Identification of functional long non-coding RNAs in gastric cancer by bioinformatics analysis

Exosomal lncRNA Mir100hg derived from cancer stem cells enhance glycolysis and promote metastasis of lung adenocarcinoma through mircroRNA-15a-5p/31-5p

BACKGROUND

Exosomes are a new class of molecular entities in the metastatic microenvironment, which can mediate bidirectional communication between cells. While exosomes-mediated interactions between tumor cells and other cell populations in the tumor microenvironment have attracted most attention, little is known about the significance of exosomes in mediating the interaction between non-stemness cancer cells and cancer stem cells during cancer progression.

METHODS

The structure, sequence and downstream target miRNAs of lncRNA Mir100hg were predicted by online web resources. The bioinformatics prediction results were validated with experimental verification: exosome tracing, electron microscopy, Luciferase assay, metabolomics sequencing and mouse tail vein model of pulmonary metastasis. A complex regulatory network of "cancer stem cells-exosomal lncRNA-non-stem cancer cells" was constructed.

RESULTS

This study demonstrates firstly that lncRNA Mir100hg is upregulated in lung cancer stem cell LLC-SD (Lung cancer stem cells) and can be delivered to non-stemness cancer cells LLC (Lewis lung cancer cells) via exosomes. In LLC, Mir100hg targets miR-15a-5p and miR-31-5p which leads to the increase of the global glycolytic activity of lung cancer cells and consequently, the enhancement of their metastatic capability.

CONCLUSION

We delineated a complex regulatory network that utilized by cancer stem cells to transfer their high metastatic activity to the low-metastatic non-stemness cancer cells through exosomal Mir100hg, thereby providing new mechanistic insights into the communication between two heterogeneous tumor cells. Video Abstract.

A concise review on the role of MIR100HG in human disorders

MIR100HG is a long non-coding RNA (lncRNA) encoded by a locus on chr11:122,028,203-122,556,721. This gene can regulate cell proliferation, apoptosis, cell cycle transition and cell differentiation. MIR100HG was firstly identified through a transcriptome analysis and found to regulate differentiation of human neural stem cells. It is functionally related with a number of signalling pathways such as TGF-β, Wnt, Hippo and ERK/MAPK signalling pathways. Dysregulation of MIR100HG has been detected in a diversity of cancers in association with clinical outcomes. Moreover, it has a role in the pathophysiology of dilated cardiomyopathy, intervertebral disk degeneration and pulmonary fibrosis. The current study summarizes the role of these lncRNAs in human disorders.

A cuproptosis-related LncRNA signature: Integrated analysis associated with biochemical recurrence and immune landscape in prostate cancer

Background: As a new form of regulated cell death, cuproptosis differs profoundly from apoptosis, ferroptosis, pyroptosis, and necroptosis. The correlation between cuproptosis and long non-coding RNAs (lncRNAs) has been increasingly studied recently. In this study, a novel cuproptosis-related lncRNA prognostic signature was developed to investigate biochemical recurrence (BCR) and tumor immune landscape in prostate cancer (PCa). Methods and Materials: The transcriptome data and clinicopathologic information of PCa patients were downloaded from The Cancer Genome Atlas (TCGA). Pearson's correlation analysis was applied to identify lncRNAs associated with cuproptosis. Based on Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a cuproptosis-related lncRNA prognostic model (risk score) to predict the BCR of PCa patients. Additionally, we also constructed a nomogram with the risk score and clinicopathologic features. The biological function, tumor mutation burden (TMB), immune cell infiltration, expression levels of immune checkpoint genes, and anti-cancer drug sensitivity were investigated. Results: We constructed and validated the cuproptosis-related lncRNA signature prognostic model (risk score) by six crlncRNAs. All patients were divided into the low- and high-risk groups based on the median risk score. The Kaplan-Meier (KM) survival analysis revealed that the high-risk group had shorter BCR-free survival (BCRFS). The risk score has been proven to be an independent prognostic factor of BCR in PCa patients. In addition, a nomogram of risk scores and clinicopathologic features was established and demonstrated an excellent predictive capability of BCR. The ROC curves further validated that this nomogram had higher accuracy of predicting the BCR compared to other clinicopathologic features. We also found that the high-risk group had higher TMB levels and more infiltrated immune cells. Furthermore, patients with high TMB in the high-risk group were inclined to have the shortest BCRFS. Finally, patients in the high-risk group were more susceptible to docetaxel, gefitinib, methotrexate, paclitaxel, and vinblastine. Conclusion: The novel crlncRNA signature prognostic model shows a greatly prognostic prediction value of BCR for PCa patients, extends our thought on the association of cuproptosis and PCa, and provides novel insights into individual-based treatment strategies for PCa.

