LINC00511 as a prognostic biomarker for human cancers: a systematic review and meta-analysis

lncRNAs and cyclin-dependent kinases: Unveiling their critical roles in cancer progression

Long non-coding RNAs (lncRNAs) are a diverse class of RNA molecules that do not code for proteins but play critical roles in gene regulation. One such role involves the modulation of cell cycle progression and proliferation through interactions with cyclin-dependent kinases (CDKs), key regulators of cell division. Dysregulation of CDK activity is a hallmark of cancer, contributing to uncontrolled cell growth and tumor formation. These lncRNA-CDK interactions are part of a complex network of molecular mechanisms underlying cancer pathogenesis, involving various signaling pathways and regulatory circuits. Understanding the interplay between lncRNAs, CDKs, and cancer biology holds promise for developing novel therapeutic strategies targeting these molecular targets for more effective cancer treatment. Furthermore, targeting CDKs, key cell cycle progression and proliferation regulators, offers another avenue for disrupting cancer pathways and overcoming drug resistance. This can open new possibilities for individualized treatment plans and focused therapeutic interventions.

YY1-induced lncRNA00511 promotes melanoma progression via the miR-150-5p/ADAM19 axis

Increasing evidence indicates that long noncoding RNAs (lncRNAs) are therapeutic targets and key regulators of tumors development and progression, including melanoma. Long intergenic non-protein-coding RNA 511 (LINC00511) has been demonstrated as an oncogenic molecule in breast, stomach, colorectal, and lung cancers. However, the precise role and functional mechanisms of LINC00511 in melanoma remain unknown. This study confirmed that LINC00511 was highly expressed in melanoma cells (A375 and SK-Mel-28 cells) and tissues, knockdown of LINC00511 could inhibit melanoma cell migration and invasion, as well as the growth of subcutaneous tumor xenografts in vivo. By using Chromatin immunoprecipitation (ChIP) assay, it was demonstrated that the transcription factor Yin Yang 1 (YY1) is capable of binding to the LINC00511 promoter and enhancing its expression in cis. Further mechanistic investigation showed that LINC00511 was mainly enriched in the cytoplasm of melanoma cells and interacted directly with microRNA-150-5p (miR-150-5p). Consistently, the knockdown of miR-150-5p could recover the effects of LINC00511 knockdown on melanoma cells. Furthermore, ADAM metallopeptidase domain expression 19 (ADAM19) was identified as a downstream target of miR-150-5p, and overexpression of ADAM19 could promote melanoma cell proliferation. Rescue assays indicated that LINC00511 acted as a competing endogenous RNA (ceRNA) to sponge miR-150-5p and increase the expression of ADAM19, thereby activating the PI3K/AKT pathway. In summary, we identified LINC00511 as an oncogenic lncRNA in melanoma and defined the LINC00511/miR-150-5p/ADAM19 axis, which might be considered a potential therapeutic target and novel molecular mechanism the treatment of patients with melanoma.

The Intergenic Type LncRNA (LINC RNA) Faces in Cancer with In Silico Scope and a Directed Lens to LINC00511: A Step toward ncRNA Precision

BACKGROUND

Long intergenic non-coding RNA, is one type of lncRNA, exerting various cellular activities, as does ncRNA, including the regulation of gene expression and chromatin remodeling. The abnormal expression of lincRNAs can induce or suppress carcinogenesis.

MAIN BODY

LincRNAs can regulate cancer progression through different mechanisms and are considered as potential drug targets. Genetic variations such as single nucleotide polymorphisms (SNPs) in lincRNAs may affect gene expression and messenger ribonucleic acid (mRNA) stability. SNPs in lincRNAs have been found to be associated with different types of cancer, as well. Specifically, LINC00511 has been known to promote the progression of multiple malignancies such as breast cancer, colorectal cancer, lung cancer, hepatocellular carcinoma, and others, making it a promising cancer prognostic molecular marker.

CONCLUSION

LincRNAs have been proved to be associated with different cancer types through various pathways. Herein, we performed a comprehensive literature and in silico databases search listing lncRNAs, lincRNAs including LINC00511, lncRNAs' SNPs, as well as LINC00511 SNPs in different cancer types, focusing on their role in various cancer types and mechanism(s) of action.

Comprehensive Analysis to Identify LINC00511-hsa-miR-625-5p-SEMA6A Pathway Fuels Progression of Skin Cutaneous Melanoma

Objective

Skin cutaneous melanoma (SKCM) is a highly lethal malignancy that poses a significant threat to human health. Recent research has shown that competing endogenous RNA (ceRNA) regulatory networks play a critical role in the development and progression of various types of cancer, including SKCM. The objective of this study is to investigate the ceRNA regulatory network associated with the transmembrane protein semaphorin 6A (SEMA6A) and identify the underlying molecular mechanisms involved in SKCM.

