Introduction:
All living organisms' genetic information is in their deoxyribonucleic acid (DNA) or ribonucleic acid (RNA), which defines an organism's genotype and possible phenotype. The study of this genetic analysis will help to determine the multiple causes of disease in humans. Nowadays, completing the human genome sequences allows researchers to broaden their study and look for genetic variables that impact complicated diseases comprising several genes.
What Is Microarray Technology?
A microarray is a collection of DNA fragments from a known sequence that collectively reflect the whole set of genes found in an organism and are organized in a grid pattern used for genetic testing. A microarray is an excellent tool for studying the biology of DNA in living structures.
Previously, scientists had to put in a lot of effort to gather a small quantity of data that might be utilized to create a theory by adding one observation at a time. However, with the advancement of microarray technology, individual tests may now provide thousands of observations on the expression of genes, allowing significant genes to emerge. It examines an organism's whole genetic process on a single chip.
What Are the Principles of Microarray?
A DNA microarray (DNA chip) can be regarded as a gene-detection test of high-density arrays of DNA fragments adhered to the surface in a predetermined pattern. The basic concept of microarray research is that mRNA (messenger RNA) or total RNA from the required cells or tissues is hybridized in parallel with various DNA sequences. It is immobilized on a solid substrate in a pre-ordered array to form a tagged sample. With the availability of genomic information, a global study of thousands of gene expressions may be conducted in a single test.
Each microarray experiment generally includes the following procedures:
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Array manufacturing.
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Target preparation.
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Hybridization.
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Washing.
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Image acquisition.
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Data processing.
What Are the Types of Arrays?
There are three types of DNA microarrays -
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Gene chips.
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Double-stranded DNA microarrays.
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Oligonucleotide DNA microarrays.
How Are Cancer Risks Identified Through Microarray Technology?
1. Gene Expression Profiling:
Gene expression levels in tumor cells can be compared to those in healthy cells using microarray analysis. By studying gene expression patterns, researchers can identify genes that are upregulated (expressed at higher levels) or downregulated (expressed at lower levels) in cancer cells. Variations in gene expression can shed light on the molecular processes that underlie cancer growth.
2. SNP (Single Nucleotide Polymorphism) Analysis:
Microarrays can be designed to detect single nucleotide polymorphisms (SNPs) in the genome. Variations in gene expression can shed light on the molecular processes that underlie cancer growth. Certain SNPs may be associated with an increased or decreased risk of developing cancer. Researchers can identify genetic variations that may contribute to cancer susceptibility by analyzing SNP patterns in individuals.
3. Copy Number Variation (CNV) Analysis:
Microarrays can also detect copy number variations, which involve changes in the number of copies of a particular segment of DNA. Amplifications or deletions of specific genomic regions may be associated with cancer development. Microarrays can help identify these copy number variations by comparing the DNA content of cancer cells to normal cells.
4. Methylation Profiling:
One epigenetic alteration that may have an impact on gene expression is DNA methylation. Microarrays can be designed to assess the methylation status of specific genes. Aberrant DNA methylation patterns, such as tumor suppressor genes' hypermethylation or oncogenes' hypomethylation, can indicate cancer risk.
5. Mutation Detection:
Microarrays can be used to detect specific mutations in cancer-related genes. By comparing cancer cells' DNA sequences to those of normal cells, researchers can identify mutations that may contribute to cancer development.
6. Integration of Data:
Researchers often integrate data from multiple microarray experiments to obtain a comprehensive view of the genetic factors involved in cancer. This may involve combining gene expression data, SNP analysis, copy number variation data, and methylation profiles to identify complex interactions and networks contributing to cancer risk.
What Are the Applications of Microarray in Head and Neck Cancer?
DNA microarrays are currently being utilized to improve the diagnosis and treatment of head and neck squamous cell carcinoma (HNSCCa). They are employed in the search for molecular indicators of head and neck cancer. Essentially, their usage will enable the identification of the passage from abnormal cells to invasive cancer and distant metastasis. A study discovered the regulation of genes encoded by cell cycle regulators, inflammatory reaction mediators, matrix metalloproteinases (MMP), and mevalonate pathway enzymes.