LncmiRHG-MIR100HG: A new budding star in cancer

MIR100HG, also known as lncRNA mir-100-let-7a-2-mir-125b-1 cluster host gene, is a new and critical regulator in cancers in recent years. MIR100HG is dysregulated in various cancers and plays an oncogenic or tumor-suppressive role, which participates in many tumor cell biology processes and cancer-related pathways. The errant expression of MIR100HG has inspired people to investigate the function of MIR100HG and its diagnostic and therapeutic potential in cancers. Many studies have indicated that dysregulated expression of MIR100HG is markedly correlated with poor prognosis and clinicopathological features. In this review, we will highlight the characteristics and introduce the role of MIR100HG in different cancers, and summarize the molecular mechanism, pathways, chemoresistance, and current research progress of MIR100HG in cancers. Furthermore, some open questions in this rapidly advancing field are proposed. These updates clarify our understanding of MIR100HG in cancers, which may pave the way for the application of MIR100HG-targeting approaches in future cancer diagnosis, prognosis, and therapy.

A Novel Prognostic Model Based on Autophagy-Related Long Non-Coding RNAs for Clear Cell Renal Cell Carcinoma

Background

Renal cell carcinoma (RCC) is one of the most common malignant tumors of the urinary system, of which the clear cell renal cell carcinoma (ccRCC) accounts for the most subtypes. The increasing discoveries of abundant autophagy-related long non-coding RNAs (ARLNRs) lead to a resurgent interest in evaluating their potential on prognosis prediction. Based on a large number of ccRCC gene samples from TCGA and clinics, ARLNRs analysis will provide a novel perspective into this field.

Methods

We calculated the autophagy scores of each sample according to the expression levels of autophagy-related genes (ARGs) and screened the survival-related ARLNRs (sARLNRs) of ccRCC patients by Cox regression analysis. The high-risk group and the low-risk group were distinguished by the median score of the autophagy-related risk score (ARRS) model. The functional annotations were detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA). The expression levels of two kinds of sARLNRs in the renal tumor and adjacent normal tissues and cell lines were verified.

Results

There were 146 ARLNRs selected by Pearson analysis. A total of 30 sARLNRs were remarkably correlated with the clinical outcomes of ccRCC patients. Eleven sARLNRs (AC002553.1, AC092611.2, AL360181.2, AP002807.1, AC098484.1, AL513218.1, AC008735.2, MHENCR, AC020907.4, AC011462.4, and AC008870.2) with the highest prognosis value were recruited to establish the ARRS in which the overall survival (OS) in the high-risk group was shorter than that in the low-risk group. ARRS could be treated as an independent prognostic factor and has significant correlations with OS. The distributions of autophagy genes were different between the high-risk group and the low-risk group. In addition, we also found that the expression levels of AC098484.1 in ccRCC cell lines and tumor tissues were lower than those in HK-2 and adjacent normal tissues, but AL513218.1 showed the inverse level. Furthermore, the AC098484.1 expressed decreasingly with the more advanced T-stages, but AL513218.1 gradually increased.

