scholarly journals miRNA-Based Feature Classifier Is Associated with Tumor Mutational Burden in Head and Neck Squamous Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yu Xia ◽  
Qi Wang ◽  
Xiaolin Huang ◽  
Xinhai Yin ◽  
Jukun Song ◽  
...  
Keyword(s):  
Mirna Expression ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Immune Checkpoints ◽  
Training Set ◽  
Test Set ◽  
Tumor Mutation Burden ◽  
Mutation Burden

Tumor mutation burden (TMB) is considered to be an independent genetic biomarker that can predict the tumor patient’s response to immune checkpoint inhibitors (ICIs). Meanwhile, microRNA (miRNA) plays a key role in regulating the anticancer immune response. However, the correlation between miRNA expression patterns and TMB is not elucidated in HNSCC. In the HNSCC cohort of the TCGA dataset, miRNAs that were differentially expressed in high TMB and low TMB samples were screened. The least absolute contraction and selection operator (LASSO) method is used to construct a miRNA-based feature classifier to predict the TMB level in the training set. The test set is used to verify the classifier. The correlation between the miRNA-based classifier index and the expression of three immune checkpoints (PD1, PDL1, and CTLA4) was explored. We further perform functional enrichment analysis on the miRNA contained in the miRNA-based feature classifier. Twenty-five differentially expressed miRNAs are used to build miRNA-based feature classifiers to predict TMB levels. The accuracy of the 25-miRNA-based signature classifier is 0.822 in the training set, 0.702 in the test set, and 0.774 in the total set. The miRNA-based feature classifier index showed a low correlation with PD1 and PDL1, but no correlation with CTLA4. The enrichment analysis of these 25 miRNAs shows that they are involved in many immune-related biological processes and cancer-related pathways. The miRNA expression patterns are related to tumor mutation burden, and miRNA-based feature classifiers can be used as biomarkers to predict TMB levels in HNSCC.

scholarly journals Comparative Transcriptome Analysis Suggests Key Roles for 5-Hydroxytryptamlne Receptors in Control of Goose Egg Production

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 455 ◽  
Author(s):  
Qingyuan Ouyang ◽  
Shenqiang Hu ◽  
Guosong Wang ◽  
Jiwei Hu ◽  
Jiaman Zhang ◽  
...  
Keyword(s):  
Egg Production ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Production Performance ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Anser Anser

To date, research on poultry egg production performance has only been conducted within inter or intra-breed groups, while those combining both inter- and intra-breed groups are lacking. Egg production performance is known to differ markedly between Sichuan white goose (Anser cygnoides) and Landes goose (Anser anser). In order to understand the mechanism of egg production performance in geese, we undertook this study. Here, 18 ovarian stromal samples from both Sichuan white goose and Landes goose at the age of 145 days (3 individuals before egg production initiation for each breed) and 730 days (3 high- and low egg production individuals during non-laying periods for each breed) were collected to reveal the genome-wide expression profiles of ovarian mRNAs and lncRNAs between these two geese breeds at different physiological stages. Briefly, 58, 347, 797, 777, and 881 differentially expressed genes (DEGs) and 56, 24, 154, 105, and 224 differentially expressed long non-coding RNAs (DElncRNAs) were found in LLD vs. HLD (low egg production Landes goose vs. high egg production Landes goose), LSC vs. HSC (low egg production Sichuan White goose vs. high egg production Sichuan white goose), YLD vs. YSC (young Landes goose vs. young Sichuan white goose), HLD vs. HSC (high egg production Landes goose vs. high egg production Sichuan white goose), and LLD vs. LSC (low egg production Landes goose vs. low egg production Sichuan white goose) groups, respectively. Functional enrichment analysis of these DEGs and DElncRNAs suggest that the “neuroactive ligand–receptor interaction pathway” is crucial for egg production, and particularly, members of the 5-hydroxytryptamine receptor (HTR) family affect egg production by regulating ovarian metabolic function. Furthermore, the big differences in the secondary structures among HTR1F and HTR1B, HTR2B, and HTR7 may lead to their different expression patterns in goose ovaries of both inter- and intra-breed groups. These results provide novel insights into the mechanisms regulating poultry egg production performance.

