scholarly journals Loss of IL-34 Expression Indicates Poor Prognosis in Patients With Lung Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhendong Wang ◽  
Jun Zhu ◽  
Tianyi Wang ◽  
Hao Zhou ◽  
Jinjie Wang ◽  
...  
Keyword(s):  
Immune System ◽  
Lung Adenocarcinoma ◽  
Poor Prognosis ◽  
Immunohistochemical Analysis ◽  
Negative Regulation ◽  
The Cancer Genome Atlas ◽  
Additional Ligand ◽  
Cancer Genome Atlas ◽  
Stimulating Factor ◽  
Independent Adverse Prognostic Factor

Interleukin 34 (IL-34), an additional ligand of the colony-stimulating factor-1 receptor (CSF-1R), promotes the secretion of pro-inflammatory cytokines and stimulates NF-κB and JNK-related signaling pathways. However, the potential mechanism and prognostic value of IL-34 in lung adenocarcinoma (LUAD) remain obscure. In this study, IL-34 was found to be downregulated in LUAD tissues compared with para-carcinoma tissues, and loss of IL-34 expression was correlated with shorter overall survival (OS), which was validated by bioinformatics\ analysis in TCGA (The Cancer Genome Atlas) cohort and immunohistochemical analysis in the NTU (Nantong University) cohort, respectively. Subsequently, loss of IL-34 promotes negative regulation of the immune system and inhibits the infiltration of immune cells. Moreover, IL-34 deficiency was shown to be an independent adverse prognostic factor for patients with LUAD, and subgroup analysis indicated that IL-34 might contribute to the stratified management of patients with LUAD. IL-34-based nomogram model significantly improved the accuracy of prognostic predictions for OS of patients with LUAD, both in the TCGA cohort and the NTU cohort. Taken together, our data suggested that loss of IL-34 expression is associated with poor prognosis and negative regulation of the immune system of patients with LUAD, contributing to the stratified management of patients with LUAD.

scholarly journals Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Lecai Xiong ◽  
Xiao Zhou ◽  
Yi Cai ◽  
Peng Dai ◽  
Jinping Zhao ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Poor Prognosis ◽  
Locally Advanced ◽  
Gene Signature ◽  
Treg Cells ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Prognostic Models ◽  
Competing Endogenous Rnas ◽  
Cancer Genome Atlas

Abstract Background: Lung adenocarcinoma (LUAD) is the most common form of non-small-cell lung cancer (NSCLC). Hypoxia has been found in 50 – 60% of locally advanced solid tumors and shown to be associated with poor prognosis in a variety of tumors, including NSCLC. The study focused on the hypoxia associated molecular hallmarks in LUAD.Methods: 15 hypoxia related genes were selected to define the hypoxia status of LUAD by ConsensusClusterPlus based on the data from The Cancer Genome Atlas(TCGA). Then, we investigate the immune status under different hypoxia status. Subsequently, we constructed prognostic models based on hypoxic-related differentially expressed genes (DEGs), identified hypoxia-related microRNAs, lncRNAs and mRNAs, and built a network based on the competing endogenous RNAs (ceRNAs) theory.Results: Two clusters (cluster1 and cluster2) were identified with different hypoxia status, cluster 1 was defined as the hypoxia subgroup, in which all 15 hypoxia-associated genes were upregulated. The infiltration of CD4 + T cells and Tfh cells was lower, while the infiltration of regulatory T (Treg) cells, the expression of PD-1/PD-L1 and TMB were higher in cluster 1, which indicated immunosuppressive status. Based on the DEGs, a risk signature containing 7 genes was established. Furthermore, three differentially expressed microRNAs (hsa-miR-9, hsa-miR-31, hsa-miR-196b) associated prognostic under different hypoxia clusters and its related mRNAs, lncRNAs were identified, then built a ceRNAs network.Conclusion: This study showed that hypoxia was associated with poor prognosis in LUAD and explored the potential mechanism from the perspective of gene signature and ceRNA theory.

scholarly journals Identification of novel autophagy-related lncRNAs associated with a poor prognosis of colon adenocarcinoma through bioinformatics analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dejun Wu ◽  
Zhenhua Yin ◽  
Yisheng Ji ◽  
Lin Li ◽  
Yunxin Li ◽  
...  
Keyword(s):  
High Risk ◽  
Poor Prognosis ◽  
Notch Pathway ◽  
Colon Adenocarcinoma ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Future Research ◽  
Risk Patients ◽  
Cancer Genome Atlas ◽  
Immune Score

