Three-lncRNA signature is a potential prognostic biomarker for pancreatic adenocarcinoma.
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ABSTRACT:
SUBMITTER: Shi X
PROVIDER: S-EPMC5966255 | biostudies-literature | 2018 May
REPOSITORIES: biostudies-literature
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Three-lncRNA signature is a potential prognostic biomarker for pancreatic adenocarcinoma.
Shi Xiuhui X Zhao Yan Y He Ruizhi R Zhou Min M Pan Shutao S Yu Shuo S Xie Yu Y Li Xu X Wang Min M Guo Xingjun X Qin Renyi R
Oncotarget 20180208 36
Pancreatic adenocarcinoma (PAAD) is a highly aggressive and metastatic cancer characterized by poor survival rates. Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including cancer and PAAD. To identify the specific lncRNAs associated with PAAD and analyze their function, we constructed a global triple network based on the competitive endogenous RNA (ceRNA) theory and RNA-seq data from The Cancer Genome Atlas. Using 182 PAAD cases, we established a lncRNA-miR ...[more]
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Project description:BackgroundGenomic instability (GI) is a critical feature of cancer which plays a key role in the occurrence and development of pancreatic adenocarcinoma (PAAD). Long non-coding RNA (LncRNA) is an emerging prognostic biomarker because it is involved in regulating GI. Recently, researchers used such GI-related LncRNAs (GILncRNAs) to establish a prognostic signature for patients with cancer and helped in predicting the overall prognosis of the patients. However, it is evident that patients with PAAD still lack such prognostic signature constructed with GILncRNA.MethodsThe present study screened GILncRNAs from 83 patients with PAAD. Prognosis-related GILncRNAs were identified by univariate Cox regression analysis. The correlation coefficients of these GILncRNAs were obtained by multivariate Cox regression analysis and used to construct a signature. The signature in the present study was then assessed through survival analysis, mutation correlation analysis, independent prognostic analysis, and clinical stratification analysis in the training set and validated in the testing as well as all TCGA set. The current study performed external clinical relevance validation of the signature and validated the effect of AC108134.2 in GILncSig on PAAD using in vitro experiments. Finally, the function of GILncRNA signature (GILncSig) dependent on Gene Ontology enrichment analysis was explored and chemotherapeutic drug sensitivity analysis was also performed.ResultsResults of the present study found that a total of 409 GILncRNAs were identified, 5 of which constituted the prognostic risk signature in this study, namely, AC095057.3, AC108134.2, AC124798.1, AL606834.1, and AC104695.4. It was found that the signature of the present study was better than others in predicting the overall survival and applied to patients with PAAD of all ages, genders, and tumor grades. Further, it was noted that the signature of the current study in the GSE102238, was correlated with tumor length, and tumor stage of patients with PAAD. In vitro, functional experiments were used in the present study to validate that AC108134.2 is associated with PAAD genomic instability and progression. Notably, results of the pRRophetic analysis in the current study showed that the high-risk group possessed reverse characteristics and was sensitive to chemotherapy.ConclusionsIn conclusion, it was evident that the GILncSig used in the present study has good prognostic performance. Therefore, the signature may become a potential sensitive biological indicator of PAAD chemotherapy, which may help in clinical decision-making and management of patients with cancer.
