Integrated expression profiles analysis reveals novel predictive biomarker in pancreatic ductal adenocarcinoma

Acquired and intrinsic gemcitabine resistance in pancreatic cancer therapy: Environmental factors, molecular profile and drug/nanotherapeutic approaches

A high number of cancer patients around the world rely on gemcitabine (GEM) for chemotherapy. During local metastasis of cancers, surgery is beneficial for therapy, but dissemination in distant organs leads to using chemotherapy alone or in combination with surgery to prevent cancer recurrence. Therapy failure can be observed as a result of GEM resistance, threatening life of pancreatic cancer (PC) patients. The mortality and morbidity of PC in contrast to other tumors are increasing. GEM chemotherapy is widely utilized for PC suppression, but resistance has encountered its therapeutic impacts. The purpose of current review is to bring a broad concept about role of biological mechanisms and pathways in the development of GEM resistance in PC and then, therapeutic strategies based on using drugs or nanostructures for overcoming chemoresistance. Dysregulation of the epigenetic factors especially non-coding RNA transcripts can cause development of GEM resistance in PC and miRNA transfection or using genetic tools such as siRNA for modulating expression level of these factors for changing GEM resistance are suggested. The overexpression of anti-apoptotic proteins and survival genes can contribute to GEM resistance in PC. Moreover, supportive autophagy inhibits apoptosis and stimulates GEM resistance in PC cells. Increase in metabolism, glycolysis induction and epithelial-mesenchymal transition (EMT) stimulation are considered as other factors participating in GEM resistance in PC. Drugs can suppress tumorigenesis in PC and inhibit survival factors and pathways in increasing GEM sensitivity in PC. More importantly, nanoparticles can increase pharmacokinetic profile of GEM and promote its blood circulation and accumulation in cancer site. Nanoparticles mediate delivery of GEM with genes and drugs to suppress tumorigenesis in PC and increase drug sensitivity. The basic research displays significant connection among dysregulated pathways and GEM resistance, but the lack of clinical application is a drawback that can be responded in future.

Prognostic and biological function value of OSBPL3 in colorectal cancer analyzed by multi-omic data analysis

BACKGROUND

Colorectal cancer (CRC) is one of the most common malignancies in the world. This study proposes to reveal prognostic biomarkers for the prognosis and treatment of CRC patients.

METHODS

Differential analysis of OSBPL3 was performed in pan-cancer, and the correlation between clinical stage and OSBPL3 was analyzed. Multiple omics analysis was used to compare the relationship between survival of patients and copy number variation, single nucleotide variant, and methylation status. Survival differences between high and low OSBPL3 expression groups were analyzed. Differentially expressed genes (DEGs) between high and low OSBPL3 expression groups were obtained, and functional enrichment analysis was implemented. Correlations between immune cells and OSBPL3 was analyzed. Drug sensitivity between the two OSBPL3 expression groups was compared. Moreover, the expression of OSBPL3 was verified by immunohistochemistry and real-time quantitative PCR.

RESULTS

OSBPL3 was differentially expressed in 13 tumors and had some correlations with T and N stages. OSBPL3 expression was regulated by methylation and higher OSBPL3 expression was associated with poorer prognosis in CRC. 128 DEGs were obtained and they were mainly involved in signaling receptor activator activity, aspartate and glutamate metabolism. T cell gamma delta and T cell follicular helper were significantly different in the high and low OSBPL3 expression groups. Moreover, OSBPL3 showed negative correlations with multiple drugs. OSBPL3 was significantly upregulated in CRC samples compared to normal samples.

CONCLUSIONS

A comprehensive analysis demonstrated that OSBPL3 had potential prognostic value, and guiding significance for CRC chemotherapeutic.

Epigenetic reprogramming-induced guanidinoacetic acid synthesis promotes pancreatic cancer metastasis and transcription-activating histone modifications

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) tends to undergo distant metastasis, especially liver metastasis, leading to a poor prognosis. Metabolic remodelling and epigenetic reprogramming are two important hallmarks of malignant tumours and participate in regulating PDAC tumorigenesis and metastasis. However, the interaction between these two processes during PDAC metastasis has not been fully elucidated.

METHODS

We performed metabolomics analysis to identify the critical metabolites associated with PDAC liver metastasis and focused on guanidinoacetic acid (GAA). Intracellular GAA content was significantly increased in liver metastatic PDAC cells compared to primary cancer cells in mouse xenograft tumour models. The effects of GAA supplementation and glycine amidinotransferase (GATM) knockdown on PDAC metastasis were assessed by analysing cell migration, filopodia formation, epithelial-mesenchymal transition (EMT), and in vivo metastasis in different cell and animal models. Next, ChIP‒qPCR, 3C‒qPCR, and CRISPRi/dCas9-KRAB experiments were used to validate the "epigenome-metabolome" mechanism. Finally, the results of in vitro approaches, including RNA-seq, CUT&RUN, RT‒qPCR, and western blot analyses, as well as luciferase reporter gene assay and transwell assay, revealed the GAA-c-Myc-HMGA axis and transcription-activating histone modifications reprogramming.

RESULTS

A high level of intracellular GAA was associated with PDAC liver metastasis. GAA could promote the migration, EMT, and liver metastasis of pancreatic cancer cells in vitro and in vivo. Next, we explored the role of GATM-mediated de novo GAA synthesis in pancreatic cancer metastasis. High expression of GATM was positively correlated with advanced N stage in PDAC. Knockdown of GATM significantly reduced the intracellular level of GAA, suppressed EMT, and inhibited PDAC liver metastasis, and these effects were attenuated by GAA supplementation. Mechanistically, we identified the active enhancers looped to the Gatm gene locus that promoted GATM expression and PDAC liver metastasis. Furthermore, we found that GAA promoted cell migration and EMT by regulating c-Myc-mediated high mobility group AT-hook protein expression. Moreover, GAA increased the H3K4me3 modification level by upregulating histone methyltransferases, which induced the transcription of metastasis-related genes, including Myc.

CONCLUSIONS

These findings revealed the critical role of the epigenome-metabolome interaction in regulating PDAC liver metastasis and suggested potential therapeutic strategies targeting GAA metabolism and epigenetic regulatory mechanisms.

Open-source curation of a pancreatic ductal adenocarcinoma gene expression analysis platform (pdacR) supports a two-subtype model

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease for which potent therapies have limited efficacy. Several studies have described the transcriptomic landscape of PDAC tumors to provide insight into potentially actionable gene expression signatures to improve patient outcomes. Despite centralization efforts from multiple organizations and increased transparency requirements from funding agencies and publishers, analysis of public PDAC data remains difficult. Bioinformatic pitfalls litter public transcriptomic data, such as subtle inclusion of low-purity and non-adenocarcinoma cases. These pitfalls can introduce non-specificity to gene signatures without appropriate data curation, which can negatively impact findings. To reduce barriers to analysis, we have created pdacR ( http://pdacR.bmi.stonybrook.edu , github.com/rmoffitt/pdacR), an open-source software package and web-tool with annotated datasets from landmark studies and an interface for user-friendly analysis in clustering, differential expression, survival, and dimensionality reduction. Using this tool, we present a multi-dataset analysis of PDAC transcriptomics that confirms the basal-like/classical model over alternatives.

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.

IL1R2 promotes tumor progression via JAK2/STAT3 pathway in human clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is known as the most aggressive subtype of genitourinary cancers. The lack of effective therapies has prompted us to further explore the complex network of genes involved in ccRCC tumor progression and metastasis and to seek new biomarkers and therapeutic strategies to improve clinical outcomes. Interleukin-1 receptor type 2 (IL1R2), a decoy receptor of IL-1, is found to be differentially expressed in various tumors types recently. However, the role of IL1R2 in ccRCC has not been documented. Herein, we found that the expression of IL1R2 in ccRCC tissues was significantly increased as the tumor's Furman pathological grade was elevated. Compared to lower IL1R2 expression, ccRCC patients with high IL1R2 expression had a significantly worse OS rate. IL1R2 could serve as an independent prognostic predictor for ccRCC patients. Depletion of IL1R2 could inhibit cell proliferation, migration, invasion, and cell cycle arrest at the G1 phase, while overexpression of IL1R2 could reverse this effect. Moreover, depletion of IL1R2 led to changes and enrichment of several signaling pathways, as shown by RNA sequencing. We subsequently verified that Janus kinase 2 / signal transducer and activator of transcription 3 (JAK2/STAT3) pathway was involved in the IL1R2 mediated regulation of cellular functions of ccRCC cells and these functions were acted by the intracellular domain of IL1R2, not the extracellular domain. Our findings suggested that IL1R2 could serve as a potential therapeutic target for ccRCC progression and metastasis via its regulation of the JAK2/STAT3 signaling pathway.

