Category Archives: Medicine in general

Old paradigms die hard

A statement in a recent Nature editorial [ vol. 554 pp. 308 – 309 ’18 ] had me thinking that a real paradigm shift in our understanding of cancer was under way, but in fact it was an out of date paradigm that tripped up the editorialist.  Since breast cancer is likely to affect us individually or someone we know, it’s worth looking at this paper.

Ductal Carcinoma In Situ (DCIS) of the breast, is breast cancer confined to one of the ducts in the breast bringing milk to the nipple.  If it stayed there forever it would be harmless, like a benign mole on the skin. Unfortunately ‘up to’ 40% of DCIS invades the lining of the duct and the soft tissue of the breast becoming Invasive Ductal Carcinoma (IDC) where it is not harmless at all.  There is currently no way to tell which DCIS will stay quiet so everyone gets treated.

A heroic paper in cell (vol. 172 pp, 205 – 217 ’18 ) used the highest of high technology to study the question.  First they used Laser Capture Microdissection to separate a selected cell from its neighbors by tracing a laser beam around the cell.  Then they used laser catapulting in which energy from an ultraviolet laser propels the microdissected cell into a collection tube.  Then they performed exon sequencing on the collected cells (e.g. they sequenced the parts of the gene coding for protein), comparing cells which were DCIS from IDCs.  Some 1,293 cells from 10 patients were studied.

There was an average of 23 mutations/patient.  “The transition from DCIS to IDC was not associated with a notable increase in the number of mutations.”  “The authors’ main finding is the remarkable genetic similarity of a patient’s tumor cells in these two distinct states”


I thought mutations caused cancer and that the more you had the worse the cancer.  Not so in this paper. A paradigm shift indeed.

What’s wrong with this thinking?  Think a bit before reading further.

If you are old enough, you may remember statements that we were 98% chimps based on our genome (or at least what was known of it at the time).  This is because the sequence of the amino acids in our 20,000 or so proteins varies only by 2% from that of the chimp.

That proves it.  Except that it doesn’t.  Amazingly enough, the amount of all 3,200,000,000 positions of our genome coding for protein is under 2%.  So 98% of or genome does NOT code for protein.  It contains the code to determine when, for how long, and where each gene is made into messenger RNA which is then made into protein.

An analogy may help.

This is like saying Monticello and Independence Hall are just the same because they’re both made out of bricks. One could chemically identify Monticello bricks as coming from the Virginia piedmont, and Independence Hall bricks coming from the red clay of New Jersey, but the real difference between the buildings is the plan.

It’s not the proteins, but where and when and how much of them are made. The control for this (plan if you will) lies outside the genes for the proteins themselves, in the rest of the genome (remember only 2% of the genome codes for the amino acids making up our 20,000 or so protein genes). The control elements have as much right to be called genes, as the parts of the genome coding for amino acids. Granted, it’s easier to study genes coding for proteins, because we’ve identified them and know so much about them. It’s like the drunk looking for his keys under the lamppost because that’s where the light is.

On this point it would be very worthwhile to look beyond the genes mutated in both sets of tumors, sequencing their promotors and enhancers.  I think it would likely show profound differences.

No further posts for a while.  We’re going to visit a new grandson, 3 days old, whose parents apparently lack the creativity to name him.



Cytocapsular tubes

“Extraordinary claims require extraordinary evidence”  Carl Sagan.  That goes in spades for a recent PNAS article vol. 115 pp. E1137 – E1146 2018 —

Start by looking at the following 3 videos




Unfortunately, to get to them, it appears that you must be a PNAS subscriber, so I’ll tell you what they show.

First, some background. Cell culture usually involves putting them into a Petri dish, something inherently two dimensional, but most cells in our body live in a 3 dimensional environment. So this work implanted Human Mammary Epithelial Cells (HMECs) into a 3 dimensional matrix of Matrigel (an extracellular matrix surrogate secreted by mouse sarcoma cells, containing, laminin, nidogen, collagen and heparan sulfate proteoglycans) Matrigel also contains the growth factors Transforming Growth Factor Beta (TGFbeta) and Epidermal Growth Factor (EGF), both of which prevent differentiation and promote proliferation. The 3d Matrigel matrix is softer and spongier than the hard surface of a Petri dish.

