Genes — Which Do We Need?

 

It’s widely known that cancers reflect cellular control going awry as a result of change in our genetic material — DNA. Beyond surgery and radiotherapy, cancer treatment uses drugs that either kill cells non-specifically or target mutated proteins. The latter give specificity for tumour cells but currently there are few such drugs. For mutations that inactivate tumour suppressor genes we have as yet no treatment, although one hope is that we will be able to replace these damaged genes with normal versions.

But there’s a problem with drug or gene replacement tactics for any genetic disease because, fundamentally, we don’t understand what we’re doing. Ideally we’d introduce the offending mutation into humans, look at its effect then follow up with our therapy and track what happens. We can’t do that, of course, and, although we can do equivalent experiments in model organisms like the fruit fly or the mouse, models are not the same as humans.

Nature’s experiments

A quite different approach is to note that under the cloak of evolution Nature has been doing these experiments for us. That’s to say, natural human genetic variation has given rise to a vast array of mutations across the population and all we need to do is find them and see what effect they have had on the biology of the individual. The “all” in the previous sentence is a weighty word because to sift out these variants requires DNA sequencing on a grand scale. Fortunately, as followers of this blog will know, such power in the shape of massively parallel sequencing is now available (see Family Tree of Breast Cancer).

The Genome Aggregation Database (gnomAD) has just published (May 2020) its latest efforts in the shape of DNA sequences of 125,748 exomes (protein-coding DNA) and 15,708 whole human genomes. It’s a simply staggering achievement, the aim being to find out what the differences between our individual genetic codes mean in terms of our health. These variants are the differences that make individual genomes unique and they include single nucleotide polymorphisms (‘SNPs’, pronounced ‘snips’ — one nucleotide (base) differing from the reference DNA sequence), insertions (additional nucleotides inserted in a DNA sequence), deletions (missing nucleotides), substitutions (multiple nucleotides altered relative to the reference sequence) and structural variants (large sections of a chromosome or entire chromosomes duplicated, deleted or rearranged).

Cataloguing genetic variation in humans.  The genome aggregation database (gnomAD) includes 15,708 whole-genome sequences and 125,748 exomes and the study catalogued the complete range of naturally occurring DNA variants.

Representation of 141,456 human DNA sequences. This way of presenting a vast amount of data is called UMAP (Uniform Manifold Approximation and Projection): the sequence of each individual is a dot, the individuals comprising six global and eight sub-continental ancestries. The pseudo colours mark clusters of related DNA sequence. Note that this ‘map’ does not relate to location: it is merely a visual representation of a lot of data. The horizontal bar indicates the number of individuals by population and sub-population in the gnomAD study with the same colour code as in the upper figure. From Karczewski et al. 2020.

It turns out that there are rather a lot of them. After filtering to minimise the errors that come with high-throughput sequencing, nearly 15 million high-quality variants were identified in the exome dataset and 230 million in the whole genome screens. In the protein-coding sequences alone there were over 400,000 variants predicted to block the function of the protein.

Where is this massive study taking us?

These naturally arising mutations provide a potentially valuable window on our genomes that we can look through to answer our title question: which of our genes are essential for survival and which can we manage without?

What gnomAD did was to construct a ‘spectrum of tolerance’ for each protein-coding gene in the human genome. This is potentially important because, for example, if a gene that is not essential for life acquires a disease-causing mutation, blocking the gene might cure the disease without killing the patient.

The clearest example of using natural in vivo models of human gene inactivation to inform therapeutic strategy has come from the LRRK2 gene. Variants in LRRK2 can change the activity of the protein it encodes so as to significantly increase the risk of Parkinson’s disease. From the gnomAD screen it turned out that variants in LRRK2 that blocked its normal activity were not strongly associated with evident disease. In other words, we can do without LRRK — and if it picks up a harmful mutation we can try to knock it out, secure in the knowledge that it’s not essential for survival.

So thank you Nature for doing the experiment we can’t do — tinkering with our own genes to see what happens.

References

Karczewski, K. J. et al. (2020). The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443.

Whiffin, N., Armean, I.M., Kleinman, A. et al. (2020). The effect of LRRK2 loss-of-function variants in humans. Nature Medicine. https://doi.org/10.1038/s41591-020-0893-5.

Cummings, B. B. et al. (2020). Transcript expression-aware annotation improves rare variant interpretation. Nature 581, 452–458.

Minikel, E. V. et al. (2020). Evaluating drug targets through human loss-of-function genetic variation. Nature 581, 459–464.

Collins, R. L. et al. (2020). A structural variation reference for medical and population genetics. Nature 581, 444–451.

Blocking the Unblockable

 

It’s very nearly 40 years since the first human ‘cancer gene’ was identified — in 1982 to be precise. By ‘cancer gene’ we mean a region of DNA that encodes a protein that has a role in normal cell behaviour but that has acquired a mutation of some sort that confers abnormal activity on the protein.

The discovery of RAS ‘oncogene’ activation by DNA and protein mutation stimulated intense activity in unveiling the origins of cancer at the molecular level that has continued to this day. It’s been an exciting and sobering story and RAS has emerged as perhaps the best example you could have of the paradox of cancer. On the one hand it seems startlingly simple: on the other it’s been impenetrably complex.

