Cholangiocarcinoma: signalling pathways

Simon Tse
Learn about Cancer with Code
3 min readSep 14, 2022

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Credit: https://en.wikipedia.org/wiki/Cholangiocarcinoma

Background

In last post, I have extracted a list of genes that are associated with the tumour development specific to cholangiocarcinoma and what information one can obtain from KEGG database. If you miss that post, you can refer to below.

At the end of last post, I show that each gene can involve in several signalling pathways that control different aspects of cell fate. In this post, I am going to cover this specific area: signalling pathway.

Approach

Signalling pathways is collected under KEGG Network Database. Each network element is identified by the N number (e.g. N00001) and a typical representation of the signalling pathway would be like following:

EGF -> EGFR -> GRB2 -> SOS -> RAS -> RAF -> MEK -> ERK -> CCND1

Each code represents a gene/gene products while the interaction between two adjacent gene/gene products is represented by a sign to indicate specific type of interactions. Below table shows the signs and their corresponding interaction type.

Credit: https://www.kegg.jp/kegg/network.html

In last post, I have retrieved following mutated genes that are found in cholangiocarcinoma.

['K-ras', 'mutation', '[HSA:3845]', '[KO:K07827]']
['p53', 'mutation', '[HSA:7157]', '[KO:K04451]']
['c-Met', 'overexpression', '[HSA:4233]', '[KO:K05099]']
['ERBB2', 'overexpression,amplification', '[HSA:2064]', '[KO:K05083]']
['p16/INK4A', 'mutation', '[HSA:1029]', '[KO:K06621]']
['COX2', 'overexpression', '[HSA:5743]', '[KO:K11987]']

To focus, I am going to work on the networks that is controlled by gene p16/INK4A.

Retrieve KEGG signalling network

p16/INK4A [1] is a protein that slows cell division by slowing the progression of the cell cycle from the G1 phase to the S phase, thereby acting as a tumor suppressor. It is encoded by the CDKN2A gene. A deletion (the omission of a part of the DNA sequence during replication) in this gene can result in insufficient or non-functional p16, accelerating the cell cycle and resulting in many types of cancer.

Let’s see what signalling networks are controlled by this protein. I am using following script to retrieve network information based on gene id HSA:1029.

Running this script will produce following result.

 ['p16/INK4A', 'mutation', 'N00066'],
['p16/INK4A', 'mutation', 'N00067'],
['p16/INK4A', 'mutation', 'N00069'],
['p16/INK4A', 'mutation', 'N00070'],
['p16/INK4A', 'mutation', 'N00071'],
['p16/INK4A', 'mutation', 'N00076'],
['p16/INK4A', 'mutation', 'N00494'],
['p16/INK4A', 'mutation', 'N00536']

Then I will run following code snippets to retrieve information on each signalling networks.

Then it will retrieve following information.

Default pathways

p16/INK4A N00066 CDKN2A -| MDM2 -| TP53 => CDKN1A -| (CCND+CDK4/6) -> RB1 // E2F
p16/INK4A N00069 CDKN2A -| (CCND+CDK4/6) -> RB1 // E2F
p16/INK4A N00494 TAX -| CDKN2A
p16/INK4A N00536 CDKN2A -| MDM2 -| TP53 => CDKN1A -| (CCNE+CDK2) -> RB1 // E2F

Deviant pathways

p16/INK4A N00067 CDKN2A* // MDM2 -| TP53 => CDKN1A -| (CCND+CDK4/6) -> RB1 // E2F
p16/INK4A N00070 CDKN2A* // (CCND+CDK4/6) -> RB1 // E2F
p16/INK4A N00071 CDKN2A* // (CCND+CDK4/6) -> RB1 // E2F
p16/INK4A N00076 CDKN2A* // MDM2 -| TP53 => CDKN1A -| (CCND+CDK4/6) -> RB1 // E2F

You will notice there is a asterisk next to CDKN2A. That means gene CDKN2A is mutated in those signalling pathways.

However, there is something wrong in those expressions. You will notice that, for example, this sign // is not found in the symbol list. That suggests the relationship between

CDKN2A* // MDM2
RB1 // E2F

is more complicated than the usual activation / inhibition or expression / repression. In order to understand the behaviour of this deviant pathway, we need more information.

Intermission

In this post, I cover how to retrieve signalling pathways that are controlled by specific gene/gene products and highlight missing information in those signalling pathway that needs to be elucidated.

In next post, I will look for way(s) to fill that missing link.

Stay tuned!

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Simon Tse
Learn about Cancer with Code

Try to apply my ML/NLP knowledge to problems I am interested in and create a narrative with the data. Current Interest: Cancer Biology