Autophagy: A Key Player in Pancreatic Cancer Progression and a Potential Drug Target

Simple Summary

With the mortality rate of pancreatic cancer predicted to rise over the coming years, it is essential that effective treatment strategies are developed as soon as possible. Pancreatic cancer has always proven very difficult to treat due to its fast growing and aggressive nature. Chemotherapeutic treatment has struggled to increase the survival rate of pancreatic cancer patients due to effective chemo-resistant properties that derive from the supporting tumor microenvironment and autophagy, a vital survival pathway. This review will explore how the autophagy pathway and tumor microenvironment help to sustain tumor survival under stress and expand into a metastatic state. Due to the comprehensive understanding of the autophagy pathway, we will highlight the potential chinks in the pancreatic tumor’s armor and identify potential targets to overcome chemo-resistance in pancreatic cancer. We will also present novel autophagy inhibitors that could reduce tumor survival and how they could be most effectively conceived.

Abstract

Pancreatic cancer is known to have the lowest survival outcomes among all major cancers, and unfortunately, this has only been marginally improved over last four decades. The innate characteristics of pancreatic cancer include an aggressive and fast-growing nature from powerful driver mutations, a highly defensive tumor microenvironment and the upregulation of advantageous survival pathways such as autophagy. Autophagy involves targeted degradation of proteins and organelles to provide a secondary source of cellular supplies to maintain cell growth. Elevated autophagic activity in pancreatic cancer is recognized as a major survival pathway as it provides a plethora of support for tumors by supplying vital resources, maintaining tumour survival under the stressful microenvironment and promoting other pathways involved in tumour progression and metastasis. The combination of these features is unique to pancreatic cancer and present significant resistance to chemotherapeutic strategies, thus, indicating a need for further investigation into therapies targeting this crucial pathway. This review will outline the autophagy pathway and its regulation, in addition to the genetic landscape and tumor microenvironment that contribute to pancreatic cancer severity. Moreover, this review will also discuss the mechanisms of novel therapeutic strategies that inhibit autophagy and how they could be used to suppress tumor progression.

Interaction Analysis of Adenovirus L5 Protein With Pancreatic Cancer Cell Surface Receptor to Analyze Its Affinity for Oncolytic Virus Therapy

This study seeks to investigate the interaction profile of the L5 protein of oncolytic adenovirus with the overexpressed surface receptors of pancreatic cancer. This is an important area of research because pancreatic cancer is one of the most fatal malignancies with a very low patient survival rate. Multiple therapies to date to improve the survival rate are reported; however, they show a comparatively low success rate. Among them, oncolytic virus therapy is a type of immunotherapy that is currently under deliberation by researchers for multiple cancer types in various clinical trials. Talimogene laherparepvec (T-VEC) is the first oncolytic virus approved by the US Food and Drug Administration (FDA) for melanoma. The oncolytic virus not only kills cancer cells but also activates the anticancer immune response. Therefore, it is preferred over others to deal with aggressive pancreatic cancer. The efficacy of therapy primarily depends on how effectively the oncolytic virus enters and infects the cancer cell. Cell surface receptors and their interactions with virus coat proteins are a crucial step for oncolytic virus entry and a pivotal determinant. The L5 proteins of the virus coat are the first to interact with host cell surface receptors. Therefore, the objective of this study is to analyze the interaction profile of the L5 protein of oncolytic adenovirus with overexpressed surface receptors of pancreatic cancer. The L5 proteins of three adenovirus serotypes HAdV2, HAdV5, and HAdV3 were utilized in this study. Overexpressed pancreatic cancer receptors include SLC2A1, MET, IL1RAP, NPR3, GABRP, SLC6A6, and TMPRSS4. The protein structures of viral and cancer cell protein were docked using the High Ambiguity Driven protein–protein DOCKing (HADDOCK) server. The binding affinity and interaction profile of viral proteins against all the receptors were analyzed. Results suggest that the HAdV3 L5 protein shows better interaction as compared to HAdV2 and HAdV5 by elucidating high binding affinity with 4 receptors (NPR3, GABRP, SLC6A6, and TMPRSS4). The current study proposed that HAdV5 or HAdV2 virus pseudotyped with the L5 protein of HAdV3 can be able to effectively infect pancreatic cancer cells. Moreover, the current study surmises that the affinity maturation of HAdV3 L5 can enhance virus attachment with all the receptors of cancer cells.

The Highly Expressed IFIT1 in Nasopharyngeal Carcinoma Enhances Proliferation, Migration, and Invasion of Nasopharyngeal Carcinoma Cells

In this study, we aimed to identify potential targets modulating the progression of nasopharyngeal carcinoma (NPC) using integrated bioinformatics analysis and functional assays. Differentially expressed genes (DEGs) between NPC and normal tissues samples were obtained from publicly availably microarray datasets (GSE68799, GSE34573, and GSE53819) in the Gene Expression Omnibus (GEO) database. The bioinformatics analysis identified 49 common DEGs from three GEO datasets, which were mainly enriched in cytokine/chemokine pathways and extracellular matrix organization pathway. Further protein-protein interaction network analysis identified 11 hub genes from the 49 DEGs. The 11 hub genes were significantly up-regulated in the NPC tissues when compared to normal tissues by analyzing the Oncomine database. The 8 hub genes including COL5A1, COL7A1, COL22A1, CXCL11, IFI44L, IFIT1, RSAD2, and USP18 were significantly up-regulated in the NPC tissues when compared to normal tissues by using the Oncomine database. Further validation studies showed that IFIT1 was up-regulated in the NPC cells. Knockdown of IFI1T1 suppressed the proliferation, migration, and invasion of NPC cells; while IFIT1 overexpression promoted the proliferation, migration, and invasion of NPC cells. In conclusion, a total of 49 DEGs and 11 hub genes in NPC using the integrated bioinformatics analysis. IFIT1 was up-regulated in the NPC cells lines, and IFIT1 may act as an oncogene by promoting NPC cell proliferation, migration, and invasion.

Ribosomal Protein S6: A Potential Therapeutic Target against Cancer?

Ribosomal protein S6 (RPS6) is a component of the 40S small ribosomal subunit and participates in the control of mRNA translation. Additionally, phospho (p)-RPS6 has been recognized as a surrogate marker for the activated PI3K/AKT/mTORC1 pathway, which occurs in many cancer types. However, downstream mechanisms regulated by RPS6 or p-RPS remains elusive, and the therapeutic implication of RPS6 is underappreciated despite an approximately half a century history of research on this protein. In addition, substantial evidence from RPS6 knockdown experiments suggests the potential role of RPS6 in maintaining cancer cell proliferation. This motivates us to investigate the current knowledge of RPS6 functions in cancer. In this review article, we reviewed the current information about the transcriptional regulation, upstream regulators, and extra-ribosomal roles of RPS6, with a focus on its involvement in cancer. We also discussed the therapeutic potential of RPS6 in cancer.

The prognostic and clinical significance of IFI44L aberrant downregulation in patients with oral squamous cell carcinoma

Background

It is a basic task in high-throughput gene expression profiling studies to identify differentially expressed genes (DEGs) between two phenotypes. RankComp, an algorithm, could analyze the highly stable within-sample relative expression orderings (REOs) of gene pairs in a particular type of human normal tissue that are widely reversed in the cancer condition, thereby detecting DEGs for individual disease samples measured by a particular platform.

Methods

In the present study, Gene Expression Omnibus (GEO) Series (GSE) GSE75540, GSE138206 were downloaded from GEO, by analyzing DEGs in oral squamous cell carcinoma based on online datasets using the RankComp algorithm, using the Kaplan-Meier survival analysis and Cox regression analysis to survival analysis, Gene Set Enrichment Analysis (GSEA) to explore the potential molecular mechanisms underlying.

