LINC01116 affects patient survival differently and is dissimilarly expressed in ER+ and ER− breast cancer samples

Abstract Background Breast cancer is the most commonly detected cancer and one of the leading causes of cancer mortality. Emerging evidence supports that aberrant expression of lncRNAs is correlated with tumor progression and various aspects of tumor development. Aim This study aimed to evaluate the expression pattern of LINC01116 in breast cancer tissues and investigate the impact of LINC01116 on patients' survival. Methods and Results Microarray and qRT‐PCR data analysis were performed, and the KM‐plotter database was used in this study. In addition, the gain of function approach was performed to examine the effect of LINC01116 on breast cancer cells in‐vitro. The results exhibited that LINC01116 is meaningfully upregulated in the ER+ tumor specimens compared to the ER– ones. Also, relative to normal tissues, the expression of LINC01116 in ER+ and ER– tumor tissues significantly increased and decreased, respectively. ROC curve analysis revealed the power of LINC01116 in distinguishing ER+ from ER– samples. Additionally, the Kaplan‐Meier survival analysis showed that the LINC01116 expression positively correlates with survival probability in all as well as ER+ patients. However, this correlation was negative in ER– patients. Furthermore, our results showed that the overexpression of LINC01116 induces TGF‐β signaling in ER– cells (MDA‐MB‐231), and microarray data analysis revealed that LINC01116 is significantly upregulated in 17β‐Estradiol treated MCF7 cells. Conclusion In conclusion, our results suggest that LINC01116 can be a potential biomarker in distinguishing ER+ and ER– tissues and has different effects on patients' survival based on ER status by affecting TGF‐β and ER signaling.

disease. 3,4 Hence, identifying potential molecular targets, regulatory elements, and diagnostic and prognostic biomarkers, such as various non-coding RNAs (ncRNA), could be helpful in cancer prevention and therapy. 5,6 Non-coding RNAs have emerged as a crucial player in cancer progression and inhibition of tumorigenesis. Recent studies have shown that ncRNAs, such as microRNAs, long non-coding RNAs (lncRNAs), and circular RNAs, can regulate gene expression at different levels of the central dogma of molecular biology, affecting various cellular processes and cancer development, such as tumor growth, angiogenesis, cell cycle, drug resistance, and epithelial to mesenchymal transition (EMT). 7,8 Moreover, ncRNAs have gained significant attention as potential diagnostic biomarkers for cancer due to their tissue-specific expression patterns and stability in body fluids. Identifying specific ncRNA signatures associated with different types of cancer could lead to the development of non-invasive diagnostic tools for early detection and monitoring of disease progression. The study of ncRNA has opened up new avenues for understanding the molecular mechanisms underlying cancer pathogenesis and has provided promising targets for therapeutic intervention. 9,10 Breast cancer, as a heterogeneous malignancy, should not be considered a single disease and can be classified into different major subtypes based on Estrogen receptor (ER) status: Estrogen-receptor-positive (ER +) and Estrogen-receptor-negative (ERÀ), which ER+ accounts for about 70% of breast cancer. 11 Detection of ER+ or ERÀ in breast cancer can allow for timely treatment and management of the disease before it progresses to an advanced stage. In addition, knowing the subtype of breast cancer can help healthcare providers tailor treatment plans to each patient's needs. 12 Although it is well-reported that ER signaling involves many mitogenic roles, such as cell growth, proliferation, and anti-apoptotic effects, 13,14 ER signaling maintains the epithelial phenotype and opposes EMT. 14,15 In contrast, transforming growth factor-β (TGF-β) oppose these roles; it can induce EMT and reveals an antiproliferative effect in breast cancer cells. Interestingly, there is a close crosstalk between ER and TGF-β, and they can suppress each other's signaling.
TGF-β signaling correlates with breast tumors and poor prognosis. In addition, TGF-induced migration and invasion of breast cancer cells are reduced by ER signaling activation. 16 It should be emphasized that several studies have reported that lncRNAs are involved in TGF-β signaling in various cancers. 17 LINC01116 (long intergenic non-protein coding RNA 1116), also known as TALNEC2 as well termed ENSG00000163364 [Ensembl], is a 1058 bp lncRNA located in the 2q31.1 genomic region. 18 LINC01116 functions in proliferation, apoptosis, and cell cycle, as an oncogene have been investigated in various cancers, such as glioma, 19,20 lung adenocarcinoma, 21,22 prostate cancer, 23 and breast cancer. 24 The expression of LINC01116 is significantly upregulated in all these cancers. [19][20][21][22][23][24] LINC01116 has also been shown to exacerbate hypoxia or ischemic injuries in myocardial, 25 cerebral ischemia, 26 and osteonecrosis. 27 It has been reported that LINC01116 expression was significantly upregulated under hypoxia, causing apoptosis and decreasing cell viability, invasion, and migration in a cardiomyocyte's cell line (H9c2). 25 It has been reported that the downregulation of LINC01116 suppresses the AKT signaling pathway in lung adenocarcinoma. 21 On the other hand, It has been proved that the overexpression of LINC01116 caused inhibition of the PI3K/AKT/mTOR signaling pathway and decreased cell viability. 27 31 in order to investigate the impact of 17β-Estradiol treatment on LINC01116 expression; and GSE26459 32 to indicate the LINC01116 expression in Tamoxifen resistance cells. These datasets were analyzed using the R language with the help of limma, GEOquery, and genefilter packages. [33][34][35][36] Quantile normalization and log2 transformation were used to modify the count data. Also, the false discovery rate (FDR) method was applied to calculate the adjusted p-value (Adj. p-value). The final graphs were produced by the pheatmap package 37 and GraphPad Prism software version 8.0.1 (GraphPad Software Inc., USA).

