ARTICLE: DDNews | Individualized Medicine vs. Precision Medicine

COMMENTARY:
Individualized medicine
vs. precision medicine
T
BY DR. JOE OLECHNO, SENIOR RESEARCH FELLOW, LABCYTE INC.
HERE ARE PEOPLE who will die of cancer this week
even though there are drugs that could help them.
At the same time, hundreds of patients will
undergo cancer chemotherapy that, while
debilitating and expensive, will not cure them
of their disease.
While cancer is a formidable foe, there is
a way to improve patient care and prognosis
immediately.
Researchers in Finland, Sweden and Spain have modified ex-vivo testing of cancer cells with significant results. Their approach is far more
“personalized” than traditional precision medicine. Their results are
striking. They provide a missing link between genomics-based mutation
determination and clinical efficacy.
Precision medicine (also referred to as “personalized medicine” or
PM) appears to many patients, doctors and researchers to be a golden
highway from disease identification to cure. The idea of interrogating
the genome of a particular cancer to determine its Achilles heel is intuitively satisfying and understandable. There are, however, significant
problems.1,2,3 First, PM is neither personalized nor precise. PM strives
to identify the appropriate biomarker (usually a DNA mutation but
proteins, peptides and metabolites can stand as biomarkers as well)
to categorize the patient as a member of a specific group of patients.
The patient is treated with a drug that has shown positive results on
previous members of the group. In other words, personalized medicine
is actually population-based medicine.
In contrast, the method described by researchers at the Institute of
Molecular Medicine, Finland, determines empirically the best treatment with what they call “individualized” medicine to differentiate it
from PM. They follow the determination of the appropriate therapy
with detailed genomics-based analyses of the patient and the cancer
to develop an understanding of the mode of action of the therapy. By
integrating the cure with an understanding of the genetic mutation,
they have changed the existing paradigm and created “individualized
system medicine.” The power of the individualized system medicine
approach includes the ability to more quickly look at mechanisms of
action, assess drug combinations, understand drug resistance, position
and de-risk drug candidates and provide more rapid drug repositioning
in a way that has not been previously achievable.4
There are three critical problems with genomics-based PM. Two of
these problems are intrinsic to the biology. Genomics-based science has
identified exciting new methods of treatment and I do not call for its
abandonment, but rather adding to the process the critical step of ex-
vivo testing to mitigate some of the deficiencies inherent with genomics
approach alone.
Problem 1—Mutations in DNA are
not clear signs of the cause of the cancer (or disease)
Typically, genomic analysis is used to determine what mutation
causes the cancer. Sometimes the therapy works and at other times,
the patient goes through debilitating chemotherapy only to find
that there was no impact on the cancer. In fact, the cancer may
have grown and further mutated during the time of the treatment,
gaining both mass and genetic changes so that it is even harder to
treat with supplementary rounds of chemotherapy.
While it may seem obvious that if you sequence the tumor and find
the genetic flaw that causes the cancer, addressing that flaw specifically
should result in remission. In fact, this desired outcome is sometimes
achieved. Yet despite the apparent causal relationship between mutation and cancer, clinicians often do not see a good correlation between
the identification of the genomic mutation and successful treatment.
Researchers at the Wellcome Trust Sanger Institute and their colleagues have observed that healthy skin tissue—tissue that appeared
normal by any measure—was full of somatic DNA mutations. DNA
mutations in the apparently healthy skin were found at the same
level as the mutations in tumor cells.5 Not only did a quarter of
all the healthy skin cells carry a cancer-causing mutation, but the
researchers found that these mutations were under strong positive selection—that is, the number of cells carrying the mutations
tended to increase even though there was no evidence of cancer.
This means that when an oncologist finds a cancer-causing mutation, it may not be the cause of the cancer jeopardizing the health
of the patient. It may just be along for the ride. But giving a drug
targeted to the harmless mutation delays getting the drug that will
actually stop the cancer. All the while, the initial cancer drug may
cause damage to healthy cells.
Similarly, researchers at Johns Hopkins showed that DNA analysis of
tumor cells tended to produce many false positives.6 They suggest that
comparing the mutations in apparently healthy tissue with that of the
tumor will determine the true, cancer-causing genes. Unfortunately,
the data from the Wellcome Trust Sanger Institute mentioned above
suggests that healthy tissue contains many different mutations, and it is
unlikely that there is a single healthy genotype to use for comparison.
Simply put, evidence of the existence of a mutation is not evidence of a
cause for cancer. Treating a patient based on a latent mutation may harm
the patient and delay helpful treatment.
Reprinted with permission from DDNews n May 2016, Volume 12, Issue 5
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Problem 2—Inability to reconcile
genomic data and phenotypic results
Two extremely good labs, the Cancer Genome Project and the Cancer
Cell Line Encyclopedia, analyzed the DNA of hundreds of different
cell-lines. They also tested the cell lines against many different drugs
to see how they responded. The data from both labs was analyzed by
Quackenbush and colleagues7 who found that their genomic results
were spot-on. Both labs obtained very similar results when they analyzed the DNA from the same cell lines. However, when these labs
tested identical drugs against these cell lines, they obtained dramatically different results. If one lab found that a particular drug was effective against a target in a cell line, the same analysis in the other lab,
more frequently than not, gave contradictory results.
This means that even if finding DNA mutations meant that you
could choose a particular target or enzyme to block in the treatment
of a cancer, you might not be able to choose the right drug. Each lab
could end up choosing a different treatment due to the difficulty in
determining the correlation between drug and response.
It is important that the two labs obtained almost identical results
in their DNA analyses. This shows that they both use consistent scientific methods that others can replicate. One assumes that if they
can match results analyzing DNA, they should also be able to get
equivalent results in drug response experiments. The fact that they
do not suggests that the problem is not something as simple as competence in scientific technique.
