There is an almost daily set of markers for a variety of
cancers which are announced often with great fanfare. However the markers may
or may not have any true meaning. We have discussed this in a prior posting and
there we discussed the work by Venet et al as summarized by DeTours:
The signatures’ prognostic potential
can then be tested instantly in genome-wide compendia of expression profiles
for hundreds of human tumors, all available for free in the public domain.
Besides stem cells markers, signatures linked to all sorts of biological
mechanisms or states have been shown to be associated with human cancer
outcome. Indeed, several new signatures are published every month in prominent
journals.
But such correlations are not all that
they seem. The accumulation of signatures with all sorts of biological meaning,
but nearly identical prognostic values, already looked suspicious to us and
others back in 2007. It seemed that every newly discovered signature was
prognostic. We collected from the literature some signatures with as little
connection to cancer as possible. We found, for example, a signature of the
blood cells of Japanese patients who were told jokes after lunch, and a
signature derived from the microarray analysis of the brains from mice that
suffered social defeat. Both of these signatures were associated with breast
cancer outcome by any statistical standards.
Namely DeTours and
his co-authors seem to say that it is all too easy to get markers for almost
anything. In the context of Dougherty and his work, one must have an underlying
verifiable model for the process and then from that verifiable model one can attempt
to ascertain what elements may have failed. Then and only then can one obtain
truly prognostic determinants which in turn may lead to means and methods to
reduce the disease state.
For example in just the recent past we have papers which
have identified the following for melanoma:
1.
MAP2K1 and MAP2K2 mutations (Nature Genetics,
2011)
2.
MAP3K5 and MAP3K9 mutations (Nature Genetics
2011)
3.
ACP5 (Cancer Cell 2011)
4. The
following complex (Cell Oct 2011):
a. A Sleeping Beauty screen followed by
MuTaME analysis discovered putative PTEN ceRNAs
b. The PTEN ceRNA ZEB2 regulates PTEN in a
miRNA-dependent manner
c. ZEB2 loss activates PI3K/AKT signaling
and promotes cell transformation
d.
Attenuated
ZEB2 expression is found in melanoma and other human cancers
5.
SNPs as reported at (Nature Genetics, 2011):
a.
an SNP in ATM
b.
an SNP in MX2 and
c.
an SNP adjacent to CASP8 .
d.
A fourth locus near CCND1 remains of potential interest,
And the list goes on. As DeTours states, it may be all too
easy to find aberrant genes, and even more so SNPs, independent of specific
pathway models. And as I have argued, just within a pathway one may have a concern
because it is also the intercellular signalling that is a concern as well. Even
more so is the understanding of the process. Specifically:
1.
A melanocyte may be normal until something
happens. What is it that happens, does a SNP occur, why, when, and then what
happens after that?
2.
If a SNP occurs is that during the development
of a DNA reading for protein generation or during cell replication. The opening
of DNA for transcription may be the event which places the melanocyte at risk.
If so then what is the risk process. Could it be radiation as suspected, or is
it the next step in a Vogelstein like progression. Namely there may have
already been SNP damages and this one could be the final straw. Is it a micro
RNA problem? The dynamics of this are essential.
3.
Knowing pathways, is it possible to work
backward and determine what the aberrant change or changes were? Pathway
changes are reflected by their products.
4.
What of the stem cell theory, must we look for
the melanoma stem cell alone, and if so how can we identify it. The stem cell
communicates, and that is a powerful mechanism to spread the cancer. How does
it communicate and how is that related to the pathway.
Thus we look to understanding cancers in the context of
pathways and then in the context of their intercellular pathways as well.
Understanding the pathway dynamics of melanoma has been
progressing fairly well over the past few years. In a recent paper by Vidwans
et al, the authors develop an interesting classification of melanoma based upon
the specific pathway elements which may go awry. This is one of the first such
classifications which goes beyond the classic morphological approach and even
those using cell surface markers, This methods now looks at the cell dynamics
and examines the malignancy based upon what specific pathway elements have
failed. We show the pathway model used in the Vidwans paper above.
The now somewhat well understood B-RAF mutation, namely the
V600E and discussed in the paper by Chapman et al:
Approximately 40 to
60% of cutaneous melanomas carry mutations in BRAF
that lead to constitutive
activation of downstream signaling through the MAPK pathway.10,11
Approximately 90% of these mutations result in the substitution of glutamic
acid for valine at codon 600 (BRAF V600E), although other activating mutations
are known (e.g., BRAF V600K and BRAF V600R).
As Chapman et al state they have an inhibitor of the mutated
B-RAF as follows:
Vemurafenib (PLX4032)
is a potent inhibitor of mutated BRAF. It has marked antitumor effects against
melanoma cell lines with the BRAF V600E mutation but not against cells with
wild-type BRAF. A phase 1
trial established the maximum tolerated dose to be 960 mg twice daily and
showed frequent tumor responses. A phase 2 trial involving patients who had
received previous treatment for melanoma with the BRAF V600E mutation showed a
confirmed response rate of 53%, with a median duration of response of 6.7
months.16
We conducted a randomized phase 3 trial to determine whether vemurafenib
would prolong the rate of overall or progression-free survival, as compared
with dacarbazine.
