Long non-coding RNA BRAF-regulated lncRNA 1 promotes lymph node invasion, metastasis and proliferation, and predicts poor prognosis in breast cancer

Role of ferroptosis and ferroptosis-related long non'coding RNA in breast cancer

Ferroptosis, a therapeutic strategy for tumours, is a regulated cell death characterised by the increased accumulation of iron-dependent lipid peroxides (LPO). Tumour-associated long non-coding RNAs (lncRNAs), when combined with traditional anti-cancer medicines or radiotherapy, can improve efficacy and decrease mortality in cancer. Investigating the role of ferroptosis-related lncRNAs may help strategise new therapeutic options for breast cancer (BC). Herein, we briefly discuss the genes and pathways of ferroptosis involved in iron and reactive oxygen species (ROS) metabolism, including the XC-/GSH/GPX4 system, ACSL4/LPCAT3/15-LOX and FSP1/CoQ10/NAD(P)H pathways, and investigate the correlation between ferroptosis and LncRNA in BC to determine possible biomarkers related to ferroptosis.

Study of LncRNA BANCR Expression in Tumor Tissues and Adjacent Normal Tissues in Gastric Cancer Patients

Background

Long non-coding RNAs (lncRNAs) have emerged as crucial regulators in various biological processes, including cancer development and progression. This study aimed to investigate the expression differences of the BRAF-activated non-coding RNA (BANCR) gene in GC tissues compared to adjacent normal tissues. The potential diagnostic significance of BANCR in GC was explored, with the aim of improving diagnostic and therapeutic approaches for this global health burden.

Materials and Methods

Tissue samples from 100 gastric cancer (GC) patients were collected, and BANCR expression was analyzed using quantitative real-time PCR. Correlations between BANCR expression and clinicopathological features were assessed, and its biomarker potential was evaluated.

Results

In individuals diagnosed with GC, the expression of BANCR was notably elevated in tumor tissues compared to adjacent normal tissues (P < 0.0001). However, the analysis of gene expression data did not demonstrate any statistically significant correlation between elevated BANCR expression and clinicopathological features. According to the ROC analysis, BANCR demonstrated an AUC of 0.6733 (P < 0.0001), with a sensitivity of 73% and a specificity of 45%. However, further evaluation is required to determine its potential as a biomarker (CI 95% = 0.5992 to 0.7473).

Conclusions

The observed upregulation of BANCR in GC tissues implies its potential involvement as an oncogenic lncRNA in GC patients. Furthermore, BANCR may serve as a promising biomarker for identification and treatment of GC.

Coding roles of long non-coding RNAs in breast cancer: Emerging molecular diagnostic biomarkers and potential therapeutic targets with special reference to chemotherapy resistance

Dysregulation of epigenetic mechanisms have been depicted in several pathological consequence such as cancer. Different modes of epigenetic regulation (DNA methylation (hypomethylation or hypermethylation of promotor), histone modifications, abnormal expression of microRNAs (miRNAs), long non-coding RNAs, and small nucleolar RNAs), are discovered. Particularly, lncRNAs are known to exert pivot roles in different types of cancer including breast cancer. LncRNAs with oncogenic and tumour suppressive potential are reported. Differentially expressed lncRNAs contribute a remarkable role in the development of primary and acquired resistance for radiotherapy, endocrine therapy, immunotherapy, and targeted therapy. A wide range of molecular subtype specific lncRNAs have been assessed in breast cancer research. A number of studies have also shown that lncRNAs may be clinically used as non-invasive diagnostic biomarkers for early detection of breast cancer. Such molecular biomarkers have also been found in cancer stem cells of breast tumours. The objectives of the present review are to summarize the important roles of oncogenic and tumour suppressive lncRNAs for the early diagnosis of breast cancer, metastatic potential, and chemotherapy resistance across the molecular subtypes.