The behavior of these cells in the Matrigel is completely different than that usually seen. In fact no one has ever seen anything like it before, which is why, if possible you must look at the 3 movies the paper supplies in the supplementary material (referenced above).

The cells move around, but nowhere to be seen are the lamellipodia or the filopodia seen in 2 dimensional cell culture.

In the first movie a small cell repeatedly generates and retracts multiple membranous protrusions called cytocapsues (some larger than the cell itself) which the cell sometimes enters.

The second has multiple cells within the tubes formed by the cytocapsules (cytocapsular tubes) migrating within them. The cells drag the tubes through the matrix, without breaking the tube or allowing another tube to merge with it.

If replicated, this work has bearing on embryology, normal organ function and cancer metastasis.

No one has ever seen anything like this. Why not? The authors say that ‘only when the polymerization, density and viscoelasticity of the Matrigel is tightly controlled are the tubes seen. Unlike secreted extracellular vesicles, cells get inside the cytocapsular tubes. The tubes themselves interconnect and form networks. The tubes degrade and decompose without cells inside them.

They note that polymerized actin (microfilaments) are present under the tube membranes.

Even though the membranes are mostly lipids, proteins are required, and eIF4E levels are elevated. Inhibiting it suppresses cytocapsular tube generation.

It’s worth repeating Sagan – “Extraordinary claims require extraordinary evidence” Stay tuned

It’s probably too good to be true

SR9009 and SR9011 are drugs which selectively kill cancer cells by an entirely new mechanism.  They mess with DNA but don’t mutate it. [ Nature vol. 553 pp. 351 – 355 ’18 ] has the details.

First a bit of background.  How do the classic hormones (estrogen, androgen, thyroid, adrenal steroids) do what they do?  Clearly they change the expression of many many genes as any post-pubertal woman will attest.  They bind to proteins called nuclear hormone receptors, changing their shape so they can bind to DNA and change gene expression.   We have 48 of them in our genome.  For a long time we didn’t know what the natural ligands of many actually were.  These were called orphan nuclear hormone receptors.  I’m not sure how many orphans are left.


SR9009 and SR9011 bind to REV-ERBalpha and REV-ERBbeta which are nuclear hormone receptors. They are agonists (e.g. they cause SR9009 and 11 to do what they do)  Their natural ligand is heme (which isn’t a hormone) and they are involved in the circadian clock.   However they also act as repressors of processes involved in tumorigenesis, including metabolism, proliferation and inflammation.

So the authors threw the agonists at a variety of tumor cells (brain cancer, leukaemia, breast cancer, colon cancer and melanoma) and watched them commit suicide (apoptosis).  They had no effect on normal cells !

How do they work?  There is only speculation at this point.  It is known that SR90xx’s inhibit autophagy, something cancer cells depend on for nourishment.  Normal cells only use autophagy under starvation conditions. They also repress several lipogenic enzymes (fatty acid synthase etc. etc) and cancer cells are said to be dependent on de novo lipogenesis (if they want to proliferate, they got to make a lot of membrane).

It’s almost too good to be true.  Stay tuned.

So much work, so little progress

Two years ago, I found going to a memorial service for a friend and classmate who died of Alzheimer’s curiously uplifting  (see the link at the end). The disease is far from ignored. A monster review in Neuron vol. 97 pp. 32 – 58 ’18 —  contained references to over 400 research articles half of them published since January 2013.

Still I found it quite depressing.  Tons of work and tons findings, and yet no coherent path to the cause (or causes); something absolutely necessary for a rational treatment, unless we somehow stumble into a therapy.

In a way it’s like cancer.  The cancer genome atlas intensively studied the genome of various cancers, looking for ‘the’ or ‘the set of’ causative mutations.  They found way too much.  The average colon and breast cancer had an average of 93 mutated genes, of which 11 were thought to be cancer promoting.  Not only that, but the same 11 were not consistent from tumor to tumor.

