LncRNA LINC00857 strengthens the malignancy behaviors of pancreatic adenocarcinoma cells by serving as a competing endogenous RNA for miR-340-5p to upregulate TGFA expression

Construction of subtype classifiers and validation of a prognostic risk model based on hypoxia-associated lncRNAs for lung adenocarcinoma

BACKGROUND

Studies have shown that long non-coding RNAs (lncRNAs) are found to be hypoxia-regulated lncRNAs in cancer. Lung adenocarcinoma (LUAD) is the leading cause of cancer death worldwide, and despite early surgical removal, has a poor prognosis and a high recurrence rate. Thus, we aimed to identify subtype classifiers and construct a prognostic risk model using hypoxia-associated long noncoding RNAs (hypolncRNAs) for LUAD.

METHODS

Clinical data of LUAD samples with prognosis information obtained from the Gene Expression Omnibus (GEO), acted as validation dataset, and The Cancer Genome Atlas (TCGA) databases, served as training dataset, were used to screen hypolncRNAs in each dataset by univariate Cox regression analysis; the intersection set was used for subsequent analyses. Unsupervised clustering analysis was performed based on the expression of hypolncRNAs using the 'ConsensuClusterPlus' package. The tumor microenvironment (TME) was compared between LUAD subgroups by analyzing the expression of immune cell infiltration, immune components, stromal components, immune checkpoints, and chemokine secretion. To identify robust prognostically associated hypolncRNAs and construct a risk score model, multivariate Cox regression analysis was performed.

RESULTS

A total of 14 hypolncRNAs were identified. Based on the expression of these hypolncRNAs, patients with LUAD were classified into three hypolncRNA-regulated subtypes. The three subtypes differed significantly in immune cell infiltration, stromal score, specific immune checkpoints, and secretion of chemokines and their receptors. The Tumor Immune Dysfunction and Exclusion (TIDE) scores and myeloid-derived suppressor cell (MDSC) scores were also found to differ significantly among the three hypolncRNA-regulated subtypes. Four of the 14 hypolncRNAs were used to construct a signature to distinguish the overall survival (OS) in TCGA dataset (P<0.0001) and GEO dataset (P=0.0032) and sensitivity to targeted drugs in patients at different risks of LUAD.

CONCLUSIONS

We characterized three regulatory subtypes of hypolncRNAs with different TMEs. We developed a signature based on hypolncRNAs, contributing to the development of personalized therapy and representing a new potential therapeutic target for LUAD.

The role of microRNAs in the different phases of liver regeneration

INTRODUCTION

Since the first discovery of microRNAs (miRs) extensive evidence reveals their indispensable role in different patho-physiological processes. They are recognized as critical regulators of hepatic regeneration, as they modulate multiple complex signaling pathways affecting liver regeneration. MiR-related translational suppression and degradation of target mRNAs and proteins are not limited to one specific gene, but act on multiple targets.

AREAS COVERED

In this review, we are going to explore the role of miRs in the context of liver regeneration and discuss the regulatory effects attributed to specific miRs. Moreover, specific pathways crucial for liver regeneration will be discussed, with a particular emphasis on the involvement of miRs within the respective signaling cascades.

EXPERT OPINION

The considerable amount of studies exploring miR functions in a variety of diseases paved the way for the development of miR-directed therapeutics. Clinical implementation has already shown promising results, but additional research is warranted to assure safe and efficient delivery. Nevertheless, given the broad functional properties of miRs and their critical involvement during hepatic regeneration, they represent an attractive treatment target to promote liver recovery after hepatic resection.

nc-RNA-mediated high expression of CDK6 correlates with poor prognosis and immune infiltration in pancreatic cancer

BACKGROUND

Emerging evidence manifests that cyclin-dependent kinase 6 (CDK6) plays an essential part in the initiation and progression of several types of human cancer, and its descending expression is correlated with an adverse prognosis. However, the precise role of CDK6 in Pancreatic cancer (PC) remains obscure.

