scholarly journals Profiling analysis of long non-coding RNA and mRNA in parathyroid carcinoma

2019 ◽  
Vol 26 (2) ◽  
pp. 163-176 ◽  
Author(s):  
Xiang Zhang ◽  
Ya Hu ◽  
Mengyi Wang ◽  
Ronghua Zhang ◽  
PeiPei Wang ◽  
...  
Keyword(s):  
Parathyroid Carcinoma ◽  
Area Under The Curve ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Current Evidence ◽  
Receptor Interaction ◽  
Signalling Molecules ◽  
Non Coding Rna ◽  
Parathyroid Tumours ◽  
Long Non Coding Rna

Parathyroid carcinoma (PCa) is a rare endocrine neoplasia that typically has unfavourable outcomes. The contribution of long non-coding RNAs (lncRNAs) to the development of malignant and benign parathyroid tumours remains largely unknown. In this study, we explored transcriptomic profiling of lncRNA and mRNA expression in 6 PCa, 6 parathyroid adenoma (PAd) and 4 normal parathyroid (PaN) tissues. In total, 2641 lncRNA transcripts and 2165 mRNA transcripts were differentially expressed between PCa and PAd. Enrichment analysis demonstrated that dysregulated transcripts were involved mainly in the extracellular matrix (ECM)–receptor interaction and energy metabolism pathways. Bioinformatics analysis suggested that ATF3, ID1, FOXM1, EZH2 and MITF may be crucial to parathyroid carcinogenesis. Series test of cluster analysis segregated differentially expressed lncRNAs and mRNAs into several expression profile models, among which the ‘plateau’ profile representing components specific to parathyroid carcinogenesis was selected to build a co-expression network. Seven lncRNAs and three mRNAs were selected for quantitative RT-PCR validation in 16 PCa, 41 PAd and 4 PaN samples. Receiver-operator characteristic curves analysis showed that lncRNA PVT1 and GLIS2-AS1 yielded the area under the curve values of 0.871 and 0.860, respectively. Higher hybridization signals were observed in PCa for PVT1 and PAd for GLIS2-AS1. In conclusion, the current evidence indicates that PAd and PCa partially share common signalling molecules and pathways, but have independent transcriptional events. Differentially expressed lncRNAs and mRNAs have intricate interactions and are involved in parathyroid tumourigenesis. The lncRNA PVT1 and GLIS2-AS1 may be new potential markers for the diagnosis of PCa.

scholarly journals LINC01018 and SMIM25 sponged miR-182-5p in endometriosis revealed by the ceRNA network construction

2020 ◽  
Vol 34 ◽  
pp. 205873842097630
Author(s):  
Li Jiang ◽  
Mengmeng Zhang ◽  
Sixue Wang ◽  
Yuzhen Xiao ◽  
Jingni Wu ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Cerna Network ◽  
Non Coding Rna ◽  
Differentially Expressed Mirnas ◽  
Long Non Coding Rna

The current study intended to explore the interaction of the long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) under the background of competitive endogenous RNA (ceRNA) network in endometriosis (EMs). The differentially expressed miRNAs (DEmiRs), differentially expressed lncRNA (DELs), and differentially expressed genes (DEGs) between EMs ectopic (EC) and eutopic (EU) endometrium based on three RNA-sequencing datasets (GSE105765, GSE121406, and GSE105764) were identified, which were used for the construction of ceRNA network. Then, DEGs in the ceRNA network were performed with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) analysis. Besides, the DEmiRs in the ceRNA network were validated in GSE124010. And the target DELs and DEGs of verified DEmiRs were validated in GSE86534. The correlation of verified DEmiRs, DEGs, and DELs was explored. Moreover, gene set enrichment analysis (GSEA) was applied to investigate the function of verified DEmiRs, DEGs, and DELs. Overall, 1352 DEGs and 595 DELs from GSE105764, along with 27 overlapped DEmiRs between GSE105765 and GSE121406, were obtained. Subsequently, a ceRNA network, including 11 upregulated and 16 downregulated DEmiRs, 7 upregulated and 13 downregulated DELs, 48 upregulated and 46 downregulated DEGs, was constructed. The GO and KEGG pathway analysis showed that this ceRNA network probably was associated with inflammation-related pathways. Furthermore, hsa-miR-182-5p and its target DELs (LINC01018 and SMIM25) and DEGs (BNC2, CHL1, HMCN1, PRDM16) were successfully verified in the validation analysis. Besides, hsa-miR-182-5p was significantly negatively correlated with these target DELs and DEGs. The GSEA analysis implied that high expression of LINC01018, SMIM25, and CHL1, and low expression of hsa-miR-182-5p would activate inflammation-related pathways in endometriosis EU samples. LINC01018 and SMIM25 might sponge hsa-miR-182-5p to upregulate downstream genes such as CHL1 to promote the development of endometriosis.

