I. Genomic analysis. This is the structure of the human genome. What genes are present? What genes are absent? What genes are present, but mutated?

II. Gene expression analysis. This is measuring RNA content. Genes are DNA. When genes are “expressed,” they make RNA. RNA is the “messenger” between the gene (DNA) and the product which is coded by the DNA (the protein), which may be a component of cell structure, but more commonly/importantly is an enzyme (a protein molecule which
catayzes, directs, regulates cellular functions, such as cell replication,
cell death, cell metabolism, cell function).

How do you measure cellular RNA (gene expression)?

Microarrays are one method. Can measure the RNA expressed by 50,000 genes at the same time. This is the advantage. The disadvantages are expense and often poor reproducibility and often not very good sensitivity to measure the sorts of changes which make critical differences.

Real time, reverse transcription polymerase chain reaction (“real time
PCR”). Can only measure a few score to a few hundred genes at a time, but it is more sensitive and reproducible than are microarrays. So microarrays are used for initial screening, to narrow the field down to a more manageable number of genes, and then real time PCR is used to hone in on the problem under study.

Another, simpler, cheaper, more practical method is something called
“Fluorescence in situ hybridization,” or “FISH.” This is very good when you only have a single gene to study (e.g. Her2/neu in breast cancer).

III. Protein expression analysis (proteonomics). Here you go beyond genes
(DNA) and beyond gene expression (RNA) to measure the actual proteins
themselves. There a myriad technologies for doing this.

IV. Protein function analysis (measures not only are proteins present, but
are they active or inactive).

V. Cell function analysis. e.g. cell culture testing

VI. Disease analysis in the patient (e.g. doing something to treat the patient, and then making a measurement on the patient, e.g. CT/PET scanning.

In terms of relevance and utility, there is an inverse hierachy between
relevance and ease of measurement.

I. is only important insofar as it influences II which is only important
insofar as it influences III, IV, V, and VI in that order. Yet I is the easiest
to measure, followed by II, III, IV, V, and VI in that order.

So the most relevant things are the hardest to do (or at least the hardest
to do RIGHT).