So it is with this epic review.  Which of the myriad findings described are causative of the disease and which are responses of the nervous system to the ’cause’ (or causes).

In the review the authors posit that Alzheimer’s disease is due to failure of ‘homeostatic systems’ that maintain a ‘set point’ of neuronal firing.  Unfortunately what is measured to determine the set point isn’t known. This seems to be an example of redefining a question into an answer.  Clearly if you juice up neuronal firing rates by stimulation they come back down, or if you inhibit them, they come back up.  So you can operationally define set point without defining it mechanistically.   It must be due to some sort of feedback on whatever it is that is sensing ‘the set point’ , but what is it that is being sensed?

The following is from an earlier post but is quite relevant to homeostasis and set points.

The whole notion of control in the presence of feedback is far from clear cut.  Here’s the story of the first inklings of feedback in endocrinology.  I watched it happen.

Endocrinology was pretty simple in med school back in the 60s. All the target endocrine glands (ovary, adrenal, thyroid, etc.) were controlled by the pituitary; a gland about the size of a marble sitting an inch or so directly behind the bridge of your nose. The pituitary released a variety of hormones into the blood (one or more for each target gland) telling the target glands to secrete, and secrete they did. That’s why the pituitary was called the master gland back then.  The master gland ruled.

Things became a bit more complicated when it was found that a small (4 grams or so out of 1500) part of the brain called the hypothalamus sitting just above the pituitary was really in control, telling the pituitary what and when to secrete. Subsequently it was found that the hormones secreted by the target glands (thyroid, ovary, etc.) were getting into the hypothalamus and altering its effects on the pituitary. Estrogen is one example. Any notion of simple control vanished into an ambiguous miasma of setpoints, influences and equilibria. Goodbye linearity and simple notions of causation.

As soon as feedback (or simultaneous influence) enters the picture it becomes like the three body problem in physics, where 3 objects influence each other’s motion at the same time by the gravitational force. As John Gribbin (former science writer at Natureand now prolific author) said in his book ‘Deep Simplicity’, “It’s important to appreciate, though, that the lack of solutions to the three-body problem is not caused by our human deficiencies as mathematicians; it is built into the laws of mathematics.” The physics problem is actually much easier than endocrinology, because we know the exact strength and form of the gravitational force.

Body Mass Index (BMI): mine, yours, and Trump’s

The ‘investigative press’ is quite concerned about President Trump’s height.  If he is 6 foot 3 and 239 pounds, he is overweight but not obese, if he is 6 foot 2 he is obese.  All this is a matter of definition by a single number — the body mass index (BMI).

So let’s all calm down and find out what ours actually is.  There is a website which will do it for you. Here’s the link — — have at it. You can use pounds feet and inches as well as kilograms and meters.

The current definition of obese is a BMI over 30, overweight between 25 and 30, and normal weight under 25.

Who cares?  Well, you should if BMI’s correlate with mortality and they do.

A great paper 5 years ago by Katherine Flegal analyzed nearly 3 million people with 270, 000 deaths reported in a variety of studies —

The problem is that the lowest mortality didn’t occur in those with normal weight (BMI < 25) but was lowest in the overweight group — not by much (6%), and second lowest in the mildly obese (BMI 30 – 35), over 35 it was 20% higher.

Naturally this did not sit well people who'd staked their research careers on telling people to lose weight.  There is a truly hilarious article describing a meeting at Harvard discussing the paper.  Here's a link   It's worth reading in its entirety, particularly for a graph it contains.

One study by a Harvard guy removed 900,000 people from the study leading to the following great comment — “It's hard to argue with data,” says Robert Eckel, an endocrinologist at University of Colorado in Denver. “We're scientists. We pay attention to data, we don't try to un-explain them.”

The Nature paper contains a terrific graph from the following paper — Source: Childers, D.K. & Allison, D.B. Int. J. obesity 34, 1231–1238 (2010).

Look at it carefully.  Mortality vs. BMI is plotted in several curves one for people between 20 – 30, one for 30 – 40, etc. etc.  Under 50 the best BMI to have in terms of mortality is under 25, but over 50 it rises, so that at 70 the low point is around 27 (in the overweight range) and not far from Trump at 6' 3" (29.9) or even at 6' 2" (30.7).