The simple bit first

Relatively quickly it was shown that there were three closely related RAS genes (KRAS, HRAS & NRAS): they all encode a small protein of just 189 amino acids and they all act as a molecular switches. That means RAS proteins can bind to a small regulator molecule (it’s GTP (guanosine triphosphate) — one of the nucleotides found in DNA and RNA). When that happens RAS changes shape so that it can interact with (i.e. stick to) a variety of effector proteins within the cell. These trigger signalling cascades that ultimately control the activity of genes in the nucleus that control cell proliferation, cell cycle progression and apoptosis (cell death). The switch is flicked off when GTP is converted to GDP — so RAS looses its effector binding capacity.

The other simple bit is that RAS turned out to be one end of the spectrum of DNA damage that can activate an oncogene: the smallest possible change in DNA — mutation of just one base changed one amino acid in the RAS protein and hence its shape. Result: permanently switched on RAS: it’s always stuck to GTP.

Cell signalling. Cells receive many signals from messengers that attach to receptor proteins spanning the outer membrane. Activated receptors turn on relays of proteins. RAS proteins are key nodes that transmit multiple signals. The coloured blocks represent a RAS controlled pathway (a relay of proteins, A, B, C, D) that ‘talk’ to the nucleus, switching on genes that drive proliferation. The arrows diverging from RAS indicate that it regulates many pathways controlling such processes as actin cytoskeletal integrity, cell proliferation, cell differentiation, cell adhesion, apoptosis and cell migration.

Oncogenic RAS and human cancers

We’ve noted that RAS signalling controls functions critical in cancer development and it’s therefore not surprising that it’s mutated, on average, in 22% of all human tumours with pancreatic cancer being an extreme example where 90% of tumours have RAS mutations (the form of RAS is actually KRAS). Those facts, together with the seeming simplicity of its molecular action, put RAS at the top of the target table for chemists seeking cancer therapies. We’ve tried to keep up with events in Mission Impossible, Molecular Dominoes and Where’s that tumour? but the repeated story has been that the upshot of the expenditure of much cash, inspiration and perspiration has, until fairly recently, been zippo. Lots of runners but none that made it into clinical trials. However, that has slowly begun to change over the last ten years and now at least five KRAS-modulating agents are in clinical trials.

A few months back Kevin Lou, Kevan Shokat and colleagues at the University of California published a study of a small molecule, ARS-1620, showing that it inhibited mutant KRAS in lung and pancreatic cancer cells. They screened for other interactions that contribute to the KRAS-driven tumour state and identified two sets of such effectors, one enhancing the engagement of ARS-1620 with its target and others that regulated tumour survival pathways in cells and in vivo. Targetting these synergised with ARS-1620 in suppressing tumour growth.

The RAS switch. Scheme of normal RAS action (top): replacement of a bound guanosine diphosphate (GDP) molecule with guanosine triphosphate (GTP) flips the switch so that RAS can interact with other proteins to turn on downstream signalling pathways that control cell growth and differentiation. Oncogenic RAS (with a single amino acid change at position 12 (Glycine to Valine) blocks the breakdown of bound GTP so the switch is always ‘on’. The new small molecule inhibitor characterized by Canon et al., AMG 510, interacts with KRASG12C to block GTP binding. The switch remains ‘off’ and the cancer-promoting activity of mutant KRAS is inhibited.

More recently Jude Canon at Amgen Research, together with colleagues from a number of institutes, described another small molecule, AMG 510, that also recognises the mutant form of KRAS with high specificity, hence impairing cell proliferation. In mice carrying human pancreatic tumours AMG 510 caused permanent tumour regression — provided the mice had functioning immune systems. In mice lacking T cells (i.e. ‘nude’ mice) the tumours re-grew but combining AMG 510 with immunotherapy (an antibody against anti-PD1) gave complete tumour regression. AMG 510 stimulated the expression of inflammatory chemokines that promoted infiltration of the tumours by T cells and dendritic cells (sometimes called ‘antigen-presenting cells’, these cells process antigens and present fragments thereof on their surface to T cells and B cells to promote the adaptive immune response). In preliminary trials four patients with non-small cell lung cancer showed significant effects — either tumour shrinkage or complete inhibition of growth.

So maybe at long last the enigma of RAS is being prised open. The efficacy of AMG 510 against lung cancers is particularly heartening as there remains little in the way of therapeutic options for these tumours.

References

Canon, J. et al. (2019). The clinical KRAS(G12C) inhibitor AMG 510 drives anti-tumour immunity. Nature 575, 217–223.

Lou, K. et al. (2019). KRASG12C inhibition produces a driver-limited state revealing collateral dependencies. Science Signaling 12, Issue 583, eaaw9450. DOI: 10.1126/scisignal.aaw9450

Little Things That May Mean a Lot

 

You may have noticed a seeming oddity about science in that you often hear nothing about a topic for ages and then along come several new pieces of work more or less together — the London bus effect. There’s number of reasons for this, one being that scientists love gadgets — they’re really little boys and girls with licence to play with their toys for a living — so when a new method or piece of kit appears there’s usually something of a band wagon response. Another factor is that different labs quite often talk to each other and this can lead to collaborative efforts sometimes resulting in several, complementary publications. We’ve seen this recently with bugs and their effect on human cancers. In Secret Army: More Manoeuvres Revealed we saw how bacteria could drive lung cancer and in Mushrooming Secret Army how fungi are now established as players in at least in one type of cancer.