Results

We identified 6 reverse gene pairs with stable REOs. All the 12 genes in these 6 reverse gene pairs have been reported to be associated with cancers. Notably, lower Interferon Induced Protein 44 Like (IFI44L) expression was associated with poorer overall survival (OS) and Disease-free survival (DFS) in oral squamous cell carcinoma patients, and IFI44L expression showed satisfactory predictive efficiency by receiver operating characteristic (ROC) curve. Moreover, low IFI44L expression was identified as risk factors for oral squamous cell carcinoma patients’ OS. IFI44L downregulation would lead to the activation of the FRS-mediated FGFR1, FGFR3, and downstream signaling pathways, and might play a role in the PI3K-FGFR cascades.

Conclusions

Collectively, we identified 6 reverse gene pairs with stable REOs in oral squamous cell carcinoma, which might serve as gene signatures playing a role in the diagnosis in oral squamous cell carcinoma. Moreover, high expression of IFI44L, one of the DEGs in the 6 reverse gene pairs, might be associated with favorable prognosis in oral squamous cell carcinoma patients and serve as a tumor suppressor by acting on the FRS-mediated FGFR signaling.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09058-y.

Clinical Value and Potential Mechanisms of Oxysterol-Binding Protein Like 3 (OSBPL3) in Human Tumors

Cancer remains one of the top culprits causing disease-related deaths. A lack of effective multi-cancer therapeutic targets has limited the prolongation of cancer patients’ survival. Therefore, it is important to explore novel oncogenic genes or versatile targets and perform a comprehensive analysis to assess their roles in the process of tumorigenesis. OSBPL3 protein is an intracellular lipid receptor of the oxysterol-binding protein superfamily, which participates in some pathological and physiological processes in tumor progression. However, its clinical roles and potential mechanisms in cancers remain unknown. Thus, we aimed to systematic explore the potential oncogenic roles of OSBPL3 across thirty-three tumors using multiple web-based and publicly available tools, including the Cancer Genome Atlas, Gene Expression Omnibus, Genotype-Tissue Expression, cBioPortal, and Human Protein Atlas database. OSBPL3 is highly expressed in major subtypes of cancers, distinctly associated with the prognosis of tumor patients. We observed X676_splice/V676G alteration in the oxysterol domain and frequent mutations of OSBPL3 involve cell survival in skin cutaneous melanoma. We also first presented that the expression of OSBPL3 was associated with tumor mutational burden (TMB) in nine cancer types. Additionally, OSBPL3 shows an enhanced phosphorylation level at S426, S251, and S273 loci within the pleckstrin homology domain in multiple tumors, such as breast cancer or lung adenocarcinoma. And OSBPL3 expression was associated with active immune cells (CD8⁺ T cells) and cancer-associated fibroblasts in breast cancer, colon adenocarcinoma, and kidney renal clear cell carcinoma and immune checkpoint genes in more than 30 tumors, but weakly associated with immune suppressive cells (myeloid-derived suppressor cells, T regulatory cells). Moreover, protein processing and mRNA metabolic signaling pathways were involved in the functional mechanisms of OSBPL3. Our study first demonstrated that a novel agent OSBPL3 plays an important role in tumorigenesis from the perspective of publicly available databases and clinical tumor samples in various cancers, which comprehensively provide insights into its biological functions and may be helpful for further investigation.

Multifaced roles of PLAC8 in cancer

The role of PLAC8 in tumorigenesis has been gradually elucidated with the development of research. Although there are common molecular mechanisms that enforce cell growth, the impact of PLAC8 is varied and can, in some instances, have opposite effects on tumorigenesis. To systematically understand the role of PLAC8 in tumors, the molecular functions of PLAC8 in cancer will be discussed by focusing on how PLAC8 impacts tumorigenesis when it arises within tumor cells and how these roles can change in different stages of cancer progression with the ultimate goal of suppressing PLAC8-relevant cancer behavior and related pathologies. In addition, we highlight the diversity of PLAC8 in different tumors and its functional output beyond cancer cell growth. The comprehension of PLAC8's molecular function might provide new target and lead to the development of novel anticancer therapies.

Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

Background

Most often, the patients with pancreatic diseases are presented with a mass in pancreatic head region and existing methods of diagnosis fail to confirm whether the head mass is malignant or benign. As subsequent management of the disease hugely depends on the correct diagnosis, we wanted to explore possible biomarkers which could distinguish benign and malignant pancreatic head masses.

Methods

In order to address that gap, we performed a case–control study to identify genome-wide differentially expressed coding and noncoding genes between pancreatic tissues collected from benign and malignant head masses. These genes were next shortlisted using stringent criteria followed by selection of top malignancy specific genes. They subsequently got validated by quantitative RT-PCR and also in other patient cohorts. Survival analysis and ROC analysis were also performed.

Results

We identified 55 coding and 13 noncoding genes specific for malignant pancreatic head masses. Further shortlisting and validation, however, resulted in 5 coding genes as part of malignancy specific multi-gene signature, which was validated in three independent patient cohorts of 145 normal and 153 PDAC patients. We also found that overexpression of these genes resulted in survival disadvantage in the patients and ROC analysis identified that combination of 5 coding genes had the AUROC of 0.94, making them potential biomarker.

Conclusions

Our study identified a multi-gene signature comprising of 5 coding genes (CDCA7, DLGAP5, FOXM1, TPX2 and OSBPL3) to distinguish malignant head masses from benign ones.

Identification of Latent Oncogenes with a Network Embedding Method and Random Forest

Oncogene is a special type of genes, which can promote the tumor initiation. Good study on oncogenes is helpful for understanding the cause of cancers. Experimental techniques in early time are quite popular in detecting oncogenes. However, their defects become more and more evident in recent years, such as high cost and long time. The newly proposed computational methods provide an alternative way to study oncogenes, which can provide useful clues for further investigations on candidate genes. Considering the limitations of some previous computational methods, such as lack of learning procedures and terming genes as individual subjects, a novel computational method was proposed in this study. The method adopted the features derived from multiple protein networks, viewing proteins in a system level. A classic machine learning algorithm, random forest, was applied on these features to capture the essential characteristic of oncogenes, thereby building the prediction model. All genes except validated oncogenes were ranked with a measurement yielded by the prediction model. Top genes were quite different from potential oncogenes discovered by previous methods, and they can be confirmed to become novel oncogenes. It was indicated that the newly identified genes can be essential supplements for previous results.

Interactive Verification Analysis of Multiple Sequencing Data for Identifying Potential Biomarker of Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) comprises around 40% of all lung cancers, and in about 70% of patients, it has spread locally or systemically when first detected leading to a worse prognosis.

Methods

We filtered out differentially expressed genes (DEGs) based on the RNA sequencing data in the Gene Expression Omnibus database and verified and deeply analyzed screened DEGs using a combined bioinformatics approach.

Results

Expressions of 11,143 genes in 694 nontumor lung tissues and LUAD cases from 8 independent laboratories were analyzed; 188 mRNAs were identified as differentially expressed genes (DEGs). A PPI network constructed with 188 DEGs screened out 8 hub DEGs (CDH5, PECAM1, VWF, CLDN5, COL1A1, MMP9, SPP1, and IL6) which highly interconnected with other nodes. The expression levels of 8 hub genes in LUAD and control were assessed in the Oncomine database, and the results were consistent. The survival curves of 8 hub genes showed that their expressions are significantly related to the prognosis of lung cancer and LUAD patients except for IL6. Since the expression of IL6 is nonspecific and highly sensitive, we choose the other 7 hub genes we had verified to do the next analysis. Mutual exclusivity or cooccurrence analysis of 7 hub genes identified a tendency towards cooccurrence between CDH5, PECAM1, and VWF in LUAD. The coexpression profiles of CDH5 in LUAD were identified, and we found that PECAM1 and VWF coexpressed with CDH5. Immunohistochemistry and RT-PCR analysis showed that higher levels of CDH5, PECAM1, and VWF were expressed in normal lung tissues but a low or undetectable level was found in LUAD tissues.