Identification of lncRNAs involved in response to ionizing radiation in fibroblasts of long-term survivors of childhood cancer and cancer-free controls

Introduction

Long non-coding ribonucleic acids (lncRNAs) are involved in the cellular damage response following exposure to ionizing radiation as applied in radiotherapy. However, the role of lncRNAs in radiation response concerning intrinsic susceptibility to late effects of radiation exposure has not been examined in general or in long-term survivors of childhood cancer with and without potentially radiotherapy-related second primary cancers, in particular.

Methods

Primary skin fibroblasts (n=52 each) of long-term childhood cancer survivors with a first primary cancer only (N1), at least one second primary neoplasm (N2+), as well as tumor-free controls (N0) from the KiKme case-control study were matched by sex, age, and additionally by year of diagnosis and entity of the first primary cancer. Fibroblasts were exposed to 0.05 and 2 Gray (Gy) X-rays. Differentially expressed lncRNAs were identified with and without interaction terms for donor group and dose. Weighted co-expression networks of lncRNA and mRNA were constructed using WGCNA. Resulting gene sets (modules) were correlated to the radiation doses and analyzed for biological function.

Results

After irradiation with 0.05Gy, few lncRNAs were differentially expressed (N0: AC004801.4; N1: PCCA-DT, AF129075.3, LINC00691, AL158206.1; N2+: LINC02315). In reaction to 2 Gy, the number of differentially expressed lncRNAs was higher (N0: 152, N1: 169, N2+: 146). After 2 Gy, AL109976.1 and AL158206.1 were prominently upregulated in all donor groups. The co-expression analysis identified two modules containing lncRNAs that were associated with 2 Gy (module1: 102 mRNAs and 4 lncRNAs: AL158206.1, AL109976.1, AC092171.5, TYMSOS, associated with p53-mediated reaction to DNA damage; module2: 390 mRNAs, 7 lncRNAs: AC004943.2, AC012073.1, AC026401.3, AC092718.4, MIR31HG, STXBP5-AS1, TMPO-AS1, associated with cell cycle regulation).

Discussion

For the first time, we identified the lncRNAs AL158206.1 and AL109976.1 as involved in the radiation response in primary fibroblasts by differential expression analysis. The co-expression analysis revealed a role of these lncRNAs in the DNA damage response and cell cycle regulation post-IR. These transcripts may be targets in cancer therapy against radiosensitivity, as well as provide grounds for the identification of at-risk patients for immediate adverse reactions in healthy tissues. With this work we deliver a broad basis and new leads for the examination of lncRNAs in the radiation response.

LDA-LNSUBRW: lncRNA-Disease Association Prediction Based on Linear Neighborhood Similarity and Unbalanced bi-Random Walk

Increasing number of experiments show that lncRNAs are involved in many biological processes, and their mutations and disorders are associated with many diseases. However, verifying the relationships between lncRNAs and diseases is time consuming and laborio. Searching for effective computational methods will contribute to our understanding of the underlying mechanisms of disease and identifying biomarkers of diseases. Therefore, we proposed a method called lncRNA-disease association prediction based on linear neighborhood similarity and unbalanced bi-random walk (LDA-LNSUBRW). Given that the known lncRNA-disease associations are rare, a pretreatment step should be performed to obtain the interaction possibility of unknown cases, so as to help us predict the potential associations. In the framework of leave-one-out cross-validation (LOOCV)and fivefold cross-validation (5-fold CV), LDA-LNSUBRW achieved effective performance with AUC of 0.8874 and 0.8632 ± 0.0051, respectively. The experimental results in this paper show that the proposed method is superior to five other state-of-the-art methods. In addition, case studies of three diseases (lung cancer, breast cancer, and osteosarcoma)were carried out to illustrate that LDA-LNSUBRW could predict the relevant lncRNAs.