AIMS

To identify the potential ceRNA regulatory axis of CDK6 in PC and explore its relationship with immune cells and immune checkpoints.

MATERIALS & METHODS

Using The Cancer Genome Atlas TCGA and GTEx data analyze the expression and survival of CDK6 in patients in pan-cancer, and cellular experiments were performed to verify the effect of CDK6 on cell function. Using GEPIA and STARBASE databases to analyze prognosis, expression and survival, and identify non coding RNA (ncRNA) that mediates CDK6 overexpression. The TIMER 2.0 database was used for immune correlation analysis.

RESULTS

We revealed CDK6 might be an oncogene in PC, and the HOXA11-AS /NR2F1-AS1- miR-454-3p axis was identified as the possible upstream ncRNA-associated pathway of CDK6 in PC. In addition, CDK6 show significant association with three immune checkpoints (PD-L1, PD-L2, and HAVCR2), the infiltration level of immune cells, and immunity biomarkers.

DISCUSSION

We discussed some applications of CDK6 in breast cancer, melanoma, and hemorrhagic malignancies. The role of miR-15a-5p, HOXA11-AS and NR2F1-AS1 in tumor development was also discussed based on existing studies. The potential mechanism of CDK6 affecting immune cells in pancreatic cancer was discussed.

CONCLUSIONS

Overall, these results established that nc-RNA-mediated high expression of CDK6 is associated with patient outcomes and immune invasion in pancreatic cancer.

DSCR9/miR-21-5p axis inhibits pancreatic cancer proliferation and resistance to gemcitabine via BTG2 signaling

The outcome of pancreatic adenocarcinoma (PAAD) patients is poor, given resistance to gemcitabine. Long noncoding RNA (lncRNA) has been implicated in the carcinogenesis of pancreatic cancer; however, its function and mechanism in PAAD resistance to gemcitabine (GEM) are yet unknown. Herein, we demonstrate that lncRNA DSCR9 is significantly reduced in PAAD in vitro and in vivo. CCK-8, BrdU and flow cytometry assays show that overexpression of DSCR9 markedly suppresses pancreatic cancer cell proliferation and invasion, and promotes apoptosis under gemcitabine treatment. BTG2 acts as a tumor suppressor by reducing the proliferation and invasion of pancreatic cancer cells and increasing gemcitabine-induced apoptosis. Immunofluorescence (IF) staining combined with fluorescence in situ hybridization (FISH) of pancreatic cancer tissues shows that DSCR9 and BTG2 are both increased in pancreatic cancer tissues. Luciferase assay shows that miR-21-5p simultaneously binds to DSCR9 and 3'UTR of BTG2; DSCR9 relieves miR-21-5p-induced inhibition of BTG2 by competing with BTG2 for miR-21-5p binding. Overexpression of miR-21-5p enhances the invasiveness of pancreatic cancer cells by promoting cancer cell proliferation and invasion and attenuating gemcitabine-induced apoptosis. Overexpression of miR-21-5p attenuates the effect of DSCR9 overexpression on BTG2 expression and invasiveness of pancreatic cancer cells. Finally, miR-21-5p expression is increased, while BTG2 expression is decreased in pancreatic cancer tissues. miR-21-5p is negatively correlated with DSCR9 and BTG2. In conclusion, the DSCR9/miR-21-5p/BTG2 axis modulates pancreatic cancer proliferation, invasion, and gemcitabine resistance.

