Biology Reference
In-Depth Information
third column of Table
18.1
is the result of clustering the ribonic matrices measured
from human breast tissues and tumors (Perou et al. 2000). The fourth and fifth
figures in the third column of the same table are the 3-D and 2-D visualizations of
the ViDaExpert-analyzed results of the t-ribons measured from budding yeast
One of the major assumptions of this section is that, to apply
ribonoscopy
to
personalized medicine, it is necessary to utilize the
molecular theory of the living
cell
such as the one developed in this topic, especially the concept of
dissipative
structures
in general and
intracellular (ic) dissipative structures
(IDSs or
ic-
dissipatons
) in particular (Sect.
3.1.2
). Ribonoscopy is one of the few experimental
methods now available that allows IDSs or ic-dissipatons to be measured genome-
wide. Personalized medicine differs from traditional medicine in that it tailors
health care (through the triad of
diagnosis
,
prognosis
, and
therapy
) to best fit
individual patients taking into account their unique genetic (i.e., nucleotide
sequence-dependent) and epigenetic (i.e., non-nucleotide sequence-dependent)
characteristics. The roles that
ribonoscopy
and the
molecular theory of the living
cell
(
MTLC
) developed in this topic play in
personalized medicine
are
schematically represented in Fig.
18.2
. Since the cell is the building block of the
human body, it is logical to anticipate that cell biology will play a fundamental role
in personalized medicine (see the top node and the bottom three nodes in Fig.
18.2
).
Ribonoscopy consists of two parts - (1) the microarray data acquisition (Step 1)
and visualization of high-dimensional microarray data (Step 2) in the form of what
computer softwares. It is here assumed that, in order to analyze ribonic spectra
correctly and identify the ribonic spectral characteristics reflective of a diseased
cell, it is necessary to apply a comprehensive
MTLC
(Step 3). In other words, it is
thought to be
impossible to identify a biomarker from ribonic spectra without
applying a comprehensive molecular model of the living cell, just as it is impossible
to interpret molecular spectra without quantum mechanics, the theory of the atom.
Once a correct biomarker (or a disease-related cell-state, or
biomarker ribonic
spectrum
) is identified, it can be utilized for developing
companion diagnostics
(i.e., the diagnostic tools that identify the patients most likely to benefit from a drug)
(Step 4),
drug target discovery
(Step 5), or
personalized drug therapy
(or pharma-
cotherapy) (Step 6).
There is an interesting analogy to be drawn between
the nuclear power industry
and
drug industry
on several levels as indicated in Table
18.2
.
The final product of a power plant is
electricity
; the final product of a drug
manufacturing plant is safe and efficient
drugs
. Both kinds of plant activities
inevitably produce wastes that contribute to environmental pollution - the
external
environmental pollution
by the nuclear power industry (e.g., the Cherbonyl, Three
Mile Island, and Fukushima disasters) and the
internal environmental pollution
by
drug industry (e.g., the Vioxx fiasco). Nuclear reactor engineering that emerged in
the 1940s as a spinoff from the atomic bomb production in the USA and the then-
USSR is based on the theory of the atom, that is, quantum mechanics that was
