Contribution of FKBP5 genetic variation to gemcitabine treatment and survival in pancreatic adenocarcinoma

CAPN2-responsive mesoporous silica nanoparticles: A promising nanocarrier for targeted therapy of pancreatic cancer

Pancreatic adenocarcinoma (PDAC) is highly resistant to conventional chemotherapeutic interventions, resulting in exceptionally low survival rates. The limited efficacy can in part be attributed to dose limitations and treatment cessation urged by toxicity of currently used chemotherapy. The advent of targeted delivery strategies has kindled hope for circumventing off-target toxicity. We have previously reported a PDAC-specific mesoporous silica nanoparticle (MSN) containing a protease linker responsive to ADAM9, a PDAC-enriched extracellularly deposited protease. Upon loading with paclitaxel these ADAM9-MSNs reduced side effects both in vitro and in vivo, however, disappointing antitumor efficacy was observed in vivo. Here, we propose that an efficient uptake of MSNs by tumor cells might underlie the lack of antitumor efficacy of MSNs functionalized with linker responsive to extracellular proteases. Harnessing this premise to improve antitumor efficacy, we performed an in silico analysis to identify PDAC-enriched intracellular proteases. We report the identification of BACE2, CAPN2 and DPP3 as PDAC enriched intracellular proteases, and report the synthesis of BACE2-, CAPN2- and DPP3-responsive MSNs. Extensive preclinical assessments revealed that paclitaxel-loaded CAPN2- and DPP3-MSNs exhibit high PDAC specificity in vitro as opposed to free paclitaxel. The administration of paclitaxel-loaded CAPN2- and DPP3-MSNs in vivo confirmed the reduction of leukopenia and induced no organ damage. Promisingly, in two mouse models CAPN2-MSNs reduced tumor growth at least as efficiently as free paclitaxel. Taken together, our results pose CAPN2-MSNs as a promising nanocarrier for the targeted delivery of chemotherapeutics in PDAC.

Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains highly lethal due to limited therapeutic options and expensive/burdensome drug discovery processes. Utilizing genomic-data-driven Connectivity Mapping (CMAP) to identify a drug closer to real-world PC targeting may improve pancreatic cancer (PC) patient outcomes. Initially, we mapped CMAP data to gene expression from 106 PC patients, identifying nine negatively connected drugs. These drugs were further narrowed down using a similar analysis for PC cell lines, human tumoroids, and patient-derived xenografts datasets, where ISOX emerged as the most potent agent to target PC. We used human and mouse syngeneic PC cells, human and mouse tumoroids, and in vivo mice to assess the ability of ISOX alone and in combination with 5FU to inhibit tumor growth. Global transcriptomic and pathway analysis of the ISOX-LINCS signature identified HDAC 6/cMyc as the target axis for ISOX. Specifically, we discovered that genetic and pharmacological targeting of HDAC 6 affected non-histone protein cMyc acetylation, leading to cMyc instability, thereby disrupting PC growth and metastasis by affecting cancer stemness. Finally, KrasG12D harboring tumoroids and mice responded effectively against ISOX and 5FU treatment by enhancing survival and controlling metastasis incidence. Overall, our data validate ISOX as a new drug to treat advanced PC patients without toxicity to normal cells. Our study supports the clinical utility of ISOX along with 5FU in future PC clinical trials.

MICAL2 implies immunosuppressive features and acts as an independent and adverse prognostic biomarker in pancreatic cancer

At present, clinical outcomes of pancreatic cancer patients are still poor. New therapeutic targets for pancreatic cancer are urgently needed. Previous studies have indicated that Microtubule Associated Monooxygenase, Calponin and LIM Domain Containing 2 (MICAL2) is highly expressed in many tumors and promotes tumor progression. However, the role played by MICAL2 in pancreatic cancer remains unclear. Based on gene expression and clinical information from multiple datasets, we used comprehensive bioinformatics analysis in combination with tissue microarray to explore the function and clinical value of MICAL2. The results showed that MICAL2 was highly expressed in pancreatic cancer tissue and exhibited potential diagnostic capability. High expression of MICAL2 was also associated with poor prognosis and acted as an independent prognostic factor. MICAL2, mainly expressed in fibroblasts of pancreatic cancer, was closely related to metastasis and immune-related features, such as epithelial-mesenchymal transformation, extracellular cell matrix degradation, and inflammatory response. Furthermore, higher MICAL2 expression in pancreatic cancer was also associated with an increase in cancer-associated fibroblasts as well as M2 macrophage infiltration, and a reduction in CD8 + T cell infiltration, thereby facilitating the formation of an immunosuppressive microenvironment. Our results helped elucidate the clinical value and function in metastasis and immunity of MICAL2 in pancreatic cancer. These findings provided potential clinical strategies for diagnosis, targeted therapy combination immunotherapy, and prognosis in patients with pancreatic cancer.

