. The adoption of a proteomic approach has improved understanding of the biology of PC and contributed to the potential identification of protein biomarkers for this disease. This review considers the most recent research efforts to develop novel proteomic biomarkers in body fluids for PC.

Potential prognostic biomarkers in pancreatic juice of resectable pancreatic ductal adenocarcinoma

Despite potentially curative surgery pancreatic cancer has a dismal prognosis. Serum cancer antigen 19-9 (CA 19-9) correlates with tumor burden, resectability and survival in patients with pancreatic ductal adenocarcinoma. Identification of novel biomarkers may facilitate early diagnosis of pancreatic cancer and improve survival. Pancreatic juice is a rich source of cancer-specific proteins rendering it a promising tool for identifying biomarkers. Recent proteomic and microRNA expression analyses have identified several biomarkers of potential diagnostic and prognostic value. Tumor markers CA 19-9 and carcinoembryonic antigen (CEA) are widely used in the characterization of premalignant and malignant lesions of the pancreas. Elevated level of CEA in bile is a marker for malignancy and a predictor of hepatic recurrence. The potential value of CA 19-9, CEA and lactate dehydrogenase as prognostic biomarkers in pancreatic juice and bile is unknown. Specimens of pancreatic juice and bile can be readily collected during surgical resection of the tumor. Profiling of pancreatic juice and bile to identify novel prognostic biomarkers may improve selection of patients for adjuvant therapy with a favorable impact on overall survival in patients diagnosed with pancreatic cancer.

Key biological processes driving metastatic spread of pancreatic cancer as identified by multi-omics studies

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy, characterized by a high metastatic burden, already at the time of diagnosis. The metastatic potential of PDAC is one of the main reasons for the poor outcome next to lack of significant improvement in effective treatments in the last decade. Key mutated driver genes, such as activating KRAS mutations, are concordantly expressed in primary and metastatic tumors. However, the biology behind the metastatic potential of PDAC is not fully understood. Recently, large-scale omic approaches have revealed new mechanisms by which PDAC cells gain their metastatic potency. In particular, genomic studies have shown that multiple heterogeneous subclones reside in the primary tumor with different metastatic potential. The development of metastases may be correlated to a more mesenchymal transcriptomic subtype. However, for cancer cells to survive in a distant organ, metastatic sites need to be modulated into pre-metastatic niches. Proteomic studies identified the influence of exosomes on the Kuppfer cells in the liver, which could function to prepare this tissue for metastatic colonization. Phosphoproteomics adds an extra layer to the established omic techniques by unravelling key functional signaling. Future studies integrating results from these large-scale omic approaches will hopefully improve PDAC prognosis through identification of new therapeutic targets and patient selection tools. In this article, we will review the current knowledge on the biology of PDAC metastasis unravelled by large scale multi-omic approaches.

Diagnostic value of selected markers and apoptotic pathways for pancreatic cancer

Pancreatic cancer occupies the fourth place as a cause of death from cancer, and the mortality rate is similar to the number of newly detected cases. Due to the late diagnosis, only 5-6% of patients with pancreatic cancer survive for five years. Given that early diagnosis is critical for improving patients' survival rates, there is an urgent need for the discovery and validation of new biomarkers with sufficient sensitivity and specificity to help diagnose pancreatic cancer early. Detection of serum tumor markers (CA19-9, CEA, CA125 and CA242) is conducive to the early diagnosis of pancreatic cancer. The combination of miR-16, miR-196a and CA19-9 plasma level was more effective, especially in early tumor screening. Furthermore, recent studies reported that mainly miR-21, miR-155 and miR-196 were dysregulated in IPMN (intraductal papillary mucinous neoplasms) and PanIN (pancreatic intraepithelial neoplasia) lesions, suggesting their usefulness as early biomarkers of these diseases. The reduced rate of apoptosis plays a crucial role in carcinogenesis, and it is one of the most important characteristics acquired by pancreatic cancer cells, which protects them from attack by the immune system and reduces the effectiveness of pharmacological treatment. This review summarizes the data concerning the clinical utility of selected biomarkers in pancreatic cancer patients. The review mainly focuses on the genetic aspects of signaling pathway disorders associated with apoptosis in the pathogenesis and diagnosis of pancreatic cancer.

