scholarly journals Identification of Potential Driver Genes Based on Multi-Genomic Data in Cervical Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuexun Xu ◽  
Hui Luo ◽  
Qunchao Hu ◽  
Haiyan Zhu
Keyword(s):  
Cervical Cancer ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Driver Genes ◽  
Molecular Alterations ◽  
Wide Range ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Significant Expression

Background: Cervical cancer became the third most common cancer among women, and genome characterization of cervical cancer patients has revealed the extensive complexity of molecular alterations. However, identifying driver mutation and depicting molecular classification in cervical cancer remain a challenge.Methods: We performed an integrative multi-platform analysis of a cervical cancer cohort from The Cancer Genome Atlas (TCGA) based on 284 clinical cases and identified the driver genes and possible molecular classification of cervical cancer.Results: Multi-platform integration showed that cervical cancer exhibited a wide range of mutation. The top 10 mutated genes were TTN, PIK3CA, MUC4, KMT2C, MUC16, KMT2D, SYNE1, FLG, DST, and EP300, with a mutation rate from 12 to 33%. Applying GISTIC to detect copy number variation (CNV), the most frequent chromosome arm-level CNVs included losses in 4p, 11p, and 11q and gains in 20q, 3q, and 1q. Then, we performed unsupervised consensus clustering of tumor CNV profiles and methylation profiles and detected four statistically significant expression subtypes. Finally, by combining the multidimensional datasets, we identified 10 potential driver genes, including GPR107, CHRNA5, ZBTB20, Rb1, NCAPH2, SCA1, SLC25A5, RBPMS, DDX3X, and H2BFM.Conclusions: This comprehensive analysis described the genetic characteristic of cervical cancer and identified novel driver genes in cervical cancer. These results provide insight into developing precision treatment in cervical cancer.

scholarly journals Inferring perturbation profiles of cancer samples

2020 ◽  
Author(s):  
Martin Pirkl ◽  
Niko Beerenwinkel
Keyword(s):  
Indirect Evidence ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Patient Specific ◽  
Driver Genes ◽  
Cancer Driver ◽  
Molecular Alterations ◽  
Incomplete Coverage ◽  
Cancer Genome Atlas ◽  
Gene Perturbations

AbstractMotivationCancer is one of the most prevalent diseases in the world. Tumors arise due to important genes changing their activity, e.g., when inhibited or over-expressed. But these gene perturbations are difficult to observe directly. Molecular profiles of tumors can provide indirect evidence of gene perturbations. However, inferring perturbation profiles from molecular alterations is challenging due to error-prone molecular measurements and incomplete coverage of all possible molecular causes of gene perturbations.ResultsWe have developed a novel mathematical method to analyze cancer driver genes and their patient-specific perturbation profiles. We combine genetic aberrations with gene expression data in a causal network derived across patients to infer unobserved perturbations. We show that our method can predict perturbations in simulations, CRISPR perturbation screens, and breast cancer samples from The Cancer Genome Atlas.AvailabilityThe method is available as the R-package nempi at https://github.com/cbg-ethz/[email protected], [email protected]

scholarly journals An integrative analysis of the age-associated multi-omic landscape across cancers

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Kasit Chatsirisupachai ◽  
Tom Lesluyes ◽  
Luminita Paraoan ◽  
Peter Van Loo ◽  
João Pedro de Magalhães
Keyword(s):  
The Cancer Genome Atlas ◽  
Driver Genes ◽  
Cancer Driver ◽  
Molecular Alterations ◽  
Age Related ◽  
Incidence And Mortality ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Using Data ◽  
Transcriptomic Changes

AbstractAge is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterise genomic, transcriptomic and epigenetic alterations in relation to patients’ age across cancer types. We show that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations are identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences are found in gliomas and endometrial cancer. We identify age-related global transcriptomic changes and demonstrate that these genes are in part regulated by age-associated DNA methylation changes. This study provides a comprehensive, multi-omics view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.

scholarly journals An Integrative Analysis of the Age-Associated Genomic, Transcriptomic and Epigenetic Landscape across Cancers

2020 ◽  
Author(s):  
Kasit Chatsirisupachai ◽  
Tom Lesluyes ◽  
Luminita Paraoan ◽  
Peter Van Loo ◽  
João Pedro de Magalhães
Keyword(s):  
The Cancer Genome Atlas ◽  
Driver Genes ◽  
Cancer Driver ◽  
Molecular Alterations ◽  
Age Related ◽  
Incidence And Mortality ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Using Data ◽  
Transcriptomic Changes

AbstractAge is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterised genomic, transcriptomic and epigenetic alterations in relation to patients’ age across cancer types. We showed that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations were identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences were found in gliomas and endometrial cancer. We identified age-related global transcriptomic changes and demonstrated that these genes are controlled by age-associated DNA methylation changes. This study provides a comprehensive view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.

