LINC01094 promotes pancreatic cancer progression by sponging miR-577 to regulate LIN28B expression and the PI3K/AKT pathway

RNA-binding MSI proteins and their related cancers: A medicinal chemistry perspective

Musashi1 and Musashi2 are RNA-binding proteins originally found in drosophila, in which they play a crucial developmental role. These proteins are pivotal in the maintenance and differentiation of stem cells in other organisms. Research has confirmed that the Musashi proteins are highly involved in cell signal-transduction pathways such as Notch and TGF-β. These signaling pathways are related to the induction and development of cancers, such as breast cancer, leukemia, hepatoma and liver cancer. In this review we focus on how Musashi proteins interact with molecules in different signaling pathways in various cancers and how they affect the physiological functions of these pathways. We further illustrate the status quo of Musashi proteins-targeted therapies and predict the target RNA regions that Musashi proteins interact with, in the hope of exploring the prospect of the design of Musashi protein-targeted medicines.

MicroRNA 211-5p inhibits cancer cell proliferation and migration in pancreatic cancer by targeting BMP2

MicroRNAs (miRNAs) are essential to the tumour growth and metastasis of several cancers. However, the implied functions of miR-211-5p in pancreatic cancer (PC) remains poorly known. In the present study, we discovered that miR-211-5p was a significantly downregulated miRNA in PC tissues compared to adjacent non-tumour tissues. Moreover, we revealed that miR-211-5p overexpression suppressed the proliferation and metastasis of PC cells. Mechanistically, miR-211-5p directly bond to 3'UTR of bone morphogenetic protein-2 (BMP2) and negatively regulated its expression. Rescue experiments showed that the biological function of miR-211-5p was reversed by BMP-2 overexpression in PC cells. Clinical data indicated that BMP2 expression was negatively correlated with miR-211-5p levels in PC patients. Our study provided evidence that miR-211-5p served as a significant suppressor in PC, provided potential targets for prognosis and treatment of patients with PC.

Identification of a pyroptosis-related long non-coding RNA Signature for prognosis and its related ceRNA regulatory network of ovarian cancer

Aim: To identify the pyroptosis-related long non-coding RNAs (lncRNAs) in ovarian cancer and construct a prognostic signature based on them. Methods: Expression data from TCGA was used to explore differentially expressed pyroptosis-related lncRNAs in ovarian cancer. A risk signature was established by LASSO and cox regression analysis and then validated. Databases such as ESTIMATE, CIBERSORT, TIMER, XCELL were used to identify the relation between this signature and the immune microenvironment of ovarian cancer. Gene Set Enrichment Analysis was introduced to identify the pathways and functions that the signature may participate in. Based on miRcode and starBase databases, microRNAs related to the lncRNAs in our signature and the positively co-expressed pyroptosis- related genes were screened and a competing endogenous RNA (ceRNA) network was then constructed. Quantitative reverse transcription PCR was conducted to validate the expression levels of two lncRNAs in this ceRNA network. Results: A 13 pyroptosis-related lncRNA prognostic signature (MYCNOS, AL161772.1, USP30-AS1, ZNF32-AS2, AC068733.3, AC012236.1, AC015802.5, KIAA1671-AS1, AC013403.2, MIR223HG, KRT7-AS, PTPRD-AS1 and LINC01094) was constructed. Patients in high-risk group had a significantly worse prognosis than that of low-risk (P<0.0001). Immune infiltration analysis found that patients identified as high-risk had a higher infiltration of macrophages and tumor-associated fibroblasts. Further pathway analysis revealed that the signature may be involved in epithelial mesenchymal transition, extracellular matrix receptor interaction, and focal adhesion. Finally, a competitive endogenous inhibition relationship was discovered between LINC01094, KRT7-AS, MYCNOS, ZNF32-AS2, AC012236.1 and pyroptosis- related genes such as IRF1, NOD1, GSDMC, NLRP1, PLCG1, GSDME and GZMB, in which LINC01094 and KRT7-AS were found to be overexpressed in three ovarian cancer cell lines. Conclusion: We constructed a pyroptosis-related lncRNA signature and correlate it to the immune microenvironment. A ceRNA regulatory network related to pyroptosis was also constructed, which provides novel insights useful for the study of pyroptosis in ovarian cancer.

