Overexpression of LncRNA BM466146 Predicts Better Prognosis of Breast Cancer

The current advances of lncRNAs in breast cancer immunobiology research

Breast cancer is the most frequently diagnosed malignancy and the leading cause of cancer-related death in women worldwide. Breast cancer development and progression are mainly associated with tumor-intrinsic alterations in diverse genes and signaling pathways and with tumor-extrinsic dysregulations linked to the tumor immune microenvironment. Significantly, abnormal expression of lncRNAs affects the tumor immune microenvironment characteristics and modulates the behavior of different cancer types, including breast cancer. In this review, we provide the current advances about the role of lncRNAs as tumor-intrinsic and tumor-extrinsic modulators of the antitumoral immune response and the immune microenvironment in breast cancer, as well as lncRNAs which are potential biomarkers of tumor immune microenvironment and clinicopathological characteristics in patients, suggesting that lncRNAs are potential targets for immunotherapy in breast cancer.

LncRNA-BC069792 suppresses tumor progression by targeting KCNQ4 in breast cancer

BACKGROUND

Breast cancer is the most common malignant tumor that threatens women's health. Attention has been paid on the study of long- non-coding RNA (lncRNA) in breast cancer. However, the specific mechanism remains not clear.

METHODS

In this study, we explored the role of lncRNA BC069792 in breast cancer. In vitro and in vivo functional experiments were carried out in cell culture and mouse models. High-throughput next-generation sequencing technology and real-time fluorescence quantitative PCR technology were used to evaluate differentially expressed genes and mRNA expression, Western blot and immunohistochemical staining were used to detect protein expression. RNA immunoprecipitation assay and dual-luciferase activity assay were used to evaluate the competing endogenous RNAs (ceRNA), and rescue and mutation experiments were used for verification.

RESULTS

We found that lncRNA BC069792 was expressed at a low level in breast cancer tissues, and significantly decreased in breast cancer with high pathological grade, lymph node metastasis and high Ki-67 index groups. Moreover, BC069792 inhibited the proliferation, invasion and metastasis of breast cancer cells in vitro and in vivo. Mechanically, BC069792 acts as a molecular sponge to adsorb hsa-miR-658 and hsa-miR-4739, to up-regulate the protein expression of Potassium Voltage-Gated Channel Q4 (KCNQ4), inhibits the activities of JAK2 and p-AKT, and plays a role in inhibiting breast cancer growth.

CONCLUSIONS

LncRNA BC069792 plays the role of tumor suppressor gene in breast cancer and is a new diagnostic index and therapeutic target in breast cancer.

Exosome-Mediated lncRNA LINC01140 Attenuates Breast Cancer Progression by Regulating the Wnt/β-Catenin Pathway

Exosome-delivered long non-coding RNAs have a role in the cancer control. It is unknown how exosomal LINC01140 contributes to the breast cancer (BC) growth. The purpose of this investigation is to identify exosomal LINC01140's function in the development of breast cancer. Using quantitative reverse transcripion polymerase chain reaction, the expression of LINC01140 was measured. To investigate how LINC01140 overexpression impacts BC cell proliferation, CCK-8 as well as colony formation assays (CFA) were employed. The expression of apoptosis-related proteins (Bax and Bcl-2) and Wnt/β-catenin signal pathway-related proteins (Wnt, C-myc, β-catenin, and p-GSK-3β) was assessed through Western blotting. Exosomes from BC cells were verified by western blotting to measure CD63 and CD9 levels. To examine how exosomal LINC01140 affects Wnt/β-catenin signaling pathway and xenograft tumor in nude mice, BC cell exosomes that were overexpressing LINC01140 were obtained and co-cultured with BC cells. In BC, it was discovered that LINC01140 had poor expression. BC cell proliferation was inhibited by overexpressing LINC01140, and the levels of the proteins Bcl-2, β-catenin, C-myc, and Wnt were lowered while Bax and p-GSK-3 were increased. In addition, exosomal LINC01140 hindered the activation of the Wnt/β-catenin signaling pathway, leading to a decrease in the growth of breast cancer cells in vivo. The presence of exosomal LINC01140 impedes the initiation of Wnt/β-catenin and reduces the cancerous characteristics of BC cells.

Long non-coding RNAs and cancer mechanisms: Immune cells and inflammatory cytokines in the tumor microenvironment

Chronic inflammation and immune response are two central hallmarks of the tumor microenvironment (TME), teeming with immune cells and inflammatory cytokines that promote tumor progression. Intriguingly, there is mutual regulation between immune cells and cytokines. Indeed, the differentiation and function of immune cells depend on cytokines secreted from tumor cells, whereas immune activation affects the dynamics of cytokines, reshaping the TME together. Long non-coding RNAs (lncRNAs) as a blooming molecule are virtually involved in physiology and pathology events, especially TME. Notably, the regulatory loop between lncRNAs and cytokines or immune activation plays a vital role in tumor growth. Thus, this review concentrates on the interaction between lncRNAs and immune cells. It puts special attention to the intertwist between lncRNAs and cytokines or immune cells, providing a theoretical basis for lncRNAs as a potential biomarker and therapeutic tumor target.

