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Modelling the Genetic and Epigenetic Signals in
Colon Cancer using a Bayesian Network
Irina A. Roznovăţ* and Heather J. Ruskin
Centre for Scientific Computing & Complex Systems Modelling (SCI-SYM),
School of Computing, Dublin City University,
Dublin, Ireland
*Corresponding author: [email protected]
Abstract—Cancer, the unregulated growth of cells, has been a major area of focus of research for years due to its impact on human
health. Cancer development can be traced back to aberrant modifications in genetic and epigenetic mechanisms within the body over
time. Giving that processing the human genome data in the laboratory is difficult, costly and time-consuming, computational modelling
is increasingly being employed to improve understanding of cancer mechanisms which determine the disease initiation and progression.
The current work aims, in part, to build a network-based model for genetic and epigenetic signals in colorectal cancer with a focus on
gene level and tumour pathways according to the interdependencies between the three main layers: micromolecular, gene interactions
and cancer stage levels.
Keywords—Genetic and epigenetic events; colon cancer; gene interactions; multilayer computational model; Bayesian network.
I.
INTRODUCTION
Cancer, the uncontrolled growth of cells caused by the deregulation of the key genes that control the cellular mechanisms, has
been a major area of interest in research for years due to its impact on human health. During the recent decades, a novel direction in
its research consists in identifying and studying the epigenetic events that affect gene expression in tumour pathways. Defined as
non-genetic hereditable modifications in chromatin structure [1], the epigenetic signals have been detected to aberrantly influence
the function of both tumour suppressor gene and oncogenes in the earliest stages of different neoplastic diseases [2]. Markers for
cancer initiation, the epigenetic events are already exploited in some cure against cancer, due to their reversibility property.
Nowadays, however, there is still a lack of precise information relating to gene control in different systems that leads to one or
more types of cancer and malignancy. This particular problem has motivated the development of the current computational model
for genetic and epigenetic signals in colon cancer. It aims to predict cancer initiation and progression with a focus on gene
interactions in tumour pathways.
II.
COLON CANCER MODEL
The current model is being developed according to the interdependencies between the three main layers: micromolecular, gene
interactions and cancer stage levels, following a Bayesian network approach to describe the gene relationships in different
pathology phenotype levels of colon cancer.
Hyper and hypomethylation, the epigenetic events associated with gene inactivation and respectively, with chromosomal
instability, have a direct influence on the DNA methylation1 (DNAm) level of a gene. In the current framework, the gene DNAm
level is updated mainly with respect to the data extracted from StatEpigen database [3] referring to gene mutations, hyper and
hypomethylation for different genes with a significant impact in colon cancer. In addition, based on the recently established
dependence between the post-transcriptional histone2 modifications (HM) and DNAm patterns, information about the core histone
methylation and acetylation (the addition of acetyl group to a chemical compound) is incorporated for computing a new gene
DNAm level [4], [5]. The authors reported that HM are more instable in nature than DNAm, and therefore, the relationships
between HM and DNAm are described using different dynamics.
The overall model layers also consider the ageing factor for updating the DNAm level and HM, since different genetic and
epigenetic events (mutations, deletions, DNAm, HM) have been reported as being progressive over time in cancer phenotype [6],
[7]. Additionally, given that the changes from a stem cell persist and are transmitted during the cellular division [8], the stem cell
property is integrated in the colorectal model.
1
The addition of a methyl group to cytosine ring
Histones are the proteins that pack DNA in nucleosomes. They are grouped in two categories: the core histones (H2A, H2B, H3, H4) and the linker histones (H1
and H5).
2
III.
FUTURE WORK
According to [9], a normal cell should be exposed to multiple successive “hits” to become cancerous. Some of the alterations
registered during the tumours development can be transmitted from generation to generation, and therefore, the risk of a new
cancer appearance is highly increased in these families. Based on these assumptions, the heredity factor will be an extension of
the gene framework presented here. Another further inclusion is represented by data on viral and bacterial infections in human
tumours. Their significant impact in cancer phenotype been reported in many studies during the recent decades [8], [10], [11]. In
[8], the authors showed that Helicobacter pylori plays an important role in gastric cancer development by increasing aberrantly
the DNAm level in stomach cells.
Subsequently, the initial colorectal cancer model will be extended to other types of cancer (breast, lung, stomach, ovarian)
following the knowledge about commonly mutated genes in cancer, such as tumour protein p53 (TP53) [12], nonpolyposis type 2
(MLH1), adenomatous polyposis coli (APC) [13]. Information about the environmental features and lifestyle characteristics, such
as exposure to chemicals, radiation, tobacco usage or alcohol consumption, highlighted in statistical reports [14], [15], will be
considered as another extension for the current model.
Finally, a parallel programing approach will be designed and implemented for describing the molecular events inside the gene
framework.
ACKNOWLEDGMENT
This project acknowledges financial support from CIESCI ERA-Net Complexity Project, (EC/IRCSET). Useful discussions
with colleagues in the Sci-Sym (ModSci) group and access to StatEpigen are also gratefully acknowledged.
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