Contra Science-Based Medicine

Epistemic status: hand-wavy, but making a serious point

TW: diets.

I recently did some reading about ketogenic diets for cancer, and I’d like to compare and contrast my approach with the explanation on the blog Science-Based Medicine, which consistently presents the “skeptical” perspective on alt-med questions.

David Gorski is a cancer biologist himself, as I am not; his posts are always informative, and I have no quarrel with his facts. I read the studies mentioned in the post, so we’re using pretty much the same set of data points. And I agree with the broad outlines of his claims: ketogenic diets have some promising but by no means conclusive preclinical evidence for brain cancers; they’re definitely not a substitute for chemotherapy in general; and Dr. Seyfried has been overselling his research as a cure for cancer in disreputable alt-med venues.

But I want to pick apart some points of perspective and interpretation.

The first part of the post is all about painting Seyfried as disreputable because of his associations with alt-med institutions. Gorski says of the American College for Advancement in Medicine, “this is not an organization with which a scientist who wishes to be taken seriously by oncologists associates himself.”

Now, I’m not defending the cancer quacks mentioned; these are people who pitch chelation and coffee enemas, things that are pretty clearly scientifically disproven.  However, I’m suspicious of the rhetorical trick of guilt by association and argument from consensus.  Surely we care about whether Seyfried is correct, not whether he is “taken seriously”, “reputable”, or “legitimate.”  These are all social words, not scientific ones, and constitute an emotional appeal to social conformity and authority.

To his credit,  Gorski doesn’t stop there; he does make substantive criticisms of Seyfried’s work.  But I think it’s worth pointing out when, as happens so often in the biomedical world, a social argument is conflated with a scientific one.

Gorski goes on to criticize Seyfried for “exaggerating how hostile the cancer research community is towards metabolism as an important, possibly critical, driver of cancer” when cancer metabolism is, in fact, an active area of current cancer research.  He goes on to say, “Dr. Seyfried, in my readings, appears all too often to speak of “cancer” as if it were a monolithic single disease. As I’ve pointed out many times before, it’s not. Indeed, only approximately 60-90% of cancers demonstrate the Warburg effect.”

None of these facts are wrong, but the interpretation is misleading. Cancer metabolism and metabolic mechanisms for cancer treatments are, in fact, common topics of cancer research; but this ought to be evidence in favor of Seyfried’s hypothesis, that it’s within the range of mainstream science and is supported by many cancer biologists, rather than being pure invention like most alt-med “cancer cures.”

I’d also argue with the statement that “cancer isn’t one disease.”  It’s true that not all cancers demonstrate the Warburg effect, but 60-90% is a lot of cancers; a drug that was effective in 60-90% of cancers would be as revolutionary an advance as chemotherapy.  An antibiotic that killed 60-90% of bacteria could fairly be said to “kill bacteria.” When most (if not all) cancers have structural features in common, that indicates that talking generally about “cancer” is meaningful, and that it doesn’t make sense to treat every sub-sub-type as though it is a completely different disease.  Cancer has both unity and diversity.  Saying “cancer isn’t one disease” is a rhetorically loaded move that means “don’t generalize from one type of cancer to another.”  But it’s not correct to never generalize; that would utterly paralyze research.  How much it’s safe to generalize depends on how common the relevant feature is across cancers; in the case of the Warburg effect, that’s a matter of current debate, but it’s fair to call it pervasive.

I don’t have much criticism of the way Gorski handles the ketogenic diet studies. He’s on the skeptical side, but skepticism is warranted. Mouse studies very frequently don’t generalize to humans; they’re suggestive, but only weak evidence. And while there were two case studies of patients who did notably better than typical glioblastoma patients on ketogenic diets, we don’t have enough patients to be confident that the improvements were a result of the diet.

But then Gorski says, “Clearly, ketogenic diets are not ready for prime time as a treatment for cancer.”

Now, wait a minute. What does that even mean?

As a cancer patient, does it make sense for you to try a ketogenic diet?  Well, there’s a plausible mechanism for it to work (particularly in brain cancer), there’s some suggestive evidence in mice and a few humans with brain cancers, and — crucially — it’s just a diet.  People go on ketogenic diets all the time, for no other reason than wanting to lose weight. It’s even been shown medically safe (though apparently hard to comply with) in cancer patients. Trying a special diet is pretty low risk, and a reasonable person aware of the evidence might very well choose to try it.

It doesn’t make sense to use a ketogenic diet as a replacement for chemotherapy or radiotherapy in cancers where those treatments work. That would be very unsafe.  But for certain advanced brain cancers, chemo barely extends life if at all, and is very unpleasant. If there’s anyone who has a good reason to refuse chemotherapy, it’s someone who’s almost certain to die soon and doesn’t want their last few months to be agonizing.

Is a ketogenic diet for cancer something that every oncologist in the world should be prescribing for his patients? No way. Should it be the “standard of care”? No; there isn’t enough evidence that it helps.  But is it worth trying for an individual who wants to? Quite possibly.

The distinction here is about where you put the reader’s locus of identity. Is a reader supposed to imagine herself as a potential cancer patient, considering whether or not to try the diet? Or as a potential administrator, considering whether or not to make the diet a policy for everyone?  The rhetorical trick Gorski’s using here is in identifying the reader with a nebulous “we”, as in “should we put cancer patients on ketogenic diets?”  You are meant to imagine a consensus, or an authoritative body.  The medical profession, the government, something like that.  This imagined “we” is the mirror image of the nebulous “they” that conspiracy theorists believe in, the “they” who doesn’t want you to know about cancer cures.

The overall effect of believing in an imagined “we” or an imagined “they” is to make social reality the primary reality.  “We” or “they” represents a vague model of “society” — the “respectable” people, the “legitimate” and “reputable” people, the “consensus”. In other words, the tribal elders. If you have a positive association with “the consensus”, as Gorski clearly does, then you want to expel the “disreputable” from the consensus.  If you have a negative association with “the consensus”, then you mistrust anything that sounds official and look for fellow mavericks and outsiders.  In neither case are you primarily evaluating claims of fact; you are evaluating people.

For instance, the existence of Phase I/II trials of the ketogenic diet on glioblastoma ought to be good news for ketogenic diets.  More evidence will soon come in; and the fact that the studies exist at all is further evidence that ketogenic diets are taken seriously by mainstream cancer researchers.  However, Gorski treats this as an indictment of Seyfried, because he wanted to do an (uncontrolled) case series of ketogenic diets rather than the more thorough controlled studies.  The overall intent of the blog post is to communicate Seyfried is disreputable, cancer is complicated, people who believe in cancer cures are beyond the pale, when one could have used exactly the same facts to make the point ketogenic diets are an exciting possibility for glioblastoma and the preliminary evidence is encouraging.

My own perspective can perhaps be summarized as “a contrarian worldview from mainstream sources.”  Looking at ordinary sources like journal articles and historical primary sources, looking at uncontroversial claims of fact, often gives me a view of the world that is quite different from the “we”-based view where “society” is more or less getting things right.  My object-level beliefs are rarely that unusual; the connotation of those beliefs is where I differ from most people.  I don’t feel myself to be safely nestled in the lamplit circle of “we”; I feel like I’m outside, tumbling in the abyss, with only the frail spark of my mind to illuminate a small patch around me.  And I think that, ultimately, the abyss is real, and the lamplit circle is imaginary.

What Is To Be Done?

Epistemic status: loose and speculative

This is the last post in my cancer series. On reflection, there’s a lot I want to edit and expand here, and I think the right format for this  is a book rather than a blog. So, over the next several months I’ll be working on that.

In the meantime, I want to draw some conclusions given what I’ve found out about cancer so far. What are the next steps? Where do we go from here? The world I see is one where the “efficient market hypothesis” doesn’t hold in cancer research. Just because an idea is promising doesn’t mean it’ll be tried, particularly in human clinical trials.

So what can you, a reader, do to cure cancer?

1. Do cancer research

This one’s kind of a no-brainer, but I put it here because I see a lot of young EA’s wondering what to do with their lives, and the most frequent ideas are things like “make a lot of money to give to charity” or “work at an EA organization”, but I really believe a broader range of object-level skills could be useful for bettering the world. Doctors and biologists are important. Ultimately, the things that kill the most human beings today are the noninfectious diseases of aging.  If your heroes are the people who eradicated smallpox, maybe you should take up the cause of ending another disease.

2. Invest in or donate to organizations doing undervalued cancer work

In my blog series, I pointed out some researchers that I thought were doing unusually promising early-stage research.  Getting preclinical studies to clinical trials takes funding.

I haven’t investigated any of these organizations as organizations — I don’t claim to know that they’re likely to be profitable investments or efficient charities. I’m just looking at the drug candidates that I’ve found promising and seeing which existing organizations are involved in researching them.

3-bromopyruvate, the glycolysis inhibitor I’m bullish on, is being developed by PreScience Labs.

The Cancer Research Institute, a nonprofit that accepts donations, has funded a great deal of important immunotherapy research, including most of the recent work on mixed bacterial vaccine by the late renowned immunologist Lloyd J. Old.

The Fibrolamellar Cancer Foundation, which focuses on the rare liver cancer fibrolamellar hepatocellular carcinoma, has Sanford Simon on its advisory board and funded his research on anti-IgG antibodies to precisely detect and potentially destroy cancer cells.

I expect that there are other avenues to funding particular lines of scientific research, from creating novel grant-giving foundations to crowdfunding experiments.

I’m also interested in institutions like IndieBio, which try to bring a radical, Silicon Valley spirit to the biotech industry, and get funding for biomedical startups working on hard problems.

3. Political reform

It would be easier to innovate in cancer research if the regulatory challenges were less onerous.  Lobbying and activism, in the US or elsewhere, could probably be helpful.

This is an area where think tanks and patient advocacy groups are relevant.  I don’t have a clear idea of which precise policy goals are the most useful and attainable, but people with more of a policy bent can probably answer that question.

A different kind of “political” approach is regulatory arbitrage — trying to find or negotiate a favorable political climate to research somewhere outside the US.

4. Further meta-research

We clearly need more evaluative work done on the questions “What types of cancer research are most promising? Where is the low-hanging fruit, if any?”  I’ve been doing that, but I’m only one perspective.  This seems valuable in the context of something like the Open Philanthropy Project, which tries to evaluate the tractability of entire goals.

