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.

scholarly journals SEMA6D Expression and Patient Survival in Breast Invasive Carcinoma

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Dongquan Chen ◽  
Yufeng Li ◽  
Lizhong Wang ◽  
Kai Jiao
Keyword(s):  
Breast Cancer ◽  
Expression Profile ◽  
Heart Development ◽  
Invasive Carcinoma ◽  
Patient Survival ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Patients ◽  
Genomic Expression ◽  
Cancer Genome Atlas ◽  
Public Datasets

Breast cancer (BC) is the second most common cancer diagnosed in American women and is also the second leading cause of cancer death in women. Research has focused heavily on BC metastasis. Multiple signaling pathways have been implicated in regulating BC metastasis. Our knowledge of regulation of BC metastasis is, however, far from complete. Identification of new factors during metastasis is an essential step towards future therapy. Our labs have focused on Semaphorin 6D (SEMA6D), which was implicated in immune responses, heart development, and neurogenesis. It will be interesting to know SEMA6D-related genomic expression profile and its implications in clinical outcome. In this study, we examined the public datasets of breast invasive carcinoma from The Cancer Genome Atlas (TCGA). We analyzed the expression of SEMA6D along with its related genes, their functions, pathways, and potential as copredictors for BC patients’ survival. We found 6-gene expression profile that can be used as such predictors. Our study provides evidences for the first time that breast invasive carcinoma may contain a subtype based on SEMA6D expression. The expression of SEMA6D gene may play an important role in promoting patient survival, especially among triple negative breast cancer patients.

Metabolic gene signature for predicting breast cancer recurrence using transcriptome analysis

2021 ◽  
Author(s):  
Juan Feng ◽  
Jun Ren ◽  
Qingfeng Yang ◽  
Lingxia Liao ◽  
Le Cui ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Recurrence ◽  
Recurrence Risk ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Patients ◽  
Metabolic Gene ◽  
Limma Package ◽  
Cancer Genome Atlas

Background: The study aimed at identifying a metabolic gene signature for stratifying the risk of recurrence in breast cancer. Materials & Methods: The data of patients were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The limma package was used to identify differentially expressed metabolic genes, and a metabolic gene signature was constructed. Results: A five-gene metabolic signature was established that demonstrated satisfactory accuracy and predictive power in both training and validation cohorts. Also, a nomogram for predicting recurrence-free survival was established using a combination of the metabolism gene risk score and the clinicopathological features. Conclusions: The proposed metabolic gene signature and nomogram have a significant prognostic value and may improve the recurrence risk stratification for breast cancer patients.

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.

Tumor mutation burden in triple negative breast cancer patients in Japan.

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. e13111-e13111 ◽  
Author(s):  
Masayuki Nagahashi ◽  
Yiwei Ling ◽  
Tetsu Hayashida ◽  
Yuko Kitagawa ◽  
Manabu Futamura ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Cancer Patients ◽  
Tumor Mutation Burden ◽  
Mutation Burden

scholarly journals Comparison of commonly used solid tumor targeted gene sequencing panels for estimating tumor mutation burden shows analytical and prognostic concordance within the cancer genome atlas cohort

2020 ◽  
Vol 8 (1) ◽  
pp. e000613
Author(s):  
Nicholas Bevins ◽  
Shulei Sun ◽  
Zied Gaieb ◽  
John A Thorson ◽  
Sarah S Murray
Keyword(s):  
Solid Tumor ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Tumor Mutation Burden ◽  
Whole Exome ◽  
Mutation Burden ◽  
Cancer Genome Atlas ◽  
Gene Panels ◽  
The Impact ◽  
Genome Atlas

BackgroundTumor mutation burden (TMB) is a biomarker frequently reported by clinical laboratories, which is derived by quantifying of the number of single nucleotide or indel variants (mutations) identified by next-generation sequencing of tumors. TMB values can inform prognosis or predict the response of a patient’s tumor to immune checkpoint inhibitor therapy. Methods for the calculation of TMB are not standardized between laboratories, with significant variables being the gene content of the panels sequenced and the inclusion or exclusion of synonymous variants in the calculations. The impact of these methodological differences has not been investigated and the concordance of reported TMB values between laboratories is unknown.MethodsSequence variant lists from more than 9000 tumors of various types were downloaded from The Cancer Genome Atlas. Variant lists were filtered to include only appropriate variant types (ie, non-synonymous only or synonymous and non-synonymous variants) within the genes found in five commonly used targeted solid tumor gene panels as well as an in-house gene panel. Calculated TMB was paired with corresponding overall survival (OS) data of each patient.ResultsRegression analysis indicates high concordance of TMB as derived from the examined panels. TMB derived from panels was consistently and significantly lower than that derived from a whole exome. TMB, as derived from whole exome or the examined panels, showed a significant correlation with OS in the examined data.ConclusionsTMB derived from the examined gene panels was analytically equivalent between panels, but not between panels and whole-exome sequencing. Correlation between TMB and OS is significant if TMB method-specific cut-offs are used. These results suggest that TMB values, as derived from the gene panels examined, are analytically and prognostically equivalent.

scholarly journals Role of tumor mutation burden-related signatures in the prognosis and immune microenvironment of pancreatic ductal adenocarcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rong Tang ◽  
Xiaomeng Liu ◽  
Wei Wang ◽  
Jie Hua ◽  
Jin Xu ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Predictive Accuracy ◽  
The Cancer Genome Atlas ◽  
Ductal Adenocarcinoma ◽  
Immune Microenvironment ◽  
Tumor Mutation Burden ◽  
Oncogenic Pathways ◽  
Mutation Burden ◽  
Cancer Genome Atlas

Abstract Background High tumor mutation burden (TMB) has gradually become a sensitive biomarker for predicting the response to immunotherapy in many cancers, including lung, bladder and head and neck cancers. However, whether high TMB predicts the response to immunotherapy and prognosis in pancreatic ductal adenocarcinoma (PDAC) remained obscure. Hence, it is significant to investigate the role of genes related to TMB (TRGs) in PDAC. Methods The transcriptome and mutation data of PDAC was downloaded from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA). Five independent external datasets of PDAC were chosen to validate parts of our results. qRT-PCR and immunohistochemical staining were also performed to promote the reliability of this study. Results The median overall survival (OS) was significantly increased in TMB_low group compared with the counterpart with higher TMB score after tumor purity adjusted (P = 0.03). 718 differentially expressed TRGs were identified and functionally enriched in some oncogenic pathways. 67 TRGs were associated with OS in PDAC. A prognostic model for the OS was constructed and showed a high predictive accuracy (AUC = 0.849). We also found TMB score was associated with multiple immune components and signatures in tumor microenvironment. In addition, we identified a PDAC subgroup featured with TMBlowMicrosatellite instabilityhigh (MSIhigh) was associated with prolonged OS and a key molecule, ANKRD55, potentially mediating the survival benefits. Conclusion This study analyzed the biological function, prognosis value, implications for mutation landscape and potential influence on immune microenvironment of TRGs in PDAC, which contributed to get aware of the role of TMB in PDAC. Future studies are expected to investigate how these TRGs regulate the initiation, development or repression of PDAC.

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