Characterization of METTL7B to Evaluate TME and Predict Prognosis by Integrative Analysis of Multi-Omics Data in Glioma

Glioma is the most common and aggressive type of primary brain malignant tumor with limited treatment approaches. Methyltransferase-like 7B (METTL7B) is associated with the pathogenesis of several diseases but is rarely studied in glioma. In this study, 1,493 glioma samples (data from our cohort, TCGA, and CGGA) expressing METTL7B were used to explore its prognostic value and mechanism in the immune microenvironment. Results showed that high expression of METTL7B is associated with poor prognosis and abundant immunosuppressive cells. Further, functional enrichment showed that METTL7B is involved in the negative regulation of immunity and carcinogenic signaling pathways. Moreover, a METTL7B-related prognostic signature constructed based on multi-omics showed a good prediction of the overall survival (OS) time of glioma patients. In conclusion, METTL7B is a potential prognostic biomarker. In addition, the prognostic prediction model constructed in this study can be used in clinical setups for the development of novel effective therapeutic strategies for glioma patients and improving overall survival.

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A Ferroptosis-Related Gene Model Predicts Prognosis and Immune Microenvironment for Cutaneous Melanoma

Frontiers in Genetics ◽

10.3389/fgene.2021.697043 ◽

2021 ◽

Vol 12 ◽

Author(s):

Congcong Xu ◽

Hao Chen

Keyword(s):

Cutaneous Melanoma ◽

Prognostic Model ◽

Cox Regression ◽

Tumor Biology ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Related Gene ◽

Immune Microenvironment ◽

Cancer Genome Atlas ◽

Prognostic Prediction

BackgroundCutaneous melanoma is a common but aggressive tumor. Ferroptosis is a recently discovered cell death with important roles in tumor biology. Nevertheless, the prognostic power of ferroptosis-linked genes remained unclear in cutaneous melanoma.MethodsCutaneous melanoma patients of TCGA (The Cancer Genome Atlas) were taken as the training cohort while GSE65904 and GSE22153 as the validation cohorts. Multifactor Cox regression model was used to build a prognostic model, and the performance of the model was assessed. Functional enrichment and immune infiltration analysis were used to clarify the mechanisms.ResultsA five ferroptosis-linked gene predictive model was developed. ALOX5 and GCH1 were illustrated as independent predictive factors. Functional assessment showed enriched immune-linked cascades. Immune infiltrating analysis exhibited the distinct immune microenvironment.ConclusionHerein, a novel ferroptosis-related gene prognostic model was built in cutaneous melanoma. This model could be used for prognostic prediction, and maybe helpful for the targeted and immunotherapies.

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Development of an Oxidative Phosphorylation-Related and Immune Microenvironment Prognostic Signature in Uterine Corpus Endometrial Carcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.753004 ◽

2021 ◽

Vol 9 ◽

Author(s):

Jinhui Liu ◽

Tian Chen ◽

Min Yang ◽

Zihang Zhong ◽

Senmiao Ni ◽

...

Keyword(s):