scholarly journals Systematic Profiling of Diagnostic and Prognostic Value of Autophagy-Related Genes for Sarcoma Patients

2020 ◽  
Author(s):  
Yuanhe Wang ◽  
Jianyi Li ◽  
Cheng Shao ◽  
Xiaojie Tang ◽  
Yukun Du ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cells ◽  
Disease Free Survival ◽  
Independent Set ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Immune Checkpoints ◽  
Systematic Analysis

Abstract Background: Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking.Methods: Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set. Results: In total, 84 DEIRGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between twp clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.636 for the OS and DFS nomograms, respectively.Conclusion: This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

scholarly journals A novel seven-microRNA signature predicts prognosis in colorectal adenocarcinoma

2020 ◽  
Author(s):  
Shengying Jiang ◽  
Xiaoli Xie ◽  
Hui-Qing Jiang
Keyword(s):  
Colorectal Adenocarcinoma ◽  
Cox Regression ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Mirna Signature ◽  
Training Set ◽  
Test Set ◽  
Related Cell

Abstract Background Colorectal carcinoma, primarily colorectal adenocarcinoma (CRA), is one of the most common malignancies, ranking third, while contributing the second cause of cancer death in the world. MicroRNAs, a type of non-coding RNA, play an important role in regulating cancer-related cell biology. To simply and accurately predict survival risk for CRA patients, we identified a novel seven-miRNA signature. The microRNA (miRNA) expression profiles along with clinical data of 512 CRA patients were downloaded from The Cancer Genome Atlas (TCGA) database, and 415 patients with complete clinical information were further divided into training set and test set randomly. To construct the prognostic signature in the training set, a series of Cox regression analyses were performed, including univariate regression, least absolute shrinkage and selectionator operator (LASSO) - Cox regression, and multivariate regression. Results Seven predictive miRNAs (miR-153-2, miR-3199-2, miR-144, miR-887, miR-561, miR-3684, and miR-505) were ultimately screened. The ROC curves for 5-year survival in the training set, test set and entire set were 0.889, 0.742, and 0.816, respectively. Kaplan-Meier analysis results of the three sets all showed p <0.05. Further analyses demonstrated that the signature was an independent prognostic risk factor for CRA patients, and its predictive ability was superior to age and TNM stage. Functional enrichment analysis revealed that p53 and ErbB pathways were related to the prognostic regulation of miRNAs in the signature in CRA patients.Conclusion Our study demonstrated the potential of this novel seven-miRNA signature to independently predict overall survival in patients with CRA. Functional enrichment analysis further revealed the possible regulatory role of miRNAs in the signature in CRA-related cell biological processes and signaling pathways.

scholarly journals An miRNA signature associated with tumor mutation burden in endometrial cancer

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Hongyu Zhou ◽  
Lihua Chen ◽  
Mei Qin ◽  
Yajie Lei ◽  
Tianjiao Li ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Mirna Signature ◽  
Training Set ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Validation Set ◽  
Brca1 Brca2 ◽  
Selection Operator

