Rapid characterization of candidate biomarkers for pancreatic cancer using cell microarrays (CMAs)

Development and clinical validation of a novel 9-gene prognostic model based on multi-omics in pancreatic adenocarcinoma

The prognoses of patients with pancreatic adenocarcinoma (PAAD) remain poor due to the lack of biomarkers for early diagnosis and effective prognosis prediction. RNA sequencing, single nucleotide polymorphism, and copy number variation data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes. GISTIC 2.0 was used to identify significantly amplified or deleted genes, and Mutsig 2.0 was used to analyze the mutation data. The Lasso method was used to construct a risk prediction model. The Rms package was used to evaluate the overall predictive performance of the signature. Finally, Western blot and polymerase chain reaction were performed to evaluate gene expression. A total of 54 candidate genes were obtained after integrating the genomic mutated genes and prognosis-related genes. The Lasso method was used to ascertain 9 characteristic genes, including UNC13B, TSPYL4, MICAL1, KLHDC7B, KLHL32, AIM1, ARHGAP18, DCBLD1, and CACNA2D4. The 9-gene signature model was able to help stratify samples at risk in the training and external validation cohorts. In addition, the overall predictive performance of our model was found to be superior to that of other models. KLHDC7B, AIM1, DCBLD1, TSPYL4, and MICAL1 were significantly highly expressed in tumor tissues compared to normal tissues. ARHGAP18 and CACNA2D4 had no difference in expression between tumor and normal tissues. UNC13B and KLHL32 expression in the normal group was higher than in the tumor group. The 9-gene signature constructed in this study can be used as a novel prognostic marker to predict the survival of patients with pancreatic adenocarcinoma.

Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis

Bladder cancer (BC) is one of the most common malignancies in terms of incidence and recurrence worldwide. The aim of this study was to identify novel prognostic biomarkers related to BC progression utilizing weighted gene co-expression network analysis (WGCNA) and further bioinformatic analysis. First, we constructed a co-expression network by using WGCNA among 274 TCGA-BLCA patients and preliminarily screened out four genes (CORO1C, TMPRSS4, PIK3C2B, and ZNF692) associated with advanced clinical traits. In support, GSE19915 and specimens from 124 patients were used to validate the genes selected by WGCNA; then, CORO1C and TMPRSS4 were confirmed as hub genes with strong prognostic values in BC. Moreover, the result of gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) indicated that CORO1C and TMPRSS4 might be involved in the process of epithelial to mesenchymal transition (EMT) reversely. In addition, high expression of CORO1C was found to be significantly correlated with tumor-infiltrating neutrophils (TINs), a negative regulatory component that facilitates tumor distant progression and induces poor clinical outcome. In conclusion, our study first identified CORO1C and TMPRSS4 as vital regulators in the process of tumor progression through influencing EMT and could be developed to effective prognostic and therapeutic targets in future BC treatment.

Cell adhesion molecule profiles, proliferation activity and p53 expression in advanced epithelial ovarian cancer induced malignant ascites-Correlation of tissue microarray and cytology microarray

INTRODUCTION

Peritoneal dissemination accompanied by ascites formation is common in epithelial ovarian cancer (EOC). Adhesion molecules are crucial in metastatic spread and the latter involves epithelial-mesenchymal transition (EMT). This study aimed at: (1) clarifying whether E-cadherin and β-catenin expression and proliferative activity in metastatic ovarian cancer are inter-related; (2) Identifying possible correlations between cell adhesion molecular expression profiles, the proliferative activity and p53 expression of tumor cells and tumor grade and stage; (3) testing the cytology microarray (CMA) technique in analyzing metastasis formation.

MATERIAL AND METHODS

Both tumorous and ascitic samples from 27 EOC patients were examined by using tissue microarray (TMA) and cytology microarray (CMA), respectively. CMA blocks were constructed using cores from each cell block of the ascitic specimens. Expression of E-cadherin, β-catenin, Ki-67 and p53 was immunohistochemically detected both in TMA and CMA blocks.