Imatinib facilitates gemcitabine sensitivity by targeting epigenetically activated PDGFC signaling in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with poor prognosis. Gemcitabine-based chemotherapy has become one of the main modalities of its management. However, gemcitabine resistance frequently occurs, leading to failure of PDAC therapy. Platelet-derived growth factors (PDGFs) and their receptors play important roles in cancer progression and chemoresistance. We aimed to investigate the biological function and therapeutic significance of platelet-derived growth factor C (PDGFC) in drug-resistant PDAC. Our study showed that PDGFC was abnormally highly expressed in gemcitabine-resistant PDAC. Silencing PDGFC expression can enhance the therapeutic effect of gemcitabine on PDAC. Mechanistically, the transcription of PDGFC is mediated by H3K27 acetylation, and PDGFC promotes gemcitabine resistance by activating the PDGFR-PI3K-AKT signaling pathway. The PDGFR inhibitor imatinib inhibits the PDGFR pathway. Imatinib and gemcitabine have a synergistic effect on the treatment of PDAC, and imatinib can significantly enhance the anti-tumor effect of gemcitabine in a drug-resistant PDAC patient-derived xenograft model. In conclusion, PDGFC is a potential predictor of gemcitabine-resistant PDAC. Imatinib inhibits PDGFR activation to promote gemcitabine sensitivity in PDAC. Combined modality regimen of imatinib and gemcitabine is likely to translate into clinical trial for the treatment of PDGFC-associated gemcitabine-resistant patients.

FASN multi-omic characterization reveals metabolic heterogeneity in pancreatic and prostate adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) and prostate cancer (PCa) are among the most prevalent malignant tumors worldwide. There is now a comprehensive understanding of metabolic reprogramming as a hallmark of cancer. Fatty acid synthase (FASN) is a key regulator of the lipid metabolic network, providing energy to favor tumor proliferation and development. Whereas the biological role of FASN is known, its response and sensitivity to inhibition have not yet been fully established in these two cancer settings.

METHODS

To evaluate the association between FASN expression, methylation, prognosis, and mutational profile in PDAC and PCa, we interrogated public databases and surveyed online platforms using TCGA data. The STRING database was used to investigate FASN interactors, and the Gene Set Enrichment Analysis platform Reactome database was used to perform an enrichment analysis using data from RNA sequencing public databases of PDAC and PCa. In vitro models using PDAC and PCa cell lines were used to corroborate the expression of FASN, as shown by Western blot, and the effects of FASN inhibition on cell proliferation/cell cycle progression and mitochondrial respiration were investigated with MTT, colony formation assay, cell cycle analysis and MitoStress Test.

RESULTS

The expression of FASN was not modulated in PDAC compared to normal pancreatic tissues, while it was overexpressed in PCa, which also displayed a different level of promoter methylation. Based on tumor grade, FASN expression decreased in advanced stages of PDAC, but increased in PCa. A low incidence of FASN mutations was found for both tumors. FASN was overexpressed in PCa, despite not reaching statistical significance, and was associated with a worse prognosis than in PDAC. The biological role of FASN interactors correlated with lipid metabolism, and GSEA indicated that lipid-mediated mitochondrial respiration was enriched in PCa. Following validation of FASN overexpression in PCa compared to PDAC in vitro, we tested TVB-2640 as a FASN inhibitor. PCa proliferation arrest was modulated by FASN inhibition in a dose- and time-dependent manner, whereas PDAC proliferation was not altered. In line with this finding, mitochondrial respiration was found to be more affected in PCa than in PDAC. FASN inhibition interfered with metabolic signaling causing lipid accumulation and affecting cell viability with an impact on the replicative processes.

CONCLUSIONS

FASN exhibited differential expression patterns in PDAC and PCa, suggesting a different evolution during cancer progression. This was corroborated by the fact that both tumors responded differently to FASN inhibition in terms of proliferative potential and mitochondrial respiration, indicating that its use should reflect context specificity.

Robust identification of common genomic biomarkers from multiple gene expression profiles for the prognosis, diagnosis, and therapies of pancreatic cancer

Pancreatic cancer (PC) is one of the leading causes of cancer-related death globally. So, identification of potential molecular signatures is required for diagnosis, prognosis, and therapies of PC. In this study, we detected 71 common differentially expressed genes (cDEGs) between PC and control samples from four microarray gene-expression datasets (GSE15471, GSE16515, GSE71989, and GSE22780) by using robust statistical and machine learning approaches, since microarray gene-expression datasets are often contaminated by outliers due to several steps involved in the data generating processes. Then we detected 8 cDEGs (ADAM10, COL1A2, FN1, P4HB, ITGB1, ITGB5, ANXA2, and MYOF) as the PC-causing key genes (KGs) by the protein-protein interaction (PPI) network analysis. We validated the expression patterns of KGs between case and control samples by box plot analysis with the TCGA and GTEx databases. The proposed KGs showed high prognostic power with the random forest (RF) based prediction model and Kaplan-Meier-based survival probability curve. The KGs regulatory network analysis detected few transcriptional and post-transcriptional regulators for KGs. The cDEGs-set enrichment analysis revealed some crucial PC-causing molecular functions, biological processes, cellular components, and pathways that are associated with KGs. Finally, we suggested KGs-guided five repurposable drug molecules (Linsitinib, CX5461, Irinotecan, Timosaponin AIII, and Olaparib) and a new molecule (NVP-BHG712) against PC by molecular docking. The stability of the top three protein-ligand complexes was confirmed by molecular dynamic (MD) simulation studies. The cross-validation and some literature reviews also supported our findings. Therefore, the finding of this study might be useful resources to the researchers and medical doctors for diagnosis, prognosis and therapies of PC by the wet-lab validation.

