Tag Archives: mutations

November 28, 2019 · 10:00 am

Thanksgiving for an oncologist


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First, I want to thank those readers who generously helped me reach my goal of fundraising for the annual Movember effort to increase awareness and support research into prostate cancer and men’s health. If you are so inclined and want to make a last minute contribution, you may do so here: https://mobro.co/michaelglode?mc=1 My itchy, scraggly moustache is destined to come off tomorrow!

Second, it has been an incredible journey since my internship to watch the evolution of our understanding of cancer. In 1972, when my mother called to tell me (a young medical intern) she “had a little lump in her breast” – it turned out to be not-so-little, and she fought the disease for another 4 years before succumbing – we had little we could do other than surgery and in some cases radiation. Even adjuvant chemotherapy (the CMF treatment) had not been published yet. During the next decade, remarkable strides were made in finding new drugs, most notably cisplatin, that allowed cures of previously lethal diseases – especially testis cancer.

Then, while on sabbatical in Helsinki in 1986, I found an article to present at our journal club that I thought would revolutionize medicine. The PCR reaction opened the door to rapid DNA sequencing. When I returned to my lab in Denver, my PhD colleague, Ian Maxwell had already started to use the technique with his own jury-rigged thermal cycler, but it would be 3 or 4 more years until a medical student in his/her 3rd year clinical rotation would be able to tell me what PCR stood for. Recognizing there would be a generation of physicians who “missed out” on what would be the revolution, I was able to help start a catch-up course in Aspen, Molecular Biology in Clinical Oncology, that is still ongoing. As a “fly on the wall” I was able to listen to the world leaders in molecular oncology (including this year’s Nobel Prize winner, Bill Kaelin) describe their research that unlocked the mysteries of how cancer works. Fly-fishing with some of them on the Frying Pan was a bonus to be cherished!

As the cancer story unfolded, I was able to participate in many clinical trials, bringing new treatments that emerged to my patients. Thanks to the brilliant writing of Siddhartha Mukherjee, author of “The Emperor of all Maladies“, it became possible for my patients to begin to understand the nagging question, “how did this happen to me?” And now, this week, a brilliant article summarizing all we know about the genes and mutations that cause cancer has appeared in the New England Journal. I invite you to read that (it’s free online) if you want to join me in peering over the horizon to the future of cancer medicine. It is both overwhelming and humbling.

The privilege of living through the last half of the 20th century and into the 21st is one of the most amazing journeys one could ask of a human lifetime. As I ponder it, looking out on the snow I will get to ski on next week and enjoying my grandchildren and family, I am truly thankful to have been here. Happy Thanksgiving to all!

 

 

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March 9, 2019 · 10:56 am

Black holes and genetic laws


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I just finished reading Stephen Hawking’s last book, Brief Answers to the Big Questions, which I found more accessible than A Brief History of Time, written more than 30 years ago. Hawking’s abilities to explain the very (for me) abstract concepts of how no information can flow out of black holes and that the amount in there is somehow directly related to the cross sectional area of the hole was satisfying. As a very math challenged individual, I’m also a fan of Heisenberg and the perplexing issue that in the quantum/wave world of particle physics, you just can’t be certain about position and momentum. Yet, there are certain laws, like the speed of light, that are never violated, at least in the universe we live in.

So what does this have to do with genetics and prostate (or other) cancers? Here is a law: A always pairs with T, and C always pairs with G. In our biologic universe, without this law, no life as we know it could exist (prions may be an exception, but that gets too far into the definition of “life”). Yet, just as with the uncertainty of Heisenberg, the base pairing in DNA/RNA is not completely inviolable. Mistakes are made…and this can result in cancer. Cancer is a genetic disease and for anyone who hasn’t read it, I still recommend you avail yourself of the incredibly well written book, The Emperor of All Maladies. In the short time since that book was written, the explosion in our understanding of how genetic errors and cancer are related has been difficult to keep up with. The Cancer Genome Atlas (clever name, eh?) is but one example, and its use by scientists skilled in math (ugh) continues to help classify cancers based on how their mutations drive them rather than just how they look under the microscope or which organ they started in. Here is the math and the results one such analysis has on predicting survival for stomach cancer:

