Identification of a Pyroptosis-Related Gene Signature for Prediction of Overall Survival in Lung Adenocarcinoma

Pyroptosis is a kind of programmed cell death that is characterized by inflammation. However, the expression of pyroptosis-related genes and their connection with prognosis in lung adenocarcinoma (LUAD) remain unknown. The aim of this study is to create and validate a LUAD prediction signature based on genes associated with pyroptosis. The TCGA and GEO were used to collect gene sequencing data and clinical information for LUAD samples. To identify patients with LUAD from the TCGA cohort, consensus clustering by pyroptosis-related genes was employed. Our prognostic model was constructed using LASSO-Cox analysis after Cox regression using differentially expressed genes. To predict patient survival, we created a seven-mRNA signature. Additionally, reliability and validity were established in the GEO cohort. To assess its diagnostic and prognostic usefulness, an integrated bioinformatics method was used. Using a risk score with varying overall survival (OS) in two cohorts (all p < 0.001 ), a seven-gene signature was developed to categorize patients into two risk categories. The signature was shown to be an independent predictor of LUAD using multivariate regression analysis. The signature was linked to a variety of immune cell subtypes according to a study of immune cell infiltration. We constructed a signature consisting of seven genes as a robust biomarker with potential for clinical use in risk stratification and OS prediction in LUAD patients, as well as a potential indicator of immunotherapy in LUAD.

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Prognostic Nomogram Based on Circular RNA-Associated Competing Endogenous RNA Network for Patients with Lung Adenocarcinoma

Oxidative Medicine and Cellular Longevity ◽

10.1155/2021/9978206 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Yang Li ◽

Rongrong Sun ◽

Rui Li ◽

Yonggang Chen ◽

He Du

Keyword(s):

Overall Survival ◽

Regression Analysis ◽

Lung Adenocarcinoma ◽

Regulatory Mechanism ◽

Cox Regression ◽

Gene Signature ◽

Differentially Expressed ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Cerna Network

Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function and application of circRNAs in lung adenocarcinoma (LUAD) are still unknown. In this study, we constructed a circRNA-associated competitive endogenous RNA (ceRNA) network to investigate the regulatory mechanism of LUAD procession and further constructed a prognostic signature to predict overall survival for LUAD patients. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were selected to construct the ceRNA network. Based on the TargetScan prediction tool and Pearson correlation coefficient, we constructed a circRNA-associated ceRNA network including 11 DEcircRNAs, 8 DEmiRNAs, and 49 DEmRNAs. GO and KEGG enrichment indicated that the ceRNA network might be involved in the regulation of GTPase activity and endothelial cell differentiation. After removing the discrete points, a PPI network containing 12 DEmRNAs was constructed. Univariate Cox regression analysis showed that three DEmRNAs were significantly associated with overall survival. Therefore, we constructed a three-gene prognostic signature for LUAD patients using the LASSO method in the TCGA-LUAD training cohort. By applying the signature, patients could be categorized into the high-risk or low-risk subgroups with significant survival differences (HR: 1.62, 95% CI: 1.12-2.35, log-rank p = 0.009 ). The prognostic performance was confirmed in an independent GEO cohort (GSE42127, HR: 2.59, 95% CI: 1.32-5.10, log-rank p = 0.004 ). Multivariate Cox regression analysis proved that the three-gene signature was an independent prognostic factor. Combining the three-gene signature with clinical characters, a nomogram was constructed. The primary and external verification C -indexes were 0.717 and 0.716, respectively. The calibration curves for the probability of 3- and 5-year OS showed significant agreement between nomogram predictions and actual observations. Our findings provided a deeper understanding of the circRNA-associated ceRNA regulatory mechanism in LUAD pathogenesis and further constructed a useful prognostic signature to guide personalized treatment of LUAD patients.

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Prognostic Significance of Gene Signature of Tertiary Lymphoid Structures in Patients With Lung Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.693234 ◽

2021 ◽

Vol 11 ◽

Author(s):

Hong Feng ◽

Fujun Yang ◽

Lihong Qiao ◽

Kai Zhou ◽

Junfei Wang ◽

...

