A lipid metabolism-related genes prognosis biomarker associated with the tumor immune microenvironment in colorectal carcinoma

Abstract Background and aim Lipid metabolic reprogramming is considered to be a new hallmark of malignant tumors. The purpose of this study was to explore the expression profiles of lipid metabolism-related genes (LMRG) in colorectal cancer (CRC). Methods The lipid metabolism statuses of 500 CRC patients from the Cancer Genome Atlas (TCGA) and 523 from the Gene Expression Omnibus (GEO GSE39582) database were analyzed. The risk signature was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression. Results A novel four-LMRG signature (PROCA1, CCKBR, CPT2, and FDFT1) was constructed to predict clinical outcomes in CRC patients. The risk signature was shown to be an independent prognostic factor for CRC and was associated with tumour malignancy. Principal components analysis demonstrated that the risk signature could distinguish between low- and high-risk patients. There were significantly differences in abundances of tumor-infiltrating immune cells and mutational landscape between the two risk groups. Patients in the low-risk group were more likely to have higher tumor mutational burden, stem cell characteristics, and higher PD-L1 expression levels. Furthermore, a genomic-clinicopathologic nomogram was established and shown to be a more effective risk stratification tool than any clinical parameter alone. Conclusions This study demonstrated the prognostic value of LMRG and showed that they may be partially involved in the suppressive immune microenvironment formation.

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Identification of a Hypoxia-Related Signature for Predicting Prognosis and the Immune Microenvironment in Bladder Cancer

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.613359 ◽

2021 ◽

Vol 8 ◽

Author(s):

Minxiao Jiang ◽

Liangliang Ren ◽

Yuanlei Chen ◽

Huan Wang ◽

Haiyang Wu ◽

...

Keyword(s):

Bladder Cancer ◽

Cox Regression ◽

Expression Profiles ◽

Clinical Information ◽

Gene Expression Omnibus ◽

High Accuracy ◽

The Cancer Genome Atlas ◽

Immune Microenvironment ◽

Cox Regression Analysis ◽

Highly Correlated

Accumulating evidence indicates that hypoxia is highly associated with bladder cancer genesis, progression, and immune microenvironment. Nevertheless, few studies have identified the role of hypoxia-related genes as a prognostic signature in bladder cancer. This study aimed to establish a hypoxia-related signature with high accuracy for prognosis and immune microenvironment prediction in bladder cancer. We obtained expression profiles and clinical information from Gene Expression Omnibus and The Cancer Genome Atlas. Then the univariate Cox regression, random survival forest algorithm, and multivariate Cox regression analysis were conducted to identify the core genes and four hypoxia-related genes (ANXA2, GALK1, COL5A1, and HS3ST1) were selected to construct the signature. Kaplan-Meier survival analysis demonstrated that patients with a low-risk score had a higher disease-specific survival rate (p < 0.0001). The areas under the curve of the signature were 0.829 at 1 year, 0.869 at 3 years, and 0.848 at 5 years, respectively. Additionally, we found this hypoxia-related signature was highly correlated with tumor immune microenvironment and had the potential to predict the efficacy of immunotherapy. In summary, our study developed a hypoxia-related signature, which had high accuracy for prognosis prediction and the potential to guide the immunotherapy for bladder cancer patients.

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A Lipid Metabolism-Related Genes Prognosis Biomarker Associated With The Tumor Immune Microenvironment in Colorectal Carcinoma

10.21203/rs.3.rs-145179/v1 ◽

2021 ◽

Author(s):

Chao YANG ◽

Shuoyang Huang ◽

Yongbin ZHENG ◽

Fengyu CAO

Keyword(s):