Screen Shot 2019-03-09 at 10.14.33 AM Screen Shot 2019-03-09 at 10.22.35 AM

As you can see, the prognosis and potentially the treatment for one subtype of “stomach cancer” might be very different for one patient than for another. Bringing this technology to prostate cancer, we already know the mutational landscape is vast. For example, this article looked at 1,013 different prostate cancers and found 97 significantly mutated genes, including 70 not previously recognized, and many present in <3% of cases. There is hidden good news in this story, in that the same mutational uncertainties that can give rise to cancer (breaking the law of AT-CG) also allows our immune systems to react to the novel mutated proteins that cancers now display. For an interview from this week’s NEJM on gene editing, click here.

Keeping up with this world of laws, broken laws, and “black holes” will be a remarkable challenge for patients and oncologists alike. My final recommendation for reading about this is a terrific article you can find here by George Sledge, one of the outstanding leaders in our field. He notes that even the most skilled oncologist, paired with the smartest of patients, will be unable to keep up. But remember this, you can’t go faster than the speed of light. That’s the law!

 

 

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August 6, 2018 · 7:26 am

The Hits Just Keep on Coming


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I have a hiking companion who loves math, computers, and to a large extent, eugenics. He posits that we will eventually understand the human genome so well that we will be able to make all humans “smart” or “better” through genetic engineering. I argue back endlessly, with little success, that his definition of “smart” and “better” may not be shared  by everyone (he counters that these definitions will be left to the parents…) and that there will be unintended consequences of diving into our DNA with CRISPR/Cas9 technology.

The wonderful complexity of humankind is, of course, reflected in every single cell in our bodies and in all of our cancer cells as well. The debate over the number of synapses (or permutations) in our brains versus atoms (or stars etc.) in the observable universe is well beyond my comprehension. Unfortunately the “much simpler” question of how many things go wrong in cancer cells is also mind boggling. Hence, the phenomenal work of one of the West Coast Dream Team’s recent publications is not surprising. A reductionist view is shown in this diagram from their paper published last month:

Screen Shot 2018-08-05 at 2.01.08 PM

The scientific team, using funds from PCF, SU2C, and Movember (among others), did a whole genome analysis of metastatic tumor specimens from 101 men with castration resistant (hormone insensitive) prostate cancer. There is an excellent report on this work from the UCSF News Center here. Lest you believe that the results have resulted in an “aha moment” that will lead to “A prostate cancer cure”, you might do as I had to do and Google the word I had not heard of in the above figure, “chromothripsis“. Rather, the research leads to some very important insights that will doubtless contribute towards more effective therapy for 1000’s of patients eventually. By looking at the structural variants in the DNA that occurs outside of expressed genes, a much more complex picture of what drives castration resistant prostate cancer (CRPC) becomes evident. For example the androgen receptor (AR) is over-expressed in the majority of metastases and this study found a region of the “junk DNA” (non-coding for genes) that lies 66.94 million base pairs upstream of the AR that was amplified in 81% of the cases. This was 11% more common than the amplification of AR itself – an indication of how important the DNA controlling a gene like AR is, compared to the gene itself. So much for calling the DNA that doesn’t code for a protein “junk”!

A second example is the insight into patients who have alterations in a gene called CDK12 that may render them more sensitive to one of the “hottest” areas of cancer research, the use of checkpoint inhibitors of the PD-1 pathway I described in my last post.  This abnormality results in the cancer cells having an increased number of “neoantigens” (targets) for the immune system to attack as shown in this illustration from another recent exceptional paper.

