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Note: Only data from one genomic profile can be selected for each downloadquery.
Viewing and Interpreting the Results
NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptOn the basis of the query criteria, the portal classifies each gene in each sample as altered ornot altered, and this classification is used for all analysis and visualizations in the portal,each of which is represented on a separate tab. We describe the results shown in each tabbelow, using example queries. The query parameters representing the first four stepsoutlined in the previous section are shown on the figure associated with each example.Results Tab 1: OncoPrint—An OncoPrint is a concise and compact graphical summaryof genomic alterations in multiple genes across a set of tumor samples. Rows representgenes, and columns represent samples. Glyphs and color coding are used to summarizedistinct genomic alterations including mutations, CNAs (amplifications and homozygousdeletions), and changes in gene expression or protein abundance. Additional details areavailable by mousing over the event indicated on the gene and include the case ID (eachcase represents a patient sample or cell line), linked to the patient view page. For mutationevents, this also displays amino acid changes. By default, cases are sorted according toalterations. Users can also restore original case orders (alphabetical order by case ID for apredefined case lists, or the same order for a customized case list). Users also have theoption to remove unaltered cases from the visualization. By visualizing gene alterationsacross a set of cases, OncoPrints help identify trends such as mutual exclusivity or co-occurrence between genes within a gene set.
In addition to the OncoPrint, this results tab also includes information about the genes
queried that is available in the Sanger Cancer Gene Census and links to the Gene database inNCBI.
We use the OncoPrint from a query for alterations in the retinoblastoma (RB) pathway genesCDKN2A (encoding the cyclin-dependent kinase inhibitor p16), CDK4 (encoding cyclin-dependent kinase 4), and RB1 in glioblastoma multiforme (GBM) as an example (Fig. 2).From the OncoPrint, 65 cases (71%) have an alteration in at least one of the three genes,with the frequency of alteration in each of the three selected genes shown. For CDKN2A,most of the alterations are homozygous deletions, and there are a few mutations. The
alterations in CDK4 are amplifications. Events associated with RB1 included a deletion andseveral mutations (3). The alterations in these three genes are distributed in a nearly
mutually exclusive way across samples, which can be statistically analyzed and visualizedwith the Mutual Exclusivity tab.
1.Perform the query as specified in Fig. 2. Once the “submit” button is pressed, theOncoPrint result is displayed automatically.
2.Use the horizontal scroll bar if the genes do not fit the window.
3.
To make an OncoPrint more compact, there are three options available from the“Customize” button: (i) scale the OncoPrint by using the “Zoom” bar; (ii) remove
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cases without an alteration by selecting “Remove Unaltered Cases”; and (iii) select“Remove Whitespace” to eliminate the gaps between samples.
4.To restore the original case order (alphabetically by case ID or as defined by theuser in the original query), select “Restore Case Order” in the “Customize” options.5.To export the OncoPrint, choose to download the OncoPrint as an XML file inscalable vector graphic (SVG) format by pressing the SVG button.
6.To obtain additional information, mouse over the indicated alteration on the gene.7.
To modify or start a query, choose “Modify Query” above the tabs for the results.
Results Tab 2: Mutual Exclusivity—Biological processes or pathways in cancer areoften deregulated through different genes or by multiple different mechanisms. The conceptof mutual exclusivity can be exploited to identify previously unknown mechanisms thatcontribute to oncogenesis and cancer progression (12). In mutual exclusivity, events ingenes associated with a specific cancer tend to be mutually exclusive across a set of tumors—that is, each tumor is likely to have only one of the genetic events. The opposite situation(co-occurrence) is when genetic alterations occur in multiple genes in the same cancersample. The portal computes a set of simple statistics to identify patterns of mutual
exclusivity or co-occurrence. For each pair of query genes (G1 and G2), the portal calculatesan odds ratio (OR) (Eq. 1) that indicates the likelihood that the events in the two genes aremutually exclusive or co-occurrent across the selected cases:
(1)
Where A = number of cases altered in both genes; B = number of cases altered in G1 but notG2; C = number of cases altered in G2 but not G1; and D = number of cases altered inneither genes.
It then assigns each pair to one of five categories that are indicative of a tendency towardmutual exclusivity, of a tendency toward co-occurrence, or of no association. A legend isprovided with the analysis. To determine whether the identified relationship is significant foreach gene pair, the portal performs a Fisher's exact test.
Using the same query used for describing OncoPrints, the mutual exclusivity analysis showsthat events in the three selected genes tended to occur in a mutually exclusive way, but thepattern was only statistically significant for CDKN2A and CDK4, and for CDKN2A andRB1, but not for CDK4 and RB1, which may be due to the small sample size (Fig. 3). Thisfits with what is known about RB signaling in GBM, which can be deactivated by
inactivation of RB1 itself (through mutation or deletion), by activation of CDK4 (a CDKthat inhibits RB1 activity) through amplification, or by inactivation of the CDK inhibitorp16, which is encoded by CDKN2A, through deletion or mutation. Thus, a single alterationin one of these genes is sufficient to deactivate the pathway, and this is what the mutualexclusivity analysis showed.
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1.
