In a recent paper on the development of Prostate Cancer
(PCa) the authors allege the role to APOBEC is critical. They note[1]:
The researchers collected patient data from close to 300
men who have had their entire cancer genome sequenced to characterise all
mutations present in the tumour. Based on the data set, the researchers have
developed the computer model which can be used to predict how prostate cancer
will develop for a given patient.
'If we have a patient with a particular set of mutations,
we can use the model to predict the most likely next mutation that the patient
will experience at some point - and how it will affect the patient's clinical
situation. As an illustration, we can predict with some probability that if you
have mutation A, you are likely to get mutation B before you get C. We can also
predict if the next mutation is likely to change the clinical outcome of the
disease'…
Mechanism Contributing to the First Mutations in Prostate
Cancer Have Been Found. The approximately 300 patients from the study all had
their entire genome sequenced. With genome sequencing, it becomes possible to
tailor the treatment of the individual - also referred to as personalized
medicine. The patients whose data the researchers have used have primarily been
so-called early onset patients. This group is defined as men who are diagnosed
with prostate cancer before reaching the age of 55 years.
'Prostate cancer develops over many years. We have
therefore been particularly interested in the group of patients where the
cancer is detected at young age as this allows us to analyses the tumour at an
early stage. This is an important element because in this way we get a cleaner
picture of the first mutations and alterations that occur in the tumour, to
find out what is the initiating factor', …
So far, it has not been known precisely what initiates
prostate cancer. However due to the focus on the earliest detected tumours, the
researchers uncovered a mutational mechanism involving an enzyme called APOBEC.
This enzyme may help trigger the disease - i.e. trigger some of the very first
mutations in prostate cancer.
'We hypothesize that this enzyme mutates the prostate
cells at a low but constant rate. Each time the cell divides, APOBEC is likely
to cause mutations. If you have early-onset prostate cancer, you may have a
couple of mutations caused by APOBEC. Twenty years later, you may have 10-20
mutations',
Now we know a great deal about PCa. There are a multiplicity
of genetic aberrations. A Nature Reviews paper has also recently noted[2]:
Genome-wide association studies (GWAS) have been
successful in deciphering the genetic component of predisposition to many human
complex diseases including prostate cancer. Germline variants identified by
GWAS progressively unraveled the substantial knowledge gap concerning prostate
cancer heritability. With the beginning of the post-GWAS era, more and more
studies reveal that, in addition to their value as risk markers, germline
variants can exert active roles in prostate oncogenesis. Consequently, current
research efforts focus on exploring the biological mechanisms underlying
specific susceptibility loci known as causal variants by applying novel and
precise analytical methods to available GWAS data.
Results obtained from these
post-GWAS analyses have highlighted the potential of exploiting prostate cancer
risk-associated germline variants to identify new gene networks and signalling
pathways involved in prostate tumorigenesis. In this Review, we describe the
molecular basis of several important prostate cancer-causal variants with an
emphasis on using post-GWAS analysis to gain insight into cancer etiology. In
addition to discussing the current status of post-GWAS studies, we also
summarize the main molecular mechanisms of potential causal variants at
prostate cancer risk loci and explore the major challenges in moving from
association to functional studies and their implication in clinical
translation.
Namely the first paper alleges the discovery of a putative
unique and predictable path and the second a plethora of GWAS results.
It is worth examining both paths. However PCa can be strange
and multifaceted. Most variants are slow growing as noted. However there are a
small percentage which have explosive growth. Just what the differentiator is
seems still unknown.
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