PI3K/Akt signaling in urological cancers: Tumorigenesis function, therapeutic potential, and therapy response regulation

In addition to environmental conditions, lifestyle factors, and chemical exposure, aberrant gene expression and mutations involve in the beginning and development of urological tumors. Even in Western nations, urological malignancies are among the top causes of patient death, and their prevalence appears to be gender dependent. The prognosis for individuals with urological malignancies remains dismal and unfavorable due to the ineffectiveness of conventional treatment methods. PI3K/Akt is a popular biochemical mechanism that is activated in tumor cells as a result of PTEN loss. PI3K/Akt escalates growth and metastasis. Moreover, due to the increase in tumor cell viability caused by PI3K/Akt activation, cancer cells may acquire resistance to treatment. This review article examines the function of PI3K/Akt in major urological tumors including bladder, prostate, and renal tumors. In prostate, bladder, and kidney tumors, the level of PI3K and Akt are notably elevated. In addition, the activation of PI3K/Akt enhances the levels of Bcl-2 and XIAP, hence increasing the tumor cell survival rate. PI3K/Akt ] upregulates EMT pathways and matrix metalloproteinase expression to increase urological cancer metastasis. Furthermore, stimulation of PI3K/Akt results in drug- and radio-resistant cancers, but its suppression by anti-tumor drugs impedes the tumorigenesis.

Construction of a novel signature based on immune-related lncRNA to identify high and low risk pancreatic adenocarcinoma patients

BACKGROUND

Pancreatic adenocarcinoma is one of the most lethal tumors in the world with a poor prognosis. Thus, an accurate prediction model, which identify patients within high risk of pancreatic adenocarcinoma is needed to adjust the treatment and elevate the prognosis of these patients.

METHODS

We obtained RNAseq data of The Cancer Genome Atlas (TCGA) pancreatic adenocarcinoma (PAAD) from UCSC Xena database, identified immune-related lncRNAs (irlncRNAs) by correlation analysis, and identified differential expressed irlncRNAs (DEirlncRNAs) between pancreatic adenocarcinoma tissues from TCGA and normal pancreatic tissues from TCGA and Genotype-Tissue Expression (GTEx). Further univariate and lasso regression analysis were performed to construct prognostic signature model. Then, we calculated the areas under curve and identified the best cut-off value to identify high- and low-risk patients with pancreatic adenocarcinoma. The clinical characteristics, immune cell infiltration, immunosuppressive microenvironment, and chemoresistance were compared between high- and low-risk patients with pancreatic adenocarcinoma.

RESULTS

We identified 20 DEirlncRNA pairs and grouped the patients by the best cut-off value. We proved that our prognostic signature model possesses a remarkable efficiency to predict prognosis of PAAD patients. The AUC for ROC curve was 0.905 for 1-year prediction, 0.942 for 2-year prediction, and 0.966 for 3-year prediction. Patients in high-risk group have poor survival rate and worse clinical characteristics. We also proved that patients in high-risk groups were in immunosuppressive status and may be resistant to immunotherapy. Anti-cancer drug evaluation was performed based on in-silico predated tool, such as paclitaxel, sorafenib, and erlotinib, may be suitable for PAAD patients in high-risk group.

CONCLUSIONS

Overall, our study constructed a novel prognostic risk model based on pairing irlncRNAs, exhibited a promising prediction value in patients with pancreatic adenocarcinoma. Our prognostic risk model may help distinguish PAAD patients suitable for medical treatments.

The role of pyroptosis-related lncRNA risk signature in ovarian cancer prognosis and immune system

Ovarian cancer is a leading cause of death in females with gynecologic cancers. Pyroptosis is a relatively new discovered programmed cell death that is believed to be associated with inflammation. However, studies on pyroptosis-related lncRNAs in ovarian cancer are limited. In this study, we identified 29 pyroptosis-related genes and screened out 72 pyroptosis-related lncRNAs. Furthermore, the 72 lncRNAs were eliminated to 2 survival-related lncRNAs using Cox regression and Lasso regression to build an ovarian cancer prognostic prediction signature and were further validated on the test set. We adopted a riskscore from the two-gene signature, and the survival in low-risk group was higher than the high-risk group. Functional enrichment analysis indicated that the differentially expressed genes (DEGs) between two risk groups were associated with tumor immunity. This study implies that pyroptosis-related genes are closely related to tumor immunity and could be potential therapeutic factors for ovarian cancer treatment.

