Low expression of LINC00982 and PRDM16 is associated with altered gene expression, damaged pathways and poor survival in lung adenocarcinoma
- Authors:
- Published online on: August 14, 2018 https://doi.org/10.3892/or.2018.6645
- Pages: 2698-2709
Abstract
Introduction
Lung cancer is one of the most common malignancies in humans and is the main cause of cancer-related deaths (1). Non-small cell lung cancer (NSCLC), accounts for ~80% of all lung cancer cases and can be divided into different histological types, including adenocarcinoma, squamous cell carcinoma and large cell carcinoma, of which lung adenocarcinoma (LUAD) is the most common subtype (2). Although significant progress has been made in regards to surgery, chemotherapy, radiation therapy and molecular-targeted therapy in the past few years, the overall 5-year survival rate of lung cancer patients is still only ~15% (3). This is due to the lack of effective early diagnostic methods and the limited efficacy of current therapies. Thus, the importance of discovering simple and effective biomarkers is not only reflected in early diagnosis, but also in improving the prognosis of lung cancer patients.
Compared with the study of biomarkers of protein-coding genes, human studies on non-coding RNA are relatively few. However, the human genome contains more than 98% non-protein coding sequences, with the vast majority transcribed into long non-coding RNAs (lncRNAs) that are >200 bases in length. In recent years, lncRNAs have been reported to serve as diagnostic and prognostic markers in cancer (4–8). In lung cancer, lncRNAs, such as MALAT-1 (9) and HOTAIR (10), have been associated with cancer development. We also previously identified a series of differentially expressed lncRNAs in 12 pairs of NSCLC tumors and adjacent tumor tissues (8), and levels of long intergenic non-protein coding RNA 982 (LINC00982) and PR domain containing 16 (PRDM16) were lower in NSCLC tumors than levels in adjacent non-tumor tissues (Fig. 1A and B). In the present study, we explored the expression and prognostic value of LINC00982 in lung cancer.
LINC00982, located on chromosome 1p36.32, has 2 transcripts and has been reported to be a tumor suppressor in gastric cancer (11,12). However, no studies are available regarding the biological function of LINC00982 in lung cancer. In the present study, we observed that LINC00982 and PRDM16 share the same enhancer, ACTRT2 (enhancer ID: GH01F003274). Dysfunction of PRDM16 has been found in many diseases. In astrocytoma patients, poor prognosis can be predicted by the hypomethylation status of the PRDM16 promoter (13). Some recent studies have reported that PRDM16 plays a significant role in the development of cancer such as prostate (14), colorectal (15,16) and myeloid cancers (17,18). As in lung cancer, the PRDM16 promoter has been reported to be methylated and upregulated PRDM16 suppressed lung cancer cell growth (19), but the value of this gene for diagnosis and prognosis has not been fully explored.
Herein, we first analyzed the independent effect of LINC00982 and PRDM16 expression on the clinical features and survival status of LUAD patients and further explored the combined effect of LINC00982 and PRDM16 expression on global gene expression, potentially affected pathways and biological functions and the prognosis of LUAD patients.
Materials and methods
Data sources
LUAD transcriptome and clinical data were downloaded from The Cancer Genome Atlas (TCGA, http://tcga-data.nci.nih.gov/) and the cBioPortal (http://www.cbioportal.org/) database in May 2016 (20,21). LUAD DNA promoter methylation data were collected from MethHC (http://methhc.mbc.nctu.edu.tw/php/search.php?opt=gene). In total, we downloaded TCGA level 3 data from 515 LUAD patients and 59 controls. All samples had RNA sequencing on the Illumina HiSeq 2000 version 2 platform and were normalized by the ‘RNA-Seq by Expectation-Maximization’ (RSEM) method. Copy number data on LINC00982 (also called FLJ42875), PRDM16 and epidermal growth factor receptor (EGFR) were also downloaded from cBioPortal database. We divided the LUAD patients into groups according to the median expression of LINC00982 (3.89) and PRDM16 (7.42). Patients in the high-PRDM16 group (≥7.42) and high-LINC00982 group (≥3.89) were designated as the ‘both-high’ group, and those with a low expression of PRDM16 (<7.42) and LINC00982 (<3.89) were considered as the ‘both-low’ group. In addition, we analyzed the expression profiles of PRDM16 and LINC00982 in lung squamous cell carcinoma (LUSC). Gene expression and clinical data on LUSC (including 501 patients and 51 controls) were also downloaded from TCGA and analyzed in the same way as the LUAD data.