scholarly journals Inferring perturbation profiles of cancer samples

2021 ◽  
Author(s):  
Martin Pirkl ◽  
Niko Beerenwinkel
Keyword(s):  
Indirect Evidence ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Supplementary Information ◽  
Patient Specific ◽  
Driver Genes ◽  
Cancer Driver ◽  
Molecular Alterations ◽  
Incomplete Coverage ◽  
Gene Perturbations

Abstract Motivation Cancer is one of the most prevalent diseases in the world. Tumors arise due to important genes changing their activity, e.g. when inhibited or over-expressed. But these gene perturbations are difficult to observe directly. Molecular profiles of tumors can provide indirect evidence of gene perturbations. However, inferring perturbation profiles from molecular alterations is challenging due to error-prone molecular measurements and incomplete coverage of all possible molecular causes of gene perturbations. Results We have developed a novel mathematical method to analyze cancer driver genes and their patient-specific perturbation profiles. We combine genetic aberrations with gene expression data in a causal network derived across patients to infer unobserved perturbations. We show that our method can predict perturbations in simulations, CRISPR perturbation screens and breast cancer samples from The Cancer Genome Atlas. Availability and implementation The method is available as the R-package nempi at https://github.com/cbg-ethz/nempi and http://bioconductor.org/packages/nempi. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiming Wang ◽  
Yan Cai ◽  
Xuewen Fu ◽  
Liang Chen
Keyword(s):  
Cervical Cancer ◽  
Poor Prognosis ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Cervical Cancer Cells ◽  
Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

scholarly journals The Prognostic Significance of MAFK and its Methylation in Cervical Cancer

2021 ◽  
Author(s):  
Mengjun Zhang ◽  
Hao Li ◽  
Yuan Liu ◽  
Siyu Hou ◽  
Ping Cui ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Aberrant Methylation ◽  
Cancer Data ◽  
Drug Candidates ◽  
Cancer Genome Atlas ◽  
Cancer Tissues

Abstract Background: The purpose of this study was to determine the value of MAFK as a biomarker of cervical cancer prognosis and to explore its methylation and possible cellular signaling pathways. Methods: We analyzed the cervical cancer data of The Cancer Genome Atlas (TCGA) through bioinformatics, including MAFK expression, methylation, prognosis and genome enrichment analysis. Results: MAFK expression was higher in cervical cancer tissues and was negatively correlated with the methylation levels of five CpG sites. MAFK is an independent prognostic factor of cervical cancer and is involved in the Nod-like receptor signaling pathway. CMap analysis screened four drug candidates for cervical cancer treatment. Conclusions: We confirmed that MAFK is a novel prognostic biomarker for cervical cancer and aberrant methylation may also affect MAFK expression and carcinogenesis. This study provides a new molecular target for the prognostic evaluation and treatment of cervical cancer.

scholarly journals Comprehensive Analysis of The Significance of Hypoxia-Related Genes in Ovarian Cancer

2021 ◽  
Author(s):  
Wancheng Zhao ◽  
Lili Yin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Mesenchymal Transition ◽  
Principal Component ◽  
Vital Role ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Mesenchymal Transition ◽  
Cancer Genome Atlas ◽  
Pca Algorithm

Abstract Background: Hypoxia-related genes have been reported to play important roles in a variety of cancers. However, their roles in ovarian cancer (OC) have remained unknown. The aim of our research was to explore the significance of hypoxia-related genes in OC patients.Methods: In this study, 15 hypoxia-related genes were screened from The Cancer Genome Atlas (TCGA) database to group the ovarian cancer patients using the consensus clustering method. Principal component analysis (PCA) was performed to calculate the hypoxia score for each patient to quantify the hypoxic status. Results: The OC patients from TCGA-OV dataset were divided into two distinct hypoxia statuses (cluster.A and cluster.B) based on the expression level of the 15 hypoxia-related genes. Most hypoxia-related genes were expressed more highly in the cluster.A group than in the cluster.B group. We also found that patients in the cluster.A group exhibited higher expression of immune checkpoint-related genes, epithelial-mesenchymal transition-related genes, and immune activation-related genes, as well as elevated immune infiltrates. PCA algorithm indicated that patients in the cluster.A group had higher hypoxia scores than that in in the cluster.B group.Conclusions: In summary, our research elucidated the vital role of hypoxia-related genes in immune infiltrates of OC. Our investigation of hypoxic status may be able to improve the efficacy of immunotherapy for OC.