| S-EPMC9012103 | biostudies-literature
Project description:BackgroundPancreatic adenocarcinoma (PAAD) is a disease with atypical symptoms, an unfavorable response to therapy, and a poor outcome. Abnormal guanylate-binding proteins (GBPs) play an important role in the host's defense against viral infection and may be related to carcinogenesis. In this study, we sought to determine the relationship between GBP2 expression and phenotype in patients with PAAD and explored the possible underlying biological mechanism.MethodWe analyzed the expression of GBP2 in PAAD tissues using a multiple gene expression database and a cohort of 42 PAAD patients. We evaluated GBP2's prognostic value using Kaplan-Meier analysis and the Cox regression model. GO and KEGG enrichment analysis, co-expression analysis, and GSEA were performed to illustrate the possible underlying biological mechanism. CIBERSORT and the relative expression of immune checkpoints were used to estimate the relationship between GBP2 expression and tumor immunology.ResultGBP2 was remarkably overexpressed in PAAD tissue. The overexpression of GBP2 was correlated with an advanced T stage and poor overall survival (OS) and GBP2 expression was an independent risk factor for OS in PAAD patients. Functional analysis demonstrated that positively co-expressed genes of GBP2 were closely associated with pathways in cancer and the NOD-like receptor signaling pathway. Most of the characteristic immune checkpoints, including PDCD1, PDCDL1, CTLA4, CD80, TIGIT, LAG3, IDO2, and VISTA, were significantly expressed in the high-GBP2 expression group compared with the low-GBP2 expression group.ConclusionGBP2 acted as a potential prognostic biomarker and was associated with immune infiltration and the expression of immune checkpoints in PAAD.
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Project description:PurposePapillary thyroid carcinoma (PTC), the most frequent type of malignant thyroid tumor, lacks novel and reliable biomarkers of patients' prognosis. In the current study, we mined The Cancer Genome Atlas (TCGA) to develop lncRNA signature of PTC.Patients and methodsThe intersection of PTC lncRNAs was obtained from the TCGA database using integrative computational method. By the univariate and multivariate Cox analysis, key lncRNAs were identified to construct the prognostic model. Then, all patients were divided into the high-risk group and low-risk group to perform the Kaplan-Meier (K-M) survival curves and time-dependent receiver operating characteristic (ROC) curve, estimating the prognostic power of the prognostic model. Functional enrichment analysis was also performed. Finally, we verified the results of the TCGA analysis by the Gene Expression Omnibus (GEO) databases and quantitative real-time PCR (qRT-PCR).ResultsAfter the comprehensive analysis, a three-lncRNA signature (PRSS3P2, KRTAP5-AS1 and PWAR5) was obtained. Interestingly, patients with low-risk scores tended to gain obviously longer survival time, and the area under the time-dependent ROC curve was 0.739. Furthermore, gene ontology (GO) and pathway analysis revealed the tumorigenic and prognostic function of the three lncRNAs. We also found three potential transcription factors to help understand the mechanisms of the PTC-specific lncRNAs. Finally, the GEO databases and qRT-PCR validation were consistent with our TCGA bioinformatics results.ConclusionWe built a three-lncRNA signature by mining the TCGA database, which could effectively predict the prognosis of PTC.
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Project description:BackgroundPancreatic adenocarcinoma (PAAD) is an aggressive solid tumour characterised by few early symptoms, high mortality, and lack of effective treatment. Therefore, it is important to identify new potential therapeutic targets and prognostic biomarkers of PAAD.MethodsThe Cancer Genome Atlas and Genotype-Tissue Expression databases were used to identify the expression and prognostic model of protocadherin 1 (PCDH1). The prognostic performance of risk factors and diagnosis of patients with PAAD were evaluated by regression analysis, nomogram, and receiver operating characteristic curve. Paraffin sections were collected from patients for immunohistochemistry (IHC) analysis. The expression of PCDH1 in cells obtained from primary tumours or metastatic biopsies was identified using single-cell RNA sequencing (scRNA-seq). Real-time quantitative polymerase chain reaction (qPCR) and western blotting were used to verify PCDH1 expression levels and the inhibitory effects of the compounds.ResultsThe RNA and protein levels of PCDH1 were significantly higher in PAAD cells than in normal pancreatic ductal cells, similar to those observed in tissue sections from patients with PAAD. Aberrant methylation of the CpG site cg19767205 and micro-RNA (miRNA) hsa-miR-124-1 may be important reasons for the high PCDH1 expression in PAAD. Up-regulated PCDH1 promotes pancreatic cancer cell metastasis. The RNA levels of PCDH1 were significantly down-regulated following flutamide treatment. Flutamide reduced the percentage of PCDH1 RNA level in PAAD cells Panc-0813 to < 50%. In addition, the PCDH1 protein was significantly down-regulated after Panc-0813 cells were incubated with 20 µM flutamide and proves to be a potential therapeutic intervention for PAAD.ConclusionPCDH1 is a key prognostic biomarker and promoter of PAAD metastasis. Additionally, flutamide may serve as a novel compound that down-regulates PCDH1 expression as a potential treatment for combating PAAD progression and metastasis.
