scholarly journals Identification of N6-methylandenosine related LncRNAs biomarkers associated with the overall survival of osteosarcoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pei Zhang ◽  
Keteng Xu ◽  
Jingcheng Wang ◽  
Jiale Zhang ◽  
Huahong Quan
Keyword(s):  
Risk Model ◽  
Cox Regression ◽  
Pearson Correlation ◽  
Distant Metastases ◽  
In Vivo Studies ◽  
Normal Tissues ◽  
Prognosis Model ◽  
Selection Operator ◽  
Cox Analysis

Abstract Purpose Osteosarcoma (OS) is a differentiation disease caused by the genetic and epigenetic differentiation of mesenchymal stem cells into osteoblasts. OS is a common, highly malignant tumor in children and adolescents. Fifteen to 20 % of the patients find distant metastases at their first visit. The purpose of our study was to identify biomarkers for tracking the prognosis and treatment of OS to improve the survival rate of patients. Materials and methods In this study, which was based on Therapeutically Applicable Research to Generate Effective Treatments (TARGET), we searched for m6A related lncRNAs in OS. We constructed a network between lncRNA and m6A, and built an OS prognostic risk model. Results We identified 14,581 lncRNAs by using the dataset from TARGET. We obtained 111 m6A-related lncRNAs through a Pearson correlation analysis. A network was built between lncRNA and m6A genes. Eight m6A-related lncRNAs associated with survival were identified through a univariate Cox analysis. A selection operator (LASSO) Cox regression was used to construct a prognostic risk model with six genes (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) obtained through least absolute shrinkage. We also discovered upregulated levels of DLGAP1-AS2 and m6A methylation in osteosarcoma tissues/cells compared with normal tissues/osteoblasts cells. Conclusion We constructed a risk score prognosis model of m6A-related lncRNAs (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) using the dataset downloaded from TRAGET. We verified the value of the model by dividing all samples into test groups and training groups. However, the role of m6A-related lncRNAs in osteosarcoma needs to be further researched by cell and in vivo studies.

scholarly journals Apelin Over-Expression Promotes Proliferation and Angiogenesis of Gastric Cancer Cells

2021 ◽  
Author(s):  
Li-Jun Tian ◽  
Hong-Zhi Liu ◽  
Qiang Zhang ◽  
Dian-Zhong Geng ◽  
Jing Yang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cyclin D1 ◽  
Cancer Cells ◽  
Signaling Pathway ◽  
Cox Regression ◽  
Gastric Cancer Cells ◽  
Over Expression ◽  
Normal Tissues

Abstract Background: Apelin is a recently identified endogenous ligand associated with proliferation and angiogenesis of several cancers. However, only few studies have reported on the functions and the role of apelin in gastric cancer (GC). Therefore, in the present study, we investigated the association and the mechanisms underlying Apelin expression and proliferation of GC cells both in vitro and in vivo.Methods: We enrolled 178 postoperative care GC patients to investigate clinicopathological and immunohistochemical factors associated with Apelin expression. The relationship between Survival of patients and apelin expression was evaluated using Kaplan-Meier method and Cox regression analyses. The expression of apelin mRNA and its proteins in GC tissues and cell lines were analyzed using quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR), western blot and ELISA. The role and mechanisms underlying regulation of Apelin expression in human GC cells were evaluated through several in vitro and in vivo experiments. Results: Apelin was over expressed in human GC cells, relative to adjacent normal tissues. The over expression of apelin was associated with vessel invasion (P <0.01), lymph node metastasis (P <0.01), late-staged tumor (T) (P <0.05), worse pathological type (P <0.05), nerve invasion (P <0.05). In addition, expression of apelin strongly and positively correlated with that of vascular endothelial growth factor (VEGF). Over-expression of apelin promoted proliferation and invasion of MGC-803 cell via the ERK/Cyclin D1/MMP-9 signaling pathway. Apelin over-expression also promoted angiogenesis of GC cells, accelerating growth of subcutaneous xenograft of the cancer cells in vivo.Conclusions: Over-expression of apelin promotes proliferation and metastasis of GC cells via the ERK/Cyclin D1/MMP-9 signaling pathway and is associated with adverse events of the cancer. Consequently, apelin is a potential therapeutic target for human GC.

scholarly journals Comprehensive Analysis of Cell Cycle-Related Genes in Patients With Prostate Cancer

