OncoGenomics Explorer

MediSapiens LtdOncoGenomics Explorer – taming Big Data

March 2012

Which are the most frequently mutated genes in ovarian serous carcinoma?

Samples from ovarian serous carcinoma

TP53, BRCA1 and BRCA2 are the three most frequently mutated genes

TP53 is mutated in almost all tumors

Mutation of the p53 gene is the key event in the development of high-grade tumors.

Unlike low-grade serous carcinoma, mutations of KRAS, BRAF, or ERBB2 occur very infrequently in

high-grade carcinoma.

Most high-grade tumors are characterized by TP53 mutations and lack mutations of KRAS,

BRAF, or ERBB2

Vang R., et al., 2009: Ovarian low-grade and high-grade serous carcinoma: pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems.

Select the aforementioned group of samples from the Mutation Heat Map and examine a summary

of clinical variables

Results can also be viewed in tabular format and subsequently be exported for further analysis

Serous ovarian cancer is also characterized by a low prevalence but statistically

recurrent mutations in a number of other genes, including NF1, RB1 and FAT3.

Study for example the proportions of point mutations or AA types in NF1...

...or study the mutations in NF1 in detail with the Gene viewer

Can be zoomed all the way down to sequence level

- The blue boxes represent the exons - Substitutions are shown as red vertical lines, insertions as light blue triangles, and deletions as pink triangles

- The SIFT score predicts whether a mutation will affect protein function

Is there a correlation between copy number variations of CCNE1 and overall survival of

the patients ?

Select the gene/genes of interest, in this case CCNE1

Overall survival tends to be lower for patients with CCNE1 amplification

The Cancer Genome Atlas Research Network, 2011: Integrated genomic analyses of ovarian carcinoma

RAB25 seems to be epigenetically silenced in a subset of HG-OvCa tumors

The Cancer Genome Atlas Research Network, 2011: Integrated genomic analyses of ovarian carcinoma

Genes with correlated CNV and expression include KRAS, POP4 and C19orf2

Wrzeszczynski KO. et al, 2011: Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer

Are genes in a region of frequent copy number gain differentially expressed between amplified

and unamplified groups of samples?

Define the two groups to be compared, for example samples with copy number gain vs. samples with normal copy number

Select the genes to be included, for example all genes in chromosome region 3q26

A volcano plot presenting the results of expression analyses between amplified and unamplified

samples in the 3q26 region

The results are shown as a volcano plot that enables the identification of genes that display high differences in expression that also are statistically significant

MYNN is a gene that is located in a region of frequent copy number gain on 3q26.2. It is differently expressed

between amplified and unamplified groups

MYNN shows a strong correlation between copy number and expression

Ramakrishna M. et al., 2010: Identification of candidate growth promoting genes in ovarian cancer through integrated copy number and expression analysis

In the volcano plot, an interesting group of genes can be selected

Select for example genes with significant p-values and large difference estimates

A heat map can be drawn of the genes from the defined gene selection and of the samples from the two selected

sample groups

...and examine a summary of clinical covariates

Select an interesting cluster of samples in the heat map...

Find out how genetic values correlate with clinical reference data...

Study for example how expression values of genes in chromosome region 8p correlate with overall survival

...or how genetic values correlate with genetic reference data

Study for example how expression values of genes in chromosome region 8p correlate with CNVs of BRCA1

Interesting genes can be selected for further analysis

Several different applications with powerful filter options offer numerous ways to study a

dataset

OncoGenomics Explorer

Technology

Transcript of OncoGenomics Explorer

Oncogenomics to Target the Tumor Cell in its Microenvironment

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