A recent publication in Nature Biotechnology8 highlighting that certain individuals are resilient to Mendelian childhood diseases despite
clear genomic evidence of the presence of the specific mutation is
just another example of DNA sequence alone not providing sufficient
proof of disease. This paper amplifies the impact of problems 1 and 2.
By adding critical information, the ex-vivo individualized systems medicine approach eliminates this problem and reproducibly generates the best
therapy for a patient’s particular cells.
Problem 3—Personalized medicine falls
back to guessing if no drug has previously been
found effective against a cancer associated
with a new genomic mutation
Assuming that you correctly determine the mutation causing the cancer among all the other somatic mutations in the sample, you may find
a mutation for which no chemotherapy has been determined. The
pharmacogenomic process can point you only to treatments that have
already been verified. That means that the drug of choice has been
tested in double-blind experiments and has gone through the required
government licensing procedures for that particular cancer. While the
number of therapies continues to grow, the personalized medicine
pathway would
miss (and would
never even look
to try) that some
cancers can be
cured by drugs
not associated
with a particular cancer. In
e s s e n c e, y o u
would need to
test all drugs
against all cancers, a herculean
feat with most
existing protocols. Personalized
medicine would
not have pointed
a doctor to using
thalidomide 9 or
methotrexate 10
against particular cancers, but
individualized
systems medicine can help uncover new uses for existing drugs in an
orderly way. For example, researchers at the Institute for Molecular
Medicine, Finland (FIMM) have shown that the antiangiogenic renal
cancer drug axitinib11 can be repurposed against T315I-mutant BCR–
ABL1-driven leukemia.
Guessing is still just guessing even if there is genomic data. Having phenotypic results that show which drug or drug combinations kill a patient’s
particular cancer is a significant advance.
A Reasonable, Cost-Effective
Complement to Genomics-Driven Testing
Finding a mutation does not necessarily mean finding the cause of
the cancer. And even if the cause of the cancer is identified correctly,
it is not easy to determine which drug will be effective against that
mutation. What is the alternative?
Researchers at FIMM12,13,14,15,16,17 and elsewhere have turned the
question on its head. Instead of trying to identify a mutation in the
DNA and then trying to find a drug that addresses that mutation,
they isolate cancerous cells from the patient. They then test those
cancerous cells against hundreds of possible drugs to see which drugs
are effective against the cancer. In some cases, they use cocktails of
Reprinted with permission from DDNews n May 2016, Volume 12, Issue 5
Old River Publications, LLC n 19035 Old Detroit Road n Rocky River, OH 44116
www.DDN-News.com n Tel: (440) 331-6600 n Fax: (440) 331-7563
drugs to see if the combinations are more efficacious than single
drugs. They frequently test the drugs at many different concentrations
to better understand the potential dosing aspects.
Just because a drug works against isolated cancer cells ex vivo does
not necessarily mean that it will work inside the body. However, the
inverse of that statement, that if it does not work on cells ex vivo it is
unlikely to work in the patient, is most likely true. This is what the
researchers found. By screening the drugs against the patient’s cancer
cells, they found other cancer drugs that were able to drive the cancer
to remission while saving patients from ineffective treatments. Most
significantly, this was true even in patients who had already failed multiple
rounds of chemotherapy.
Chemotherapy has both monetary and health costs whether or not
it leads to a cure. First-line treatments can fail and force the patient to
alternatives. Every new round of treatment eats away at the window
of opportunity to cure the disease.
The researchers at FIMM have developed an empirical, individualized test that can screen hundreds to thousands of drugs against
a patient’s particular cancer quickly and at low cost. The test can
eliminate chemotherapy that is highly likely to fail and it informs the
clinician of the best options. With DNA analyses, as they describe in
their papers, individualized systems medicine can help expand the
understanding of cancers and guide future drug discovery.
While labs in Finland, Sweden18 ,19,20 and Spain21 are already investigating the technique, more labs should be moving this forward. As
a member of a family that has been struck multiple times by cancer, I
hate to think that I would need to book a flight to Finland in order to
get the best options for chemotherapy.
Testing drugs for efficacy before starting chemotherapy will reduce
costly but futile rounds of therapy. It would also identify active drugs
and let the patient and doctor make secondary decisions on price.
This could increase competition and drive down prices, especially on
those drugs that show little if any efficacy.
While PM may give lip service to non-genomic assays, by far
the greatest effort and the largest number of dollars are being
directed towards using genomic markers to determine healthcare.
In part, this is because the success of the Human Genome Project.
Excellent scientists from the NIH, NCI, academia and private
industry combined to provide the first full human DNA sequence.
The question then was, “What’s next?” With hundreds of sequencers
purchased and thousands of molecular biologists now trained,
how could all these resources be put to good (and desired by the
public) use? Healthcare was the obvious choice. But to the hammer,
everything is a nail.
I believe that there is a role for genomic analyses in healthcare,
I just do not think that it will be the panacea that many suggest. I
am especially concerned that excellent tools, like those developed
by FIMM, are not being used by researchers locked into solely the
genomic pathway.
I urge clinicians and researchers to explore the work begun in
Finland. The procedures are straightforward and the results can
be rapidly available. The technique offers the promise of increased
remissions, reduced failure of chemotherapy and decreased healthcare
expense. A multilevel winning strategy uniting ex-vivo testing with
genomics-based analyses appears within our grasps, and we need to
take hold. n
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Reprinted with permission from DDNews n May 2016, Volume 12, Issue 5
Old River Publications, LLC n 19035 Old Detroit Road n Rocky River, OH 44116
www.DDN-News.com n Tel: (440) 331-6600 n Fax: (440) 331-7563