Bioinformatics analysis combined with experiments to explore potential prognostic factors for pancreatic cancer

Identification of exosome-related genes associated with prognosis and immune infiltration features in pancreatic cancer

BACKGROUND

This study is designed to explore the prognostic significance of exosome-related genes (ERGs) and their impact on the the tumor microenvironment (TME) of pancreatic cancer.

METHODS

Transcriptomic data alongside clinical details of patients with PC were retrieved from both The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) repository. A collection of 121 exosome-associated genes were obtained from the ExoBCD database. For constructing a risk scoring model, the absolute shrinkage and selection operator (LASSO) regression method was employed. Gene set enrichment and variance analyses were facilitated by the clusterProfiler and GSVA R software tools. Additionally, CIBERSORT was used to estimate immune cell infiltration levels. Lastly, the TIDE algorithm was leveraged to evaluate the connection between gene expression and drug sensitivity. A series of experiments were used to verify the role of DLGAP5 in PC.

RESULTS

Two unique molecular clusters were uncovered, and our analysis revealed a connection between ERG dysregulation across multiple layers and patient demographic, histopathological attributes, prognosis, as well as immune cell infiltration patterns within the TME. An ERG_score was developed for forecasting overall survival and its predictive capacity was confirmed in PC cases. A precise nomogram was established to enhance the clinical utility of the ERG_score. Patients in the low-risk group exhibited higher immune and ESTIMATE scores than that in the high-risk group, displaying an improved overall survival (OS). The ERG_score was associated with cancer stem cell (CSC) index and drug sensitivity. Crucial evaluations of ERGs illuminated the significance of DLGAP5, emphasizing its expression in PC and its contributory role in tumor growth stimulation.

CONCLUSIONS

Our investigation reveals a correlation between the exosome-related risk assessment signature and the survival outcome as well as immune cell infiltration in patients with PC. This finding potentially paves the way for enhanced therapeutic strategies for PC.

Kernel-based hierarchical structural component models for pathway analysis on survival phenotype

BACKGROUND

High-throughput sequencing, particularly RNA-sequencing (RNA-seq), has advanced differential gene expression analysis, revealing pathways involved in various biological conditions. Traditional pathway-based methods generally consider pathways independently, overlooking the correlations among them and ignoring quite a few overlapping biomarkers between pathways. In addition, most pathway-based approaches assume that biomarkers have linear effects on the phenotype of interest.

OBJECTIVE

This study aims to develop the HisCoM-KernelS model to identify survival phenotype-related pathways by accommodating complex, nonlinear relationships between genes and survival outcomes, while accounting for inter-pathway correlations.

METHODS

We applied HisCoM-KernelS model to the TCGA pancreatic ductal adenocarcinoma (PDAC) RNA-seq dataset, comprising 4,498 protein-coding genes mapped to 186 KEGG pathways from 148 PDAC samples. Kernel machine regression was used to model pathway effects on survival outcomes, incorporating hierarchical gene-pathway structures. Model parameters were estimated using the alternating least squares algorithm, and the significance of pathways was assessed through a permutation test.

RESULTS

HisCoM-KernelS identified several pathways significantly associated with pancreatic cancer survival, including those corroborated by previous studies. HisCoM-KernelS, especially with the Gaussian kernel, showed a better balance of detection rate and number of significant pathways compared to four other existing pathway-based methods: HisCoM-PAGE, Global Test, GSEA, and CoxKM.

CONCLUSION

HisCoM-KernelS successfully extends pathway-based analysis to survival outcomes, capturing complex nonlinear gene effects and inter-pathway correlations. Its application to the TCGA PDAC dataset emphasizes its utility in identifying biologically relevant pathways, offering a robust tool for survival phenotype research in high-throughput sequencing data.

Retracted article: MicroRNA-4521 targets hepatoma up-regulated protein (HURP) to inhibit the malignant progression of breast cancer

Changwen Li, Sen Pengb, and Chuangang Tanga. MicroRNA-4521 targets hepatoma up-regulated protein (HURP) to inhibit the malignant progression of breast cancer. Bioengineered. 2021 Oct. doi: 10.1080/21655979.2021.1996016.Since publication, significant concerns have been raised about the compliance with ethical policies for human research and the integrity of the data reported in the article.When approached for an explanation, the authors provided some original data but were not able to provide all the necessary supporting information. As verifying the validity of published work is core to the scholarly record's integrity, we are retracting the article. All authors listed in this publication have been informed.We have been informed in our decision-making by our editorial policies and the COPE guidelines.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as 'Retracted.'

Transcriptional regulation of DLGAP5 by AR suppresses p53 signaling and inhibits CD8+T cell infiltration in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a challenging subtype with unclear biological mechanisms. Recently, the transcription factor androgen receptor (AR) and its regulation of the DLGAP5 gene have gained attention in TNBC pathogenesis. In this study, we found a positive correlation between high AR expression and TNBC cell proliferation and growth. Furthermore, we confirmed DLGAP5 as a critical downstream regulator of AR with high expression in TNBC tissues. Knockdown of DLGAP5 significantly inhibited TNBC cell proliferation, migration, and invasion. AR was observed to directly bind to the DLGAP5 promoter, enhancing its transcriptional activity and suppressing the activation of the p53 signaling pathway. In vivo experiments further validated that downregulation of AR or DLGAP5 inhibited tumor growth and enhanced CD8+T cell infiltration. This study highlights the crucial roles of AR and DLGAP5 in TNBC growth and immune cell infiltration. Taken together, AR inhibits the p53 signaling pathway by promoting DLGAP5 expression, thereby impacting CD8+T cell infiltration in TNBC.