 

Regulatory Problems with Cancer Research

Epistemic status: more argumentative than the other posts in this sequence. This is obviously informed by my own political views, but my intent is to be convincing to a range of audiences.

In this sequence I’ve been arguing that, while most cancer drugs developed over the past several decades are not very effective, there are potentially exciting avenues of research that haven’t gotten much attention or funding yet.

Why is this the case?  Cancer research is a huge field full of intelligent people. Cancer is a very common disease and there’s a lot of money to be made in treating it. “Curing cancer” is a byword for a lofty goal.  Why should there be any 20-dollar bills lying on the sidewalk at all?

In particular, why would there be less progress since the War on Cancer, which allocated much more federal funding to cancer research than was available before?

The conventional story is that cancer is simply hard. We already gathered the low-hanging fruit of radiotherapy and cytotoxic chemotherapy; now we’re trying to cure the tougher cancers, and it just takes more money and time.

I’ve been arguing that the “cancer is hard” story is incorrect. Targeted chemotherapy, the most popular approach for the past two decades, tends to fail because of the incredible diversity and mutability of cancer.  Approaches that focus on what cancers have in common, like their high glucose requirements or susceptibility to immune defenses, might turn out to work much better.

But, if I’m correct, why hasn’t some enterprising cancer researcher already come to the same conclusions? Even if I’m wrong, I’m not unique; a lot of my argument is just echoing James Watson’s views. Why haven’t any investors and funders decided it might be a good idea to try cancer research the way the discoverer of the double helix thinks we should do it?

This can be explained by an increase in the regulatory burden of cancer research in the past several decades. Clinical trials have become more expensive, require more paperwork, and allow less freedom of judgment from clinicians and researchers.  Only a large pharmaceutical company can afford to run Phase II and III clinical trials these days.  There’s more money in cancer research than ever, but it’s harder to try new things on sick people.  This tends to narrow cancer research to established players and drug classes.

In the world of early-stage tech startups, success follows a power-law distribution. Investors gain more money by funding a handful of huge successes than they lose by giving small investments to a lot of things that don’t work out. So it makes sense that, for instance, YCombinator keeps casting a wider net, accepting startups at earlier stages, and actively seeking outliers and mavericks. They want to make sure they don’t miss the next AirBnB.

It would seem to make sense that investing in drug candidates would work similarly; you don’t want to miss the next Gleevec either.  But if the cost of testing is too high, casting a wide net becomes much more expensive. You can’t just give the founders of an early-stage biotech company a little funding to see if they can do something awesome with it.  And so, medical research becomes much more conservative.

Regulation Has Increased Costs and Slowed Drug Development

90% or more of a typical drug’s costs come from Phase III clinical trials. So it makes sense to focus on the costs and barriers associated with clinical trials, to see if they’ve gone up over time and what the consequences have been.

As of 2005, the R&D cost of the average drug was $1.3 billion. In 1975, that figure was $100 million. (That is, drug trials have gotten on average more than 13 times more expensive over the past forty years.)  Phase III trials are becoming longer, involving more procedures and more hours of work, and have lower enrollment and retention due to more stringent enrollment criteria and trial protocols.  

Protocols for clinical trials are now over 200 pages long on average. The combined costs are $26,000 per patient.  The annual rate of cost increase is itself increasing, from an annual increase of 7.3% in 1970-1980 to 12.2% from 1980-1990 (inflation-adjusted.)  The estimated cost per life-year saved from current clinical cancer trials is approximately $2.7 million.

It now takes an average of 12-15 years from drug discovery to marketing, compared to an average of 8 years in the 1960’s.  Before the 1962 Kefauver-Harris amendment that vastly increased FDA powers, it took only 7 months. For oncology drugs, just the preclinical work takes 6 years; once early clinical trial data are in, it takes 26-27 months to proceed to Phase II or III; and it takes an average of 14.7 clinical trials (Phase I, II, or III) to get a drug approved.

Running a clinical trial requires protocols to be approved by the FDA, the NCI (National Cancer Institute, the primary funder of cancer research in the US), and various IRBs (institutional review boards, administered by the OHRP, or Office of Human Research Protections.)  On average, “16.8% of the total costs of an observational protocol are devoted to IRB interactions, with exchanges of more than 15,000 pages of material, but with minimal or no impact on human subject protection or on study procedures.”  Adverse events during trials require a time-consuming reporting and re-consent process. While protocols used to be guidelines for investigators to follow, they are now considered legally binding documents; so that, for instance, if a patient changes the dates of chemotherapy to schedule around family or work responsibilities, that is considered to be a violation of protocol that can void the whole trial.

To handle this regulatory burden, an entire industry of CROs (contract research organizations) has grown up, administering trials and handling paperwork to make the experimental drug look good to federal regulators. Like tax preparers, CROs have an incentive to keep the regulatory process complex and expensive.

The result of all this added cost is that fewer drugs get developed than otherwise would.  Sam Peltzman’s 1973 study of drug availability and safety before and after the 1962 Kefauver-Harris amendment (which significantly enhanced FDA powers) found that a model of drug development predicted a post-1962 average of 41 new drugs approved per year, while the actual average was 16 new drugs approved per year. The pre-1962 average number of drugs approved per year was 40.

 

This is a graph of the number of new drug applications approved by the FDA every year from 1944 to the present. Note that the number of drugs approved has been largely flat since the 1962 Kefauver-Harris amendment, though the decline in drug approvals appears to precede the law by several years.

Increased Drug Regulation Has Not Meaningfully Decreased Risk

Peltzman’s study on the Kefauver-Harris amendment found that there was little evidence suggesting that more ineffective drugs reached the market pre-1962 compared to post-1962.

Comparing the US to Great Britain and Spain, each of which approve more drugs per year than the US, the other countries have no higher rates of postmarket withdrawals of drugs, suggesting that the extra regulatory scrutiny is not providing us with safer drugs.

Toxic death rates haven’t dropped much in Phase I trials. In 6639 patients, comprising 211 trials, between 1972 and 1987, the toxic death rate was 0.5%. In 11,935 patients, comprising 460 studies, between 1991 and 2002, the toxic death rate was also 0.5%.  

Between 1999 and 2006, the number of adverse drug reactions recorded in the US has actually been increasing, particularly  as the proportion of elderly patients taking many drugs has increased.

The most common severe drug interactions are often from old, well-known drugs, like insulin, warfarin, and digoxin.  “Antibiotics, anticoagulants, digoxin, diuretics, hypoglycaemic agents, antineoplastic agents and nonsteroidal anti-inflammatory drugs (NSAIDs) are responsible for 60% of ADRs leading to hospital admission and 70% of ADRs occurring in hospital.”  Increasing regulation on new drugs isn’t going to stop the problem of increasing adverse drug reactions, because most of those come from old drugs.

Cost-Benefit Tradeoffs Support Looser Regulations On Drugs

Gieringer’s 1985 study estimated the loss of life from FDA-related delay of drugs since 1962 to be in the hundreds of thousands.  This only includes the delay of drugs that were eventually approved, not the potentially beneficial drugs that were never approved or never developed, so it’s probably a vast underestimate.

In a recent paper, “Is the FDA Too Conservative Or Too Aggressive?“, the authors apply a Bayesian decision analysis to evaluate the overall cost of a trial based on the disease burden of Type I vs. Type II errors.

The classical approach used by the FDA is to constrain experiments to a maximum 2.5% risk of Type I error for all tests, and then choose a power for the alternative hypothesis by making the sample size large enough.  That is, no drug can be approved if there is a greater than 2.5% chance that it is ineffective.

This doesn’t make sense from a disease risk standpoint, because for very severe diseases, the risk of not trying a drug that might work is higher than the risk of trying a drug that doesn’t work.  The authors use data from the U.S. Burden of Disease study, which measures Years Lived with Disability to compute the “optimal” level of acceptable risk of inefficacy for drugs for different diseases. For instance, in pancreatic cancer, the BDA-optimal risk of Type 1 error is 27.9%, since the disease is so deadly.

Cancer in general, being both common and deadly, is an especially good area for looser drug regulation.  If a new therapy increased the cure rate of lung cancer by just 1% (through improved adjuvant therapy) and increased the average life expectancy of uncured patients by just 3 months, the [five-year] regulation-induced delay would cost more than 2,000,000 life-years worldwide.

Even this cost-benefit framing may be understating the case for FDA and OHRP reform, though. The problem seems to be less that the standards for efficacy are too high, than that the costs of compliance are too high because of redundant and excessive required documentation.  It would in principle be possible to streamline the process of conducting clinical trials without reducing its rigor.

We Think About Risk Wrong

In medical contexts, people often talk about the unknown as disrespectable. An “unapproved” drug, an “untested” drug, an “unproven” drug, a treatment that is “not indicated”, all sound unsettling.  Nobody wants to play cowboy in life-and-death situations.

But this kind of language is not actually about reducing risk.  Reality is probabilistic; all choices have potential risks and potential benefits. There’s no real wall, out in the universe, between the “safe/known” and the “unsafe/unknown”; that’s a human framing, akin to the Ellsberg paradox or the bias of ambiguity aversion. People prefer known risks to unknown risks.

In other words: death and disease are scary, and rightly so, but people will tend to be less frightened of risks that seem normal and natural (people have always died of cancer) than of risks that seem outlandish or like somebody’s fault (taking an experimental drug that might or might not work).  Chosen risk, conscious risk, stepping into the unknown, is viewed as worse than the risk of passively allowing harm to occur.  Even if the objective risk-benefit calculations actually work out the other way.

This is an instinct worth fighting.  Cancer is a common disease, yes; but the “normalcy” of it can blind us to the horrifying death toll.  As Bertrand Russell said, the mark of a civilized man is the capacity to read a column of numbers and weep.

Fear of action isn’t actually about making people safer. It’s about making people feel safer, because they aren’t looking at the whole picture.  It’s about making people feel like they can’t be blamed.