Systematic review of peri-operative prognostic biomarkers in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) continues to be associated with a poor prognosis. This systematic review aimed to summarize the literature regarding potential prognostic biomarkers to facilitate validation studies and clinical application.

METHODS

A systematic review was performed (2004-2014) according to PRISMA guidelines. Studies were ranked using REMARK criteria and the following outcomes were examined: overall/disease free survival, nodal involvement, tumour characteristics, metastasis, recurrence and resectability.

RESULTS

256 biomarkers were identified in 158 studies. 171 biomarkers were assessed with respect to overall survival: urokinase-type plasminogen activator receptor, atypical protein kinase C and HSP27 ranked the highest. 33 biomarkers were assessed for disease free survival: CD24 and S100A4 were the highest ranking. 17 biomarkers were identified for lymph node involvement: Smad4/Dpc4 and FOXC1 ranked highest. 13 biomarkers were examined for tumour grade: mesothelin and EGFR were the highest ranking biomarkers. 10 biomarkers were identified for metastasis: p16 and sCD40L were the highest ranking. 4 biomarkers were assessed resectability: sCD40L, s100a2, Ca 19-9, CEA.

CONCLUSION

This review has identified and ranked specific biomarkers that should be a primary focus of ongoing validation and clinical translational work in PDAC.

Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

OBJECTIVES

The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling.

METHODS

Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion.

RESULTS

Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥ 2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining.

CONCLUSIONS

The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC.

The role of S100 proteins and their receptor RAGE in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with low survival rates. Current therapeutic treatments have very poor response rates due to the high inherent chemoresistance of the pancreatic-cancer cells. Recent studies have suggested that the receptor for advanced glycation end products (RAGE) and its S100 protein ligands play important roles in the progression of PDAC. We will discuss the potential role of S100 proteins and their receptor, RAGE, in the development and progression of pancreatic cancer.

Serum calprotectin: a new potential biomarker for thyroid papillary carcinoma

The aim of this study was to evaluate serum calprotectin levels and oxidative stress status in patients with papillary thyroid carcinoma (PTC) and the changes in their levels after total thyroidectomy. The study involved 30 patients with PTC and 30 healthy controls. Blood samples were obtained from the PTC patients before and 1 month after the operation. Preoperative and postoperative serum samples from PTC patients and healthy controls were analysed for calprotectin, total antioxidant status (TAS), total oxidant status (TOS) and lipid hydroperokside (LOOH). The preoperative calprotectin, TOS, OSI and LOOH levels of the patients with PTC were significantly higher compared to those of the control group (p < 0.001, for each). The levels of calprotectin decreased significantly in patients with PTC after the operation (p < 0.001), while TAS, TOS and OSI levels remained unchanged (p = 0.313, p = 0.085 and p = 0.163, respectively). Preoperative serum calprotectin levels were positively correlated with TOS, OSI and LOOH levels and negatively correlated with TAS levels in patients with PTC. In conclusion, serum calprotectin levels is increased in patients with PTC, and calprotectin is positively correlated with TOS and LOOH. Serum calprotectin levels is significantly decreased after total thyroidectomy.

Molecular interaction of a kinase inhibitor midostaurin with anticancer drug targets, S100A8 and EGFR: transcriptional profiling and molecular docking study for kidney cancer therapeutics

The S100A8 and epidermal growth factor receptor (EGFR) proteins are proto-oncogenes that are strongly expressed in a number of cancer types. EGFR promotes cellular proliferation, differentiation, migration and survival by activating molecular pathways. Involvement of proinflammatory S100A8 in tumor cell differentiation and progression is largely unclear and not studied in kidney cancer (KC). S100A8 and EGFR are potential therapeutic biomarkers and anticancer drug targets for KC. In this study, we explored molecular mechanisms of interaction profiles of both molecules with potential anticancer drugs. We undertook transcriptional profiling in Saudi KCs using Affymetrix HuGene 1.0 ST arrays. We identified 1478 significantly expressed genes, including S100A8 and EGFR overexpression, using cut-off p value <0.05 and fold change ≥2. Additionally, we compared and confirmed our findings with expression data available at NCBI's GEO database. A significant number of genes associated with cancer showed involvement in cell cycle progression, DNA repair, tumor morphology, tissue development, and cell survival. Atherosclerosis signaling, leukocyte extravasation signaling, notch signaling, and IL-12 signaling were the most significantly disrupted signaling pathways. The present study provides an initial transcriptional profiling of Saudi KC patients. Our analysis suggests distinct transcriptomic signatures and pathways underlying molecular mechanisms of KC progression. Molecular docking analysis revealed that the kinase inhibitor "midostaurin" has amongst the selected drug targets, the best ligand properties to S100A8 and EGFR, with the implication that its binding inhibits downstream signaling in KC. This is the first structure-based docking study for the selected protein targets and anticancer drug, and the results indicate S100A8 and EGFR as attractive anticancer targets and midostaurin with effective drug properties for therapeutic intervention in KC.