Screen Shot 2018-08-05 at 2.27.16 PM

The ongoing research from the many scientific teams focused on prostate cancer is awe-inspiring when you consider the complexities involved in the two figures in this post alone. Even getting a complete picture from a single patient is impossible, given the genetic instability and the variable mutations found in different metastases. Remember, this team looked at the DNA from only one (or a few) of the many metastatic sites found in each patient. Other studies have shown lots of different mutations depending on which site is evaluated as I reviewed here.  In spite of all of this complexity, the ability to at least begin to understand what is going on “underneath the hood” is the way forward, and just as we can recognize Fords vs Chevys vs Toyotas, “brands” that emerge from such studies will lead to treatments that are more appropriate for certain classes of patients. As we have known for a very long time, the most common feature is the “gasoline” of testosterone, and how it fuels the amplified AR has remained an effective target for the newer drugs like abiraterone, enzalutamide, and apalutamide. Perhaps studies such as this one will lead to a way of kinking the hose upstream of the gasoline nozzle, or throwing sand (immunotherapy) into the engine itself. But… to admit that we will never understand it all (or design the “perfect human”) still seems an appropriate expression of humility to me.

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April 28, 2018 · 9:53 am

Improving our focus


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I have had two life changing experiences in focusing. The first was when my wife discovered the Myers-Briggs personality classification system and found I am a “strong P”. This meant I couldn’t help it when I was on my way to take out the garbage, noticed a light had burned out, put the garbage down and went to get a light bulb, but found that there was a spot on the carpet that needed cleaning and finally found the carpet cleaner but an hour later wondered why there was a garbage sack in the hall. Prior to her discovery, she just thought I was an idiot, but she became [somewhat] more tolerant of the foibles when she could “classify” me. The second was when I had my congenital cataracts removed and new lenses inserted in my eyes. It was a whole new world of color. I had been living in a fish tank with scum on the glass and “wow, the world is really pretty!” was my response when I took the patches off the next morning. “Trees have LEAVES!”

Focus in understanding prostate cancer is becoming clearer as well. For several decades we have known that the Gleason scoring system is pretty darn good at predicting the cancer’s behavior, adding a lot to what we knew when there was only the digital rectal exam… “Oh, oh, that feels like a really big tumor” or “Maybe I’m feeling something but I can’t be sure”.  Then came the number of biopsies positive, the percentage of each core, differentiating 3+4 vs 4+3, and now an avalanche of new molecular markers, briefly reviewed here. Combining the old standby risk categories with the newer methodologies has been challenging.

A recent paper in the JCO provides us with one way of integrating the old risk categories with the newer molecular classifications. Using the widely adopted risk categories of the NCCN, the authors added to this, one of the more mature molecular classifiers, the 22 gene Decipher™ scoring system to reclassify (focus) a new model to predict outcomes. As I explained previously, these genetic tests are typically developed looking at the level of gene expression in biopsies or in removed prostates in a group of patients for whom an outcome is known (examples include prostate cancer free survival at 10 years or freedom from metastases at 5 years). The investigators (or companies) then go to a different institution or collection of biopsy material and see if their gene expression model developed from the first group accurately predicts the outcome in the second group. This is called “validation” of the test. Decipher has done all of this. The question is how it might change the risk classification of the “old” system.

This figure illustrates how it plays out when a large number of institutions collaborate to study the information gained and develop a new model.Screen Shot 2018-04-28 at 10.16.05 AM

As an example of how this can be used in the “real life” clinic, we are often faced with a patient who has a “favorable intermediate” prostate cancer. Let’s say this is a 75 year old man with excellent health. Should we advise that he adopt a “watchful waiting” strategy, given his age and the relatively low risk? By adding the genomic test, you can see that 27% of the time, this might be a bad recommendation. Similarly, in the unfavorable intermediate group, 40% of patients are moved into a high risk category. Such a patient might be well advised to “do more” (example: more prolonged ADT with radiation, or use of brachytherapy in addition to external beam radiation if they had chosen radiation therapy as their preferred treatment modality).

These kinds of improved focus will allow investigators to do better studies prospectively as well. In breast cancer it is already a standard of care to do molecular classification of certain stages and types of tumors, allowing women to make far better decisions on whether (for example) to take chemotherapy in addition to surgery/radiation. In prostate cancer, where I have been concerned that we aren’t “racing for the cure“, rather we are “crawling for the cure”, it looks like we may be catching up. Research is the answer – sign up and contribute!