AbstractLncRNAs play a pivotal role in tumorigenesis and development. However, the potential involvement of lncRNAs in colon adenocarcinoma (COAD) needs to be further explored. All the data used in this study were obtained from The Cancer Genome Atlas database, and all analyses were conducted using R software. Basing on the seven prognosis-related lncRNAs finally selected, we developed a prognosis-predicting model with powerful effectiveness (training cohort, 1 year: AUC = 0.70, 95% Cl = 0.57–0.78; 3 years: AUC = 0.71, 95% Cl = 0.6–0.8; 5 years: AUC = 0.76, 95% Cl = 0.66–0.87; validation cohort, 1 year: AUC = 0.70, 95% Cl = 0.58–0.8; 3 years: AUC = 0.73, 95% Cl = 0.63–0.82; 5 years: AUC = 0.68, 95% Cl = 0.5–0.85). The VEGF and Notch pathway were analyzed through GSEA analysis, and low immune and stromal scores were found in high-risk patients (immune score, cor =  − 0.15, P < 0.001; stromal score, cor =  − 0.18, P < 0.001) , which may partially explain the poor prognosis of patients in the high-risk group. We screened lncRNAs that are significantly associated with the survival of patients with COAD and possibly participate in autophagy regulation. This study may provide direction for future research.

scholarly journals High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiming Wang ◽  
Yan Cai ◽  
Xuewen Fu ◽  
Liang Chen
Keyword(s):  
Cervical Cancer ◽  
Poor Prognosis ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Cervical Cancer Cells ◽  
Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

scholarly journals CYSTM1: A Novel Biomarker for Hepatocellular Carcinoma Prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Jinguo Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Early Stage ◽  
Human Tumor ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background: The expression and molecular mechanism of cysteine rich transmembrane module containing 1 (CYSTM1) in human tumor cells remains unclear. The aim of this study was to determine whether CYSTM1 could be used as a potential prognostic biomarker for hepatocellular carcinoma (HCC).Methods: We first demonstrated the relationship between CYSTM1 expression and HCC in various public databases. Secondly, Kaplan–Meier analysis and Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CYSTM1 and the survival of HCC patients which data was downloaded in the cancer genome atlas (TCGA) database. Finally, we used the expression data of CYSTM1 in TCGA database to predict CYSTM1-related signaling pathways through bioinformatics analysis.Results: The expression level of CYSTM1 in HCC tissues was significantly correlated with T stage (p = 0.039). In addition, Kaplan–Meier analysis showed that the expression of CYSTM1 was significantly associated with poor prognosis in patients with early-stage HCC (p = 0.003). Multivariate analysis indicated that CYSTM1 is a potential predictor of poor prognosis in HCC patients (p = 0.036). The results of biosynthesis analysis demonstrated that the data set of CYSTM1 high expression was mainly enriched in neurodegeneration and oxidative phosphorylation pathways.Conclusion: CYSTM1 is an effective biomarker for the prognosis of patients with early-stage HCC and may play a key role in the occurrence and progression of HCC.

Identification of predictive biomarker for immunotherapy by associating with CD8+T cell Infiltration in lung adenocarcinoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e21177-e21177
Author(s):  
Puyuan Xing ◽  
Teng Li ◽  
Han Wang ◽  
Lin Yang ◽  
Guoqiang Wang ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Predictive Biomarkers ◽  
Tumor Infiltrating Lymphocytes ◽  
Predictive Performance ◽  
Predictive Biomarker ◽  
Pooled Analysis ◽  
The Cancer Genome Atlas ◽  
T Cell Infiltration ◽  
Or Groups ◽  
Cancer Genome Atlas

e21177 Background: Tumor immune microenvironment (TIME) has been proved associated with response to immunotherapy(I/O). We hypothesized that screening potential mutation pattern which could significantly impact the tumor infiltrating lymphocytes(TILs) can help us to identify predictive biomarkers for I/O in Lung adenocarcinoma(LUAD). Methods: Multiple-dimensional data from The Cancer Genome Atlas LUAD cohort (n = 514) was used for building a mathematical model beween mutation signature and CD8+TIL score (based on MCP-counter). An independent public validation cohort (cohort 1: LUAD, n = 598) were used to assess the immunotherapeutic predictive performance of the potential mutation patterns. Results: Top 100 gene associated with CD8+TIL score were selected based on MC+ model which can provides the minimum non-convexity of the penalized loss given the level of bias. Seven TIME genes (SPTA1 coef 0.09; MET coef 0.02; HSD3B1 coef -0.00; STAT4 coef -0.01; EGFR coef -0.08; PIK3CB coef -0.08; KEAP1 coef -0.24) were generated by taking the intersection of the top 100 mutant genes and FoundationOne (F1) CDx NGS 315 genes panel and verified in cohort 1. Survival analysis showed that SPTA1mt was the only one that associated with both significantly longer PFS (median PFS 3.15 vs 2.89 months; HR 0.65; 95% CI 0.45 to 0.93; p = 0.02) and OS (median PFS 15.08 vs 7.36 months; HR 0.59; 95% CI 0.40 to 0.88; p = 0.01) for patients who received I/O compared with chemotherapy(CT) among seven TIME genes. In order to test our hypothesis fully, a pooled analysis of SPTA1mt (a core positive predictors of CD8+TILs) and KEAP1mt (a core negative predictors for CD8+TILs ) were conducted and yielded that co occurrence of SPTA1mt and KEAP1mt had a compound effects for TIME. The validation showed that co mutation with SPTA1mt was accompanied by an decrease HR for I/O vs. CT in both PFS (HR S+K vs. K only 0.59 vs 1.56) and OS (HR S+K vs. K only 0.39 vs 0.80) for KEAP1mt patients. Conclusions: Our data show that it is feasible to identify individuals or groups of individual with specific mutations to immunotherapy responses from TIME view. SPTA1mt was a core predictors for higher CD8+ TILs and can be identified as a predictive biomarker for benefit from I/O compared with CT. Prospective studies are warranted for further investigation.