Now add to these a paper by Hila Sberro, Ami Bhatt and colleagues from Stanford, Berkeley and the Biomedical Sciences Research Center Alexander Fleming, Vari, Greece that reveals a huge pool of hitherto unknown proteins in the human microbiome.

What Sberro & Co did was to take tissue samples (1,773 of them) from humans (skin, vagina, gut and mouth) and look at the DNA sequences therein. What you get doing this is the ‘metagenome’ — i.e., the DNA of the whole community you pick up — and that type of study is therefore called ‘comparative genomics’.

Scheme showing how metagenomic analysis can identify thousands of small coding regions of DNA from microbiome sequences obtained from a range of human tissues. From Sberro et al., 2019.

They focused on ‘small’ proteins of 50 or fewer amino acids. The hormone insulin has 51 amino acids and proteins in the size range up to about 50 amino acids are often called ‘peptides’. Perhaps counter-intuitively, large proteins are easier to isolate than the little chaps who have for this reason been rather overlooked — until now that is.

Some over-sight because Sberro et al. discovered more than 400,000 of these potential mini-proteins lurking in the nooks and crannies of their human volunteers. This hitherto largely unknown horde (fewer that 5% had been identified before) turned out to be made up of about 4,500 ‘families’ — groups of proteins that are similar in size and amino acid content.

This is a really astonishing finding quite literally under our noses. At the moment we have no idea what most of these bacterial proteins do. As you might expect, some of the proteins appear to be involved in keeping cells alive (they’re ‘housekeeping genes’). You might also guess that some may not have any role at all — they’re just a kind of accidental by-product — but, by and large, Nature doesn’t waste energy and making proteins is a very expensive business in energetic terms. And if you’re in any doubt about the importance of ‘peptides’, give a moment’s thought to the human proteins oxytocin (9 amino acids that plays an important role in sexual reproduction and in childbirth) and — even smaller — the tripeptide (i.e. 3 amino acids) glutathione that protects most living things from damage by free radicals.

As some of the small, bacterial proteins are present in large amounts we can be confident they too do something useful — perhaps protect the bacteria themselves from their own toxins, made to kill viruses.

And, as ever, when we get to understand what these little guys are up to they may be useful in, for example, interventional medicine.

Reference

Sberro, H. et al., 2019. Large-Scale Analyses of Human Microbiomes Reveal Thousands of Small, Novel Genes. Cell 178, 1-15.

Mushrooming Secret Army

 

We have in these pages talked quite a bit about our ‘secret army’ — the bugs that share our body to the extent that bacteria outnumber us on a cell-to-cell basis by at least three to one. As we noted in Secret Army: More Manoeuvres Revealed, bacteria are just one part of what is collectively called the microbiota’ but with over 2000 different species and a total gene pool hundreds of times bigger than our own 20,000 or so, they are by far the biggest. And it’s gradually become clear that they are not with us just because our bodies are warm, damp and comfortable but they help us get the most out of our food and they’re important in the working of our immune system.

Bacteria and cancer

Most critically, in the present context, we now know that shifts in proportions of species in the microbiome can influence cancer development and perhaps even the spread of tumour cells around the body.

Small fry

Important though they are, bacteria aren’t the only members of the microbiome — which includes fungi, viruses and various single-celled parasites (protozoa). Today’s story is about fungi, a group of microorganisms familiar to gardeners world-wide, that includes yeasts and molds, as well as the more familiar mushrooms. There’s estimated to be several million species of fungi, although only about 120,000 have been described. Some we can eat, some can kill us and, of course, there’s magic mushrooms.

With all this diversity you might wonder whether any fungi have elbowed their way into us to share the delights of the human body alongside bacterial microbes. Of course they have: most people will have heard of candidiasis — a fungal infection caused by Candida yeasts that belong to the genus Candida. Candida normally finds its niche in places like the mouth (giving the condition called thrush), gut, vagina and on the skin and usually doesn’t give us any trouble. But, truth to tell, we’ve known very little about fungi in us until recently when the power of DNA sequencing has started to be applied to the topic. This has confirmed that we do carry lots of fungi around with us, albeit that they are only a tiny fraction of the microbial community (somewhat less than 0.1%).

New actor in the cancer cast

This fungal force of microbes is known as the mycobiome (as distinct from the microbiome) and, in contrast to bacteria, there is no evidence that it has a role in cancer. Until, that is, the recent publication from New York University School of Medicine by Berk Aykut, George Miller and friends showing that fungi travel from the gut to the pancreas where a particular species can actually give cancer a helping hand. The cancer in question is pancreatic ductal adenocarcinoma (PDA) that has a particularly dismal prognosis.How a fungus can drive cancer. The scheme represents a tumour in the pancreas changing the make up of the adjacent fungal community and how a protein in the blood called mannose binding lectin (MBL) can attach to the outer surface of a fungal cell. When this happens MBL changes shape so it can then stick to another protein (C3) which in turn activates a relay of proteins called the complement cascade. One upshot of this can be to promote tumour growth. From Dambuza and Brown 2019.

How did they do it?

Aykut et al. first used DNA sequencing to look for fungus-specific sequences in the pancreas of humans with PDA and in mouse models of PDA, They’d previously shown that the bacterial load goes up by about 1000-fold in tumours compared with healthy tissue and, lo and behold, they found a similar increase in fungi. Next they tagged strains of fungus with a fluorescent label and showed that the cells could migrate from the gut to the pancreas of mice in under 30 minutes.

