Identification of Critical Pathways and Potential Key Genes in Poorly Differentiated Pancreatic Adenocarcinoma

A prognostic binary classifier comprised of five critical mRNAs stratified pancreatic cancer patients following resection

Background

Pancreatic cancer is characterized by an extremely poor prognosis, even following potentially curative resection. Classical prognostic markers such as histopathological or clinical parameters have limited predictive power. The present study aimed to establish a prognostic model combining mRNA expression data with histopathological and clinical data to better predict survival and stratify pancreatic cancer patients following resection. We pioneered three models in one study and systematically evaluated the clinical benefits of all three models.

Methods

To identify differentially expressed genes in pancreatic cancer, mRNA data from normal (GTEx database) and pancreatic cancer (TCGA database) tissues were used. Survival analysis was carried out to identify prognosis-relevant genes from the identified differentially expressed genes and LASSO regression was used to filter out hub genes. The risk score of several hub genes was calculated according to gene expression and coefficients. Validation was carried out using an independent set of GEO microarray data. Multivariate COX regression was used for identifying independent clinical and pathological risk factors related to patient's survival in the TCGA database and a prognostic model combining mRNA expression data with histopathological and clinical data was established. Another prognostic model using clinicopathological factors from the SEER database was conceived based on multivariate COX regression. NRI (net reclassification improvement) and IDI (integrated discrimination index) were used to compare the predictive capabilities of the different models.

Results

We identified 1589 differentially expressed genes (DEGs) through the comparison of normal and pancreatic cancer tissues, of whom 317 were associated with prognosis(p < 0.05). LASSO regression identified five hub genes, MYEOV, ANXA2P2, MET, CEP55, and KRT7, that were used for the five-mRNA-classifier prognostic model. The classifier could stratify patients into a short and long survival group: 5-year overall survival in the training set (TCGA, 6 % vs 52 %, p < 0.001), test set (TCGA, 18 % vs 55 %,p < 0.01) and external validation set (GEO, 0 % vs 25 %, p < 0.05). Sensitivity analysis showed that the mRNA model (model 1) was better than the clinicopathological no-mRNA model (model 2) in predicting 5-year survival in the TCGA database (AUC: 0.877 vs 0.718, z = 3.165, p < 0.01) and better than the multi-factor prognostic model (model 3) from the SEER database (AUC: 0.754, z = 2.637, p < 0.01). On predictive performance, model 1 improved model 2 (NRI = 0.084, z = 1.288, p = 0.198; IDI = 0.055, z = 1.041,p = 0.298) and model 3 (NRI = 0.167,z = 1.961,p = 0.05; IDI = 0.086, z = 1.427, p = 0.154).

Conclusion

The five-mRNA-classifier is a reliable and feasible instrument to predict the prognosis of pancreatic cancer patients following resection. It might help in patiens counseling and assist clinicians in providing individualized treatment for patients in different risk groups.

ECM1 and KRT6A are involved in tumor progression and chemoresistance in the effect of dexamethasone on pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) has a very poor prognosis. Neoadjuvant chemotherapy is an effective PDAC treatment option, but chemotherapy causes unfavorable side effects. Glucocorticoids (e.g., dexamethasone [DEX]) are administered to reduce side effects of chemotherapy for solid tumors, including pancreatic cancer. Glucocorticoids have both beneficial and detrimental effects, however. We investigated the functional changes and gene-expression profile alterations induced by DEX in PDAC cells. PDAC cells were treated with DEX, and the cell proliferation, migration, invasion, and chemosensitivity to gemcitabine (GEM) were evaluated. The results demonstrated decreased cell proliferative capacity, increased cell migration and invasion, and decreased sensitivity to GEM. A comprehensive genetic analysis revealed marked increases in ECM1 and KRT6A in DEX-treated PDAC cells. We evaluated the effects of ECM1 and KRT6A expression by using PDAC cells transfected with those genes. Neither ECM1 nor KRT6A changed the cells' proliferation, but each enhanced cell migration and invasion. ECM1 decreased sensitivity to GEM. We also assessed the clinicopathological significance of the expressions of ECM1 and KRT6A in 130 cases of PDAC. An immunohistochemical analysis showed that KRT6A expression dominated the poorly differentiated areas. High expressions of these two proteins in PDAC were associated with a poorer prognosis. Our results thus demonstrated that DEX treatment changed PDAC cells' functions, resulting in decreased cell proliferation, increased cell migration and invasion, and decreased sensitivity to GEM. The molecular mechanisms of these changes involve ECM1 and KRT6A, whose expressions are induced by DEX.