In a way this data fits with the fact that for a long time Americans were getting fatter and fatter, yet living longer and longer.  For details see —

Why should the best BMI for you to have rise after age 50?  I've not seen this explanation anywhere else.

The BMI is far from perfect, but to calculate it all you need are two simple measurements that anyone can make — height and weight. It doesn't rely on what people remember.  However the calculation is not a simple ratio of weight divided by height but weight divided by height squared.

People lose height as they age, so the BMI is quite sensitive to it (remember the denominator has height squared).  Well as a high school basketball player my height was 6′ 1”+, now (at age 75) its 6’0″ (God knows what it is several years later). So even with constant weight my BMI goes up.

Well it’s time to do the calculation to see what a fairly common shrinkage from 73.5 inches to 72 would to to the BMI (at a constant weight). Surprisingly it is not trivial — (72/73.5) * (72/73.5) = .9596. So the divisor is 4% less meaning the BMI is 4% more, which is almost exactly what the low point on the curve does with each passing decade after 50 ! ! ! This might even be an original observation, and it would explain a lot.

As long as I’m on the subject of the ‘investigative press’  here is how they glossed over Hillary’s fainting spell during the presidential campaign, calling it a stumble.  Remarkable discipline that they all used the same word.  So take their worries about Trump’s weight with a grain of salt.

“Like the Michigan poll I started out with, most of the latest campaign surveys were carried out during last weekend and earlier this week, when the news was dominated by Clinton’s stumble outside Ground Zero, which prompted the campaign to reveal that she had pneumonia.” John Cassiday New Yorker

“For Orient—and the many media organizations that have recently been circulating her work—Clinton’s stumble looked like proof that they were right.” Wired —

The Boston Globe had a similar echo of the meme that all Hillary did when leaving the 9/11 ceremony was stumble.

As Richard Pryor famously said when his wife caught him with another woman. He denies anything is going on, and asks his wife, “Who you gonna believe, me or your lying eyes?”

See for yourself —


What are prions for?

Prions existed in yeast billions of years before humanity came on the scene. Why are they still there? What are they for?  Immediately we are back in the Aristotelian world of teleology, where everything had a reason for existence and a purpose.  Teleology is simply impossible to avoid in biology. “Nothing in Biology Makes Sense Except in the Light of Evolution” is a famous quote from the magnificently named Theodosius Dobzhansky, which clothes naked teleology with respectable scientific garments.

Here’s an example of this sort of thing from back in the day.  When I was back in the Denver VA as a neurology resident dealing with the complications of immunosuppressants in Starzl’s early work on transplantation, we wondered what on earth the transplantation antigens were for.  All we knew then, is that they were important in transplant rejection. Surely they were not there to prevent cells of the same or another species from finding a new home in us.  Only later did we figure out that they were involved in antigen presentation.

A fascinating article from the first Science of the new year — describes how the yeast organism might be using one of them (Sup35) — e.g. what the prion domains are for.  Normally the Sup35 protein functions to terminate messenger RNA (mRNA) translation into protein. However the first 123 amino acids of Sup35 can aggregate forming amyloid fibrils.  It contains a series of 9 amino acid repeats with consensus sequence PQGGYQQYN (single letter amino acid code — which is similar to the human prion protein repeats (PHGGGWGQ).

This work showed that under a variety of stesses (energy depletion, lowering of intracellular pH) Sup35 doesn’t form amyloid-like prions, but something rather different — liquidlike spherical condensates, which subsequently solidify to form a protein gel.  Next to the prion domain is a very acidic region, important in formation of the condensate.  Low pH is seen in energy depletion, and protonates the acidic amino acids in the acidic region leading to condensate formation.   A mutated Sup35 containing only the prion domain and the acidic region will form the condensates as well in a pH dependent manner.  The condensates are far from irreversible (like prions) as they quickly disappear when the pH is raised.

If you take out the prion domain from Sup35, the catalytic region (a GTPase) in the carboxy terminal part forms irreversible aggregates — so the prion domain is in some way preventing this.