They then tracked down a protein called mannose binding lectin (MBL) expression of which is associated with poor survival in human PDA patients. MBL is a ‘serum protein’, meaning that it floats around in blood. This led to the discovery that MBL can bind to the surface of fungal cells and when it does so changes shape to permit activation of a relay of signal proteins called the complement system. This ‘complement cascade’ is part of our immune system, enhancing the capacity of antibodies and phagocytic cells to clear microbes from the circulation.

Jules Bordet was the chap who first showed that something in normal blood plasma could help to kill off bacteria back at the end of the 19th century and, as such, deserves to be better remembered as a famous Belgian.

The complement system is pretty amazing because, whilst it can trigger an immune response against invading pathogens, it can also switch on inflammatory pathways that help cells grow and move around — in other words, give a helping hand to tumours.

Fungible?

I met this word for the first time a few days ago, courtesy of the journalist and author Ann Treneman. You’d think that no piece on fungi would be complete without it but it turns out to have nothing to do with mushrooms: it just means interchangeable or switchable. But hang on! We can squeeze it in by asking a very relevant question: are pancreatic fungi fungible in terms of their capacity to promote cancer? Aykut et al. did just that and the answer was ‘no they’re not.’ One species seems to be particularly abundant in PDA: the genus Malassezia. This was true for both mouse and human tumours and perhaps that shouldn’t surprise us as Malassezia is the most abundant fungal species in mammalian skin, accounting for more than 80% of our skin mycobiome. So it’s Malassezia not other species (e.g., Candida) that has the power to drive cancer.

Spores of the yeast Malassezia

Fungal footnote

In a final exciting experiment Aykut et al. showed that antifungal drugs halted PDA progression in mice and improved the ability of chemotherapy to shrink the tumour. This obviously raises the notion that if we can find ways of shifting the balance of fungal communities or interfering with the link to the complement cascade we might have a completely new line on desperately needed therapies for this disease.

References

Aykut, B. et al., (2019). The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL. Nature 574, 264–267.

Dambuza, I.M. and Brown, G.D. (2019). Fungi accelerate pancreatic cancer. Nature 574, 184-185.

Secret Army: More Manoeuvres Revealed

 

I don’t know about you but I find it difficult to grasp the idea that there are more bugs in my body than there are ‘me’ cells. That is, microorganisms (mostly bacteria) outnumber the aggregate of liver, skin and what-have-you cells. They’re attracted, of course, to the warm, damp surfaces of the cavities in our bodies that are covered by a sticky, mucous membrane, e.g., the mouth, nose and especially the intestines (the gastrointestinal tract).

The story so far

Over the last few years it’s become clear that these co-residents — collectively called the microbiota — are not just free-loaders. They’re critical to our well-being in helping to fight infection by other microrganisms (as we noted in Our Inner Self), they influence our immune system and in the gut they extract the last scraps of nutrients from our diet. So maybe it makes them easier to live with if we keep in mind that we need them every bit as much as they depend on us.

We now know that there are about 2000 different species of bacteria in the human gut (yes, that really is 2,000 different types of bug) and, with all that diversity, it’s not surprising that the total number of genes they carry far exceeds our own complement (by several million to about 20,000). In it’s a small world we noted that obesity causes a switch in the proportions of two major sub-families of bacteria, resulting in a decrease in the number of bug genes. The flip side is that a more diverse bug population (microbiome) is associated with a healthy status. What’s more, shifts of this sort in the microbiota balance can influence cancer development. Even more remarkably, we saw in Hitchhiker Or Driver? That the microbiome may also play a role in the spread of tumours to secondary sites (metastasis).

Time for a deep breath

If all this is going on in the intestines you might well ask “What about the lungs?” — because, and if you didn’t know you might guess, their job of extracting oxygen from the air we inhale means that they are covered with the largest surface area of mucosal tissue in the body. They are literally an open invitation to passing microorganisms — as we all know from the ease with which we pick up infections.

In view of what we know about gut bugs a rather obvious question is “Could the bug community play a role in lung cancer?” It’s a particularly pressing question because not only is lung cancer the major global cause of cancer death but 70% lung cancer patients have bacterial infections and these markedly influence tumour development and patient survival. Tyler Jacks, Chengcheng Jin and colleagues at the Massachusetts Institute of Technology approached this using a mouse model for lung cancer (in which two mutated genes, Kras and P53 drive tumour formation).

In short they found that germ-free mice (or mice treated with antibiotics) were significantly protected from lung cancer in this model system.

How bacteria can drive lung cancer in mice. Left: scheme of a lung with low levels of bacteria and normal levels of immune system cells. Right: increased levels of bacteria accelerate tumour growth by stimulating the release of chemicals from blood cells that in turn activate cells of the immune system to release other effector molecules that promote tumour growth. The mice were genetically altered to promote lung tumour growth (by mutation of the Kras and P53 genes). In more detail the steps are that the bacteria cause macrophages to release interleukins (IL-1 & IL-23) that stick to a sub-set of T cells (γδ T cells): these in turn release factors that drive tumour cell proliferation, including IL-22. From Jin et al. 2019.

As lung tumours grow in this mouse model the total bacterial load increases. This abnormal regulation of the local bug community stimulates white blood cells (T cells present in the lung) to make and release small proteins (cytokines, in particular interleukin 17) that signal to neutrophils and tumour cells to promote growth.