CT109-SN-38, a Novel Antibody-drug Conjugate with Dual Specificity for CEACAM5 and 6, Elicits Potent Killing of Pancreatic Cancer Cells

BACKGROUND

CEACAM5 and CEACAM6 are glycosylphosphatidylinositol (GPI)- linked members of the carcinoembryonic antigen-related cell adhesion molecule (CEACAM) family, which are frequently upregulated in epithelial cancers where they contribute to invasion, metastasis, immune evasion, and resistance to anoikis. CT109 is a novel antibody with dual specificity to both CEACAM5 and 6.

OBJECTIVES

In this study, we aimed to perform the preclinical characterization of CT109 and antibody- drug conjugate (ADCs) derivatives of CT109, focusing on CT109-SN-38.

METHODS

CT109's cognate epitope was characterized by scanning mutagenesis. CT109 specificity and internalization kinetics were assessed by immunoblot and flow cytometry, respectively. Cognate antigen expression prevalence in colorectal cancer and normal tissue arrays was determined by immunohistochemistry. CT109 conjugations were generated by the reaction of reduced CT109 cysteines with maleimide-functionalized payload linkers. In vitro cytotoxic activity of CT109 ADCs was characterized on antigen-positive and negative pancreatic ductal adenocarcinoma cell (PDAC) lines using a luminometric viability assay. In vivo efficacy of CT109-SN-38 was assessed on a PDAC tumor xenograft model at 10 and 25 mg/kg concentrations.

RESULTS

CT109 was shown to bind a glycoepitope centered on N309. CT109 is internalized in the CEACAM5+/CEACAM6+ double-positive PDAC line, BxPC-3, with a t1/2 of 2.3 hours. CT109 ADCs elicit a dose and antigen-dependent cytotoxic effect, with CT109-SN-38 exhibiting an IC50 value of 21 nM in BxPC-3 cells. In a BxPC-3 tumor xenograft model, CT109-SN-38 reduced tumor growth and induced regression in 3/10 mice at a concentration 25 mg/kg.

CONCLUSION

These data suggest that further preclinical and clinical development of CT109-SN-38 is warranted.

Emerging Prognostic and Predictive Significance of Stress Keratin 17 in HPV-Associated and Non HPV-Associated Human Cancers: A Scoping Review

A growing body of literature suggests that the expression of cytokeratin 17 (K17) correlates with inferior clinical outcomes across various cancer types. In this scoping review, we aimed to review and map the available clinical evidence of the prognostic and predictive value of K17 in human cancers. PubMed, Web of Science, Embase (via Scopus), Cochrane Central Register of Controlled Trials, and Google Scholar were searched for studies of K17 expression in human cancers. Eligible studies were peer-reviewed, published in English, presented original data, and directly evaluated the association between K17 and clinical outcomes in human cancers. Of the 1705 studies identified in our search, 58 studies met criteria for inclusion. Studies assessed the prognostic significance (n = 54), predictive significance (n = 2), or both the prognostic and predictive significance (n = 2). Altogether, 11 studies (19.0%) investigated the clinical relevance of K17 in cancers with a known etiologic association to HPV; of those, 8 (13.8%) were focused on head and neck squamous cell carcinoma (HNSCC), and 3 (5.1%) were focused on cervical squamous cell carcinoma (SCC). To date, HNSCC, as well as triple-negative breast cancer (TNBC) and pancreatic cancer, were the most frequently studied cancer types. K17 had prognostic significance in 16/17 investigated cancer types and 43/56 studies. Our analysis suggests that K17 is a negative prognostic factor in the majority of studied cancer types, including HPV-associated types such as HNSCC and cervical cancer (13/17), and a positive prognostic factor in 2/17 studied cancer types (urothelial carcinoma of the upper urinary tract and breast cancer). In three out of four predictive studies, K17 was a negative predictive factor for chemotherapy and immune checkpoint blockade therapy response.