2022 ◽  
Vol 11 ◽  
Author(s):  
Zehua Liu ◽  
Rongfang Pan ◽  
Wenxian Li ◽  
Yanjiang Li
Keyword(s):  
Prostate Cancer ◽  
Cell Cycle ◽  
Risk Score ◽  
Risk Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Cancer Center ◽  
Clinical Prognosis ◽  
Normal Tissues

This study aimed to identify critical cell cycle-related genes (CCRGs) in prostate cancer (PRAD) and to evaluate the clinical prognostic value of the gene panel selected. Gene set variation analysis (GSVA) of dysregulated genes between PRAD and normal tissues demonstrated that the cell cycle-related pathways played vital roles in PRAD. Patients were classified into four clusters, which were associated with recurrence-free survival (RFS). Moreover, 200 prognostic-related genes were selected using the Kaplan–Meier (KM) survival analysis and univariable Cox regression. The prognostic CCRG risk score was constructed using random forest survival and multivariate regression Cox methods, and their efficiency was validated in Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70770. We identified nine survival-related genes: CCNL2, CDCA5, KAT2A, CHTF18, SPC24, EME2, CDK5RAP3, CDC20, and PTTG1. Based on the median risk score, the patients were divided into two groups. Then the functional enrichment analyses, mutational profiles, immune components, estimated half-maximal inhibitory concentration (IC50), and candidate drugs were screened of these two groups. In addition, the characteristics of nine hub CCRGs were explored in Oncomine, cBioPortal, and the Human Protein Atlas (HPA) datasets. Finally, the expression profiles of these hub CCRGs were validated in RWPE-1 and three PRAD cell lines (PC-3, C4-2, and DU-145). In conclusion, our study systematically explored the role of CCRGs in PRAD and constructed a risk model that can predict the clinical prognosis and immunotherapeutic benefits.

scholarly journals Long non-coding RNA LINC00641 promotes the growth and invasiveness of hepatocellular carcinoma by antagonizing miR-501-3p

2021 ◽  
Author(s):  
Haitao Xie ◽  
Hui Zhou ◽  
Yan Jiang ◽  
Wenqian Xu ◽  
Leping Zeng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Normal Liver ◽  
In Vivo Studies ◽  
Luciferase Reporter ◽  
Normal Tissues ◽  
Non Coding Rna ◽  
Long Non Coding Rna ◽  
Proliferation And Invasion ◽  
Hcc Cells

IntroductionLong non-coding RNA LINC00641 has been reported to regulate tumor progression in several cancers. However, the expression and function of LINC00641 in hepatocellular carcinoma (HCC) is still unclear.Material and methodsIn this study, we measured the expression of LINC00641 in 79 pairs of HCC and adjacent normal liver tissues. The clinical significance of LINC00641 in HCC was explored. We also investigated the function of LINC00641 in HCC proliferation and invasion.ResultsWe observed that LINC00641 expression was significantly increased in HCC relative to normal tissues (P < 0.0001). High expression of LINC00641 was significantly associated with vascular invasion, advanced TNM stage, and reduced overall survival in HCC patients. Knockdown of LINC00641 inhibited the proliferation, colony formation, and invasion of HCC cells. In contrast, overexpression of LINC00641 promoted HCC cell growth and invasiveness. In vivo studies confirmed that knockdown of LINC00641 restrained tumorigenesis of HCC cells. Mechanistic studies revealed that LINC00641 inhibited the expression of miR-501-3p, which has been previously reported to act as a tumor suppressor in HCC. Furthermore, luciferase reporter assays validated that LINC00641 harbored a target site for miR-501-3p. Rescue experiments demonstrated that LINC00641-induced proliferation and invasion of HCC cells was reversed by co-expression of miR-501-3p.ConclusionsTaken together, LINC00641 contributes to aggressive phenotype of HCC cells by sponging miR-501-3p and represents a promising therapeutic target for this disease.

scholarly journals Prognostic model of head and neck squamous cell carcinoma based on 12 ferroptosis-related genes

2021 ◽  
Author(s):  
Sijia Li ◽  
Hongyang Zhang ◽  
Wei Li
Keyword(s):  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Model Based ◽  
Cox Analysis