Application of integrin subunit genes in pancreatic cancer and the construction of a prognosis model

Background

Pancreatic adenocarcinoma (PAAD) is a highly aggressive malignant tumor with a poor prognosis. Integrin subunit genes (ITGs) serve as biomarkers for various types of cancers; however, to date, no prognostic research has been conducted on the ITGs in PAAD. This study aims to fill this gap by investigating the role of ITGs in PAAD prognosis.

Methods

RNA-sequencing data, clinicopathological features, and survival information from The Cancer Genome Atlas (TCGA) database were sourced via GTEx. The GSE62452 data set was acquired from the Gene Expression Omnibus (GEO) database. A single-sample gene set enrichment analysis (ssGSEA) was first conducted to classify the PAAD samples from TCGA and GEO data sets with different ITG scores. A differential analysis was employed to identify the differentially expressed genes (DEGs) between the normal and PAAD samples, and between the high and low ITG score groups in both TCGA and GEO data sets.

Results

A total of 22 key differentially expressed ITGs (KDE-ITGs) were identified and enriched in eight Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway, focal adhesion, and the extracellular matrix (ECM)-receptor interaction. A prognostic model comprising the eight KDE-ITGs was established. Additionally, 2,371 DEGs were found between the high- and low-risk groups, which were mainly enriched in the Gene Ontology (GO) terms of cell morphogenesis and cytokine production, and KEGG pathways such as necroptosis, lysosome, and ferroptosis. Further, the proportions of T cells and cluster of differentiation 8 (CD8) T cells, and the expression levels of immune checkpoints, such as cluster of differentiation 274 (CD274) and lymphocyte activating gene 3 (LAG3), differed significantly between the two risk groups.

Conclusions

The eight identified KDE-ITGs in PAAD were used to establish a new prognosis model, which might have clinical application, especially in immunotherapy.

The identification of biomarkers for Alzheimer's disease using a systems biology approach based on lncRNA-circRNA-miRNA-mRNA ceRNA networks

In addition to being the most prevalent form of neurodegeneration among the elderly, AD is a devastating multifactorial disease. Currently, treatments address only its symptoms. Several clinical studies have shown that the disease begins to manifest decades before the first symptoms appear, indicating that studying early changes is crucial to improving early diagnosis and discovering novel treatments. Our study used bioinformatics and systems biology to identify biomarkers in AD that could be used for diagnosis and prognosis. The procedure was performed on data from the GEO database, and GO and KEGG enrichment analysis were performed. Then, we set up a network of interactions between proteins. Several miRNA prediction tools including miRDB, miRWalk, and TargetScan were used. The ceRNA network led to the identification of eight mRNAs, four circRNAs, seven miRNAs, and seven lncRNAs. Multiple mechanisms, including the cell cycle and DNA replication, have been linked to the promotion of AD development by the ceRNA network. By using the ceRNA network, it should be possible to extract prospective biomarkers and therapeutic targets for the treatment of AD. It is possible that the processes involved in DNA cell cycle and the replication of DNA contribute to the development of Alzheimer's disease.

Single-cell analysis identifies critical regulators of spermatogonial development and differentiation in cattle-yak bulls

Spermatogenesis is a continuous process in which functional sperm are produced through a series of mitotic and meiotic divisions and morphological changes in germ cells. The aberrant development and fate transitions of spermatogenic cells cause hybrid sterility in mammals. Cattle-yak, a hybrid animal between taurine cattle (Bos taurus) and yak (Bos grunniens), exhibits male-specific sterility due to spermatogenic failure. In the present study, we performed single-cell RNA sequencing analysis to identify differences in testicular cell composition and the developmental trajectory of spermatogenic cells between yak and cattle-yak. The composition and molecular signatures of spermatogonial subtypes were dramatically different between these 2 animals, and the expression of genes associated with stem cell maintenance, cell differentiation and meiotic entry was altered in cattle-yak, indicating the impairment of undifferentiated spermatogonial fate decisions. Cell communication analysis revealed that signaling within different spermatogenic cell subpopulations was weakened, and progenitor spermatogonia were unable to or delayed receiving and sending signals for transformation to the next stage in cattle-yak. Simultaneously, the communication between niche cells and germ cells was also abnormal. Collectively, we obtained the expression profiles of transcriptome signatures of different germ cells and testicular somatic cell populations at the single-cell level and identified critical regulators of spermatogonial differentiation and meiosis in yak and sterile cattle-yak. The findings of this study shed light on the genetic mechanisms that lead to hybrid sterility and speciation in bovid species.