Lipid Metabolism ◽

High Risk ◽

Risk Score ◽

Cox Regression ◽

Expression Profiles ◽

Low Risk ◽

Metabolic Reprogramming ◽

Immune Microenvironment ◽

Potential Biomarker ◽

Tumor Immune Microenvironment

Abstract Background: Lipid metabolic reprogramming was considered as a new hallmark of malignant tumors. It has been reported to play a crucial biological role in cell proliferation, energy homeostasis and signal-transduction. However, the important value of lipid metabolism-related genes(LMRGs) in prognostic prediction and the tumor immune microenvironment has not been explored by large sample studies in colorectal cancer(CRC). Methods: In this study, the lipid metabolism status of 1086 CRC samples was analyzed using RNA expression profiles and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, of which the former was determined as training set and the latter as validation set. The risk signature was constructed by the univariate Cox regression and Least Absolute Shrinkage and Selection Operator(LASSO) COX regression. The patients were stratified into high- and low-risk groups according to the median value of the risk score. Immune and mutation landscape between low- and high-risk CRC patients were also explored. Additionally, we established a nomogram integrating the risk signature and clinical factors to improve risk assessment of CRC patients. Results: A four LMRGs signature, including PROCA1, CCKBR, CPT2 and FDFT1, was constructed to predict the prognosis of CRC. The risk signature as an independent prognostic factor for CRC was associated with a variety of parameters. Survival analysis showed that patients with low risk score had a better prognosis. There were different immune landscapes between low and high-risk CRC patients, especially in monocytes, dendritic cells, M0 and M2-like macrophages. Patients in the low-risk group were more likely to have higher tumor mutation burden, stem cell characteristics and level of PD-L1 expression. In addition, it was found that genes that played crucial biological functions in tumorigenesis (including TP53, PI3K and MUC16) had significant differences in mutation frequency between two groups. Conclusion: A lipid metabolism-related risk signature for predicting the prognosis of CRC was identified in this study. Furthermore, this prognostic signature may be a potential biomarker for predicting the efficacy of chemotherapy and anti-PD-L1 therapy in CRC.

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Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

BMC Cancer ◽

10.1186/s12885-021-08173-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ping Yan ◽

Zuotian Huang ◽

Tong Mou ◽

Yunhai Luo ◽

Yanyao Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Malignant Tumors ◽

Expression Profiles ◽

Clinical Information ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

High Rate ◽

Competing Endogenous Rna ◽

Tissue Samples ◽

Potential Biomarkers

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

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Screening the genome for HCC-specific CpG methylation signatures as biomarkers for diagnosis and prognosis evaluation

BMC Medical Genomics ◽

10.1186/s12920-021-01015-9 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Rui-kun Zhang ◽

Jia-lin Liu

Keyword(s):

Cox Regression ◽

Malignant Tumors ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Survival Prediction ◽

Training Set ◽

Cpg Sites ◽

Diagnosis And Prognosis ◽

Patient Prognosis ◽

Prognosis Evaluation

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and invasive malignant tumors in the world. The change in DNA methylation is a key event in HCC. Methods Methylation datasets for HCC and 17 other types of cancer were downloaded from The Cancer Genome Atlas (TCGA). The CpG sites with large differences in methylation between tumor tissues and paracancerous tissues were identified. We used the HCC methylation dataset downloaded from the TCGA as the training set and removed the overlapping sites among all cancer datasets to ensure that only CpG sites specific to HCC remained. Logistic regression analysis was performed to select specific biomarkers that can be used to diagnose HCC, and two datasets—GSE157341 and GSE54503—downloaded from GEO as validation sets were used to validate our model. We also used a Cox regression model to select CpG sites related to patient prognosis. Results We identified 6 HCC-specific methylated CpG sites as biomarkers for HCC diagnosis. In the training set, the area under the receiver operating characteristic (ROC) curve (AUC) for the model containing all these sites was 0.971. The AUCs were 0.8802 and 0.9711 for the two validation sets from the GEO database. In addition, 3 other CpG sites were analyzed and used to create a risk scoring model for patient prognosis and survival prediction. Conclusions Through the analysis of HCC methylation datasets from the TCGA and Gene Expression Omnibus (GEO) databases, potential biomarkers for HCC diagnosis and prognosis evaluation were ascertained.

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ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

Cancer Cell International ◽

10.1186/s12935-021-02380-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Bai-Quan Qiu ◽

Xia-Hui Lin ◽

Song-Qing Lai ◽

Feng Lu ◽

Kun Lin ◽

...

Keyword(s):

Lung Cancer ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Malignant Tumors ◽

Expression Profiles ◽

The Cancer Genome Atlas ◽

Hub Genes ◽

Immune Infiltration ◽

Prognostic Effect ◽

Cancer Genome Atlas

Abstract Background Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study. Methods Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells. Results We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes. Conclusion Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

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Screening and Identifying m6A Regulators as an Independent Prognostic Biomarker in Pancreatic Cancer Based on The Cancer Genome Atlas Database

BioMed Research International ◽

10.1155/2021/5573628 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Bi Lin ◽

Yangyang Pan ◽

Dinglai Yu ◽

Shengjie Dai ◽

Hongwei Sun ◽

...

