lncRNA USP30-AS1 sponges miR-765 and modulates the progression of colon cancer

Long noncoding RNA USP30-AS1 promotes influenza A virus replication by enhancing PHB1 function

Long noncoding RNAs (lncRNAs) are important regulators of gene expression. Although evidence accumulated over the past decade shows that lncRNAs have key roles in the interaction between viruses and hosts, the functions of the majority of differentially expressed lncRNAs in response to viral infections remain uncharacterized so far. In this study, we have identified that USP30 antisense RNA 1 (USP30-AS1), a host antisense lncRNA, is hijacked by influenza A virus (IAV) to assist its replication. We show that USP30-AS1 is IAV-induced via the Janus protein tyrosine kinase-signal transducer and the activator of transcription (JAK-STAT) signaling pathway. Functionally, ectopic expression of USP30-AS1 significantly promotes IAV replication. Conversely, silencing USP30-AS1 suppresses IAV replication. Mechanistically, USP30-AS1 directly binds prohibitin 1 (PHB1) and modulates its protein stability and function. On the one hand, the binding of USP30-AS1 sequesters PHB1 away from the E3 ubiquitin ligase, tripartite motif containing 21 (TRIM21), thereby protecting the protein stability of PHB1. On the other hand, USP30-AS1 serves as a molecular scaffold for enhancing the interaction between PHB1 and interferon regulatory factor 3 (IRF3), which in turn impedes the nuclear import of IRF3. Therefore, our data unveil an important role of USP30-AS1 in promoting viral replication by modulating PHB1 stability and functions, providing a new insight into the role of lncRNAs in the interplay between IAV and host.

The expression of the lncRNAs USP30-AS1, ELFN1-AS1, GAS8-AS1, and SNHG11 in breast cancer samples from Iranian patients from 2014 to 2019: a cross-sectional study

OBJECTIVE

Breast cancer is a widely prevalent and life-threatening malignancy that affects women worldwide. The identification of novel molecular markers associated with tumor progression is highly important for enhancing early detection, tailoring treatment approaches, and monitoring therapeutic outcomes. In this study, we investigated the expression patterns of four long noncoding RNAs (lncRNAs): USP30 antisense RNA1 (USP30-AS1), ELFN1 antisense RNA1 (ELFN1-AS1), GAS8 antisense RNA1 (GAS8-AS1), and small nucleolar RNA host gene 11 (SNHG11).

RESULTS

In breast cancer specimens, USP30-AS1 and GAS8-AS1 expression was decreased, whereas ELFN1-AS1 and SNHG11 expression was increased in breast cancer tissues compared with adjacent noncancer tissues. Decreased USP30-AS1 levels were associated with a smaller tumor size, lower tumor grade and stage, and the absence of lymphatic and vascular invasion. Lower GAS8-AS1 expression was associated with a lower tumor grade and positive estrogen and progestin receptor status. Elevated ELFN1-AS1 expression was associated with breast cancer that lacked P53 mutation. These changes suggest their promise as biomarkers for distinguishing between cancerous and noncancerous tissues.

Unraveling the role of long non-coding RNAs in therapeutic resistance in acute myeloid leukemia: New prospects & challenges

Acute Myeloid Leukemia (AML) is a fatal hematological disease characterized by the unchecked proliferation of immature myeloid blasts in different tissues developed by various mutations in hematopoiesis. Despite intense chemotherapeutic regimens, patients often experience poor outcomes, leading to substandard remission rates. In recent years, long non-coding RNAs (lncRNAs) have increasingly become important prognostic and therapeutic hotspots, due to their contributions to dysregulating many functional epigenetic, transcriptional, and post-translational mechanisms leading to alterations in cell expressions, resulting in increased chemoresistance and reduced apoptosis in leukemic cells. Through this review, I highlight and discuss the latest advances in understanding the major mechanisms through which lncRNAs confer therapy resistance in AML. In addition, I also provide perspective on the current strategies to target lncRNA expressions. A better knowledge of the critical role that lncRNAs play in controlling treatment outcomes in AML will help improve existing medications and devise new ones.

