MicroRNA-200c modulates the expression of MUC4 and MUC16 by directly targeting their coding sequences in human pancreatic cancer.

Transmembrane mucins, MUC4 and MUC16 are associated with tumor progression and metastatic potential in human pancreatic adenocarcinoma. We discovered that miR-200c interacts with specific sequences within the coding sequence of MUC4 and MUC16 mRNAs, and evaluated the regulatory nature of this association. Pancreatic cancer cell lines S2.028 and T3M-4 transfected with miR-200c showed a 4.18 and 8.50 fold down regulation of MUC4 mRNA, and 4.68 and 4.82 fold down regulation of MUC16 mRNA compared to mock-transfected cells, respectively. A significant reduction of glycoprotein expression was also observed. These results indicate that miR-200c overexpression regulates MUC4 and MUC16 mucins in pancreatic cancer cells by directly targeting the mRNA coding sequence of each, resulting in reduced levels of MUC4 and MUC16 mRNA and protein. These data suggest that, in addition to regulating proteins that modulate EMT, miR-200c influences expression of cell surface mucins in pancreatic cancer

Machine Learning Analyses of Highly-Multiplexed Immunofluorescence Identifies Distinct Tumor and Stromal Cell Populations in Primary Pancreatic Tumors

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge for patients and clinicians. OBJECTIVE: To analyze the distribution of 31 different markers in tumor and stromal portions of the tumor microenvironment (TME) and identify immune cell populations to better understand how neoplastic, non-malignant structural, and immune cells, diversify the TME and influence PDAC progression. METHODS: Whole slide imaging (WSI) and cyclic multiplexed-immunofluorescence (MxIF) was used to collect 31 different markers over the course of nine distinctive imaging series of human PDAC samples. Image registration and machine learning algorithms were developed to largely automate an imaging analysis pipeline identifying distinct cell types in the TME. RESULTS: A random forest algorithm accurately predicted tumor and stromal-rich areas with 87% accuracy using 31 markers and 77% accuracy using only five markers. Top tumor-predictive markers guided downstream analyses to identify immune populations effectively invading into the tumor, including dendritic cells, CD4+ T cells, and multiple immunoregulatory subtypes. CONCLUSIONS: Immunoprofiling of PDAC to identify differential distribution of immune cells in the TME is critical for understanding disease progression, response and/or resistance to treatment, and the development of new treatment strategies

Ubiquitous Aberration in Cholesterol Metabolism Across Pancreatic Ductal Adenocarcinoma

Pancreatic cancer (PC) is characterized by metabolic deregulations that often manifest as deviations in metabolite levels and aberrations in their corresponding metabolic genes across the clinical specimens and preclinical PC models. Cholesterol is one of the critical metabolites supporting PC, synthesized or acquired by PC cells. Nevertheless, the significance of the de novo cholesterol synthesis pathway has been controversial in PC, indicating the need to reassess this pathway in PC. We utilized preclinical models and clinical specimens of PC patients and cell lines and utilized mass spectrometry-based sterol analysis. Further, we also performed in silico analysis to corroborate the significance of de novo cholesterol synthesis pathway in PC. Our results demonstrated alteration in free sterol levels, including free cholesterol, across in vitro, in vivo, and clinical specimens of PC. Especially, our sterol analyses established consistent alterations in free cholesterol across the different PC models. Overall, this study demonstrates the significance and consistency in deviation of cholesterol synthesis pathway in PC while showing the aberrations in sterol metabolite intermediates and the related genes using preclinical models, in silico platforms, and the clinical specimens

Trefoil Factor(s) and CA19.9: A Promising Panel for Early Detection of Pancreatic Cancer

BACKGROUND: Trefoil factors (TFF1, TFF2, and TFF3) are small secretory molecules that recently have gained significant attention in multiple studies as an integral component of pancreatic cancer (PC) subtype-specific gene signature. Here, we comprehensively investigated the diagnostic potential of all the member of trefoil family, i.e., TFF1, TFF2, and TFF3 in combination with CA19.9 for detection of PC. METHODS: Trefoil factors (TFFs) gene expression was analyzed in publicly available cancer genome datasets, followed by assessment of their expression in genetically engineered spontaneous mouse model (GEM) of PC (KrasG12D; Pdx1-Cre (KC)) and in human tissue microarray consisting of normal pancreas adjacent to tumor (NAT), precursor lesions (PanIN), and various pathological grades of PC by immunohistochemistry (IHC). Serum TFFs and CA19.9 levels were evaluated via ELISA in comprehensive sample set (n = 362) comprised of independent training and validation sets each containing benign controls (BC), chronic pancreatitis (CP), and various stages of PC. Univariate and multivariate logistic regression and receiver operating characteristic curves (ROC) were used to examine their diagnostic potential both alone and in combination with CA19.9. FINDINGS: The publicly available datasets and expression analysis revealed significant increased expression of TFF1, TFF2, and TFF3 in human PanINs and PC tissues. Assessment of KC mouse model also suggested upregulated expression of TFFs in PanIN lesions and early stage of PC. In serum analyses studies, TFF1 and TFF2 were significantly elevated in early stages of PC in comparison to benign and CP control group while significant elevation in TFF3 levels were observed in CP group with no further elevation in its level in early stage PC group. In receiver operating curve (ROC) analyses, combination of TFFs with CA19.9 emerged as promising panel for discriminating early stage of PC (EPC) from BC (AUC INTERPRETATION: In silico, tissue and serum analyses validated significantly increased level of all TFFs in precursor lesions and early stages of PC. The combination of TFFs enhanced sensitivity and specificity of CA19.9 to discriminate early stage of PC from benign control and chronic pancreatitis groups

Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to inefficient diagnosis and tenacious drug resistance. Activation of pancreatic stellate cells (PSCs) and consequent development of dense stroma are prominent features accounting for this aggressive biology1,2. The reciprocal interplay between PSCs and pancreatic cancer cells (PCCs) not only enhances tumour progression and metastasis but also sustains their own activation, facilitating a vicious cycle to exacerbate tumorigenesis and drug resistance3-7. Furthermore, PSC activation occurs very early during PDAC tumorigenesis8-10, and activated PSCs comprise a substantial fraction of the tumour mass, providing a rich source of readily detectable factors. Therefore, we hypothesized that the communication between PSCs and PCCs could be an exploitable target to develop effective strategies for PDAC therapy and diagnosis. Here, starting with a systematic proteomic investigation of secreted disease mediators and underlying molecular mechanisms, we reveal that leukaemia inhibitory factor (LIF) is a key paracrine factor from activated PSCs acting on cancer cells. Both pharmacologic LIF blockade and genetic Lifr deletion markedly slow tumour progression and augment the efficacy of chemotherapy to prolong survival of PDAC mouse models, mainly by modulating cancer cell differentiation and epithelial-mesenchymal transition status. Moreover, in both mouse models and human PDAC, aberrant production of LIF in the pancreas is restricted to pathological conditions and correlates with PDAC pathogenesis, and changes in the levels of circulating LIF correlate well with tumour response to therapy. Collectively, these findings reveal a function of LIF in PDAC tumorigenesis, and suggest its translational potential as an attractive therapeutic target and circulating marker. Our studies underscore how a better understanding of cell-cell communication within the tumour microenvironment can suggest novel strategies for cancer therapy

MicroRNA-200c Modulates the Expression of MUC4 and MUC16 by Directly Targeting Their Coding Sequences in Human Pancreatic Cancer

<div><p>Transmembrane mucins, MUC4 and MUC16 are associated with tumor progression and metastatic potential in human pancreatic adenocarcinoma. We discovered that miR-200c interacts with specific sequences within the coding sequence of MUC4 and MUC16 mRNAs, and evaluated the regulatory nature of this association. Pancreatic cancer cell lines S2.028 and T3M-4 transfected with miR-200c showed a 4.18 and 8.50 fold down regulation of MUC4 mRNA, and 4.68 and 4.82 fold down regulation of MUC16 mRNA compared to mock-transfected cells, respectively. A significant reduction of glycoprotein expression was also observed. These results indicate that miR-200c overexpression regulates MUC4 and MUC16 mucins in pancreatic cancer cells by directly targeting the mRNA coding sequence of each, resulting in reduced levels of MUC4 and MUC16 mRNA and protein. These data suggest that, in addition to regulating proteins that modulate EMT, miR-200c influences expression of cell surface mucins in pancreatic cancer.</p> </div

microRNA-200c targets MUC16.

<p>(A) S2.028 and (B) T3M-4-miR200c and respective vector control transfected cell lysates were separated by SDS-Agarose gel electrophoresis and subjected to western blot using an anti-MUC16 antibody (left panels). Band intensity was quantified by densitometry and analyzed using the imageJ program (right panels). Significant reductions of both high and low molecular weight MUC16 protein isoforms were observed in miR-200c expressing S2.028 (A) and T3M-4 cells (B) than compared to vector control cells. α-tubulin was used as a loading control.</p

Prediction of miR-200c interaction sites in MUC4 and MUC16 genes.

<p>Possible miR-200c targeting regions in MUC4 and MUC16 were identified by using the RegRNA MicroRNA target prediction web server (<a href="http://regrna.mbc.nctu.edu.tw/index1.php" target="_blank"><u>http://regrna.mbc.nctu.edu.tw/index1.php</u></a>). A, RegRNA miRNA target prediction shows that miR-200c binds between base pairs 820-842 in the first exon of MUC4. B, In MUC16 mRNA, the miR-200c is predicted to bind nine different exons including E1, E3, E19, E39, E44, E49, E54, E64 and E73. The numbers indicate the region of mRNAs that interact with miR-200c.</p

Quantitative analysis of miR-200c expression in human pancreatic cancer cell lines and ectopic expression of miR-200c in S2.028 and T3M-4 cells.

<p>(A) The expression of miR-200c in seven pancreatic cancer cells were determined by Real-time PCR. Each sample was run in quadruplicate and error bars represent SD. S2.028 (B) and T3M-4 cells (C) stably expressing the primary transcript of miR-200c were evaluated for miR-200c expression by Real-time PCR. Each measurement was carried out in triplicate. These values were normalized with internal control U6 rRNA. The fold increase in transcript levels over vector control is expressed as Mean ± S.D. The p value was determined by using the Student’s t-test. Differences with a p value < 0.05 were considered statistically significant.</p