Conclusions

Taken together, we speculate that CDH5, PECAM1, and VWF played an important role in LUAD.

A novel lncRNA-miRNA-mRNA competitive endogenous RNA network for uveal melanoma prognosis constructed by weighted gene co-expression network analysis

AIMS

Uveal melanoma (UM) is the most common and aggressive intraocular tumor in adults, and long-term survival of UM patients remains poor. Abnormal competitive endogenous RNA (ceRNA) networks promote the initiation and progression of many tumors and may thus serve as useful prognostic indicators. Here, we do a comprehensive analysis of long non-coding RNA (lncRNA)-microRNA (miRNA)-mRNA ceRNA networks as prognostic markers for UM.

MATERIALS AND METHODS

The Cancer Genome Atlas UM dataset was used to identify survival-related mRNA and lncRNA modules through weighted gene co-expression network analysis (WGCNA). Prognostic miRNAs were identified using univariate Cox proportional hazard regression. We then used Cox and least absolute shrinkage and selection operator regression to screen for prognostic hub mRNAs and establish a hub ceRNA network. A nomogram of five hub mRNAs was constructed and Kaplan-Meier survival analysis performed.

KEY FINDINGS

Six mRNA modules were constructed, two of which involved 1490 mRNAs that significantly correlated with survival. Among the three lncRNA modules constructed, one involved 199 survival-related lncRNAs. Five hub prognostic mRNAs were identified and a hub ceRNA network constructed, consisting of six lncRNAs, four miRNAs, and five mRNAs, with high prognostic value.

SIGNIFICANCE

We describe a hub ceRNA network of survival-associated lncRNAs, miRNAs, and mRNA that may underlie a critical post-translational regulatory mechanism determining UM aggression. These hub RNAs may be valuable prognostic markers and therapeutic targets in UM.

Interferon-Induced Protein 44 and Interferon-Induced Protein 44-Like Restrict Replication of Respiratory Syncytial Virus

RSV infects all children under 2 years of age, but only a subset of children get severe disease. We hypothesize that susceptibility to severe RSV necessitating hospitalization in children without predefined risk factors is, in part, mediated at the antiviral gene level. However, there is a large array of antiviral genes, particularly in the ISG family, the mechanism of which is poorly understood. Having previously identified IFI44 and IFI44L as possible genes of interest in a bioinformatic screen, we dissected the function of these two genes in the control of RSV. Through a range of overexpression and knockout studies, we show that the genes are antiviral and antiproliferative. This study is important because IFI44 and IFI44L are upregulated after a wide range of viral infections, and IFI44L can serve as a diagnostic biomarker of viral infection.

Cellular intrinsic immunity, mediated by the expression of an array of interferon-stimulated antiviral genes, is a vital part of host defense. We have previously used a bioinformatic screen to identify two interferon-stimulated genes (ISG) with poorly characterized function, interferon-induced protein 44 (IFI44) and interferon-induced protein 44-like (IFI44L), as potentially being important in respiratory syncytial virus (RSV) infection. Using overexpression systems, CRISPR-Cas9-mediated knockout, and a knockout mouse model, we investigated the antiviral capability of these genes in the control of RSV replication. Overexpression of IFI44 or IFI44L was sufficient to restrict RSV infection at an early time postinfection. Knocking out these genes in mammalian airway epithelial cells increased levels of infection. Both genes express antiproliferative factors that have no effect on RSV attachment but reduce RSV replication in a minigenome assay. The loss of Ifi44 was associated with a more severe infection phenotype in a mouse model of infection. These studies demonstrate a function for IFI44 and IFI44L in controlling RSV infection.

IMPORTANCE RSV infects all children under 2 years of age, but only a subset of children get severe disease. We hypothesize that susceptibility to severe RSV necessitating hospitalization in children without predefined risk factors is, in part, mediated at the antiviral gene level. However, there is a large array of antiviral genes, particularly in the ISG family, the mechanism of which is poorly understood. Having previously identified IFI44 and IFI44L as possible genes of interest in a bioinformatic screen, we dissected the function of these two genes in the control of RSV. Through a range of overexpression and knockout studies, we show that the genes are antiviral and antiproliferative. This study is important because IFI44 and IFI44L are upregulated after a wide range of viral infections, and IFI44L can serve as a diagnostic biomarker of viral infection.

Bioinformatics analysis of gene expression profile of serous ovarian carcinomas to screen key genes and pathways

Background

Serous ovarian carcinomas (SCA) are the most common and most aggressive ovarian carcinoma subtype which etiology remains unclear. To investigate the prospective role of mRNAs in the tumorigenesis and progression of SCA, the aberrantly expressed mRNAs were calculated based on the NCBI-GEO RNA-seq data.

Results

Of 21,755 genes with 89 SCA and SBOT cases from 3 independent laboratories, 59 mRNAs were identified as differentially expressed genes (DEGs) (|log₂Fold Change| > 1.585, also |FoldChange| > 3 and adjusted P < 0.05) by DESeq R. There were 26 up-regulated DEGs and 33 down-regulated DEGs screened. The hierarchical clustering analysis, functional analysis and pathway enrichment analysis were performed on all DEGs and found that Polo-like kinase (PLK) signaling events are important. PPI network constructed with different filtration conditions screened out 4 common hub genes (KIF11, CDC20, PBK and TOP2A). Mutual exclusivity or co-occurrence analysis of 4 hub genes identified a tendency towards co-occurrence between KIF11 and CDC20 or TOP2A in SCA (p < 0.05). To analyze further the potential role of KIF11 in SCA, the co-expression profiles of KIF11 in SCA were identified and we found that CDC20 co-expressed with KIF11 also is DEG that we screened out before. To verify our previous results in this paper, we assessed the expression levels of 4 hub DEGs (all up-regulated) and 4 down-regulated DEGs in Oncomine database. And the results were consistent with previous conclusions obtained from GEO series. The survival curves showed that KIF11, CDC20 and TOP2A expression are significantly related to prognosis of SCA patients.

Conclusions

From all the above results, we speculate that KIF11, CDC20 and TOP2A played an important role in SCA.

Pancreatic cancer cells show lower oleic acid oxidation and their conditioned medium inhibits oleic acid oxidation in human myotubes

BACKGROUND

/Objectives: We aimed to metabolically compare healthy primary human pancreatic epithelial cells (hPEC) to a pancreatic cancer cell line (PANC-1) and explore the effect on energy metabolism of exposing primary human myotubes to conditioned medium from hPEC and PANC-1 cells.

METHODS

Differences in metabolism were examined with radiolabeled glucose, oleic acid and lactic acid, and by qPCR. Mass spectrometry-based proteomics was used to study global protein secretion from the two cell types. Pathway analyses were performed.

RESULTS

PANC-1 cells tended to have higher glucose uptake, production of lactic acid, and glucose oxidation compared to hPEC cells. PANC-1 cells had higher uptake but lower oxidation of oleic acid, and mitochondrial reserve capacity from oleic acid was lower in PANC-1 cells. These differences in energy metabolism were reflected by differences in gene expressions and pathway analyses of the secretome. Conditioned medium from PANC-1 cells attenuated oleic acid oxidation in primary human myotubes.

CONCLUSIONS

Metabolic characterization of the PANC-1 cells revealed a glycolytic phenotype since they had an active glucose oxidation. Furthermore, PANC-1 cells showed a lower oleic acid oxidation and secreted a high amount of proteins into conditioned medium that also induced a reduced oleic acid oxidation in myotubes.

Development and validation of a lipogenic genes panel for diagnosis and recurrence of colorectal cancer

Background & aim

Accumulated evidence indicates that the elevation of lipid metabolism is an essential step in colorectal cancer (CRC) development, and analysis of the key lipogenic mediators may lead to identifying the new clinically useful prognostic gene signatures.

Methods

The expression pattern of 61 lipogenic genes was assessed between CRC tumors and matched adjacent normal tissues in a training set (n = 257) with the Mann-Whitney U test. Cox's proportional hazards model and the Kaplan–Meier method were used to identifying a lipogenic-biomarkers signature associated with the prognosis of CRC. The biomarkers signature was then confirmed in two independent validation groups, including a set of 223 CRC samples and an additional set of 203 COAD profiles retrieving from the Cancer Genome Atlas (TCGA).