Abstract Background: The purpose of our study is establishing a model based on ferroptosis-related genes predicting the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).Methods: In our study, transcriptome and clinical data of HNSCC patients were from The Cancer Genome Atlas, ferroptosis-related genes and pathways were from Ferroptosis Signatures Database. Differentially expressed genes (DEGs) were screened by comparing tumor and adjacent normal tissues. Functional enrichment analysis of DEGs, protein-protein interaction network and gene mutation examination were applied. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression were used to identified DEGs. The model was constructed by multivariate Cox regression analysis and verified by Kaplan-Meier analysis. The relationship between risk scores and other clinical features was also analyzed. Univariate and multivariate Cox analysis was used to verified the independence of our model. The model was evaluated by receiver operating characteristic analysis and calculation of the area under the curve (AUC). A nomogram model based on risk score, age, gender and TNM stages was constructed.Results: We analyzed data including 500 tumor tissues and 44 adjacent normal tissues and 259 ferroptosis-related genes, then obtained 73 DEGs. Univariate Cox regression analysis screened out 16 genes related to overall survival, and LASSO analysis fingered out 12 of them with prognostic value. A risk score model based on these 12 genes was constructed by multivariate Cox regression analysis. According to the median risk score, patients were divided into high-risk group and low-risk group. The survival rate of high-risk group was significantly lower than that of low-risk group in Kaplan-Meier curve. Risk scores were related to T and grade. Univariate and multivariate Cox analysis showed our model was an independent prognostic factor. The AUC was 0.669. The nomogram showed high accuracy predicting the prognosis of HNSCC patients.Conclusion: Our model based on 12 ferroptosis-related genes performed excellently in predicting the prognosis of HNSCC patients. Ferroptosis-related genes may be promising biomarkers for HNSCC treatment and prognosis.

scholarly journals MicroRNA-361-5p Inhibits Cancer Cell Growth by Targeting CXCR6 in Hepatocellular Carcinoma

2016 ◽  
Vol 38 (2) ◽  
pp. 777-785 ◽  
Author(s):  
Jian-Jun Sun ◽  
Guo-Yong Chen ◽  
Zhan-Tao Xie
Keyword(s):  
Hepatocellular Carcinoma ◽  
Nude Mice ◽  
In Vivo Studies ◽  
Luciferase Reporter ◽  
Western Blots ◽  
Normal Tissues ◽  
Proliferation And Invasion ◽  
Hcc Cells

Background/Aims: A growing body of evidence supports the notion that MicroRNAs (miRNAs) function as key regulators of tumorigenesis. In the present study, the expression and roles of miRNA-361-5p were explored in hepatocellular carcinoma (HCC). Methods: Quantitative real-time PCR was used to detect the expression miR-361-5p in HCC tissues and pair-matched adjacent normal tissues. MTT and BrdU assays were used to identify the role of miR-361-5p in the regulation of proliferation and invasion of HCC cells. Using bioinformatics analysis, luciferase reporter assays and Western blots were used to identify the molecular target of miR-361-5p. nude mice were used to detect the anti-tumor role of miR-361-5p in vivo. Results: miR-361-5p was down-regulated in HCC tissues in comparison to adjacent normal tissues, due to hypermethylation at its promoter region. Overexpression of miR-361-5p suppressed proliferation and invasion of HCC cells. Chemokine (C-X-C Motif) receptor 6 (CXCR6) was identified as a target of miR-361-5p. Indeed, knockdown of CXCR6 photocopied, while overexpression of CXCR6 largely attenuated the anti-proliferative effect of miR-361-5p. More importantly, in vivo studies demonstrated that forced expression of miR-361-5p significantly inhibited tumor growth in the nude mice. Conclusion: Our results indicate that miR-361-5p acts as a tumor suppressor and might serve as a novel therapeutic target for the treatment of HCC patients.

Anti-CEA and Other Antibodies in the Study of Gastrointestinal Tumors

1992 ◽  
Vol 7 (3) ◽  
pp. 198-202 ◽  
Author(s):  
S. Lastoria ◽  
C. Caracò ◽  
E. Vergara ◽  
L. Castelli ◽  
M. Salvatore
Keyword(s):  
Monoclonal Antibodies ◽  
Distant Metastases ◽  
Gastrointestinal Tumors ◽  
Primary Tumors ◽  
Factors Affecting ◽  
Normal Tissues ◽  
Antibody Uptake ◽  
The Impact