Keyword(s):

Overall Survival ◽

Lung Adenocarcinoma ◽

Immune Cell ◽

Prognostic Significance ◽

Gene Signature ◽

Driver Gene ◽

Immune Microenvironment ◽

High Group ◽

Tertiary Lymphoid Structures ◽

Lymphoid Structures

BackgroundLung adenocarcinoma (LUAD) is a highly mortal cancer. Tertiary lymphoid structures (TLS) are ectopic lymphoid organs with similar morphological and molecular characters to secondary lymphoid organ. The aim of this study is to investigate the prognostic effect of a gene signature associated with TLSs, including B-cell-specific genes.MethodsClinical data of 515 LUAD patients in the TGCA cohort were used to examine the relationship of TLS signature with immune microenvironment, tumor mutational burden (TMB), and driver gene mutations. Patients were divided into the TLS signature high group and TLS signature low group, and comparative analysis of survival and its influencing factors between the two groups was performed. The resulting data were then validated in the GSE37745 cohort.ResultsTLS signature high group had significantly better overall survival (OS) and progression-free interval (PFI) as well as significantly higher infiltration of immune cell subsets, cancer immune cycle (CIC) signature except for immunogram score2 (IGS2), and expression of major checkpoint genes than the TLS signature low group. Notably, while TLS signature was not markedly associated with TMB and mutation frequencies of driver genes, there were significant differences in overall survival of patients with given mutation status of EGFR, KRAS, BRAF and TP53 genes between the TLS signature high and low groups.ConclusionThis study provided evidence that LUAD patients with high TLS signature had a favorable immune microenvironment and better prognosis, suggesting that TLS signature is an independent positive prognostic factor for LUAD patients.

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A Novel Ferroptosis-Related Gene Signature Predicts Overall Survival of Breast Cancer Patients

Biology ◽

10.3390/biology10020151 ◽

2021 ◽

Vol 10 (2) ◽

pp. 151

Author(s):

Haifeng Li ◽

Lu Li ◽

Cong Xue ◽

Riqing Huang ◽

Anqi Hu ◽

...

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Prediction Model ◽

Risk Score ◽

Cox Regression ◽

Gene Prediction ◽

Clinical Information ◽

Risk Groups ◽

Gene Signature ◽

Breast Cancer Patients

Breast cancer is the second leading cause of death in women, thus a reliable prognostic model for overall survival (OS) in breast cancer is needed to improve treatment and care. Ferroptosis is an iron-dependent cell death. It is already known that siramesine and lapatinib could induce ferroptosis in breast cancer cells, and some ferroptosis-related genes were closely related with the outcomes of treatments regarding breast cancer. The relationship between these genes and the prognosis of OS remains unclear. The data of gene expression and related clinical information was downloaded from public databases. Based on the TCGA-BRCA cohort, an 8-gene prediction model was established with the least absolute shrinkage and selection operator (LASSO) cox regression, and this model was validated in patients from the METABRIC cohort. Based on the median risk score obtained from the 8-gene model, patients were stratified into high- or low-risk groups. Cox regression analyses identified that the risk score was an independent predictor for OS. The findings from CIBERSORT and ssGSEA presented noticeable differences in enrichment scores for immune cells and pathways between the abovementioned two risk groups. To sum up, this prediction model has potential to be widely applied in future clinical settings.

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Identification of a circadian gene signature that predicts overall survival in lung adenocarcinoma

PeerJ ◽

10.7717/peerj.11733 ◽

2021 ◽

Vol 9 ◽

pp. e11733

Author(s):

Xinliang Gao ◽

Mingbo Tang ◽

Suyan Tian ◽

Jialin Li ◽

Wei Liu

Keyword(s):