The Scaffold Immunophilin FKBP51 Is a Phosphoprotein That Undergoes Dynamic Mitochondrial-Nuclear Shuttling

The immunophilin FKBP51 forms heterocomplexes with molecular chaperones, protein-kinases, protein-phosphatases, autophagy-related factors, and transcription factors. Like most scaffold proteins, FKBP51 can use a simple tethering mechanism to favor the efficiency of interactions with partner molecules, but it can also exert more complex allosteric controls over client factors, the immunophilin itself being a putative regulation target. One of the simplest strategies for regulating pathways and subcellular localization of proteins is phosphorylation. In this study, it is shown that scaffold immunophilin FKBP51 is resolved by resolutive electrophoresis in various phosphorylated isoforms. This was evidenced by their reactivity with specific anti-phosphoamino acid antibodies and their fade-out by treatment with alkaline phosphatase. Interestingly, stress situations such as exposure to oxidants or in vivo fasting favors FKBP51 translocation from mitochondria to the nucleus. While fasting involves phosphothreonine residues, oxidative stress involves tyrosine residues. Molecular modeling predicts the existence of potential targets located at the FK1 domain of the immunophilin. Thus, oxidative stress favors FKBP51 dephosphorylation and protein degradation by the proteasome, whereas FK506 binding protects the persistence of the post-translational modification in tyrosine, leading to FKBP51 stability under oxidative conditions. Therefore, FKBP51 is revealed as a phosphoprotein that undergoes differential phosphorylations according to the stimulus.

Single Cell RNA-Seq Identifies Immune-Related Prognostic Model and Key Signature-SPP1 in Pancreatic Ductal Adenocarcinoma

There are no reliable biomarkers for early diagnosis or prognosis evaluation in pancreatic ductal adenocarcinoma (PDAC). Multiple scRNA-seq datasets for PDAC were retrieved from online databases and combined with scRNA-seq results from our previous study. The malignant ductal cells were identified through calculating copy number variation (CNV) scores. The robust markers of malignant ductal cells in PDAC were found. Five immune-related signatures, including SPP1, LINC00683, SNHG10, LINC00237, and CASC19, were used to develop a risk score formula to predict the overall survival of PDAC patients. We also constructed an easy-to-use nomogram, combining risk score, N stage, and margin status. The expression level of SPP1 was related to the prognosis and immune regulators. We found that SPP1 was mainly expressed in ductal cells and macrophages in PDAC. In conclusion, we constructed a promising prognostic model based on immune-related signatures for PDAC using scRNA-seq and TCGA_PAAD datasets.

Assessing equivalent and inverse change in genes between diverse experiments

Background: It is important to identify when two exposures impact a molecular marker (e.g., a gene's expression) in similar ways, for example, to learn that a new drug has a similar effect to an existing drug. Currently, statistically robust approaches for making comparisons of equivalence of effect sizes obtained from two independently run treatment vs. control comparisons have not been developed. Results: Here, we propose two approaches for evaluating the question of equivalence between effect sizes of two independent studies: a bootstrap test of the Equivalent Change Index (ECI), which we previously developed, and performing Two One-Sided t-Tests (TOST) on the difference in log-fold changes directly. The ECI of a gene is computed by taking the ratio of the effect size estimates obtained from the two different studies, weighted by the maximum of the two p-values and giving it a sign indicating if the effects are in the same or opposite directions, whereas TOST is a test of whether the difference in log-fold changes lies outside a region of equivalence. We used a series of simulation studies to compare the two tests on the basis of sensitivity, specificity, balanced accuracy, and F1-score. We found that TOST is not efficient for identifying equivalently changed gene expression values (F1-score = 0) because it is too conservative, while the ECI bootstrap test shows good performance (F1-score = 0.95). Furthermore, applying the ECI bootstrap test and TOST to publicly available microarray expression data from pancreatic cancer showed that, while TOST was not able to identify any equivalently or inversely changed genes, the ECI bootstrap test identified genes associated with pancreatic cancer. Additionally, when investigating publicly available RNAseq data of smoking vs. vaping, no equivalently changed genes were identified by TOST, but ECI bootstrap test identified genes associated with smoking. Conclusion: A bootstrap test of the ECI is a promising new statistical approach for determining if two diverse studies show similarity in the differential expression of genes and can help to identify genes which are similarly influenced by a specific treatment or exposure. The R package for the ECI bootstrap test is available at https://github.com/Hecate08/ECIbootstrap.

Domination based classification algorithms for the controllability analysis of biological interaction networks

Deciding the size of a minimum dominating set is a classic NP-complete problem. It has found increasing utility as the basis for classifying vertices in networks derived from protein-protein, noncoding RNA, metabolic, and other biological interaction data. In this context it can be helpful, for example, to identify those vertices that must be present in any minimum solution. Current classification methods, however, can require solving as many instances as there are vertices, rendering them computationally prohibitive in many applications. In an effort to address this shortcoming, new classification algorithms are derived and tested for efficiency and effectiveness. Results of performance comparisons on real-world biological networks are reported.