Long non‑coding RNAs as diagnostic and prognostic biomarkers for colorectal cancer (Review)

Colorectal cancer (CRC) ranks as the 3rd most common cancer globally and is the 2nd leading cause of cancer-related death. Owing to the lack of specific early symptoms and the limitations of existing early diagnostic methods, most patients with CRC are diagnosed at advanced stages. To overcome these challenges, researchers have increasingly focused on molecular biomarkers, with particular interest in long non-coding RNAs (lncRNAs). These non-protein-coding RNAs, which exceed 200 nucleotides in length, play critical roles in the development and progression of CRC. The stability and detectability of lncRNAs in the circulatory system make them promising candidate biomarkers. The analysis of circulating lncRNAs in peripheral blood represents a potential option for minimally invasive diagnostic tests based on liquid biopsy samples. The present review aimed to evaluate the efficacy of lncRNAs with altered expression levels in peripheral blood as diagnostic markers for CRC. Additionally, the clinical significance of lncRNAs as prognostic markers for this disease were summarized.

The role of miR-765 in human cancers

MicroRNAs, a collection of short noncoding RNAs, are promising biomarkers for identifying cancer in its early stages and tracking the effectiveness of treatment. This is due to their critical role in regulating gene expression and other vital biological functions via cell-level epigenetic mechanisms. This review brings together data on the molecular and clinical effects of miR-765 on different types of cancer. Significant variation in miR-765 levels has been observed in a variety of cancer types, suggesting that it could have an oncogene or tumor suppressor role. A number of pathways, including PLP2/Notch, VEGFA/Akt1, PDX1, KLK4, RUNX2, DPF3, EMP3, APE1, ERK/EMT axis, and others, are impacted by the inclusion of miR-765 in their analysis. MiR-765 is an essential biomarker that shows promise as a diagnostic tool for various types of cancer. The latest research has identified them as reliable predictive markers for detecting tumor development at an early stage. Based on our study, miR-765 shows promising potential as a biomarker for prognosis in multiple types of cancer. Specifically, we suggest that miR-765 could be an early detection marker for tumor development, progression, and metastasis.

Senescence-Related LncRNAs: Pioneering Indicators for Ovarian Cancer Outcomes

In gynecological oncology, ovarian cancer (OC) remains the most lethal, highlighting its significance in public health. Our research focused on the role of long non-coding RNA (lncRNA) in OC, particularly senescence-related lncRNAs (SnRlncRNAs), crucial for OC prognosis. Utilizing data from the genotype-tissue expression (GTEx) and cancer genome Atlas (TCGA), SnRlncRNAs were discerned and subsequently, a risk signature was sculpted using co-expression and differential expression analyses, Cox regression, and least absolute shrinkage and selection operator (LASSO). This signature's robustness was validated through time-dependent receiver operating characteristics (ROC), and multivariate Cox regression, with further validation in the international cancer genome consortium (ICGC). Gene set enrichment analyses (GSEA) unveiled pathways intertwined with risk groups. The ROC, alongside the nomogram and calibration outcomes, attested to the model's robust predictive accuracy. Of particular significance, our model has demonstrated superiority over several commonly utilized clinical indicators, such as stage and grade. Patients in the low-risk group demonstrated greater immune infiltration and varied drug sensitivities compared to other groups. Moreover, consensus clustering classified OC patients into four distinct groups based on the expression of 17 SnRlncRNAs, showing diverse survival rates. In conclusion, these findings underscored the robustness and reliability of our model and highlighted its potential for facilitating improved decision-making in the context of risk assessment, and demonstrated that these markers potentially served as robust, efficacious biomarkers and prognostic tools, offering insights into predicting OC response to anticancer therapeutics.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-024-00163-z.

The functions and mechanisms of long non-coding RNA in colorectal cancer

CRC poses a significant challenge in the global health domain, with a high number of deaths attributed to this disease annually. If CRC is detected only in its advanced stages, the difficulty of treatment increases significantly. Therefore, biomarkers for the early detection of CRC play a crucial role in improving patient outcomes and increasing survival rates. The development of a reliable biomarker for early detection of CRC is particularly important for timely diagnosis and treatment. However, current methods for CRC detection, such as endoscopic examination, blood, and stool tests, have certain limitations and often only detect cases in the late stages. To overcome these constraints, researchers have turned their attention to molecular biomarkers, which are considered a promising approach to improving CRC detection. Non-invasive methods using biomarkers such as mRNA, circulating cell-free DNA, microRNA, LncRNA, and proteins can provide more reliable diagnostic information. These biomarkers can be found in blood, tissue, stool, and volatile organic compounds. Identifying molecular biomarkers with high sensitivity and specificity for the early and safe, economic, and easily measurable detection of CRC remains a significant challenge for researchers.