It’s Too Hard to Do Transformative Biomedical Research Today

Derek Lowe, an always insightful observer of the pharmaceutical scene,  comments on the VC firm Andreessen Horowitz’s first foray into biotech, “In this business, you work for years before you can have the tiniest hope of ever selling anything to anyone. And before you can do that, you have to (by Silicon Valley standards) abjectly crawl before the regulatory agencies in the US and every other part of the world you want to sell in. Even to get the chance to abase yourself in this fashion, you have to generate a mountain of carefully gathered and curated data, in which every part of every step must be done just so or the whole thing’s invalid, go back and start again and do it right this time. The legal and regulatory pressure is, by Valley standards, otherworldly.”

It shouldn’t be.

I am not a policy expert, so I don’t know what the appropriate next steps are.  What kinds of reforms in FDA and OHRP rules have a reasonable chance of being passed?  I don’t know at this point, and I hope some of my readers do.

I do know that committed activists can change things. In 1992, after a decade of heroic advocacy by AIDS patients, the FDA created the “accelerated approval” process, which can approve drugs for life-threatening diseases after Phase II studies.

We have to find a way to continue that legacy.

3-Bromopyruvate

Epistemic status: fairly confident

Most cancer cells, instead of using cellular respiration, get ATP  from glycolysis. This is called the “Warburg Effect.”

Glycolysis is less efficient than cellular respiration, which is why cancer cells have higher glucose requirements and why interventions that improve insulin sensitivity (like metformin) have anti-cancer effects.  The high glucose consumption of cancer cells is so reliable an indicator of cancer that it is the basis of detecting metastases in PET scans.

Tumor progression is associated with the emergence of the Warburg effect.  One hypothesis for why is that cancer cells lose mitochondrial function (and thus the capacity for cellular respiration) as they mutate; another is that the hypoxic environment of a tumor makes cellular respiration impossible.

Because  reliance on glycolysis is such a general feature of cancer, a natural type of drug to try on cancers is a glycolysis inhibitor, which would cut off tumors’ energy supply.  To the extent that the Warburg effect is a result of the inability to engage in cellular respiration, glycolysis inhibitors should not fail as cancers continue to advance, but should, if anything, become more effective; cancer cells which have lost mitochondrial function are unlikely to regain it, while cancer cells which have some distinctive surface marker targeted by a drug are likely to lose it over time.

An early-stage drug called 3-bromopyruvate is a glycolysis inhibitor which has shown promising animal results.

3-BP is a strong alkylating agent that inhibits the glycolysis enzyme GAPDH.

In a rat model of hepatocellular carcinoma [1], rats were treated with 2.0 mM of 3-BP; all treated rats survived more than seven months, while all control rats died within days.  The 3-BP eradicated large bulging tumors in the treated rats. The cellular ATP level of healthy cells stayed constant while the cellular ATP level of cancer cells dropped to 10% of its former level.

In a study of rabbits with liver tumors [2], mean survival in the control group was 18 days while mean survival in the treated group (with intraarterial 3-BP) was 55 days.  The tumors in treated animals had not grown and were mostly necrotic; the livers in control animals was almost completely replaced by tumor, with extension into the diaphragm and lungs.  Death in the treated animals was believed to be due to extrahepatic disease (by the time of treatment, the tumors were already metastatic, both in control and treated animals.)  Three animals were treated “earlier” (one week after implantation): one survived, the other two survived 80 days and died of lung metastases.  Intravenous administration, by contrast, was not effective.

Another rabbit study [3] found that intravenous 3-BP doesn’t kill liver tumors but does eliminate their lung metastases.

3-BP  also enhances survival of nude mice injected with human mesothelioma.[4]  There was a control group, a 3-BP treated group, a cisplatin-treated group, and a combined 3-BP and cisplatin group.   In the control group, 3-BP only group, and cisplatin only group, all mice died before day 45. In the combined group, survival was better than control (p = 0.0021), 3-BP alone (p = 0.0024), and cisplatin alone (p = 0.0161).  

In a study of 3-BP on mice with lymphoma[5], a significant reduction in tumor activity was found among those given repeated treatments (p = 0.0043 at day 7) but in those given only a single treatment, the effect was only significant at the second day (p = 0.0152 at day 2) and afterwards the tumors returned to normal.  The only manifestation of toxicity was lower body weight in the 3-BP-treated groups.

Microencapsulated 3-BP, delivered systemically, into a mouse model of pancreatic ductal carcinoma[6], causes minimal to no tumor progression, compared to animals treated with gemcitabine, which had a 60-fold increase in BLI, a measure of tumor activity.

Glioma cells are refractory to most treatment. D-amino acid oxidase combined with 3-bromopyruvate [7] decreased proliferation and viability in rats.

Aerosolized 3-BP also prevents the development of lung cancer in carcinogen-treated mice, without causing liver toxicity.[11]

There has been one human case study of 3-bromopyruvate, [8] on a young man with terminal fibrolamellar carcinoma. At the time of treatment, he was on a feeding tube, he had ascites, and his spleen was swollen due to complete blockage of the renal artery. He had already been treated with chemotherapy.  The University of Frankfurt’s ethics committee permitted him to be treated with a 3-BP, through the TACE delivery method (transcatheter arterial chemoembolism). He began having symptoms of tumor lysis syndrome, a dangerous condition associated with tumor necrosis.  CT scans showed that the tumors were necrotic after administering 3-BP, and the tumor areas were encapsulated and showed fibrosis.   His mobility was limited due to pre-existing ascites and edema, but he began to go out in his wheelchair. He died of liver failure 2 years after his initial diagnosis.   A fluid sample from his ascites found some mesothelial cells, but detected no tumor cells.

There are also a few negative results about 3-BP, but these are explainable by differences in protocols from the successful studies. One study of rabbits with liver cancer found 3-BP didn’t significantly increase tumor necrosis relative to controls, but it only used a single administration rather than repeated administration.[9]  One study of rabbits with liver cancer found that 3-BP killed them, but that was with a dose of 12x the dose in the successful studies.[10]  

This is fairly strong animal evidence, across a variety of cancers, of the most confident kind (tumor eradication and prolonged survival, not just inhibition of growth).  The single human study is not strongly conclusive but leans towards a positive effect.

One major issue is that intra-arterial administration for liver cancer seems to work while systemic administration doesn’t, though other types of cancer do seem to respond to systemic, microencapsulated, or aerosolized delivery. Clearly, attention needs to be paid to optimizing dosage, administration schedule, and delivery method.

As well as being a glycolysis inhibitor, 3-BP is also an alkylating agent, like most cytotoxic chemotherapies; this suggests it may work along multiple pathways. It also suggests we might see similar side effects to cytotoxic chemotherapy in humans.

3-BP is not the only glycolysis-inhibiting drug that has been tried.

Imatinib, which is by far the most successful targeted cancer therapy, is, among other things, a glycolysis inhibitor.

Dichloroacetic acid had some promising animal studies and stabilized five patients with recurrent glioblastoma on palliative care[12] for fifteen months (note that median survival time after the first round of radiation + chemo is only 15 months itself). But DCA has carcinogenic effects in animals, so research was halted. It also lost credibility due to alt-med practitioners selling DCA without FDA approval.

Lonidamine, another glycolysis inhibitor, is currently in clinical trials for brain cancer, but its past clinical results have been unspectacular.  I would have to look in more detail to understand whether there’s any mechanistic reason why 3-BP could be expected to do better than lonidamine in human trials; but for now, the failure of an earlier glycolysis inhibitor is admittedly an argument against 3-BP.

The case for 3-BP may be somewhat weakened but not wholly dismantled by alternate hypotheses about what causes the increased rate of glycolysis in cancer.

The “Reverse Warburg Effect” is a theory that argues that in some epithelial cancers (such as types of breast cancer), it is not the cancer cells but a type of neighboring healthy cells called fibroblasts that have elevated levels of glycolysis.  Glycolysis inhibitors still work on such cancers, however; DCA blocks cancer growth in vitro in fibroblast-induced breast cancer tumor growth.[13]

The Crabtree effect[14] is the phenomenon that some tumor cells have a reversible, short-term shift to glycolysis in the presence of glucose; in such cells, glycolysis inhibitors might not work because the cells could switch back to cellular respiration.  The overall effectiveness of glycolysis inhibitors on cancer will depend on whether the shift to glycolysis is mostly a facultative or an obligate phenomenon.  We can expect glycolysis inhibition to slow growth even if it doesn’t kill tumors, because glycolysis allows for faster cell growth than respiration; but if tumor cells can switch back and forth from glycolysis to respiration, then glycolysis inhibitors wouldn’t be likely to eradicate late-stage tumors, but only to stall early ones.

Overall, 3-BP looks like an unusually strong early-stage cancer drug. It appears likely to be broadly effective among many types of cancer. It is simple, has dramatic results (in animals), and is upstream.

Mechanistically, glycolysis inhibitors seem to be a strategy that is robust to different hypotheses about the cause of the high rate of glycolysis in cancer, and glycolysis inhibitors that are also generally cytotoxic would be even more robust to mechanistic uncertainty.

While there are many preclinical drugs that never succeed in humans, 3-BP is fairly novel in mechanism and seems likelier to pan out than the average new targeted therapy, precisely because it relies on a strategy of attacking cancer that is quite simple, should be broadly applicable across cancers and shouldn’t change over time as tumors evolve.  In order for a tumor to “work around” 3-BP, it would have to create an alternate enzyme to catalyze the 6th step of glycolysis, which seems unlikely; while in order for a tumor to work around an angiogenesis inhibitor, for instance, it would only have to find a different way to stimulate blood vessel growth, which, given the wide variety of growth factors in the human body, is not too unlikely.

References

[1]Ko, Young H., et al. “Advanced cancers: eradication in all cases using 3-bromopyruvate therapy to deplete ATP.” Biochemical and biophysical research communications 324.1 (2004): 269-275.

[2]Vali, Mustafa, et al. “Targeting of VX2 rabbit liver tumor by selective delivery of 3-bromopyruvate: a biodistribution and survival study.” Journal of Pharmacology and Experimental Therapeutics 327.1 (2008): 32-37.

[3]Geschwind, Jean-Francois H., et al. “Novel Therapy for Liver Cancer Direct Intraarterial Injection of a Potent Inhibitor of ATP Production.” Cancer research62.14 (2002): 3909-3913.