Identification of Key Deregulated RNA-Binding Proteins in Pancreatic Cancer by Meta-Analysis and Prediction of Their Role as Modulators of Oncogenesis

RNA-binding proteins (RBPs) play a significant role in multiple cellular processes with their deregulations strongly associated with cancer. However, there are not adequate evidences regarding global alteration and functions of RBPs in pancreatic cancer, interrogated in a systematic manner. In this study, we have prepared an exhaustive list of RBPs from multiple sources, downloaded gene expression microarray data from a total of 241 pancreatic tumors and 124 normal pancreatic tissues, performed a meta-analysis, and obtained differentially expressed RBPs (DE-RBPs) using the Limma package of R Bioconductor. The results were validated in microarray datasets and the Cancer Genome Atlas (TCGA) RNA sequencing dataset for pancreatic adenocarcinoma (PAAD). Pathway enrichment analysis was performed using DE-RBPs, and we also constructed the protein-protein interaction (PPI) network to detect key modules and hub-RBPs. Coding and noncoding targets for top altered and hub RBPs were identified, and altered pathways modulated by these targets were also investigated. Our meta-analysis identified 45 upregulated and 15 downregulated RBPs as differentially expressed in pancreatic cancer, and pathway enrichment analysis demonstrated their important contribution in tumor development. As a result of PPI network analysis, 26 hub RBPs were detected and coding and noncoding targets for all these RBPs were categorized. Functional exploration characterized the pathways related to epithelial-to-mesenchymal transition (EMT), cell migration, and metastasis to emerge as major pathways interfered by the targets of these RBPs. Our study identified a unique meta-signature of 26 hub-RBPs to primarily modulate pancreatic tumor cell migration and metastasis in pancreatic cancer. IGF2BP3, ISG20, NIP7, PRDX1, RCC2, RUVBL1, SNRPD1, PAIP2B, and SIDT2 were found to play the most prominent role in the regulation of EMT in the process. The findings not only contribute to understand the biology of RBPs in pancreatic cancer but also to evaluate their candidature as possible therapeutic targets.

Interferon alpha-inducible protein 27 (IFI27) is a prognostic marker for pancreatic cancer based on comprehensive bioinformatics analysis

Accurate biomarkers to predict the genesis and progression of pancreatic adenocarcinoma (PAAD) are needed in the fight against this deadly disease. Here, we combined multiple datasets (GEO, TCGA and GTEx) to conduct a comprehensive analysis of pancreatic cancer. Through an in-depth analysis, we discovered that the expression of the gene encoding interferon alpha-inducible protein 27 (IFI27) was significantly higher in pancreatic cancer tissues than that in normal tissues, and that higher expression of IFI27 was negatively correlated with the overall survival rate of pancreatic cancer patients. The functional annotation of IFI27 demonstrated relationships to cellular immunity and metabolism, especially glycolysis. Analysis of infiltrating immune cells displayed that higher expression of IFI27 expression correlates with decreased CD8 + T cells and increased M2 macrophages in the tumor immune microenvironment (TIME), then biochemical analyses of a mouse model and immunohistochemical (IHC) staining verified that glycolytic enzymes and M2 macrophages increased significantly in pancreatic cancer tissues. We speculate that IFI27 may affect the tumor microenvironment (TME) of PAAD by regulating cellular immunity and metabolism, thereby promoting the progression of pancreatic carcinoma and worsening the prognosis. These findings of our present study are solid evidence that IFI27 is a potential prognostic biomarker of pancreatic cancer and that it affects the tumor immune microenvironment.

Stress-Responsive Gene FK506-Binding Protein 51 Mediates Alcohol-Induced Liver Injury Through the Hippo Pathway and Chemokine (C-X-C Motif) Ligand 1 Signaling

BACKGROUND AND AIMS

Chronic alcohol drinking is a major risk factor for alcohol-associated liver disease (ALD). FK506-binding protein 51 (FKBP5), a cochaperone protein, is involved in many key regulatory pathways. It is known to be involved in stress-related disorders, but there are no reports regarding its role in ALD. This present study aimed to examine the molecular mechanism of FKBP5 in ALD.

APPROACH AND RESULTS

We found a significant increase in hepatic FKBP5 transcripts and protein expression in patients with ALD and mice fed with chronic-plus-single binge ethanol. Loss of Fkbp5 in mice protected against alcohol-induced hepatic steatosis and inflammation. Transcriptomic analysis revealed a significant reduction of Transcriptional enhancer factor TEF-1 (TEA) domain transcription factor 1 (Tead1) and chemokine (C-X-C motif) ligand 1 (Cxcl1) mRNA in ethanol-fed Fkbp5-/- mice. Ethanol-induced Fkbp5 expression was secondary to down-regulation of methylation level at its 5' untranslated promoter region. The increase in Fkbp5 expression led to induction in transcription factor TEAD1 through Hippo signaling pathway. Fkbp5 can interact with yes-associated protein (YAP) upstream kinase, mammalian Ste20-like kinase 1 (MST1), affecting its ability to phosphorylate YAP and the inhibitory effect of hepatic YAP phosphorylation by ethanol leading to YAP nuclear translocation and TEAD1 activation. Activation of TEAD1 led to increased expression of its target, CXCL1, a chemokine-mediated neutrophil recruitment, causing hepatic inflammation and neutrophil infiltration in our mouse model.

CONCLUSIONS

We identified an FKBP5-YAP-TEAD1-CXCL1 axis in the pathogenesis of ALD. Loss of FKBP5 ameliorates alcohol-induced liver injury through the Hippo pathway and CXCL1 signaling, suggesting its potential role as a target for the treatment of ALD.