So basically the two other parts of Sup35 function to protect the business end of Sup35 from being totally put out of commission by irreversible aggregation.

The authors found that yeast cells containing Sup35 lacking the prion domain, after recovering from stress, showed impaired translational activity and a growth defect presumably because there was less functional Sup35 around. This may be what the prion domain is doing.

My guess is that the aggregation of Sup35 into actual prions has a function in yeast that we just haven’t figured out yet.

It will be interesting to see if other yeast prions (there are many) show the similar behavior (condensate formation under stress).

Are the inclusions found in neurologic disease attempts at defense rather then the cause?

Thinking about pathologic changes in neurologic disease has been simplistic in the extreme.  Intially both senile plaques and neurofibrillary tangles were assumed to be causative for Alzheimer’s.  However there are 3 possible explanations for any microscopic change seen in any disease.  The first is that they are causative (the initial assumption).  The second is that they are a pile of spent bullets, which the neuron uses to defend itself against the real killer.  The third is they are tombstones, the final emanations of a dying cell.

A fascinating recent paper [ Neuron vol. 97 pp. 3 – 4, 108 – 124 ’18 ] gives strong evidence that some inclusions can be defensive rather than toxic.  It contains the following;

“In these studies, we found that formation of large inclusions was correlated with protection from a-synuclein toxicity”

The paper is likely to be a landmark because it ties two neurologic diseases (Parkinsonism and Alzheimer’s) together by showing that they may due to toxicity produced by single mechanism — inhibition of mitochondrial function.

Basically, the paper says that overproduction of alpha synuclein (the major component of the Lewy body inclusion of Parkinsonism) and tau (the major component of the neurofibrillary tangle of Alzheimer’s disease) produce death and destruction by interfering with mitochondria.  The mechanism is mislocalization of a protein called Drp1 which is important in mitochondrial function (it’s required for mitochondrial fission).

Actin isn’t just found in muscle, but is part of the cytoskeleton of every cell.  Alpha-synuclein is held to alter actin dynamics by binding to another protein called spectrin (which also binds to actin).  The net effect is to mislocalize Drp1 so it doesn’t bind to mitochondria where it is needed.  It isn’t clear to me from reading the paper, just where the Drp1 actually goes.

In any event overexpressing spectrin causes the alpha-synuclein to bind to it forming inclusions and protecting the cells.

There is a similar mechanism proposed for tau, and co-expressing alpha synuclein with Tau significantly enhances the toxicity of both models of tau toxicity which implies that they work by a common mechanism.

Grains of salt are required because the organism used for the model is the humble fruitfly (Drosophila).

Not a great way to end 2017

Not a great way to end 2017

2017 ended with a rejection of the following letter to PNAS.

As a clinical neurologist with a long standing interest in muscular dystrophy(1), I was referred many patients who turned out to have chronic fatigue syndrome (CFS) . Medicine, then and now, has no effective treatment for CFS.

A paper (2) cited In an excellent review of cellular senescence (3) was able to correlate an intracellular marker of senescence (p16^INK4a) with the degree of fatigue experienced by patients undergoing chemotherapy for breast cancer. Chemotherapy induces cellular senescence, and the fatigue was thought to come from the various cytokines secreted by senescent cells (Senescence Associated Secretory Phenotype—SASP) It seems logical to me to test CFS patients for p16^INK4a (4).
I suggested this to the senior author; however, he was nominated as head of the National Cancer Institute just 9 days later. There the matter rested until the paper of Montoya et al. (5) appeared in July. I looked up the 74 individual elements of the SASP and found that 9 were among the 17 cytokines whose levels correlated with the degree of fatigue in CFS. However, this is not statistically significant as Montoya looked at 51 cytokines altogether.

In October, an article(6) on the possibility of killing senescent cells to prevent aging contained a statement that Judith Campisi’s group (which has done much of the work on SASP) had identified “hundreds of proteins involved in SASPs”. (These results have not yet been published.) It is certainly possible that many more of Montoya’s 17 cytokines are among them.

