Function and regulation annotation of up-regulated long non-coding RNA LINC01234 in gastric cancer

Biomarkers of gastric cancer: current advancement

Gastric cancer (GC) is one of the most prevalent malignant types worldwide, especially in East Asia. Due to its frequently advanced stage at diagnosis, the mortality from GC is high and the prognosis is still unsatisfactory. Thus, early detection using effective screening approaches is vital to decrease the morbidity and mortality of GC. Interestingly, biomarkers can be used for diagnosis, prediction of sensitivity to treatment, and prognosis in GC. The potential biomarkers detectable in liquid biopsies such as circulating tumor cells (CTCs), long non-coding RNAs (lncRNAs), cell-free DNA (cfDNA), microRNAs, and exosomes reveal numerous information regarding the early prediction and the outcomes for GC patients. Additionally, using the novel serum biomarkers has opened up new opportunities for diagnosing and monitoring patients with GC. This review mainly summarizes the novel progress and approaches in GC biomarkers, which could be potentially used for early diagnosis and therapy monitoring. Meanwhile, we also discussed the advantages, disadvantages, and future perspectives of GC biomarkers.

Oncogenic roles of LINC01234 in various forms of human cancer

Abnormal expression of long non-coding RNAs (lncRNAs) plays an essential role in various malignant neoplasia. As a newly identified lncRNA, LINC01234 is abnormally expressed in several types of cancers and promotes the development of cancers. Accumulating evidence indicates that overexpression of LINC01234 is associated with poor clinical outcomes. Moreover, LINC01234 modulates many cellular events as a putative proto-oncogene, including proliferation, migration, invasion, apoptosis, cell cycle progression, and EMT. In terms of molecular mechanism, LINC01234 regulates gene expression by acting as ceRNA, participating in signaling pathways, interacting with proteins and other molecules, and encoding polypeptide. It reveals that LINC01234 may serve as a potential biomarker for cancer diagnosis, treatment, and prognosis. This review summarizes the expression pattern, biological function, and molecular mechanism of LINC01234 in human cancer and discusses its potential clinical utility.

The lncRNA Signatures of Genome Instability to Predict Survival in Patients with Renal Cancer

Long noncoding RNAs (lncRNAs) exert an increasingly important effect on genome instability and the prognosis of cancer patients. The present research established a computational framework originating from the mutation assumption combining lncRNA expression profile and somatic mutation profile in the genome of renal cancer to assess the effect of lncRNAs on the gene instability of renal cancer. A total of 45 differentially expressed lncRNAs were evaluated to be genome-instability-associated from the high and low cumulative somatic mutations groups. Then we established a prognosis model based on three genome-instability-associated lncRNAs (AC156455.1, AC016405.3, and LINC01234)-GlncScore. The GlncScore was then verified in testing cohort and the total TCGA renal cancer cohort. The GlncScore was evaluated to have an accurate prediction for the survival of patients. Furthermore, GlncScore was associated with somatic mutation patterns, indicating its capacity of reflecting genome instability in renal cancer. In conclusion, this study evaluated the effect of lncRNAs on genome instability of renal cancer and provided new hidden cancer biomarkers related to genome instability in renal cancer.

Identification of lncRNA-associated competing endogenous RNA networks for occurrence and prognosis of gastric carcinoma

Background

Gastric cancer (GC) is one of the common digestive malignancies worldwide and causes a severe public health issue. So far, the underlying mechanisms of GC are largely unclear. Thus, we aim to identify the long non‐coding RNA (lncRNA)‐associated competing endogenous RNA (ceRNA) for GC.

Methods

TCGA database was downloaded and used for the identification of differentially expressed (DE) lncRNAs, miRNAs, and mRNAs, respectively. Then, the ceRNA network was constructed via multiple online datasets and approaches. In addition, various in vitro assays were carried out to validate the effect of certain hub lncRNAs.

Results

We constructed a ceRNA network, including 76 lncRNAs, 18 miRNAs, and 159 mRNAs, which involved multiple critical pathways. Next, univariate and multivariate analysis demonstrated 11 lncRNAs, including LINC02731, MIR99AHG, INHBA‐AS1, CCDC144NL‐AS1, VLDLR‐AS1, LIFR‐AS1, A2M‐AS1, LINC01537, and LINC00702, and were associated with OS, and nine of those lncRNAs were considered as hub lncRNAs involved in the sub‐ceRNA network. The in vitro assay indicated two lncRNAs, INHBA‐AS1 and CCDC144NL‐AS1, which were positively related to the GC aggressive features, including proliferation, invasion, and migration.

Conclusions

We identified nine hub lncRNAs and the associated ceRNA network related to the prognosis of GC, and then validated two out of them as promising oncogenes in GC.

