Downregulated LINC00460 inhibits cell proliferation and promotes cell apoptosis in prostate cancer

Ferroptosis-Related lncRNAs Act as Novel Prognostic Biomarkers in the Gastric Adenocarcinoma Microenvironment, Immunotherapy, and Chemotherapy

Ferroptosis, a form of programmed cell death akin to necrosis, is managed by iron and is distinguished by lipid peroxidation. Gastric cancer is a highly aggressive form of cancer, responsible for the third highest number of cancer-related deaths globally. Despite this, the potential of ferroptosis to predict the occurrence of this cancer is yet to be determined. In this research, a comprehensive examination was conducted to explore the link between long noncoding RNAs (lncRNAs) and ferroptosis, in order to uncover an lncRNA signature that can predict drug susceptibility and tumor mutational burden (TMB) in gastric adenocarcinoma. We conducted an in-depth analysis of the GC immune microenvironment and immunotherapy, with a particular focus on ferroptosis-related lncRNA prognostic biomarkers, and further explored the correlation between these factors and prognosis, immune infiltration, single nucleotide variation (SNV), and drug sensitivity for gastric adenocarcinoma patients. Through our investigations, we have discovered five lncRNA signatures related to ferroptosis that can accurately forecast the prognosis of gastric adenocarcinoma patients and also regulate the proliferation, migration, and occurrence of ferroptosis in gastric adenocarcinoma cells. In conclusion, this lncRNA signature associated with ferroptosis may be employed as a prognostic indicator for gastric adenocarcinoma, thus presenting a potential solution.

Development of genomic instability-associated long non-coding RNA signature: A prognostic risk model of clear cell renal cell carcinoma

Purpose

Renal clear cell carcinoma (ccRCC) is the most lethal of all pathological subtypes of renal cell carcinoma (RCC). Genomic instability was recently reported to be related to the occurrence and development of kidney cancer. The biological roles of long non-coding RNAs (lncRNAs) in tumorigenesis have been increasingly valued, and various lncRNAs were found to be oncogenes or cancer suppressors. Herein, we identified a novel genomic instability-associated lncRNA (GILncs) model for ccRCC patients to predict the overall survival (OS).

Methods

The Cancer Genome Atlas (TCGA) database was utilized to obtain full transcriptome data, somatic mutation profiles, and clinical characteristics. The differentially expressed lncRNAs between the genome-unstable-like group (GU) and the genome-stable-like group (GS) were defined as GILncs, with |logFC| > 1 and an adjusted p-value< 0.05 for a false discovery rate. All samples were allocated into GU-like or GS-like types based on the expression of GILncs observed using hierarchical cluster analyses. A genomic instability-associated lncRNA signature (GILncSig) was constructed using parameters of the included lncRNAs. Quantitative real-time PCR analysis was used to detect the in vitro expression of the included lncRNAs. Validation of the risk model was performed by the log-rank test, time-dependent receiver operating characteristic (ROC) curves analysis, and multivariate Cox regression analysis.

Results

Forty-six lncRNAs were identified as GILncs. LINC00460, AL139351.1, and AC156455.1 were employed for GILncSig calculation based on the results of Cox analysis. GILncSig was confirmed as an independent predictor for OS of ccRCC patients. Additionally, it presented a higher efficiency and accuracy than other RCC prognostic models reported before.

Conclusion

GILncSig score was qualified as a critical indicator, independent of other clinical factors, for prognostic prediction of ccRCC patients.

Identification of a prognostic classifier based on EMT-related lncRNAs and the function of LINC01138 in tumor progression for lung adenocarcinoma

Purpose: This study aimed to develop a prognostic indicator based on epithelial-mesenchymal transition (EMT)-related long noncoding RNAs (lncRNAs) and explore the function of EMT-related lncRNAs in malignant progression in lung adenocarcinoma (LUAD).

Materials and methods: A LUAD dataset was acquired from The Cancer Genome Atlas (TCGA) to identify prognostic EMT-related lncRNAs via differential expression analysis and univariate Cox regression analysis. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was utilized for variable selection and model construction. The EMT-related prognostic index (ERPI) was calculated according to the model and served as a classifier to divide LUAD individuals into high-ERPI and low-ERPI groups. A nomogram incorporating ERPI and clinicopathological variables was constructed. TCGA-LUAD, GSE50081, and GSE31210 were used to test the predictive capacity of the ERPI and nomogram. The characteristics of the tumor microenvironment (TME) were evaluated via the ESTIMATE, TIMER, and ssGSEA algorithms. Gene set variation analysis (GSVA) and ssGSEA were used to annotate the functions of the high-ERPI and low-ERPI groups. CCK8, transwell assay, wound-healing assay, and clone formation assay were conducted to clarify the biological functions of prognostic EMT-related lncRNAs.