Cuprotosis Programmed-Cell-Death-Related lncRNA Signature Predicts Prognosis and Immune Landscape in PAAD Patients

In terms of mortality and survival, pancreatic cancer is one of the worst malignancies. Known as a unique type of programmed cell death, cuprotosis contributes to tumor cell growth, angiogenesis, and metastasis. Cuprotosis programmed-cell-death-related lncRNAs (CRLs) have been linked to PAAD, although their functions in the tumor microenvironment and prognosis are not well understood. This study included data from the TCGA-PAAD cohort. Random sampling of PAAD data was conducted, splitting the data into two groups for use as a training set and test set (7:3). We searched for differentially expressed genes that were substantially linked to prognosis using univariate Cox and Lasso regression analysis. Through the use of multivariate Cox proportional risk regression, a risk-rating system for prognosis was developed. Correlations between the CRL signature and clinicopathological characteristics, tumor microenvironment, immunotherapy response, and chemotherapy sensitivity were further evaluated. Lastly, qRT-PCR was used to compare CRL expression in healthy tissues to that in tumors. Some CRLs are thought to have strong correlations with PAAD outcomes. These CRLs include AC005332.6, LINC02041, LINC00857, and AL117382.1. The CRL-based signature construction exhibited outstanding predictive performance and offers a fresh approach to evaluating pre-immune effectiveness, paving the way for future studies in precision immuno-oncology.

Identification of a prognostic classifier based on EMT-related lncRNAs and the function of LINC01138 in tumor progression for lung adenocarcinoma

Purpose: This study aimed to develop a prognostic indicator based on epithelial-mesenchymal transition (EMT)-related long noncoding RNAs (lncRNAs) and explore the function of EMT-related lncRNAs in malignant progression in lung adenocarcinoma (LUAD).

Materials and methods: A LUAD dataset was acquired from The Cancer Genome Atlas (TCGA) to identify prognostic EMT-related lncRNAs via differential expression analysis and univariate Cox regression analysis. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was utilized for variable selection and model construction. The EMT-related prognostic index (ERPI) was calculated according to the model and served as a classifier to divide LUAD individuals into high-ERPI and low-ERPI groups. A nomogram incorporating ERPI and clinicopathological variables was constructed. TCGA-LUAD, GSE50081, and GSE31210 were used to test the predictive capacity of the ERPI and nomogram. The characteristics of the tumor microenvironment (TME) were evaluated via the ESTIMATE, TIMER, and ssGSEA algorithms. Gene set variation analysis (GSVA) and ssGSEA were used to annotate the functions of the high-ERPI and low-ERPI groups. CCK8, transwell assay, wound-healing assay, and clone formation assay were conducted to clarify the biological functions of prognostic EMT-related lncRNAs.

Results: Ninety-seven differentially expressed EMT-related lncRNAs were identified, 15 of which were related to overall survival (OS). A prognostic signature was constructed based on 14 prognostic EMT-related lncRNAs to calculate the ERPI of each patient, and the predictive ability of ERPI was verified in TCGA, GSE50081, and GSE31210. The low-ERPI group survived longer and had a lower percentage of patients in advanced stage than the high-ERPI group. The nomogram had the highest predictive accuracy, followed by ERPI and stage. Patients with low ERPI had higher infiltration degree of immune cells and stronger immune responses than those with high ERPI. A series of in vitro experiments demonstrated that knockdown of LINC01138 dampened variability, proliferation, and motility of A549 and H460 cells.

Conclusion: Our study developed a prognostic classifier with robust prognostic performance and clarified the biological functions of LINC01138 in LUAD, aiding in making individual treatments for patients with LUAD and dissecting the mechanism of oncogenesis.

The Emerging Role of RNA N6-Methyladenosine Modification in Pancreatic Cancer

Pancreatic cancer (PC) is one of the most common malignant cancers, ranking the seventh highest causes of cancer-related deaths globally. Recently, RNA N6-methyladenosine (m6A) is emerging as one of the most abundant RNA modifications in eukaryote cells, involved in multiple RNA processes including RNA translocation, alternative splicing, maturation, stability, and degradation. As reported, m6A was dynamically and reversibly regulated by its “writers”, “erasers”, and “readers”, Increasing evidence has revealed the vital role of m6A modification in the development of multiple types of cancers including PC. Currently, aberrant m6A modification level has been found in both PC tissues and cell lines. Moreover, abnormal expressions of m6A regulators and m6A-modified genes have been reported to contribute to the malignant development of PC. Here in this review, we will focus on the function and molecular mechanism of m6A-modulated RNAs including coding RNAs as well as non-coding RNAs. Then the m6A regulators will be summarized to reveal their potential applications in the clinical diagnosis, prognosis, and therapeutics of PC.