Transcription factors TP63 facilitates malignant progression of thyroid cancer by upregulating KRT17 expression and inducing epithelial-mesenchymal transition

Thyroid cancer (TC) is a relatively prevalent endocrine tumor among women, the incidence of which is rapidly rising. In this present study, we aimed to provide new therapeutic targets from the aspect of transcription factor-target gene interaction. TP63 and KRT17 were both highly expressed in TC tissues and cells. The results of ChIP and dual-luciferase assays confirmed TP63 to bind the KRT17 promoter. Cell function assays revealed that knockdown of TP63 could repress TC cell progression. Furthermore, the rescue assay verified that TP63 could facilitate KRT17 expression to activate the AKT signaling pathway, which in turn stimulated TC cell invasion and migration, and induced EMT. All these results verified that TP63 facilitates TC malignant progression by promoting KRT17 expression and inducing EMT.

A Comprehensive Transcriptional Signature in Pancreatic Ductal Adenocarcinoma Reveals New Insights into the Immune and Desmoplastic Microenvironments

Pancreatic ductal adenocarcinoma (PDAC) prognoses and treatment responses remain devastatingly poor due partly to the highly heterogeneous, aggressive, and immunosuppressive nature of this tumor type. The intricate relationship between the stroma, inflammation, and immunity remains vaguely understood in the PDAC microenvironment. Here, we performed a meta-analysis of stroma-, and immune-related gene expression in the PDAC microenvironment to improve disease prognosis and therapeutic development. We selected 21 PDAC studies from the Gene Expression Omnibus and ArrayExpress databases, including 922 samples (320 controls and 602 cases). Differential gene enrichment analysis identified 1153 significant dysregulated genes in PDAC patients that contribute to a desmoplastic stroma and an immunosuppressive environment (the hallmarks of PDAC tumors). The results highlighted two gene signatures related to the immune and stromal environments that cluster PDAC patients into high- and low-risk groups, impacting patients' stratification and therapeutic decision making. Moreover, HCP5, SLFN13, IRF9, IFIT2, and IFI35 immune genes are related to the prognosis of PDAC patients for the first time.

Development and evaluation of a gold nanourchin (GNU)-based sandwich architecture for SERS immunosensing in liquid

Nanosensors represent a class of emerging promising nanotools that can be used for the rapid, sensitive and specific detection of relevant molecules such as biomarkers of cancer or other diseases. The sensing platforms that rely on the exceptional physical properties of colloidal gold nanoparticles have gained a special attraction and various architectural designs were proposed with the aim of rapid and real-time detection, identification and monitoring of the capturing events. Moreover, biomarker sensing in liquid samples allows a more facile implementation of the nanosensors by circumventing the need for invasive practices such as biopsies, in favor of non-invasive investigations with potential for use as point-of-care assays. Herein, we propose a sandwich-type surface enhanced Raman scattering (SERS) immuno-nanosensor which is aimed for detecting and quantifying Carcinoembryonic antigen-related cell adhesion molecule 5 (CEA-CAM5), a protein involved in intercellular adhesion and signaling pathways that acts as a tumor marker in several types of cancer. For constructing the proposed system, colloidal gold nano spheres (GNS) and gold nano-urchins (GNU) were chemically synthesized, labeled with SERS active molecules, conjugated with polymers, functionalized with antibodies as capturing substrates and tested in two different sensing configurations: pairs of GNUs-GNUs and GNUs-GNSs. When the target antigen is present in the analyte solution, nanoparticle bridging occurs and a subsequent amplification of the characteristic Raman signal of the label molecule appears due to the formation of hot-spots in interparticle gaps. The capability of observing small analyte concentrations in liquid samples with an easy-to-handle portable Raman device makes the proposed system feasible for rapid, non-invasive and cost-effective clinical or laboratory use.

Common and differential features of liver and pancreatic cancers: molecular mechanism approach

AIM

The aim of this study was to introduce biomarkers commonly involved in pancreatic cancer metastasis to the liver.

BACKGROUND

The liver is affected by metastatic disease in pancreatic cancer.

METHODS

Two cancer biomarkers were distinguished through a STRING database protein query. The dysregulated proteins of the two cancers were included in 2 networks drawn by Cytoscape software v 3.2.7. 20 top nodes and achieved by the Network analyzer application of Cytoscape based on degree value. The common hub nodes were determined, and action maps were analyzed.

RESULTS

Among 20 hubs of each studied cancer, 18 common hub nodes (90% of hubs) were identified and screened by action maps. Four proteins, AKT1, CDKN2A, ERBB2, and IL6, were identified as common central proteins related to the two studied diseases.

CONCLUSION

AKT1, CDKN2A, ERBB2, and IL6 are common protein core of liver and pancreatic cancers, while STAT3, CASP3, NOTCH1, and CTNNB1 are possible differential proteins to discriminate these cancers.