Differential expression analysis
A paired sample t-test was used to analyze the differential gene expression and DNA methylation of LINC00982 and PRDM16 between the 59 paired tumor tissue and adjacent normal tissues. In order to illustrate the association between copy number variation and gene expression of LINC00982 and PRDM16, we matched LUAD patient IDs and then divided these patients into high- and low-expression groups according to the median expression of LINC00982 and PRDM16. The Mann-Whitney U statistic was used to calculate the differences between the two groups. We extracted expression information on EGFR and used it as a reference. Spearman's correlation analysis was used to explore the association of LINC00982 and PRDM16 expression. A P-value <0.05 was considered to indicate a statistically significant difference.
Differentially expressed genes in the ‘both-high’ and ‘both-low’ groups were analyzed using R v 3.3.3 (https://www.r-project.org/) and the bioconductor ibrary (https://bioconductor.org/packages). The empirical Bayes algorithm (function ‘eBayes’) in the limma package (22) was used to detect differentially expressed genes between the ‘both-high’ and ‘both-low’ groups and controls. We converted all gene expression values to z-scores and used heatmaps in the ‘pheatmap’ package(https://CRAN.R-project.org/package=pheatmap) to show the results. Significantly differentially expressed genes (upregulated or downregulated) were considered as an absolute value of the logarithmic transformed fold-change (log2 (FC)) ≥1 and a false discovery rate (FDR)-adjusted P-value ≤0.05. A Venn diagram was used to compare the upregulated and downregulated genes and affected pathways between the ‘both-high’ and ‘both-low’ groups, respectively.
Pathway enrichment analysis
We performed KEGG pathway enrichment analysis using differentially expressed genes in the ‘both-high’ and ‘both-low’ groups. The following formula was used to conduct the enrichment analysis:
P(X=k)=1-Cmk·CN-mn-kCNnWhere N is the number of all genes in the dataset, m represents the number of differentially expressed genes in the dataset, n is the number of all genes in the enriched KEGG pathway and k is the number of differentially expressed genes in the KEGG pathway. An FDR P-value ≤0.05 was considered significantly enriched. The enrichment percentage in each subsystem was calculated as the number of differentially expressed genes divided by the number of all genes.
Gene co-expression with PRDM16 and LINC00982 was defined by the Spearman's correlation coefficient between each gene and PRDM16 and LINC00982 expression. Genes with an absolute Spearman's correlation coefficient >0.3 were considered to be co-expressed with PRDM16 and LINC00982. In LUAD, the Spearman's correlation coefficient information was downloaded from cBioPortal (http://www.cbioportal.org/index.do). Co-expressed genes were uploaded into the Ingenuity Pathway Analysis software (Qiagen Redwood City Inc., Redwood City, CA, USA) to compare enriched pathways.
Clinicopathological and survival analysis
For clinical data analysis, categorical variables (i.e., sex, race, residual tumors, primary site, stage and smoking history) were given as numbers and percentages. Continuous variables (e.g., age) are presented as the mean ± standard deviation (SD). Student's t-tests were used to compare the means for continuous variables in two groups, and χ2 tests were used to compare the prevalence of categorical variables. Kaplan-Meier survival curves were constructed to compare differences in overall survival and disease-free survival between the high-LINC00982 and low-LINC00982 groups and the high-PRDM16 and low-PRDM16 groups, as well as the ‘both-low’ and ‘both-high’ groups. The log-rank test was used to assess differences in survival between groups using the ‘survival’ package in R. Furthermore, we analyzed the association of LINC00982 and PRDM16 expression on overall survival and disease-free survival stratified by tumor stage. The effect of LINC00982 and PRDM16 expression and other clinicopathological factors (sex, age, residual tumors, primary site, stage and smoking status) on overall survival and disease-free survival was analyzed by using univariate Cox regression models. A multivariate Cox regression model was used to compare the independent effect of LINC00982 and PRDM16 expression on overall survival and disease-free survival and adjusted for corresponding covariates (smoking history, primary site, residual tumors and stage).