Localization of gastrointestinal tumors by means of labeled monoclonal antibodies is a new, sensitive and suitable technique currently used in several centers. Encouraging results have been documented with several monoclonal antibodies by different authors. This article reviews our experience with radioimmunoscintigraphy in 59 patients with colorectal cancer in follow-up, using 131I and 111In labeled B72.3, and in 16 patients with primary gastrointestinal tumors using 99mTc anti-CEA monoclonal antibody (type F023C5). The sensitivity of both B72.3 and anti-CEA was greater than 70% either for primary tumors and abdominal recurrences or distant metastases except hepatic ones. A significant gradient in antibody uptake was measured on surgical biopsies between tumors and normal tissues allowing a good in vivo contrast for gamma detection. We have defined the impact of some factors affecting in vivo tumor targeting. In fact, pharmacodynamics of MAbs, percentage of injected dose bound to tissues were measured, and in particular antigenic content in tumor nodules was quantified. Furthermore, the results of RIS were compared to those obtained by CT and other imaging modalities.

scholarly journals Suppression of p53-inducible gene 3 is significant for glioblastoma progression and predicts poor patient prognosis

Tumor Biology ◽  
2017 ◽  
Vol 39 (3) ◽  
pp. 101042831769457 ◽  
Author(s):  
Jishu Quan ◽  
Yong Li ◽  
Meihua Jin ◽  
Dunfu Chen ◽  
Xuezhe Yin ◽  
...  
Keyword(s):  
Cox Regression ◽  
Good Prognosis ◽  
World Health ◽  
Loss Of Function ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Health Organization ◽  
Proliferation And Invasion ◽  
Inducible Gene

Glioblastoma is the most malignant and invasive brain tumor with extremely poor prognosis. p53-inducible gene 3, a downstream molecule of the tumor suppressor p53, has been found involved in apoptosis and oxidative stress response. However, the functions of p53-inducible gene 3(PIG3) in cancer are far from clear including glioblastoma. In this study, we found that p53-inducible gene 3 expression was suppressed in glioblastoma tissues compared with normal tissues. And the expression of p53-inducible gene 3 was significantly associated with the World Health Organization grade. Patients with high p53-inducible gene 3 expression have a significantly longer median survival time (15 months) than those with low p53-inducible gene 3 expression (8 months). According to Cox regression analysis, p53-inducible gene 3 was an independent prognostic factor with multivariate hazard ratio of 0.578 (95% confidence interval, 0.352–0.947; p = 0.030) for overall survival. Additionally, gain and loss of function experiments showed that knockdown of p53-inducible gene 3 significantly increased the proliferation and invasion ability of glioblastoma cells while overexpression of p53-inducible gene 3 inhibited the proliferation and invasion ability. The results of in vivo glioblastoma models further confirmed that p53-inducible gene 3 suppression promoted glioblastoma progression. Altogether, our data suggest that high expression of p53-inducible gene 3 is significant for glioblastoma inhibition and p53-inducible gene 3 independently indicates good prognosis in patients, which might be a novel prognostic biomarker or potential therapeutic target in glioblastoma.

scholarly journals Application of an Autophagy-Related Gene Prognostic Risk Model Based on TCGA Database in Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Huadi Shi ◽  
Fulan Zhong ◽  
Xiaoqiong Yi ◽  
Zhenyi Shi ◽  
Feiyan Ou ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Risk Score ◽  
Risk Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
Survival Prediction ◽  
Aberrant Expression ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Model Based

Background: Autophagy plays an important role in the development of cancer. However, the prognostic value of autophagy-related genes (ARGs) in cervical cancer (CC) is unclear. The purpose of this study is to construct a survival model for predicting the prognosis of CC patients based on ARG signature.Methods: ARGs were obtained from the Human Autophagy Database and Molecular Signatures Database. The expression profiles of ARGs and clinical data were downloaded from the TCGA database. Differential expression analysis of CC tissues and normal tissues was performed using R software to screen out ARGs with an aberrant expression. Univariate Cox, Lasso, and multivariate Cox regression analyses were used to construct a prognostic model which was validated by using the test set and the entire set. We also performed an independent prognostic analysis of risk score and some clinicopathological factors of CC. Finally, a clinical practical nomogram was established to predict individual survival probability.Results: Compared with normal tissues, there were 63 ARGs with an aberrant expression in CC tissues. A risk model based on 3 ARGs was finally obtained by Lasso and Cox regression analysis. Patients with high risk had significantly shorter overall survival (OS) than low-risk patients in both train set and validation set. The ROC curve validated its good performance in survival prediction, suggesting that this model has a certain extent sensitivity and specificity. Multivariate Cox analysis showed that the risk score was an independent prognostic factor. Finally, we mapped a nomogram to predict 1-, 3-, and 5-year survival for CC patients. The calibration curves indicated that the model was reliable.Conclusion: A risk prediction model based on CHMP4C, FOXO1, and RRAGB was successfully constructed, which could effectively predict the prognosis of CC patients. This model can provide a reference for CC patients to make precise treatment strategy.

