Detection of Long Non-Coding RNA in Archival Tissue: Correlation with Polycomb Protein Expression in Primary and Metastatic Breast Carcinoma

A major function of long non-coding RNAs (lncRNAs) is regulating gene expression through changes in chromatin state. Experimental evidence suggests that in cancer, they can influence Polycomb Repressive Complexes (PRC) to retarget to an occupancy pattern resembling that of the embryonic state. We have previously demonstrated that the expression level of lncRNA in the HOX locus, including HOTAIR, is a predictor of breast cancer metastasis. In this current project, RNA in situ hybridization of probes to three different lncRNAs (HOTAIR, ncHoxA1, and ncHoxD4), as well a immunohistochemical staining of EZH2, is undertaken in formalin-fixed paraffin-embedded breast cancer tissues in a high throughput tissue microarray format to correlate expression with clinicopathologic features. Though overall EZH2 and HOTAIR expression levels were highly correlated, the subset of cases with strong HOTAIR expression correlated with ER and PR positivity, while the subset of cases with strong EZH2 expression correlated with an increased proliferation rate, ER and PR negativity, HER2 underexpression, and triple negativity. Co-expression of HOTAIR and EZH2 trended with a worse outcome. In matched primary and metastatic cancers, both HOTAIR and EZH2 had increased expression in the metastatic carcinomas. This is the first study to show that RNA in situ hybridization of formalin fixed paraffin-embedded clinical material can be used to measure levels of long non-coding RNAs. This approach offers a method to make observations on lncRNAs that may influence the cancer epigenome in a tissue-based technique.     

Identification of key lncRNAs in the carcinogenesis and progression of colon adenocarcinoma by co-expression network analysis

Colon adenocarcinoma (COAD) is one of the most common cancers, and its carcinogenesis and progression is influenced by multiple long non-coding RNAs (lncRNA), especially through the miRNA sponge effect. In this study, more than 4000 lncRNAs were re-annotated from the microarray datasets through probe sequence mapping to obtain reliable lncRNA expression profiles. As a systems biology method for describing the correlation patterns among genes across microarray samples, weighted gene co-expression network analysis was conducted to identify lncRNA modules associated with the five stepwise stages from normal colonic samples to COAD (n = 94). In the most relevant module (R² = −0.78, P = 4E-20), four hub lncRNAs were identified (CTD-2396E7.11, PCGF5, RP11-33O4.1, and RP11-164P12.5). Then, these four hub lncRNAs were validated using two other independent datasets including GSE20916 (n = 145) and GSE39582 (n = 552). The results indicated that all hub lncRNAs were significantly negatively correlated with the three-stage colonic carcinogenesis, as well as TNM stages in COAD (one-way analysis of variance P < 0.05). Kaplan-Meier survival curve showed that patients with higher expression of each hub lncRNA had a significantly higher overall survival rate and lower relapse risk (log-rank P < 0.05). In conclusion, through co-expression analysis, we identified and validated four key lncRNAs in association with the carcinogenesis and progression of COAD, and these lncRNAs might have important clinical implications for improving the risk stratification, therapeutic decision and prognosis prediction in COAD patients.     

Expression profile of lncRNAs and miRNAs in esophageal cancer: Implications in diagnosis,prognosis, and therapeutic response

Esophageal cancer is the seventh most common cancer worldwide. Although a number of environmental and lifestyle-related risk factors have been identified for this kind of cancer, the exact molecular mechanisms of tumor evolution have not been clarified yet. Long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) as important regulators of gene expression and chromatin configuration have essential roles in the pathogenesis of esophageal cancer. They have been shown to alter the function of cancer-related signaling pathways such as phosphoinositide 3-kinase/protein kinase B and Wnt pathway, thus they might modulate the response of patients to pathway-targeted therapies. Moreover, a number of lncRNAs, such as AFAP1-AS1, UCA1, HOTAIR, LOC285194, and TUSC7, are involved in conferring chemoresistant/radioresistant in esophageal cancer cells. A complex network of interaction exists between lncRNAs and miRNAs in the context of esophageal cancer. Finally, various panels of lncRNAs and miRNAs have been introduced that can predict the survival of esophageal cancer patients. In this review article, we summarize the recent findings regarding the role of miRNAs and lncRNAs in the pathogenesis of esophageal cancer with the special focus on their regulatory roles on signaling pathways, their potential as diagnostic/prognostic markers, and their relevance with therapeutic response.     