scholarly journals Long Non-Coding RNA Expression Profile Associated with Malignant Progression of Oral Submucous Fibrosis

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Shanghui Zhou ◽  
Yun Zhu ◽  
Zhijing He ◽  
Dahe Zhang ◽  
Feng Guo ◽  
...  
Keyword(s):  
Expression Profile ◽  
Egf Receptor ◽  
Oral Submucous Fibrosis ◽  
Enrichment Analysis ◽  
Malignant Progression ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Non Coding Rna ◽  
Submucous Fibrosis ◽  
Long Non Coding Rna

Oral submucous fibrosis (OSF) as one of the premalignant disorders endures a series of histopathological stages to invasive oral squamous cell carcinoma (OSCC) eventually. However, the role of long non-coding RNA (lncRNA) expression in OSF malignant progression still remains poorly understood. Through RNA-sequencing normal mucous, OSF and OSCC tissues, we found 687 lncRNA transcripts significantly and differentially expressed during OSF progression, including 231 upregulated lncRNAs and 456 downregulated lncRNAs, indicating that lncRNAs are involved in the regulation of different stages of OSF development. Further functional enrichment analysis showed these differentially expressed lncRNAs participated in inflammation signaling, Wnt signaling, angiogenesis, CCKR signaling, integrin signaling, PDGF signaling, p53 signaling, and EGF receptor (EGFR) signaling pathways, which contribute to inflammatory and fibroelastic pathogenetic changes of OSF and further malignant progression. Five novel lncRNAs were differentially expressed during OSF progression with varied expression levels, indicating the importance of these lncRNAs in OSF malignant development. Moreover, some lncRNAs have been previously identified to be associated with OSCC pathogenesis, including HCG22, RP11-397A16.1, LINC00271, CTD-3179P9.1, and ZNF667-AS1. Thus, our study firstly comprehensively elucidated lncRNAs expression profile of malignant procession from OSF premalignant lesion to OSCC, which will enlighten our understanding of the importance of lncRNA involved in OSF malignant development.

scholarly journals Dynamic characteristics and functional analysis provide new insights into long non-coding RNA responsive to Verticillium dahliae infection in Gossypium hirsutum

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guoning Wang ◽  
Xingfen Wang ◽  
Yan Zhang ◽  
Jun Yang ◽  
Zhikun Li ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Verticillium Wilt ◽  
Dynamic Characteristics ◽  
Target Genes ◽  
Acid Metabolism ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Alpha Linolenic Acid ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Abstract Background Verticillium wilt is a widespread and destructive disease, which causes serious loss of cotton yield and quality. Long non-coding RNA (lncRNA) is involved in many biological processes, such as plant disease resistance response, through a variety of regulatory mechanisms, but their possible roles in cotton against Verticillium dahliae infection remain largely unclear. Results Here, we measured the transcriptome of resistant G. hirsutum following infection by V. dahliae and 4277 differentially expressed lncRNAs (delncRNAs) were identified. Localization and abundance analysis revealed that delncRNAs were biased distribution on chromosomes. We explored the dynamic characteristics of disease resistance related lncRNAs in chromosome distribution, induced expression profiles, biological function, and these lncRNAs were divided into three categories according to their induced expression profiles. For the delncRNAs, 687 cis-acting pairs and 14,600 trans-acting pairs of lncRNA-mRNA were identified, which indicated that trans-acting was the main way of Verticillium wilt resistance-associated lncRNAs regulating target mRNAs in cotton. Analyzing the regulation pattern of delncRNAs revealed that cis-acting and trans-acting lncRNAs had different ways to influence target genes. Gene Ontology (GO) enrichment analysis revealed that the regulatory function of delncRNAs participated significantly in stimulus response process, kinase activity and plasma membrane components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that delncRNAs participated in some important disease resistance pathways, such as plant-pathogen interaction, alpha-linolenic acid metabolism and plant hormone signal transduction. Additionally, 21 delncRNAs and 10 target genes were identified as being involved in alpha-linolenic acid metabolism associated with the biosynthesis of jasmonic acid (JA). Subsequently, we found that GhlncLOX3 might regulate resistance to V. dahliae through modulating the expression of GhLOX3 implicated in JA biosynthesis. Further functional analysis showed that GhlncLOX3-silenced seedlings displayed a reduced resistance to V. dahliae, with down-regulated expression of GhLOX3 and decreased content of JA. Conclusion This study shows the dynamic characteristics of delncRNAs in multiaspect, and suggests that GhlncLOX3-GhLOX3-JA network participates in response to V. dahliae invasion. Our results provide novel insights for genetic improvement of Verticillium wilt resistance in cotton using lncRNAs.

