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Medicine Science

Personalized Cancer Vaccines Safely Fight, Kill Tumors In Early Human Trials (arstechnica.com) 73

Emily Mullin reports via MIT Technology Review: Now two personalized cancer vaccine approaches appear to have safely prevented cancer relapse in a dozen patients with late-stage skin cancer. In recent years, scientists have realized that each patient's tumor harbors a unique set of genetic characteristics, or mutations. So for cancer vaccines to be effective, they'll probably also have to be unique. Two clinical trials, detailed today in separate papers in Nature, are among the first to show that this might be possible. In one trial, eight of 13 melanoma patients who got a personalized cancer vaccine were tumor-free nearly two years after being treated. In a smaller study, four of the six patients who received a vaccine had no detectable cancer for more than two years after treatment. All patients had their tumors surgically removed before getting the vaccine. The customized vaccines are an emerging class of therapies that take advantage of neoantigens, proteins that appear on tumors and seem to be specific to each cancer patient. To make the vaccines, researchers first sequenced DNA and RNA extracted from each patient's tumor. They then used computer algorithms to analyze the mutations on each tumor and predict the best targets that code for neoantigens. Based on that data, they created a personalized vaccine containing up to 20 of these neoantigens. Each patient received several injections of the vaccine over a few months.
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Personalized Cancer Vaccines Safely Fight, Kill Tumors In Early Human Trials

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  • The problem is cost (Score:5, Informative)

    by Anonymous Coward on Friday July 07, 2017 @05:23AM (#54762377)

    This all sounds promising, but the problem with personalized treatment is the cost.

    From the article:

    "The customized vaccines are an emerging class of therapies that take advantage of neoantigens, proteins that appear on tumors and seem to be specific to each cancer patient. To make the vaccines, researchers first sequenced DNA and RNA extracted from each patient’s tumor. They then used computer algorithms to analyze the mutations on each tumor and predict the best targets that code for neoantigens. Based on that data, they created a personalized vaccine containing up to 20 of these neoantigens. Each patient received several injections of the vaccine over a few months."

    Protein discovery is really hard to do. This is a good approach, by sequencing the DNA and using that to feed into a computer model to determine what proteins are expressed by the mutations. This modeling though is extremely complex and rarely accurate, as there are too many variables that are hard to determine without extensive lab analysis to support it. This could cost around $100,000 or more, if you're lucky it could cost less, but still in the $50k to $75k range.

    Then once you have your target, you need to develop something to neutralize it. Most cancer immunotherapy are monoclonal antibodies, of which the methodology to develop them is well known in industry, but can still be expensive. There's never been a synthetic, computer modeled antibody that's as good as a mouse or rabbit monoclonal antibody, and to get one good antibody you're likely going through about 1,000 mice at around $200 to $400 a pop, so this is most likely around $200k to $400k.

    And there's no way to scale this with volume, because it's discovery not production. Every person would need a new discovery every time, so you're looking at $500,000 per patient roughly speaking. So while promising science, no healthcare system can afford this without bankrupting itself.

    Herein is the problem with cancer immunotherapy. The latest one on the market is Keytruda by Merck. One year's dosage can cost around $150,000, so while it's quite effective as a drug, it can bankrupt patients and payer systems very quickly. Somehow the cost aspects of these drugs need to be addressed, because there's simply no way they be effective on the broader market without some ability to lower the cost.

    • Comment removed (Score:5, Insightful)

      by account_deleted ( 4530225 ) on Friday July 07, 2017 @05:59AM (#54762477)
      Comment removed based on user account deletion
    • by Anonymous Coward

      Exactly. And while it seems possible to drive the cost down by "mass production" (in this case, of course, rather automation of the whole chain), this'll be only viable if you (expect to) get enough paying customers. The traditional way to achieve that has been up to now to bet investment capital, thus inflating the bubble we're accumulating in front of us ever more and more.