ADAM9-Responsive Mesoporous Silica Nanoparticles for Targeted Drug Delivery in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) has the worst survival rate of all cancers. This poor prognosis results from the lack of efficient systemic treatment regimens, demanding high-dose chemotherapy that causes severe side effects. To overcome dose-dependent toxicities, we explored the efficacy of targeted drug delivery using a protease-dependent drug-release system. To this end, we developed a PDAC-specific drug delivery system based on mesoporous silica nanoparticles (MSN) functionalized with an avidin-biotin gatekeeper system containing a protease linker that is specifically cleaved by tumor cells. Bioinformatic analysis identified ADAM9 as a PDAC-enriched protease, and PDAC cell-derived conditioned medium efficiently cleaved protease linkers containing ADAM9 substrates. Cleavage was PDAC specific as conditioned medium from leukocytes was unable to cleave the ADAM9 substrate. Protease linker-functionalized MSNs were efficiently capped with avidin, and cap removal was confirmed to occur in the presence of PDAC cell-derived ADAM9. Subsequent treatment of PDAC cells in vitro with paclitaxel-loaded MSNs indeed showed high cytotoxicity, whereas no cell death was observed in white blood cell-derived cell lines, confirming efficacy of the nanoparticle-mediated drug delivery system. Taken together, this research introduces a novel ADAM9-responsive, protease-dependent, drug delivery system for PDAC as a promising tool to reduce the cytotoxicity of systemic chemotherapy.

Extending the lymphoblastoid cell line model for drug combination pharmacogenomics

Combination drug therapies have become an integral part of precision oncology, and while evidence of clinical effectiveness continues to grow, the underlying mechanisms supporting synergy are poorly understood. Immortalized human lymphoblastoid cell lines (LCLs) have been proven as a particularly useful, scalable and low-cost model in pharmacogenetics research, and are suitable for elucidating the molecular mechanisms of synergistic combination therapies. In this review, we cover the advantages of LCLs in synergy pharmacogenomics and consider recent studies providing initial evidence of the utility of LCLs in synergy research. We also discuss several opportunities for LCL-based systems to address gaps in the research through the expansion of testing regimens, assessment of new drug classes and higher-order combinations, and utilization of integrated omics technologies.

FK506-binding protein 5 promotes the progression of papillary thyroid carcinoma

Objective

To detect the expression of FK506-binding protein 5 (FKBP5) in human papillary thyroid carcinoma (PTC) tissues, and explore its possible role in the progression of PTC.

Methods

FKBP5 expression levels were assessed in 115 PTC tissues and corresponding normal tissues by immunohistochemistry. We also examined the correlations between FKBP5 expression and clinicopathological factors and survival in 75 patients with PTC. The effects of FKBP5 on the proliferation and apoptosis of PTC cells were detected by colony-formation, MTT, and flow cytometry assays, respectively. We further investigated the effects of FKBP5 on tumor growth in mice.

Results

We revealed high expression levels of FKBP5 in human PTC tissues compared with normal tissues. Furthermore, high FKBP5 expression was associated with an increased incidence of intraglandular dissemination, and lower overall and progression-free survival. FKBP5 depletion remarkably suppressed the proliferation and induced apoptosis of PTC cells in vitro. FKBP5 further contributed to the growth of PTC tumors in mice.

Conclusions

The results of this study demonstrated the potential involvement of FKBP5 in the progression of PTC, and confirmed FKBP5 as a novel therapeutic target for PTC treatment.

An Integrated Data Analysis of mRNA, miRNA and Signaling Pathways in Pancreatic Cancer

Although many genes and miRNAs have been reported for various cancers, pancreatic cancer's specific genes or miRNAs have not been studied precisely yet. Therefore, we have analyzed the gene and miRNA expression profile of pancreatic cancer data in the gene expression omnibus (GEO) database. The microarray-derived miRNAs and mRNAs were annotated by gene ontology (GO) and signaling pathway analysis. We also recognized mRNAs that were targeted by miRNA through the mirDIP database. An integrated analysis of the microarray revealed that only 6 out of 43 common miRNAs had significant differences in their expression profiles between the tumor and normal groups (P value < 0.05 and |log Fold Changes (logFC)|> 1). The hsa-miR-210 had upregulation, whereas hsa-miR-375, hsa-miR-216a, hsa-miR-217, hsa-miR-216b and hsa-miR-634 had downregulation in pancreatic cancer (PC). The analysis results also revealed 109 common mRNAs by microarray and mirDIP 4.1 databases. Pathway analysis showed that amoebiasis, axon guidance, PI3K-Akt signaling pathway, absorption and focal adhesion, adherens junction, platelet activation, protein digestion, human papillomavirus infection, extracellular matrix (ECM) receptor interaction, and riboflavin metabolism played important roles in pancreatic cancer. GO analysis revealed the significant enrichment in the three terms of biological process, cellular component, and molecular function, which were identified as the most important processes associated strongly with pancreatic cancer. In conclusion, DTL, CDH11, COL5A1, ITGA2, KIF14, SMC4, VCAN, hsa-mir-210, hsa-mir-217, hsa-mir-216a, hsa-mir-216b, hsa-mir-375 and hsa-mir-634 can be reported as the novel diagnostic or even therapeutic markers for the future studies. Also, the hsa-mir-107 and hsa-mir-125a-5p with COL5A1, CDH11 and TGFBR1 genes can be introduced as major miRNA and genes on the miRNA-drug-mRNA network. The new regulatory network created in our study could give a deeper knowledge of the pancreatic cancer.