Results

Five genes, including ACOT8, ACSL5, FASN, HMGCS2, and SCD1, were significantly enhanced in CRC tumors. Using the cutoff value 0.493, the samples were classified into high risk and low risk. The AUC of panel for discriminating of all, early (I-II stages), and advanced CRC (III-IV stages) were 0.8922, 0.8446, and 0.9162 (Training set), along with 0.8800, 0.8205, and 0.7351 (validation set I), and 0.9071, 0.8946, and 0.9107 (Validation set II), respectively. There was a reverse correlation between the high predicted point of panel and worse OS of CRC patients in training set (HR (95% CI): 0.1096 (0.07089–0.1694), P < 0.001), validation set I (HR (95% CI): 0.3350 (0.2116–0.5304), P < 0.001), and validation set II (HR (95% CI): 0.1568 (0.1090–0.2257), P < 0.001).

Conclusion

Our study showed that the panel of ACOT8/ACSL5/FASN/HMGBCS2/SCD1 genes had a better prognostic performance than validated clinical risk scales and is applicable for early detection of CRC and tumor recurrence.

RNA-sequencing and microarray data mining revealing: the aberrantly expressed mRNAs were related with a poor outcome in the triple negative breast cancer patients

Background

Triple negative breast cancer (TNBC) account for about 20% of breast carcinomas and the American society of clinical oncology guidelines does not specify approaches for TNBC patients since lack of specific driver molecules and targeted drugs.

Methods

We filtered out the aberrantly expressed mRNAs on the basis of RNA-seq data deposited in the Gene Expression Omnibus database, and verified and deeply analyzed screened differentially expressed genes (DEGs) using a combined bioinformatics approach.

Results

Of 21,755 genes with 472 TNBC cases from 3 independent laboratories, 159 mRNAs were identified as DEGs. To verify our results, we assessed the expression levels of top 8 DEGs in Oncomine database. The hierarchical clustering analysis, functional and pathway enrichment analysis were carried out for all DEGs. The results reveal that N-acetyltransferase 1 (NAT1) is most obvious of expression change's gene. Protein-protein interaction (PPI) network construction of 159 DEGs selected 3 hub genes: desmoglein 3 (DSG3), family with sequence similarity 83 member D (FAM83D) and GATA binding protein 3 (GATA3). For further analysis of the potential role of NAT1 in TNBC, the co-expression profiles of NAT1 in BC were made out, and we found that there are 5 genes [GATA3, trefoil factor 3 (TFF3), forkhead box A1 (FOXA1), signal peptide, CUB domain and EGF like domain containing 2 (SCUBE2), G protein-coupled receptor 160 (GPR160)] which co-expressed with NAT1 also were DEGs that we screened out before. Co-occurrence analysis confirmed that same as DEGs, GATA3 and SCUBE2 co-expressed with NAT1, and had a tendency towards a co-occurrence with NAT1 in TNBC. The survival curves showed that NAT1, GATA3 and SCUBE2 expression are significantly related with prognosis.

Conclusions

From all above results, we speculate that NAT1, GATA3 and SCUBE2 play a vital role in TNBC.

Placenta-Specific 8 Is Overexpressed and Regulates Cell Proliferation in Low-Grade Human Pancreatic Neuroendocrine Tumors

BACKGROUND/AIMS

Many aspects of the biology of pancreatic neuroendocrine tumors (PanNETs), including determinants of proliferative, invasive, and metastatic potential, remain poorly understood. Placenta-specific 8 (PLAC8), a gene with unknown molecular function, has been reported to have tumor-promoting roles in different human malignancies, including exocrine pancreatic cancer. Since preliminary data suggested deregulation of PLAC8 expression in PanNET, we have performed detailed analyses of PLAC8 expression and function in human PanNET.

METHODS

Primary tissue from PanNET patients was immunohistochemically stained for PLAC8, and expression was correlated with clinicopathological data. In vitro, PLAC8 expression was inhibited by siRNA transfection in PanNET cell lines and effects were analyzed by qRT-PCR, Western blot, and proliferation assays.

RESULTS

We report that PLAC8 is expressed in the majority of well-differentiated human PanNETs, predominantly in early-stage and low-grade tumors. SiRNA-mediated knockdown of PLAC8 in PanNET cells resulted in decreased proliferation and viability, while apoptosis was not induced. Mechanistically, these effects were mediated by attenuation of cell cycle progression, as Western blot analyses demonstrated upregulation of the tumor suppressor p21/CDKN2A and downregulation of the cell cycle regulator Cyclin D1 as well as reduced levels of phosphorylated ribosomal protein s6 and retinoblastoma protein.

CONCLUSION

Our findings establish PLAC8 as a central mediator of cell growth in a subset of human PanNET, providing evidence for the existence of distinct molecular subtypes within this class of tumors.

Identification of potential hub genes associated with the pathogenesis and prognosis of pancreatic duct adenocarcinoma using bioinformatics meta-analysis of multi-platform datasets

Pancreatic duct adenocarcinoma (PDAC) is a highly malignant type of cancer with a low five-year survival rate. Gene alterations are crucial to the molecular pathogenesis of PDAC. Therefore, the present study analyzed gene expression profiles to reveal genes involved in the tumorigenesis of PDAC. A total of eight gene expression profiles (GSE15471, GSE16515, GSE41368, GSE62165, GSE62452, GSE71729, GSE71989 and GSE91035) and a PDAC dataset were acquired from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database, respectively. Differentially expressed genes (DEGs) were screened using functional annotation, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) network construction. A Cox proportional hazards model was then constructed and used to analyze the data. A total of 136 DEGs (67 up- and 69 downregulated genes) were identified between PDAC tissues and normal tissues. The ‘extracellular matrix-related’ genes were the most enriched in the GO term analysis. ‘Pancreatic secretion’, ‘phosphoinositide-3-kinase–protein kinase B/Akt (PI3K-Akt) signaling pathway’, ‘protein digestion and absorption’ and ‘ECM-receptor interaction’ were the most enriched categories in KEGG pathway analysis. Following PPI network construction, the 10 most significant genes [albumin, epidermal growth factor, matrix metalloproteinase (MMP) 9, epidermal growth factor receptor, fibronectin 1, MMP1, plasminogen activator inhibitor-1, tissue inhibitor of metalloproteinase 1, plasminogen activator urokinase (PLAU) and PLAU receptor) exhibiting a high degree of connectivity, were identified as the hub genes likely to be associated with the pathogenesis of PDAC. In addition, a prognostic predictive system for PDAC, composed of five genes (laminin subunit γ 2, laminin subunit β 3, serpin family B member 5, amphiregulin and secreted frizzled related protein 4), was constructed. This was validated in the GSE62452 dataset (using 66 PDAC samples with outcome data) and TCGA PDAC dataset (using 146 PDAC samples with outcome data). In conclusion, the present study revealed potential hub genes involved in PDAC progression, providing directive significance for individualized clinical decision-making and molecular-targeting therapy in patients with PDAC.

The YAP1-NMU Axis Is Associated with Pancreatic Cancer Progression and Poor Outcome: Identification of a Novel Diagnostic Biomarker and Therapeutic Target

Yes-associated protein (YAP)-1 is highly upregulated in pancreatic cancer and associated with tumor progression. However, little is known about the role of YAP1 and related genes in pancreatic cancer. Here, we identified target genes regulated by YAP1 and explored their role in pancreatic cancer progression and the related clinical implications. Analysis of different pancreatic cancer databases showed that Neuromedin U (NMU) expression was positively correlated with YAP1 expression in the tumor group. The Cancer Genome Atlas data indicated that high YAP1 and NMU expression levels were associated with poor mean and overall survival. YAP1 overexpression induced NMU expression and transcription and promoted cell motility in vitro and tumor metastasis in vivo via upregulation of epithelial-mesenchymal transition (EMT), whereas specific inhibition of NMU in cells stably expressing YAP1 had the opposite effect in vitro and in vivo. To define this functional association, we identified a transcriptional enhanced associate domain (TEAD) binding site in the NMU promoter and demonstrated that YAP1-TEAD binding upstream of the NMU gene regulated its transcription. These results indicate that the identified positive correlation between YAP1 and NMU is a potential novel drug target and biomarker in metastatic pancreatic cancer.