Perform the query as specified in Fig. 3. Once the “submit” button is pressed, theOncoPrint result is displayed automatically.2.
Select the Mutual Exclusivity tab.
Note: This tab will only show if more than one gene is selected in the query.
Results Tab 3: Correlation Plots—The cBioPortal offers several different ways ofvisualizing discrete genetic events (CNAs or mutations) and continuous events, such as dataregarding mRNA or protein abundance, or DNA methylation.
For each gene specified in the query, the portal can generate various plots, depending on thedata available. The mRNA versus copy-number option displays a box-and-whisker plot toshow mRNA expression from user-selected data sources of a gene plotted in relation to itscopy-number status in each sample. Copy-number status can be homozygously deleted,heterozygously deleted, diploid, gained (meaning an amplification event with relatively fewcopies), or amplified (meaning an amplification event with many copies). The mRNA-versus-DNA methylation option displays a scatter plot of mRNA expression compared withDNA methylation data of a gene across all selected samples. A methylation beta-value is anestimate for the methylation level of a CpG locus using the ratio of intensities between
methylated and unmethylated alleles. The RPPA protein level versus mRNA option displaysa scatter plot of protein abundance compared with mRNA abundance for a gene across allselected samples.
Genes and data types are selected by using drop-down menus, and only those options forwhich data are available are provided in the menus. All plots can be exported as PDFdocuments for use in publications.
The example query to illustrate this type of analysis is a query of ERBB2 (a known proto-oncogene encoding an epidermal growth factor receptor) in colon and rectum
adenocarcinoma. ERBB2 is amplified in a subset of colorectal cancer samples (8). ThecBioPortal results show that ERBB2 mRNA is increased in the samples in which ERBB2 isamplified (Fig. 4A) and that the tumors with the highest amount of ERBB2 mRNA had thehighest amount of ERBB2 protein (Fig. 4B).
1.Perform the query shown in Fig. 4. Once the “submit” button is pressed, theOncoPrint result is displayed automatically.2.Select the Plots tab.
3.Select “mRNA expression (microarray)” from the first Data Types menu.4.Select “Putative copy-number alternations from GISTIC” from the second DataTypes menu.
5.Select “mRNA v. Copy Number” from the Plot Type menu.6.Press the arrow button to generate the graph shown in Fig. 4A.7.To export as a PDF, click the PDF link at the top near the graph title.8.
Select “RPPA protein level v. mRNA” from the Plot Type menu.
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9.Press the arrow button to generate the graph shown in Fig. 4B.
Note: If a combination that cannot be plotted is selected, an error message isdisplayed.
Results Tab 4: Mutations—The Mutations tab provides details as both a graphicalsummary and a customizable table about all nonsynonymous mutations identified in eachquery gene. The graphical summary shows the position and frequency of all mutations in thecontext of Pfam protein domains (13) encoded by the canonical gene isoform. All DNAmutations are standardized to the canonical RefSeq isoform (using Oncotator, http://www.broadinstitute.org/oncotator/). When a DNA mutation only affects noncanonicalisoforms, the mutations are not included in the graphical summary. Future versions of theportal will provide this information in a separate table.
Below the graphical summary is a table of all nonsynonymous mutations. This table, whichcan be sorted and filtered, provides the following information if the data are available: caseID for each sample (hyperlinked to the patient view page of the specific sample containingthe mutation); amino acid change; type of mutations (missense, nonsense, splice site,
frameshift insertion or deletion, in-frame insertion or deletion, nonstop, nonstart); number ofmutations at this position in COSMIC (Catalogue Of Somatic Mutations In Cancer) (14);predicted functional impact of missense mutations [with hyperlinks to Mutation Assessor(15) for the specified mutation and a multiple sequence alignment]; link to a 3D structurewith the mutation highlighted (with hyperlinks to Mutation Assessor); mutation status(somatic or germline–germline mutations are currently only provided for BRCA1 and
BRCA2 in some studies); validation status (valid or unknown); the sequencing center wherethe sample was sequenced and the mutation identified; variant allele frequency in the tumor;variant allele frequency in the matched normal sample; exact genomic position
(chromosome, start, end, reference allele, variant allele); variant and reference allele counts(the number of variant and reference alleles found in the sequencing results of tumor andnormal samples); and information about the affected isoform. The last three are not shownby default but may be displayed. Users can perform a search for any text in the table withthe search option.
The example query to illustrate this type of analysis is a query of ERBB2 in colon andrectum adenocarcinoma using only sequenced tumors (Fig. 5). The graphical summary ofthe mutations associated with this query showed that there are 10 ERBB2 nonsynonymousmutations in colorectal cancer samples, and four of them are V842I in the kinase domain(Fig. 5), suggesting that this is a hotspot for protein activation. From the table, the kinasedomain mutations at amino acids 755, 777, and 842 have been observed in several othercancer studies before (6, 8, and 2 COSMIC entries, respectively) (Fig. 5B).
1.Perform the query shown in Fig. 5.2.Select the Mutations tab.
3.
Mouse over the colored regions representing protein domains to view details aboutthe domain and its starting and ending residues in the protein sequence.
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