GPRC5A: An emerging prognostic biomarker for predicting malignancy of Pancreatic Cancer based on bioinformatics analysis

Background: Pancreatic cancer (PaCa) is a highly lethal malignancy. The treatment options for PaCa lack efficacy. The study aimed to explore the molecular biomarkers for predicting survival of PaCa and identify the potential carcinogenic mechanisms of the selected gene. Methods: Based on public databases of PaCa, differentially expressed genes (DEGs) were identified using Networkanalyst. Survival analyses were exerted on GEPIA. Oncomine and The Human Protein Atlas were used for verifying the expression on mRNA and protein levels. Enrichment analyses were generated on Metascape and gene set enrichment analysis (GSEA). Univariate analyses were performed to determine the clinical factors associated with the expression of GPRC5A. Results: GPRC5A was identified as the most valuable gene in predicting survival of PaCa patients. Patients with high expression of GPRC5A showed larger tumor size, higher TNM stages, higher tumor grade, and more positive resection margin. In mutant KRAS, TP53, CDKN2A and SMAD4 group, the expression of GPRC5A was higher than non-mutant group. Mechanistically, GPRC5A may promote metastasis of PaCa mainly via regulating epithelial-mesenchymal transition (EMT) and neuroactive ligand-receptor interaction. Conclusion: GPRC5A may act as an oncogene in the progression of PaCa and could be a prognostic biomarker in predicting survival of PaCa.

Aberrant lactate dehydrogenase A signaling contributes metabolic signatures in pancreatic cancer

Background

Pancreatic cancer (PC) has the lowest 5-year survival rate; therefore, new early screening methods and therapeutic targets are still urgently required. Emerging technologies such as metabolomic-based liquid biopsy may contribute to the field. We found aberrant lactate dehydrogenase A (LDHA) signaling to be an unfavorable biomarker for PC.

Methods

A total of 9 genes of the glycolysis pathway were detected by enrichment analysis in the PC Gene Expression Omnibus (GEO) dataset. The relationship between LDHA/pyruvate kinase (PKM)/fructose biphosphate aldolase A (ALDOA)/glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and patient survival was analyzed by Kaplan-Meier plotting analysis of The Cancer Genome Atlas (TCGA). The detection of changing metabolites in the serum of PC patients was performed using a nuclear magnetic resonance (NMR) spectrometer.

Results

We found LDHA was an independent predictor of overall survival (OS) in PC patients (P<0.001). Consistent with genetic aberrance of LDHA, we identified significant alterations in patients’ glycolysis-related metabolites, including upregulation of lactic acid and downregulation of pyruvic acid. A 0.956 area under the curve (AUC) was achieved using the combinative metabolites score of lactic acid, pyruvic acid, citric acid, and glucose to distinguish PC from healthy controls.

Conclusions

Aberrant LDHA signaling is an unfavorable biomarker for PC and consequential metabolic changes constitute potential diagnostic signatures of PCs.

USP15 promotes the apoptosis of degenerative nucleus pulposus cells by suppressing the PI3K/AKT signalling pathway

OBJECTIVES

Degenerative disc disease is characterized by an enhanced breakdown of its existing nucleus pulposus (NP) matrix due to the dysregulation of matrix enzymes and factors. Ubiquitin-specific protease 15 (USP15) is reported to be abnormal in certain human diseases. However, its role in NP degeneration remains unclear. Therefore, we aimed to explore the function of USP15 in degenerative NP cell specimens.

METHODS

We induced gene silencing and overexpression of USP15 in degenerative NP cells using RNA interference (RNAi) and a lentiviral vector, respectively. qRT-PCR and Western blotting were used to determine gene and protein expression levels. Cell apoptosis was analysed via flow cytometry. Protein interaction was examined by performing a co-immunoprecipitation assay. Furthermore, the PI3K inhibitor LY294002 and agonist IGF-1 were used to investigate the link between USP15 and AKT in NP degeneration.

RESULTS

We found that USP15 was up-regulated in degenerative NP cells and that its overexpression accelerated the process of apoptosis. Moreover, USP15 expression levels negatively correlated with AKT phosphorylation in degenerative NP cells. Furthermore, targeting and silencing USP15 with miR-338-3p and studying its interaction with FK506-binding protein 5 (FKBP5) revealed enhancement of FKBP5 ubiquitination, indicating that USP15 is a component of the FKBP5/AKT signalling pathway in degenerative NP cells.

CONCLUSIONS

Our results show that USP15 exacerbates NP degradation by deubiquitinating and stabilizing FKBP5. This in turn results in the suppression of AKT phosphorylation in degenerative NP cells. Therefore, our study provides insights into the understanding of USP15 function as a potential molecule in the network of NP degeneration.

Bioinformatics Data Mining Repurposes the JAK2 (Janus Kinase 2) Inhibitor Fedratinib for Treating Pancreatic Ductal Adenocarcinoma by Reversing the KRAS (Kirsten Rat Sarcoma 2 Viral Oncogene Homolog)-Driven Gene Signature

Pancreatic ductal adenocarcinoma (PDAC) is still one of the most aggressive and lethal cancer types due to the late diagnosis, high metastatic potential, and drug resistance. The development of novel therapeutic strategies is urgently needed. KRAS (Kirsten rat sarcoma 2 viral oncogene homolog) is the major driver mutation gene for PDAC tumorigenesis. In this study, we mined cancer genomics data and identified a common KRAS-driven gene signature in PDAC, which is related to cell–cell and cell–extracellular matrix (ECM) interactions. Higher expression of this gene signature was associated with poorer overall survival of PDAC patients. Connectivity Map (CMap) analysis and drug sensitivity profiling predicted that a clinically approved JAK2 (Janus kinase 2)-selective inhibitor, fedratinib (also known as TG-101348), could reverse the KRAS-driven gene signature and exhibit KRAS-dependent anticancer activity in PDAC cells. As an approved treatment for myelofibrosis, the pharmacological and toxicological profiles of fedratinib have been well characterized. It may be repurposed for treating KRAS-driven PDAC in the future.