[4]Zhang, Xiaodong, et al. “Novel therapy for malignant pleural mesothelioma based on anti-energetic effect: an experimental study using 3-Bromopyruvate on nude mice.” Anticancer research 29.4 (2009): 1443-1448.

[5]Schaefer, Niklaus G., et al. “Systemic administration of 3-bromopyruvate in treating disseminated aggressive lymphoma.” Translational Research 159.1 (2012): 51-57.

[6]Chapiro, Julius, et al. “Systemic Delivery of Microencapsulated 3-Bromopyruvate for the Therapy of Pancreatic Cancer.” Clinical Cancer Research (2014): clincanres-1271.

[7]El Sayed, S. M., et al. “D-amino acid oxidase gene therapy sensitizes glioma cells to the antiglycolytic effect of 3-bromopyruvate.” Cancer gene therapy 19.1 (2011): 1-18.

[8]Ko, Y. H., et al. “A translational study “case report” on the small molecule “energy blocker” 3-bromopyruvate (3BP) as a potent anticancer agent: from bench side to bedside.” Journal of bioenergetics and biomembranes 44.1 (2012): 163-170.

[9]Shin, S. W., et al. “Hepatic intra-arterial injection of 3-bromopyruvate in rabbit VX2 tumor.” Acta Radiologica 47.10 (2006): 1036-1041.

[10]Chang, Jung Min, et al. “Local toxicity of hepatic arterial infusion of hexokinase II inhibitor, 3-bromopyruvate: in vivo investigation in normal rabbit model.”Academic radiology 14.1 (2007): 85-92.

[11]Zhang, Qi, et al. “Aerosolized 3-bromopyruvate inhibits lung tumorigenesis without causing liver toxicity.” Cancer Prevention Research 5.5 (2012): 717-725.

[12]Michelakis, E. D., et al. “Metabolic modulation of glioblastoma with dichloroacetate.” Science translational medicine 2.31 (2010): 31ra34-31ra34.

[13]Bonuccelli, Gloria, et al. “The reverse Warburg effect: glycolysis inhibitors prevent the tumor promoting effects of caveolin-1 deficient cancer associated fibroblasts.” Cell cycle 9.10 (2010): 1960-1971.

[14]Diaz-Ruiz, Rodrigo, Michel Rigoulet, and Anne Devin. “The Warburg and Crabtree effects: On the origin of cancer cell energy metabolism and of yeast glucose repression.” Biochimica et Biophysica Acta (BBA)-Bioenergetics 1807.6 (2011): 568-576.

Metformin, Fasting, and Exercise

Epistemic status: fairly confident.

TW: discussion of diet and exercise

In the post on anti-IgG, I talked about the strategy of routing around the complexity of cancer by finding a way to detect and kill a wide range of cancer cells at once. Another set of strategies for routing around complexity focuses on starving a wide range of cancer cells of the resources they need to grow.

Some strategies of this kind, like VEGF inhibitors to prevent angiogenesis, don’t work as well as one might hope: bevacizumab does not prolong survival more than a few months in any cancer.

However, one might hope that it’s possible to do better by looking at a very fundamental aspect of cancer cells: their extremely high energy requirements.  Obviously cells growing and proliferating rapidly need more energy than typical cells; this is especially true given the Warburg effect in which most cancer cells use glycolysis, which is less efficient than cellular respiration and requires more glucose.  Insulin insensitivity, in which tissues are slow to absorb glucose from the blood, leaves more resources available for cancer cells.  (This is a vastly oversimplified model and I do not fully understand how insulin relates to cancer growth.  There are multiple possible mechanisms whereby high insulin levels and insulin resistance contribute to cancer.)

Some simple methods that improve insulin sensitivity — exercise, fasting, and the type 2 diabetes drug metformin — seem to have anti-cancer effects.

Exercise

The effect of exercise on cancer is extremely confounded by other factors, so I won’t discuss it in much detail, except to say that observational studies have found that regular exercise has a preventative effect on some types of cancer.

At least 170 observational studies have been conducted on the association between exercise and cancer risk. The evidence is strongest for colon, breast, and prostate cancer.  Colon cancer had 43 of 51 studies demonstrate a reduced risk of cancer with physical activity, with a 40-50% reduction in risk; breast cancer had 32 of 44 studies demonstrate a reduced risk of cancer with physical activity, with a 30-40% reduction in risk; prostate cancer had 17 of 30 studies demonstrate a reduced risk of cancer with physical activity, with a 10-30% reduction in risk.[0]

In colon cancer, the effect of exercise was found in both recreational and occupational activity, and was observed even after controlling for BMI and dietary intake.

One possible mechanism for exercise’s preventative effects is that it reduces the level of sex hormones, which play a role in promoting the growth of breast and prostate cancer.  Exercise also improves insulin sensitivity and decreases the circulating levels of insulin-like growth factor (IGF); IGF and circulating insulin play a role in cancer growth.

Metformin

Metformin is a drug for Type 2 diabetes. It targets the enzyme AMPK, which induces muscles to take up glucose from the blood. This inhibits the production of glucose by the liver, which is why it reduces hyperglycemia in diabetics. It also increases insulin sensitivity and decreases insulin-induced suppression of fatty acid oxidation.

Insulin promotes cancer growth; insulin affects tumor cells either directly or indirectly through sex hormones, insulin-like growth factors, or adipokines.  Cancer cells have high energy requirements because of their rapid growth rate and their dependence on glycolysis.

Epidemiologic Evidence

A retrospective study of 11,876 diabetes patients in a Scottish hospital found that taking metformin slightly reduced the risk of cancer. The odds ratio was 0.86.[1]

A subsequent cohort study at the same hospital, of 4085 metformin users vs. 4085 matched diabetics who didn’t take metformin, found 7.3% of the metformin users vs. 11.6% of the comparators got cancer within 10 years, an odds ratio of 0.63 after adjusting for sex, age, BMI, SES, A1C, smoking, and drug use.  Also, 3.0% of metformin users died of cancer, compared to 6.1% of comparators.[2]

Complete response rates in breast cancer (defined as no sign of invasive carcinoma at the time of surgery, after a course of chemotherapy) were 24% for the metformin group, 8% for the non-metformin diabetic group, and 16% for the nondiabetic group.  This is statistically significant for metformin vs. non-metformin (p = 0.007) but not for metformin vs. nondiabetic.

A study of 1353 patients with diabetes found a 0.43 hazard ratio for cancer mortality among those taking metformin.[8]

A meta-study of 11 epidemiologic studies of metformin and cancer found a pooled relative risk for cancer incidence of 0.55.  The relative risk varied by year of use: 0.77 for 1 year, 0.6 for 2 years, and 0.28 for 5 years.  These studies compared diabetics using metformin to diabetics using other treatments, and included all types of cancers.[6]

A meta-study of 4 cohort studies and 2 RCTs found a pooled risk ratio of 0.66 for all-cancer mortality, 0.67 for all-cancer incidence.[9]

In a cohort of 480,984 Taiwanese participants, cancer incidence was twice as high for diabetics not on metformin as for nondiabetics; diabetics on metformin had similar cancer risk to nondiabetics.  Metformin users vs. diabetic metformin non-users had a hazard ratio of 0.47.[7]

Experimental Human Evidence

In 55 breast cancer patients randomized to metformin or no drug before surgery,  Ki67 levels (a measure of cellular proliferation) in the tumors dropped in all but 2 metformin patients but remained stable in control patients.[12]  However, a different randomized trial found no effect of preoperative metformin on Ki67 levels.[13]

A meta-analysis of randomized controlled studies where diabetics were given either metformin or a comparator found that cancer incidence was no lower in patients given metformin.[14]  This is a nontrivial concern, given that non-metformin drugs tend to be given to patients with more severe diabetes, meaning that observational studies comparing metformin-treated patients to other diabetics may be biased.

In-Vitro Evidence

Metformin inhibits growth of breast cancer cells and upregulates AMP-kinase activity in those sells; siRNA specific to AMP-kinase (blocking its expression) makes the anti-cancer effect of metformin stop.[3]

Metformin preferentially kills breast cancer stem cells, and prevents their transformation into tumor cells.[4]

Metformin inhibits p53-/-  colon cancer cell lines.[5]  These are usually the hardest type of cancer to treat; cancers with the p53 gene mutated are usually advanced and not responsive to most chemotherapies.

Animal Evidence

Metformin + doxorubicin kills all tumors in mice injected with breast cancer stem cells, while doxorubicin alone cause only a 2-fold decrease in tumor volume and metformin alone has little effect.  Mice remain in remission for 60 days after doxorubicin + metformin, vs. 20 days for doxorubicin alone.[4]

Hamsters fed a high fat diet and a carcinogen got pancreatic cancer 50% of the time; hamsters fed the high fat diet, metformin, and the carcinogen didn’t get cancer.[10]

Mice given ovarian cancer xenographs had about half the total tumor mass when treated with metformin; it also inhibits proliferation, metastasis, and angiogenesis. Metformin + cisplatin  resulted in significantly less proliferation, tumor area, mitotic counts, and vasculature than cisplatin or metformin alone.[11]

Metformin Conclusions

Metformin is definitely simple in its mechanism, and quite cheap. It is also probably upstream, though I don’t know yet how early in the process of cancer development its unusually high energy requirements arise.  It’s not especially decisive, given that it only has a moderate preventative effect and only inhibits growth, rather than killing cancer cells.

We don’t yet have direct evidence of how it works in humans as an adjuvant to chemotherapy or what its long-term effects on non-diabetics are; these seem like obvious experiments to run. Moreover, given its good side-effect profile, it’s plausible that healthy people could take metformin as a cancer preventative.

Fasting

Short-term fasts (<2 days) while taking chemotherapy may make the side effects milder and the effects stronger.  There is very little clinical evidence about this because doctors are understandably concerned about causing excessive weight loss in cancer patients; however, from the information I have available, it appears that short-term fasts followed by eating freely are safe.

In a case study[16] of 10 humans who had fasted voluntarily before and after chemotherapy, patients reported fewer side effects from courses of chemotherapy during which they fasted compared to courses of chemotherapy during which they ate.  They had faster recovery of blood cell and platelet counts during the chemotherapy regimens when they fasted. 