scholarly journals IIMLP: integrated information-entropy-based method for LncRNA prediction

2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Junyi Li ◽  
Huinian Li ◽  
Xiao Ye ◽  
Li Zhang ◽  
Qingzhe Xu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Dna Sequences ◽  
Information Entropy ◽  
Area Under The Curve ◽  
Prediction Method ◽  
Machine Learning Algorithms ◽  
Reading Frame ◽  
Non Coding Rna ◽  
The One ◽  
Long Non Coding Rna

Abstract Background The prediction of long non-coding RNA (lncRNA) has attracted great attention from researchers, as more and more evidence indicate that various complex human diseases are closely related to lncRNAs. In the era of bio-med big data, in addition to the prediction of lncRNAs by biological experimental methods, many computational methods based on machine learning have been proposed to make better use of the sequence resources of lncRNAs. Results We developed the lncRNA prediction method by integrating information-entropy-based features and machine learning algorithms. We calculate generalized topological entropy and generate 6 novel features for lncRNA sequences. By employing these 6 features and other features such as open reading frame, we apply supporting vector machine, XGBoost and random forest algorithms to distinguish human lncRNAs. We compare our method with the one which has more K-mer features and results show that our method has higher area under the curve up to 99.7905%. Conclusions We develop an accurate and efficient method which has novel information entropy features to analyze and classify lncRNAs. Our method is also extendable for research on the other functional elements in DNA sequences.

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals Long-non Coding RNAs Related to Fat Deposition in Pigs Included lncRNA Corresponding to Human MALAT1

2021 ◽  
Author(s):  
Katarzyna Piórkowska ◽  
Kacper Żukowski ◽  
Katarzyna Ropka-Molik ◽  
Mirosław Tyra
Keyword(s):  
Regulatory Elements ◽  
Fat Deposition ◽  
Differentially Expressed ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Sequencing Method ◽  
Non Coding Rnas ◽  
Potential Interactions ◽  
Long Non Coding Rna ◽  
Generation Sequencing

Obesity is a problem in the last decades since the development of different technologies forced the submission of a faster pace of life, resulting in nutrition style changes. In turn, domestic pigs are an excellent animal model in recognition of adiposity-related processes, corresponding to the size of individual organs, the distribution of body fat in the organism, and similar metabolism. The present study applied the next-generation sequencing method to identify adipose tissue (AT) transcriptomic signals related to increased fat content by identifying differentially expressed genes (DEGs), included long-non coding RNA molecules. The Freiburg RNA tool was applied to recognise predicting hybridisation energy of RNA-RNA interactions. The results indicated several long non-coding RNAs (lncRNAs) whose expression was significantly positively or negatively associated with fat deposition. lncRNAs play an essential role in regulating gene expression by sponging miRNA, binding transcripts, facilitating translation, or coding other smaller RNA regulatory elements. In the pig fat tissue of obese group, increased expression of lncRNAs corresponding to human MALAT1 was observed that previously recognised in the obesity-related context. Moreover, hybridisation energy analyses pinpointed numerous potential interactions between identified differentially expressed lncRNAs, and obesity-related genes and miRNAs expressed in AT.

scholarly journals Aberrant expression of long non-coding RNA in thyroid neoplasms