Cell lines
Human LUAD cell lines A549, H1299 and H1975 and a normal lung epithelium cell line (BEAS-2B) were obtained from the Chinese Academy of Sciences Committee on Type Culture Collection Cell Bank (Shanghai, China). All cell lines were cultured in Dulbecco's modified Eagle's medium (DMEM; Thermo Fisher Scientific, Inc., Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS; Sigma-Aldrich; Merck KGaA, Darmstadt, Germany), 25 U/ml penicillin and 25 µg/ml streptomycin at 37°C in 5% CO2.
Quantitative real-time PCR (RT-qPCR) analysis
Total RNA was extracted from cell lines samples with Invitrogen™ TRIzol reagent (Thermo Fisher Scientific, Inc.) according to the manufacturer's instructions. Reverse-transcription PCR was performed with the Prime-Script RT Reagent kit (Tiangen Biotech, Beijing, China). Gene expression levels were determined by RT-qPCR and normalized against an endogenous control (β-actin) using SYBR Premix Ex Taq (ABI; Thermo Fisher Scientific, Inc.). Data were analyzed using the ΔΔCt approach and expressed as the target gene/β-actin ratio [2−ΔCt (target gene - β−actin)]. The primers of the longer transcription of LINC00982 (NR_015440.1, termed LINC00982-1) were as follows: Forward: 5′-CCGGCCCTCTTAGCTTCAAA-3′ and reverse, 5′-GTGGAAAAGAAACCCACCGC-3′. The primers of the shorter transcription of LINC00982 (NR_024371.1, termed LINC00982-2) were as follows: Forward: 5′-GCTTCCCTTCCGTTCACTCA-3′ and reverse: 5′-GGCTGAGTCTTTCTGGACCC-3′. Primers for PRDM16 were as follows: forward: 5′-GTTCTGCGTGGATGCAAATCA-3′ and reverse: 5′-GGTGAGGTTCTGGTCATCGC-3′. Data analysis was conducted using GraphPad Prism 6 (GraphPad Software, Inc., La Jolla, CA, USA). Data were analyzed using one-way analysis of variance (ANOVA) followed by the Least Significant Difference (LSD) method.
Results
LINC00982 and PRDM16 expression profiles in NSCLC
The expression of LINC00982 and PRDM16 in 59 human LUAD tissues was significantly decreased compared to the paired adjacent normal lung tissues (Fig. 2A and B). In addition, the same trend was observed in the LUSC tissues (data not shown). Furthermore, we stratified LUAD patients by the median expression of LINC00982 and PRDM16 and found that the low-LINC00982 (<3.89) and low-PRDM16 (<7.42) groups were decreased in tumors compared to adjacent normal lung tissues, whereas the high-LINC00982 (≥3.89) and high-PRDM16 (≥7.42) groups had no significant changes (data not shown). Analysis of copy number variations revealed that the copy number of the two genes was also lower in patients with low gene expression (Fig. 2C and D). EGFR expression was positively associated with gene copy number (Fig. 2C and D) as had been previously observed (23). In addition, the low level of expression was consistent with the hypermethylation of the promoter region of these two genes in tumor samples compared with adjacent tissues (Fig. 2E and F). We analyzed the Spearman's correlation between LINC00982 and PRDM16 expression and found that they were positively correlated (Fig. 2G).