Development and Validation of an Mesenchymal-Related Long Non-Coding RNA Prognostic Model in Glioma

Glioma is well known as the most aggressive and prevalent primary malignant tumor in the central nervous system. Molecular subtypes and prognosis biomarkers remain a promising research area of gliomas. Notably, the aberrant expression of mesenchymal (MES) subtype related long non-coding RNAs (lncRNAs) is significantly associated with the prognosis of glioma patients. In this study, MES-related genes were obtained from The Cancer Genome Atlas (TCGA) and the Ivy Glioblastoma Atlas Project (Ivy GAP) data sets of glioma, and MES-related lncRNAs were acquired by performing co-expression analysis of these genes. Next, Cox regression analysis was used to establish a prognostic model, that integrated ten MES-related lncRNAs. Glioma patients in TCGA were divided into high-risk and low-risk groups based on the median risk score; compared with the low-risk groups, patients in the high-risk group had shorter survival times. Additionally, we measured the specificity and sensitivity of our model with the ROC curve. Univariate and multivariate Cox analyses showed that the prognostic model was an independent prognostic factor for glioma. To verify the predictive power of these candidate lncRNAs, the corresponding RNA-seq data were downloaded from the Chinese Glioma Genome Atlas (CGGA), and similar results were obtained. Next, we performed the immune cell infiltration profile of patients between two risk groups, and gene set enrichment analysis (GSEA) was performed to detect functional annotation. Finally, the protective factors DGCR10 and HAR1B, and risk factor SNHG18 were selected for functional verification. Knockdown of DGCR10 and HAR1B promoted, whereas knockdown of SNHG18 inhibited the migration and invasion of gliomas. Collectively, we successfully constructed a prognostic model based on a ten MES-related lncRNAs signature, which provides a novel target for predicting the prognosis for glioma patients.

Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology

Background

There is evidence that long non-coding RNA (lncRNA) is related to genetic stability. However, the complex biological functions of these lncRNAs are unclear.

Method

TCGA - KIRC lncRNAs expression matrix and somatic mutation information data were obtained from TCGA database. “GSVA” package was applied to evaluate the genomic related pathway in each samples. GO and KEGG analysis were performed to show the biological function of lncRNAs-mRNAs. “Survival” package was applied to determine the prognostic significance of lncRNAs. Multivariate Cox proportional hazard regression analysis was applied to conduct lncRNA prognosis model.

Results

In the present study, we applied computational biology to identify genome-related long noncoding RNA and identified 26 novel genomic instability-associated lncRNAs in clear cell renal cell carcinoma. We identified a genome instability-derived six lncRNA-based gene signature that significantly divided clear renal cell samples into high- and low-risk groups. We validated it in test cohorts. To further elucidate the role of the six lncRNAs in the model’s genome stability, we performed a gene set variation analysis (GSVA) on the matrix. We performed Pearson correlation analysis between the GSVA scores of genomic stability-related pathways and lncRNA. It was determined that LINC00460 and LINC01234 could be used as critical factors in this study. They may influence the genome stability of clear cell carcinoma by participating in mediating critical targets in the base excision repair pathway, the DNA replication pathway, homologous recombination, mismatch repair pathway, and the P53 signaling pathway.

Conclusion subsections

These data suggest that LINC00460 and LINC01234 are crucial for the stability of the clear cell renal cell carcinoma genome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08356-9.

The Role and Specific Mechanism of OCT4 in Cancer Stem Cells: A Review

Recently, evidences show that cancer stem cells (CSCs) are a type of cancer cell group with self-renewal and play a huge role in tumor recurrence, metastasis, and drug resistance. Finding new treatment directions and targets for cancer prognosis and reducing mortality has become a top priority. OCT4, as a transcription factor, participates in maintaining the stem characteristics of CSCs, but the mechanism of OCT4 is often overlooked. In this review, we try to illustrate the mechanism by which OCT4 plays a role in CSCs from the perspective of genetic modification of OCT4, non-coding RNA, complexes and signaling pathways associated with OCT4. Our ultimate goal is to provide new targets for cancer treatment to prolong the survival of cancer patients.

Function and regulation annotation of up-regulated long non-coding RNA LINC01234 in gastric cancer

Background

Accumulated evidences indicate that long non‐coding RNAs (lncRNAs) participate in many biological mechanisms. Moreover, it acts as an essential regulator in various human diseases such as gastric cancer (GC). Nevertheless, the comprehensive regulatory roles and clinical significance of most lncRNAs in GC are not fully understood.

Methods

In this research, our aim was to investigate the underlying mechanism of lncRNA LINC01234 in GC. Firstly, the usage of qRT‐PCR helped to establish expression pattern of LINC01234 in GC tissues. Following this, appropriate statistical tests were applied to analyze the relation between expression level and clinicopathological factors. Ultimately, potential functions and regulatory network of LINC01234 were concluded via GSEA and a series of bioinformatics tools or databases, respectively.

Results

Consequently, at the end of research we found LINC01234 is up‐regulated in GC tissues in comparison with adjacent normal tissues. Furthermore, its expression level is correlated with differentiation of patients with GC. It is also important to highlight bioinformatics analysis revealed that LINC01234 is involved in cancer‐associated pathways such as cell cycle and mismatch repair. Also, regulatory network of LINC01234 presented a probability in the involvement of tumorigenesis through regulating cancer‐associated genes.

Conclusion

Overall, our results suggested that LINC01234 may play a crucial role in GC.