      Does it matter? I don't know, but I'm a bit wary to see how e.g. Tesla is valuated wrt. Chrysler or GM -- or Apple wrt. others who are

    • Cost isn't a problem for a rich dying person. If it really was your only hope $500,000 is within reach of probably 25% of families in North America. And don't get me started on the stupidity of OHIP (Ontario's Health system), I've watched them spend close to $300,000 twice on friends or relatives who had zero chance of recovery.
      • And don't get me started on the stupidity of OHIP (Ontario's Health system), I've watched them spend close to $300,000 twice on friends or relatives who had zero chance of recovery.
        That would happen in most western health care systems. And rightfully so. You never really know the chance of a small wonder.
        The only treatments in Germany which can be denied, not technically, but by playing the system are transplantations.
        People are on a list, basically how urgent it is. But there is also a factor involved, how

    • This all sounds promising, but the problem with personalized treatment is the cost.

      Yeah, those new-fangled "computers" (anyone old enough to remember when "computer" was a job description?) cost so damn much there'll never be a real demand for more than a few dozen in the world, much less the country...

      • by Anonymous Coward

        Maybe we finally found something useful for AI to do besides driving cars for people too lazy to steer a wheel

    • by Kjella ( 173770 ) on Friday July 07, 2017 @08:31AM (#54763027) Homepage

      Not that long ago "sequencing the DNA" would have been a prohibitingly expensive step. Show that this works for broad classes of cancer patients and we'll find cheaper ways than guessing with lab rats. Lab work can also often be automated to a fraction of the cost in volume. For cancer in young people $500k is not bad if it keeps them cancer free, we spend huge amounts on medicines that only prolong the inevitable.

      • by e r ( 2847683 )

        ...we spend huge amounts on medicines that only prolong the inevitable.

        ALL medicine is only prolonging the inevitable.

    • The first of anything is going to be ridiculously expensive. The first transistor was the size of a fist and took years in a lab to build. Your pc right now has millions of transistors in it. If you could move it back to 1947, the cost of your computer would exceed the GDP of the entire planet.

      • The first transistor was the size of a fist

        Nonsense.The first transistor, a point contact device, was perhaps the size of a thumb nail. It was surrounded by mechanisms to hold and tension the contacts, and the whole contraption might be called fist sized, but not the transistor.

    • by wren337 ( 182018 ) on Friday July 07, 2017 @09:13AM (#54763327) Homepage
      I also expect that we will find some number of relatively common mutations, over time. Cancer is a coding mistake that leads to uncontrolled growth. The fact that we've named certain of these errors, that we know how they progress and how to treat them, tells me that there are common coding mistakes that trigger cancerous growth. If we got this down to 100 or 1000 or 10000 different vaccines that covered 75% of cancers, and you could pick the right vaccine(s) with a DNA test, we'd be kicking ass.
    • by Anonymous Coward

      You seem to be saying that the cost cannot come down in the future, to which I disagree. Just look at the price of gene sequencing: $100M in 2001 per genome, to less than $10k per genome in 2012, to just over $1k per genome in 2015 (google: "price of gene sequencing"). As biology becomes an information science, it will see the same gains

    • by Anonymous Coward

      The problem is not the cost. Cancer treatment is already expensive, right now.

      https://costprojections.cancer.gov/annual.costs.html

      To pretend that things like sequencing and protein analytics won't improve is disingenuous at best, idiotic at worst. Yes, it will scale in the sense that people tend to get much better at any repeated, analytic task.

    • maybe stop fighting pointless wars. Solve our energy problems instead of exacerbating them to protect rich guys oil investments. That'd work too.
    • Uhh you just said that they use computer algorithms to determine the neo-antigens.
      I read the Nature papers as well. I am familiar with most of the techniques described. Aside from the initial sample gathering. I saw nothing that can't be automated. Once the tumor is sampled there is very little (if any) human judgement needed. You will of course need robots to perform the assays and make the vaccines, but all of that is highly automatable.

      The only parts of the process that are difficult (though not at all i

    • by e3m4n ( 947977 )

      that's always the case in just about any sort of technology. We throw away outdated smart phones that are hundreds of times more powerful than the computer that put apollo 11 on the moon. At one time only a few people on the planet had access to the sort of computing power we take for granted daily. Eventually this kind of therapy will take an hour, require a needle biopsy of the mass, and a smartphone to run the sequencing via bluetooth to some piece of field-grade lab equipment to sequence the structure.