LncRNAs as potential diagnostic and prognostic biomarkers in gastric cancer: A novel approach to personalized medicine

Gastric cancer is the third leading cause of cancer death with 5-year survival rate of about 30–35%. Since early detection is associated with decreased mortality, identification of novel biomarkers for early diagnosis and proper management of patients with the best response to therapy is urgently needed. Long noncoding RNAs (lncRNAs) due to their high specificity, easy accessibility in a noninvasive manner, as well as their aberrant expression under different pathological and physiological conditions, have received a great attention as potential diagnostic, prognostic, or predictive biomarkers. They may also serve as targets for treating gastric cancer. In this review, we highlighted the role of lncRNAs as tumor suppressors or oncogenes that make them potential biomarkers for the diagnosis and prognosis of gastric cancer. Relatively, lncRNAs such as H19, HOTAIR, UCA1, PVT1, tissue differentiation-inducing nonprotein coding, and LINC00152 could be potential diagnostic and prognostic markers in patients with gastric cancer. Also, the impact of lncRNAs such as ecCEBPA, MLK7-AS1, TUG1, HOXA11-AS, GAPLINC, LEIGC, multidrug resistance-related and upregulated lncRNA, PVT1 on gastric cancer epigenetic and drug resistance as well as their potential as therapeutic targets for personalized medicine was discussed.     

A prognostic 11 long noncoding RNA expression signature for breast invasive carcinoma

Breast cancer, the most common cancer in women worldwide, is associated with high mortality. The long non-coding RNAs (lncRNAs) with a little capacity of coding proteins is playing an increasingly important role in the cancer paradigm. Accumulating evidences demonstrate that lncRNAs have crucial connections with breast cancer prognosis while the studies of lncRNAs in breast cancer are still in its primary stage. In this study, we collected 1052 clinical patient samples, a comparatively large sample size, including 13 159 lncRNA expression profiles of breast invasive carcinoma (BRCA) from The Cancer Genome Atlas database to identify prognosis-related lncRNAs. We randomly separated all of these clinical patient samples into training and testing sets. In the training set, we performed univariable Cox regression analysis for primary screening and played the model for Robust likelihood-based survival for 1000 times. Then 11 lncRNAs with a frequency more than 600 were selected for prediction of the prognosis of BRCA. Using the analysis of multivariate Cox regression, we established a signature risk-score formula for 11 lncRNA to identify the relationship between lncRNA signatures and overall survival. The 11 lncRNA signature was validated both in the testing and the complete set and could effectively classify the high-/low-risk group with different OS. We also verified our results in different stages. Moreover, we analyzed the connection between the 11 lncRNAs and the genes of ESR1, PGR, and Her2, of which protein products (ESR, PGR, and HER2) were used to classify the breast cancer subtypes widely. The results indicated correlations between 11 lncRNAs and the gene of PGR and ESR1. Thus, a prognostic model for 11 lncRNA expression was developed to classify the BRAC clinical patient samples, providing new avenues in understanding the potential therapeutic methods of breast cancer.     

Proteomics-based identification of HSP60 as a tumor-associated antigen in early stage breast cancer and ductal carcinoma in situ

The detection of autoantibodies in cancer patients has been shown to constitute an excellent tool for early diagnosis. Because breast cancer still lacks early diagnostic markers, we investigated novel tumor-associated antigens and related autoantibodies in sera from patients with early stage breast cancer compared to autoimmune disease, other cancers, and healthy volunteers, using a proteomics-based approach. Among the 26 protein antigens specifically recognized by early stage breast cancer sera, we focused on Heat Shock Protein 60 (HSP60). Using ELISA, we investigated the frequency of autoantibodies directed against this protein in the sera of 240 individuals, comprising patients with either ductal carcinoma in situ (DCIS) ( n = 49) or early stage breast cancer ( n = 58), other cancers ( n = 20), autoimmune disease ( n = 20), and healthy subjects ( n = 93). Autoantibodies directed against HSP60 were present in 16/49 (31%) early stage breast cancer and 18/58 (32.6%) DCIS patients, compared to 4/93 (4.3%) healthy subjects. In particular, autoantibodies were present in 11/23 patients (47.8%) with high-grade DCIS, compared to 5/26 (19.2%) with low-grade DCIS. HSP60 mRNA levels were significantly higher in primary breast cancer compared to healthy breast tissues. Using immunohistochemistry, we found that HSP60 expression gradually increases from normal through DCIS to invasive tissues. Our results indicate that HSP60 autoantibodies may be of interest in terms of clinical utility for the early diagnosis of breast cancer and more particularly in DCIS. Moreover, HSP60 overexpression during the first steps of breast carcinogenesis may be functionally correlated to tumor growth and/or progression.     