Abstract Tumor mutation burden (TMB) is an essential biomarker to predict immunotherapy response. TMB measurement was mainly evaluated by whole-exome sequencing (WES), which was costly and difficult to be widely applied. In the present study, we aimed to establish and validate a miRNA signature to predict TMB level in endometrial cancer using The Cancer Genome Atlas (TCGA) database. MiRNA expression and somatic mutation profiles of uterine corpus endometrial carcinoma (UCEC) were downloaded from TCGA database. Total 518 patients with UCEC were randomly classified into training set (n=311) and validation set (n=207). Thirty-five differentially expressed miRNAs between high-TMB and low-TMB group were identified in training set. Least absolute shrinkage and selection operator (LASSO) method was performed to select out 26 miRNAs to establish the optimal signature. The accuracy of the miRNA signature for predicting TMB level was 0.833 for training set, 0.749 for validation set and 0.799 for total set. Moreover, the miRNA signature had significant correlation with immune checkpoints related genes (PD-1, PD-L1, CTLA-4) and mismatch repair related genes (BRCA1, BRCA2, MLH1, MSH6) expression. In conclusion, this miRNA signature could predict TMB level in endometrial cancer and might have some merits in providing guidance for immunotherapy in endometrial cancer.

scholarly journals Systematic profiling of diagnostic and prognostic value of autophagy-related genes for sarcoma patients

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuanhe Wang ◽  
Jianyi Li ◽  
Cheng Shao ◽  
Xiaojie Tang ◽  
Yukun Du ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cells ◽  
Disease Free Survival ◽  
Independent Set ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Immune Checkpoints ◽  
Systematic Analysis

Abstract Background Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking. Methods Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set. Results In total, 84 DEARGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between two clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.747 for the OS and DFS nomograms, respectively. Conclusion This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

scholarly journals Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuan Chen ◽  
Ruiyuan Xu ◽  
Rexiati Ruze ◽  
Jinshou Yang ◽  
Huanyu Wang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Histone Modification ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Training Set ◽  
Test Set ◽  
Cox Regression Analysis ◽  
Small Molecule Drugs

Abstract Background Pancreatic cancer (PC) is a highly fatal and aggressive disease with its incidence and mortality quite discouraging. An effective prediction model is urgently needed for the accurate assessment of patients’ prognosis to assist clinical decision-making. Methods Gene expression data and clinicopathological data of the samples were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Differential expressed genes (DEGs) analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, random forest screening and multivariate Cox regression analysis were applied to construct the risk signature. The effectiveness and independence of the model were validated by time-dependent receiver operating characteristic (ROC) curve, Kaplan–Meier (KM) survival analysis and survival point graph in training set, test set, TCGA entire set and GSE57495 set. The validity of the core gene was verified by immunohistochemistry and our own independent cohort. Meanwhile, functional enrichment analysis of DEGs between the high and low risk groups revealed the potential biological pathways. Finally, CMap database and drug sensitivity assay were utilized to identify potential small molecular drugs as the risk model-related treatments for PC patients. Results Four histone modification-related genes were identified to establish the risk signature, including CBX8, CENPT, DPY30 and PADI1. The predictive performance of risk signature was validated in training set, test set, TCGA entire set and GSE57495 set, with the areas under ROC curve (AUCs) for 3-year survival were 0.773, 0.729, 0.775 and 0.770 respectively. Furthermore, KM survival analysis, univariate and multivariate Cox regression analysis proved it as an independent prognostic factor. Mechanically, functional enrichment analysis showed that the poor prognosis of high-risk population was related to the metabolic disorders caused by inadequate insulin secretion, which was fueled by neuroendocrine aberration. Lastly, a cluster of small molecule drugs were identified with significant potentiality in treating PC patients. Conclusions Based on a histone modification-related gene signature, our model can serve as a reliable prognosis assessment tool and help to optimize the treatment for PC patients. Meanwhile, a cluster of small molecule drugs were also identified with significant potentiality in treating PC patients.

scholarly journals MicroRNAs Expression Patterns Predict Tumor Mutational Burden in Colorectal Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Jiahao Huang ◽  
Haizhou Liu ◽  
Yang Zhao ◽  
Tao Luo ◽  
Jungang Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Mirna Expression ◽  
Checkpoint Inhibitors ◽  
Expression Patterns ◽  
The Cancer Genome Atlas ◽  
Training Set ◽  
Test Set ◽  
Internal Validation ◽  
Mutational Burden ◽  
Tumor Mutational Burden