Pharmacogenomics-Driven Prediction of Antidepressant Treatment Outcomes: A Machine-Learning Approach With Multi-trial Replication

We set out to determine whether machine learning–based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 white outpatients with MDD treated with citalopram/escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN‐AMPS; n = 398), Sequenced Treatment Alternatives to Relieve Depression (STAR*D; n = 467), and International SSRI Pharmacogenomics Consortium (ISPC; n = 165) trials. A genomewide association study for PGRN‐AMPS plasma metabolites associated with SSRI response (serotonin) and baseline MDD severity (kynurenine) identified single nucleotide polymorphisms (SNPs) in DEFB1,ERICH3,AHR, and TSPAN5 that we tested as predictors. Supervised machine‐learning methods trained using SNPs and total baseline depression scores predicted remission and response at 8 weeks with area under the receiver operating curve (AUC) > 0.7 (P < 0.04) in PGRN‐AMPS patients, with comparable prediction accuracies > 69% (P ≤ 0.07) in STAR*D and ISPC. These results demonstrate that machine learning can achieve accurate and, importantly, replicable prediction of SSRI therapy response using total baseline depression severity combined with pharmacogenomic biomarkers.

Interaction between early-life stress and FKBP5 gene variants in major depressive disorder and post-traumatic stress disorder: A systematic review and meta-analysis

BACKGROUND

Gene-environment interaction contributes to the risks of psychiatric disorders. Interactions between FKBP5 gene variants and early-life stress may enhance the risk not only for mood disorder, but also for a number of other behavioral phenotypes. The aim of the present study was to review and conduct a meta-analysis on the results from published studies examining interaction between FKBP5 gene variants and early-life stress and their associations with stress-related disorders such as major depression and PTSD.

METHODS

A literature search was conducted using PsychINFO and PubMed databases until May 2017. A total of 14 studies with a pooled total of 15109 participants met the inclusion criteria, the results of which were combined and a meta-analysis was performed using the differences in correlations as the effect measure. Based on literature, rs1360780, rs3800373, and rs9470080 SNPs were selected within the FKBP5 gene and systematic review was conducted.

RESULTS

Based on the Comprehensive Meta-Analysis software, no publication bias was detected. Sensitivity analysis and credibility of meta-analysis results also indicated that the analyses were stable. The meta-analysis showed that individuals who carry T allele of rs1360780, C-allele of rs3800373 or T-allele of rs9470080 exposed to early-life trauma had higher risks for depression or PTSD.

LIMITATIONS

The effects of ethnicity, age, sex, and different stress measures were not examined due to limited sample size.

CONCLUSIONS

These results provide strong evidence of interactions between FKBP5 genotypes and early-life stress, which could pose a significant risk factor for stress-associated disorders such as major depression and PTSD.

FKBP51 decreases cell proliferation and increases progestin sensitivity of human endometrial adenocarcinomas by inhibiting Akt

In this study, we investigated the role of FK506 binding protein 51 (FKBP51) in human endometrial adenocarcinoma progression. Immunohistochemical analysis showed decreased FKBP51 expression in endometrial adenocarcinoma tissues. Moreover, higher FKBP51 expression was observed in the normal secretory phase than in proliferative-phase endometrial tissues. FKBP51-shRNA transfected KLE cells showed high Ser473-phospho Akt with decreased p21 and p27 levels, which promoted S-G₂/M phase cell cycle progression and proliferation. Conversely, FKBP51 overexpressing Ishikawa cells showed low Ser473-phospho Akt, which led to increased p21 and p27 levels and, in turn, G₀/G₁ cell cycle arrest and decreased cell proliferation. FKBP51 overexpression in progesterone receptor-positive Ishikawa cells sensitized them to medroxyprogesterone acetate (MPA; progestin) treatment by repressing Akt signaling. Conversely, FKBP51-shRNA knockdown in RL95-2 cells attenuated progestin sensitivity. These findings indicate FKBP51 inhibits cell proliferation and promotes progestin sensitivity in endometrial adenocarcinoma by decreasing Akt signaling.

Genomic Variations in Pancreatic Cancer and Potential Opportunities for Development of New Approaches for Diagnosis and Treatment

Human pancreatic cancer has a very poor prognosis with an overall five-year survival rate of less than 5% and an average median survival time of six months. This is largely due to metastatic disease, which is already present in the majority of patients when diagnosed. Although our understanding of the molecular events underlying multi-step carcinogenesis in pancreatic cancer has steadily increased, translation into more effective therapeutic approaches has been inefficient in recent decades. Therefore, it is imperative that novel and targeted approaches are designed to facilitate the early detection and treatment of pancreatic cancer. Presently, there are numerous ongoing studies investigating the types of genomic variations in pancreatic cancer and their impact on tumor initiation and growth, as well as prognosis. This has led to the development of therapeutics to target these genetic variations for clinical benefit. Thus far, there have been minimal clinical successes directly targeting these genomic alterations; however research is ongoing to ultimately discover an innovative approach to tackle this devastating disease. This review will discuss the genomic variations in pancreatic cancer, and the resulting potential diagnostic and therapeutic implications.