Overall Survival ◽

Regression Analysis ◽

Lung Adenocarcinoma ◽

Circadian Clock ◽

Cox Regression ◽

Gene Signature ◽

Differentially Expressed ◽

Circadian Gene ◽

Cox Regression Analysis ◽

Circadian Genes

Background Lung adenocarcinoma (LUAD) is one of the most common subtypes of lung cancer which is the leading cause of death in cancer patients. Circadian clock disruption has been listed as a likely carcinogen. However, whether the expression of circadian genes affects overall survival (OS) in LUAD patients remains unknown. In this article, we identified a circadian gene signature to predict overall survival in LUAD. Methods RNA sequencing (HTSeq-FPKM) data and clinical characteristics were obtained for a cohort of LUAD patients from The Cancer Genome Atlas (TCGA). A multigene signature based on differentially expressed circadian clock-related genes was generated for the prediction of OS using Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and externally validated using the GSE72094 dataset from the GEO database. Results Five differentially expressed genes (DEGs) were identified to be significantly associated with OS using univariate Cox proportional regression analysis (P < 0.05). Patients classified as high risk based on these five DEGs had significantly lower OS than those classified as low risk in both the TGCA cohort and GSE72094 dataset (P < 0.001). Multivariate Cox regression analysis revealed that the five-gene-signature based risk score was an independent predictor of OS (hazard ratio > 1, P < 0.001). Receiver operating characteristic (ROC) curves confirmed its prognostic value. Gene set enrichment analysis (GSEA) showed that Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to cell proliferation, gene damage repair, proteasomes, and immune and autoimmune diseases were significantly enriched. Conclusion A novel circadian gene signature for OS in LUAD was found to be predictive in both the derivation and validation cohorts. Targeting circadian genes is a potential therapeutic option in LUAD.

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Development and External Validation of a Novel Immune Checkpoint–Related Gene Signature for Prediction of Overall Survival in Hepatocellular Carcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2020.620765 ◽

2021 ◽

Vol 7 ◽

Author(s):

Enfa Zhao ◽

Shimin Chen ◽

Ying Dang

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Immune Checkpoint ◽

Immune Cell ◽

Cox Regression ◽

Expression Profiles ◽

External Validation ◽

Gene Signature ◽

Cancer Genome ◽

Related Gene

Objective: The purpose of this study was to develop and validate a novel immune checkpoint–related gene signature for prediction of overall survival (OS) in hepatocellular carcinoma (HCC).Methods: mRNA expression profiles and clinical follow-up information were obtained in the International Cancer Genome Consortium database. An external dataset from The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma database was used to validate the results. The univariate and multivariate Cox regression analyses were performed based on the differentially expressed genes. We generated a four-mRNA signature to predict patient survival. Furthermore, the reliability and validity were validated in TCGA cohort. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value.Results: A four-gene (epidermal growth factor, mutated in colorectal cancer, mitogen-activated protein kinase kinase 2, and NRAS proto-oncogene, GTPase) signature was built to classify patients into two risk groups using a risk score with different OS in two cohorts (all P < 0.0001). Multivariate regression analysis demonstrated the signature was an independent predictor of HCC. Furthermore, the signature presented an excellent diagnostic power in differentiating HCC and adjacent tissues. Immune cell infiltration analysis revealed that the signature was associated with a number of immune cell subtypes.Conclusion: We identified a four–immune checkpoint–related gene signature as a robust biomarker with great potential for clinical application in risk stratification and OS prediction in HCC patients and could be a potential indicator of immunotherapy in HCC. The diagnostic signature had been validated to accurately distinguish HCC from adjacent tissues.

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Scoring System Based on RNA Modification Writer-Related Genes to Predict Overall Survival and Therapeutic Response in Bladder Cancer

Frontiers in Immunology ◽

10.3389/fimmu.2021.724541 ◽

2021 ◽

Vol 12 ◽

Author(s):

Pu Zhang ◽

Zijian Liu ◽

Decai Wang ◽

Yunxue Li ◽

Yifei Xing ◽

...

Keyword(s):

Overall Survival ◽

Bladder Cancer ◽

Immune Cell ◽

Cox Regression ◽

Gene Signature ◽

Rna Modification ◽

Lasso Regression ◽

Related Gene ◽

Mutation Burden ◽

Selection Operator

IntroductionIt’s widely reported the “writer” enzymes mediated RNA adenosine modifications which is known as a crucial mechanism of epigenetic regulation in development of tumor and the immunologic response in many kinds of cancers. However, the potential roles of these writer genes in the progression of bladder cancer (BLCA) remain unclear.Materials and MethodsWe comprehensively described the alterations of 26 RNA modification writer genes in BLCA from the genetic and transcriptional fields and identified writer-related genes from four independent datasets. Utilizing least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression, we constructed a ten writer-related gene signature. After that, we confirmed the predictive and prognostic value of this signature on another six independent datasets and established a nomogram to forecast the overall survival (OS) and mortality odds of BLCA patients clinically.ResultsThe writer-related genes signature showed good performance in predicting the OS for BLCA patients. Moreover, the writer-related gene signature was related to EMT-related pathways and immune characteristics. Furthermore, the immune cell infiltration levels of CD8 T cells, cytotoxic cells, M1/2 macrophage cells and tumor mutation burden might be able to predict which patients will benefit from immunotherapy. This could also be reflected by the writer-related gene signature.ConclusionsThis signature might play an important role in precision individualized immunotherapy. The present work highlights the crucial clinical implications of RNA modifications and may help developing individualized therapeutic strategies for patients with BLCA.