Methods

Expression profiles of four RNAs, including pseudogenes, long non-coding RNAs, microRNAs, and mRNAs were obtained from The Cancer Genome Atlas database. The analysis was completed by bioinformatics methods, and the expression levels of the selected genes were verified by cell experiments.

Results

Bioinformatics analysis revealed that the LINC00511-hsa-miR-625-5p-SEMA6A ceRNA network was associated with SKCM prognosis. Furthermore, immune infiltration analysis indicated that the LINC00511-hsa-miR-625-5p-SEMA6A axis may have an impact on changes in the tumor immune microenvironment of SKCM.

Conclusion

The LINC00511-hsa-miR-625-5p-SEMA6A axis could be a promising therapeutic target and a prognostic biomarker for SKCM.

Increased interleukin-6 is associated with long COVID-19: a systematic review and meta-analysis

BACKGROUND

Coronavirus disease 2019 (COVID-19) can involve persistence, sequelae, and other clinical complications that last weeks to months to evolve into long COVID-19. Exploratory studies have suggested that interleukin-6 (IL-6) is related to COVID-19; however, the correlation between IL-6 and long COVID-19 is unknown. We designed a systematic review and meta-analysis to assess the relationship between IL-6 levels and long COVID-19.

METHODS

Databases were systematically searched for articles with data on long COVID-19 and IL-6 levels published before September 2022. A total of 22 published studies were eligible for inclusion following the PRISMA guidelines. Analysis of data was undertaken by using Cochran's Q test and the Higgins I-squared (I²) statistic for heterogeneity. Random-effect meta-analyses were conducted to pool the IL-6 levels of long COVID-19 patients and to compare the differences in IL-6 levels among the long COVID-19, healthy, non-postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (non-PASC), and acute COVID-19 populations. The funnel plot and Egger's test were used to assess potential publication bias. Sensitivity analysis was used to test the stability of the results.

RESULTS

An increase in IL-6 levels was observed after SARS-CoV-2 infection. The pooled estimate of IL-6 revealed a mean value of 20.92 pg/ml (95% CI = 9.30-32.54 pg/ml, I² = 100%, P < 0.01) for long COVID-19 patients. The forest plot showed high levels of IL-6 for long COVID-19 compared with healthy controls (mean difference = 9.75 pg/ml, 95% CI = 5.75-13.75 pg/ml, I² = 100%, P < 0.00001) and PASC category (mean difference = 3.32 pg/ml, 95% CI = 0.22-6.42 pg/ml, I² = 88%, P = 0.04). The symmetry of the funnel plots was not obvious, and Egger's test showed that there was no significant small study effect in all groups.

CONCLUSIONS

This study showed that increased IL-6 correlates with long COVID-19. Such an informative revelation suggests IL-6 as a basic determinant to predict long COVID-19 or at least inform on the "early stage" of long COVID-19.

Comprehensive analysis of lncRNA-mRNA co-expression networks in HPV-driven cervical cancer reveals the pivotal function of LINC00511-PGK1 in tumorigenesis

BACKGROUND

Mounting evidence suggests that noncoding RNAs (lncRNAs) were involved in various human cancers. However, the role of these lncRNAs in HPV-driven cervical cancer (CC) has not been extensively studied. Considering that HR-HPV infections contribute to cervical carcinogenesis by regulating the expression of lncRNAs, miRNAs and mRNAs, we aim to systematically analyze lncRNAs and mRNAs expression profile to identify novel lncRNAs-mRNAs co-expression networks and explore their potential impact on tumorigenesis in HPV-driven CC.

METHODS

LncRNA/mRNA microarray technology was utilized to identify the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) in HPV-16 and HPV-18 cervical carcinogenesis compared to normal cervical tissues. Venn diagram and weighted gene co-expression network analysis (WGCNA) were used to identify the hub DElncRNAs/DEmRNAs that were both significantly correlated with HPV-16 and HPV-18 CC patients. LncRNA-mRNA correlation analysis and functional enrichment pathway analysis were performed on these key DElncRNAs/DEmRNAs in HPV-16 and HPV-18 CC patients to explore their mutual mechanism in HPV-driven CC. A lncRNA-mRNA co-expression score (CES) model was established and validated by using the Cox regression method. Afterward, the clinicopathological characteristics were analyzed between CES-high and CES-low groups. In vitro, functional experiments were performed to evaluate the role of LINC00511 and PGK1 in cell proliferation, migration and invasion in CC cells. To understand whether LINC00511 play as an oncogenic role partially via modulating the expression of PGK1, rescue assays were used.