This new finding reveals that cross-talk between the local microbiota and the immune system can drive lung tumour development. The extent of lung tumour growth correlated with the levels of bacteria in the airway but not with those in the intestinal tract — so this is an effect specific to the lung bugs.

Indeed, rather than the players prominent in the intestines (Bs & Fs) that we met in Hitchhiker Or Driver?, the most common members of the lung microbiome are Staphylococcus, Streptococcus and Lactobacillus.

In a final twist Jin & Co. took bacteria from late-stage tumours and inoculated them into the lungs of mice with early tumours that then grew faster.

These experiments have revealed a hitherto unknown role for bacteria in cancer and, of course, the molecular signals identified join the ever-expanding list of potential targets for drug intervention.

References

Jin, C. et al. (2019). Commensal Microbiota Promote Lung Cancer Development via γδ T Cells. Cell 176, 998-1013.e16.

Food Fix For Pharma Failure

 

If you held a global quiz, Question: “Which biological molecules can you name?” I guess, setting aside ‘DNA‘, the top two would be insulin and glucose. Why might that be? Well, the World Health Organization reckons diabetes is the seventh leading cause of death in the world. The number of people with diabetes has quadrupled in the last 30 years to over 420 million and, together with high levels of blood glucose (sugar), it kills nearly four million a year.

There are two forms of diabetes: in both the level of glucose in the blood is too high. That’s normally regulated by the hormone insulin, made in the pancreas. In Type 1 diabetes insulin isn’t made at all. In Type 2 insulin is made but doesn’t work properly.

When insulin is released into the bloodstream it can ‘talk’ to cells by binding to protein receptors that span cell membranes. Insulin sticks to the outside, the receptor changes shape and that switches on signalling pathways inside the cell. One of these causes transporter molecules to move into the cell membrane so that they can carry glucose from the blood into the cell. When insulin doesn’t work it is this circuit that’s disrupted.

Insulin signalling. Insulin binds to its receptor which transmits a signal across the cell membrane, leading to the activation of the enzyme PIK3. This leads indirectly to the movement of glucose transporter proteins to the cell membrane and influx of glucose.

So the key thing is that, under normal conditions, when the level of blood glucose rises (after eating) insulin is released from the pancreas. Its action (via insulin receptors on target tissues e.g., liver, muscle and fat) promotes glucose uptake and restores normal blood glucose levels. In diabetes, one way or another, this control is compromised.

Global expansion

Across most of the world the incidence of diabetes, obesity and cancer are rising in parallel. In the developed world most people are aware of the link between diabetes and weight: about 90% of adults with diabetes are overweight or obese. Over 2 billion adults (about one third of the world population) are overweight and nearly one third of these (31%) are obese — more than the number who are underweight. The cause and effect here is that obesity promotes long-term inflammation and insulin resistance — leading to Type 2 diabetes.

Including cancer

The first person who seems to have spotted a possible connection between diabetes and cancer was the 19th-century French surgeon Theodore Tuffier. He was a pioneer of lung and heart surgery and of spinal anaesthesia and he’s also a footnote in the history of art by virtue of having once owned A Young Girl Reading, one of the more famous oil paintings produced by the prolific 18th-century artist Jean-Honoré Fragonard (if you want to see it head for the National Gallery of Art in Washington DC). Tuffier noticed that having type 2 diabetes increased the chances of patients getting some forms of cancer and pondered whether there was a relationship between diabetes and cancer.

It was a good question then but it’s an even better one now when this duo have become dominant causes of morbidity and mortality worldwide.

We now know that being overweight increases the risk of a wide range of cancers including two of the most common types — breast and bowel cancers. Unsurprisingly, the evidence is also clear that diabetes (primarily type 2) is associated with increased risk for some cancers (liver, pancreas, endometrium, colon and rectum, breast, bladder).

With all this inter-connecting it’s perhaps not surprising that the pathway by which insulin regulates glucose also talks to signalling cascades involved in cell survival, growth and proliferation — in other words, potential cancer initiators. The central player in all this is a protein called PIK3 (it’s an enzyme that adds phosphate groups (so it’s a ‘kinase’) to a lipid called phosphatidylinositol bisphosphate, an oily, water-soluble component of the plasma membrane). It’s turned out that PIK3 is one of the most commonly mutated genes in human cancers — e.g., PIK3 mutations occur in 25–40% of all human breast cancers.

Signalling pathways switched on by mutant PIK3. A critical upshot is the activation of cell survival and growth that leads to cancer.

Accordingly, much effort has gone into producing drugs to block the action of PIK3 (or other steps in this signal pathway). The problem is that these have worked as cancer treatments either very variably or not at all.

The difficulty arises from the inter-connectivity of signalling that we’ve just described: a drug blocking insulin signalling causes the liver to release glucose and prevents muscle and fats cells from taking up glucose. Result: blood sugar levels rise (hyperglycaemia). This effect is usually transient as the pancreas makes more insulin that restores normal glucose levels.

Blockade of mutant PIK3 by an inhibitor. This blocks the route to cancer but glucose levels rise in the circulation (hyperglycaemia) promoting the release of insulin (top). Insulin can now signal through the normal pathway (bottom), overcoming the effect of the anti-cancer drug. Note that the cell has two copies of the PIK3 gene/protein, one of which is mutated, the other remaining normal.