scholarly journals Construction and Validation of an Autophagy-Related Prognostic Model for Osteosarcoma Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Hu Qian ◽  
Ting Lei ◽  
Pengfei Lei ◽  
Yihe Hu
Keyword(s):  
Prognostic Value ◽  
Risk Model ◽  
Cox Regression ◽  
Bone Development ◽  
Treatment Strategies ◽  
Risk Groups ◽  
Low Risk ◽  
Lasso Regression ◽  
Prognostic Accuracy ◽  
Selection Operator

While the prognostic value of autophagy-related genes (ARGs) in OS patients remains scarcely known, increasing evidence is indicating that autophagy is closely associated with the development and progression of osteosarcoma (OS). Therefore, we explored the prognostic value of ARGs in OS patients and illuminate associated mechanisms in this study. When the OS patients in the training/validation cohort were stratified into high- and low-risk groups according to the risk model established using least absolute shrinkage and selection operator (LASSO) regression analysis, we observed that patients in the low-risk group possessed better prognosis ( P < 0.0001 ). Univariate/Multivariate COX regression and subgroup analysis demonstrated that the ARGs-based risk model was an independent survival indicator for OS patients. The nomogram incorporating the risk model and clinical features exhibited excellent prognostic accuracy. GO, KEGG, and GSVA analyses collectively indicated that bone development-associated pathway mediated the contribution of ARGs to the malignance of OS. Immune infiltration analysis suggested the potential pivotal role of macrophage in OS. In summary, the risk model based on 12 ARGs possessed potent capacity in predicting the prognosis of OS patients. Our work may assist clinicians to map out more reasonable treatment strategies and facilitate individual-targeted therapy in osteosarcoma.

scholarly journals Development of a Prognostic Signature Based on Hypoxia-related Genes for Thyroid Cancer

2021 ◽  
Author(s):  
HongYang Zhang ◽  
Sijia Li ◽  
Wei Li
Keyword(s):  
Overall Survival ◽  
Thyroid Cancer ◽  
Prognostic Value ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Risk Scores ◽  
Prognostic Signature ◽  
Prognosis Model ◽  
Cox Analysis

Abstract Background. We aimed to establish a model to predict the prognosis of patients with thyroid cancer based on differentially expressed hypoxia-related genes.Methods. By comparing the genes in TCGA database and hypoxiaDB database, we obtained differentially expressed genes (DEGs) related to hypoxia in thyroid cancer. Gene function enrichment analysis was performed, and a protein-protein interaction network was constructed using the STRING database. Univariate Cox regression were used to screen hypoxia-related genes with prognostic value. Subsequently, multivariate Cox analysis was used to determine prognostic markers based on thyroid cancer, a prognosis model based on these genes was established. The Kaplan-Meier analysis, Receiver operating characteristic (ROC) analysis and The Harrell’s concordance indexes in the training set and the validation set were used to evaluate the performance of the model. Finally, we conducted univariate analyses of the prognostic value of clinical data (including risk scores) of thyroid cancer patients.Results. 326 hypoxia-related thyroid cancer genes were found. Functional enrichment analysis demonstrated they were mainly involved in regulating biological functions. 23 genes have been proved to be associated with the prognosis of thyroid cancer with univariate Cox regression, among them, 11 marker genes were used to construct a new prognosis model by multivariate Cox analysis. Accordingly, the system of risk scores was constructed, patients with high-risk scores (P <0.005) had shorter overall survival than those with low-risk scores. The ROC curve indicated good performance of the eleven-gene signature at predicting overall survival. The Harrell’s concordance indexes in the internally validated for the 11-gene prognostic signature was 0.881. Moreover, univariate analysis showed that the risk score and age were significantly associated with patient overall survival. The model we created was significantly associated with patient overall survival.Conclusions. The model we established had excellent performance in the prognosis of thyroid cancer.

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