Role of lncRNA BANCR in Human Cancers: An Updated Review

Being located in a gene desert region on 9q21.11-q21.12, BRAF-activated non-protein coding RNA (BANCR) is an lncRNA with 693 bp length. It has been discovered in 2012 in a research aimed at assessment of gene expression in the melanocytes in association with BRAF mutation. Increasing numbers of studies have determined its importance in the tumorigenesis through affecting cell proliferation, migration, invasion, apoptosis, and epithelial to mesenchymal transition. BANCR exerts its effects via modulating some tumor-related signaling pathways particularly MAPK and other regulatory mechanisms such as sponging miRNAs. BANCR has been up-regulated in endometrial, gastric, breast, melanoma, and retinoblastoma. Conversely, it has been down-regulated in some other cancers such as those originated from lung, bladder, and renal tissues. In some cancer types such as colorectal cancer, hepatocellular carcinoma and papillary thyroid carcinoma, there is no agreement about BANCR expression, necessitating the importance of additional functional studies in these tissues. In the present manuscript, we review the investigations related to BANCR expression changes in cancerous cell lines, clinical samples, and animal models of cancer. We also discuss the outcome of its deregulation in cancer progression, prognosis, and the underlying mechanisms of these observations.

ICLRBBN: a tool for accurate prediction of potential lncRNA disease associations

Growing evidence has elucidated that long non-coding RNAs (lncRNAs) are involved in a variety of complex diseases in human bodies. In recent years, it has become a hot topic to develop effective computational models to identify potential lncRNA-disease associations. In this article, a novel method called ICLRBBN (Internal Confidence-Based Local Radial Basis Biological Network) is proposed to detect potential lncRNA-disease associations by adopting an internal confidence-based radial basis biological network. In ICLRBBN, a novel internal confidence-based collaborative filtering recommendation algorithm was designed first to mine hidden features between lncRNAs and diseases, which guarantees that ICLRBBN can be more effectively applied to predict new diseases. Then, a unique three-layer local radial basis function network consisting of diseases and lncRNAs was constructed, based on which the association probability between diseases and lncRNAs was calculated by combining different characteristics of lncRNAs with local information of diseases. Finally, we compared ICLRBBN with 6 state-of-the-art methods based on two different validation frameworks. Simulation results showed that area under the receiver operating characteristic curve (AUC) values achieved by ICLRBBN outperformed all competing methods. Furthermore, case studies illustrated that ICLRBBN has a promising future as a powerful tool in the practical application of lncRNA-disease association prediction. A web service for prediction of potential lncRNA-disease associations is available at http://leelab2997.cn/.

High BANCR expression is associated with worse prognosis in human malignant carcinomas: an updated systematic review and meta-analysis

Background

BRAF-activated noncoding RNA (BANCR) is aberrantly expressed in various tumor tissues and has been confirmed to function as a tumor suppressor or oncogene in many types of cancers. Considering the conflicting results and insufficient sampling, a meta-analysis was performed to explore the prognostic value of BANCR in various carcinomas.

Methods

A comprehensive literature search of PubMed, Web of Science, EMBASE, Cochrane Library and the China National Knowledge Infrastructure (CNKI) was conducted to collect relevant articles.

Results

The pooled results showed a strong relationship between high BANCR expression and poor overall survival (OS) (HR (hazard ratio) =1.60, 95% confidence interval (CI): 1.19–2.15, P = 0.002) and recurrence-free survival (RFS) (HR = 1.53, 95% CI: 1.27–1.85, P < 0.00001). In addition, high BANCR expression predicted advanced tumor stage (OR (odds ratio) =2.39, 95% CI: 1.26–4.53, P = 0.008), presence of lymph node metastasis (OR = 2.03, 95% CI: 1.08–3.83, P = 0.03), positive distant metastasis (OR = 3.08, 95% CI: 1.92–4.96, P < 0.00001) and larger tumor sizes (OR = 1.63, 95% CI: 1.09–2.46, P = 0.02). However, no associations were found for smoking status (OR = 1.01, 95% CI: 0.65–1.56, P = 0.98), age (OR = 0.88, 95% CI: 0.71–1.09, P = 0.236) and sex (OR = 0.91, 95% CI: 0.72–1.16, P = 0.469). The sensitivity analysis of OS showed that the results of each publication were almost consistent with the combined results, and the merged results have high robustness and reliability.