Role of long non-coding RNAs in pancreatic cancer pathogenesis and treatment resistance- A review

Pancreatic cancer (PC) is one of the deadliest cancers associated with poor prognosis. The lack of reliable means of early cancer detection contributes to this disease's dismal prognosis. Long non-coding RNAs (LncRNAs) are protein-free RNAs produced by genome transcription; they play critical roles in gene expression regulation, epigenetic modification, cell proliferation, differentiation, and reproduction. Recent research has shown that lncRNAs play important regulatory roles in PC behaviors, in addition to their recently found functions. Several in-depth investigations have shown that lncRNAs are strongly linked to PC development and progression. Here, we discuss how lncRNAs, which are often overlooked, play many roles as regulators in the molecular mechanism underlying PC. This review also discusses the involved LncRNAs in PC pathogenesis and treatment resistance.

Regulatory Role of Fatty Acid Metabolism-Related Long Noncoding RNA in Prostate Cancer: A Computational Biology Study Analysis

In elderly men, prostate cancer is a leading cause of death. Tumor cells require more energy to progress than normal cells, and this energy is mainly dependent on the large amount of ATP support generated by lipid metabolism. Therefore, in this study, we focused on long noncoding RNAs related to lipid metabolism in prostate cancer to discover the biological mechanisms of lipid metabolism regulation. The TCGA-PRAD cohort was used in this study for computational biology analysis. In lipid metabolism biological pathways, 1959 long noncoding RNAs were identified by Pearson correlation coefficient analysis of protein-coding genes, then univariate regression with P values fewer than 0.05. We further identified 784 lncRNAs that were lipid metabolism-related lncRNAs considered to have prognostic value for disease-free survival. Subsequently, we constructed two lncRNA expression patterns of lipid metabolism based on these lncRNAs by nonnegative matrix dimensionality reduction. These two expression patterns showed significant differences in disease-free survival curves for those diagnosed with prostate cancer. We found significant differences in mRNA surveillance pathway and mRNA processing between C1 and C2 groups based on the WGCNA method to explore the biological characteristics of these two expression patterns. Finally, we constructed a disease-free survival (PFS) model based on these lncRNAs. The results identified lncRNAs involved in lipid metabolism and revealed differences in their expression patterns. Additionally, the results offer candidate ideas and approaches concerning the precision treatment of prostate cancer by studying lipid metabolism by candidate long noncoding RNAs.

An immune infiltration-related long non-coding RNAs signature predicts prognosis for hepatocellular carcinoma

Background: With a high incidence and dismal survival rate, hepatocellular carcinoma (HCC) tops the list of the world's most frequent malignant tumors. Immunotherapy is a new approach to cancer treatment, and its effect on prolonging overall survival (OS) varies from patient to patient. For a more effective prognosis and treatment of HCC, we are committed to identifying immune infiltration-related long non-coding RNAs (IIRLs) with prognostic value in hepatocellular carcinoma. Methods: In our study, we calculated immune scores of 369 hepatocellular carcinoma samples from the Cancer Genome Atlas (TCGA) database by using an estimation algorithm, and obtained long non-coding RNAs (lncRNAs) associated with immune infiltration by using Weighted Gene Co-expression Network analysis (WGCNA). For training cohort, univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis were used to determine prognostic IIRLs, we established a prognostic IIRLs signature. By testing cohort and entire cohort, we confirmed that the signature is practical. The prognosis of people with different clinicopathological stages and risk scores were predicted by the nomogram we constructed. In addition, Immune cell infiltration analysis and prediction of therapeutic drugs were performed. Results: 93 IIRLs were obtained by WGCNA. Furthermore, the prognostic value of these IIRLs were evaluated by using univariate Cox, Lasso and multivariate Cox analysis. Four IIRLs were used to create a signature with a prognosis. Time-related receiver operating characteristic (ROC) curve revealed that this model had an acceptable prognostic value for HCC patients. By using univariate and multivariate Cox regression analysis, this risk score has been shown to be an independent prognostic factor for HCC. The nomogram we made showed good predictions. Except for that, the treatment with immune checkpoint inhibitors (ICI) was likely to be more effective for low-risk patients. Conclusion: Based on four IIRLs, a prognostic signature was created in this research showed good accuracy in predicting OS. This study also provided valuable references for Immunotherapy of hepatocellular carcinoma.