| S-EPMC10642060 | biostudies-literature
Project description:BackgroundPancreatic adenocarcinoma (PAAD) is characterized by lower immunogenicity with a poor response rate to immune checkpoint inhibitors (ICIs) and exhibits the poorest prognosis of all solid tumors, which results in the highest tumor-related mortality among malignancies. However, the underlying mechanisms are poorly understood. In addition, diverse carbohydrate sulfotransferases (CHSTs), which are involved in the sulfation process of these structures, play an important role in the metastatic spread of tumor cells. Aberrant glycosylation is beginning to emerge as an influencing factor in tumor immunity and immunotherapy. Therefore, it might serve as a biomarker of the immunotherapeutic response in tumors. The purpose of the study was to evaluate the role of CHST12 in PAAD prognosis and its relevance to the immunotherapeutic response.MethodsA comprehensive investigation of the interactions between CHST12 expression and the immune microenvironment as well as the clinical significance of CHST12 in PAAD was conducted. Data derived from the Cancer Genome Atlas (TCGA) database were analyzed using univariate and multivariate approaches, the Tumor Immune Estimation Resource (TIMER), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Publicly available datasets were analyzed in this study. These data can be found on websites such as http://www.xiantao.love and https://www.proteinatlas.org. An assessment of the predictive value of CHST12 for PAAD prognosis was conducted using univariate and multivariate Cox regression analysis, Kaplan-Meier analysis, and nomograms. The TIMER algorithm calculates the proportions of six types of immune cells. The TIDE algorithm was used to indicate the characteristics of tumors that respond to ICI therapy.ResultsThe mRNA and protein levels of CHST12 showed the opposite trend. CHST12 mRNA expression was significantly upregulated in PAAD. According to Cox regression analysis, CHST12 RNA expression acts as a protective factor for overall survival [hazard ratio (HR), 0.617, P < 0.04]. Functional annotation indicated that CHST12-associated differentially expressed genes (DEGs) were related to the signaling activity of receptor tyrosine kinases and the regulation of ubiquitin-protein transferase. These are usually involved in tumor development and may be related to the treatment responses of immune checkpoint inhibitors (ICIs). There was significantly higher CHST12 mRNA expression in PAAD samples than in non-malignant samples.ConclusionsIn PAAD, elevated CHST12 mRNA expression might regulate immune cell infiltration into the tumor microenvironment (TME) and may predict clinical outcomes.
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Project description:Introduction: Long non-coding RNAs (lncRNAs) exhibit crucial roles in human tumors. However, the role of lncRNA CARD8-AS1 in lung adenocarcinoma remains elusive. This study investigated the role of CARD8-AS1 in lung adenocarcinoma. Materials and Methods: The expression of CARD8-AS1 was detected by RT-qPCR analysis and confirmed using an online database. The clinical value of CARD8-AS1 was evaluated using the Kaplan-Meier curve and multivariate Cox regression analyses. The effects of CARD8-AS1 on cancer cell proliferation, migration, and invasion potential were assessed through several cellular experiments. Western blot assay was used to measure Bcl-2 and Bax protein levels. The interaction among CARD8-AS1, miR-650, and Bax, was assessed using a dual-luciferase reporter assay. Results: The expression of CARD8-AS1 was decreased in lung adenocarcinoma tissues and cell lines (p < 0.001). Low expression of CARD8-AS1 was related to tumor size (p = 0.042), TNM stage (p = 0.021), lymph node metastasis (p = 0.025), and poor overall survival (p < 0.05). Elevated expression of CARD8-AS1 could suppress cellular viability, migration potential, and invasion ability (p < 0.05). The Bcl-2 protein levels were decreased while Bax levels were increased by overexpression of CARD8-AS1 (p < 0.001). miR-650 may thus be a direct target of CARD8-AS1 and Bax may be a direct target of miR-650. Discussion: CARD8-AS1 expression was downregulated in lung adenocarcinoma and associated with several clinical parameters. CARD8-AS1 exerted tumor-suppressive effects by targeting the miR-650 and then regulating Bax expression. CARD8-AS1/miR-650 may serve as novel prognostic biomarkers and potential therapeutic targets for the treatment of lung adenocarcinoma.