The landscape of immune checkpoint-related long non-coding RNAs core regulatory circuitry reveals implications for immunoregulation and immunotherapy responses

Long non-coding RNAs (lncRNAs) could modulate expression of immune checkpoints (ICPs) by cooperating with immunity genes in tumor immunization. However, precise functions in immunity and potential for predicting ICP inhibitors (ICI) response have been described for only a few lncRNAs. Here we present an integrated framework that leverages network-based analyses and Bayesian network inference to identify the regulated relationships including lncRNA, ICP and immunity genes as ICP-related LncRNAs mediated Core Regulatory Circuitry Triplets (ICP-LncCRCTs) that can make robust predictions. Hub ICP-related lncRNAs such as MIR155HG and ADAMTS9-AS2 were highlighted to play central roles in immune regulation. Specific ICP-related lncRNAs could distinguish cancer subtypes. Moreover, the ICP-related lncRNAs are likely to significantly correlated with immune cell infiltration, MHC, CYT. Some ICP-LncCRCTs such as CXCL10-MIR155HG-ICOS could better predict one-, three- and five-year prognosis compared to single molecule in melanoma. We also validated that some ICP-LncCRCTs could effectively predict ICI-response using three kinds of machine learning algorithms follow five independent datasets. Specially, combining ICP-LncCRCTs with the tumor mutation burden (TMB) improves the prediction of ICI-treated melanoma patients. Altogether, this study will improve our grasp of lncRNA functions and accelerating discovery of lncRNA-based biomarkers in ICI treatment.

MIR143HG promotes methylation of transcription factor HOXB7 promoter by recruiting methyltransferase DNMT1 to prevent the progression of colon cancer

In recent years, accumulating evidence has demonstrated the role of long noncoding RNAs (lncRNAs) in colon cancer. We aim to investigate the role of MIR143HG, also known as CARMN (Cardiac mesoderm enhancer-associated noncoding RNA) in colon cancer and explore the related mechanisms. An RNAseq data analysis was performed to screen differentially expressed lncRNAs associated with colon cancer. Next, MIR143HG expression was quantified in colon cancer cells. Moreover, the contributory roles of MIR143HG in the progression of colon cancer with the involvement of DNMT1 and HOXB7 (Homeobox B7) were evaluated after restored MIR143HG or depleted HOXB7. Finally, the effects of MIR143HG were investigated in vivo by measuring tumor formation in nude mice. High-throughput transcriptome sequencing was employed to validate the specific mechanisms by which MIR143HG and HOXB7 affect tumor growth in vivo. MIR143HG was found to be poorly expressed, while HOXB7 was highly expressed in colon cancer. MIR143HG could promote HOXB7 methylation by recruiting DNMT1 to reduce HOXB7 expression. Upregulation of MIR143HG or downregulation of HOXB7 inhibited cell proliferation, invasion and migration and facilitated apoptosis in colon cancer cells so as to delay the progression of colon cancer. The same trend was identified in vivo. Our study provides evidence that restoration of MIR143HG suppressed the progression of colon cancer via downregulation of HOXB7 through DNMT1-mediated HOXB7 promoter methylation. Thus, MIR143HG may be a potential candidate for the treatment of colon cancer.