As Bankhead states:
Patients with
metastatic melanoma had an "astounding" 63% reduction in the risk of
death when treated with an investigational agent that targets a mutation found
in about half of the tumors, data from a large international trial showed.
Treatment with the
BRAF inhibitor vemurafenib improved progression-free survival (PFS) by 74%.
Analysis of six-month overall survival (OS) showed a 20% absolute difference
between patients treated with vemurafenib versus dacarbazine.
Though follow-up is
brief, the results already make a case for vemurafenib as the comparator for
future trials of new agents for advanced melanoma, Paul. B. Chapman, MD, of
Memorial Sloan-Kettering Cancer Center in New York City, said at the American
Society of Clinical Oncology meeting.
"The median
follow-up was only three months, yet the hazard ratio for death was 0.37 in
favor of vemurafenib," Chapman said in an interview with MedPage
Today. "That's an astounding difference that is almost never
seen in oncology trials."
From 40% to 60% of
cutaneous melanomas have BRAF mutations that activate downstream signaling
through the MAP kinase pathway. About 90% of the mutations involve a specific
substitution at codon 600 (BRAF V600E), Chapman and co-authors wrote…
The above demonstrates how understanding pathways we can
target pathway drugs to mitigate the progression of the disease. However
progression free survival is of limited duration. The cancer cell finds
alternative paths to mutate. Thus the question is does one target one path
after another as they progress or try a multi mix cocktail in hopes of
preventing the development of any new paths. Is it possible, for example, to
stop the transcription of melanocytes all together, and thus stop any and all
expression so as to silence say all pathways.
In another piece Bankhead states the cost issues:
Vemurafenib has an
estimated cost of $56,000 for a six-month course of therapy, and ipilimumab
costs about $120,000 for four weeks of treatment. Both drugs also have
potentially serious adverse effects. In approving ipilimumab, the FDA cautioned
that the drug has been associated with severe adverse effects that have included
"severe to fatal autoimmune reactions."
The problem is that although the results are highly
favorable for the short term, approximately six months, the long term is still
questionable. It may be like imatinib and CML, namely there is a change in the
cancer stem cells allowing a work-around of the blockage. Thus the costs would
be considerable. Also the use of multiple drugs may as in leukemias result in
“cures”. However the above costs, which may be at $20,000 per month of life
extended, are excessive. The quality of life extended may not be the best and
the drug while providing a “benefit” has not truly changed the end state,
namely death of the patient. It has merely delayed the inevitable.
The issue of drugs, pathways, and targeting a sustainable
remission is more than likely the target. As one has seen in many childhood
cancers the goal of a sustainable remission is achieveable with cocktails of
drugs and perhaps such may be the case here as well. Vidwans et al refer to
their web site ( see http://mmdm.cancercommons.org/ml/index.php/A_Melanoma_Molecular_Disease_Model
) which provides a superb interactive asset for linking pathway elements,
disease stage, trials and specific modalities for possible mitigation and control.
The Table below is a modified version of the Vidwans table taken from their
paper.
Now in contrast we have seen, as previously indicated, many
papers where we have been presented with prognostic markers for melanoma and
its development. Yet none seem to develop and verify them in the context of an
underlying system model. The above mentioned work of Vidwans et al seems to be
one of the first to commence that effort.
References:
1.
Bankhead, C, Melanoma Drug Still on a Roll, http://www.medpagetoday.com/Oncology/SkinCancer/30412
2.
Bankhead, C, Melanoma Survival Benefit Called
'Astounding' MedPage; http://www.medpagetoday.com/Oncology/SkinCancer/30413
3.
Chapman et al, Improved Survival with
Vemurafenib in Melanoma with BRAF V600E Mutation, NEJM, N Engl J Med
2011;364:2507-16.. http://www.nejm.org/doi/pdf/10.1056/NEJMoa1103782
4.
Murphy, M., Diagnostic and Prognostic Biomarkers
and Theraputic Targets in Melanoma, Humana (New York) 2012.
5.
Vidwans, S. et al, A Melanoma Molecular Disease
Model, PLOS ONE March 2011 V 6 No 3. http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0018257
.
6.
Venet et al, Most Random Gene Expression
Signatures Are Significantly Associated with Breast Cancer Outcome, PLOS, http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002240
7.
Detours, V., Opinion: Confounded Cancer Markers,
http://the-scientist.com/2011/12/07/opinion-confounded-cancer-markers/
8.
Dougherty, E., W. Bittner, Epistemology of the
Cell: A Systems Perspective on Biological Knowledge, Wiley, 2011.
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