Keyword(s):

Pancreatic Cancer ◽

Cox Regression ◽

Malignant Tumors ◽

Expression Profiles ◽

Tumor Therapy ◽

Disease Free Survival ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas ◽

Genome Atlas

Background. Pancreatic cancer is one of the most malignant tumors of the digestive system, and its treatment has rarely progressed for the last two decades. Studies on m6A regulators for the past few years have seemingly provided a novel approach for malignant tumor therapy. m6A-related factors may be potential biomarkers and therapeutic targets. This research is focused on the gene characteristics and clinical values of m6A regulators in predicting prognosis in pancreatic cancer. Methods. In our study, we obtained gene expression profiles with copy number variation (CNV) data and clinical characteristic data of 186 patients with pancreatic cancer from The Cancer Genome Atlas (TCGA) portal. Then, we determined the alteration of m6a regulators and their correlation with clinicopathological features using the log-rank tests, Cox regression model, and chi-square test. Additionally, we validated the prognostic value of m6A regulators in the International Cancer Genome Consortium (ICGC). Results. The results suggested that pancreatic cancer patients with ALKBH5 CNV were associated with worse overall survival and disease-free survival than those with diploid genes. Additionally, upregulation of the writer gene ALKBH5 had a positive correlation with the activation of AKT pathways in the TCGA database. Conclusion. Our study not only demonstrated genetic characteristic changes of m6A-related genes in pancreatic cancer and found a strong relationship between the changes of ALKBH5 and poor prognosis but also provided a novel therapeutic target for pancreatic cancer therapy.

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Integrative Analysis of ceRNA Network Reveals Functional lncRNAs in Intrahepatic Cholangiocarcinoma

BioMed Research International ◽

10.1155/2019/2601271 ◽

2019 ◽

Vol 2019 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Dongkai Zhou ◽

Bingqiang Gao ◽

Qifan Yang ◽

Yang Kong ◽

Weilin Wang

Keyword(s):

Intrahepatic Cholangiocarcinoma ◽

Cox Regression ◽

Expression Profiles ◽

Adaptive Immune Response ◽

Gene Expression Omnibus ◽

Integrative Analysis ◽

The Cancer Genome Atlas ◽

Messenger Rnas ◽

Cox Regression Analysis ◽

Cerna Network

Intrahepatic cholangiocarcinoma (ICC) is the second most common lethal liver cancer worldwide. Currently, despite the latest developments in genomics and transcriptomics for ICC in recent years, the molecular pathogenesis promoting ICC remains elusive, especially in regulatory mechanisms of long noncoding RNAs (lncRNAs), which acts as competing endogenous RNA (ceRNA). In order to elucidate the molecular mechanism of functional lncRNA, expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were obtained from The Cancer Genome Atlas (TCGA) database and an integrative analysis of the ICC-associated ceRNA network was performed. Moreover, gene oncology enrichment analyses for the genes in the ceRNA network were implemented and novel prognostic biomarker lncRNA molecules were identified. In total, 6,738 differentially expressed mRNAs (DEmRNAs), 2,768 lncRNAs (DElncRNAs), and 173 miRNAs (DEmiRNAs) were identified in tumor tissues and adjacent nontumor ICC tissues with the thresholds of adjusted P<0.01 and logFC>2. An ICC-specific ceRNA network was successfully constructed with 30 miRNAs, 16 lncRNAs, and 80 mRNAs. Gene oncology enrichment analyses revealed that they were associated with the adaptive immune response, T cell selection and positive regulation of GTPase activity categories. Among the ceRNA networks, DElncRNAs ARHGEF26-AS1 and MIAT were found to be hub genes in underexpressed and overexpressed networks, respectively. Notably, univariate Cox regression analysis indicated that DElncRNAs HULC significantly correlated with overall survival (OS) in ICC patients (P value < 0.05), and an additional survival analysis for HULC was reconfirmed in an independent ICC cohort from the Gene Expression Omnibus (GEO) database. These findings contribute to a more comprehensive understanding of the ICC-specific ceRNA network and provide novel strategies for subsequent functional studies of lncRNAs in ICC.

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An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.685379 ◽

2021 ◽

Vol 9 ◽

Author(s):

Qian Xu ◽

Yurong Chen

Keyword(s):

Lung Adenocarcinoma ◽

Cox Regression ◽

Characteristic Curve ◽

Staging System ◽

Risk Groups ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Related Gene ◽

Net Benefit ◽

Cox Regression Analysis

Aging is an inevitable time-dependent process associated with a gradual decline in many physiological functions. Importantly, some studies have supported that aging may be involved in the development of lung adenocarcinoma (LUAD). However, no studies have described an aging-related gene (ARG)-based prognosis signature for LUAD. Accordingly, in this study, we analyzed ARG expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). After LASSO and Cox regression analyses, a six ARG-based signature (APOC3, EPOR, H2AFX, MXD1, PLCG2, and YWHAZ) was constructed using TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of overall survival (OS). Cox regression analysis indicated that the ARG signature was an independent prognostic factor in LUAD. A nomogram based on the ARG signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Moreover, to visualize the prediction results, we established a web-based calculator yurong.shinyapps.io/ARGs_LUAD/. Calibration plots showed good consistency between the prediction of the nomogram and actual observations. Receiver operating characteristic curve and decision curve analyses indicated that the ARG nomogram had better OS prediction and clinical net benefit than the staging system. Taken together, these results established a genetic signature for LUAD based on ARGs, which may promote individualized treatment and provide promising novel molecular markers for immunotherapy.