If this is the case, a rational therapy for CFS is immediately apparent; namely, the senolytics, a class of drugs which kills senescent cells. A few senolytics are currently available clinically and many more are under development as a way to attack the aging process (6).

If Montoya still has cells from the patients in the study, measuring p16^INK4a could prove or disprove the idea. However, any oncology service could do the test. If the idea proves correct, then there would be a way to treat the debilitating fatigue of both chemotherapy and CFS—not to mention the many more medical conditions in which severe fatigue is found.
Chemotherapy is a systemic process, producing senescent cells everywhere, which is why DeMaria (2) was able to use circulating blood cells to measure p16^INK4a. It is possible that the senescent cells producing SASP in CFS are confined to one tissue; in which case testing blood for p16^INK4a would fail. (That would be similar to pheochromocytoma cells, in which a few localized cells produce major systemic effects.)

Although senolytics might provide symptomatic treatment (something worthwhile having since medicine presently has nothing for the CFS patient), we’d still be in the dark about what initially caused the cells to become senescent. But this would be research well worth pursuing.

Anyone intrigued by the idea should feel free to go ahead and test it. I am a retired neurologist with no academic affiliation, lacking the means to test it.

1 Robinson, L (1979) Split genes and musclar dystrophy. Muscle Nerve 2: 458 – 464

2. He S, Sharpless N (2017) Senescence in Health and Disease. Cell 170: 1000 – 1011

3. Demaria M, et al. (2014) Cellular senescence promotes adverse effects of chemotherapy and cancer relapse. Cancer Discov. 7: 165 – 176


5. Montoya JG, et al., (2017) Cytokine signature associated with disease severity in chronic fatigue syndrome patients, Proc Natl Acad Sci USA 114: E7150-E7158

6. Scudellari M, (2017) To stay young, kill zombie cells Nature 551: 448 – 450

Why drug development is hard #30 — more new interactions we had no idea existed

We’re full of proteins which bind RNA wrangling it into a desired conformation.  The ribosome (whose enzymatic business end is pure RNA) has a mere 80 proteins doing this.  Its mass is 4,300,000 times that of a hydrogen atom.  However the idea that RNA could return the favor was pretty much unheard of until [ Science vol. 358 pp. 993 – 994, 1051 – 1055 ’17 — ].

As is often the case, viruses and the RNA world continue to instruct us.  In order to survive, some viruses induce cells to express a long (2,200+ nucleotides) nonCoding (for protein that is) RNA called lncRNA-ACOD1.   It binds to a protein enzyme (called GOT2, for Glutamic acid OxaloAcetic Transaminase 2) increasing its catalytic efficiency.  This shifts cellular metabolism around making it more favorable for virus proliferation, as GOT2 is found in mitochondria being used to replenish tricarboxylic cycle intermediates — e.g. making more energy available to the virus.

lncRNA-ACOD1 is induced by a variety of viruses, most importantly influenza virus in man, and vaccinia, herpes simplex 1, vesicular stomatitis virus in mice.  Exactly how viruses induce it isn’t clear, but the transcription factor NFkappaB is involved.

Viruses continue to teach us.  The amino acids of GOT2 (#15 – #68) and the interacting sequence of nucleotides in lncRNA-ACOD1 (#165 – #390) are well conserved across species.  This might be a primordial mechanism from the RNA world (forgotten but not gone) to produce ATP production to compe with metabolic stress.   The RNA/protein binding site is close (4.2 Angstroms) to the substrate binding site.

The fun is just starting as several other lncRNAs are induced by viruses.  You can only imagine what they will tell us.  Another set of drug targets perhaps, or worse, the cause of peculiar side effects from drugs already in use.

Been busy

I haven’t posted for a while because I’ve been writing a letter to PNAS concerning my idea that chronic fatigue syndrome symptoms are a manifestation of an excess of senescent cells pumping out all sorts of inflammatory proteins into the systemic circulation.  The way to prove or disprove the idea is to measure p15^INK4a in circulating white cells.  The letter is now written and my wife is attempting to put it into English.  For details about the idea please see  Wish me luck that the letter is accepted.