Expression of endoplasmic reticulum oxidoreductase 1-α in cholangiocarcinoma tissues and its effects on the proliferation and migration of cholangiocarcinoma cells

Abstract

Endoplasmic reticulum oxidoreductase 1-α (ERO1A) is a kind of hypoxia-induced endoplasmic reticulum oxidase that regulates translation and folding of oxidized proteins. This study aimed to explore the clinicopathological significance of ERO1A and the effect on the biological behavior of cholangiocarcinoma (CCA) cells.

Methods

Immunohistochemical staining was used to detect the expression of ERO1A, carcinoembryonic antigen (CEA), and carbohydrate antigen 19–9 (CA19-9) in cholangiocarcinoma. Immunofluorescence staining was performed to detect the subcellular localization of ERO1A in CCA cells. The expression of ERO1A in CAA cells after depletion or overexpression was verified by Western blot assay. Then, the effect of ERO1A on proliferation in CCA cells was verified by MTT assay and colony formation assay. Wound healing assays and migration assays were performed to detect the effect of ERO1A on cell migration ability. Finally, we explored the role of ERO1A in EMT and Akt/mTOR signaling pathway.

Results

In this study, our data demonstrated that ERO1A, CEA, and CA19-9 were expressed in cholangiocarcinoma tissues, and the positive rates were 95%, 95%, and 55%, respectively. The high expression of ERO1A is associated with clinical stage and pathological stage of CCA. In vitro data indicate that deletion of ERO1A can inhibit the proliferation and migration of CCA cells and vice versa. In addition, ERO1A has been shown to be closely related to EMT and Akt/mTOR pathways.

Conclusion

In summary, we found that high expression of ERO1A is associated with poor prognosis in patients, and ERO1A can promote the proliferation and migration of CCA cells. In conclusion, ERO1A can be used as an independent biomarker for predicting the prognosis of CCA.

Splice-site variant in ACSL5: a marker promoting opposing effect on cell viability and protein expression

Long-chain Acyl-CoA synthetases (ACSLs) activate fatty acids (FAs) by thioesterification with Coenzyme A (CoA), generating FA-CoAs. These products are essential for lipid metabolism and carcinogenesis. In previous study, we identified an intronic variant rs2256368:A>G, whose G allele promotes exon 20 skipping in up to 43% of ACSL5 transcripts but its functional relevance is unclear. Here, we compared the expression of splice (Spl) and nonsplice (NSpl) ACSL5 variants and the effect on cell viability under culture conditions that force cells to metabolize fatty acids. We found that lymphoblastoid cell lines from 1000 Genomes Project, bearing Spl genotypes, showed a reduced expression of total ACSL5 protein due to an inefficient translation of the Spl RNA. These cells impaired growth in cultures with phorbol myristate acetate-ionomycin (PMA-Io) or medium deprived of glucose, while production of reactive oxygen species increased in PMA-Io. Specific ACSL5-isoform transfection in HEK239T (kidney), U87 (astroglioma), and HOG (oligodendrocyte) cells showed the Spl protein to be the causal factor of cell-growth inhibition, despite its reduced protein expression. Our findings indicate that the variant rs2256368:A>G can predict a growth inhibitory activity, caused by the Spl isoform of ACSL5 protein, opposed to the activity of the NSpl. Deep understanding of its functioning might have application in metabolic diseases and cancer.

Prognostic Biomarkers in Pancreatic Cancer: Avoiding Errata When Using the TCGA Dataset

Data from the Cancer Genome Atlas (TCGA) are now easily accessible through web-based platforms with tools to assess the prognostic value of molecular alterations. Pancreatic tumors have heterogeneous biology and aggressiveness ranging from the deadly adenocarcinoma (PDAC) to the better prognosis, neuroendocrine tumors. We assessed the availability of the pancreatic cancer TCGA data (TCGA_PAAD) from several repositories and investigated the nature of each sample and how non-PDAC samples impact prognostic biomarker studies. While the clinical and genomic data (n = 185) were fairly consistent across all repositories, RNAseq profiles varied from 176 to 185. As a result, 35 RNAseq profiles (18.9%) corresponded to a normal, inflamed pancreas or non-PDAC neoplasms. This information was difficult to obtain. By considering gene expression data as continuous values, the expression of the 5312 and 4221 genes were significantly associated with the progression-free and overall survival respectively. Considering the cohort was not curated, only 4 and 14, respectively, had prognostic value in the PDAC-only cohort. Similarly, mutations in key genes or well-described miRNA lost their prognostic significance in the PDAC-only cohort. Therefore, we propose a web-based application to assess biomarkers in the curated TCGA_PAAD dataset. In conclusion, TCGA_PAAD curation is critical to avoid important biological and clinical biases from non-PDAC samples.

Oxysterols and Gastrointestinal Cancers Around the Clock

This review focuses on the role of oxidized sterols in three major gastrointestinal cancers (hepatocellular carcinoma, pancreatic, and colon cancer) and how the circadian clock affects the carcinogenesis by regulating the lipid metabolism and beyond. While each field of research (cancer, oxysterols, and circadian clock) is well-studied within their specialty, little is known about the intertwining mechanisms and how these influence the disease etiology in each cancer type. Oxysterols are involved in pathology of these cancers, but final conclusions about their protective or damaging effects are elusive, since the effect depends on the type of oxysterol, concentration, and the cell type. Oxysterol concentrations, the expression of key regulators liver X receptors (LXR), farnesoid X receptor (FXR), and oxysterol-binding proteins (OSBP) family are modulated in tumors and plasma of cancer patients, exposing these proteins and selected oxysterols as new potential biomarkers and drug targets. Evidence about how cholesterol/oxysterol pathways are intertwined with circadian clock is building. Identified key contact points are different forms of retinoic acid receptor related orphan receptors (ROR) and LXRs. RORs and LXRs are both regulated by sterols/oxysterols and the circadian clock and in return also regulate the same pathways, representing a complex interplay between sterol metabolism and the clock. With this in mind, in addition to classical therapies to modulate cholesterol in gastrointestinal cancers, such as the statin therapy, the time is ripe also for therapies where time and duration of the drug application is taken as an important factor for successful therapies. The final goal is the personalized approach with chronotherapy for disease management and treatment in order to increase the positive drug effects.

Targeting glypican-4 overcomes 5-FU resistance and attenuates stem cell-like properties via suppression of Wnt/β-catenin pathway in pancreatic cancer cells

The existences of cancer stem cells in patients with pancreatic cancer are considered as pivotal factors contributing to chemoresistance and disease relapse. Glypican-4 (GPC4) is one of the members of the glypicans family, which underlies human congenital malformations and multiple diseases. However, its potential biological function in pancreatic cancer still remains elusive. In this study, we are the first to demonstrate that GPC4 was involved in 5-fluorouracil (5-FU) resistance and pancreatic cancer stemness through comprehensive bioinformatical analysis. Functional experiments showed that knockdown of GPC4 sensitized pancreatic cancer cells to 5-FU and attenuated stem cell-like properties. In terms of mechanism research, knockdown of GPC4 suppressed the activation of Wnt/β-catenin pathway and its downstream targets. Furthermore, the expression of GPC4 was significantly upregulated in pancreatic cancer tissues compared with normal tissues and remarkably correlated with patients' overall survival according to the data derived from the Cancer Genome Atlas database. Taken together, our results suggest that GPC4 is a key regulator in chemoresistance and pancreatic cancer stemness. Thus, targeting GPC4 may serve as a promising strategy for pancreatic cancer therapy.

Transcriptome-wide association study identifies multiple genes and pathways associated with pancreatic cancer

AIM

To identify novel candidate genes for pancreatic cancer.

METHODS

We performed a transcriptome-wide association study (TWAS) analysis of pancreatic cancer (PC). GWAS summary data were driven from the published studies of PC, totally involving 558 542 SNPs in 1896 individuals with pancreatic cancer and 1939 healthy controls. FUSION software was applied to the PC GWAS summary data for tissue-related TWAS analysis, including whole blood, peripheral blood, adipose, and pancreas. The functional relevance of identified genes with PC was further validated by Oncomine, STRING, and CluePedia tool.