RESULTS

E-cadherin expression was higher in ascitic cells than in primary tumor cells (p = .294). β-catenin expression was significantly lower in ascitic cells than in primary tumor cells (p = .006). Expression of Ki-67 was lower and expression of p53 was higher in primary tumors than in ascitic cells, for p53 the difference was significant (p = .001). Both Ki-67 and p53 expression elevated significantly in high-grade primary tumor cells and in ascites cells (p = .039, and p = .004, respectively).

CONCLUSION

Epithelial-mesenchymal transition- mesenchymal-epithelial transition is suggested as the best descriptive term for our IHC observations which accompany increased proliferative activity of ascitic cells. The CMA method is an adequate and reliable method for the analysis of ascitic tumor cells disseminating from ovarian malignancies.

Multiparametric plasma EV profiling facilitates diagnosis of pancreatic malignancy

Pancreatic ductal adenocarcinoma (PDAC) is usually detected late in the disease process. Clinical workup through imaging and tissue biopsies is often complex and expensive due to a paucity of reliable biomarkers. We used an advanced multiplexed plasmonic assay to analyze circulating tumor-derived extracellular vesicles (tEVs) in more than 100 clinical populations. Using EV-based protein marker profiling, we identified a signature of five markers (PDACEV signature) for PDAC detection. In our prospective cohort, the accuracy for the PDACEV signature was 84% [95% confidence interval (CI), 69 to 93%] but only 63 to 72% for single-marker screening. One of the best markers, GPC1 alone, had a sensitivity of 82% (CI, 60 to 95%) and a specificity of 52% (CI, 30 to 74%), whereas the PDACEV signature showed a sensitivity of 86% (CI, 65 to 97%) and a specificity of 81% (CI, 58 to 95%). The PDACEV signature of tEVs offered higher sensitivity, specificity, and accuracy than the existing serum marker (CA 19-9) or single-tEV marker analyses. This approach should improve the diagnosis of pancreatic cancer.

A breast cancer cell microarray (CMA) as a rapid method to characterize candidate biomarkers

Tissue microarrays (TMAs) have become an invaluable tool in cancer research to evaluate expression and subcellular localization of proteins in cells and tissues. As the catalogs of candidate biomarkers and therapeutic targets become more extensive, there is a need to characterize and validate these targets and biomarkers in cell lines as a primary biological system in research laboratories. Thus, cell microarrays (CMAs) are useful as a high-throughput screening tool. Here, we constructed a CMA containing 32 publicly available immortalized breast cell lines with the goal of creating a method to rapidly screen for antigens of interest in breast cancer research in a relatively easy, rapid and cost-effective manner. As proof of concept, we performed immunocytochemical staining of the HER2 receptor, as the status of this protein is relevant to breast cancer and has previously been reported for these cell lines. We observed a complete concordance of our staining with the published status of HER2 in these cell lines. In addition, we examined the expression of CD44, epithelial markers EpCAM and E-cadherin and tyrosine phosphoproteins. The labeling of these proteins correlates with the known biology of the cell lines. Our results demonstrate the utility of our method to screen for potential biomarkers and therapeutic targets in breast cancer and we suggest that CMAs be used as a general approach in breast cancer research.

Evaluation of cross-sample contamination in tissue microarrays by polymerase chain reaction

In the past decade, the popularity and power of Tissue Microarray (TMA) technology has increased since it provides a method to detect diagnostic and prognostic markers in an array of clinical tissue specimens collected for translational research. TMAs allow for rapid and cost-effective analysis of hundreds of molecular markers at the nucleic acid and protein levels. This technology is particularly useful in the realization of the Human Protein Atlas Project, since it aims to create a reference database of non-redundant human proteins. In this context, it is important to assure the lack of cross-sample contamination due to the repeated use of the same needle in consecutive coring. Here we show that carry-over contamination from one tissue core to another does not occur, reinforcing the accuracy of the TMA technology in the simultaneous testing of multiple bio-samples.