RESULTS

We identified 81 lncRNAs and 211 mRNAs that were commonly differentially expressed in HPV-16 and HPV-18 CC tissues compared to normal tissues. The results of lncRNA-mRNA correlation analysis and functional enrichment pathway analysis showed that the LINC00511-PGK1 co-expression network may make an important contribution to HPV-mediated tumorigenesis and be closely associated with metabolism-related mechanisms. Combined with clinical survival data, the prognostic lncRNA-mRNA co-expression score (CES) model based on LINC00511 and PGK1 could precisely predict patients' overall survival (OS). CES-high patients had a worse prognosis than CES-low patients and the enriched pathways and potential targets of applicable drugs were explored in CES-high patients. In vitro experiments confirmed the oncogenic functions of LINC00511 and PGK1 in the progression of CC, and revealed that LINC00511 functions in an oncogenic role in CC cells partially via modulating the expression of PGK1.

CONCLUSIONS

Together, these data identify co-expression modules that provide valuable information to understand the pathogenesis of HPV-mediated tumorigenesis, which highlights the pivotal function of the LINC00511-PGK1 co-expression network in cervical carcinogenesis. Furthermore, our CES model has a reliable predicting ability that could stratify CC patients into low- and high-risk groups of poor survival. This study provides a bioinformatics method to screen prognostic biomarkers which leads to lncRNA-mRNA co-expression network identification and construction for patients' survival prediction and potential drug applications in other cancers.

LINC00511, a future star for the diagnosis and therapy of digestive system malignant tumors

The digestive system malignant tumors (DSMTs), mainly consist of digestive tract and digestive gland tumors, become an inescapable culprit to hazard human health worldwide. Due to the huge hysteresis in the cognitive theories of DSMTs occurrence and progression, advances in medical technology have not improved the prognosis. Therefore, more studies on a variety of tumor-associated molecular biomarkers and more detailed disclosure on potential regulatory networks are urgently needed to facilitate the diagnostic and therapeutic strategies of DSMTs. With the development of cancer bioinformatics, a special type of endogenous RNA involved in multi-level cellular function regulation rather than encoding protein, is categorized as non-coding RNAs (ncRNAs) and becomes a hotspot issue in oncology. Among them, long non-coding RNAs (lncRNAs), transcription length > 200 nt, show obvious superiority in both research quantity and dimension compared to microRNAs (miRNAs) and circular RNAs (circRNAs). As a recently discovered lncRNA, LINC00511 has been confirmed to be closely associated with DSMTs and might be exploited as a novel biomarker. In the present review, the comprehensive studies of LINC00511 in DSMTs are summarized, as well as the underlying molecular regulatory networks. In addition, deficiencies in researches are point out and discussed. The Cumulative oncology studies provide a fully credible theoretical basis for identifying the regulatory role of LINC00511 in human DSMTs. LINC00511, proved to be an oncogene in DSMTs, might be defined as a potential biomarker for diagnosis and prognosis evaluation, as well as a rare therapeutic target.

A review on the role of LINC00511 in cancer

Long Intergenic Non-Protein Coding RNA 511 (LINC00511) is an RNA gene being mostly associated with lung cancer. Further assessments have shown dysregulation of this lncRNA in a variety of cancers. LINC00511 has interactions with hsa-miR-29b-3p, hsa-miR-765, hsa-mir-150, miR-1231, TFAP2A-AS2, hsa-miR-185-3p, hsa-miR-29b-1-5p, hsa-miR-29c-3p, RAD51-AS1 and EZH2. A number of transcription factors have been identified that regulate expression of LINC00511. The current narrative review summarizes the role of LINC00511 in different cancers with an especial focus on its prognostic impact in human cancers.

Metformin Treatment Modulates Long Non-Coding RNA Isoforms Expression in Human Cells

Long noncoding RNAs (lncRNAs) undergo splicing and have multiple transcribed isoforms. Nevertheless, for lncRNAs, as well as for mRNA, measurements of expression are routinely performed only at the gene level. Metformin is the first-line oral therapy for type 2 diabetes mellitus and other metabolic diseases. However, its mechanism of action remains not thoroughly explained. Transcriptomic analyses using metformin in different cell types reveal that only protein-coding genes are considered. We aimed to characterize lncRNA isoforms that were differentially affected by metformin treatment on multiple human cell types (three cancer, two non-cancer) and to provide insights into the lncRNA regulation by this drug. We selected six series to perform a differential expression (DE) isoform analysis. We also inferred the biological roles for lncRNA DE isoforms using in silico tools. We found the same isoform of an lncRNA (AC016831.6-205) highly expressed in all six metformin series, which has a second exon putatively coding for a peptide with relevance to the drug action. Moreover, the other two lncRNA isoforms (ZBED5-AS1-207 and AC125807.2-201) may also behave as cis-regulatory elements to the expression of transcripts in their vicinity. Our results strongly reinforce the importance of considering DE isoforms of lncRNA for understanding metformin mechanisms at the molecular level.