RESULTS

Transcriptome-wide association study analysis identified 19 genes significantly associated with PC, such as LRP5L (P value = 5.21 × 10^-5 ), SOX4 (P value = 3.2 × 10^-4 ), and EGLN3 (P value = 6.2 × 10^-3 ). KEGG pathway enrichment analysis detected several PC-associated pathways, such as One carbon pool by folate (P value = 1.60 × 10^-16 ), Cell cycle (P value = 1.27 × 10^-7 ), TGF-beta signaling pathway (P value = 4.64 × 10^-6 ). Further comparing the 19 genes with previously identified overexpressed genes in PC patients found one overlapped gene SOX4.

CONCLUSION

We identified some novel candidate genes and pathways associated with PC. Our results provide novel clues for the genetic mechanism studies of pancreatic cancer.

Bridging the molecular and biological functions of the oxysterol-binding protein family

Oxysterol-binding protein (OSBP) and OSBP-related proteins (ORPs) constitute a large eukaryotic gene family that transports and regulates the metabolism of sterols and phospholipids. The original classification of the family based on oxysterol-binding activity belies the complex dual lipid-binding specificity of the conserved OSBP homology domain (OHD). Additional protein- and membrane-interacting modules mediate the targeting of select OSBP/ORPs to membrane contact sites between organelles, thus positioning the OHD between opposing membranes for lipid transfer and metabolic regulation. This unique subcellular location, coupled with diverse ligand preferences and tissue distribution, has identified OSBP/ORPs as key arbiters of membrane composition and function. Here, we will review how molecular models of OSBP/ORP-mediated intracellular lipid transport and regulation at membrane contact sites relate to their emerging roles in cellular and organismal functions.

Liquid Biopsy Using Whole Blood from Testis Tumor and Colon Cancer Patients-A New and Simple Way?

Tumor cells shed exosomes, which are released to the blood. Detecting tumor-derived exosomes containing RNA in plasma (liquid biopsy) is currently being investigated for early identification of occult metastases or relapses. Isolation of exosomes is laborious, resulting in low RNA yields. As a more robust (but less sensitive) alternative, the authors examined whether whole blood can be used as well. Tumor samples from nonmetastasized seminoma (n = 5) and colon cancer patients (n = 6) were taken during surgery. Whole-blood samples were taken before and 5-7 d after surgery. A whole genome mRNA microarray screening was performed. Candidate genes were selected based on two criteria: (1) gene expression in the presurgical whole-blood sample/tumor biopsy; and (2) a two-fold decrease in the copy number of candidate genes was expected in the postsurgical whole-blood sample 5-7 d after intervention, relative to the presurgical blood sample. The rationale behind this is the loss of tumor material in the body and the decline in the release of tumor-derived RNA in exosomes. For both tumor entities and for each patient, several hundred candidate genes could be identified. In a group-wise comparison, 20 candidate genes could be identified in the seminoma and 32 in the colon cancer group. These findings indicate that whole blood might be suitable for a liquid biopsy. However, this study identified the short period after surgery (5-7 d) as a possible confounder. The authors plan to add an additional time point several weeks after the operation to discriminate tumor candidate genes from genes induced by the surgery.

IFI44L is a novel tumor suppressor in human hepatocellular carcinoma affecting cancer stemness, metastasis, and drug resistance via regulating met/Src signaling pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. The disease recurrent rate is relatively high resulted in poor 5-year survival in advanced HCC. Cancer stem cells (CSCs) have been considered to be one of the main mechanisms for chemoresistance, metastasis, and recurrent disease. Interferon-induced protein 44-like (IFI44L) gene is a type I interferon-stimulated gene (ISG) and belongs to the IFI44 family. Previous reports indicated antiviral activity against HCV in IFI44L, however, its precise role and function in HCC has not been unveiled.

METHODS

To explore the characteristics of hepatic CSCs, we successfully enriched hepatic cancer stem-like cells from three established liver cancer cell lines (Hep3B, HepG2, and PLC lines). Parental Hep3B and HepG2 cells and their sphere cells were treated with doxorubicin for 48 h and cell viability was measured by MTT assay. HCC tissue blocks from 217 patients were sampled for tissue microarray (TMA). Follow-up information and histopathological and clinical data including age, gender, tumor grade, advanced stages, HBV, HCV, tumor number, tumor size, relapse-free survival, and overall survival were obtained from the cancer registry and medical charts. The liver TMA was evaluated for IFI44L expression using immunohistochemical staining and scores.

RESULTS

These hepatic cancer stem-like cells possess important cancer stemness characteristics including sphere-forming abilities, expressing important HCC cancer stem cell markers, and more chemoresistant. Interestingly, we found that overexpression of IFI44L decreased chemoresistance towards doxorubicin and knockdown of IFI44L restored chemoresistance as well as promoted sphere formation. Furthermore, we found that depletion of IFI44L enhanced migration, invasion, and pulmonary metastasis through activating Met/Src signaling pathway. Clinically, the expression level of IFI44L significantly reduced in HCC tumor tissues. Low expression of IFI44L levels also correlated with larger tumor size, disease relapse, advanced stages, and poor clinical survival in HCC patients.

CONCLUSION

Taken together, we first demonstrated that IFI44L is a novel tumor suppressor to affect cancer stemness, metastasis, and drug resistance via regulating Met/Src signaling pathway in HCC and can be serve as an important prognostic marker.

Curation of the Pancreatic Ductal Adenocarcinoma Subset of the Cancer Genome Atlas Is Essential for Accurate Conclusions about Survival-Related Molecular Mechanisms

Purpose: Publicly available databases, for example, The Cancer Genome Atlas (TCGA), containing clinical and molecular data from many patients are useful in validating the contribution of particular genes to disease mechanisms and in forming novel hypotheses relating to clinical outcomes.Experimental Design: The impact of key drivers of cancer progression can be assessed by segregating a patient cohort by certain molecular features and constructing survival plots using the associated clinical data. However, conclusions drawn from this straightforward analysis are highly dependent on the quality and source of tissue samples, as demonstrated through the pancreatic ductal adenocarcinoma (PDAC) subset of TCGA.Results: Analyses of the PDAC-TCGA database, which contains mainly resectable cancer samples from patients in stage IIB, reveal a difference from widely known historic median and 5-year survival rates of PDAC. A similar discrepancy was observed in lung, stomach, and liver cancer subsets of TCGA. The whole transcriptome expression patterns of PDAC-TCGA revealed a cluster of samples derived from neuroendocrine tumors, which have a distinctive biology and better disease prognosis than PDAC. Furthermore, PDAC-TCGA contains numerous pseudo-normal samples, as well as those that arose from tumors not classified as PDAC.Conclusions: Inclusion of misclassified samples in the bioinformatic analyses distorts the association of molecular biomarkers with clinical outcomes, altering multiple published conclusions used to support and motivate experimental research. Hence, the stringent scrutiny of type and origin of samples included in the bioinformatic analyses by researchers, databases, and web-tool developers is of crucial importance for generating accurate conclusions. Clin Cancer Res; 24(16); 3813-9. ©2018 AACR.

DDX5/p68 associated lncRNA LOC284454 is differentially expressed in human cancers and modulates gene expression

Long non-coding RNAs (lncRNAs) are emerging as important players in regulation of gene expression in higher eukaryotes. DDX5/p68 RNA helicase protein which is involved in splicing of precursor mRNAs also interacts with lncRNAs like, SRA and mrhl, to modulate gene expression. We performed RIP-seq analysis in HEK293T cells to identify the complete repertoire of DDX5/p68 interacting transcripts including 73 single exonic (SE) lncRNAs. The LOC284454 lncRNA is the second top hit of the list of SE lncRNAs which we have characterized in detail for its molecular features and cellular functions. The RNA is located in the same primary transcript harboring miR-23a∼27a∼24-2 cluster. LOC284454 is a stable, nuclear restricted and chromatin associated lncRNA. The sequence is conserved only in primates among 26 different species and is expressed in multiple human tissues. Expression of LOC284454 is significantly reduced in breast, prostate, uterus and kidney cancer and also in breast cancer cell lines (MCF7 and T47D). Global gene expression studies upon loss and gain of function of LOC284454 revealed perturbation of genes related to cancer-related pathways. Focal adhesion and cell migration pathway genes are downregulated under overexpression condition, and these genes are significantly upregulated in breast cancer cell lines as well as breast cancer tissue samples suggesting a functional role of LOC284454 lncRNA in breast cancer pathobiology.