Prognostic role of long non-coding RNA USP30-AS1 in ovarian cancer: insights into immune cell infiltration in the tumor microenvironment

Ovarian cancer represents a formidable gynecologic malignancy bearing a dismal prognosis owing to the dearth of reliable early detection approaches and a high recurrence rate. Long non-coding RNAs (lncRNAs) have garnered immense attention as key orchestrators involved in diverse biological processes and take part in cancer initiation and progression. The present study investigated the potential significance of lncRNA USP30-AS1 in ovarian cancer prognosis, as well as its putative association with immune cell infiltration in tumor immune microenvironment (TIME). By analyzing publicly available datasets, we identified six lncRNAs with prognostic prediction ability, including USP30-AS1. The results revealed a significant positive correlation of USP30-AS1 expression with the infiltration of immune cells such as Th1 cells, TFH, CD8 T cells, B cells, antigen-presenting dendritic cells (aDC), and plasmacytoid dendritic cells (pDC) in ovarian cancer specimens. These findings provide compelling evidence of the potential involvement of lncRNA in the regulation of the TME in ovarian carcinoma. The outcomes from this study underscore the potential of USP30-AS1 as a promising prognostic biomarker for ovarian cancer. Additionally, the findings offer significant insights into the plausible role of lncRNAs in modulating immune activities, thus adding to our understanding of the disease biology. Additional investigations are necessary to unravel the molecular mechanisms underpinning these connections and validate the results seen in independent cohorts and experimental models.

Pyroptosis-related lncRNA prognostic signatures for cutaneous melanoma and tumor microenvironment status

Aims: To explore whether the expression of pyroptosis-related lncRNAs makes a difference in the prognosis and antitumor immunity of cutaneous melanoma (CM) patients. Methods: A series of analyses were conducted to establish a prognostic risk model and validate its accuracy. Immune-related analyses were performed to further assess the associations among immune status, tumor microenvironment and the prognostic risk model. Results: Eight pyroptosis-related lncRNAs relevant to prognosis were ascertained and applied to establish the prognostic risk model. The low-risk group had a higher overall survival rate. Conclusion: The established prognostic risk model presents better prediction ability for the prognosis of CM patients and provides new possible therapeutic targets for CM.

T2DB: A Web Database for Long Non-Coding RNA Genes in Type II Diabetes

Type II diabetes (T2D) is a growing health problem worldwide due to increased levels of obesity and can lead to other life-threatening diseases, such as cardiovascular and kidney diseases. As the number of individuals diagnosed with T2D rises, there is an urgent need to understand the pathogenesis of the disease in order to prevent further harm to the body caused by elevated blood glucose levels. Recent advances in long non-coding RNA (lncRNA) research may provide insights into the pathogenesis of T2D. Although lncRNAs can be readily detected in RNA sequencing (RNA-seq) data, most published datasets of T2D patients compared to healthy donors focus only on protein-coding genes, leaving lncRNAs to be undiscovered and understudied. To address this knowledge gap, we performed a secondary analysis of published RNA-seq data of T2D patients and of patients with related health complications to systematically analyze the expression changes of lncRNA genes in relation to the protein-coding genes. Since immune cells play important roles in T2D, we conducted loss-of-function experiments to provide functional data on the T2D-related lncRNA USP30-AS1, using an in vitro model of pro-inflammatory macrophage activation. To facilitate lncRNA research in T2D, we developed a web application, T2DB, to provide a one-stop-shop for expression profiling of protein-coding and lncRNA genes in T2D patients compared to healthy donors or subjects without T2D.

An Immune-Related lncRNA Pairing Model for Predicting the Prognosis and Immune-Infiltrating Cell Condition in Human Ovarian Cancer

Ovarian cancer is the second common cancer among the gynecological tumors. It is difficult to be found and diagnosed in the early stage and easy to relapse due to chemoresistance and deficiency in choices of treatment. Therefore, future exploring the biomarkers for diagnosis, treatment, and prognosis prediction of ovarian cancer is significant to women in the world. We downloaded data from TCGA and GTEx and used R “limma” package for analyzing the differentially expressed immune-related lncRNA in ovarian cancer and finally got 7 downregulated and 171 upregulated lncRNA. Then, we paired the differentially expressed immune-related lncRNA and constructed a novel lncRNA pairing model containing 7 lncRNA pairs. Based on the cut-off point with the highest AUC value, 102 patients were selected in high-risk group and 272 in low-risk group. The KM analysis suggested that the patients in the low-risk group had a longer overall survival. Future analysis showed the correlations between risk scores and clinicopathological parameters and infiltrating immune cells. In conclusion, we identified an immune-related lncRNA pairing model for predicting the prognosis and immune-infiltrating cell condition in human ovarian cancer, which thus further can instruct immunotherapy.