Cancer cells are quicker to die during a period of fasting than healthy cells are; this phenomenon is known as differential stress resistance and has been observed repeatedly in animal and in-vitro studies.

An in-vitro study[15] of tumor cells and RAS-mutated yeast cells found that 48-hour fasts sensitized the cells to chemotherapy; in mice, tumors were less than half the size in fasted mice than fed mice after 34 days and 5 fasting cycles, and mice were able to regain normal weight.

Mice injected with glioma were more responsive to chemotherapy and radiotherapy when they were subjected to 48-hour fasts; by day 28, 85% of the fasting + chemo mice were alive, compared to 40% of the fasting alone and chemo alone mice.  89% of the fasting + radiotherapy mice were alive by day 32, compared to 40% each of the fasting alone and radiotherapy alone mice.[17]

The differential stress resistance response appears to be associated with the effect of fasting on reducing IGF-1, a growth factor which promotes cancer.  Mice injected with metastatic melanoma and treated with doxyrubicin died 40% of the time from the doxorubicin and by 90 days all were dead from either the chemotherapy or metastases; the mice that lacked the ability to produce IGF-1 (mimicking the effect of fasting) survived 60% of the time.[18]

A cohort of Ecuadorian people with IGF deficiency (who are of unusually short stature, due to lack of growth hormone sensitivity) had unusually low rates of cancer; 20% of their unaffected relatives died of cancer but none of the IGF-deficient subjects did, a statistically significant difference.[19]

Conclusions

There’s some kind of rough emerging picture around insulin, glucose levels, and the metabolic syndrome, whereby insulin and growth factors and high blood glucose are associated with cancer growth, and insulin-sensitivity-promoting things like metformin, exercise, and short-term fasts have anti-cancer effects. There are multiple possible causal pathways that seem to point in the same direction. There’s a sort of “antifragile” heuristic here — cancer cells are especially vulnerable in multiple ways to metabolic stress, and messing with their energy supply might be a robust way to attack cancer even though there are surely many undiscovered biochemical pathways. These strategies seem to be more targeted at cancer prevention and growth inhibition than cancer eradication, except for metformin’s surprising effects on advanced cancer cell lines.  As usual, I think the conclusions to draw are “more research here”, not “cancer is cured”, though in this case there are obvious lifestyle choices that people can experiment with. And it seems clear that clinical trials of metformin and fasting during chemotherapy would be useful.

References

[0]Friedenreich, Christine M., and Marla R. Orenstein. “Physical activity and cancer prevention: etiologic evidence and biological mechanisms.” The Journal of nutrition 132.11 (2002): 3456S-3464S.

[1]Evans, Josie MM, et al. “Metformin and reduced risk of cancer in diabetic patients.” Bmj 330.7503 (2005): 1304-1305.

[2]Libby, Gillian, et al. “New Users of Metformin Are at Low Risk of Incident Cancer A cohort study among people with type 2 diabetes.” Diabetes care 32.9 (2009): 1620-1625.

[3]Zakikhani, Mahvash, et al. “Metformin is an AMP kinase–dependent growth inhibitor for breast cancer cells.” Cancer research 66.21 (2006): 10269-10273.

[4]Hirsch, Heather A., et al. “Metformin selectively targets cancer stem cells, and acts together with chemotherapy to block tumor growth and prolong remission.”Cancer research 69.19 (2009): 7507-7511.

[5]Buzzai, Monica, et al. “Systemic treatment with the antidiabetic drug metformin selectively impairs p53-deficient tumor cell growth.” Cancer research 67.14 (2007): 6745-6752.

[6]DeCensi, Andrea, et al. “Metformin and cancer risk in diabetic patients: a systematic review and meta-analysis.” Cancer prevention research 3.11 (2010): 1451-1461.

[7]Lee, Meei-Shyuan, et al. “Type 2 diabetes increases and metformin reduces total, colorectal, liver and pancreatic cancer incidences in Taiwanese: a representative population prospective cohort study of 800,000 individuals.”BMC cancer 11.1 (2011): 20.

[8]Landman, Gijs WD, et al. “Metformin associated with lower cancer mortality in type 2 diabetes ZODIAC-16.” Diabetes care 33.2 (2010): 322-326.

[9]Noto, Hiroshi, et al. “Cancer risk in diabetic patients treated with metformin: a systematic review and meta-analysis.” PloS one 7.3 (2012): e33411.

[10]Schneider, Matthias B., et al. “Prevention of pancreatic cancer induction in hamsters by metformin.” Gastroenterology 120.5 (2001): 1263-1270.

[11]Rattan, Ramandeep, et al. “Metformin suppresses ovarian cancer growth and metastasis with enhancement of cisplatin cytotoxicity in vivo.” Neoplasia 13.5 (2011): 483-IN28.

[12]Hadad, Sirwan, et al. “Evidence for biological effects of metformin in operable breast cancer: a pre-operative, window-of-opportunity, randomized trial.” Breast cancer research and treatment 128.3 (2011): 783-794.

[13]Bonanni, Bernardo, et al. “Dual effect of metformin on breast cancer proliferation in a randomized presurgical trial.” Journal of Clinical Oncology30.21 (2012): 2593-2600.

[14]Stevens, R. J., et al. “Cancer outcomes and all-cause mortality in adults allocated to metformin: systematic review and collaborative meta-analysis of randomised clinical trials.” Diabetologia 55.10 (2012): 2593-2603.

[15] Lee, Changhan, et al. “Fasting cycles retard growth of tumors and sensitize a range of cancer cell types to chemotherapy.” Science translational medicine4.124 (2012): 124ra27-124ra27.

[16]Safdie, Fernando M., et al. “Fasting and cancer treatment in humans: A case series report.” Aging (Albany NY) 1.12 (2009): 988.

[17]Safdie, Fernando, et al. “Fasting enhances the response of glioma to chemo-and radiotherapy.” (2012): e44603.

[18]Lee, Changhan, et al. “Reduced levels of IGF-I mediate differential protection of normal and cancer cells in response to fasting and improve chemotherapeutic index.” Cancer research 70.4 (2010): 1564-1572.

[19]Guevara-Aguirre, Jaime, et al. “Growth hormone receptor deficiency is associated with a major reduction in pro-aging signaling, cancer, and diabetes in humans.” Science translational medicine 3.70 (2011): 70ra13-70ra13.

CAR-T Immunotherapy

Epistemic status: moderate confidence.

CAR-T immunotherapy has a reputation for being the new exciting thing in cancer, and as far as I can tell, this reputation is mostly deserved.

It’s not a single therapy, but a general technique. You graft the monoclonal antibody of your choice onto a T-cell with retroviral vectors; then it can selectively attack any type of cell that has a distinctive antigen.

An advantage of CAR-T cells is that the chimeric antigen receptor need not depend on HLA, so it can overcome the tumor’s ability to downregulate HLA molecules.  CAR-T cells bind directly to the antigen, usually on the surface of the cell.

Early clinical trials have shown really strong responses to CAR-T therapy in leukemia and lymphoma.

CAR-T caused complete remission in two children with refractory acute lymphoblastic leukemia; one relapsed after two months and one remission was ongoing.  (ALL is curable in 80% of children, but prognosis is poor for those with chemotherapy-resistant disease.) The cells were modified with specificity for CD19, a hallmark of B-cells.

LeY-specific CAR-T cells in relapsed acute myeloid leukemia (AML) caused a (temporary) remission in 1 of 4 patients.

CD-19 specific CAR-T cells produced an 88% complete response rate out of 16 patients with relapsed acute lymphoblastic leukemia; there were 10 complete remissions.

5 out of 5 adult patients with relapsed ALL treated with CD19-specific CAR-T cells had complete remissions.

3 out of 11 patients with high-risk neuroblastoma had complete remissions upon treatment with EBV-specific and GD2-specific CAR-T cells.

Of 3 patients with relapsed indolent B-cell lymphoma treated with CD20-specific CAR-T cells, 2 survived progression-free for 12 and 24 months, and 1 had a partial remission and relapsed after 12 months.

Leukemia and lymphoma are “easy mode” for a few reasons. First of all, several types of such cancers have very specific biomarkers. The Philadelphia chromosome  is pretty much unique to the leukemias on which it exists. B-cell lymphoma is restricted to B-cells, and CD19 and CD20 are markers that occur on almost all B-cells and no other cells.  The common solid-tumor cancers (lung, breast, colon, prostate, etc) have no equivalently specific markers. Second of all, blood cancers are easier for drugs to physically access than solid tumors, which produce a hostile “microenvironment” that protects the tumor against attack, especially immune attack.

Challenges facing CAR-T therapy include the cost of engineering T-cells, and poor in-vivo persistence of transferred T-cells.  Second- and third-generation CAR-T therapies involve editing multiple stimulatory domains, since using only one often fails.  Exogenous cytokine administration, especially IL-2, is used to enhance persistence of T-cells.  A challenge especially for solid tumors is transferring T-cells to the site of disease, and resisting the immune-suppressive effects of the tumor microenvironment.  Fever enhances the adherence of T-cells to the tumor microvasculature, so heat therapy may be helpful here.  (Note that fever is also a factor in spontaneous remissions and bacterial cancer therapies.)

Attempts so far in solid tumors include CAR-T cells specific for HER2, VEGF, EGFR, and GD2.  So far, it doesn’t work most of the time, though the GD2 studies in neuroblastoma got some complete remissions. The HER2-sensitive trial caused one death due to the T-cells attacking healthy tissue and causing respiratory failure. Lack of specificity and lack of persistence have been problems, but as of 2015 we’re still waiting for the results of many solid-tumor clinical studies.

CAR-T is “decisive” in some types of leukemia and lymphoma; complete remissions in a majority of patients is a nearly-unheard-of result in the world of cancer. It’s not particularly “simple”, because it can be customized arbitrarily with different antigens, different activating domains, etc.  It’s also only somewhat “upstream” — T-cells appear fairly late in the process of immune response to cancer.

Ultimately, though, CAR-T is only as good as the specificity of the cell surface antigens it uses.  It’s subject to the universal challenge of targeted cancer drugs: different cancers have different biomarkers, no one biomarker appears in a majority of cancers, and cancers change their biomarkers as they advance.