Overall Survival ◽

Oxidative Phosphorylation ◽

Endometrial Carcinoma ◽

Cox Regression ◽

Prognostic Signature ◽

Immune Microenvironment ◽

Uterine Corpus ◽

Chemotherapy Drugs ◽

Specific Subset ◽

Lower Expression

Background: As the fourth most common malignant tumors in women, uterine corpus endometrial carcinoma (UCEC) requires novel and reliable biomarkers for prognosis prediction to improve the overall survival. Oxidative phosphorylation (OXPHOS) is found to be strongly correlated with the progression of tumor. Here, we aimed to construct an OXPHOS-related and immune microenvironment prognostic signature to stratify UCEC patients for optimization of treatment strategies.Method: Prognosis-associated OXPHOS-related differentially expressed genes were identified by multivariable Cox regression from TCGA–UCEC cohort. Based on the candidate genes, an OXPHOS-related prognostic signature was constructed by the train set data and verified by the entire set. When integrated with relevant clinical characteristics, a nomogram was also created for clinical application. Through comparison of tumor microenvironment between different risk groups, the underlying mechanism of the model and the inner correlation between immune microenvironment and energy metabolism were further investigated.Results: An OXPHOS-related signature containing ATP5IF1, COX6B1, FOXP3, and NDUFB11 was constructed and had better predictive ability compared with other recently published signatures in UCEC. Patients with lower risk score showed higher immune cell infiltration, higher ESTIMATE score (p = 2.808E−18), lower tumor purity (p = 2.808E−18), higher immunophenoscores (IPSs) (p < 0.05), lower expression of mismatch repair (MMR) proteins (p < 0.05), higher microsatellite instability (MSI), lower expression of markers of N6-methyladenosine (m6A) mRNA methylation regulators, higher tumor mutation burden (TMB) (p = 1.278E−9), and more sensitivity to immune checkpoint blockade (ICB) (p < 0.001) and chemotherapy drugs, thus, possessing improved prognosis.Conclusion: An OXPHOS-related and immune microenvironment prognostic signature classifying EC patients into different risk subsets was constructed in our study, which could be used to predict the prognosis of patients and help to select a specific subset of patients who might benefit from immunotherapy and chemotherapy, thus, improving the overall survival rate of UCEC. These findings may contribute to the discovery of novel and robust biomarkers or target therapy in UCEC and give new insights into the molecular mechanism of tumorigenesis and progression of UCEC.

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A Novel Four-MicroRNA Signature for Prognosis and Diagnosis in Colorectal Cancer

10.21203/rs.3.rs-70357/v1 ◽

2020 ◽

Author(s):

Yan Chen ◽

Ying Qin ◽

Yaoyao Zhou ◽

Mengmeng Dai ◽

Qinsheng Sun ◽

...

Keyword(s):

Colorectal Cancer ◽

Overall Survival ◽

Regression Analysis ◽

Mirna Expression ◽

Validation Cohort ◽

Expression Profiles ◽

Functional Enrichment ◽

Prognostic Signature ◽

Discovery Cohort ◽

Diagnostic Signature

Abstract Background and aims: Colorectal cancer (CRC) remains a global public health problem. We aimed to access prognostic microRNAs (miRNAs) associated with overall survival (OS) and evaluate their diagnostic value in CRC.Methods: Three serum miRNA expression profiles from Gene Expression Omnibus (GEO) database and tissue miRNA expression profile of CRC from The Cancer Genome Atlas (TCGA) database were studied to get common differentially expressed miRNA (DEmiRNAs) in serums and tissues. 569 CRC patients with survival information from TCGA database were randomly divided into the discovery and validation cohort. Based on the TCGA discovery cohort, the univariate cox analysis, least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate cox proportional hazards regression analysis were performed and a prognostic signature was constructed. The prognostic capacity of the signature was verified in TCGA validation cohort and the prognostic signature expression in tumors and serums was validated in an independent microarray dataset and our clinical set. We also evaluated the diagnostic power of the model in serum by calculating the area under the receiver operating characteristic (ROC) curve in a clinical set. Functional enrichment analyses were applied to analyze the potential roles of the signature in CRC.Results: A total of 154 common DEmiRNAs were identified. Based on the TCGA discovery cohort, a four-miRNA (miR-10b, miR-130a, miR-561, miR-4684) prognostic signature was constructed and a predictive nomogram model including the expression of above four miRNAs showed good performance for predicting the 3- and 5-year overall survival. The findings were well verified in TCGA validation cohort. miR-10b, miR-130a, miR-561 and miR-4684 were significantly upregulated both in CRC tumors and serums. Circulating miR-10b, miR-130a, miR-561 and miR-4684 levels were significantly downregulated after surgical resection of tumor in CRC patients, suggesting these four circulating miRNAs in the serum were tumor derived. The four circulating miRNA combination might act as a novel diagnostic signature for CRC. Functional enrichment analyses suggested that above four miRNAs might be related to the progression of CRC. Conclusions: We developed a novel reliable prognostic and diagnostic signature, which should be beneficial for CRC screening and clinical therapeutic decision-making.