We used Kaplan-Meier curves to explore the effect of LINC00982 and PRDM16 expression on LUAD patient survival status. The results indicated that patients with low expression of LINC00982 or PRDM16 showed poor overall survival and disease-free survival than the high-expression corresponding groups, although the effect of LINC00982 on disease-free survival did not reach the significance threshold (Fig. 3). We also analyzed the effect of these two genes on survival in LUSC patients; however, neither affected survival status (data not shown). Therefore, we focused on the influence of LINC00982 and PRDM16 on LUAD in the subsequent analyses. In order to study the combined effect of LINC00982 and PRDM16 on patient survival, we combined the low-LINC00982 group and low-PRDM16 group into the ‘both-low’ group, as well as combining the high-LINC00982 group and high-PRDM16 group into the ‘both-high’ group. The Kaplan-Meier curves revealed that compared with the ‘both-low’ group, patients with high expression of these two genes presented with significantly prolonged overall survival (HR=0.55, P<0.001) and disease-free survival (HR=0.72, P=0.042) (Fig. 4). We also observed a consistent trend in patients with early-stage disease (I/II) (data not shown).
Gene expression and pathway analysis of LINC00982 and PRDM16 in LUAD
In Fig. 5 the gene expression profiles and KEGG pathway enrichment results in LUAD patients are displayed. Genes with an expression value of zero were removed. In total, we assessed the gene expression of 19,606 genes in 515 LUAD patients and 59 controls (data not shown). The global gene expression in the high-LINC00982 group and low-LINC00982 group revealed a relatively large difference, as well as the high-PRDM16 and low-PRDM16 patients. Other characteristics (sex, age, race, smoking status and stage) were approximately randomly distributed, indicating that these variables contributed less to gene expression changes. A Venn diagram of differentially expressed genes in the ‘both-high’ and ‘both-low’ groups compared with adjacent normal tissues is shown in Fig. 5B and C. In total, 3,951 and 5,103 differentially expressed genes were observed in the ‘both-high’ group (data not shown) and the ‘both-low’ group (data not shown), respectively. Furthermore, there were 2,125 common downregulated and 1,407 common upregulated genes between the ‘both-high’ and ‘both-low’ groups (Fig. 5B and C). From the KEGG enrichment results, there were 48 significantly enriched pathways in the ‘both-high’ group (data not shown) and 78 significantly enriched pathways in the ‘both-low’ group (data not shown). There were 41 commonly and 44 differentially enriched KEGG pathways between the two groups (Fig. 5D). The enrichment profiles indicated that most of the pathways resulted in serious damage in the ‘both-low’ group as compared to the ‘both high’-group (Fig. 5E and F). We also analyzed the biological pathway enrichment of the genes co-expressed with LINC00982 and PRDM16 using Ingenuity Pathway Analysis (Fig. 6). There were several common pathways associated with co-expression of LINC00982 and PRDM16, such as cyclins and cell cycle regulation, NSCLC signaling and ERK/MAPK signaling.
LINC00982 and PRDM16 expression, clinicopathological variables and patient survival
Table I depicts the 515 LUAD patient characteristics in the high- and low-expressed LINC00982 and PRDM16 groups. We observed that females exhibited higher expression of LINC00982 (P=0.043) and PRDM16 (P=0.002) compared with males. There were no differences in age, race, residual tumor or primary site between the high-LINC00982 and low-LINC00982 groups, or between the high-PRDM16 and low-PRDM16 groups. Furthermore, patients in the low-LINC00982 group showed higher smoking frequency (P=0.002) and more serious disease stage (P=0.009) compared with the high-LINC00982 group. We also observed more patients who currently smoke in the low-PRDM16 group compared with the high-PRDM16 group (P<0.001). The results for smoking status, stage and gene expression of LINC00982 and PRDM16 are not shown.