If anti-IgG pans out as a much broader cancer-detection mechanism, it seems that it could in principle be applicable to CAR-T.  Also, combination CAR-T with multiple antigens pattern-matches to something that could improve effectiveness.

CAR-T is not an underappreciated area of research — it’s very actively funded and a vigorous research field.  To the extent that it pans out, which will become clearer when the current round of clinical trials publish results, it’s evidence for the “cancer establishment” doing something right, very much as imatinib was a triumph of “big science” and targeted chemotherapy.

The cynical viewpoint is that, like imatinib and targeted chemotherapies, a single clear-cut triumph can lend credibility to a wide class of drugs that mostly don’t work on more difficult cancers, and that since CAR-T is so mutable, it is especially vulnerable to such “exploitation.”  One way or another, we’ll find out when the solid tumor results finish coming in.

Routing Around the Cancer Biomarker Problem with Antibodies

Epistemic status: fairly low confidence

One of the heuristics I’ve been using in this series is that drugs that rely on tumor-specific biomarkers are not very effective. We’ve seen that most targeted chemotherapies have little or no effect on survival; we’ve seen that immunotherapies that depend on tumor-specific antigens are limited by the tendency of advanced cancers to “escape” immunosurveillance by shedding their antigens.

The “cancer is hard and complex” model accurately predicts this. Cancer is diverse, both between tumor types and across the course of the disease.  Most tumor-specific biomarkers also occur on some healthy tissues, and don’t occur on all tumors.  Most targeted drugs have problems with both sensitivity and specificity — they miss too many cancer cells, and attack too many healthy cells.

But cancer might not be as hard if you can route around the complexity by focusing on vulnerabilities that all or most cancers have in common.

This paper from a team of researchers led by Sanford Simon provides one possible strategy: detecting endogenous antibodies.

Specific autoantibodies to particular tumor-specific antigens have fairly low sensitivity for cancer. For example, “In patients with hepatocellular carcinoma (HCC), probing for a single autoantibody in the serum gives a positive result in 10–20% of patients; the detection increases to 66% with a panel of ten autoantibodies²⁰. While the sensitivity of tumor detection can be increased by using a panel of antibodies over a single antibody²¹, the results are still insufficient for diagnosis in many tumor types.”

Antibodies are part of the adaptive immune response. Also known as immunoglobulins, they are Y-shaped molecules produced by B cells that tag microbes, infected cells, or tumor cells for further attack by other parts of the immune system.

What if, instead of trying to detect a tumor-specific antigen with a targeted drug, you tried to detect all the tumor-specific antigens at once by detecting all the antibodies that the body is already using to identify tumor cells?

That’s what Simon and his team did. They attached a fluorescent chemical to an anti-IgG antibody, which binds to all IgG antibodies (regardless of which antibody they’re selecting for.) The fluorescence was 64x greater in mouse tumor tissue than in normal tissue.

The effect worked across a wide variety of mouse  cancer types: breast cancer, prostate cancer, liver cancer, leukemia, etc.

IgG autoantibodies are abundant in all human, rat, and swine sera, increase with age, and are statistically significantly lower in cancer, Alzheimer’s, and Parkinson’s patients compared to age- and gender-matched controls; they are hypothesized to play a role in clearing the body of debris and damaged or mutated cells.

Gold nanoparticles  mixed with blood serum pick up a “corona” of protein which includes IgG molecules of all types, and the total amount of IgG is higher in cancer than non-cancer patients.  “The test has a 90–95% specificity and 50% sensitivity in detecting early stage prostate cancer, representing a significant improvement over the current PSA test.”

I’ve spoken to Dr. Simon and seen some of his unpublished results, which involved distinguishing tumor from healthy tissue down to the cellular level with fluorescent anti-IgG, in both mice and human tumors of many types.

In a sense, this is an “obvious” idea. If the body produces many kinds of tumor-specific antibodies, each of which selects for some cancers, then measuring the overall level of all antibodies would be a much more robust test that selects more specifically for a wider range of cancers.  It’s essentially just bagging applied to cancer detection.

This is usually presented as a method for detecting cancer, but it could also be a method for treating cancer.  Attaching cytotoxic chemotherapy to an anti-IgG antibody (in place of the fluorescent protein) would concentrate the chemo in the tumor as opposed to the rest of the body, allowing higher doses to be administered safely.

It could also be a guide for better cancer surgery; washing the body cavity with IgG-binding fluorescent protein would make the tumor area light up, helping the surgeon cut precisely where needed and making sure to get adequate margins.

Obviously much more development is needed to identify exactly how precise anti-IgG is on humans.  Since cancers eventually lose antigens as they advance, this can be expected to be less effective on advanced cancers.  However, since cancers lose antigens one at a time as they mutate, an anti-IgG-based therapy that was sensitive to all antigens at once would in principle lose effectiveness later than an immunotherapy based only on a single antigen.

As far as cancer heuristics go, IgG detection is definitely “simple”, it is fairly “upstream”, but it is only moderately “decisive” (we don’t yet have extended survival times or extremely high published precision numbers).  I think it’s potentially important and under-appreciated, however, especially given the very high level of current investment in antibody-based immunotherapies.

Cancer Immunosurveillance Interlude

Epistemic status: summary of standard research + rough thoughts of my own

How exactly does the immune system fight cancer?  And what does that imply for immunotherapy opportunities?

In 1909, Paul Ehrlich proposed the hypothesis that the body protects itself from cancer via immune mechanisms.  Fifty years later, Lewis Thomas and F. Macfarlane Burnet revisited the hypothesis.  Thomas’ argument was evolutionary — he said that complex organisms must develop mechanisms to protect against neoplastic disease as they develop mechanisms mediating homograft rejection.  By contrast, Burnet’s argument was functional; he believed tumor-specific antigens could provoke an immune response. In 1964 the first tumor-specific antigens were observed in mice.  

However, it wasn’t until the 1990s that the immune surveillance hypothesis (that the immune system fights cancer) was widely accepted.  This is because nude mice (mice without thymuses, which have greatly reduced numbers of T cells) don’t have higher rates of cancer than normal mice, either spontaneous or induced by carcinogens. If immune-deficient mice aren’t getting more cancer, went the theory, then the immune system can’t be targeting tumors.  What wasn’t known at the time was that nude mice do have some T-cells, a working innate immune system, and natural killer (NK) cells, which weren’t discovered until 1975.  What really confirmed the immune surveillance hypothesis were other kinds of immunodeficient mice which do have elevated rates of cancer.

The cytokine IFN-gamma has been shown to protect the host against spontaneous, chemically-induced, and transplanted tumors.  Mice lacking the IFN-gamma receptor were 10-20x as sensitive to tumor induction. (STAT1, the famous oncogene, is the transcription factor that mediates most of IFN-gamma’s effects on cells.  Mice with mutations in STAT1 are unable to resist injected tumors.)  IFN-gamma is a signaling molecule involved in both adaptive and innate immunity.  It is the key cytokine that prompts T cells (CD4+) to develop into Th1 cells.  It also promotes NK cell activity, NO synthesis, and much more.

NK cells were discovered in 1975 as a distinct cell type that could kill tumor cells w/o prior sensitization.  NK cells are cytotoxic lymphocytes. They exocytose granules containing perforin, which kill cells by inducing apoptosis.  Perforin, true to its name, punches holes in cell membranes; perforin-deficient mice are 2-3x as likely to produce tumors in response to carcinogens.  Also, NK cell ligands binding to TNF receptor superfamily members on cancer cells induce cytotoxicity. 

NK-deficient mice get more tumors.  Infiltration of tumors with NK cells in humans is a positive prognostic indicator, and lower NK-like cytotoxicity of peripheral blood lymphocytes is predictive of cancer risk.

NKG2DL is an activating receptor on NK cells and some other cells. Its ligands do not occur on healthy tissue. NKG2DL expression is activated by stresses such as heat shock, viral infection, DNA damage, or UV radiation.  NKG2DL ligands have been observed on lots of tumor types.  Cancer cells “shed” these ligands a lot, though, which allows them to evade NK attacks.

MICA and MICB are examples of cellular-stress-related NKG2D ligands.  Tumor cells expressing MICA/B are more vulnerable to NK cells.   MICA/B are found in a high percentage of carcinomas; the only healthy tissue that contains these ligands is gastrointestinal epithelium.

In short, we are now aware of various lines of evidence that the immune system does indeed attack cancers, and that certain kinds of immune deficiency make individuals more susceptible to cancer. (The increased rates of cancers in immunosuppressed individuals such as AIDS patients and transplant recipients are further evidence for the immunosurveillance hypothesis.)

The current theory of the immune response to cancer goes as follows:

1. As the tumor physically expands (causing pressure on surrounding tissues and growing new blood vessels) the innate immune system starts producing inflammation.
2. NK cells and T cells are recruited to the tumor site.
3. T cells and NK cells produce tons of IFN-gamma!  This amplifies the immune response!
4. IFN-gamma activates macrophages
5. macrophages produce IL-2
6. IL-2 stimulates NK cells to produce more IFN-gamma! GOTO 3 and repeat, in a positive feedback loop!
7. IFN-gamma stimulates macrophages and NK cells to do more tumor killing
8. IFN-gamma causes apoptosis and anti-growth processes in the tumor itself
9. Now the adaptive immune response starts; dendritic cells are recruited to the tumor site
10. dendritic cells show tumor antigens to T cells, which home to the tumor
11. tumor-specific T cells kill tumor cells
12. T cells produce even more IFN-gamma! GOTO 3, more positive feedback loop!

Clearly, IFN-gamma is a very big deal here. IFN-gamma is involved in the Th1 (or cellular) immune response, which trades off against the Th2 (humoral) immune response.  There’s a simplistic but suggestive theory that a lot of the diseases of modern aging (heart disease, cancer, diabetes, Alzheimer’s) are associated with a shift in the balance of the immune system towards Th2 and away from Th1 responses; this may be relevant here.

Toll-like receptors, which are expressed on tumor cells and release IL-6, a Th2-promoting cytokine, tend to suppress the immune response to tumors, helping the tumor evade immune surveillance.  Blocking the toll-like receptor slows tumor growth and prolongs survival in mice. This is also consistent with the Th1/Th2 balance hypothesis.