Generation of MHC class I diversity in primary tumors and selection of the malignant phenotype

Intratumor heterogeneity among cancer cells is promoted by reversible or irreversible genetic alterations and by different microenvironmental factors. There is considerable experimental evidence of the presence of a variety of malignant cell clones with a wide diversity of major histocompatibility class I (MHC-I) expression during early stages of tumor development. This variety of MHC-I phenotypes may define the evolution of a particular tumor. Loss of MHC-I molecules frequently results in immune escape of MHC-negative or -deficient tumor cells from the host T cell-mediated immune response. We review here the results obtained by our group and other researchers in animal models and humans, showing how MHC-I intratumor heterogeneity may affect local oncogenicity and metastatic progression. In particular, we summarize the data obtained in an experimental mouse cancer model of a methylcholanthrene-induced fibrosarcoma (GR9), in which isolated clones with different MHC-I expression patterns demonstrated distinct local tumor growth rates and metastatic capacities. The observed "explosion of diversity" of MHC-I phenotypes in primary tumor clones and the molecular mechanism ("hard"/irreversible or "soft"/reversible) responsible for a given MHC-I alteration might determine not only the metastatic capacity of the cells but also their response to immunotherapy. We also illustrate the generation of further MHC heterogeneity during metastatic colonization and discuss different strategies to favor tumor rejection by counteracting MHC-I loss. Finally, we highlight the role of MHC-I genes in tumor dormancy and cell cycle control.

Application of Tissue Microarray Technology to Stem Cell Research

There is virtually an unlimited number of possible Tissue Microarray (TMA) applications in basic and clinical research and ultimately in diagnostics. However, to assess the functional importance of novel markers, researchers very often turn to cell line model systems. The appropriate choice of a cell line is often a difficult task, but the use of cell microarray (CMA) technology enables a quick screening of several markers in cells of different origins, mimicking a genomic-scale analysis. In order to improve the morphological evaluations of the CMA slides we harvested the cells by conventional trypsinization, mechanical scraping and cells grown on coverslips. We show that mechanical scraping is a good evaluation method since keeps the real morphology very similar to those grown on coverslips. Immunofluorescence images are of higher quality, facilitating the reading of the biomarker cellular and subcellular localization. Here, we describe CMA technology in stem cell research.

Pancreatic Cancer Database: an integrative resource for pancreatic cancer

Pancreatic cancer is the fourth leading cause of cancer-related death in the world. The etiology of pancreatic cancer is heterogeneous with a wide range of alterations that have already been reported at the level of the genome, transcriptome, and proteome. The past decade has witnessed a large number of experimental studies using high-throughput technology platforms to identify genes whose expression at the transcript or protein levels is altered in pancreatic cancer. Based on expression studies, a number of molecules have also been proposed as potential biomarkers for diagnosis and prognosis of this deadly cancer. Currently, there are no repositories which provide an integrative view of multiple Omics data sets from published research on pancreatic cancer. Here, we describe the development of a web-based resource, Pancreatic Cancer Database (http://www.pancreaticcancerdatabase.org), as a unified platform for pancreatic cancer research. PCD contains manually curated information pertaining to quantitative alterations in miRNA, mRNA, and proteins obtained from small-scale as well as high-throughput studies of pancreatic cancer tissues and cell lines. We believe that PCD will serve as an integrative platform for scientific community involved in pancreatic cancer research.

An improved high-output cell microarray technology

AIMS

Cell microarray (CMA) is a high-throughput scientific research tool, which has greatly accelerated many analyses based at the cellular level. However, there are few described methods for constructing CMAs. Here, we introduce a new, simple, high-output CMA method that is applicable to a broad range of cellular samples.

METHODS

In this method, a recipient block (length, 3.6 cm; width, 2.7 cm; depth, 2 cm) with 40 dot markers was moulded using a transparent plastic box. Adenocarcinoma cells were collected from malignant pleural effusions, cell cylinders were moulded with plastic piping and the cylinders were manually arrayed one by one into the corresponding location of the 60 °C pre-softened recipient block using the guide holes drilled with a steel needle. We constructed a 40-cylinder CMA to prove this method. The expression of cytokeratin 7 (CK7) in the CMA was examined to confirm antigen preservation and epidermal growth factor receptor (EGFR) gene mutation was screened for in five samples.

