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. 2017 Apr 11;3(4):e00277.
doi: 10.1016/j.heliyon.2017.e00277. eCollection 2017 Apr.

Progression inference for somatic mutations in cancer

Leif E Peterson  1   2   3   4   5 , Tatiana Kovyrshina  1   6
Affiliations

Progression inference for somatic mutations in cancer

Leif E Peterson et al. Heliyon. .

Abstract

Computational methods were employed to determine progression inference of genomic alterations in commonly occurring cancers. Using cross-sectional TCGA data, we computed evolutionary trajectories involving selectivity relationships among pairs of gene-specific genomic alterations such as somatic mutations, deletions, amplifications, downregulation, and upregulation among the top 20 driver genes associated with each cancer. Results indicate that the majority of hierarchies involved TP53, PIK3CA, ERBB2, APC, KRAS, EGFR, IDH1, VHL, etc. Research into the order and accumulation of genomic alterations among cancer driver genes will ever-increase as the costs of nextgen sequencing subside, and personalized/precision medicine incorporates whole-genome scans into the diagnosis and treatment of cancer.

Keywords: Cancer research; Computational biology; Genetics; Oncology.

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Figures

Figure 1
Figure 1
Computational algorithm for Permutation-based Affinity Matrix (PBAM) method.
Figure 2
Figure 2
Box plot showing distribution of between-event PBAM cjk matrix element values used for weighted directed acyclic graph generation.
Figure 3
Figure 3
Box plot showing distribution of between-event MIBN MI(x,y) mutual information values used for weighted directed acyclic graph generation.
Figure 4
Figure 4
PBAM analysis results for Invasive Breast Carcinoma.
Figure 5
Figure 5
MIBN analysis results for Invasive Breast Carcinoma.
Figure 6
Figure 6
PBAM analysis results for Colorectal Adenocarcinoma.
Figure 7
Figure 7
MIBN analysis results for Colorectal Adenocarcinoma.
Figure 8
Figure 8
PBAM analysis results for Lung Adenocarcinoma.
Figure 9
Figure 9
MIBN analysis results for Lung Adenocarcinoma
Figure 10
Figure 10
PBAM analysis results for Ovarian Serous Cystadenocarcinoma.
Figure 11
Figure 11
MIBN analysis results for Ovarian Serous Cystadenocarcinoma.
Figure 12
Figure 12
PBAM analysis results for Prostate Adenocarcinoma.
Figure 13
Figure 13
MIBN analysis results for Prostate Adenocarcinoma.
Figure 14
Figure 14
PBAM analysis results for Renal Clear Cell Cancer.
Figure 15
Figure 15
MIBN analysis results for Renal Clear Cell Cancer.
Figure 16
Figure 16
PBAM analysis results for Stomach Adenocarcinoma.
Figure 17
Figure 17
MIBN analysis results for Stomach Adenocarcinoma.
Figure 18
Figure 18
PBAM analysis results for Uterine Corpus Endometrial Carcinoma.
Figure 19
Figure 19
MIBN analysis results for Uterine Corpus Endometrial Carcinoma.
Figure 20
Figure 20
PBAM analysis results for Acute Myelogenous Leukemia.
Figure 21
Figure 21
MIBN analysis results for Acute Myelogenous Leukemia.
Figure 22
Figure 22
PBAM analysis results for Brain Lower Grade Gliomas.
Figure 23
Figure 23
MIBN analysis results for Brain Lower Grade Gliomas.
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