The mechanism of lncRNAs in the crosstalk between epithelial-mesenchymal transition and tumor microenvironment for early colon adenocarcinoma based on molecular subtyping

A large number of colon adenocarcinoma (COAD) patients are already advanced when diagnosed. In this study, we aimed to further understand the mechanism of tumor development in early COAD by focusing on epithelial-mesenchymal transition (EMT) and long non-coding RNAs (lncRNAs). Expression profiles of early COAD patients were obtained from public databases. EMT-related lncRNAs were used as a basis for constructing molecular subtypes through unsupervised consensus clustering. Genomic features, pathways and tumor microenvironment (TME) were compared between two subtypes. LncATLAS database was applied to analyze the relation between lncRNAs and transcription factors (TFs). First order partial correlation analysis was conducted to identify key EMT-related lncRNAs.C1 and C2 subtypes with distinct prognosis were constructed. Oncogenic pathways such as EMT, KRAS signaling, JAK-STAT signaling, and TGF-β signaling were significantly enriched in C2 subtype. Higher immune infiltration and expression of immune checkpoints were also observed in C2 subtype, suggesting the key EMT-related lncRNAs may play a critical role in the modulation of TME. In addition, JAK-STAT signaling pathway was obviously enriched in upregulated TFs in C2 subtype, which indicated a link between key lncRNAs and JAK-STAT signaling that may regulate TME. The study further expanded the research on the role of EMT-related lncRNAs in the early COAD. The six identified EMT-related lncRNAs could serve as biomarkers for early screening COAD.

MicroRNAs and long non-coding RNAs in pancreatic cancer: From epigenetics to potential clinical applications

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are two relevant classes of non-coding RNAs (ncRNAs) that play a pivotal role in a number of molecular processes through different epigenetic regulatory mechanisms of gene expression. As a matter of fact, the altered expression of these types of RNAs leads to the development and progression of a varied range of multifactorial human diseases. Several recent reports elucidated that miRNA and lncRNAs have been implicated in pancreatic cancer (PC). For instance, dysregulation of such ncRNAs has been found to be associated with chemoresistance, apoptosis, autophagy, cell differentiation, tumor suppression, tumor growth, cancer cell proliferation, migration, and invasion in PC. Moreover, several aberrantly expressed miRNAs and lncRNAs have the potential to be used as biomarkers for accurate PC diagnosis. Additionally, miRNAs and lncRNAs are considered as promising clinical targets for PC. Therefore, in this review, we discuss recent experimental evidence regarding the clinical implications of miRNAs and lncRNAs in the pathophysiology of PC, their future potential, as well as the challenges that have arisen in this field of study in order to drive forward the design of ncRNA-based diagnostics and therapeutics for PC.

Lin-28 Homolog B-Activated Protein Disulfide Isomerase A4 Regulates Cell Proliferation, Migration and Invasion of Glioma

The goal of this study is to elucidate the role of protein disulfide isomerase A4 (PDIA4) in glioma, as well as its regulatory mechanism. Cell transfection was performed to adjust the expression level of PDIA4 and RNA-binding protein lin-28 homolog B (LIN28B). The expression of PDIA4 in human astrocytes and glioma cell lines was determined by quantitative real-time PCR and western blot. CCK-8, colony formation, Transwell and wound-healing assays were applied to determine the capabilities of cells to proliferate, invade and migrate. The connection between PDIA4 and LIN28B was demonstrated by RNA immunoprecipitation (RIP) and RNA pull down assays. As a result, PDIA4 was elevated in glioma. PDIA4 depletion hugely suppressed cell proliferative ability, which was characterized by the reduced cell viability and colony formation, and declined contents of PCNA and Ki67. Meanwhile, PDIA4 knockdown repressed the cell capabilities to migrate and invade, accompanied with downregulated MMP2 and MMP9. LIN28N was also found to be upregulated in glioma cells, and was verified to bind with PDIA4 and positively regulate PDIA4 expression. Additionally, LIN28B overexpression partly hindered the suppressive impacts of PDIA4 knockdown on cell abilities to proliferate, migrate and invade. In conclusion, this study delineates that LIN28B-mediated PDIA4 plays a critical role in the progression of glioma.

Screening and validation of platelet activation-related lncRNAs as potential biomarkers for prognosis and immunotherapy in gastric cancer patients

Background: Platelets (PLT) have a significant effect in promoting cancer progression and hematogenous metastasis. However, the effect of platelet activation-related lncRNAs (PLT-related lncRNAs) in gastric cancer (GC) is still poorly understood. In this study, we screened and validated PLT-related lncRNAs as potential biomarkers for prognosis and immunotherapy in GC patients.