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Establishment and Validation of a Ferroptosis-Related Gene Signature to Predict Overall Survival in Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.793636 ◽

2022 ◽

Vol 12 ◽

Author(s):

Su Wang ◽

Zhen Xie ◽

Zenghong Wu

Keyword(s):

Overall Survival ◽

High Risk ◽

Lung Adenocarcinoma ◽

Risk Group ◽

Risk Groups ◽

Gene Signature ◽

Low Risk ◽

Functional Enrichment ◽

Related Gene ◽

Prognostic Signature

Background: Lung adenocarcinoma (LUAD) is the most common and lethal subtype of lung cancer. Ferroptosis, an iron-dependent form of regulated cell death, has emerged as a target in cancer therapy. However, the prognostic value of ferroptosis-related genes (FRGs)x in LUAD remains to be explored.Methods: In this study, we used RNA sequencing data and relevant clinical data from The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) dataset to construct and validate a prognostic FRG signature for overall survival (OS) in LUAD patients and defined potential biomarkers for ferroptosis-related tumor therapy.Results: A total of 86 differentially expressed FRGs were identified from LUAD tumor tissues versus normal tissues, of which 15 FRGs were significantly associated with OS in the survival analysis. Through the LASSO Cox regression analysis, a prognostic signature including 11 FRGs was established to predict OS in the TCGA tumor cohort. Based on the median value of risk scores calculated according to the signature, patients were divided into high-risk and low-risk groups. Kaplan–Meier analysis indicated that the high-risk group had a poorer OS than the low-risk group. The area under the curve of this signature was 0.74 in the TCGA tumor set, showing good discrimination. In the GEO validation set, the prognostic signature also had good predictive performance. Functional enrichment analysis showed that some immune-associated gene sets were significantly differently enriched in two risk groups.Conclusion: Our study unearthed a novel ferroptosis-related gene signature for predicting the prognosis of LUAD, and the signature may provide useful prognostic biomarkers and potential treatment targets.

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A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction

International Journal of Genomics ◽

10.1155/2020/8347639 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

Menghuang Zhao ◽

Wenbin Huang ◽

Shuangwei Zou ◽

Qi Shen ◽

Xueqiong Zhu

Keyword(s):

Gene Expression ◽

Cervical Cancer ◽

Overall Survival ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Clinicopathological Parameters ◽

Prognostic Signature ◽

Kaplan Meier ◽

Hpv Status

Aims. This study is aimed at identifying a prognostic signature for cervical cancer. Main Methods. The gene expression data and clinical information of cervical cancer and normal cervical tissues were acquired from The Cancer Genome Atlas and from three datasets of the Gene Expression Omnibus database. DESeq2 and Limma were employed to screen differentially expressed genes (DEGs). The overlapping DEGs among all datasets were considered the final DEGs. Then, the functional enrichment analysis was performed. Moreover, the Cox proportional hazards regression was performed to establish a prognostic signature of the DEGs. The Kaplan-Meier analysis was applied to test the model. Relationships between gene expression and clinicopathological parameters in cervical cancer, including age, HPV status, histology, stage, and lymph node metastasis, were analysed by the chi-square test. The somatic mutations of these prognostic genes were assessed through cBioPortal. The robustness of the model was verified in another two independent validation cohorts. Key Findings. In total, 169 overlapping upregulated genes and 29 overlapping downregulated genes were identified in cervical cancer compared with normal cervical tissues. Functional enrichment analysis indicated that the DEGs were mainly enriched in DNA replication, the cell cycle, and the p53 signalling pathway. Finally, a 5-gene- (ITM2A, DSG2, SPP1, EFNA1, and MMP1) based prognostic signature was built. According to this model, each patient was given a prognostic-related risk value. The Kaplan-Meier analysis showed that a higher risk was related to worse overall survival in cervical cancer, with an area under the receiver operating characteristic curve of 0.811 for 15 years. The validity of this model in the prediction of cervical cancer outcome was verified in another two independent datasets. In addition, our study also found that the low expression of ITM2A was associated with cervical adenocarcinoma. Interestingly, DSG2 was associated with the HPV status of cervical cancer. Significance. Our study constructed a prognostic model in cervical cancer and discovered two novel genes, ITM2A and DSG2, associated with cervical carcinogenesis and survival.

