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 Association of RYR2 Mutation With Tumor Mutation Burden, Prognosis, and Antitumor Immunity in Patients With Esophageal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zaoqu Liu ◽  
Long Liu ◽  
Dechao Jiao ◽  
Chunguang Guo ◽  
Libo Wang ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Somatic Mutation ◽  
Antitumor Immunity ◽  
Immune Cell ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Potential Biomarker

Background: Esophageal adenocarcinoma (EAC) remains a leading cause of cancer-related deaths worldwide and demonstrates a predominant rising incidence in Western countries. Recently, immunotherapy has dramatically changed the landscape of treatment for many advanced cancers, with the benefit in EAC thus far been limited to a small fraction of patients.Methods: Using somatic mutation data of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium, we delineated the somatic mutation landscape of EAC patients from US and England. Based on the expression data of TCGA cohort, multiple bioinformatics algorithms were utilized to perform function annotation, immune cell infiltration analysis, and immunotherapy response assessment.Results: We found that RYR2 was a common frequently mutated gene in both cohorts, and patients with RYR2 mutation suggested higher tumor mutation burden (TMB), better prognosis, and superior expression of immune checkpoints. Moreover, RYR2 mutation upregulated the signaling pathways implicated in immune response and enhanced antitumor immunity in EAC. Multiple bioinformatics algorithms for assessing immunotherapy response demonstrated that patients with RYR2 mutation might benefit more from immunotherapy. In order to provide additional reference for antitumor therapy of different RYR2 status, we identified nine latent antitumor drugs associated with RYR2 status in EAC.Conclusion: This study reveals a novel gene whose mutation could be served as a potential biomarker for prognosis, TMB, and immunotherapy of EAC patients.

scholarly journals Association of RYR2 Mutation with Tumor Mutation Burden, Prognosis and Antitumor Immunity in Patients with Esophageal Adenocarcinoma

2021 ◽  
Author(s):  
Zaoqu Liu ◽  
Long Liu ◽  
Chunguang Guo ◽  
Libo Wang ◽  
Zhaonan Li ◽  
...  
Keyword(s):  
Antitumor Immunity ◽  
Immune Cell ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Potential Biomarker ◽  
Cancer Genome Atlas ◽  
Additional Reference

Abstract BackgroundEsophageal adenocarcinoma (EAC) remains a leading cause of cancer-related deaths worldwide, and demonstrates a predominant rising incidence in Western countries. Recently, immunotherapy has dramatically changed the landscape of treatment for many advanced cancers, the benefit in EAC thus far been limited to a small fraction of patients. MethodsUsing somatic mutations data of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), we delineated somatic mutation landscape of EAC patients from US and England. Bioinformatics algorithms were utilized to perform function annotation, immune cell infiltration analysis, and immunotherapy response assessment.ResultsWe found that RYR2 was a common frequently mutated gene (FMG) in both cohorts, and patients with RYR2 mutation suggested higher tumor mutation burden (TMB), better prognosis, and superior expression of immune checkpoints. Moreover, RYR2 mutation upregulated the signaling pathways implicated in immune response and enhanced antitumor immunity in EAC. Multiple bioinformatics algorithms for assessing immunotherapy response demonstrated that patients with RYR2 mutation might benefit more from immunotherapy. In order to provide additional reference for antitumor therapy of different RYR2 status, we identified nine latent antitumor drugs associated with RYR2 status in EAC. ConclusionsThis study reveals a novel gene whose mutation could be served as a potential biomarker for prognosis, TMB, and immunotherapy of EAC patients.