Hierarchical multi-label classification based on LSTM network and Bayesian decision theory for LncRNA function prediction

Growing evidence shows that long noncoding RNAs (lncRNAs) play an important role in cellular biological processes at multiple levels, such as gene imprinting, immune response, and genetic regulation, and are closely related to diseases because of their complex and precise control. However, most functions of lncRNAs remain undiscovered. Current computational methods for exploring lncRNA functions can avoid high-throughput experiments, but they usually focus on the construction of similarity networks and ignore the certain directed acyclic graph (DAG) formed by gene ontology annotations. In this paper, we view the function annotation work as a hierarchical multilabel classification problem and design a method HLSTMBD for classification with DAG-structured labels. With the help of a mathematical model based on Bayesian decision theory, the HLSTMBD algorithm is implemented with the long-short term memory network and a hierarchical constraint method DAGLabel. Compared with other state-of-the-art algorithms, the results on GOA-lncRNA datasets show that the proposed method can efficiently and accurately complete the label prediction work.

Integrated Analysis of RNA Binding Protein-Related lncRNA Prognostic Signature for Breast Cancer Patients

Long non-coding RNAs (lncRNAs) have been well known for their multiple functions in the tumorigenesis, development, and prognosis of breast cancer (BC). Mechanistically, their production, function, or stability can be regulated by RNA binding proteins (RBPs), which were also involved in the carcinogenesis and progression of BC. However, the roles and clinical implications of RBP-related lncRNAs in BC remain largely unknown. Therefore, we herein aim to construct a prognostic signature with RBP-relevant lncRNAs for the prognostic evaluation of BC patients. Firstly, based on the RNA sequencing data of female BC patients from The Cancer Genome Atlas (TCGA) database, we screened out 377 differentially expressed lncRNAs related to RBPs. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were then performed to establish a prognostic signature composed of 12-RBP-related lncRNAs. Furthermore, we divided the BC patients into high- and low-risk groups by the prognostic signature and found the overall survival (OS) of patients in the high-risk group was significantly shorter than that of the low-risk group. Moreover, the 12-lncRNA signature exhibited independence in evaluating the prognosis of BC patients. Additionally, a functional enrichment analysis revealed that the prognostic signature was associated with some cancer-relevant pathways, including cell cycle and immunity. In summary, our 12-lncRNA signature may provide a theoretical reference for the prognostic evaluation or clinical treatment of BC patients.

Predicting the immune landscape of invasive breast carcinoma based on the novel signature of immune-related lncRNA

Background

The composition of the population of immune‐related long non‐coding ribonucleic acid (irlncRNA) generates a signature, irrespective of expression level, with potential value in predicting the survival status of patients with invasive breast carcinoma.

Methods

The current study uses univariate analysis to identify differentially expressed irlncRNA (DEirlncRNA) pairs from RNA‐Seq data from The Cancer Genome Atlas (TCGA). 36 pairs of DEirlncRNA pairs were identified. Using various algorithms to construct a model, we have compared the area under the curve and calculated the 5‐year curve of Akaike information criterion (AIC) values, which allows determination of the threshold indicating the maximum value for differentiation. Through cut‐off point to establish the optimal model for distinguishing high‐risk or low‐risk groups among breast cancer patients. We assigned individual patients with invasive breast cancer to either high risk or low risk groups depending on the cut‐off point, re‐evaluated the tumor immune cell infiltration, the effectiveness of chemotherapy, immunosuppressive biomarkers, and immunotherapy.

Results

After re‐assessing patients according to the threshold, we demonstrated an effective means of distinguish the severity of the disease, and identified patients with different clinicopathological characteristics, specific tumor immune infiltration states, high sensitivity to chemotherapy,wellpredicted response to immunotherapy and thus a more favorable survival outcome.

Conclusions

The current study presents novel findings regarding the use of irlncRNA without the need to predict precise expression levels in the prognosis of breast cancer patients and to indicate their suitability for anti‐tumor immunotherapy.

Roles of long noncoding RNAs on tumor immune escape by regulating immune cells differentiation and function

A long noncoding RNA (lncRNA) transcript is generally more than 200 nucleotides in length and rarely codes for any protein. Currently, many lncRNAs have been identified among mammalian genomes, and their known functions are associated with various physiological activities or pathological processes. Some lncRNAs are dysregulated in a variety of malignant tumors, while increasing evidence indicates that abnormal expression can contribute to the regulation of immune cells in tumors and to shaping the immune response. More specifically, lncRNAs participate in regulating the differentiation of immune cells, also known as myeloid and lymphoid cells, as well as recruiting various immunosuppressive factors to influence the tumor microenvironment, thereby promoting tumor cell immune escape. However, we still know very little about the specific mechanism of lncRNAs in immune escape of cancer. Nonetheless, although unprecedented achievements have allowed the development of a new generation of anti-tumor immune therapies to be applied in clinical trials, the drug resistance caused by immune escape has become a major clinical challenge. The focus of this review is to describe the relationship among lncRNAs, immune cells, and tumor immune escape, in order to identify novel diagnostic and therapeutic targets in human cancers.