BackgroundTumor mutational burden (TMB) could be a measure of response to immune checkpoint inhibitors therapy for patients with colorectal cancer (CRC). MicroRNAs (miRNAs) participate in anticancer immune responses. In the present study, we determined miRNA expression patterns in patients with CRC and built a signature that predicts TMB.MethodsNext generation sequencing (NGS) on formalin-fixed paraffin-embedded samples from CRC patients was performed to measure TMB levels. We used datasets from The Cancer Genome Atlas to compare miRNA expression patterns in samples with high and low TMB from patients with CRC. We created an miRNA-based signature index using the selection operator (LASSO) and least absolute shrinkage method from the training set. We used an independent test set as internal validation. We used real-time polymerase chain reaction (RT-PCR) to validate the miRNA-based signature classifier.ResultsTwenty-seven samples from CRC patients underwent NGS to determine the TMB level. We identified four miRNA candidates in the training set for predicting TMB (N = 311). We used the test set (N = 204) for internal validation. The four-miRNA-based signature classifier was an accurate predictor of TMB, with accuracy 0.963 in the training set. In the test set, it was 0.902; and it was 0.946 in the total set. The classifier was superior to microsatellite instability (MSI) for predicting TMB in TCGA dataset. In the validation cohort, MSI status more positively correlated with TMB levels than did the classifier. Validation from RT-qPCR showed good target discrimination of the classifier for TMB prediction.ConclusionTo our knowledge, this is the first miRNA-based signature classifier validated using high quality clinical data to accurately predict TMB level in patients with CRC.

scholarly journals Long Non-coding RNA Expression Patterns in Stomach Adenocarcinoma Serve as an Indicator of Tumor Mutation Burden and Are Associated With Tumor-Infiltrating Lymphocytes and Microsatellite Instability

2021 ◽  
Vol 9 ◽  
Author(s):  
Dongdong Yang ◽  
Jinling Yu ◽  
Bing Han ◽  
Yue Sun ◽  
Steven Mo ◽  
...  
Keyword(s):  
Microsatellite Instability ◽  
Tumor Immunity ◽  
Expression Patterns ◽  
Operator Method ◽  
Tumor Infiltrating Lymphocytes ◽  
Immune Checkpoints ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Stomach Adenocarcinoma ◽  
Infiltrating Lymphocytes

Long non-coding RNAs (lncRNAs) are crucial in controlling important aspects of tumor immunity. However, whether the expression pattern of lncRNAs in stomach adenocarcinoma (STAD) reflects tumor immunity is not fully understood. We screened differentially expressed lncRNAs (DElncRNAs) between high and low tumor mutation burden (TMB) STAD samples. Using the least absolute shrinkage and selection operator method, 33 DElncRNAs were chosen to establish a lncRNA-based signature classifier for predicting TMB levels. The accuracy of the 33-lncRNA-based signature classifier was 0.970 in the training set and 0.950 in the test set, suggesting the expression patterns of the 33 lncRNAs may be an indicator of TMB in STAD. Survival analysis showed that a lower classifier index reflected better prognosis for STAD patients, and the index showed correlation with expression of immune checkpoint molecules (PD1, PDL1, and CTLA4), tumor-infiltrating lymphocytes, and microsatellite instability. In conclusion, STAD samples with different tumor mutation burdens have different lncRNA expression patterns. The 33-lncRNA-based signature classifier index may be an indicator of TMB and is associated expression of immune checkpoints, tumor-infiltrating lymphocytes, and microsatellite instability.

scholarly journals A MiRNA-based Signature is Associated With Tumor Mutational Burden in Colon Adenocarcinoma

2020 ◽  
Author(s):  
Weijie xue ◽  
Yixiu Wang ◽  
Zhiqi Gong ◽  
Chenyu Yang ◽  
Yuwei Xie ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Differential Expression ◽  
Colon Adenocarcinoma ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Component Analysis ◽  
Immune Checkpoints ◽  
Training Set ◽  
Test Set ◽  
Lasso Method