Identification of potential biomarkers for pancreatic ductal adenocarcinoma: a bioinformatics analysis

PDA is an aggressive cancer with a 5-year survival rate, which is very low. There is no effective prognosis or therapy for PDA because of the lack of target biomarkers. The objective of this article is to identify the target biomarkers for PDA using a bioinformatics approach. In this work, we have analysed the three microarray datasets from the NCBI GEO database. We used the Geo2R tool to analyse the microarray data with the Benjamini and Hochberg false discovery rate method, and the significance level cut-off was set to 0.05. We have identified 659 DEGs from the datasets. There are a total of 15 hub genes that were selected from the PPI network constructed using the STRING application. Furthermore, these 15 genes were evaluated on PDA patients using TCGA and GTEx databases in (GEPIA). The online tool DAVID was used to analyse the functional annotation information for the DEGs. The functional pathway enrichment was performed on the GO and KEGG. The hub genes were mainly enriched for cell division, chromosome segregation, protein binding and microtubule binding. Further, the gene alteration study was performed using the cBioportal tool and screened out six hub genes (ASPM, CENPF, BIRC5, TTK, DLGAP5, and TOP2A) with a high alteration rate in PDA samples. Furthermore, Kaplan-Meier survival analysis was performed on the six hub genes and identified poor-survival outcomes that may be involved in tumorigenesis and PDA development. So, this study concludes that, these six hub genes may be potential prognostic biomarkers for PDA.

Value of diffusion kurtosis MR imaging and conventional diffusion weighed imaging for evaluating response to first-line chemotherapy in unresectable pancreatic cancer

OBJECTIVE

To investigate the diagnostic value of diffusion kurtosis magnetic resonance imaging (DKI) and conventional diffusion-weighted imaging (DWI) for evaluating the response to first-line chemotherapy in unresectable pancreatic cancer.

MATERIALS AND METHODS

We retrospectively analyzed 21 patients with clinically and pathologically confirmed unresected pancreatic cancer who received palliative chemotherapy. Three-tesla MRI examinations containing DWI sequences with b values of 0, 100, 700, 1400, and 2100 s/mm2 were performed before and after chemotherapy. Parameters included the apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), and mean diffusional kurtosis (MK). The performances of the DWI and DKI parameters in distinguishing the response to chemotherapy were evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Overall survival (OS) was calculated from the date of first treatment to the date of death or the latest follow-up date.

RESULTS

The ADCchange and MDchange were significantly higher in the responding group (PR group) than in the nonresponding group (non-PR group) (ADCchange: 0.21 ± 0.05 vs. 0.11 ± 0.09, P = 0.02; MDchange: 0.37 ± 0.24 vs. 0.10 ± 0.12, P = 0.002). No statistical significance was shown when comparing ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost between the PR and non-PR groups. The ROC curve analysis indicated that MDchange (AUC = 0.898, cutoff value = 0.7143) performed better than ADCchange (AUC = 0.806, cutoff value = 0.1369) in predicting the response to chemotherapy.

CONCLUSION

The ADCchange and MDchange demonstrated strong potential for evaluating the response to chemotherapy in unresectable pancreatic cancer. The MDchange showed higher specificity in the classification of PR and non-PR than the ADCchange. Other parameters, including ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost, are not suitable for response evaluation. The combined model SUMchange demonstrated superior performance compared to the individual DWI and DKI models. Further experiments are needed to evaluate the potential of DWI and DKI parameters in predicting the prognosis of patients with unresectable pancreatic cancer.

DLGAP5 triggers proliferation and metastasis of bladder cancer by stabilizing E2F1 via USP11

Bladder cancer (BLCA) is one of the most widespread malignancies worldwide, and displays significant tumor heterogeneity. Understanding the molecular mechanisms exploitable for treating aggressive BLCA represents a crucial objective. Despite the involvement of DLGAP5 in tumors, its precise molecular role in BLCA remains unclear. BLCA tissues exhibit a substantial increase in DLGAP5 expression compared with normal bladder tissues. This heightened DLGAP5 expression positively correlated with the tumor's clinical stage and significantly affected prognosis negatively. Additionally, experiments conducted in vitro and in vivo revealed that alterations in DLGAP5 expression notably influence cell proliferation and migration. Mechanistically, the findings demonstrated that DLGAP5 was a direct binding partner of E2F1 and that DLGAP5 stabilized E2F1 by preventing the ubiquitination of E2F1 through USP11. Furthermore, as a pivotal transcription factor, E2F1 fosters the transcription of DLGAP5, establishing a positive feedback loop between DLGAP5 and E2F1 that accelerates BLCA development. In summary, this study identified DLGAP5 as an oncogene in BLCA. Our research unveils a novel oncogenic mechanism in BLCA and offers a potential target for both diagnosing and treating BLCA.

circ_0058063 promotes breast cancer progression by upregulating DLGAP5 via sponging miR-557

OBJECTIVE

Accumulating evidence indicates that circular RNAs (circRNAs) contribute to breast cancer (BC) development and progression. However, the role of circ_0058063 in BC and its underlying molecular processes remain unclear.

METHODS

The expression of circ_0058063, miR-557, and DLGAP5 in BC tissues and cells was determined using real time quantitative PCR or western blotting. The functions of circ_0058063 in BC cells were detected using CCK-8, Transwell, caspase-3 activity, and xenograft tumor assays. The specific binding of circ_0058063/miR-557 and DLGAP5/miR-557 was verified using RNA immunoprecipitation (RIP) and dual-luciferase reporter assays.