We used univariate Cox proportional hazards models to analyze the effect of LINC00982 and PRDM16 expression, as well as other clinicopathological variables, on patient survival status (Table II). We found that high expression of LINC00982 in the continuous and categorical models all showed prolonged overall survival and disease-free survival (all P<0.05). Furthermore, the expression of PRDM16 in the continuous and categorical models also associated with survival (all P<0.05). Other clinicopathological variables such as residual tumors and stage also showed significant association with survival status. Therefore, we used multivariate Cox proportional hazards models adjusting for covariates including residual tumor and stage to verify the effect of LINC00982 and PRDM16 expression on patient survival status (Table III). The results indicated that the LINC00982 and PRDM16 low-expression groups were both associated with decreased overall survival (all P<0.05). However, the expression of these two genes did not affect disease-free survival. The above analysis showed that LINC00982 and PRDM16 independently affected overall survival.
 | Table II.Association of LINC00982 and PRDM16 expression, clinicopathological characteristics and survival status. |
RT-qPCR validation
We explored LINC00982-1, LINC00982-2 and PRDM16 expression in LUAD cell lines (A549, H1299 and H1975) and a normal lung epithelium cell line (BEAS-2B) by RT-qPCR (Fig. 7). We found that LINC00982-1, LINC00982-2, the two transcripts of LINC00982 and PRDM16 expression were significantly decreased in LUAD cell lines (A549, H1299 and H1975) compared to normal cell lines (BEAS-2B).
Discussion
Our results revealed that the combined effect of LINC00982 and PRDM16 expression was a risk factor that affected global gene expression, altered cancer-related pathways and biological functions, and decreased patient survival in LUAD. Additionally, our experimental results revealed that LINC00982 and PRDM16 transcripts were downregulated in LUAD cell lines compared with the normal BEAS-2B cell line.
LUAD is a complex disease that is associated with altered gene expression, DNA methylation, protein modification and non-coding RNA dysfunction (24). In particular, lncRNAs play a significant role in cellular homeostasis and tumorigenesis and often serve as markers of prognosis and diagnostic targets for therapy (25). A recent study suggested that CCAT2, a LUAD-specific lncRNA, promoted invasion and metastasis of LUAD (26). In a previous study, Fei et al reported that LINC00982 is dysregulated in gastric cancer patients, and the high expression of LINC00982 was related to better overall survival (11). LINC00982 is located about 0.5 kb telomeric at the 5′ untranslated region of PRDM16, which suggests that these transcripts have the same enhancer, ACTRT2 (27). The PRDM16 gene is not only associated with myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) (28), but also solid tumors such as lung cancer. Some studies have indicated that PRDM16 expression is downregulated in lung cancer cells due to the methylation of its promoter (19), which was consistent with our results.
In the present study, compared with adjacent normal tissues, LINC00982 and PRDM16 expression were significantly decreased in tumor samples. Considering the increased methylation level of the promoter region and the decreased copy number in LUAD patients, we speculated that the dysregulation of LINC00982 and PRDM16 may be caused by DNA methylation and gene copy number disorders. Furthermore, we used three survival analysis models to show that high expression of LINC00982 and PRDM16 was associated with higher patient survival, especially overall survival. In addition, patients with high expression of LINC00982 and PRDM16 demonstrated better overall survival and disease-free survival than patients with low expression of these two genes. Notably, these associations were consistent in patients with early tumor stages (stage I and II), combined with the evidence that high expression of LINC00982 and PRDM16 were related to low TNM stage, which may aid the early diagnosis of LUAD and improve the prognosis of affected patients, especially with a combination of changes in their expression.
Through pathway enrichment analysis, we found that PRDM16-associated genes were enriched in many canonical pathways, which are consistent with LINC00982-associated gene enriched pathways. However, the extents of the impact are differential, such as cyclins and cell cycle regulation, aldosterone signaling in epithelial cells, and estrogen-mediated S-phase entry. We observed that LINC00982 and PRDM16 were negatively associated with cyclins and cell cycle regulation in LUAD. Tumors are characterized by malignant cell growth and proliferation. Abnormalities in cell proliferation, differentiation and apoptosis are involved in the development and progression of tumors, and cell cycle disorder is the most important mechanism of tumor growth (29). The cell cycle is a highly orderly process. As a regulatory factor, cyclin overexpression is associated with carcinogenesis (30–32). In many tumor cells and proliferating cells, cyclin is overexpressed, and many tumor-suppressor genes such as p53 (29), BRCA1 (33) and Rb (34) play crucial roles in blocking the cell cycle. Consistent with our findings, a recent study reported that LINC00982 inhibited cell proliferation and rendered cell cycle arrest in gastric cancer cells (11) and PRDM16 was also reported to alter cell cycle distribution in stem (35), indicating that LINC00982 and PRDM16 may impede the occurrence and development of LUAD by mediating cell cycle arrest.
