introduction to cancer bioinformatics

1. Introduction to Cancer Bioinformatics
Cancer is a disease caused by some genetic and epigenetic changes. In its simplest
form, cancer is a genetic disease caused by a cell genome change which includes
point mutation, insertion mutation, deletion mutation and chromosome translocation.
At present, the basic research of cancer is undergoing a revolution in genetics.
Cancer bioinformatics promotes the progress of science and technology in the post
genomic era, which enables molecular biologists to study DNA (genome), mRNA
(transcriptome) and protein sequence (proteome) more precisely. Describing the
mechanism of cancer in a comprehensive context provides an opportunity for
researchers to obtain more useful data for analysis and combining them in a new way.
Database resources of cancer bioinformatics
1. CGAP
The Cancer Genome Anatomy Project (CGAP) was initiated and maintained by the
National Cancer Institute (NCI) in 1996. So far, it has become the first in the field of
cancer genetics. In addition, the program has used new technologies to build hundreds
of libraries. The new technologies mentioned include serial analysis of gene
expression (SAGE) and massively parallel signaling sequencing (MPSS). SAGE
technology is a comprehensive analysis method for rapid analysis of gene expression
information developed in recent years, and it is one of the best methods for
recognized transcriptome profiling research. MPSS is a large-scale, high-throughput
new technology for gene analysis based on DNA sequencing. It can obtain the gene
expression sequence through the establishment of tag library, the connection of
microbeads to tags, enzymatic digestion ligation reaction and biological information
analysis. MPSS has the characteristics of low expression level, small gene difference,
no need to know the sequence of genes in advance, automation and high throughput.
2. HCGP
In Brazil, the FAPESP/LICR Human Cancer Genome Project (HCGP) has studied
EST from more than 1 million prevalent tumors using a new technology called open
reading frame EST. The expression sequences studied by CGAP and HCGP were
integrated into the International Database Cancer Gene Expression. Both CGAP and
HCGP programs have been combined, which essentially share a common goal—to
create a catalogue of cancer expression, and they annotate and submit to GenBank
sequences of millions of tumors and normal tissues. The aim of these two programs is

2. to determine the unique expression patterns of genes in normal cells, precancerous
cells and cancer cells, with a view to improving the detection, diagnosis and treatment
of patients.
3. CaBIG
The Cancer Biomedical Information Grid (caBIG) is an ambitious new program
funded and maintained by the American Cancer Institute (NCI). It aims to establish a
cancer network that integrates four types of information: information interfaces,
vocabulary/terminology and ontology, data elements and information models. The
caBIG initiative is a grid project organized voluntarily by researchers and
organisations with the goal of creating a global network of cancer research. To this
end, efforts have been made to develop standards for the application and analysis
process so that cooperation and data sharing can be more easily carried out. In
addition, caBIG undertook development projects in different fields, such as the
development of clinical trial management systems, Ontology acquisition tools and in
vivo imaging systems.
Methods applied in cancer bioinformatics
With the generation of large-scale data and the advent of analytical techniques, the
pattern of cancer research is changing. The application of genomics, transcriptomics,
proteomics, and bioinformatics has enabled people to test a large number of new
hypotheses, thus contributing to the development of cancer research. The application
of these large-scale technologies has expanded the detectable number of genetic
variants associated with the development of specific types of cancer and has been able
to integrate molecular characteristics to predict cancer and treatment response.
1. Genomics
The so-called genomics refers to the development and application of DNA maps, new
sequencing technologies and computer programs to analyze the whole genome
structure and function of the living body. An important new content of genomics
technology is the incorporation of biomedical research, and the most relevant one is
"cancer genomics" that integrates a large amount of data and computer resources and
helps to study the genomic structural changes of cancer cells or cancer tissues.
2. Transcriptomics
All transcripts of a genome at any time are called transcriptomes. Similar to genomics
concepts, transcriptomics is defined as the science of comprehensively studying the
transcriptome. Unlike the genome, the transcriptome is very dynamic, not only
between different tissues of the same organism, but also between pathological status,
such as cancerous and healthy tissues. Based on this result, many researchers have
studied the expression profiles of a large number of genes and tried to identify the
expression of genes in cancer tissues.
3. Proteomics
Protein is an important component of organisms and participates in almost all
physiological and cellular metabolic processes. Large-scale studies of all proteins
expressed in a cell or tissue, their modifications and interactions are called proteomics
which is generally considered the next step in the study of biological systems after
genomics and transcriptomics. However, proteome research is far more complex than

3. genomics, which is determined by the intrinsic complex characteristics of proteins,
such as the wide variety of post-translational modifications of proteins.
Cancer bioinformatics deals with organization and data so that important trends and
patterns can be identified, with the ultimate goal of discovering new therapeutic
and/or diagnostic options for cancer. The first step towards this goal is to find a
blueprint for gene expression that represents specific cancer conditions. It is generally
accepted that biological state and physiology cannot be represented by the expression
of a gene. Therefore, in order to reveal molecular markers that represent the initiation
and progression of cancer, researchers have conducted extensive genomic analyses,
such as microarrays of gene expression, microarray-comparative genomic
hybridization (Array CGH), and tissue chips. However, considerable changes occur
during specific cancerous stages, including post-replication, transcription, translation
or post-translation stages of the genome and modification stages, such as gene
amplification, altered RNA splicing, phosphorylation, methylation, and differences in
protein secretion and stability, which cannot be envisaged by genomic analysis. The
analysis and identification of proteome can identify and quantitatively analyze all
proteins in biological samples.