Heterogeneity of MSI-H gastric cancer identifies a subtype with worse survival

2020 ◽  
Vol 58 (1) ◽  
pp. 12-19 ◽  
Author(s):  
Yanmei Yang ◽  
Zhong Shi ◽  
Rui Bai ◽  
Wangxiong Hu
Keyword(s):  
Immune Checkpoint Blockade ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Synonymous Mutations ◽  
The Poor ◽  
Symptom Alleviation ◽  
Cancer Genome Atlas ◽  
Stomach Adenocarcinoma ◽  
Asian Cohort ◽  
Matrix Factorisation

BackgroundMicrosatellite instability-high (MSI-H) tumour patients generally have a better prognosis than microsatellite-stable (MSS) ones due to the large number of non-synonymous mutations. However, an increasing number of studies have revealed that less than half of MSI-H patients gain survival benefits or symptom alleviation from immune checkpoint-blockade treatment. Thus, an in-depth inspection of heterogeneous MSI-H tumours is urgently required.MethodsHere, we used non-negative matrix factorisation (non-NMF)-based consensus clustering to define stomach adenocarcinoma (STAD) MSI-H subtypes in samples from The Cancer Genome Atlas and an Asian cohort, GSE62254.ResultsMSI-H STAD samples are basically clustered into two subgroups (MSI-H1 and MSI-H2). Further examination of the immune landscape showed that immune suppression factors were enriched in the MSI-H1 subgroup, which may be associated with the poor prognosis in this subgroup.ConclusionsOur results illustrate the genetic heterogeneity within MSI-H STADs, with important implications for cancer patient risk stratification, prognosis and treatment.

scholarly journals 46 Integration of multiple platforms to discover idh-mutant glioma subtypes

2018 ◽  
Vol 45 (S3) ◽  
pp. S14-S15
Author(s):  
Yasin Mamatjan ◽  
Farshad Nassiri ◽  
Severa Bunda ◽  
Fabio Moraes ◽  
Kenneth D. Aldape ◽  
...  
Keyword(s):  
Hox Genes ◽  
The Cancer Genome Atlas ◽  
Research Network ◽  
P Value ◽  
Biologically Relevant ◽  
Group 4 ◽  
Wide Range ◽  
Diffuse Gliomas ◽  
Cancer Genome Atlas ◽  
Promoter Mutations

Purpose: Diffuse gliomas can be divided on the basis of presence or absence of mutation in IDH genes. IDH-mutant diffuse gliomas represent a wide range of clinical outcome, which is not accounted for by current clinical and pathologic parameters. We aim to identify clinically and biologically relevant subgroups within IDH-mutant gliomas to gain a deeper insight into finer sub-classification. Methods: We used 412 IDH-mutant glioma samples that were profiled by The Cancer Genome Atlas (TCGA) Research Network, utilising methylation/mRNA datasets to identify subtypes with unique molecular signatures. We applied a Similarity Network Fusion (SNF) on individual platforms and their integrations. Results: SNF approach split glioma into four groups. The integrated RNA/methylation subtype produced a highly prognostic groups that predict survival (p-value=0.003) compared to mRNA and methylation alone. We observed a high degree of correlation between integrative subtypes and somatic mutations. Groups 1&4 had higher TERT promoter mutations (35% and 16%, respectively) compared to groups 2&3. Groups 1&4 showed increased TERT expression (34% and 14% respectively), and high percentage of TP53 and ATRX mutations. Multivariate analysis after adjusting for confounding factors including grade and age showed prognostic factors associated with survival (HR=3.2, p-value=0.001) in group 4 versus others. Conclusions: The results indicate that clinically relevant alterations exist within IDH-mutant gliomas that could stratify patients for treatment. Interestingly, group 4 showed high expression of HOX genes (18/18) (p-value=0.01) and higher methylation of Hox genes (21) (p-value=0.01) compared to others. Higher expression of specific Hox genes were associated with worse survival.

scholarly journals Interfocal heterogeneity challenges the clinical usefulness of molecular classification of primary prostate cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kristina Totland Carm ◽  
Andreas M. Hoff ◽  
Anne Cathrine Bakken ◽  
Ulrika Axcrona ◽  
Karol Axcrona ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Classification ◽  
Primary Diagnosis ◽  
The Cancer Genome Atlas ◽  
Clinical Usefulness ◽  
Whole Exome ◽  
Primary Prostate Cancer ◽  
Cancer Genome Atlas ◽  
Prostate Cancers

Abstract Prostate cancer is a highly heterogeneous disease and typically multiple distinct cancer foci are present at primary diagnosis. Molecular classification of prostate cancer can potentially aid the precision of diagnosis and treatment. A promising genomic classifier was published by The Cancer Genome Atlas (TCGA), successfully classifying 74% of primary prostate cancers into seven groups based on one cancer sample per patient. Here, we explore the clinical usefulness of this classification by testing the classifier’s performance in a multifocal context. We analyzed 106 cancer samples from 85 distinct cancer foci within 39 patients. By somatic mutation data from whole-exome sequencing and targeted qualitative and quantitative gene expression assays, 31% of the patients were uniquely classified into one of the seven TCGA classes. Further, different samples from the same focus had conflicting classification in 12% of the foci. In conclusion, the level of both intra- and interfocal heterogeneity is extensive and must be taken into consideration in the development of clinically useful molecular classification of primary prostate cancer.

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