[Small interfering RNA-mediated α-enolase knockdown suppresses glycolysis and proliferation of human glioma U251 cells in vitro]

OBJECTIVE

To investigate the role of α-enolase (ENO1) in regulating glucose metabolism and cell growth in human glioma cells.

METHODS

Glucose uptake and lactate generation were assessed to evaluate the changes in glucose metabolism in human glioma U251 cells with small interfering RNA (siRNA)-mediated ENO1 knockdown. MTT assay and 5-ethynyl-2'-deoxyuridine (EdU) staining were used to examine the cell growth and cell cycle changes following siRNA transfection of the cells.

RESULTS

Transfection of U251 cells with siRNA-ENO1 markedly reduced glucose uptake (P=0.023) and lactate generation (P=0.007) in the cells and resulted in significant suppression of cell proliferation (*P<0.05) since the second day following the transfection. Transfection with siRNA-ENO1 also obviously suppressed cell cycle G1/S transition in the cells (P=0.0425). The expressions of HK2 and LDHA, the marker genes for glucose metabolism, were significantly down-regulated in the cells with siRNA-mediated ENO1 knockdown.

CONCLUSION

ENO1 as a potential oncogene promotes glioma cell growth by positively modulating glucose metabolism.

Long noncoding RNA NORAD, a novel competing endogenous RNA, enhances the hypoxia-induced epithelial-mesenchymal transition to promote metastasis in pancreatic cancer

Background

Pancreatic cancer, one of the top two most fatal cancers, is characterized by a desmoplastic reaction that creates a dense microenvironment, promoting hypoxia and inducing the epithelial-to-mesenchymal transition (EMT) to facilitate invasion and metastasis. Recent evidence indicates that the long noncoding RNA NORAD may be a potential oncogenic gene and that this lncRNA is significantly upregulated during hypoxia. However, the overall biological role and clinical significance of NORAD remains largely unknown.

Methods

NORAD expression was measured in 33 paired cancerous and noncancerous tissue samples by real-time PCR. The effects of NORAD on pancreatic cancer cells were studied by overexpression and knockdown in vitro. Insights into the mechanism of competitive endogenous RNAs (ceRNAs) were gained from bioinformatics analyses and luciferase assays. In vivo, metastatic potential was identified using an orthotopic model of PDAC and quantified using bioluminescent signals. Alterations in RhoA expression and EMT levels were identified and verified by immunohistochemistry and Western blotting.

Results

NORAD is highly expressed in pancreatic cancer tissues and upregulated in hypoxic conditions. NORAD upregulation is correlated with shorter overall survival in pancreatic cancer patients. Furthermore, NORAD overexpression promoted the migration and invasion of pancreatic carcinoma cells, while NORAD depletion inhibited EMT and metastasis in vitro and in vivo. In particular, NORAD may function as a ceRNA to regulate the expression of the small GTP binding protein RhoA through competition for hsa-miR-125a-3p, thereby promoting EMT.

Conclusions

Elevated expression of NORAD in pancreatic cancer tissues is linked to poor prognosis and may confer a malignant phenotype upon tumor cells. NORAD may function as a ceRNA to regulate the expression of the small GTP binding protein RhoA through competition for hsa-miR-125a-3p. This finding may contribute to a better understanding of the role played by lncRNAs in hypoxia-induced EMT and provide a potential novel diagnostic and therapeutic target for pancreatic cancer.

Electronic supplementary material

The online version of this article (10.1186/s12943-017-0738-0) contains supplementary material, which is available to authorized users.

Common Subcluster Mining in Microarray Data for Molecular Biomarker Discovery

Molecular biomarkers can be potential facilitators for detection of cancer at early stage which is otherwise difficult through conventional biomarkers. Gene expression data from microarray experiments on both normal and diseased cell samples provide enormous scope to explore genetic relations of disease using computational techniques. Varied patterns of expressions of thousands of genes at different cell conditions along with inherent experimental error make the task of isolating disease related genes challenging. In this paper, we present a data mining method, common subcluster mining (CSM), to discover highly perturbed genes under diseased condition from differential expression patterns. The method builds heap through superposing near centroid clusters from gene expression data of normal samples and extracts its core part. It, thus, isolates genes exhibiting the most stable state across normal samples and constitute a reference set for each centroid. It performs the same operation on datasets from corresponding diseased samples and isolates the genes showing drastic changes in their expression patterns. The method thus finds the disease-sensitive genesets when applied to datasets of lung cancer, prostrate cancer, pancreatic cancer, breast cancer, leukemia and pulmonary arterial hypertension. In majority of the cases, few new genes are found over and above some previously reported ones. Genes with distinct deviations in diseased samples are prospective candidates for molecular biomarkers of the respective disease.

Recurrence-associated gene signature optimizes recurrence-free survival prediction of colorectal cancer

High throughput gene expression profiling has showed great promise in providing insight into molecular mechanisms. Metastasis‐related mRNAs may potentially enrich genes with the ability to predict cancer recurrence, therefore we attempted to build a recurrence‐associated gene signature to improve prognostic prediction of colorectal cancer (CRC). We identified 2848 differentially expressed mRNAs by analyzing CRC tissues with or without metastasis. For the selection of prognostic genes, a LASSO Cox regression model (least absolute shrinkage and selection operator method) was employed. Using this method, a 13‐mRNA signature was identified and then validated in two independent Gene Expression Omnibus cohorts. This classifier could successfully discriminate the high‐risk patients in discovery cohort [hazard ratio (HR) = 5.27, 95% confidence interval (CI) 2.30–12.08, P < 0.0001). Analysis in two independent cohorts yielded consistent results (GSE14333: HR = 4.55, 95% CI 2.18–9.508, P < 0.0001; GSE33113: HR = 3.26, 95% CI 2.16–9.16, P = 0.0176). Further analysis revealed that the prognostic value of this signature was independent of tumor stage, postoperative chemotherapy and somatic mutation. Receiver operating characteristic (ROC) analysis showed that the area under ROC curve of this signature was 0.8861 and 0.8157 in the discovery and validation cohort, respectively. A nomogram was constructed for clinicians, and did well in the calibration plots. Furthermore, this 13‐mRNA signature outperformed other known gene signatures, including oncotypeDX colon cancer assay. Single‐sample gene‐set enrichment analysis revealed that a group of pathways related to drug resistance, cancer metastasis and stemness were significantly enriched in the high‐risk patients. In conclusion, this 13‐mRNA signature may be a useful tool for prognostic evaluation and will facilitate personalized management of CRC patients.

Genome-scale analysis to identify prognostic markers in patients with early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy

BACKGROUND

Molecular analysis is a promising source of clinically useful prognostic biomarkers. The aim of this investigation was to identify prognostic biomarkers for patients with early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy.

METHODS

An RNA sequencing dataset of PDAC was obtained from The Cancer Genome Atlas. Survival analysis and weighted gene co-expression network analysis were used to investigate the prognostic markers of early-stage PDAC after pancreaticoduodenectomy.

RESULTS

Using whole genome expression level screening, we identified 1,238 markers that were related to the prognosis of PDAC after pancreaticoduodenectomy, and identified 9 hub genes (ARHGAP30, HCLS1, CD96, FAM78A, ARHGAP15, SLA2, CD247, GVINP1, and IL16) using the weighted gene co-expression network analysis approach. We also constructed a signature comprising the 9 hub genes and weighted by the regression coefficient derived from a multivariate Cox proportional hazards regression model to divide patients into a high-risk group, with increased risk of death, and a low-risk group, with significantly improved overall survival (adjusted P=0.026, adjusted HR =0.513, 95% CI =0.285-0.924). The prognostic signature of the 9 genes demonstrated good performance for predicting 1-year overall survival (area under the respective receiver operating characteristic curves =0.641).

CONCLUSION

Our results have provided a new prospect for prognostic biomarkers of PDAC after pancreaticoduodenectomy, and may have a value in clinical application.