Various researchers measured overall variations in the expression of genes in HNSCCa using 9216 clones of DNA microarrays. They discovered 375 variable expression patterns and split 17 patients with head and neck cancers into two therapeutically distinct groups. The findings of their study indicated that genomic profiling might be utilized to predict outcomes and identify pathways that need further investigation for possible linkages to prognosis in HNSCCa.
cDNA subtractive techniques and microarrays also identified nine recognized genes abundantly expressed in HNSCCa tissue specimens compared to healthy tissue specimens. In addition, four previously undiscovered genes were revealed to be widely expressed in a subset of malignancies.
An array of 588 known cancer genes and nine housekeeping genes can be used to demonstrate a consistent drop in cytokeratins (differentiation markers) and an increase in angiogenic and growth factors (signal-transducing molecules) and proteases. The Wnt and Notch growth and differentiation regulatory pathways may play a role in squamous cell carcinoma.
Comparative genomic hybridization (CGH), spectral karyotyping (SKY), and microarrays can discover sites of chromosomal instability and architectural alteration in HNSCCa. Scientists can establish recurring chromosomal abnormalities and connect them to microarray analyses.
Genomic patterns can identify cancers in nonmalignant tissues using hierarchical cluster analysis. Gene expression of the collagen type XI alpha-1 gene and a new gene found in nine tumors can sometimes be undetectable in surrounding nonmalignant tissues.
The predictive variables in HNSCCa may be efficiently tested by employing cell-line microarrays. Stem cell marker Oct4 has higher radioresistance in HNSCCa. The advantages of cell-line microarrays include immunohistochemistry (IHC) staining analyses to focus on cancer cells while removing the bulk of unspecific sources of undesired IHC.
However, a key drawback is that patient-related aspects, such as immunologic response, which can considerably influence radiotherapeutic success, cannot be considered.
What Are the Advantages and Disadvantages of Microarray?
Advantages of microarray:
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Protects valuable records.
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Standardization of test findings.
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Useful screening procedure.
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Improves significance level.
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Decrease in consumption level.
Disadvantages of Microarray:
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Potentially representative tissues.
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Inadequate tissue volume.
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Not suited for diagnostic procedures.
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Observational error.
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Time consuming.
How to Use a Microarray to Select Biomarkers?
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Another technique to investigate genome-wide expression data for cancer diagnosis is to convert it into surrogate molecular markers.
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Biomarkers can be measured using low-cost, commonly used clinical procedures such as RT-PCR, ELISA, and immunohistochemistry.
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They can be identified in serum or other bodily fluids, allowing the development of noninvasive diagnostic tests, especially essential in malignancies with restricted access to diagnostic biopsies (e.g., lung, ovary, pancreas).
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Biomarkers are often picked from a list of genes that constitute a predictor. However, when combined, genes that predict the class to which a fresh sample belongs are not always useful biomarkers.
Are Microarrays the Prospect for the Future?
The array source must be thoroughly analyzed before using microarrays to maximize the possibility of favorable study results. Microarrays preserve valuable tissue, reduce storage space, and investigate any uncovered novel molecular markers. It may be possible to plan a suitable treatment method with a patient database and pertinent indicator marker information employing arrays in the future. They may transform the way research is performed in the future.
Microarrays reduce time-consuming laboratory procedures to a single test. It can decrease from over 2000 slides to less than five slides. They have the potential to become a routine investigative tool as the costs of new medicines rise and the focus shifts to rational drug development and production.
Conclusion:
Microarrays were discovered in 1990 and have contributed significantly to transforming the future of medical and dental practice. Despite this, we are just beginning to perceive what can be achieved with this technology. Based on randomized clinical trials, the future will allow researchers to make advancements in diagnosis, prevention, and other ways to provide better healthcare for patients. Microarray technology, one of the most promising technologies in head and neck cancer research, has the potential to expedite molecular investigations.