Is our journey really necessary?

By now you might be wondering whether there is anything that makes grappling with insulin signaling worth the bother. Well, there is — and here it is. It’s a recent piece of work by Benjamin Hopkins, Lewis Cantley and colleagues at Weill Cornell Medicine, New York who looked at ways of getting round the insulin feedback response so that the effect of PIK3 inhibitors could be boosted.

Sketch showing the effect of diet on the potency of an anti-cancer drug in mice. The red line represents normal tumour growth. The black line shows the effect of PIK3 blockade when the mice are on a ketogenic diet: tumour growth is suppressed. On a normal diet the drug alone has only a slight effect on tumour growth. Similar results were obtained in a variety of model tumours (Hopkins et al., 2018).

They first showed that, in a range of model tumours in mice, insulin feedback caused by blockade of PIK3 was sufficient to switch on signalling even in the continued presence of anti-PIK3 drugs. The really brilliant result was that changing the diet of the mice could offset this effect. Switching the mice to a high-fat, adequate-protein, low-carbohydrate (sugar) diet essentially stopped the growth of tumours driven by mutant PIK3 treated with PIK3 blockers. This is a ketogenic (or keto) diet, the idea being to deplete the store of glucose in the liver and hence limit the rise in blood glucose following PIK3 blockade.

Giving the mice insulin after the drug drastically reduces the effect of the PIK3 inhibitor, supporting the idea that that a keto diet improves responses to PIK3 inhibitors by reducing blood insulin and hence its capacity to switch on signalling in tumour cells.

A few weeks prior to the publication of the PIK3 results another piece of work showed that adding the amino acid histidine to the diet of mice can increase the effectiveness of the drug methotrexate against leukemia. Methotrexate was one of the first anti-cancer agents to be made and has been in use for 70 years.

These are really remarkable results — as far as I know the first time diet has been shown to influence the efficacy of anti-cancer drugs. It doesn’t mean that all tumours with mutations in PIK3 have suddenly become curable or that the long-serving methotrexate is going to turn out to be a panacea after all — but it does suggest a way of improving the treatment of many types of tumour.

References

Hopkins, B.D. et al. (2018). Suppression of insulin feedback enhances the efficacy of PI3K inhibitors. Nature 560, 499-503.

Kanarek, N. et al. (2018). Histidine catabolism is a major determinant of methotrexate sensitivity. Nature 559, 632–636.

Now wash your hands!

 

You must have spent the last 20 years on a distant planet if you’re unaware that we’re heading for Antibiotic Armaggedon — the rise of “Superbugs”, i.e., bacteria resistant to once-successful medication. Microbes resistant to multiple antimicrobials are called multidrug resistant. It’s a desperate matter because it means trivial infections may become fatal and currently safe surgical procedures may become dangerous.

Time-line of the discovery of different antibiotic classes in clinical use. The key point is that the last antibiotic class to become a successful treatment was discovered in 1987.

What’s the problem?
It’s 30 years since we came up a new class of antibiotics. The golden age launched by Fleming’s celebrated discovery of penicillin is long gone and while the discovery curve has drifted ever downwards since 1960 the bugs have been busy.

Just how busy a bug can be was shown by a large-scale experiment carried out by Roy Kishony and friends. They built a “Mega-Plate” — a Petri Dish 2 ft by 4 ft filled with a jelly for the bacteria to grow in. The bugs were seeded into channels at either end so they would grow towards the middle. The only thing stopping them was four channels dosed with antibiotic at increasing concentrations — 10 times more in each successive channel.

The bugs grow until they hit a wall of antibiotic. There they pause for a think — and, after a bit, an intrepid little group start to make their way into the higher dose of drug. Gradually the number of groups expand until a tidal wave sweeps over that barrier. This is repeated at each new ‘wall’ — four times until the whole tray is a bug fest.

When they pause at each new ‘wall’ they’re not ‘thinking’ of course. They’re just picking up random mutations in their DNA until they are able to advance into the high drug environment. So this experiment is a fantastic visual display of bugs becoming drug-resistant. And it’s terrifying because it takes about 11 days for them to overcome four levels of drug. It’s even more scary in the speeded-up movie as that lasts less than two minutes.

Sound familiar?
It should do as this is a cancer column and readers will know that cancers arise by picking up mutations. To highlight the similarities the picture below is the left-hand half of the bug tray with new colonies shown as linked dots. You could perfectly well think of these as early stage cancer cells acquiring mutations in ‘driver’ genes that push them towards tumour formation.

So that’s pretty scary too and the only good news is that animal cells reproduce much more slowly than bacteria. The fastest they can manage is about 48 hours to grow and divide into two new cells and for many it’s much slower than that. Bugs, on the other hand, can do it in 20 minutes if you feed them enough of the right stuff.

Which is why we don’t all get zonked by cancer at an early age.

The evolution of bacteria on a “Mega-Plate” Petri Dish. The vertical red lines mark the boundaries of increasing antibiotic concentrations. You could equally think of each dot that represents a new bacterial colony being early stage cancer cells acquiring mutations in ‘driver’ genes (white arrows) that push them towards tumour formation. From Roy Kishony’s Laboratory at Harvard Medical School.

