Page 54 - Bio Engineering Approaches to Cancer Diagnosis and Treatment

52 CHAPTER 3 Immune assay assisted cancer diagnostic

Table 3.4 Advantages and disadvantages of proteomic technology.
Proteomic
technology Advantages Disadvantages
ELISA Very robust, it has the highest Requires well-characterized
sensitivity, good technology antibody for detection and
for specific and single marker extensive validation. Not
detection. It could be used for amenable to direct discovery
marker detection in body fluid or
tissue
2D-PAGE It has a direct identification It has a low sensitivity and
marker. Reproducible and efficiency. Can’t be used as a
more quantities combined with direct means for early biomarker
fluorescent dyes detection
MudPIT Has high sensitivity, can be used It needs identification for pattern
for detection and identification of diagnosis
potential biomarkers, have a vast
coverage in biomarker detection
Proteomic pattern It doesn’t need any protein IDs It has medium sensitivity and
diagnosis weight limit for biomarkers.
It can’t be used for direct
identification markers
Protein It has high sensitivity with high It's limited by antibody sensitivity,
microarrays efficiency. Format flexible and it required enough knowledge to
could be used in any situation. It be used
has the ability to detect PTMs

means that it can detect markers with high sensitivity from body fluids such as serum,
plasma, and urine. Proteomic technique is not sufficient for high accuracy diagnosis.
In a recent study, some gene alternation like somatic mutation is characterized in
patient with breast cancer, however, it is poorly understood with proteomic tech-
nique. Mertines et al. have shown that usage of MS analysis with proteomic array
techniques would increase the region of discovery in cancer. They have selected
125 breast cancer samples and found 77 high-quality data. They also have identified
G-proteins what wasn’t easily detected by miRNA techniques [26]. This highlights
that this combined approach can be a worthy method for accurate identification.
Recently studies have shown that functional proteome positively complements
genomic and transcriptomic data, and this approach has the ability to detect new
biomarkers. In a pan-cancer study, researchers have found a relationship between
HER2 variation, mRNA expression, and protein expression levels in different stages
of cancer. The detail molecular landscape which has been obtained by this approach
could not be concluded by just analyzing either DNA or RNA alone. This case report
has supported the importance of combination of both techniques in biomarker detec-
tion [22–26].
Among proteomic technology, proteomic array is known as the best one, because
of all positive features. The proteomic array has divided into three techniques: (1)