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A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer

BMC Cancer ◽

10.1186/s12885-021-08687-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yingchun Liang ◽

Fangdie Ye ◽

Chenyang Xu ◽

Lujia Zou ◽

Yun Hu ◽

...

Keyword(s):

Overall Survival ◽

Bladder Cancer ◽

Prognostic Value ◽

Cox Regression ◽

Risk Group ◽

Expression Profiles ◽

Risk Groups ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Prognosis Prediction

Abstract Background The effective treatment and prognosis prediction of bladder cancer (BLCA) remains a medical problem. Ferroptosis is an iron-dependent form of programmed cell death. Ferroptosis is closely related to tumour occurrence and progression, but the prognostic value of ferroptosis-related genes (FRGs) in BLCA remains to be further clarified. In this study, we identified an FRG signature with potential prognostic value for patients with BLCA. Methods The corresponding clinical data and mRNA expression profiles of BLCA patients were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to extract FRGs related to survival time, and a Cox regression model was used to construct a multigene signature. Both principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were performed for functional annotation. Results Clinical traits were combined with FRGs, and 15 prognosis-related FRGs were identified by Cox regression. High expression of CISD1, GCLM, CRYAB, SLC7A11, TFRC, ACACA, ZEB1, SQLE, FADS2, ABCC1, G6PD and PGD was related to poor survival in BLCA patients. Multivariate Cox regression was used to construct a prognostic model with 7 FRGs that divided patients into two risk groups. Compared with that in the low-risk group, the overall survival (OS) of patients in the high-risk group was significantly lower (P < 0.001). In multivariate regression analysis, the risk score was shown to be an independent predictor of OS (HR = 1.772, P < 0.01). Receiver operating characteristic (ROC) curve analysis verified the predictive ability of the model. In addition, the two risk groups displayed different immune statuses in ssGSEA and different distributed patterns in PCA. Conclusion Our research suggests that a new gene model related to ferroptosis can be applied for the prognosis prediction of BLCA. Targeting FRGs may be a treatment option for BLCA.

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Identification of prognostic alternative splicing events related to the immune microenvironment of hepatocellular carcinoma

Molecular Medicine ◽

10.1186/s10020-021-00294-3 ◽

2021 ◽

Vol 27 (1) ◽

Author(s):

Shanshan Yu ◽

Luya Cai ◽

Chuan Liu ◽

Ruihong Gu ◽

Lingyi Cai ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Alternative Splicing ◽

Cox Regression ◽

Malignant Tumors ◽

Prognostic Significance ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Immune Microenvironment ◽

The Impact

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, and its 5-year survival rate is less than 20%, despite various treatments being available. Increasing evidence indicates that alternative splicing (AS) plays a nonnegligible role in the formation and development of the tumor microenvironment (TME). However, the comprehensive analysis of the impact on prognostic AS events on immune-related perspectives in HCC is lacking but urgently needed. Methods The transcriptional data and clinical information of HCC patients were downloaded from TCGA (The Cancer Genome Atlas) database for calculating immune and stromal scores by ESTIMATE algorithm. We then divided patients into high/low score groups and explored their prognostic significance using Kaplan–Meier curves. Based on stromal and immune scores, differentially expressed AS events (DEASs) were screened and evaluated with functional enrichment analysis. Additionally, a risk score model was established by applying univariate and multivariate Cox regression analyses. Finally, gene set variation analysis (GSVA) was adopted to explore differences in biological behaviors between the high- and low-risk subgroups. Results A total of 370 HCC patients with complete and qualified corresponding data were included in the subsequent analysis. According to the results of ESTIMATE analysis, we observed that the high immune/stromal score group had a longer survival probability, which was significantly correlated with prognosis in HCC patients. In addition, 467 stromal/immune score-related DEASs were identified, and enrichment analysis revealed that DEASs were significantly enriched in pathways related to HCC tumorigenesis and the immune microenvironment. More importantly, the final prognostic signature containing 16 DEASs showed powerful predictive ability. Finally, GSVA demonstrated that activation of carcinogenic pathways and immune-related pathways in the high-risk group may lead to poor prognosis. Conclusions Collectively, these outcomes revealed prognostic AS events related to carcinogenesis and the immune microenvironment, which may yield new directions for HCC immunotherapy.

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