Methods: We obtained relevant datasets from the Cancer Genome Atlas (TCGA) and Gene Ontology (GO) Resource Database. Pearson correlation analysis was used to identify PLT-related lncRNAs. By using the univariate, least absolute shrinkage and selection operator (LASSO) Cox regression analyses, we constructed the PLT-related lncRNAs model. Kaplan-Meier survival analysis, univariate, multivariate Cox regression analysis, and nomogram were used to verify the model. The Gene Set Enrichment Analysis (GSEA), drug screening, tumor immune microenvironment analysis, epithelial-mesenchymal transition (EMT), and DNA methylation regulators correlation analysis were performed in the high- and low-risk groups. Patients were regrouped based on the risk model, and candidate compounds and immunotherapeutic responses aimed at GC subgroups were also identified. The expression of seven PLT-related lncRNAs was validated in clinical medical samples using quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

Results: In this study, a risk prediction model was established using seven PLT-related lncRNAs -(AL355574.1, LINC01697, AC002401.4, AC129507.1, AL513123.1, LINC01094, and AL356417.2), whose expression were validated in GC patients. Kaplan-Meier survival analysis, the receiver operating characteristic (ROC) curve analysis, univariate, multivariate Cox regression analysis verified the accuracy of the model. We screened multiple targeted drugs for the high-risk patients. Patients in the high-risk group had a poorer prognosis since low infiltration of immune killer cells, activation of immunosuppressive pathways, and poor response to immunotherapy. In addition, we revealed a close relationship between risk scores and EMT and DNA methylation regulators. The nomogram based on risk score suggested a good ability to predict prognosis and high clinical benefits.

Conclusion: Our findings provide new insights into how PLT-related lncRNAs biomarkers affect prognosis and immunotherapy. Also, these lncRNAs may become potential biomarkers and therapeutic targets for GC patients.

Identification of a Hypoxia-Angiogenesis lncRNA Signature Participating in Immunosuppression in Gastric Cancer

Hypoxia and angiogenesis are the leading causes of tumor progression, and their strong correlation has been discovered in many cancers. However, their collective function’s prognostic and biological roles were not reported in gastric cancer. Hence, we aimed to investigate the effects of hypoxia and angiogenesis on gastric cancer via sequencing data. This study used weighted gene coexpression network analysis and random forest regression to build a hypoxia-angiogenesis-related model (HARM) via the TCGA-STAD lncRNA data. It estimated the HARM’s correlation with clinical features and its accuracy for survival prediction. Sequential functional analyses were conducted to investigate its biological role, and we next sought the immune landscape status and immunological function variation by ESTIMATE score calculation and GSVA, respectively. Seven different algorithms were conducted to assess the immunocyte infiltration, and TIDE score and immune checkpoint levels were compared between the high- and low-HARM groups. As a result, we found that HARM predicted patient survival with high accuracy and was correlated with higher stages of gastric cancer. Various cancer-associated pathways and macrophage-related regulations were upregulated in the high-HRAM group. The high-HARM group harbored higher immune levels, and M2 macrophages and cancer-associated fibroblasts were particularly highly unfiltered. Furthermore, globally upregulated immune checkpoints and higher TIDE scores were observed in the high-HARM group. Finally, we filtered eight drugs with lower IC50 in the high-HARM group as potential drugs for the HARM-targeted therapy. We believe this study opens up novel perspectives into the interaction between hypoxia-angiogenesis and immunosuppression and will provide novel insights for gastric cancer immunotherapy.

Targeting AVIL, a New Cytoskeleton Regulator in Glioblastoma

Glioblastoma (GBM) is the most common adult neural malignancy and the deadliest. The standard of care is optimal, safe, cytoreductive surgery followed by combined radiation therapy and alkylating chemotherapy with temozolomide. Recurrence is common and therapeutic options in the recurrent setting are limited. The dismal prognosis of GBM has led to novel treatments being a serious roadblock in the field, with most new treatments failing to show efficacy. Targeted therapies have shown some success in many cancers, but GBM remains one of the most difficult to treat, especially in recurrence. New chemotherapeutic directions need to be explored, possibly expanding the targeted chemotherapy spectrum in previously unforeseen ways. In this perspective paper, we will explain why AVIL, an actin-binding protein recently found to be overexpressed in GBM and a driving force for GBM, could prove versatile in the fight against cancer. By looking at AVIL and its potential to regulate FOXM1 and LIN28B, we will be able to highlight a way to improve outcomes for GBM patients who normally have very little hope.