Molecular classification of breast carcinoma in situ

Pleomorphic variant of invasive lobular carcinoma (PILC) is an aggressive variant of invasive lobular carcinoma (ILC). Its in situ counterpart, pleomorphic lobular carcinoma in situ (PLCIS) is a recently described entity. Morphologically it has the typical architectural pattern of LCIS, but the neoplastic cells resemble intermediate grade DCIS. Molecular signatures that distinguish PLCIS from DCIS and LCIS would provide additional tools to aid in the histopathologic classification of PLCIS as a lesion distinct from LCIS and DCIS. CIS lesions, obtained from a study cohort of 38 breast cancer patients, were divided into 18 DCIS, 14 PLCIS and 6 LCIS. DNA from microdissected archival tissue was interrogated for loss or gain of 112 breast-cancer-specific genes using the Multiplex Ligation-dependent Probe Amplification Assay (MLPA). Classification Regression Tree (CART) analysis was employed to develop a gene-based molecular classification to distinguish or separate out PLCIS from DCIS and LCIS. Molecular classification via CART, based on gene copy number, agreed with histopathology in 34/38 CIS cases. Loss of CASP1 was predictive of LCIS (n=4) with one misclassified PLCIS. Gain of RELA predicted only the LCIS classification (n=2 cases). STK15 and TNFRSF1B were predictive only for DCIS with no misclassifications. Gain of EHF and TNFRSF1B and loss of NCOA3 were predictive of PLCIS, but not without misclassification. Molecular reclassification by CART was accomplished in 4 CIS cases: 1 PLCIS was reclassified as LCIS, 1 LCIS reclassified as PLCIS, and 2 DCIS cases as PLCIS. This study provides additional rationale for molecular modeling strategies in the evaluation of CIS lesions. This diagnostic aid may serve to minimize misclassification between PLCIS and DCIS, and PLCIS and LCIS, aiding to increase accuracy in the differential diagnosis of CIS lesions.     

Long non-coding RNA <Emphasis Type="Italic">HOTAIR</Emphasis> regulates proliferation and invasion via activating Notch signalling pathway in retinoblastoma

Retinoblastoma is the most frequently occurring tumour in the eyes in early childhood. Novel targets that are important for the diagnosis or treatment of retinoblastoma could be valuable in increasing the survival rate of patients affected by this disease. Long non-coding RNAs (lncRNAs) are a recently discovered type of RNAs with no protein-coding function; yet it has become increasingly clear that lncRNAs are responsible for important gene regulatory functions in various diseases. In this study, the expression of lncRNA HOTAIR was measured by qRT-PCR, and HOTAIR expression was found to be significantly upregulated in human retinoblastomas tissues as compared with that in paracancerous tissues. Knockdown of HOTAIR restricted the proliferation and invasion of the more invasive retinoblastoma Y79 cells, and led to G0/G1 arrest, possibly through inhibiting phospho-RB1, RB1 and CCNE. Furthermore, we found that the Notch signalling pathway was activated abnormally in retinoblastoma cell lines, while knockdown of HOTAIR attenuated the endogenous Notch signalling pathway in vitro and in vivo. In addition, knockdown of HOTAIR could inhibit the tumour progression in a xenograft model of retinoblastoma. In summary, our findings indicate that HOTAIR may play important roles in retinoblastoma progression via Notch pathway. HOTAIR has the potential to enhance the development of novel targeted diagnostic and therapeutic approaches for retinoblastoma.     

Long noncoding RNAs expression in gastric cancer

Long noncoding RNAs (lncRNAs) have been involved in the pathogenesis of several human cancers including gastric cancer. In the current study, we selected five lncRNAs namely NEAT1, TUG1, PANDA, UCA1, and GHET1 to assess their expressions in gastric cancer samples compared with adjacent noncancerous tissues (ANCTs) from the same patients. Some previous reports have shown contribution of these lncRNAs in gastric cancer. However, we aimed to explore their associations with patients’ clinicopathological data and their potential as diagnostic biomarkers. Significant associations were found between site of primary tumor and relative expression of all lncRNAs in cancer samples compared with ANCTs. Besides, GHET1 relative expression was associated with lymph node status. The diagnostic power of GHET1 was higher from other lncRNAs. Combination of GHET1, TUG1, UCA1, and PANDA increased the diagnostic power and significance (AUC = 0.8; P < 0.0001). The current study supports participation of lncRNAs in the pathogenesis of gastric cancer and highlights their potential as diagnostic biomarkers.     