Enough of that!
But for once I don’t want to talk about cancer but about a really fascinating piece of work that caught my eye in the journal Cell Reports. It’s by Gianni Panagiotou, Kang Kang and colleagues from The University of Hong Kong and The Hans Knöll Institute, Jena, Germany and it’s all about their travels on the Hong Kong MTR (Mass Transit Railway). This is the network of over 200 km of railway lines with 159 stations that serves the urbanised areas of Hong Kong IslandKowloon, and the New Territories and has a cross- border connection to the neighboring city of Shenzhen in mainland China.

An MTR train on the Tung Chung line that links Lantau Island with Hong Kong Island.

Being scientists of course they weren’t just having a day out. They wanted to know the contents of the microbiome that they and their fellow travellers picked up on the palms of their hands when riding the rails. ‘Microbiome’ means all of the collection of microorganisms — though in practice this is almost entirely bacteria. So they swabbed the palms of volunteers and then threw the full power of modern DNA sequencing and genetic analysis at what they’d scraped off. Or, as they put it: “We conducted a metagenomic study of the Hong Kong MTR system.”

And if you’re thinking it might be possible to take a trip on the Hong Kong Metro without grabbing a handrail or otherwise engaging in what on the London Underground used to be called ‘strap-hanging’ you clearly haven’t tried it!

Hong Kong MTR.

 

The MTR System and Sampling Procedure. Left: The eight urban lines studied: the Airport Express line and Disneyland Resort branch were excluded. The Central-Hong Kong station and the cross-border rail stations connecting with the MTR and the Shenzhen metro system are labeled. Right: The sampling procedure included handwashing, handrail touching for 30 min and swabbing. From Kang et al. 2018.

Hold very tight please! 

It’s going to become a seriously bumpy ride. The major findings were:

  1. Four groups (phyla) of bacteria dominated: Actinobacteria [51%], Proteobacteria [27%], Firmicutes [11%] and Bacteroidetes [2%]. Followers of this blog will be delighted to spot the last two (B & F) as we’ve met them several times before (in Hitchhiker Or Driver?, Fast Food Fix Focuses on Fibre, Our Inner Self, The Best Laid Plans In Mice and Men, and, of course, in it’s a small world) — that’s how important they are in the context of cancer.
  2. The dominant organism (29% of the community) was P. acnes (one of the Actinobacteria — it’s the bug linked to the skin condition of acne).
  3. Some non-human-associated species (e.g., soil organisms) also popped up that varied enormously in amount from day to day — perhaps because of weather conditions (e.g., humidity).
  4. Variation in the make-up of the microbial communities picked up depended, more than anything else, on the time of day. There was a marked decrease in diversity in afternoon samples compared with those taken in the morning.
  5. Specific species of bacteria associated with individual metro lines. That is, sets of bug types are relatively abundant on a given line compared with all other lines, giving a kind of line-specific signature — though the distinction declines from morning to afternoon. The most physically isolated line, MOS (Ma On Shan), had a greater number of signature species. The MOS runs entirely above ground alongside the Shing Mun Channel, a polluted brackish river, and its ‘signature’ includes bacteria found in sewage.
  6. All of which brings us to bugs with antibiotic resistance genes (ARGs). Across the network 136 ARG families were detected including 24 that are clinically important. Strikingly, lines closer to Shenzhen (ER (East Rail) and MOS) tend to have higher ARG input during the day. Critically, the ER line a.m. signatures become p.m.-enriched in all MTR lines far from Shenzhen — that is, these ARG families spread over the network during the day.

Simplified map of the Hong Kong MTR indicating how antibiotic resistance genes spread during the day from the ER and MOS lines to the entire network. Tetracycline resistance genes: tetA, tetO, tetRRPP and tetMWOS; vancomycin resistance genes: vanC, vanX. From Kang et al. 2018.

These results clearly suggest that the ER line, the only cross-border line linked to mainland China, may be a source of clinically important ARGs, especially against tetracycline, a commonly used antibiotic in China’s swine feedlots. Antibiotics, including tetracycline, can be detected in the soil in the Pearl River Delta area where the cities of Hong Kong and Shenzhen are located.

It should be said that this is by no means the first survey of bugs on rails. Notable ones have looked at the New York and Boston metro systems and they too revealed the potential health risks of the bug communities found on trains and in the stations, including the presence of pathogens and antibiotic resistance. The Boston survey highlighted that different types of materials have surfaces that are preferred by different microbes with high variation in functional capacity and pathogenic potential.

One obvious suggestion from these studies is that world-wide we could do a lot to improve sanitation, e.g., by having hand sanitizer dispensers in all sensible places (at the exits of metro, railway and bike-sharing stations and airports and of course in hospitals). The Hong Kong data are seriously frightening and most people seem blissfully unaware that the invisible world they reveal carries the potential for the destruction of us all.

But, as ever, there’s two sides to the matter. We’ve evolved over millions of years to live with bugs and they with us. However you wash your hands you won’t get rid of every bug and anyway, as what’s-his-name almost says, “They’ll be back!” We all carry around micro-organisms that can be fatal if they get to the wrong place. But, if you’re reasonably fit, there’s a lot to be said for simply following sensible, basic hygiene rules with a philosophy of ‘live and let live.’

Have a nice day commuters, wherever you are!

References

Kang K., et al. (2018). The Environmental Exposures and Inner- and Intercity Traffic Flows of the Metro System May Contribute to the Skin Microbiome and Resistome. Cell Reports 24, 1190–1202.