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Development and Validation of a Seven-Gene Signature for Predicting the Prognosis of Lung Adenocarcinoma

BioMed Research International ◽

10.1155/2020/1836542 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Yingqing Zhang ◽

Xiaoping Zhang ◽

Xiaodong Lv ◽

Ming Zhang ◽

Xixi Gao ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Risk Score ◽

Cox Regression ◽

Risk Group ◽

Clinical Information ◽

R Package ◽

Tumor Stage ◽

Gene Signature ◽

High Risk Group ◽

Kaplan Meier

Background. Prognosis is a main factor affecting the survival of patients with lung adenocarcinoma (LUAD), yet no robust prognostic model of high effectiveness has been developed. This study is aimed at constructing a stable and practicable gene signature-based model via bioinformatics methods for predicting the prognosis of LUAD sufferers. Methods. The mRNA expression data were accessed from the TCGA-LUAD dataset, and paired clinical information was collected from the GDC website. R package “edgeR” was employed to select the differentially expressed genes (DEGs), which were then used for the construction of a gene signature-based model via univariate COX, Lasso, and multivariate COX regression analyses. Kaplan-Meier and ROC survival analyses were conducted to comprehensively evaluate the performance of the model in predicting LUAD prognosis, and an independent dataset GSE26939 was accessed for further validation. Results. Totally, 1,655 DEGs were obtained, and a 7-gene signature-based risk score was developed and formulated as risk_score=0.000245∗NTSR1+7.13E−05∗RHOV+0.000505∗KLK8+7.01E−05∗TNS4+0.000288∗C1QTNF6+0.00044∗IVL+0.000161∗B4GALNT2. Kaplan-Meier survival curves revealed that the survival rate of patients in the high-risk group was lower in both the TCGA-LUAD dataset and GSE26939 relative to that of patients in the low-risk group. The relationship between the risk score and clinical characteristics was further investigated, finding that the model was effective in prognosis prediction in the patients with different age (age>65, age<65) and TNM stage (N0&N1, T1&T2, and tumor stage I/II). In sum, our study provides a robust predictive model for LUAD prognosis, which boosts the clinical research on LUAD and helps to explore the mechanism underlying the occurrence and progression of LUAD.

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Ferroptosis-Related Gene Signature and Patterns of Immune Infiltration Predict the Overall Survival in Patients With Lung Adenocarcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.692530 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yuxuan Wang ◽

Weikang Chen ◽

Minqi Zhu ◽

Lei Xian

Keyword(s):

Overall Survival ◽

Lung Adenocarcinoma ◽

Immune Cells ◽

Cox Regression ◽

Expression Profiles ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Related Gene ◽

Cox Regression Analysis ◽

Prognosis Prediction

Background: Lung adenocarcinoma (LUAD) is a malignant tumor with high heterogeneity and poor prognosis. Ferroptosis, a form of regulated cell-death–related iron, has been proven to trigger inflammation-associated immunosuppression in the tumor microenvironment, which promotes tumor growth. Therefore, the clinical prognostic value of ferroptosis-related genes in LUAD needs to be further explored.Method: In this study, we downloaded the mRNA expression profiles and corresponding clinical data of LUAD patients from the Cancer Genome Atlas database. The least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to construct ferroptosis-related gene signature. Based on these, we established the nomograms for prognosis prediction and validated the model in the GSE72094 dataset. The cell type was identified using the CIBERSORT algorithm for estimating relative subsets of RNA transcripts, which was then used to screen significant tumor immune-infiltrating cells associated with the LUAD prognosis prediction model. Subsequently, we applied co-expression analysis to reveal the relationship between ferroptosis-related genes and significant immune cells.Results: The univariate COX regression analysis showed that 20 genes were associated with the overall survival (OS) as prognostic differentially expressed genes (DEGs) (FDR <0.05). Patients were divided into two risk groups using a 13-gene signature, with the high-risk group having a significantly worse OS than their low-risk counterparts (p < 0.001). We used receiver operating characteristic (ROC) curve analysis to confirm the predictive capacity of the signature. Besides, we identified seven pairs of ferroptosis-related genes and tumor-infiltrating immune cells associated with the prognosis of LUAD patients.Conclusion: In this study, we construct a ferroptosis-related gene signature that can be used for prognostic prediction in LUAD. In addition, we reveal a potential connection between ferroptosis and tumor-infiltrating immune cells.