RESULTS

circ_0058063 expression was upregulated in BC tissues and cells. circ_0058063 knockdown inhibited proliferation and migration but promoted apoptosis in MCF-7 and MDA-MB-231 cells in vitro. In vivo studies further validated that the knockdown of circ_0058063 repressed tumor growth. Mechanistically, circ_0058063 directly sponged miR-557 and negatively regulated its expression. Additionally, miR-557 inhibition reversed the tumor-suppressive effects of the circ_0058063 knockdown on the survival of MDA-MB-231 and MCF-7 cells. Moreover, miR-557 directly targeted DLGAP5. DLGAP5 knockdown suppressed MCF-7 and MDA-MB-231 cell growth, and these effects were reversed by miR-557 downregulation.

CONCLUSION

Our findings verify that circ_0058063 acts as a sponge for miR-557 to upregulate DLGAP5 expression. These findings suggest that the circ_0058063/miR-557/DLGAP5 axis is an important regulator of oncogenic function and may be a promising therapeutic target for BC.

Anti-tumor target screening of sea cucumber saponin Frondoside A: a bioinformatics and molecular docking analysis

Cancer remains the leading cause of death worldwide. In spite of significant advances in targeted and immunotherapeutic approaches, clinical outcomes for cancer remain poor. The aim of the present study was to investigate the potential mechanisms and therapeutic targets of Frondoside A for the treatment of liver, pancreatic, and bladder cancers. The data presented in our study demonstrated that Frondoside A reduced the viability and migration of HepG2, Panc02, and UM-UC-3 cancer cell in vitro. Moreover, we utilized the GEO database to screen and identify for differentially expressed genes (DEGs) in liver, pancreatic, and bladder cancers, which resulted in the identification of 714, 357, and 101 DEGs, respectively. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation were performed using the Metascape database for DEGs that were significantly associated with cancer development. The protein-protein interaction (PPI) networks of the identified DEGs in liver, pancreatic, and bladder cancers were analyzed using Cytoscape 3.9.0 software, and subsequently identified potential key genes that were associated with these networks. Subsequently, their prognostic values were assessed by gene expression level analysis and Kaplan-Meier survival analysis (GEPIA). Furthermore, we utilized TIMER 2.0 to investigate the correlation between the expression of the identified key gene and cancer immune infiltration. Finally, molecular docking simulations were performed to assess the affinity of Frondoside A and key genes. Our results showed a significant correlation between these DEGs and cancer progression. Combined, these analyses revealed that Frondoside A involves in the regulation of multiple pathways, such as drug metabolism, cell cycle in liver cancer by inhibiting the expression of CDK1, TOP2A, CDC20, and KIF20A, and regulates protein digestion and absorption, receptor interaction in pancreatic cancer by down-regulation of ASPM, TOP2A, DLGAP5, TPX2, KIF23, MELK, LAMA3, and ANLN. While in bladder cancer, Frondoside A regulates muscle contraction, complement and coagulation cascade by increase FLNC expression. In conclusion, the present study offers valuable insights into the molecular mechanism underlying the anticancer effects of Frondoside A, and suggests that Frondoside A can be used as a functional food supplement or further developed as a natural anti-cancer drug.

DLGAP5 Regulates the Proliferation, Migration, Invasion, and Cell Cycle of Breast Cancer Cells via the JAK2/STAT3 Signaling Axis

The aim of this study was to discover new biomarkers to detect breast cancer (BC), which is an aggressive cancer with a high mortality rate. In this study, bioinformatic analyses (differential analysis, weighted gene co-expression network analysis, and machine learning) were performed to identify potential candidate genes for BC to study their molecular mechanisms. Furthermore, Quantitative Real-time PCR and immunohistochemistry assays were used to examine the protein and mRNA expression levels of a particular candidate gene (DLGAP5). And the effects of DLGAP5 on cell proliferation, migration, invasion, and cell cycle were further assessed using the Cell Counting Kit-8 assay, colony formation, Transwell, wound healing, and flow cytometry assays. Moreover, the changes in the JAK2/STAT3 signaling-pathway-related proteins were detected by Western Blot. A total of 44 overlapping genes were obtained by differential analysis and weighted gene co-expression network analysis, of which 25 genes were found in the most tightly connected cluster. Finally, NEK2, CKS2, UHRF1, DLGAP5, and FAM83D were considered as potential biomarkers of BC. Moreover, DLGAP5 was highly expressed in BC. The down-regulation of DLGAP5 may inhibit the proliferation, migration, invasion, and cell cycle of BC cells, and the opposite was true for DLGAP5 overexpression. Correspondingly, silencing or overexpression of the DLGAP5 gene inhibited or activated the JAK2/STAT3 signaling pathway, respectively. DLGAP5, as a potential biomarker of BC, may impact the cell proliferation, migration, invasion, cell cycle, and BC development by modulating the JAK2/STAT3 signaling pathway.

Precision oncology: Artificial intelligence, circulating cell-free DNA, and the minimally invasive detection of pancreatic cancer-A pilot study

BACKGROUND

Pancreatic cancer (PC) is among the most lethal cancers. The lack of effective tools for early detection results in late tumor detection and, consequently, high mortality rate. Precision oncology aims to develop targeted individual treatments based on advanced computational approaches of omics data. Biomarkers, such as global alteration of cytosine (CpG) methylation, can be pivotal for these objectives. In this study, we performed DNA methylation profiling of pancreatic cancer patients using circulating cell-free DNA (cfDNA) and artificial intelligence (AI) including Deep Learning (DL) for minimally invasive detection to elucidate the epigenetic pathogenesis of PC.