| Quantitative real-time polymerase chain reaction
The quantitative real-time polymerase chain reaction (qRT-PCR) was

| KEGG pathway analysis of differentially correlated genes
The powerful, comprehensive, online enrichment tool (Enrichr [39][40][41] was utilized to use the Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis 42 for the differentially correlated genes with LINC01116 (Pearson correlation coefficient method).

| Statistical analysis
The results are presented as means ± standard deviation (SD 3 | RESULTS

| LINC01116 is highly expressed in ER+ samples
Firstly, differentially expressed genes in ER+ and ERÀ samples were investigated by analyzing data from the GSE45827 dataset ( Figure 1A). Then we applied a filter to recognize the top differentially expressed lncRNAs ( Figure 1B), and LINC01116 was the most significant lncRNA with a high expression level in the ER+ samples compared to the ERÀ ones (Log fold change (FC) ≈ 2.7) ( Table 2 and Figure 1C). Furthermore, qRT-PCR was performed on tumor and margin tumor breast tissues (40 pairs), and results showed a 10.3-fold increase in LINC01116 expression in ER+ compared with ERÀ tissues ( Figure 1D). Additionally, to examine the power of LINC01116 in distinguishing ER+ from ERÀ in breast cancer samples, the ROC curve was used to evaluate the sensitivity and specificity of LINC01116. The area under the curve of LINC01116 was calculated at about 0.94 (p-value <.0001) for GSE45827 samples ( Figure 1E) and 0.7 (p-value = .015) for breast cancer tissues ( Figure 1F), which is deemed as a potential biomarker in ER+ breast cancer. In addition, using the GSE46924 microarray dataset, the impact of 17β-Estradiol treatment on Surprisingly, data showed the expression of LINC01116 significantly downregulated in MCF7 Tamoxifen-resistant cells compared to Tamoxifen-sensitive cells ( Figure 1H).

| The LINC01116 expression pattern in breast cancer tissues
We analyzed the expression of LINC01116 compared to the normal samples using the GSE45827 microarray dataset. There was no sig-

| The overexpression of LINC01116 induces TGF-β signaling
To determine the pathways in which LINC01116 is involvedin ERÀ samples, we collected negatively and positively correlated genes with LINC01116 using GSE45827 microarray data analysis ( p-value <.05).
Enrichr online tool (using the KEGG pathway analysis) revealed that positively correlated genes were mainly involved in the TGF-β signaling pathway, and negatively correlated genes were primarily involved in the cell cycle ( Figure 4D).

| DISCUSSION
Breast cancer is the most frequently diagnosed cancer and one of the top causes of cancer death worldwide. 45 Early diagnosis of breast T A B L E 3 Genes that are negatively correlated with LINC01116 in ER+ samples and positively correlated in ERÀ samples (the sum of the absolute value of the correlations >.7) (p-value<.02).  Figure 1B) 81 Estrogen signaling is one of the most crucial signaling pathways in breast cancer, which mediates cell proliferation and apoptosis and suppresses EMT. [13][14][15] ER is a desired target for endocrine therapy and confers a better prognosis in breast cancer patients. 51 Our results show that the expression of LINC01116 is upregulated in 17β-  19 In the present study, we show that the overexpression of LINC01116 increases the TGF-β signaling in MDA-MB-231 cells and upregulates the SNAI1 expression, which acts as a marker for EMT. 14 In addition, apart from the positive correlation between LINC01116 and the aforementioned genes involved drug resistance in ERÀ samples (Table 3), there is a positive correlation between LINC01116 and Activin A Receptor Type 1B (ACVR1B, also known as ALK4), which is related to the TGF-β superfamily and promotes invasion, EMT, and metastasis in breast cancer. 59