2019 ◽  
pp. 17-25
Author(s):  
В.Д. Якушина ◽  
А.С. Танас ◽  
А.В. Лавров
Keyword(s):  
Thyroid Cancer ◽  
Signaling Pathway ◽  
In Silico ◽  
Thyroid Nodules ◽  
Differentially Expressed ◽  
Follicular Variant ◽  
Aberrant Expression ◽  
Lncrna Expression ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Актуальность. Длинные некодирующие РНК (днРНК) при раке щитовидной железы плохо изучены; не известны днРНК, общие и специфичные для фолликулярного и классического вариантов папиллярного рака, не установлены днРНК, аберрантно экспрессированные при других основных субтипах злокачественных новообразований щитовидной железы, а также при доброкачественных новообразованиях. Цель исследования - определить днРНК, аберрантно экспрессированные при фолликулярной аденоме (ФА), фолликулярном раке (ФРЩЖ), фолликулярном и классическом вариантах папиллярного рака (ПРЩЖ), анапластическом раке (АРЩЖ) щитовидной железы. Методы. Проанализирована экспрессия днРНК по данным исследований на микрочипах (8 независимых экспериментов, доступных в GEO) и секвенирования РНК (PRJEB11591 и TCGA-THCA). Исследованы 246 образцов нормальной ткани щитовидной железы, 26 - ФА, 30 - ФРЩЖ, 181 - фолликулярного варианта ПРЩЖ, 481 - классического варианта ПРЩЖ и 49 - АРЩЖ. Для классического и фолликулярного вариантов ПРЩЖ выполнена валидация дифференциальной экспрессии in silico. Потенциальные биологические функции были оценены в результате анализа обогащения коэкспрессированных генов. Результаты. Определены днРНК, дифференциально экспрессированные при ФА, ФРЩЖ, фолликулярном и классическом вариантах ПРЩЖ и АРЩЖ. Выявлены 8 днРНК, экспрессия которых изменена во всех субтипах новообразований щитовидной железы, 22 - общих для ПРЩЖ, 32 - специфичных для классического варианта ПРЩЖ, 1 - специфичная для фолликулярного варианта ПРЩЖ, и 177 - специфичных для АРЩЖ. Статистически значимо дифференциально экспрессированных днРНК в ФРЩ по сравнению с ФА не выявлено. Ранее известные онкогенные и супрессорные днРНК NR2F1-AS1, LINC00511, SLC26A4-AS1, CRNDE, RMST впервые обнаружены в новообразованиях щитовидной железы. Выявленные днРНК предположительно вовлечены в клеточную адгезию, организацию экстрацеллюлярного матрикса, образование эндодермы, регуляцию клеточного цикла и митоза, полярности клеток, сигнальные пути VEGF и WNT. Выводы. Установлены общие и специфичные паттерны экспрессии днРНК в доброкачественных и злокачественных новообразованиях щитовидной железы. Background. Long non-coding RNA (lncRNA) in thyroid cancer are poorly investigated; no lncRNAs common and specific for the follicular and classical variants of papillary cancer, as well as no lncRNAs aberrantly expressed in benign nodules or other subtypes of thyroid cancer are established. The objective of the study is to determine long noncoding RNAs aberrantly expressed in follicular adenoma (FA), follicular carcinoma (FTC), follicular and classical variants of papillary carcinoma (PTC), anaplastic carcinoma (ATC). Methods. lncRNA expression was analyzed in dataset of Microarray (8 independent experiments available in GEO) and RNA-seq studies (PRJEB11591 and TCGA-THCA). In total, 246 samples of normal thyroid tissue, 26 FAs, 30 FTCs, 181 follicular variant PTCs, 481 classic variant PTCs and 49 ATCs were examined. In silico validation was performed. Potential biological functions were assessed by enrichment analysis of coexpressed genes. Results. LncRNAs differentially expressed in FA, FTC, follicular, and classical variants of PTC, and ATC are identified. There are 8 lncRNAs common for all investigated thyroid nodules, 22 common for PTC, 32 specific for classical PTC, 1 specific for follicular variant of PTC, and 177 specific for ATC. No lncRNA significantly differentially expressed in FTC compared to FA is identified. The previously described oncogenic and suppressor lncRNAs NR2F1-AS1, LINC00511, SLC26A4-AS1, CRNDE, RMST are detected in thyroid carcinomas for the first time. Identified lncRNA are putatively involved in cell adhesion, extracellular matrix organization, endoderm formation, VEGF signaling pathway, WNT signaling pathway and cell polarity, cell cycle and mitosis. Conclusion. The general and specific patterns of lncRNA expression in benign and malignant thyroid nodules are established.