scholarly journals Deciphering N6-Methyladenosine-Related Genes Signature to Predict Survival in Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jie Zhu ◽  
Min Wang ◽  
Daixing Hu
Keyword(s):  
Lung Adenocarcinoma ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Lasso Regression ◽  
Gene Expressions ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Selection Operator ◽  
Cox Analysis

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death. Among these, lung adenocarcinoma (LUAD) accounts for most cases. Due to the improvement of precision medicine based on molecular characterization, the treatment of LUAD underwent significant changes. With these changes, the prognosis of LUAD becomes diverse. N6-methyladenosine (m6A) is the most predominant modification in mRNAs, which has been a research hotspot in the field of oncology. Nevertheless, little has been studied to reveal the correlations between the m6A-related genes and prognosis in LUAD. Thus, we conducted a comprehensive analysis of m6A-related gene expressions in LUAD patients based on The Cancer Genome Atlas (TCGA) database by revealing their relationship with prognosis. Different expressions of the m6A-related genes in tumor tissues and non-tumor tissues were confirmed. Furthermore, their relationship with prognosis was studied via Consensus Clustering Analysis, Principal Components Analysis (PCA), and Least Absolute Shrinkage and Selection Operator (LASSO) Regression. Based on the above analyses, a m6A-based signature to predict the overall survival (OS) in LUAD was successfully established. Among the 479 cases, we found that most of the m6A-related genes were differentially expressed between tumor and non-tumor tissues. Six genes, HNRNPC, METTL3, YTHDC2, KIAA1429, ALKBH5, and YTHDF1 were screened to build a risk scoring signature, which is strongly related to the clinical features pathological stages (p<0.05), M stages (p<0.05), T stages (p < 0.05), gender (p=0.04), and survival outcome (p=0.02). Multivariate Cox analysis indicated that risk value could be used as an independent prognostic factor, revealing that the m6A-related genes signature has great predictive value. Its efficacy was also validated by data from the Gene Expression Omnibus (GEO) database.

scholarly journals The Prediction and Prognostic Significance of INPP5K Expression in Patients with Liver Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ruobing Wang ◽  
Yan Jiao ◽  
Yanqing Li ◽  
Siyang Ye ◽  
Guoqiang Pan ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Mrna Expression ◽  
Poor Prognosis ◽  
Prognostic Significance ◽  
The Cancer Genome Atlas ◽  
Inositol Polyphosphate ◽  
Chi Square ◽  
Cancer Genome Atlas ◽  
Poor Outcomes ◽  
The Relationship

Liver cancer is a devastating disease for humans with poor prognosis. Although the survival rate of patients with liver cancer has improved in the past decades, the recurrence and metastasis of liver cancer are still obstacles for us. Inositol polyphosphate-5-phosphatase K (INPP5K) belongs to the family of phosphoinositide 5-phosphatases (PI 5-phosphatases), which have been reported to be associated with cell migration, polarity, adhesion, and cell invasion, especially in cancers. However, there have been few studies on the correlation of INPP5K and liver cancer. In this study, we explored the prognostic significance of INPP5K in liver cancer through bioinformatics analysis of data collected from The Cancer Genome Atlas (TCGA) database. Chi-square and Fisher exact tests were used to evaluate the relationship between INPP5K expression and clinical characteristics. Our results showed that low INPP5K expression was correlated with poor outcomes in liver cancer patients. Univariate and multivariate Cox analyses demonstrated that low INPP5K mRNA expression played a significant role in shortening overall survival (OS) and relapse-free survival (RFS), which might serve as the useful biomarker and prognostic factor for liver cancer. In conclusion, low INPP5K mRNA expression is an independent risk factor for poor prognosis in liver cancer.

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