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 PEG3 mutation is associated with elevated tumor mutation burden and poor prognosis in breast cancer

2020 ◽  
Vol 40 (8) ◽  
Author(s):  
Min Zhang ◽  
Jin Zhang
Keyword(s):  
Breast Cancer ◽  
The Cancer Genome Atlas ◽  
Confounding Factors ◽  
Breast Cancer Patients ◽  
Wild Type ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Genome Atlas ◽  
Brca1 Brca2 ◽  
Common Malignancy

Abstract Background: Breast cancer is the second most common malignancy in women and considered as a severe health burden. PEG3 mutations have been observed in several cancers. However, the associations of PEG3 mutation with tumor mutation burden (TMB) and prognosis in breast cancer have not been investigated. Methods: In our study, the somatic mutation data of 986 breast cancer patients from The Cancer Genome Atlas (TCGA) were analyzed. Results: It showed that PEG3 had a relatively high mutation rate (2%). After calculated the TMB in PEG3 mutant and PEG3 wild-type groups, we found the TMB value was significantly higher in PEG3 mutant samples than that in PEG3 wild-type samples (P = 5.6e-07), which was independent of the confounding factors including age, stage, mutations of BRCA1, BRCA2 and POLE (odd ratio, 0.45; 95% CI, 0.20–0.98; P=0.044). Survival analysis revealed that PEG3 mutant samples had inferior survival outcome compared with the PEG3 wild-type samples after adjusted for the confounding factors above (hazard ratio, 0.27; 95% CI: 0.12–0.57; P<0.001). Conclusion: These results illustrated that PEG3 mutation was associated with high TMB and inferior prognosis, suggesting PEG3 mutation might play a guiding role in prognosis prediction and immunotherapy selection in breast cancer.

Comprehensive assessment of PD-L1 and PD-L2 dysregulation in gastrointestinal cancers

Epigenomics ◽  
2020 ◽  
Author(s):  
Qijie Zhao ◽  
Jinan Guo ◽  
Yueshui Zhao ◽  
Jing Shen ◽  
Parham Jabbarzadeh Kaboli ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Signaling Pathways ◽  
Underlying Mechanism ◽  
Comprehensive Analysis ◽  
The Cancer Genome Atlas ◽  
Gastrointestinal Cancers ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: PD-L1 and PD-L2 are ligands of PD-1. Their overexpression has been reported in different cancers. However, the underlying mechanism of PD-L1 and PD-L2 dysregulation and their related signaling pathways are still unclear in gastrointestinal cancers. Materials & methods: The expression of PD-L1 and PD-L2 were studied in The Cancer Genome Atlas and Genotype-Tissue Expression databases. The gene and protein alteration of PD-L1 and PD-L2 were analyzed in cBioportal. The direct transcription factor regulating PD-L1/ PD-L2 was determined with ChIP-seq data. The association of PD-L1/PD-L2 expression with clinicopathological parameters, survival, immune infiltration and tumor mutation burden were investigated with data from The Cancer Genome Atlas. Potential targets and pathways of PD-L1 and PD-L2 were determined by protein enrichment, WebGestalt and gene ontology. Results: Comprehensive analysis revealed that PD-L1 and PD-L2 were significantly upregulated in most types of gastrointestinal cancers and their expressions were positively correlated. SP1 was a key transcription factor regulating the expression of PD-L1. Conclusion: Higher PD-L1 or PD-L2 expression was significantly associated with poor overall survival, higher tumor mutation burden and more immune and stromal cell populations. Finally, HIF-1, ERBB and mTOR signaling pathways were most significantly affected by PD-L1 and PD-L2 dysregulation. Altogether, this study provided comprehensive analysis of the dysregulation of PD-L1 and PD-L2, its underlying mechanism and downstream pathways, which add to the knowledge of manipulating PD-L1/PD-L2 for cancer immunotherapy.

INITIAL EXPERIENCE IN ESTIMATING TUMOR MUTATION BURDEN IN PEDIATRIC HEPATOCELLULAR CARCINOMA

2021 ◽  
Vol 100 (3) ◽  
pp. 193-199
Author(s):  
D.G. Akhaladze ◽  
◽  
G.S. Rabaev ◽  
N.V. Zhukov ◽  
M.A. Pyatnitskiy ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Primary Tumor ◽  
Checkpoint Inhibitors ◽  
Pediatric Population ◽  
Case Series ◽  
Immune Checkpoints ◽  
Initial Experience ◽  
Tumor Mutation Burden ◽  
Detection Frequency ◽  
Mutation Burden