Association of genetic polymorphisms with survival of pancreatic ductal adenocarcinoma patients

Germline genetic variability might contribute, at least partially, to the survival of pancreatic ductal adenocarcinoma (PDAC) patients. Two recently performed genome-wide association studies (GWAS) on PDAC overall survival (OS) suggested (P < 10(-5)) the association between 30 genomic regions and PDAC OS. With the aim to highlight the true associations within these regions, we analyzed 44 single-nucleotide polymorphisms (SNPs) in the 30 candidate regions in 1722 PDAC patients within the PANcreatic Disease ReseArch (PANDoRA) consortium. We observed statistically significant associations for five of the selected regions. One association in the CTNNA2 gene on chromosome 2p12 [rs1567532, hazard ratio (HR) = 1.75, 95% confidence interval (CI) 1.19-2.58, P = 0.005 for homozygotes for the minor allele] and one in the last intron of the RUNX2 gene on chromosome 6p21 (rs12209785, HR = 0.88, 95% CI 0.80-0.98, P = 0.014 for heterozygotes) are of particular relevance. These loci do not coincide with those that showed the strongest associations in the previous GWAS. In silico analysis strongly suggested a possible mechanistic link between these two SNPs and pancreatic cancer survival. Functional studies are warranted to confirm the link between these genes (or other genes mapping in those regions) and PDAC prognosis in order to understand whether these variants may have the potential to impact treatment decisions and design of clinical trials.

Hsp90-binding immunophilin FKBP51 forms complexes with hTERT enhancing telomerase activity

FK506-binding proteins are members of the immunophilin family of proteins. Those immunophilins associated to the 90-kDa-heat-shock protein, Hsp90, have been proposed as potential modulators of signalling cascade factors chaperoned by Hsp90. FKBP51 and FKBP52 are the best characterized Hsp90-bound immunophilins first described associated to steroid-receptors. The reverse transcriptase subunit of telomerase, hTERT, is also an Hsp90 client-protein and is highly expressed in cancer cells, where it is required to compensate the loss of telomeric DNA after each successive cell division. Because FKBP51 is also a highly expressed protein in cancer tissues, we analyzed its potential association with hTERT·Hsp90 complexes and its possible biological role. In this study it is demonstrated that both immunophilins, FKBP51 and FKBP52, co-immunoprecipitate with hTERT. The Hsp90 inhibitor radicicol disrupts the heterocomplex and favors the partial cytoplasmic relocalization of hTERT in similar manner as the overexpression of the TPR-domain peptide of the immunophilin. While confocal microscopy images show that FKBP51 is primarily localized in mitochondria and hTERT is totally nuclear, upon the onset of oxidative stress, FKBP51 (but not FKBP52) becomes mostly nuclear colocalizing with hTERT, and longer exposure times to peroxide favors hTERT export to mitochondria. Importantly, telomerase activity of hTERT is significantly enhanced by FKBP51. These observations support the emerging role assigned to FKBP51 as antiapoptotic factor in cancer development and progression, and describe for the first time the potential role of this immunophilin favoring the clonal expansion by enhancing telomerase activity.

Gene-Stress-Epigenetic Regulation of FKBP5: Clinical and Translational Implications

Stress responses and related outcomes vary markedly across individuals. Elucidating the molecular underpinnings of this variability is of great relevance for developing individualized prevention strategies and treatments for stress-related disorders. An important modulator of stress responses is the FK506-binding protein 51 (FKBP5/FKBP51). FKBP5 acts as a co-chaperone that modulates not only glucocorticoid receptor activity in response to stressors but also a multitude of other cellular processes in both the brain and periphery. Notably, the FKBP5 gene is regulated via complex interactions among environmental stressors, FKBP5 genetic variants, and epigenetic modifications of glucocorticoid-responsive genomic sites. These interactions can result in FKBP5 disinhibition that has been shown to contribute to a number of aberrant phenotypes in both rodents and humans. Consequently, FKBP5 blockade may hold promise as treatment intervention for stress-related disorders, and recently developed selective FKBP5 blockers show encouraging results in vitro and in rodent models. Although risk for stress-related disorders is conferred by multiple environmental and genetic factors, the findings related to FKBP5 illustrate how a deeper understanding of the molecular and systemic mechanisms underlying specific gene-environment interactions may provide insights into the pathogenesis of stress-related disorders.

In vitro human cell line models to predict clinical response to anticancer drugs

In vitro human cell line models have been widely used for cancer pharmacogenomic studies to predict clinical response, to help generate pharmacogenomic hypothesis for further testing, and to help identify novel mechanisms associated with variation in drug response. Among cell line model systems, immortalized cell lines such as Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines (LCLs) have been used most often to test the effect of germline genetic variation on drug efficacy and toxicity. Another model, especially in cancer research, uses cancer cell lines such as the NCI-60 panel. These models have been used mainly to determine the effect of somatic alterations on response to anticancer therapy. Even though these cell line model systems are very useful for initial screening, results from integrated analyses of multiple omics data and drug response phenotypes using cell line model systems still need to be confirmed by functional validation and mechanistic studies, as well as validation studies using clinical samples. Future models might include the use of patient-specific inducible pluripotent stem cells and the incorporation of 3D culture which could further optimize in vitro cell line models to improve their predictive validity.