METHODS

The Illumina Infinium HD Assay was used for genome-wide DNA methylation profiling of cfDNA in treatment-naïve patients. Six AI algorithms were used to determine PC detection accuracy based on cytosine (CpG) methylation markers. Additional strategies for minimizing overfitting were employed. The molecular pathogenesis was interrogated using enrichment analysis.

RESULTS

In total, we identified 4556 significantly differentially methylated CpGs (q-value < 0.05; Bonferroni correction) in PC versus controls. Highly accurate PC detection was achieved with all 6 AI platforms (Area under the receiver operator characteristics curve [0.90-1.00]). For example, DL achieved AUC (95% CI): 1.00 (0.95-1.00), with a sensitivity and specificity of 100%. A separate modeling approach based on logistic regression-based yielded an AUC (95% CI) 1.0 (1.0-1.0) with a sensitivity and specificity of 100% for PC detection. The top four biological pathways that were epigenetically altered in PC and are known to be linked with cancer are discussed.

CONCLUSION

Using a minimally invasive approach, AI, and epigenetic analysis of circulating cfDNA, high predictive accuracy for PC was achieved. From a clinical perspective, our findings suggest that that early detection leading to improved overall survival may be achievable in the future.

Management of Metastatic Pancreatic Cancer-Comparison of Global Guidelines over the Last 5 Years

Pancreatic cancer (PC) is usually diagnosed at an advanced stage of its development, which results in lower overall survival (OS). Prognosis is also poor even with curative-intent surgery. Approximately 80% of patients with localized PDAC have micrometastases at the time of diagnosis, which leads to a worse prognosis than in other cancers. The objective of this study is to present the progress in the treatment of metastatic pancreatic cancer based on the recommendations of oncological scientific societies, such as ESMO, NCCN, ASCO, NICE and SEOM, over the last 5 years. Combined FOLFIRINOX therapy is mostly a recommended therapy among patients with good performance statuses, while gemcitabine is recommended for more fragile patients as a first-line treatment. The newest guidelines suggest that molecular profiling of the tumor should be the first step in determining the course of treatment. The use of modern molecular therapies in patients with specific gene mutations should extend the survival of patients with this disease.

Momordicine I suppresses glioma growth by promoting apoptosis and impairing mitochondrial oxidative phosphorylation

Glioblastoma (GBM) is the most common type of primary brain tumor. Patients with GBM have poor survival outcomes. Isolated components of Momordica charantia have anticancer effects. However, the bioactivity of M. charantia extracts against GBM remains unknown. We tested four major extracts of M. charantia and found that momordicine I reduced glioma cell viability without serious cytotoxic effects on astrocytes. Momordicine I suppressed glioma cell colony formation, proliferation, migration, and invasion. Momordicine I also induced apoptosis, intracellular reactive oxygen species (ROS) production, and senescence in glioma cells. Moreover, momordicine I decreased the oxidative phosphorylation capacity of glioma cells and inhibited tumor sphere formation in temozolomide (TMZ)-resistant GBM cells. We further explored whether the antiglioma effect of momordicine I may be related to cell cycle modulation and DLGPA5 expression. Our results indicate that the cytotoxic effect of momordicine I on glioma cells suggests its potential therapeutic application to GBM treatment. See also Figure 1(Fig. 1).

High Expression of DLGAP5 Indicates Poor Prognosis and Immunotherapy in Lung Adenocarcinoma and Promotes Proliferation through Regulation of the Cell Cycle

Background

Lung adenocarcinoma (LUAD) is one of the most common types of cancer in the respiratory system, with a high mortality and recurrence rate. The role of disc large-associated protein 5 (DLGAP5) in LUAD progression and tumor microenvironment (TME) remains unclear. This study is aimed at revealing the functional role of DLGAP5 in LUAD based on bioinformatics analysis and experimental validation.

Methods

Differential expression analysis, protein-protein interaction (PPI) network, and Cox regression analysis were applied to screen potential prognostic biomarkers. The mRNA and protein levels of DLGAP5 were analyzed using The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA) databases. The CCK-8 and colony formation assays were performed to assess the effect of DLGAP5 on cell proliferation. RNA sequencing (RNA-seq) and enrichment analyses were utilized to explore the biological functions of DLGAP5. Furthermore, flow cytometry was used to explore the role of DLGAP5 on the cell cycle. The ssGSEA algorithm in the R package "GSVA" was applied to quantify immune infiltrating cells, and the tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict the efficacy of immunotherapy. Moreover, analyses using the cBioPortal and MethSurv databases were performed to evaluate the mutation and methylation of DLGAP5, respectively. Finally, the prognostic value of DLGAP5 was estimated using the TCGA and the Gene Expression Omnibus (GEO) databases. The nomogram model was constructed using the TCGA-LUAD cohort and evaluated by adopting calibration curves, time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

Results

DLGAP5 mRNA and protein abundance were significantly elevated in LUAD, and knockdown of DLGAP5 remarkably suppressed lung cancer cell proliferation through induction of cell cycle G1 arrest. In addition, DLGAP5 expression was positively correlated with Th2 cells and negatively correlated with B cells, T follicular helper cells, and mast cells. LUAD patients with high DLGAP5 expression may be resistant to immunotherapy. Hypermethylation levels of the cg23678254 site of DLGAP5 or its enhanced expression were unfavorable for the survival of LUAD patients. Meanwhile, DLGAP5 expression was associated with TNM stages, tumor status, and therapy outcome. Notably, the prognostic model constructed based on DLGAP5 expression exhibited great predictive capability, which was promising for clinical applications.