Identification and Validation of Apparent Imbalanced Epi-lncRNAs Prognostic Model Based on Multi-Omics Data in Pancreatic Cancer

Background: Globally, pancreatic adenocarcinoma is a recognized cause of pancreatic death (PAAD) associated with high mortality. Long non-coding RNAs (lncRNAs) play an important role in several biological processes in pancreatic cancer.

Methods: The gene expression profile of PAAD patients were obtained from The Cancer Genome Atlas (TCGA) database. The limma package was used to identify epigenetic disorders of lncRNAs and PCG. Subsequently, the genomic characteristics and landscape of lncRNAs were explored. The pancreatic cancer-related lncRNAs gene set from Lnc2Cancer v3.0 were collected and the difference between cancer samples and normal samples were analysed. A prognostic model consisting of five epigenetic lncRNA (epi-lncRNAs) was established by univariate and multivariate Cox proportional hazards regression analyses and was verified across different data sets. Finally, the expression of core epi-lncRNAs was identified by PCR experiment.

Results: A total of 2237 epi-lncRNAs, 11855 non-epi-lncRNAs, 13518 epi-PCGs, and 6097 non-epi-PCGs, were identified. The abnormal frequency of lncRNAs in pancreatic cancer was much lower than that in PCG, and 138 epi-lncRNAs were enriched in human cancer-related lncRNAs. Epi-lncRNAs had a higher number with longer lengths and a greater number of transcripts. Epi-lncRNAs associated with epigenetic disorders had a higher number of exons, gene length, and isomers as compared to non-epi-lncRNAs. Further, the five pancreatic cancer-specific epi-lncRNA genes (AL161431.1, LINC00663, LINC00941, SNHG10, and TM4SF1-AS1) were identified. Based on these five pancreatic cancer-specific epis-lncRNAs, a prognostic model for pancreatic cancer was established. The RT-PCR result confirmed that AL161431.1, LINC00663, LINC00941, and SNHG10 expressions in pancreatic cancer samples were higher as compared to normal pancreatic samples; the expression of TM4SF1-AS1 in pancreatic cancer cells was significantly lower than that in normal pancreatic samples.

Conclusions: Epigenetic abnormalities could promote abnormal lncRNA expression in pancreatic cancer and may play an important role in its progression.

LINC00857 promotes the proliferation of pancreatic cancer via MET, STAT3, and CREB

BACKGROUND

Long non-coding RNA (lncRNA) LINC00857 promotes cell proliferation in various cancers and is overexpressed in pancreatic cancer (PC). However, the role of LINC00857 in PC is yet to be clarified.

METHODS

In this study, we used Gene Expression Profiling Interactive Analysis (GEPIA) to investigate transcriptional data of LINC00857 in different cancers. We determined LINC00857 expression in 4 PC cell lines, and one normal pancreatic cell line by quantitative real-time reverse transcription PCR (qRT-PCR). small interfering RNA (siRNA) was employed to specifically knockdown LINC00857 in BxPc3 and PANC1 cells. Cell proliferation was evaluated using WST-1. Western blotting analysis was used to detect the expression levels of downstream proteins of LINC00857.

RESULTS

We revealed that the knockdown of LINC00857 in PC cell lines inhibited the proliferation of the PC cells. We found that LINC00857 downregulation was followed by the downregulation of oncogenic proteins mesenchymal-epithelial transition (MET), signal transducer and activator of transcription 3 (STAT3), and cAMP response element-binding protein (CREB).

CONCLUSIONS

Our study indicated that LINC00857 regulated the expression of STAT3 and CREB via regulating the expression of MET, and consequently promoted the growth of PC cells. The results allowed us to deepen our understanding of the pathogenesis of PC and provided a potential target for the clinical treatment of PC.