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A Novel Immune-Related Prognostic Model for Response to Immunotherapy and Survival in Patients With Lung Adenocarcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.651406 ◽

2021 ◽

Vol 9 ◽

Author(s):

Yujia Zheng ◽

He Tian ◽

Zheng Zhou ◽

Chu Xiao ◽

Hengchang Liu ◽

...

Keyword(s):

Overall Survival ◽

Cell Death ◽

Programmed Cell Death ◽

Lung Adenocarcinoma ◽

Regression Model ◽

Immune Cells ◽

Cox Regression ◽

Consensus Clustering ◽

Cox Regression Model ◽

Immune Infiltration

Lung adenocarcinoma is one of the most malignant diseases worldwide. The immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) and programmed cell death-ligand 1 (PD-L1) have changed the paradigm of lung cancer treatment; however, there are still patients who are resistant. Further exploration of the immune infiltration status of lung adenocarcinoma (LUAD) is necessary for better clinical management. In our study, the CIBERSORT method was used to calculate the infiltration status of 22 immune cells in LUAD patients from The Cancer Genome Atlas (TCGA). We clustered LUAD based on immune infiltration status by consensus clustering. The differentially expressed genes (DEGs) between cold and hot tumor group were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Last, we constructed a Cox regression model. We found that the infiltration of M0 macrophage cells and follicular helper T cells predicted an unfavorable overall survival of patients. Consensus clustering of 22 immune cells identified 5 clusters with different patterns of immune cells infiltration, stromal cells infiltration, and tumor purity. Based on the immune scores, we classified these five clusters into hot and cold tumors, which are different in transcription profiles. Hot tumors are enriched in cytokine–cytokine receptor interaction, while cold tumors are enriched in metabolic pathways. Based on the hub genes and prognostic-related genes, we developed a Cox regression model to predict the overall survival of patients with LUAD and validated in other three datasets. In conclusion, we developed an immune-related signature that can predict the prognosis of patients, which might facilitate the clinical application of immunotherapy in LUAD.

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Hypoxia-Related Immune Gene Signature Predicting Prognosis in Patients With Hepatocellular Carcinoma

10.21203/rs.3.rs-476159/v1 ◽

2021 ◽

Author(s):

Lingshan Zhou ◽

Yuan Yang ◽

Min Liu ◽

Rong Liu ◽

Man Ren ◽

...

Keyword(s):

Immune Cell ◽

Cox Regression ◽

Biological Significance ◽

Gene Signature ◽

Chemotherapeutic Agents ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Immune Gene ◽

Consensus Clustering

Abstract BackgroundHepatocellular carcinoma (HCC) remains a global health challenge. Increasing evidence indicates that hypoxia is crucial in the evolution and progression of HCC by regulating the tumor immune microenvironment. The present study aimed to construct a prognostic relevant hypoxia-related immune gene (HRIG) signature. MethodsWe analyzed the expression profile of the 163 HRIGs and clinical information of 371 patients with HCC obtained from The Cancer Genome Atlas (TCGA). Then, consensus clustering analysis was performed to divide HCC patients into clusters 1 and 2 based on the HRIG expression. Subsequently, A multigene signature was constructed by Least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Then, we evaluated the prognostic capability of this signature by Kaplan-Meier analysis, univariate Cox regression and multivariate Cox regression. The prognostic value of the signature was validated in the International Cancer Genome Consortium (ICGC) database. Furthermore, the functional enrichment analyses were preformed to elucidate their biological significance. Finally, we evaluated the infiltration of immune cells and the sensitivity of administrating chemotherapeutic agents.ResultsA total of 37 prognosis-related HRIGs were obtained. Subsequently, we constructed an 8-gene signature on the basis of prognosis-related HRIGs, which had a good performance in predicting the overall survival of patients with HCC. In addition, the signature expressed robust when validated in ICGC. The results revealed that these genes involved in some of the HCC-related pathways and was associated with the infiltration of immune cell subtypes. More importantly, the identified model was linked to the sensitivity of some chemotherapeutic agents. ConclusionsHRIG signature is an effective predictor for the prognosis of patients with HCC.

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