iCAGES: integrated CAncer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes

Dong, Chengliang; Guo, Yunfei; Yang, Hui; He, Zhike; Liu, Xiaoming; Wang, Kai

doi:10.1186/s13073-016-0390-0

Cited by 47 publications

(46 citation statements)

References 76 publications

(120 reference statements)

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“…In the challenging process of identifying driver mutations, we analyzed recurrently mutated genes, bi-allelic alterations in the same gene, mutation type, iCAGES [18] candidate driver mutations, copy number and survival (Supplementary Tables 3, 4, 5, 6, 7, 8, 9, 10, Supplementary Figure 2). Using this approach, we identified 21 genes as possible candidate cancer driver genes (Table 1), including 7 top candidate genes: TP53 , FAT1 , DSEL , CALML5 , DCLRE1C , MUC16 and KBTBD8 .…”

Section: Resultsmentioning

confidence: 99%

The subclonal structure and genomic evolution of oral squamous cell carcinoma revealed by ultra-deep sequencing

et al. 2017

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Recent studies suggest that head and neck squamous cell carcinomas are very heterogeneous between patients; however the subclonal structure remains unexplored mainly due to studies using only a single biopsy per patient. To deconvolute the clonal structure and describe the genomic cancer evolution, we applied whole-exome sequencing combined with ultra-deep targeted sequencing on oral squamous cell carcinomas (OSCC). From each patient, a set of biopsies was sampled from distinct geographical sites in primary tumor and lymph node metastasis.We demonstrate that the included OSCCs show a high degree of inter-patient heterogeneity but a low degree of intra-tumor heterogeneity. However, some OSCC cancers contain complex subclonal architectures comprising distinct subclones only found in geographically distinct regions of the primary tumors. In several cases we find mutations in the primary tumor that are not present in the lymph node metastasis. We conclude that metastatic potential in our population is acquired early in tumor evolution as evident by the ongoing parallel evolution in several primary tumors.

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Section: Resultsmentioning

confidence: 99%

The subclonal structure and genomic evolution of oral squamous cell carcinoma revealed by ultra-deep sequencing

et al. 2017

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“…Prediction of driver genes and pathways. Driver genes were predicted using 4 distinct computational tools, including OncodriveCLUST v.0.4.1 (11), OncodriveFM v.0.0.1 (12), The integrated Cancer Genome Score (iCAGES,) (13) and Drivers Genes and Pathways (DrGaP v.0.1.0) (14). The parameters were set to default values.…”

Section: Methodsmentioning

confidence: 99%

Comprehensive characterization�of driver genes in diffuse large B�cell lymphoma

et al. 2020

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Diffuse large B cell lymphoma (DLBCL) is the most common hematological malignancy and is one of the most frequent non-Hodgkin lymphomas. Large-scale genomic studies have defined genetic drivers of DLBCL and their association with functional and clinical outcomes. However, the lymphomagenesis of DLBCL is yet to be fully understood.In the present study, four computational tools OncodriveFM, OncodriveCLUST, integrated Cancer Genome Score and Driver Genes and Pathways were used to detect driver genes and driver pathways involved in DLBCL. The aforementioned tools were also used to perform an integrative investigation of driver genes, including co-expression network, protein-protein interaction, copy number variation and survival analyses. The present study identified 208 driver genes and 31 driver pathways in DLBCL. IGLL5, MLL2, BTG2, B2M, PIM1, CARD11 were the top five frequently mutated genes in DLBCL. NOTCH3, LAMC1, COL4A1, PDGFRB and KDR were the 5 hub genes in the blue module that were associated with patient age. TP53, MYC, EGFR, PTEN, IL6, STAT3, MAPK8, TNF and CDH1 were at the core of the protein-protein interaction network. PRDM1, CDKN2A, CDKN2B, TNFAIP3, RSPO3 were the top five frequently deleted driver genes in DLBCL, while ACTB, BTG2, PLET1, CARD11, DIXDC1 were the top five frequently amplified driver genes in DLBCL. High EIF3B, MLH1, PPP1CA and RECQL4 expression was associated with decreased overall survival rate of patients with DLBCL. High XPO1 and LYN expression were associated with increased overall survival rate of patients with DLBCL. The present study improves the understanding of the biological processes and pathways involved in lymphomagenesis. The driver genes, EIF3B, MLH1, PPP1CA, RECQL4, XPO1 and LYN, pave the way for developing prognostic biomarkers and new therapeutic strategies for DLBCL.

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“…We predicted somatic driver genes using iCAGES [13], an efficient tool to search cancer driver genes, based on somatic mutation data of each case. Three layers of analysis steps were executed in iCAGES tool.…”

Section: Identification Of Somatic Driver Genesmentioning

confidence: 99%

Molecular subtyping and prognostic assessment based on tumor mutation burden in patients with lung adenocarcinomas

Wang

Xie

et al. 2019

Preprint

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Tumor mutation burden (TMB) is a potential biomarker for response to immunotherapy.The subset of patients with TMB has not been well characterized in lung adenocarcinomas. Here we performed molecular subtyping based on TMB and compared the features of different subtypes including clinical features, somatic driver genes and mutational signatures. We found that patients with lower tumor mutation burden had a longer disease-free survival, while higher tumor mutation burden is associated with smoking and aging. Analysis of somatic driver genes and mutational signatures demonstrates a significant association between somatic RYR2 mutations and the subtype with higher mutation burden. Overall, our study identified two molecular subtypes based on TMB and described the corresponding difference in their clinical and genomic levels.

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iCAGES: integrated CAncer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes

Cited by 47 publications

References 76 publications

The subclonal structure and genomic evolution of oral squamous cell carcinoma revealed by ultra-deep sequencing

The subclonal structure and genomic evolution of oral squamous cell carcinoma revealed by ultra-deep sequencing

Comprehensive characterization�of driver genes in diffuse large B�cell lymphoma

Molecular subtyping and prognostic assessment based on tumor mutation burden in patients with lung adenocarcinomas

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