The Stanford-Cancer Genome Atlas Portal allows users to explore clinical associations of cancer drivers in three main ways: 1. By searching a gene/miR/protein name to see associated clinical parameters or filtering by cancer type and clinical parameter. 2. By profiling genetic/proteomic changes between classes of a selected clinical parameter in a cancer type. 3. By testing the "two hit hypothesis" to see if two genetic/proteomic changes occur together more than expected by chance.

1. THE STANFORD-CANCER GENOME ATLAS PORTAL:
A WEB/MOBILE NAVIGATION INTERFACE FOR EXPLORING THE
CLINICAL ASSOCIATIONS OF CANCER DRIVERS
Tutorial: How to navigate the web portal

2. Three ways of looking TCGA data
What are the clinically relevant genes/miRs/proteins?
• By name of genes, miRs or proteins
• By cancer type
• By clinical parameters
Profiling by clinical parameters:
What is the difference in genetic/proteomic changes
between classes in a clinical parameter in a certain
cancer?
Two hit hypothesis test:
Do the two genetic/proteomic changes occur together
or not?
I
II
III

3. I. Checking what clinical parameters are associated with
genes/miRs/proteins of your interest
Type the name of gene/miR/protein here:
Ex) TP53
Click Submit

4. I. Checking what clinical parameters are associated with
genes/miRs/proteins of your interest
Type the name of gene/miR/protein here:
Ex) TP53
Click Submit
Get to the summary page of TP53

5. I. Check what clinical parameters are associated with
genes/miRs/proteins of your interest
TP53 is associated with:
i) Race in breast cancer
ii) Triple marker in breast cancer
iii) N-Status in thyroid cancer
iv) Histo grade in uterine cancer

6. The mutation frequency of genes/miRs/proteins of your interest
across all cancer types
Sort function

7. The copy number variation frequency of genes/miRs/proteins of
your interest across all cancer types

8. I. What are the clinically relevant genes/miRs/proteins?
When you are interested in a certain cancer type, click here and select a cancer type

9. I. What are the clinically relevant genes/miRs/proteins?
If you select COADREAD, webpage shows the summary list with clinical parameters that are
available in COADREAD

10. I. What are the clinically relevant genes/miRs/proteins?
If you select genes in ClinicalStage, webpage shows the list of genes associated with a clinical stage in
COADREAD

11. I. What are the clinically relevant genes/miRs/proteins?
Clinical parameters with categorical values; click each class in a clinical parameter

12. I. What are the clinically relevant genes/miRs/proteins?
When you are interested in a clinical parameter, click here and select a clinical parameter

13. I. What are the clinically relevant genes/miRs/proteins?
If you select clinical stage, the web page shows the summary list from all the cancer types
currently in our data set where clinical stage is available. This is a pan-TCGA summary type
page.

14. I. What are the clinically relevant genes/miRs/proteins?
If you select genes in STAD, the web page shows the list of genes associated with a clinical stage in
stomach cancers

15. I. In summary, you can get to the summary page of WRN which is
associated with clinical stage in colorectal cancer three different ways

16. I. In summary, you can get to the summary page of WRN which is
associated with clinical stage in colorectal cancer by three different ways

17. II. Profiling by Clinical Parameter
When you want to know the differences of a gene between samples with different
clinical parameter types - in terms of genetic/proteomic profiling - use the middle
panel
How does PIK3CA behave differently between EBV infected and non-infected
samples in stomach cancer?
1. Type PIK3CA
2. Select STAD
3. Select EBV present
4. Click Submit

18. II. Profiling by Clinical Parameter
Summary of PIK3CA CNV between EBV infected and
non-infected samples in stomach cancer

19. II. Profiling by Clinical Parameter
Difference in PIK3CA mutations between EBV infected and non-infected samples in stomach cancer

20. II. Profiling by Clinical Parameter
Difference in expression level of PIK3CA between EBV infected and non-infected samples in stomach cancer

21. III. Two hit hypothesis test
What is the difference in copy number changes of TP53 between samples with and
without TP53 mutation in colorectal cancers?
Second level sample group:
With this example, it will then split colorectal cancers
into two groups –
i) samples with TP53 mutation
ii) samples without TP53 mutations
First level sample group:
With this example, what is the distribution of copy
number changes of TP53 in each group?

22. III. Testing two hit hypothesis
Summarize the copy number changes of TP53 by samples with/without TP53
mutations in colorectal cancers

23. III. Testing two hit hypothesis
Summarize the copy number changes of TP53 by samples with/without TP53
mutations in colorectal cancers
Hemizygous deletion occurred significantly more in samples with TP53 mutations than samples without
TP53 mutations