Abstract Background:Tumor mutation burden (TMB) has become an independent biomarker for predicting the response of Immune checkpoint inhibitors.MiRNA plays an important role in cancer-related immune regulation but the relationship between expression of miRNA and TMB is unclear in colon adenocarcinoma (COAD).Method:The transcriptome profiling data, clinical data, mutation annotation data and miRNA expression profiles for cases with COAD were downloaded from TCGA database, and then COAD samples were randomly divided into training set and test set. The differential expression miRNAs of high and low TMB group in training set was obtained as a signature by the least absolute shrinkage and selection operator (LASSO) logistic regression, and it was verified in test set. UsingLASSO method, principal component analysis (PCA) and ROC to verify the credibility of signature.In addition, the correlation betweenthemiRNA-based signature and immune checkpoints was performed.In the end, enrichment analysis of the miRNAs in signature was performed to explore the biological function.Results:18 differential expression miRNAswere obtainedaccording to LASSO method. According to LASSO method, principal component analysis (PCA) and ROC, we found that the credibility of signature, and the signature can discriminate the high and low TMB level. Furthermore, the results of correlation between the 18-miRNA-based signature and immune checkpoints showed that the miRNA-based model has a strong positive correlation with TMB, weak positive correlation with CTLA4 and CD274 (PD-L1). However, there is no correlation between the model and SNCA (PD-1).Finally, enrichment analysis of the 18miRNAs demonstrated that the 18 miRNAs were involved in process of immunity and cancer pathways.Conclusion:We established a novel miRNA-based signature integrating expression of miRNAs and TMB levels. The 18-miRNA-based signature can effectively predict and discriminate the TMB levels in COAD, and provides apotential guide of ICIs treatment.

Systems Biology Approaches Reveal a Multi-stress Responsive WRKY Transcription Factor and Stress Associated Gene Co-expression Networks in Chickpea

2019 ◽  
Vol 14 (7) ◽  
pp. 591-601 ◽  
Author(s):  
Aravind K. Konda ◽  
Parasappa R. Sabale ◽  
Khela R. Soren ◽  
Shanmugavadivel P. Subramaniam ◽  
Pallavi Singh ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Gene Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Wrky Transcription Factor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Callose Deposition ◽  
Significant Probability

Background: Chickpea is a nutritional rich premier pulse crop but its production encounters setbacks due to various stresses and understanding of molecular mechanisms can be ascribed foremost importance. Objective: The investigation was carried out to identify the differentially expressed WRKY TFs in chickpea in response to herbicide stress and decipher their interacting partners. Methods: For this purpose, transcriptome wide identification of WRKY TFs in chickpea was done. Behavior of the differentially expressed TFs was compared between other stress conditions. Orthology based cofunctional gene networks were derived from Arabidopsis. Gene ontology and functional enrichment analysis was performed using Blast2GO and STRING software. Gene Coexpression Network (GCN) was constructed in chickpea using publicly available transcriptome data. Expression pattern of the identified gene network was studied in chickpea-Fusarium interactions. Results: A unique WRKY TF (Ca_08086) was found to be significantly (q value = 0.02) upregulated not only under herbicide stress but also in other stresses. Co-functional network of 14 genes, namely Ca_08086, Ca_19657, Ca_01317, Ca_20172, Ca_12226, Ca_15326, Ca_04218, Ca_07256, Ca_14620, Ca_12474, Ca_11595, Ca_15291, Ca_11762 and Ca_03543 were identified. GCN revealed 95 hub genes based on the significant probability scores. Functional annotation indicated role in callose deposition and response to chitin. Interestingly, contrasting expression pattern of the 14 network genes was observed in wilt resistant and susceptible chickpea genotypes, infected with Fusarium. Conclusion: This is the first report of identification of a multi-stress responsive WRKY TF and its associated GCN in chickpea.

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