Expression and diagnostic value of HE4 in pancreatic adenocarcinoma

Human epididymis protein 4 (HE4) is a recognized biomarker in ovarian and endometrial cancer and over-expressed in pancreatic adenocarcinoma. The diagnostic value of HE4 in pancreatic adenocarcinoma remains unknown. Here we elucidate mRNA, protein and serum level of HE4 in pancreatic adenocarcinoma. HE4 mRNA level in tumor adjacent tissues and pancreatic adenocarcinoma tissues were tested by real time-PCR. Tissue microarray containing normal, adenocarcinoma, and adjacent pancreatic tissue was tested by immunohistochemistry (IHC). Serum level of HE4, carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 15-3 (CA15-3) and carbohydrate antigen 125 (CA125) were detected by ELISA assay in control and tumor patients. Further we compared the sensitivity and specificity of determining HE4, CA19-9, CA15-3, and CA125 for diagnosis of pancreatic adenocarcinoma and assessed the complementary diagnostic value of HE4, CA19-9, CA15-3 and CA125. Real time PCR showed significantly increased HE4 mRNA level in pancreatic adenocarcinoma compared with control. Result of IHC showed that HE4 significantly higher expressed in the human pancreatic carcinoma tissues than in both normal and adjacent non-tumorous pancreatic tissues, and the staining intensity is inversely correlated with the clinical stage. HE4 was highly expressed in early stage of pancreatic adenocarcinoma. Serum HE4 level is higher in cases with pancreatic adenocarcinoma than in the controls. Serum HE4 levels could research to a sensitivity of 45.83% and specificity of 93.75% when the Cutoff was set at 4.59 ng/mL. The Combined HE4 and CA19-9 increased the sensitivity to 83.33%; and interestingly, the combination of HE4 with CA15-3 led to the most powerful sensitivity of 87.5%. Combined with CA19-9 and CA15-3, HE4 could be a potential biomarker to improve the diagnostic power for pancreatic adenocarcinoma.

Potential serum biomarkers for glioblastoma diagnostic assessed by proteomic approaches

BACKGROUND

The rapid progress of proteomics over the past years has allowed the discovery of a large number of potential biomarker candidates to improve early tumor diagnosis and therapeutic response, thus being further integrated into clinical environment. High grade gliomas represent one of the most aggressive and treatment-resistant types of human brain cancer, with approximately 9-12 months median survival rate for patients with grade IV glioma (glioblastoma). Using state-of-the-art proteomics technologies, we have investigated the proteome profile for glioblastoma patients in order to identify a novel protein biomarker panel that could discriminate glioblastoma patients from controls and increase diagnostic accuracy.

RESULTS

In this study, SELDI-ToF MS technology was used to screen potential protein patterns in glioblastoma patients serum; furthermore, LC-MS/MS technology was applied to identify the candidate biomarkers peaks. Through these proteomic approaches, three proteins S100A8, S100A9 and CXCL4 were selected as putative biomarkers and confirmed by ELISA. Next step was to validate the above mentioned molecules as biomarkers through identification of protein expression by Western blot in tumoral versus peritumoral tissue.

CONCLUSIONS

Proteomic technologies have been used to investigate the protein profile of glioblastoma patients and established several potential diagnostic biomarkers. While it is unlikely for a single biomarker to be highly effective for glioblastoma diagnostic, our data proposed an alternative and efficient approach by using a novel combination of multiple biomarkers.