In recent years, precision medicine has increasingly been used in the treatment of cancer, especially in exploring and identifying biomarkers (36). The treatment of LUAD is typically carried out with multiple targeted therapies. Therefore, a better understanding of both coding genes and non-coding RNAs will help to improve the diagnosis and prognosis of human LUAD (37,38). In the present study, we identified LINC00982 and PRDM16 gene markers for predicting overall and disease-free survival based on RNA-Seq data that was obtained from TCGA. Additionally, after correcting for covariates, low expression of both LINC00982 and PRDM16 remained associated with reduced overall survival by Cox analysis models. Furthermore, by stratified analysis, low expression of both LINC00982 and PRDM16 was associated with poor overall survival and disease-free survival in stage I and II patients. In addition, we found that the risk ratio of LINC00982 or PRDM16 expression was lower than both LINC00982 and PRDM16 expression based on survival analysis. We therefore concluded that the interaction of LINC00982 and PRDM16 may play a significant role in the prognosis of LUAD patients than single LINC00982 or PRDM16 expression, and it was better to use these two genes as prognostic markers than using only one gene. However, we observed no association between the expression of LINC00982 and PRDM16 with patient survival in LUSC. This difference may be due to tumor heterogeneity if the genes that drive LUAD and LUSC are different (39). Finally, we observed that LINC00982 and PRDM16 were substantially decreased in human LUAD cell lines compared with a normal cell line. Therefore, we hypothesized that a combination of LINC00982 and PRDM16 expression may help to facilitate the prognosis of LUAD.
In conclusion, in the present study we found that LINC00982 and PRDM16 had low expression in tumor samples compared with adjacent normal tissues, and their expression levels were associated with their methylation status and copy number variations. Furthermore, patients with low expression of LINC00982 and PRDM16 were associated with more altered gene expression and influenced pathways compared with high-expression groups. In addition, independently and jointly, low expression of LINC00982 and PRDM16 was associated with poor patient survival, revealing that this combination had prognostic and diagnostic value. Our findings may also provide useful information to obtain a better understanding of LUAD. However, there are also several limitations in this study. Firstly, the biological functions of LINC00982 and PRDM16 need to be validated in cell and animal experiments. Secondly, it was a retrospective study, and as these findings are based on the reanalysis of TCGA data, prospective random population studies are needed to confirm these promising results. Lastly, data concerning drug therapy and prognosis of LUAD patients are not available and limit the analysis of outcomes in our study. Given the limitations of this study, further large-sample and in-depth studies are required to confirm these results.
Acknowledgements
Not applicable.
Funding
The present study was financially supported by the National Natural Science Foundation of China (grant no. 81602929), the Scientific Project of Shanghai Health and Planning Commission (grant no. 20164Y0198) and the Shanghai Municipal Planning Commission of Science and Research Fund (grant no. 20144Y0249).
Availability of data and materials
LUSC and LUAD transcriptome and clinical data were downloaded from The Cancer Genome Atlas (TCGA, http://tcga-data.nci.nih.gov/) and the cBioPortal (http://www.cbioportal.org/) database. LUAD DNA promoter methylation data were collected from MethHC (http://methhc.mbc.nctu.edu.tw/php/search.php?opt=gene). The other datasets used during the present study are available from the corresponding author upon reasonable request.
Authors' contributions
BQ, XY and WLv designed this study. XY and WLv performed data collection. WLv, WLi, TF and XY conducted data analysis. XY, NF, YW and HL performed the experiment. All authors wrote the manuscript. WLv, WLi, XY and BQ revised the manuscript. The final version of the manuscript has been read and approved by all authors, and each author believes that the manuscript represents honest work.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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