Results: Ninety-seven differentially expressed EMT-related lncRNAs were identified, 15 of which were related to overall survival (OS). A prognostic signature was constructed based on 14 prognostic EMT-related lncRNAs to calculate the ERPI of each patient, and the predictive ability of ERPI was verified in TCGA, GSE50081, and GSE31210. The low-ERPI group survived longer and had a lower percentage of patients in advanced stage than the high-ERPI group. The nomogram had the highest predictive accuracy, followed by ERPI and stage. Patients with low ERPI had higher infiltration degree of immune cells and stronger immune responses than those with high ERPI. A series of in vitro experiments demonstrated that knockdown of LINC01138 dampened variability, proliferation, and motility of A549 and H460 cells.

Conclusion: Our study developed a prognostic classifier with robust prognostic performance and clarified the biological functions of LINC01138 in LUAD, aiding in making individual treatments for patients with LUAD and dissecting the mechanism of oncogenesis.

LINC00460 Is a Dual Biomarker That Acts as a Predictor for Increased Prognosis in Basal-Like Breast Cancer and Potentially Regulates Immunogenic and Differentiation-Related Genes

Breast cancer (BRCA) is a serious public health problem, as it is the most frequent malignant tumor in women worldwide. BRCA is a molecularly heterogeneous disease, particularly at gene expression (mRNAs) level. Recent evidence shows that coding RNAs represent only 34% of the total transcriptome in a human cell. The rest of the 66% of RNAs are non−coding, so we might be missing relevant biological, clinical or regulatory information. In this report, we identified two novel tumor types from TCGA with LINC00460 deregulation. We used survival analysis to demonstrate that LINC00460 expression is a marker for poor overall (OS), relapse-free (RFS) and distant metastasis-free survival (DMFS) in basal-like BRCA patients. LINC00460 expression is a potential marker for aggressive phenotypes in distinct tumors, including HPV-negative HNSC, stage IV KIRC, locally advanced lung cancer and basal-like BRCA. We show that the LINC00460 prognostic expression effect is tissue-specific, since its upregulation can predict poor OS in some tumors, but also predicts an improved clinical course in BRCA patients. We found that the LINC00460 expression is significantly enriched in the Basal-like 2 (BL2) TNBC subtype and potentially regulates the WNT differentiation pathway. LINC00460 can also modulate a plethora of immunogenic related genes in BRCA, such as SFRP5, FOSL1, IFNK, CSF2, DUSP7 and IL1A and interacts with miR-103-a-1, in-silico, which, in turn, can no longer target WNT7A. Finally, LINC00460:WNT7A ratio constitutes a composite marker for decreased OS and DMFS in Basal-like BRCA, and can predict anthracycline therapy response in ER-BRCA patients. This evidence confirms that LINC00460 is a master regulator in BRCA molecular circuits and influences clinical outcome.

Long Noncoding RNA LINC00460 Promotes Hepatocellular Carcinoma Progression via Regulation of miR-342-3p/AGR2 Axis

BACKGROUND

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related death worldwide. LINC00460, a novel long non-coding RNA (lncRNA), was recently confirmed as an oncogene in various cancers. However, the biological function and underlying mechanism of LINC00460 in HCC is largely obscure.

METHODS

Fifty pairs of tumor tissue and adjacent normal tissues from HCC patients, as well as six HCC cell lines and a normal human hepatic epithelial cell line were subjected to qRT-PCR assay to evaluate the expression levels of LINC00460. CCK-8 assays were used to detect the proliferation of HCC cells. Transwell assay was used to measure the migration and invasion abilities of HCC cells. RNA pull-down and luciferase assays were performed to verify the direct interaction between LINC00460 and miR-342-3p. A xenograft model of HCC was established to validate the in vivo function of LINC00460 in HCC progression.

RESULTS

We firstly detected LINC00460 expression was significantly upregulated in both HCC tumor tissues and cell lines. The upregulation of LINC00460 was positively associated with HCC progression. Functionally, LINC00460 facilitated HCC cell proliferation, migration, and invasion capacities, which due to that LINC00460 could physically bind to and repress miR-342-3p to elevate the expression of AGR2.

CONCLUSION

Our data firstly reveal the clinical relevance, biological function, and regulatory mechanism of LINC00460 in HCC development. LINC00460 promotes HCC progression by elevating AGR2 expression via sponging miR-342-3p, providing a promising therapeutic target for HCC treatment.