Crosstalk between autophagy inhibitors and endosome-related secretory pathways: a challenge for autophagy-based treatment of solid cancers

Autophagy is best known for its role in organelle and protein turnover, cell quality control, and metabolism. The autophagic machinery has, however, also adapted to enable protein trafficking and unconventional secretory pathways so that organelles (such as autophagosomes and multivesicular bodies) delivering cargo to lysosomes for degradation can change their mission from fusion with lysosomes to fusion with the plasma membrane, followed by secretion of the cargo from the cell. Some factors with key signalling functions do not enter the conventional secretory pathway but can be secreted in an autophagy-mediated manner.Positive clinical results of some autophagy inhibitors are encouraging. Nevertheless, it is becoming clear that autophagy inhibition, even within the same cancer type, can affect cancer progression differently. Even next-generation inhibitors of autophagy can have significant non-specific effects, such as impacts on endosome-related secretory pathways and secretion of extracellular vesicles (EVs). Many studies suggest that cancer cells release higher amounts of EVs compared to non-malignant cells, which makes the effect of autophagy inhibitors on EVs secretion highly important and attractive for anticancer therapy. In this review article, we discuss how different inhibitors of autophagy may influence the secretion of EVs and summarize the non-specific effects of autophagy inhibitors with a focus on endosome-related secretory pathways. Modulation of autophagy significantly impacts not only the quantity of EVs but also their content, which can have a deep impact on the resulting pro-tumourigenic or anticancer effect of autophagy inhibitors used in the antineoplastic treatment of solid cancers.

Long noncoding RNA as a biomarker for the prognosis of ischemic stroke: A protocol for meta-analysis and bioinformatics analysis

BACKGROUND

As the most common type of cerebrovascular disease, ischemic stroke is the disturbance of cerebrovascular circulation caused by various factors, with complex pathogenesis. At present, the molecular mechanism of ischemic stroke is still unclear, and there lacks early diagnostic markers. Therefore, there is an urgent need to find effective preventive measures, active diagnostic methods and rapid treatment measures. In recent years, related studies have displayed that long noncoding RNAs (lncRNAs) is related to the prognosis of ischemic stroke. However, the results are not supported by some evidence. Therefore, in this study, meta-analysis was used to analyze the relationship between lncRNAs and the prognosis of ischemic stroke. In addition, we carried out bioinformatics analysis to study the action mechanism and related pathways of lncRNAs in ischemic stroke.

METHODS

Literature search was operated on databases up to March 2021, including China National Knowledge Infrastructure, Chinese Biomedical literature Database, Chinese Scientific and Journal Database, Wan Fang database, Web of Science, PubMed, and EMBASE. The relationship between lncRNAs expression and survival outcome was estimated by hazard ratio (HR) and 95% confidence interval (CI). Meta-analysis was conducted on the Stata 16.0. Starbase v2.0 software predicts microRNAs (miRNAs) that interacts with lncRNAs. In addition, HMDD v2.0 database filters out miRNAs related to ischemic stroke. Furthermore, Consite transcription factor database was used to predict the transcription factors of each lncRNAs and miRNA. At the same time, the transcription factors related to ischemic stroke were screened out after intersection. miRwalk online software was applied to predict the target mRNA of each miRNA, and the common target genes were screened by consistent method. The molecular regulatory network map of lncRNAs in ischemic stroke was drawn. Based on the overlapping target genes, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network analysis were carried out to explore the possible mechanism.

RESULTS

The results of this meta-analysis would be submitted to peer-reviewed journals for publication.

CONCLUSION

This study will provide evidence-based medical evidence for the relationship between lncRNA and the prognosis of ischemic stroke. What is more, bioinformatics analysis will provide ideas for the study of ischemic stroke mechanism.

ETHICS AND DISSEMINATION

The private information from individuals will not be published. This systematic review also should not damage participants' rights. Ethical approval is not available. The results may be published in a peer-reviewed journal or disseminated in relevant conferences.

OSF REGISTRATION NUMBER

DOI 10.17605/OSF.IO/QBZW6.