The level of tumor mutation burden (TMB) is a predictive factor of immune checkpoints that determines the potential effectiveness of immune checkpoint inhibitors and indications for their prescription regardless of the type of tumor in adults and children. However, the prevalence of tumors with high TMB in the pediatric population has not been well studied. Objective of the research: to assess the detection frequency of high TMB (>10 mutations per megabase) in pediatric hepatocellular carcinoma (HCC). Materials and methods of research: Next Generation Sequencing, Ion AmpliSeq™ Comprehensive Cancer Panel (409 genes) of tumor DNA samples from 4 children with HCC was performed. The calculation of the mutational load was carried out according to the work of Z.R. Chalmers et al. Results: out of 4 analyzed samples, TMB levels have lower cut-off value than needed for the immunity checkpoint inhibitors for 2 patients to administer: 5,9 mut/MB (primary tumor), 9,2 mut/MB (metastasis), while in 2 other patients the TMB has level above the threshold – 10,9 mut/MB (primary tumor) and 48,5 mut/MB (relapse metastasis), respectively. Conclusion: this paper presents the initial experience of estimation of the TMB level in children with HCC. In our case series report, the level allowing the prescription of immunotherapy (>10 mut/MB) was observed in 2 patients. Further research on a larger cohort of patients is useful to assess the role of mutational burden in disease prediction and effectiveness of immunotherapy.

Integrated analysis of tumor mutation burden and immune infiltrates in endometrial cancer

2020 ◽  
pp. 100660
Author(s):  
Hongyu Zhou ◽  
Lihua Chen ◽  
Yajie Lei ◽  
Tianjiao Li ◽  
Haoran Li ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Integrated Analysis ◽  
Tumor Mutation Burden ◽  
Mutation Burden

scholarly journals Genome-Wide Identification of a Novel Autophagy-Related Signature for Colorectal Cancer

Dose-Response ◽  
2019 ◽  
Vol 17 (4) ◽  
pp. 155932581989417 ◽  
Author(s):  
Zhi Huang ◽  
Jie Liu ◽  
Liang Luo ◽  
Pan Sheng ◽  
Biao Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Signaling Pathway ◽  
Risk Score ◽  
Low Risk ◽  
Training Data ◽  
The Cancer Genome Atlas ◽  
Training Set ◽  
Data Set ◽  
Validation Set ◽  
Cox Analysis

Background: Plenty of evidence has suggested that autophagy plays a crucial role in the biological processes of cancers. This study aimed to screen autophagy-related genes (ARGs) and establish a novel a scoring system for colorectal cancer (CRC). Methods: Autophagy-related genes sequencing data and the corresponding clinical data of CRC in The Cancer Genome Atlas were used as training data set. The GSE39582 data set from the Gene Expression Omnibus was used as validation set. An autophagy-related signature was developed in training set using univariate Cox analysis followed by stepwise multivariate Cox analysis and assessed in the validation set. Then we analyzed the function and pathways of ARGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Finally, a prognostic nomogram combining the autophagy-related risk score and clinicopathological characteristics was developed according to multivariate Cox analysis. Results: After univariate and multivariate analysis, 3 ARGs were used to construct autophagy-related signature. The KEGG pathway analyses showed several significantly enriched oncological signatures, such as p53 signaling pathway, apoptosis, human cytomegalovirus infection, platinum drug resistance, necroptosis, and ErbB signaling pathway. Patients were divided into high- and low-risk groups, and patients with high risk had significantly shorter overall survival (OS) than low-risk patients in both training set and validation set. Furthermore, the nomogram for predicting 3- and 5-year OS was established based on autophagy-based risk score and clinicopathologic factors. The area under the curve and calibration curves indicated that the nomogram showed well accuracy of prediction. Conclusions: Our proposed autophagy-based signature has important prognostic value and may provide a promising tool for the development of personalized therapy.