    • I realize there's a slashdot memo that says the earth is over populated so we have to appraise the cost of solar as plummeting and break through health techniques as soaring, but come on here.

      The differences between people is being closed by ALGORITHMS. ALGORITHMS have zero overhead. You can moan about IP or whatever, but competition can bring that difference way, way down.

      You make a claim that this approach is rarely accurate, but that's not reflected in the data above. By the same token gene sequenc
    • by Shotgun ( 30919 )

      I was interviewing for a job a couple years ago. It was a company bought up by Quintiles that was automating the process of DNA sequencing. They were targeting sub $1,000 tests with the use case being targeted cancer drugs.

    • by tobiah ( 308208 )

      Good summary of established technology, but cost is a red herring:
      1) Moores Law may not be as fast for manufacturing, but it still holds that things get cheaper on repetition. Cars, TVs and computers all used to be luxury items for the well-off.
      2) I've done a fair amount of coding for DNA/RNA analysis, and the resulting assays cost a few hundred dollars to run. A profitable $1000 test could be developed that IDs the cancer and describes the treatment in a few years time. An alternative to monoclonal antibod

    • Not to worry, Martin Shkreli will buy it and reduce the cost. Oh wait.
  • by famebait ( 450028 ) on Friday July 07, 2017 @06:14AM (#54762523)

    Now we only need to try it out on modern humans.

    • by aquabat ( 724032 )
      Oh my God, this is so dangerous. Even if we discount the ethical issues of experimenting on our distant ancestors, the temporal danger is enormous. If Wikihistory has taught us anything, it may be that messing with the timeline could have had far-reaching and pan-dimensional consequences. I mean, for all we know, this could will have been what causes cancer in humans the first time.
  • by CharlieG ( 34950 ) on Friday July 07, 2017 @07:08AM (#54762687) Homepage

    He thought he was dead for sure - stage IV melanoma. He's cancer free. Amazing stuff

  • by Anonymous Coward

    This isn't a 'vaccine'. Besides which, there is on such as 'vaccination' because Jenner was a fraudster.

    http://www.whale.to/v/hadwen1.html

    Why has nobody rebutted that speech yet? Ever? Anywhere on the entire internet?

  • What about the patients that DIDN'T get a vaccine? Did they do better or worse than the treated ones?
    • Re:Control group (Score:5, Informative)

      by Pasquina ( 980638 ) * on Friday July 07, 2017 @09:50AM (#54763579)
      Early stage (Phase I) trials usually don't have control groups because the goal is to test for toxicity of the therapy. Later stage (Phase II, III) look to compare efficacy against the "standard of care." In this study, no one was admitted to the study but did not receive the therapy - that will happen in the next study.

      Phase I trials are traditionally done in health volunteers, but these days, cancer trials are frequently performed in late stage cancer patients because they are desperate and have no other (Western medical) options. These patients had exceedingly little chance of spontaneous recovery, so you can assume the "control" group would have close to 0% survival.

      The fact that they got such a huge response is amazing and highly promising.
      • Agreed. The stage IV survival rate for Melanoma for five years is 15%. To be two years along without any relapse is remarkable, IMHO.
  • Im not an immunologist, but why couldn't this same vaccine not also be given to someone fighting their first battle with cancer also? Wouldnt these sequencing shots also serve as an immune system booster for that specific rna/dna sequence?

    • Short answer: Yes, in theory.

      Unproven therapies usually start out by treating patients with no other good options. Without good data, there is no reason to believe the new therapy is better than the standard of care - that's the whole point of late stage trials.

      As doctors and the FDA and insurance companies and patients get more convinced that a therapy is useful, there will be a push to use it at an earlier line of therapy, and the company will run trials in earlier stage patients. Eventually, this c
  • Once a large enough library of these neoantigens is created wouldn't the process become as simple as a google search for the right combo seen before and just use it? I understand that currently the sample size is small thus the neoantigens seem to be unique to each patient but as the sample size increases I am confident we will start seeing repeats. Can anyone who know about this comment?

Keep up the good work! But please don't ask me to help.

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