Conclusion

Our study identified and verified some sARLNRs with clinical significances and revealed their potential values on predicting prognoses of ccRCC patients, which may provide a novel perspective for autophagy-related research and clinical decisions.

Knockdown of long non-coding RNA TPT1-AS1 inhibits invasion and migration of hepatocarcinoma cells

BACKGROUND

The long non-coding RNA (lncRNA) TPT1-AS1 has been proved to affect the migration and invasion of tumor cells by different means, but its specific role and related mechanisms in hepatic carcinoma still need further research.

AIM

To investigate the expression of TPT1-AS1 in hepatocarcinoma tissues and cell lines and explore its biological role in the invasion and migration of hepatocarcinoma cells.

METHODS

Real-time quantitative PCR was used to measure lncRNA TPT1-AS1 expression in hepatocarcinoma tissue and cell lines (Huh7, SMMC-7721, HCCLM3, and HepG2). After being transfected with small interfering RNA (siRNA-TPT1-AS1), the invasion and migration of HepG2 cells were detected by transwell assay and wound healing assay. Western blot was used to measure the epithelial-mesenchymal transition (EMT) process and the activity of the PI3K/AKT pathway.

RESULTS

TPT1-AS1 was up-regulated in hepatopcarcinoma tissues and cell lines Huh7, SMMC-7721, HCCLM3, and HepG2. Transfection with siRNA-TPT1-AS1 noticeably restrained HepG2 cell invasion and migration, and suppressed the EMT process. Furthermore, TPT1-AS1 knockdown reduced MMP-9 expression and inhibited the activation of the PI3K/AKT pathway.

CONCLUSION

TPT1-AS1 is up-n regulated in hepatic carcinoma. Knockdown of TPT1-AS1 inhibits the invasion and migration of HepG2 cells via mechanisms that may be associated with reducing the activity of PI3K/AKT pathway and the expression of its downstream gene MMP-9, and inhibiting the EMT process.

HAND2-AS1: A functional cancer-related long non-coding RNA

Long non-coding RNAs (lncRNAs) regulate gene expression and carcinogenesis. The lncRNA heart and neural crest derivatives expressed transcript 2 antisense RNA 1 (HAND2‑AS1) suppresses tumor growth, and its expression level was lower in tumor tissues than in adjacent normal tissues of most types of human cancers, including non-small cell lung cancer, ovarian cancer, breast cancer, gastric cancer, colorectal cancer, cervical cancer, endometrial cancer, prostate cancer, and esophagus squamous cell carcinoma. However, one study reported that the HAND2‑AS1 expression was upregulated in hepatocellular carcinoma tissues comparing with non-tumor tissues and it promoted tumor development. The aberrant expression of HAND2-AS1 was strongly linked to tumor progression and prognosis. Moreover, HAND2-AS1 was involved in tumor cell proliferation, differentiation, apoptosis, and cellular glucose metabolism. This review summarizes data on the expression profile, functions, underlying mechanism, and clinical value of HAND2-AS1 in cancer. The expression profile of HAND2-AS1 in 33 tumors was evaluated by bioinformatics analysis of The Cancer Genome Atlas.

Identification of functional long non-coding RNAs in gastric cancer by bioinformatics analysis

Long non-coding RNAs (lncRNAs) have been proven to play important roles in various cancers, including gastric cancer (GC). However, detailed knowledge about lncRNAs in GC is limited. Therefore we carried out an in-depth study of public data and found 83 differently expressed lncRNAs in GC. To further confirm the target genes of these lncRNAs, we constructed a co-expression network between lncRNAs and mRNAs and found three lncRNAs (MBNL1-AS1, HAND2-AS1 and MIR100HG) were at the core of the network. By coalition analysis of clinical information and the three lncRNAs' expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor. Clinical samples showed patients with higher MIR100HG expression had poorer prognosis, and further experiments demonstrated that MIR100HG was associated with proliferation, migration and invasion of GC cells. Hopefully, MIR100HG might be considered as a novel prognostic factor and biomarker for GC.