Conclusion

DLGAP5 promotes lung cancer cell proliferation through regulation of the cell cycle and is associated with multiple immune infiltrating cells. Furthermore, DLGAP5 predicts poor prognosis and response to immunotherapy in lung adenocarcinoma.

Specific Blood RNA Profiles in Individuals with Acute Spinal Cord Injury as Compared with Trauma Controls

Background

Spinal cord injury (SCI) is known to cause a more robust systemic inflammatory response than general trauma without CNS injury, inducing severe secondary organ damage, especially the lung and liver. Related studies are principally focused on the mechanisms underlying repair and regeneration in the injured spinal cord tissue. However, the specific mechanism of secondary injury after acute SCI is widely overlooked, compared with general trauma.

Methods

Two datasets of GSE151371 and GSE45376 related to the blood samples and spinal cord after acute SCI were selected to identify the differentially expressed genes (DEGs). In GSE151371, functional enrichment analysis on specific DEGs of blood samples was performed. And the top 15 specific hub genes were identified from intersectional genes between the specific upregulated DEGs of blood samples in GSE151371 and the upregulated DEGs of the spinal cord in GSE45376. The specific functional enrichment analysis and the drug candidates of the hub genes and the miRNAs-targeted hub genes were also analyzed and predicted.

Results

DEGs were identified, and a total of 64 specific genes were the intersection of upregulated genes of the spinal cord in GSE45376 and upregulated genes of human blood samples in GSE151371. The top 15 hub genes including HP, LCN2, DLGAP5, CEP55, HMMR, CDKN3, PRTN3, SKA3, MPO, LTF, CDC25C, MMP9, NEIL3, NUSAP1, and CD163 were calculated from the 64 specific genes. Functional enrichment analysis of the top 15 hub genes revealed inflammation-related pathways. The predicted miRNAs-targeted hub genes and drug candidates of hub genes were also performed to put forward reasonable treatment strategies.

Conclusion

The specific hub genes of acute SCI as compared with trauma without CNS injury were identified. The functional enrichment analysis of hub genes showed a specific immune response. Several predicted drugs of hub genes were also obtained. The hub genes and the predicted miRNAs may be potential biomarkers and therapeutic targets and require further validation.

Bisphenol A interacts with DLGAP5 and regulates IL-6/JAK2/STAT3 signaling pathway to promote tumorigenesis and progression of osteosarcoma

OBJECTIVE

It has been suggested that Bisphenol A (BPA), a high-production-volume industrial chemical, can accelerate the development of various type of cancers. However, the effect of BPA on osteosarcoma and the underlying mechanisms are yet to be established. Therefore, in this study we tried to explore the carcinogenic effects of BPA on osteosarcoma and the underlying mechanism.

METHODS

SaOs-2 cancer cell line was used to treat with BPA at the doses of 0.1, 1, 10 μM DGLAP5 knockdown and overexpression methods were constructed by using adenovirus mediated transfection, and the functional analysis of DGLAP5 was investigated to evaluate the carcinogenic effect of BPA on osteosarcoma through DLGAP5. Xenograft and metastatic mouse model were used to evaluate in vivo experiments.

RESULTS

In this study, BPA at 10 μM promoted the proliferation, migration and invasion in vitro, and accelerate the progression and metastasis in vivo. Also, exposure to BPA was associated with poor survival of osteosarcoma in mice. In addition, we observed that BPA at 10 μM significantly increased the expression of DGLAP5 in osteosarcoma. Silencing DGLAP5 could reverse the effect of BPA on proliferation, migration and invasion. Mechanically, BPA promoted IL-6, JAK2, and STAT3 expression and promoted tumor progression in an IL-6-dependent manner through up-regulation of DLGAP5.

CONCLUSION

Our findings demonstrated that BPA could promote the proliferation, migration, invasion of osteosarcoma cells and related to poor survival in a mouse model. DLGAP5 is one of the most critical targets of BPA to act as a carcinogen through IL-6/JAK2/STAT3 signaling pathway.

DLGAP4 acts as an effective prognostic predictor for hepatocellular carcinoma and is closely related to tumour progression

Disc large associated protein 4 (DLGAP4) plays an important role in neurological diseases, but the role and mechanism of DLGAP4 in hepatocellular carcinoma (HCC) remain unclear. In this study, the prognostic effect of DLGAP4 on HCC patients was investigated by means of bioinformatics. The correlation of DLGAP4 expression with the prognosis of HCC patients was evaluated by TCGA data analysis, and the correlation between DLGAP4 expression and the clinical characteristics of HCC patients was evaluated by the Wilcoxon signed rank test and logistic regression analysis. Kaplan‒Meier and Cox regression methods were used to assess the effect of DLGAP4 expression level on overall survival, and nomograms were used to illustrate the correlation between DLGAP4 gene expression and HCC risk. The genes related to DLGAP4 in HCC were screened, and GO/KEGG enrichment analysis was performed. Furthermore, in vitro and in vivo experiments were conducted to detect the effect of DLGAP4 expression on the proliferation, migration and metastasis of HCC cells. We also examined the effect of DLGAP4 expression on enriched pathway proteins to explore the possible mechanism. The expression levels of DLGAP4 were significantly higher in HCC cell lines and tissue samples than in normal liver cell lines and tissues. The expression of DLGAP4 was significantly associated with clinical characteristics. Survival analysis showed that high expression of DLGAP4 was associated with a poor prognosis in HCC. Multivariate analysis showed that high expression of DLGAP4 was an independent risk factor affecting the overall survival rate in HCC patients. By means of ROC curve analysis and nomograms, we determined the value of DLGAP4 expression in the diagnosis and prognosis evaluation of HCC. GO/KEGG enrichment analysis showed that the PPAR signalling pathway was differentially enriched in patients with high expression of DLGAP4. According to in vitro and in vivo experiments, DLGAP4 knockdown inhibited the proliferation and metastasis of HCC cells and decreased the expression of PPARβ/δ protein. In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cell, and increased the expression of PPARβ/δ protein.In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cells and increased the expression of PPARβ/δ protein. The results show a close correlation between DLGAP4 expression and clinicopathological features of HCC, and DLGAP4 can be used as a prediction biomarker of HCC.