There is a whole zoo of tumor-specific antigens which are more common in tumor cells than in healthy cells and which the immune system can recognize.  Some of these (gp100, NY-ESO-1, p53, HER2, etc) have been used as drug targets.  The problem with this strategy is that, as tumors advance, they evade immune surveillance by losing these distinctive antigens, through a process of natural selection.  It’s not uncommon to lose all HLA class I antigens in many carcinomas.  

Spontaneous remissions of cancers often look immunological in origin, but they are rare. Normally, once a cancer is large enough to observe macroscopically, it only grows or stabilizes, never shrinks; if the immune system could reliably destroy macroscopic solid tumors, you’d see tumors shrinking and growing in size without treatment.  The current theory is that “escape” from immune surveillance happens at a cellular level; cells that present antigens die, cells that don’t survive, and so the cancer shifts over time to become resistant to the immune system.  This suggests that immunotherapies which target specific antigens face similar kinds of strategic considerations to antibiotics; you have to be careful to avoid promoting resistance.  (One consequence of this hypothesis is that giving courses of immunotherapy that are too short in duration could be directly counterproductive.)

The immunology of cancer really is complex and I’ve really only scratched the surface here; what I’m trying to do is to generalize from the standard picture given in the research literature and come to some conclusions as to what types of treatment approaches are and are not likely to be fruitful. My suspicion is that antigen-specific immunotherapies, like growth factor-specific targeted therapies, are not particularly likely to work a priori, despite being popular as drug candidates, for similar reasons; most cancers will have multiple “tricks up their sleeve” and attacking one tumor-specific marker won’t necessarily reach a large proportion of tumor types or produce sustained results.

Dunn, Gavin P., Lloyd J. Old, and Robert D. Schreiber. “The immunobiology of cancer immunosurveillance and immunoediting.” Immunity 21.2 (2004): 137-148.

Waldhauer, Inja, and Alexander Steinle. “NK cells and cancer immunosurveillance.” Oncogene 27.45 (2008): 5932-5943.

Dunn, Gavin P., Lloyd J. Old, and Robert D. Schreiber. “The three Es of cancer immunoediting.” Annu. Rev. Immunol. 22 (2004): 329-360.

Khong, Hung T., and Nicholas P. Restifo. “Natural selection of tumor variants in the generation of “tumor escape” phenotypes.” Nature immunology 3.11 (2002): 999-1005.

Huang, Bo, et al. “Toll-like receptors on tumor cells facilitate evasion of immune surveillance.” Cancer research 65.12 (2005): 5009-5014.

Bacterial Infections and Cancer Remissions

Epistemic status: pretty confident but only making weak claims

In previous posts I’ve talked about how progress on cancer treatment has slowed and how recent targeted chemotherapy drugs are mostly ineffective, and floated some heuristics as to how we might approach cancer research better.  In this and subsequent posts I’ll look at some examples of therapies and research directions that I think are promising. Mostly these aren’t of the form “this is a cure for cancer, go out and take it right now” so much as they are “there might be a cure for cancer around this vicinity, it needs further research, and it seems underappreciated.”  I don’t claim to have an exhaustive list, but I do think I have enough examples to convince a reader that there’s a lot more interesting stuff out there than the conventional “cancer is hard because the low-hanging fruit is gone” story would imply.

In this post, I want to talk about the evidence that bacterial infections sometimes cause complete remissions in cancers.

Antitumor Immunity

Since the 1980s, the scientific consensus has converged on the view that the immune system destroys cancerous cells as they arise. A clinical case of cancer is simply one in which the body fails to fight off the tumor before it becomes large enough to be measurable or cause symptoms.

The current model of antitumor immunity works as follows:

Here’s how antitumor immunity is currently believed[1] to work:

• dendritic cells sample antigens from the tumor
• dendritic cells receive a signal to mature and differentiate
• these activated dendritic cells generate T-cell responses in the lymphatic tissues
• cytotoxic T cells enter the tumor to perform their function

So activating either dendritic cells or T-cells could result in a stronger immune response to cancer. This is the theory behind many experimental immunotherapies, including cancer vaccines and CAR T-cell immunotherapy.[2]

Spontaneous Remission and Regression

Sometimes cancer regresses or disappears by itself, without treatment; very frequently these cases follow a feverish infection.  There have been many anecdotal and historical accounts of such “miraculous” recoveries, including the story of St. Peregrine.[3]

A review [4] of case studies found 237 cases of spontaneous regression in 1900-1965, and 504 cases from 1966-1987.  These occurred in many kinds of solid and hematological cancers. The most common kinds were kidney, neuroblastoma, malignant melanoma, choriocarcinoma, and bladder.  These are not the commonest cancers; lung, colon, and breast cancer were underrepresented among spontaneous regressions.  Another review [5] observed that “the prevalent view regarding the mechanism for spontaneous regression is the involvement of immunological factors in the host,” noting that regressing tumors have been observed to have elevated cytokine counts or elevated levels of cytotoxic lymphocytes.  A 1976 survey [8] concluded, “Spontaneous remission of acute leukemia is associated with bacterial infection and is of short duration, weeks to months. Spontaneous regression of lymphoma or plasma cell dyscrasia is often of substantial duration, months or years, and frequently is associated with viral infections.” Another review article [10] confirms the relationship between bacterial infection and spontaneous remission in leukemia: “In 1950, Shear reported that brief remissions in children with untreated leukemia were observed in about 10% of the patients. Three quarters of these remissions were preceded by an episode of acute infection.”

A case study [6] from 1976 of a patient with malignant melanoma who refused treatment observed a spontaneous remission; there was an inflammatory reaction with lymphocytic infiltrate and increased lymphocyte cytotoxicity over the time course of regression, consistent with an immunological cause.

A case study [7] of acute myeloblastic leukemia found a spontaneous remission; the remission occurred after a severe febrile pneumonia, which was treated with leukocyte transfusions.

A case study [9] of two patients with acute myeloblastic leukemia observed that both had spontaneous remissions after infection and blood transfusions.

A case study [11] of a patient with acute myeloid leukemia observed a spontaneous remission after a severe streptococcal infection.

A case study [12] of a patient with hepatocellular carcinoma observed a spontaneous remission following massive gastrointestinal hemorrhage, shock, and blood transfusion.

A case series [13] of 52 patients observed that postoperative empyema (collection of pus in the body) after pneumoectomy increases five-year survival in lung cancer from 18% to 50%.

Finally, it is a traditional observation that a history of infectious disease anticorrelates with cancer risk.  A literature review [14] found that cancer patients are less likely than healthy patients to have a history of febrile infections.  “Individuals who had never experienced a febrile infectious disease were 2.5–46.2 times more likely to have developed cancer than those who had had febrile infections.”

This body of evidence suggests that the immune response to infectious disease has an antitumor effect.

Coley Toxins

In 1891, surgeon William Coley treated a patient with a sarcoma by injecting Streptococcus pyogenes culture into the tumor, and caused a complete regression and 8-year remission, after a severe erysipelas infection from which the patient almost died. Heat-killed Streptococci were safer, but didn’t have a tumor-shrinking effect.  Adding heat-killed Serratia marrescens to the mixture made it effective again, and caused 60 out of 210 (29%) terminally ill sarcoma patients to have relapse-free survival of more than 10 years.[10]   By comparison, modern 5-year survival rates [23] for soft-tissue sarcoma are 83% for localized sarcoma, 54% for regional sarcoma, and 16% for sarcoma with distant spread. So Coley’s patients may have had better or comparable results to modern patients.

Coley tried at least 13 different vaccine formulations over time, making it difficult to compare results.  “Although Coley, in his numerous publications, seldom gave full details of site, dosage, frequency, or duration of vaccine application, the optimal therapy regimen, with hindsight, seemed to be intratumoral, intramuscular, or intraperitoneal injections over long periods of time.”[10]

Coley selected his patients deliberately to maximize the chance of recovery; he favored sarcoma patients because the bacterial vaccine seemed to work best on them. Cases of spontaneous remission following erysipelas infections were also predominantly soft-tissue sarcomas.[16]

Coley’s preparations, known as “Coley Toxins”, were in use until 1963, when the Estes-Kefauver Act ruled that drugs had to prove safety and efficacy to be FDA-approved.[15]

A retrospective review [17] published in in Alternative Therapies in Health and Medicine compared 128 Coley cases from 1890 to 1960 with 1675 controls from SEER who received a cancer diagnosis in 1983. Patients were matched by age, site, stage, and radiation treatment status.  10-year survival rate was not significantly different for Coley’s patients vs. modern controls, which suggests that Coley toxins were of comparable efficacy to chemotherapy.

A 1971 retrospective study[18] of 47 patients with reticulum sarcoma of the bone, treated with Coley toxins before 1956, found a five-year survival rate of 64%.  22 cases (48%) achieved permanent results.  With surgery or radiation therapy alone, five-year survival rates were 32-38%.  As of 2015, reticulosarcoma, also known as lymphoma of the bone, has 89% five-year survival in stage I if treated with chemo + radiotherapy. But bone lymphoma is also often a sign of metastatic disease, which would have lower survival rates. 16 of the 47 cases in the 1971 study were metastatic.  The failures of Coley toxins tended to be briefer courses rather than longer ones, and intramuscular rather than intratumoral or intravenous.

More recent attempts to replicate the effectiveness of Coley toxins (also known as mixed bacterial vaccine or MBV) have been less successful. A Chinese study[20] in 1991 of 86 patients with hepatocellular carcinoma were randomized to either MBV or control; there was a nonsignificant trend towards better survival in the MBV group. An uncontrolled study [21] of MBV in 12 patients with refractory malignancies found one partial response, and a “dramatic improvement in performance status and disease stabilization” in a patient with AIDS and Kaposi’s sarcoma.  An uncontrolled German study[22] of 12 patients with NY-ESO-1 expressing tumors (6 melanoma, 2 sarcoma, 2 prostate cancer, 1 with head and neck cancer, 1 with bladder cancer) found one partial response after treatment with MBV.