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November 24, 2017 · 10:50 pm

23 & You – Genetic tests for pca


The genetics of prostate cancer are daunting, but there are now a range of tests available that could be used at almost every stage of the disease IF you can deal with the answers you are likely to receive. Generally these tests are the product of science that goes something like this: A complete molecular picture is taken of all the mutations or all the genes expressed in a series of prostate cancer patients diagnosed years ago. For these patients “all you need to do” is go back to the paraffin blocks that were saved for each patient, extract the DNA/RNA and quantify gene expression and any mutations that can be detected. A decade ago, the technology for doing this was daunting, but now it is relatively easy. Once you have the gene expression profile, you can ask a computer to look for gene expressions that correlate with a certain outcome. For example, you take 500 patients from one center for whom the outcome is known…50 patients are dead, 32 from prostate cancer…70 patients developed metastases by 5 years…these 315 patients are alive and well with no evidence of recurrence…etc. Let’s say there are 50 genes that show changes in expression or mutation. Do we need all 50 to forecast what happened to the patients in that group? No. A computer algorithm can keep testing combinations and permutations of genes and reduce the 50 to a smaller number. We can either let the computer pick the final genes, or we could start with genes we think are related to tumor progression and then do the reduction. In the end, we have a small number of genes with characteristics that accurately separate the patients into “good” and “bad” groups and everything in between. We now take our gene panel, reduced to something like a computer chip and apply the test to 500 patients at another institution blinded from what actually happened to those patients. If our algorithm works, we should be able to accurately predict what happened to those patients in the next 5 or 10 years. If it works, our testing system has been validated, and we can begin offering the test to newly diagnosed patients at some stage of illness. For example, a Gleason 3+4=7 patient might fall into a group where surgery produced a 90% chance of being cured at 10 years, or a 40% chance depending on the gene expression. BUT…and this is key…what to do about the result is still a complex decision for both patient and physician. If you are a Gleason 3+3=6 patient and with no treatment at all you have an 85% chance of “cure” at ten years, is that good enough? What if it is a 95% chance? Will that make you more comfortable choosing no treatment, or do you want to be cured at any cost (impotence, incontinence, other side effects of radiation or surgery)?

As none of these tests has been proven in a prospective study – that is, using the tests to do something like even more aggressive therapy in a group of high risk patients, we are still in the early stages of understanding how and when to use them. Fortunately, my colleague, Dave Crawford and some colleagues have put together an excellent website to help patients/doctors understand the tests. http://www.pcmarkers.com has a list of most of the available tests and you can see what results might look like before you and your physician decide to send one off. This is a rapidly evolving field however, and not every test that is being commercialized is listed, and at big centers, there are always new tests being developed.

Finally, as with all of medicine, the payment systems/insurance coverage is crazily complex. Only today, I received an email with the “news” that a cardiologist/congressman, Rep. Buchson has introduced a bill called the “Prostate Cancer Misdiagnosis Elimination Act of 2017” that uses DNA profiling to make sure the tissue being tested is yours. You could theoretically apply this test to ANY cancer biopsy of course, so why prostate cancer? Then there is the motivation…call me cynical, but I suspected that the good congressman, meddling in medicine, might have a local connection, and sure enough, the company that markets the test is from his home state, Indiana. Not to say it isn’t important to know that tissue being tested comes from the correct patient or that the test isn’t a nice application of the kind of technology that identified OJ’s blood, just that we live in interesting times where medical technology is rapidly consuming more and more of our tax/insurance/personal dollars. Personalized medicine will depend totally on this type of technology and can be incredibly expensive. Whether it saves money or consumes it may depend on how many “worthless” (for that patient…and is a treatment with only a 5% chance of working really worthless??…not if you are in the 5% group) treatments are avoided and at what cost. I don’t have the answers. Hopefully this blog at least helps you begin to understand the current molecular diagnostic landscape.

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