NEAT1/MALAT1/XIST/PKD--Hsa-Mir-101-3p--DLGAP5 Axis as a Novel Diagnostic and Prognostic Biomarker Associated With Immune Cell Infiltration in Bladder Cancer

Background: The clinical value of the biomarkers of bladder cancer (BC) is limited due to their low sensitivity or specificity. As a biomarker, DLG associated protein 5 (DLGAP5) is a potential cell cycle regulator in cancer cell carcinogenesis. However, its functional part in BC remains unclear. Therefore, this study aims to identify DLGAP5 expression in BC and its potential diagnostic and prognostic values. Eventually, it predicts the possible RNA regulatory pathways of BC.

Methods: Data on DLGAP5 expression levels in BC and normal bladder tissues were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The receiver operating characteristic (ROC), Kaplan–Meier survival curves, and the univariate and multivariate Cox regression analysis determined the diagnostic and prognostic values of DLGAP5 in BC patients. Finally, the StarBase predicted the target RNAs and constructed networks using Cytoscape.

Results: DLGAP5 expression was significantly upregulated in BC tissue, verified by the TCGA (p &lt; 0.001), GSE3167, GSE7476, and GSE65635 datasets (p &lt; 0.01). BC patients with increased DLGAP5 had poor overall survival (OS) (p = 0.01), disease specific survival (DSS) (p = 0.006) and progress free interval (DFI) (p = 0.007). The area under the ROC curve (AUC) was 0.913. The multivariate Cox analysis identified that lymphovascular invasion (p = 0.007) and DLGAP5 (p = 0.002) were independent prognostic factors.

Conclusion: Increased DLGAP5 expression was closely associated with a poor prognosis in BC patients. In this case, DLGAP5 might be a diagnostic and prognostic biomarker for BC. DLGAP5 expression might be regulated by NEAT1/MALAT1/XIST/PKD--Hsa-mir-101-3p pathways.

Whole Genome Transcriptomic Analysis of Ovary Granulosa Cells Revealed an Anti-Apoptosis Regulatory Gene DLGAP5 in Polycystic Ovary Syndrome

The mechanisms underlining pathogenesis of polycystic ovary syndrome (PCOS) remain largely unknown. Dysfunction of ovarian granulosa cells plays an important role. The present study performed the lncRNA and mRNA profiling by whole genome transcriptomic sequencing of ovary granulosa cells from women with PCOS and investigated the potential role of differentially expressed gens (DEGs) in the pathomechanism of PCOS. In total, 1,936 DEGs (30 upregulated and 1,906 downregulated mRNAs and lncRNAs) were identified in the ovary granulosa cells between control and PCOS group. Functional enrichment analysis showed that DEGs were mainly associated with cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and olfactory transduction. qRT-PCR validated the upregulation of DLGAP5 mRNA in ovary from PCOS group when compared to control group. Immunostaining and TUNEL assays showed that DLGAP5 protein level was increased while apoptosis was decreased in follicles of ovary in PCOS group. In vitro functional assays showed that DLGPA5 knockdown repressed viability and proliferation, but enhanced apoptosis and disrupted cell cycle in granulosa cells; while DLGAP5 overexpression had the opposite effects in granulosa cells. In conclusion, the study showed differentially expressed lncRNA and mRNA profile in the granulosa cells in ovaries of PCOS. Functional results demonstrated that DLGAP5 is a dysregulated candidate gene in the pathogenesis of PCOS, especially granulosa cell apoptosis and proliferation.

Pan-cancer analysis of the oncogenic role of discs large homolog associated protein 5 (DLGAP5) in human tumors

BACKGROUND

In recent years, there have been many studies on the relationship between DLGAP5 and different types of cancers, yet there is no pan-cancer analysis of DLGAP5. Therefore, this study aims to analyze the roles of DLGAP5 in human tumors.

METHODS

Firstly, we evaluated the expression level of DLGAP5 in 33 types of tumors throughout the datasets of TCGA (Cancer Genome Atlas) and GEO (Gene Expression Synthesis). Secondly, we used the GEPIA2 and Kaplan-Meier plotter to conduct Survival prognosis analysis. Additionally, cBioPortal web was utilized to analyze the genetic alteration of DLGAP5, after which we selected hepatocellular carcinoma (HCC) cell lines to define the function of DLGAP5. Last but not least, we performed immune infiltration analysis and DLGAP5-related gene enrichment analysis.