Serum microRNA signatures for the detection of pancreatobiliary cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15718-e15718
Author(s):  
Shuichi Mitsunaga ◽  
Shogo Nomura ◽  
Kazuo Hara ◽  
Yukiko Takayama ◽  
Makoto Ueno ◽  
...  
Keyword(s):  
Validation Cohort ◽  
External Validation ◽  
Diagnostic Value ◽  
Healthy Controls ◽  
Mirna Signature ◽  
Training Set ◽  
Linear Discriminant ◽  
Serum Mirna ◽  
Validation Set ◽  
Sensitivity Specificity

e15718 Background: The diagnostic value of serum microRNAs (miRNA) in a highly sensitive microarray for pancreatobiliary cancer (PBca) has been demonstrated. This study attempted to build and validate a signature comprised of multiple serum miRNA markers for discriminating PBca from healthy controls. Methods: A multicenter prospective study on the diagnostic performance of serum miRNAs was conducted. The patients (pts) with treatment-naïve PBca and healthy participants aged ≥60 years were enrolled. Clinical data and sera were collected. Target population was randomly divided to training or validation cohort with an allocation ratio of 2:1. Twenty-nine serum miRNA markers on the microarray data were analyzed. Using any combinations of the markers, a Fisher’s linear discriminant analysis was performed, and the resulting sensitivity, specificity and AUC of ROC curve to discriminate PBca from healthy controls were calculated for each combination. Marker combinations with a sensitivity/specificity (SN/SP) of ≥80%/90% and high AUC in comparison with AUC of CA19-9 were defined as the diagnostic miRNA signature, which were selected in the training cohort. Next, the signatures were screened out which showed a good reproducibility in the validation cohort. As an independent external cohort, PBca pts and healthy with pooled frozen sera were enrolled and the identified miRNA signatures were further validated. Results: Total of 546 participants (80 healthy and 223 PBca in training set, 40 healthy and 104 PBca in validation set, 49 healthy and 50 PBca in external validation set) were analyzed in this study. Four serum miRNA combinations were identified as the diagnostic miRNA signature. In the training set, four miRNA signatures, consisted of 10 miRNAs, were developed. For the best-performed miRNA signature, the SN/SP and AUC in the validation and external validation cohorts were 84/90% and 0.95 (CA19-9: 73/95% and 0.88) and 84/90% and 0.93 (CA19-9: 80/94% and 0.87), respectively. Conclusions: The diagnostic serum miRNA signatures for PBca were identified in this study.

scholarly journals Cervical Spine Osteoradionecrosis or Bone Metastasis after Radiotherapy for Nasopharyngeal Carcinoma? The MRI-Based Radiomics for Characterization

2020 ◽  
Author(s):  
Xi Zhong ◽  
Li Li ◽  
Huali Jiang ◽  
Jinxue Yin ◽  
Bingui Lu ◽  
...  
Keyword(s):  
Cervical Spine ◽  
Nasopharyngeal Carcinoma ◽  
Clinical Utility ◽  
Training Set ◽  
Decision Curve Analysis ◽  
Contrast Enhanced ◽  
Validation Set ◽  
Selection Operator ◽  
Radiomics Signature ◽  
Good Calibration

Abstract Background: To develop and validate an MRI-based radiomics nomogram for differentiation of cervical spine ORN from metastasis after radiotherapy (RT) in nasopharyngeal carcinoma (NPC).Methods: A radiomics nomogram was developed in a training set that comprised 46 NPC patients after RT with 95 cervical spine lesions (ORN, n = 51; metastasis, n = 44), and data were gathered from January 2008 to December 2012. 279 radiomics features were extracted from the axial contrast-enhanced T1-weighted image (CE-T1WI). A radiomics signature was created by using the least absolute shrinkage and selection operator (LASSO) algorithm. A nomogram model was developed based on the radiomics scores. The performance of the nomogram was determined in terms of its discrimination, calibration, and clinical utility. An independent validation set contained 25 consecutive patients with 47 lesions (ORN, n = 25; metastasis, n = 22) from January 2013 to December 2015. Results: The radiomics signature that comprised eight selected features was significantly associated with the differentiation of cervical spine ORN and metastasis. The nomogram model demonstrated good calibration and discrimination in the training set [AUC, 0.725; 95% confidence interval (CI), 0.622–0.828] and the validation set (AUC, 0.720; 95% CI, 0.573–0.867). The decision curve analysis indicated that the radiomics nomogram was clinically useful.Conclusions: MRI-based radiomics nomogram shows potential value to differentiate cervical spine ORN from metastasis after RT in NPC.

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