Microarray analysis of long-noncoding RNAs and mRNA expression profiles in human steroid-induced avascular necrosis of the femoral head

This study performed the first microarray analysis of long-noncoding RNA (lncRNA) and mRNA expression profiles in human steroid-induced avascular necrosis of the femoral head (SAVNFH). Expression levels of lncRNAs and mRNAs in three human SAVNFH samples and three human femoral head fracture samples (controls) were detected using third-generation lncRNA microarrays (KangChen Biotech, Shanghai, China). The fold change, false discovery rate, and P value were utilized to filter genes with significant differential expression in the SAVNFH samples compared with the control samples. In total, there were 1179 upregulated and 3214 downregulated lncRNAs (P2. zerofold, P < 0.05). Meanwhile, 1092 upregulated and 565 downregulated mRNAs were found in the SAVNFH samples compared with the control samples. Then, quantitative real-time polymerase chain reaction was used to confirm the previous microarray results using 8 and 20 selected dysregulated lncRNAs and mRNAs, respectively, and the results generally confirmed the microarray findings. Finally, we used Gene Ontology (GO) and pathway analysis to investigate the functions of the altered mRNAs and their associated GO terms and biological pathways. The Immune system process term (GO:0002376) was the most significantly upregulated GO term, and the Regulation of blood coagulation term (GO:0030193) was the most significantly downregulated GO term in the biological process category for the SAVNFH samples. “Hematopoietic cell lineage - Homo sapiens (human) (Pathway ID: hsa04640)” and “Complement and coagulation cascades - Homo sapiens (human) (Pathway ID: hsa04610)” were the most significantly up- and downregulated pathways in the SAVNFH samples compared with the controls. In conclusion, the differential expression of lncRNAs and mRNAs may be correlated with the pathogenesis of SAVNFH, and these significantly dysregulated lncRNAs and mRNAs may function through networks or participate in several specific biological processes. Further research is needed to understand their exact functions and mechanisms in SAVNFH.     

Analysis of competing endogenous RNA network identifies a poorly differentiated cancer-specific RNA signature for hepatocellular carcinoma

Plenty of evidence has suggested that long noncoding RNAs (lncRNAs) play a vital role in competing endogenous RNA (ceRNA) networks. Poorly differentiated hepatocellular carcinoma (PDHCC) is a malignant phenotype. This paper aimed to explore the effect and the underlying regulatory mechanism of lncRNAs on PDHCC as a kind of ceRNA. Additionally, prognosis prediction was assessed. A total of 943 messenger RNAs (mRNAs), 86 miRNAs, and 468 lncRNAs that were differentially expressed between 137 PDHCCs and 235 well-differentiated HCCs were identified. Thereafter, a ceRNA network related to the dysregulated lncRNAs was established according to bioinformatic analysis and included 29 lncRNAs, 9 miRNAs, and 96 mRNAs. RNA-related overall survival (OS) curves were determined using the Kaplan-Meier method. The lncRNA ARHGEF7-AS2 was markedly correlated with OS in HCC (P = .041). Moreover, Cox regression analysis revealed that patients with low ARHGEF7-AS2 expression were associated with notably shorter survival time (P = .038). In addition, the area under the curve values of the lncRNA signature for 1-, 3-, and 5-year survival were 0.806, 0.741, and 0.701, respectively. Furthermore, a lncRNA nomogram was established, and the C-index of the internal validation was 0.717. In vitro experiments were performed to demonstrate that silencing ARHGEF7-AS2 expression significantly promoted HCC cell proliferation and migration. Taken together, our findings shed more light on the ceRNA network related to lncRNAs in PDHCC, and ARHGEF7-AS2 may be used as an independent biomarker to predict the prognosis of HCC.     

Long non-coding RNAs and chromatin modifiers

The emergence of long non-coding RNAs (lncRNAs) has shaken up our conception of gene expression regulation, as lncRNAs take prominent positions as components of cellular networks. Several cellular processes involve lncRNAs, and a significant number of them have been shown to function in cooperation with chromatin modifying enzymes to promote epigenetic activation or silencing of gene expression. Different model mechanisms have been proposed to explain how lncRNAs achieve regulation of gene expression by interacting with the epigenetic machinery. Here we describe these models in light of the current knowledge of lncRNAs, such as Xist and HOTAIR, and discuss recent literature on the role of the three-dimensional structure of the genome in the mechanism of action of lncRNAs and chromatin modifiers.