RESULTS

The CMA prepared by this method had well-defined array configurations, good cellular morphology and well-preserved proteins and DNA. A total of 1000 sections could be easily gained from this CMA block.

CONCLUSIONS

This simple and low-cost method provides a novel way of preparing a high-output CMA.

Age- and sex-associated differences in the glycopatterns of human salivary glycoproteins and their roles against influenza A virus

Recent studies have elucidated that expression of certain glycoproteins in human saliva is increased or decreased according to age; meanwhile, human saliva may inhibit viral infection and prevent viral transmission. However, little is known about the age- and sex-associated differences in the glycopatterns of human salivary glycoproteins and their significant roles against influenza A virus (IVA). Here, we investigate the glycopatterns of human salivary glycoproteins with 180 healthy saliva samples divided into six age/sex groups using lectin microarrays and fabricate saliva microarrays to validate the terminal carbohydrate moieties of glycoproteins in individual saliva samples. Furthermore, we assess the inhibiting and neutralizing activity of saliva against two strains of influenza A (H9N2) virus. We find that seven lectins (e.g., MAL-II and SNA) show significant age differences in both females and males, and seven lectins (e.g., WFA and STL) show significant sex differences in children, adults and elderly people. Interestingly, we observe that elderly individuals have strongest resistance to IVA partly by presenting more terminal α2-3/6-linked sialic acid residues in their saliva, which bind with the influenza viral hemagglutinations. We conclude that age- and sex-associated differences in the glycopatterns of human salivary glycoproteins may provide pivotal information to help understand some age related diseases and physiological phenomena.

Pancreatic tumors and immature immunosuppressive myeloid cells in blood and spleen: role of inhibitory co-stimulatory molecules PDL1 and CTLA4. An in vivo and in vitro study

BACKGROUND

Blood and spleen expansion of immature myeloid cells (IMCs) might compromise the immune response to cancer. We studied in vivo circulating and splenic T lymphocyte and IMC subsets in patients with benign and malignant pancreatic diseases. We ascertained in vitro whether pancreatic adenocarcinoma (PDAC)-associated IMC subsets are induced by tumor-derived soluble factors and whether they are immunosuppressive focusing on the inhibitory co-stimulatory molecules PDL1 and CTLA4.

METHODOLOGY AND PRINCIPAL FINDINGS

103 pancreatic and/or splenic surgical patients were enrolled including 52 PDAC, 10 borderline and 10 neuroendocrine tumors (NETs). Lymphocytes and IMCs were analysed by flow cytometry in blood, in spleen and in three PDAC cell conditioned (CM) or non conditioned PBMC. PDL1 and CTLA4 were studied in 30 splenic samples, in control and conditioned PBMC. IMCs were FACS sorted and co-coltured with allogenic T lymphocytes. In PDAC a reduction was found in circulating CD8(+) lymphocytes (p = 0.004) and dendritic cells (p = 0.01), which were reduced in vitro by one PDAC CM (Capan1; p = 0.03). Blood myeloid derived suppressive cells (MDSCs) CD33(+)CD14(-)HLA-DR(-) were increased in PDAC (p = 0.022) and were induced in vitro by BxPC3 CM. Splenic dendritic cells had a higher PDL1 expression (p = 0.007), while CD33(+)CD14(+)HLA-DR(-) IMCs had a lower CTLA4 expression (p = 0.029) in PDAC patients. In vitro S100A8/A9 complex, one of the possible inflammatory mediators of immune suppression in PDAC, induced PDL1 (p = 0.018) and reduced CTLA4 expression (p = 0.028) among IMCs. IMCs not expressing CTLA4 were demonstrated to be immune suppressive.

CONCLUSION

In PDAC circulating dendritic and cytotoxic T cells are reduced, while MDSCs are increased and this might favour tumoral growth and progression. The reduced CTLA4 expression found among splenic IMCs of PDAC patients was demonstrated to characterize an immune suppressive phenotype and to be consequent to the direct exposure of myeloid cells to pancreatic cancer derived products, S100A8/A9 complex in particular.