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Project description:Background: Recent studies have highlighted the important roles of long non-coding RNAs (lncRNAs) in pancreatic adenocarcinoma (PCa) prognosis. However, most studies explored a limited number of lncRNAs based on small sample size. Methods: Systematic and comprehensive analysis of the data from The Cancer Genome Atlas (TCGA) was performed to identify a panel of lncRNA signature for predicting prognosis in PCa. Results: A total of 160 PCa patients with complete clinical data were included in our study. Twelve lncRNAs were identified to be significantly associated with overall survival (OS) in PCa patients using Cox regression analysis. A risk score formula was constructed to assess the prognostic value of the lncRNA signature in PCa. Patients with high risk score had worse OS than those with low risk score. The multivariate Cox regression analyses revealed that the lncRNA signature was an independent prognostic factor. Additionally, the signature might act as an indicator to predict treatment outcome. Functional enrichment analyses showed that the lncRNAs might involve in several molecular pathways closely related with PCa such as DNA replication, pancreatic cancer and regulation of tor signaling. Conclusions: Our study demonstrated a lncRNA signature including 12 lncRNAs with the potential to be served as an independent prognostic biomarker of PCa.
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Project description:Pancreatic adenocarcinoma (PAAD) is a common, highly malignant, and aggressive gastrointestinal tumor. The conventional treatment of PAAD shows poor results, and patients have poor prognosis. The synthesis and degradation of proteins are essential for the occurrence and development of tumors. Aggrephagy is a type of autophagy that selectively degrades aggregated proteins. It decreases the formation of aggregates by degrading proteins, thus reducing the harm to cells. By breaking down proteins, it decreases the formation of aggregates; thus, minimizing damage to cells. For evaluating the response to immunotherapy and prognosis in PAAD patients, in this study, we developed a reliable signature based on aggrephagy-related genes (ARGs). We obtained 298 AGGLncRNAs. Based on the results of one-way Cox and LASSO analyses, the lncRNA signature was constructed. In the risk model, the prognosis of patients in the low-risk group was noticeably better than that of the patients in the high-risk group. Additionally, the ROC curves and nomograms validated the capacity of the risk model to predict the prognosis of PAAD. The patients in the low-risk and high-risk groups showed considerable variations in functional enrichment and immunological analysis. Regarding drug sensitivity, the low-risk and high-risk groups had different half-maximal inhibitory concentrations (IC50).
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Project description:Recent evidence suggests that aberrant expression of long non-coding RNA (lncRNA) can drive the initiation and progression of malignancies. However, little is known about the prognostic potential of lncRNA. We aimed at constructing a lncRNA-based signature to improve the prognosis prediction of pancreatic adenocarcinoma (PAAD). The PAAD samples with clinical information were obtained from The Cancer Genome Atlas and International Cancer Genome Consortium. We established an eight-IRlncRNA signature in a training cohort. The prognostic value of eight-IRlncRNA signature was validated in two distinct cohorts when compared to other four prognostic models. We continued to analyze its independence in subgroups by univariate and multivariate Cox regression. We constructed a nomogram for clinicopathologic features and 1-, 3-, and 5-year overall survival performance. Moreover, Gene set enrichment analysis and Gene Set Variation Analysis distinguished the typical functions between high- and low-risk groups. In addition, we further observed the different correlations of immune cell between eight IRlncRNAs. Eight-IRlncRNA signature appears to be a good performer to predict the survival capability of PAAD patients, and the nomogram will enable PAAD patients to be more accurately managed in clinical practice.
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