Coley toxins are popular in alt-med circles, and the effects haven’t been replicated in a modern experiment. However, the historical data does seem to show dramatic effects, and it is mechanistically plausible that bacterial vaccines stimulate the immune system.  A point in defense of Coley toxins is that the few existing modern trials don’t copy what Coley did (repeated, intratumoral injections, calibrated to produce fever, with patients selected for sarcoma).  A controlled trial of Coley toxins under those conditions could be extremely valuable.

Endotoxin and Tumor Necrosis Factor

Endotoxin, also known as lipopolysaccharide, is a molecule found on the membrane of Gram-negative bacteria, which elicits a strong immune response in the host.  Endotoxin causes the release of inflammatory cytokines, fever, and in extreme cases septic shock.  It also has antitumor effects, strengthening the case that bacterial infection can cause cancer regression.

A study [24] of intravenously administered endotoxin found that it caused partial responses in 2 out of 18 patients with colorectal cancer.  Intravenous endotoxin caused one complete remission out of 37 patients [25] with colorectal and non-small-cell lung cancer.

Parenteral injection of bacterial endotoxin in mice reliably [26] causes necrosis of experimental tumors.  Spindle cell sarcoma (SA-1) and fibrosarcoma (Meth A) regress completely, while CaD2 (breast carcinoma) and BP3 (another kind of fibrosarcoma) grow unchanged.  Necrosis occurred in all tumors. Endotoxin does not cause tumor regression in T-cell deficient mice.  In mice whose tumors regressed, subsequent injection with cells from the same tumor did not grow, suggesting that sensitized T-cells are the cause of the tumor resistance.

Environmental exposure to endotoxin in Chinese workers in the textile industry is inversely associated with lung cancer risk (HR = 0.60, p = 0.002)[27].

The anti-tumor activity of endotoxin appears to be associated with tumor necrosis factor, or TNF.  In 1975 [28] it was observed that Bacillus Calmette-Guerin-infected mice treated with endotoxin produced a substance, dubbed TNF, which was as effective as endotoxin itself in causing regression of transplanted sarcomas in mice.

TNF is too dangerous to give patients intravenously, but it is effective on sarcomas when administered locally when combined with cytotoxic chemotherapy.  High-dose TNF-alpha administered[29] in isolation perfusion of the limbs of 23 patients with metastatic melanoma or soft-tissue sarcoma found 21 complete responses and 2 partial responses.  In 186 patients [30]with locally advanced soft-tissue sarcomas, isolated limb perfusion with tumor necrosis factor caused complete response in 18%, partial response in 57%, and limb salvage in 82%.

There certainly appears to be a TNF-mediated anti-tumor response, and it is suggestive (and in line with the evidence about spontaneous remissions and Coley toxins) that this effect is associated with fever and especially strong against sarcomas.

Conclusions

I don’t believe there’s a single well-established bacterial cancer treatment right now, but it does seem clear that bacterial infections, particularly febrile infections, and derived substances like endotoxin and TNF, can often cause cancer remissions, especially in sarcomas and some advanced cancers.  Additional “protocol engineering” followed by randomized trials might yield a reliable bacterial therapy.  In the contexts where they are effective, bacterial and bacterial-derived treatments seem to cause meaningful increases in survival time, whereas most targeted chemotherapies do not.

References

[1]Mellman, Ira, George Coukos, and Glenn Dranoff. “Cancer immunotherapy comes of age.” Nature 480.7378 (2011): 480-489.

[2]http://www.cancer.gov/about-cancer/treatment/research/car-t-cells

[3]https://en.wikipedia.org/wiki/Peregrine_Laziosi

[4]Challis, G. B., and H. J. Stam. “The spontaneous regression of cancer: a review of cases from 1900 to 1987.” Acta Oncologica 29.5 (1990): 545-550.

[5]Papac, Rose J. “Spontaneous regression of cancer.” Cancer treatment reviews22.6 (1996): 395-423.

[6]Bodurtha, A. J., et al. “A clinical, histologic, and immunologic study of a case of metastatic malignant melanoma undergoing spontaneous remission.” Cancer37.2 (1976): 735-742.

[7]Ifrah, Norbert, et al. “Spontaneous remission in adult acute leukemia.” Cancer56.5 (1985): 1187-1190.

[8]Wiernik, Peter H. “Spontaneous regression of hematologic cancers.” National Cancer Institute Monograph 44 (1976): 35-38.

[9]Mitterbauer, M., et al. “Spontaneous remission of acute myeloid leukemia after infection and blood transfusion associated with hypergammaglobulinaemia.”Annals of hematology 73.4 (1996): 189-193.

[10]Hobohm, Uwe. “Fever and cancer in perspective.” Cancer Immunology, Immunotherapy 50.8 (2001): 391-396.

[11] Maywald, O., et al. “Spontaneous remission in adult acute myeloid leukemia in association with systemic bacterial infection—case report and review of the literature.” Annals of hematology 83.3 (2004): 189-194.

[12]Tocci, G., et al. “Spontaneous remission of hepatocellular carcinoma after massive gastrointestinal haemorrhage.” Bmj 300.6725 (1990): 641-642.

[13]Ruckdeschel, John C., et al. “Postoperative empyema improves survival in lung cancer: documentation and analysis of a natural experiment.” New England Journal of Medicine 287.20 (1972): 1013-1017.

[14] Kleef, Ralf, et al. “Fever, cancer incidence and spontaneous remissions.”Neuroimmunomodulation 9.2 (2001): 55-64.

[15]http://www.cancerresearch.org/news-publications/our-blog/april-2015/whatever-happened-to-coleys-toxins

[16]Wiemann, Bernadette, and Charlie O. Starnes. “Coley’s toxins, tumor necrosis factor and cancer research: a historical perspective.” Pharmacology & therapeutics 64.3 (1994): 529-564.

[17]Richardson, Mary Ann, et al. “Coley toxins immunotherapy: a retrospective review.” Alternative therapies in health and medicine 5.3 (1999): 42.

[18]Miller, Theodore R., and Jesse T. Nicholson. “End results in reticulum cell sarcoma of bone treated by bacterial toxin therapy alone or combined with surgery and/or radiotherapy (47 cases) or with concurrent infection (5 cases).”Cancer 27.3 (1971): 524-548.

[19]Jamshidi, Khodamorad, et al. “Stage IE Primary Bone Lymphoma: Limb Salvage for Local Recurrence.” Archives of bone and joint surgery 3.1 (2015): 39.

[20]Tang, Zhao You, et al. “Preliminary result of mixed bacterial vaccine as adjuvant treatment of hepatocellular carcinoma.” Medical oncology and tumor pharmacotherapy 8.1 (1991): 23-28.

[21]Vas, H. Francis Ha, et al. “Clinical results and immunologic effects of a mixed bacterial vaccine in cancer patients.” Medical oncology and tumor pharmacotherapy 10.4 (1993): 145-158.

[22]Karbach, Julia, et al. “Phase I clinical trial of mixed bacterial vaccine (Coley’s toxins) in patients with NY-ESO-1 expressing cancers: immunological effects and clinical activity.” Clinical Cancer Research 18.19 (2012): 5449-5459.

[23]http://www.cancer.org/cancer/sarcoma-adultsofttissuecancer/detailedguide/sarcoma-adult-soft-tissue-cancer-survival-rates

[24]Engelhardt, Rupert, Andreas Mackensen, and Chris Galanos. “Phase I trial of intravenously administered endotoxin (Salmonella abortus equi) in cancer patients.” Cancer research 51.10 (1991): 2524-2530.

[25]Otto, F., et al. “Phase II trial of intravenous endotoxin in patients with colorectal and non-small cell lung cancer.” European Journal of Cancer 32.10 (1996): 1712-1718.

[26]Berendt, MICHAEL J., ROBERT J. North, and DAVID P. Kirstein. “The immunological basis of endotoxin-induced tumor regression. Requirement for T-cell-mediated immunity.” The Journal of experimental medicine 148.6 (1978): 1550-1559.

[27]Astrakianakis, George, et al. “Lung cancer risk among female textile workers exposed to endotoxin.” Journal of the National Cancer Institute 99.5 (2007): 357-364.

[28]Carswell, E. A., et al. “An endotoxin-induced serum factor that causes necrosis of tumors.” Proceedings of the National Academy of Sciences 72.9 (1975): 3666-3670.

[29]Liénard, Danielle, et al. “High-dose recombinant tumor necrosis factor alpha in combination with interferon gamma and melphalan in isolation perfusion of the limbs for melanoma and sarcoma.” Journal of clinical oncology 10.1 (1992): 52-60.

[30]Eggermont, A. M., et al. “Isolated limb perfusion with tumor necrosis factor and melphalan for limb salvage in 186 patients with locally advanced soft tissue extremity sarcomas. The cumulative multicenter European experience.” Annals of surgery 224.6 (1996): 756.

A note on protocols

Epistemic status: speculative

One thing that stands out about the history of chemotherapy is that what made it broadly effective in leukemia and lymphoma were not drugs but protocols.  Cytotoxic chemo drugs in the 1940’s-60’s had real anti-tumor effects but short-lived remissions until clinicians began administering chemo for longer periods and with combinations of drugs. 

Until working protocols had been set up, chemotherapy was highly controversial.  “As Alfred Gellhorn recently recounted to the authors, the otherwise great clinician Loeb, a giant in the field at the time, had a blind spot when it came to caring for cancer patients and testing chemotherapy. He was fond of saying to Gellhorn, rather openly, “Alfred, you belong to the lunatic fringe.”  This “lunatic fringe” of early chemotherapists persisted in trying different protocols until they got success, despite a heavy death toll.

I’m not sure if someone has made this distinction before, but there seems to be a difference between the “discovery phase” when you observe that some treatment has a desirable property (e.g. a drug has anti-tumor activity) and the “engineering phase” when you figure out how to optimize delivery of that treatment.

In the tech industry, the conventional wisdom is that you need rapid iteration for the “engineering phase” of optimizing the performance of something that already sort of works.

The problem is that rapid iteration on human patients is hard to do, and more so today than in the past.

Rapid iteration is also not particularly suited to the structure of controlled trials.  Trying lots of relatively small changes is harder at large scale and with formal standards of experimental design. It’s more the sort of thing that makes sense for case series.  But it takes a lot of independence on the part of researcher-clinicians, and I suspect that it’s not done enough.