Conclusions

The results showed that elevated BANCR expression was associated with unfavorable prognosis for most cancer patients, and BANCR could serve as a promising therapeutic target and independent prognostic predictor in most of cancer types.

Long noncoding RNAs and exosomal lncRNAs: classification, and mechanisms in breast cancer metastasis and drug resistance

Breast cancer is the most common cancer, and the second cause of cancer-related deaths (after lung cancer) among women. Developing tumor metastasis and invasion is the most important cause of death in breast cancer patients. Several key factors participate in breast cancer metastasis including long noncoding RNAs (lncRNAs). lncRNAs are a category of cellular RNAs that are longer than 200 nucleotides in length. Accumulating evidence suggests that lncRNAs have the potential to be promising diagnostic, prognostic biomarkers and therapeutic targets in breast cancer. Understanding the role of lncRNAs and their mechanisms of functions might help to further discovery of breast cancer biological characteristics. In this review, we discuss physiological functions, epigenetic regulation, transcriptional regulation of lncRNAs, and their important role in tumor progression and metastasis. Some lncRNAs function as oncogenes and some function as tumor suppressors. Interestingly, recent reports depict that hypomethylation of promoters of lncRNAs play a pivotal role in cancer progression, suggesting the importance of epigenetic regulation. Furthermore, we discuss the role of lncRNAs in exosomes and their function in drug resistance, and therapeutic importance of exosomal lncRNAs in cancer biology. In summary, lncRNAs have a great potential to consider them as novel prognostic biomarkers as well as new therapeutic targets in breast cancer.

LLCLPLDA: a novel model for predicting lncRNA-disease associations

Long noncoding RNAs play a significant role in the occurrence of diseases. Thus, studying the relationship prediction between lncRNAs and disease is becoming more popular. Researchers hope to determine effective treatments by revealing the occurrence and development of diseases at the molecular level. However, the traditional biological experimental way to verify the association between lncRNAs and disease is very time-consuming and expensive. Therefore, we developed a method called LLCLPLDA to predict potential lncRNA-disease associations. First, locality-constrained linear coding (LLC) is leveraged to project the features of lncRNAs and diseases to local-constraint features, and then, a label propagation (LP) strategy is used to mix up the initial association matrix and the obtained features of lncRNAs and diseases. To demonstrate the performance of our method, we compared LLCLPLDA with five methods in the leave-one-out cross-validation and fivefold cross-validation scheme, and the experimental results show that the proposed method outperforms the other five methods. Additionally, we conducted case studies on three diseases: cervical cancer, gliomas, and breast cancer. The top five predicted lncRNAs for cervical cancer and gliomas were verified, and four of the five lncRNAs for breast cancer were also confirmed.

Research progresses in roles of LncRNA and its relationships with breast cancer

Some progresses have been made in research of long non-coding RNA (hereunder referred to as LncRNA) related to breast cancer. Lots of data about LncRNA transcription concerning breast cancer have been obtained from large-scale omics research (e.g. transcriptomes and chips). Some LncRNAs would become indices for detecting breast cancer and judging its development and prognosis. LncRNAs may affect genesis and development of breast cancer in multiple ways. Perhaps they could develop into potential targets for treating breast cancer if they are carcinogenic. Like those from other studies of breast cancer, many data gained from omics research remain to be validated by much experimental work. For instance, it is still necessary to demonstrate reliability of LncRNAs as indices for diagnosing breast cancer and judging its prognosis (particularly for various subtypes of breast cancer), effectiveness and feasibility of these genes for treating breast cancer as targets. In this paper, recent years’ literatures about LncRNAs which are related to breast cancer are summarized and sorted out to review the research progresses in relationships between LncRNAs and breast cancer.