RESULTS

DLGAP5 is highly expressed in most type of cancers, and there is a significant correlation between the expression of DLGAP5 and the prognosis of cancer patients. We have observed that DLGAP5 promotes the proliferation and invasion of hepatocellular carcinoma (HCC) cell lines. We also found that DLGAP5 expression was related with the CD8⁺ T-cell infiltration status in kidney renal clear cell carcinoma, uveal melanoma, and thymoma, and cancer-associated fibroblast infiltration was observed in breast invasive carcinoma, kidney renal papillary cell carcinoma and testicular germ cell tumors. In addition, enrichment analysis revealed that cell cycle- and oocyte meiosis-associated functions were involved in the functional mechanism of DLGAP5.

CONCLUSIONS

Taken together, our unpresented pan-cancer analysis of DLGAP5 provides a relatively integrative understanding of the oncogenic role of DLGAP5 in various tumors. DLGAP5 may prompt HCC cellular proliferation, invasion and metastasis. All of these provides solid basement and will promote more advanced understanding the role of DLGAP5 in tumorigenesis and development from the perspective of clinical tumor samples and cells.

RETRACTED: Pancreatic cancer cells-derived exosomal long non-coding RNA CCAT1/microRNA-138-5p/HMGA1 axis promotes tumor angiogenesis

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor-in-Chief. Concern was raised about the reliability of the Western blot results in Figs. 2B and 5I+J, which appear to have the same eyebrow shaped phenotype as many other publications tabulated here (https://docs.google.com/spreadsheets/d/149EjFXVxpwkBXYJOnOHb6RhAqT4a2llhj9LM60MBffM/edit#gid=0). In addition, Fig. 4B appears to show a digital composition of xenografted tumors. The journal requested the corresponding author comment on these concerns and provide the raw data. However the authors were not able to satisfactorily fulfil this request and therefore the Editor-in-Chief decided to retract the article.

Role of long noncoding RNA taurine-upregulated gene 1 in cancers

Long non-coding RNAs (lncRNAs) are a group of non-protein coding RNAs with a length of more than 200 bp. The lncRNA taurine up-regulated gene 1 (TUG1) is abnormally expressed in many human malignant cancers, where it acts as a competitive endogenous RNA (ceRNA), regulating gene expression by specifically sponging its corresponding microRNAs. In the present review, we summarised the current understanding of the role of lncRNA TUG1 in cancer cell proliferation, metastasis, angiogenesis, chemotherapeutic drug resistance, radiosensitivity, cell regulation, and cell glycolysis, as well as highlighting its potential application as a clinical biomarker or therapeutic target for malignant cancer. This review provides the basis for new research directions for lncRNA TUG1 in cancer prevention, diagnosis, and treatment.

LINC00261: a burgeoning long noncoding RNA related to cancer

Long noncoding RNAs (lncRNAs), are transcripts longer than 200 nucleotides that are considered to be vital regulators of many cellular processes, particularly in tumorigenesis and cancer progression. long intergenic non-protein coding RNA 261 (LINC00261), a recently discovered lncRNA, is abnormally expressed in a variety of human malignancies, including pancreatic cancer, gastric cancer, colorectal cancer, lung cancer, hepatocellular carcinoma, breast cancer, laryngeal carcinoma, endometrial carcinoma, esophageal cancer, prostate cancer, choriocarcinoma, and cholangiocarcinoma. LINC00261 mainly functions as a tumor suppressor that regulates a variety of biological processes in the above-mentioned cancers, such as cell proliferation, apoptosis, motility, chemoresistance, and tumorigenesis. In addition, the up-regulation of LINC00261 is closely correlated with both favorable prognoses and many clinical characteristics. In the present review, we summarize recent research documenting the expression and biological mechanisms of LINC00261 in tumor development. These findings suggest that LINC00261, as a tumor suppressor, has bright prospects both as a biomarker and a therapeutic target.

Construction of a lncRNA/pseudogene-hsa-miR-30d-5p-GJA1 regulatory network related to metastasis of pancreatic cancer

Pancreatic cancer, the most lethal malignant tumor, is notorious for its poor prognosis and metastatic potential. Non-coding RNAs (ncRNAs) are reported to play key roles in cancer metastasis. In this study, miRNA and gene expression profiles between metastatic pancreatic cancer cell M8 and its parental cell BxPC.3 were determined. Using differential expression analysis, survival analysis, target gene prediction, pathway enrichment analysis, intersection analysis and correlation analysis, hsa-miR-30d-5p/GJA1 axis was identified as the most potential pathway involved in metastasis of pancreatic cancer. Subsequently, two upstream lncRNAs (HELLPAR and OIP-AS1) and four upstream pseudogenes (AC093616.1, AC009951.1, TMEM183B and PABPC1P4) of hsa-miR-30d-5p/GJA1 axis were predicted and were then identified via assessment of RNA-RNA expression relationship. Furthermore, CTNNA1, CTNNB1 and CTNND1 were regarded as three crucial molecules to be participated in hsa-miR-30d-5p/GJA1-mediated metastatic potential in pancreatic cancer. In conclusion, we established a novel lncRNA/pseudogene-hsa-miR-30d-5p-GJA1 regulatory network linked to metastasis of pancreatic cancer.