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An Inflammation-Related Nine-Gene Signature to Improve Prognosis Prediction of Lung Adenocarcinoma

Disease Markers ◽

10.1155/2021/9568057 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Ze-jing Liu ◽

Peng-xiao Hou ◽

Xi-xing Wang

Keyword(s):

Overall Survival ◽

Lung Adenocarcinoma ◽

Prognostic Value ◽

Risk Group ◽

Gene Signature ◽

High Risk Group ◽

Risk Scores ◽

Lasso Regression ◽

Prognostic Signature ◽

Prognostic Prediction

Background. A novel predictive model was rarely reported based on inflammation-related genes to explore clinical outcomes of lung adenocarcinoma (LUAD) patients. Methods. Using TCGA database, we screened nine inflammation-related genes with a prognostic value, and LASSO regression was applied for model construction. The predictive value of the prognostic signature developed from inflammation-related genes was assessed by survival assays and multivariate assays. PCA and t-SNE analysis were performed to demonstrate clustering abilities of risk scores. Results. Thirteen inflammation-related genes (BTG2, CCL20, CD69, DCBLD2, GPC3, IL7R, LAMP3, MMP14, NMUR1, PCDH7, PIK3R5, RNF144B, and TPBG) with prognostic values were finally identified. LASSO regression further screened nine candidates (BTG2, CCL20, CD69, IL7R, MMP14, NMUR1, PCDH7, RNF144B, and TPBG). Then, a prognostic prediction model using the above nine genes was constructed. A reliable clustering ability of risk score was demonstrated by PCA and t-SNE assays in 500 LUAD patients. The survival assays revealed that the overall survivals of the high-risk group were distinctly poorer than those of the low-risk group with 1-, 3-, and 5-year AUC values of 0.695, 0.666, and 0.694, respectively. Finally, multivariate assays demonstrated the scoring system as an independent prognostic factor for overall survival. Conclusions. Our study shows that the signature of nine inflammation-related genes can be used as a prognostic marker for LUAD.

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Abstract 3182: Tumor immune microenvironment based molecular functional clustering reveals a prognostic signature that predicts overall survival in patients with gastric cancer

10.1158/1538-7445.am2021-3182 ◽

2021 ◽

Author(s):

Prashant V. Thakkar ◽

Olga Kudryashova ◽

Daria Melikhova ◽

Naira Samarina ◽

Sandrine Degryse ◽

...

Keyword(s):

Gastric Cancer ◽

Overall Survival ◽

Prognostic Signature ◽

Immune Microenvironment ◽

Functional Clustering ◽

Tumor Immune Microenvironment

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A genomic mutation signature predicts the clinical outcomes of immunotherapy and characterizes immunophenotypes in gastrointestinal cancer

npj Precision Oncology ◽

10.1038/s41698-021-00172-5 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Xi Jiao ◽

Xin Wei ◽

Shuang Li ◽

Chang Liu ◽

Huan Chen ◽

...

Keyword(s):

Gastrointestinal Cancer ◽

Prognostic Value ◽

Cox Regression ◽

Prognostic Biomarker ◽

Cancer Center ◽

Genomic Profile ◽

Prognostic Signature ◽

Powerful Predictor ◽

Potential Biomarker ◽

Peking University

AbstractThe association between genetic variations and immunotherapy benefit has been widely recognized, while such evidence in gastrointestinal cancer remains limited. We analyzed the genomic profile of 227 immunotherapeutic gastrointestinal cancer patients treated with immunotherapy, from the Memorial Sloan Kettering (MSK) Cancer Center cohort. A gastrointestinal immune prognostic signature (GIPS) was constructed using LASSO Cox regression. Based on this signature, patients were classified into two subgroups with distinctive prognoses (p < 0.001). The prognostic value of the GIPS was consistently validated in the Janjigian and Pender cohort (N = 54) and Peking University Cancer Hospital cohort (N = 92). Multivariate analysis revealed that the GIPS was an independent prognostic biomarker. Notably, the GIPS-high tumor was indicative of a T-cell-inflamed phenotype and immune activation. The findings demonstrated that GIPS was a powerful predictor of immunotherapeutic survival in gastrointestinal cancer and may serve as a potential biomarker guiding immunotherapy treatment decisions.

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