scholarly journals Differential long non-coding RNA expression profile and function analysis in primary Sjogren’s syndrome

2021 ◽  
Author(s):  
Xiaochan Chen ◽  
Qi Cheng ◽  
Yan Du ◽  
Lei Liu ◽  
Huaxiang Wu
Keyword(s):  
B Cells ◽  
Primary Sjögren’S Syndrome ◽  
Differentially Expressed ◽  
Expression Level ◽  
Primary Sjogren’S Syndrome ◽  
Primary Sjögren's Syndrome ◽  
Cerna Network ◽  
Non Coding Rna ◽  
Long Non Coding Rna ◽  
Healthy Persons

Abstract Background: Primary Sjögren’s syndrome (pSS) is a chronic autoimmune disease characterized by abnormal immune cell activation. This study aimed to investigate differentially expressed long non-coding RNA (lncRNA) in peripheral blood mononuclear cells (PBMCs) in patients with pSS to identify lncRNAs that affect pSS pathogenesis. Methods: Total RNA was extrated from PBMCs of 30 patients with pSS and 15 healthy persons. Transcriptome sequencing was used to screen differentially expressed lncRNAs and mRNAs in 8 RNA samples from the discovery cohort. The differentially expressed mRNAs underwent functional enrichment analysis. A protein interaction relationship (PPI) and ceRNA network was constructed. Real-time PCR was used to validate screened lncRNAs in all 45 RNA samples. Results: 1180 lncRNAs and 640 mRNAs were differentially expressed in pSS patients (fold change > 2 in healthy persons). The PPI network was constructed with 640 mRNAs and a ceRNA network with four key lncRNAs (GABPB1-AS1, PSMA3-AS1, LINC00847 and SNHG1). RT-PCR revealed that GABPB1-AS1 and PSMA3-AS1 were significantly upregulated 3.0-and 1.4-fold in the pSS group, respectively. The GABPB1-AS1 expression level was positively correlated with the percentage of B cells and IgG levels. Conclusions: GABPB1-AS1 was significently upregulated in pSS patients, and its expression level is positively correlated with the percentage of B cells and IgG levels. GABPB1-AS1 may be involved in the pathogenesis of pSS.

scholarly journals Prognostic value of an immune long non-coding RNA signature in liver hepatocellular carcinoma

2019 ◽  
Author(s):  
rui kong ◽  
Nan Wang ◽  
Wei Han ◽  
Yuejuan Zheng ◽  
Jie Lu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Liver Hepatocellular Carcinoma ◽  
Long Non Coding Rna

Abstract Background: In recent years, long non-coding RNAs (lncRNAs) are emerging as crucial regulators in the immunological process of liver hepatocellular carcinoma (LIHC). Increasing studies have found that some lncRNAs could be used as a diagnostic or therapeutic target for clinical management, but little research has investigated the role of immune-related lncRNA in tumor prognosis. In this study, we aimed to develop an immune lncRNA signature for the precise diagnosis and prognosis of liver hepatocellular carcinoma. Methods: Gene expression profiles of LIHC samples obtained from TCGA were screened for immune-related genes using two reference gene sets. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate cox analysis. Then the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were carried out to evaluate the capability of immune lncRNA signature as a prognostic indicator. Results: Six long non-coding RNA MSC−AS1, AC009005.1, AL117336.3, AL031985.3, AL365203.2, AC099850.3 were identified via correlation analysis and cox regression analysis considering their interactions with immune genes. Next, tumor samples were separated into two risk groups by the signature with different clinical outcomes. Stratification analysis showed the prognostic ability of this signature acted as an independent factor. The AUC value of ROC curve was 0.779. The Kaplan-Meier method was used in survival analysis and results showed a statistical difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Data from gene set enrichment analysis (GSEA) further unveiled several potential biological processes of these biomarkers may involve in. Conclusion: In summary, the study demonstrated the potential role of the six-lncRNA signature served as an independent prognostic factor for LIHC patients.

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