Wu, N., Qiao, M., Zhang, B., Cheng, W.D., and Zhu, Y.G. (2010). Abundance and diversity of tetracycline resistance genes in soils adjacent to representative swine feedlots in China. Environ. Sci. Technol. 44, 6933–6939.

Li, Y.W., Wu, X.L., Mo, C.H., Tai, Y.P., Huang, X.P., and Xiang, L. (2011). Investigation of sulfonamide, tetracycline, and quinolone antibiotics in vegetable farmland soil in the Pearl River Delta area, southern China. J. Agric. Food Chem. 59, 7268–7276.

Leung, M.H., Wilkins, D., Li, E.K., Kong, F.K., and Lee, P.K. (2014). Indoor-air microbiome in an urban subway network: diversity and dynamics. Appl. Environ. Microbiol. 80, 6760–6770.

Robertson, C.E., Baumgartner, L.K., Harris, J.K., Peterson, K.L., Stevens, M.J., Frank, D.N., and Pace, N.R. (2013). Culture-independent analysis of aerosol microbiology in a metropolitan subway system. Appl. Environ. Microbiol. 79, 3485–3493.

Afshinnekoo, E., Meydan, C., Chowdhury, S., Jaroudi, D., Boyer, C., Bernstein, N., Maritz, J.M., Reeves, D., Gandara, J., Chhangawala, S., et al. (2015). Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics. Cell Syst 1, 72–87.

Hsu, T., Joice, R., Vallarino, J., Abu-Ali, G., Hartmann, E.M., Shafquat, A., Du- Long, C., Baranowski, C., Gevers, D., Green, J.L., et al. (2016). Urban Transit System Microbial Communities Differ by Surface Type and Interaction with Humans and the Environment. mSystems 1, e00018–e00016.

Same Again Please

 

It’s often said that every family has its secret — Uncle Fred’s fondness for the horses, Cousin Bertha’s promiscuity, etc. — whatever it is that ‘we don’t talk about.’ If that’s true the scientific community is no exception. For us the unutterable is reproducibility — meaning you’ve done an experiment, new in some way, but the key questions are: ‘Can you do it again with the same result?’ and, even more important: ‘Can someone else repeat it?’

Once upon a time in my lab we had a standing joke: whoever came bounding along shouting about a new result would be asked ‘How reproducible is it?’ Reply: ‘100%!’ Next question: ‘How often have you done the experiment?’ Reply: ‘Once!!’ Boom, boom!!!

Not a rib-tickler but it did point to the knottiest problem in biological science namely that, when you start tinkering with living systems, you’re never fully in control.

How big is the problem?

But, as dear old Bob once put it, The Times They Are a-Changin’. Our problem was highlighted in the cancer field by the Californian biotechnology company Amgen who announced in 2012 that, over a 10 year period, they’d selected 53 ‘landmark’ cancer papers — and failed to replicate 47 of them! Around the same time a study by Bayer HealthCare found that only about one in four of published studies on potential drug targets was sufficiently strong to be worth following up.

More recently the leading science journal Nature found that almost three quarters of over 1,500 research scientists surveyed had tried to replicate someone else’s experiment and failed. It gets worse! More than half of them owned up to having failed to repeat one of their own experiments! Hooray! We have a result!! If you can’t repeat your own experiment either you’re sloppy (i.e., you haven’t done exactly what you did the first time) or you’ve highlighted the biological variability in the system you’re studying.

If you want an example of biological variation you need look no further than human conception and live births. Somewhere in excess of 50% of fertilized human eggs don’t make it to birth. In other words, if you do a ‘thought experiment’ in which a group of women carry some sort of gadget that flags when one of their eggs is fertilized, only between one in two and one in five of those ‘flagged’ will actually produce an offspring.

However you look at it, whether it’s biological variation, incompetence or plain fraud, we have a problem and Nature’s survey revealed that, to their credit, the majority of scientists agreed that there was a ‘significant crisis.’

The results of the survey by Nature from Baker 2016.

Predictably, but disturbingly for us in the biomedical fields, the greatest confidence in published results was shown by the chemists and physicists whereas only 50% of data in medicine were thought to be reproducible. Oh dear!

Tackling the problem in cancer

The Reproducibility Project: Cancer Biology, launched in 2013, is a collaboration between the Center for Open Science and Science Exchange.

The idea was to take 50 cancer papers published in leading journals and to attempt to replicate their key findings in the most rigorous manner. The number was reduced from 50 to 29 papers due to financial constraints and other factors but the aim remains to find out what affects the robustness of experimental results in preclinical cancer research.

It is a formidable project. Before even starting an experiment, the replication teams devised detailed plans, based on the original reports and, as the result of many hours effort, came up with a strategy that both they and the original experimenters considered was the best they could carry out. The protocols were then peer reviewed and the replication plans were published before the studies began.

Just to give an idea of the effort involved, a typical replication plan comprises many pages of detailed protocols describing reagents, cells and (where appropriate) animals to be used, statistical analysis and any other relevant items, as well as incorporating the input from referees.

The whole endeavor is, in short, a demonstration of scientific practice at its best.

To date ten of these replication studies have been published.

How are we doing?

The critical numbers are that 6 of the 10 replications ‘substantially reproduced’ the original findings, although in 4 of these some results could not be replicated. In 4 of the 10 replications the original findings were not reproduced.

The first thing to say is that a 60% rate of ‘substantial’ successful replication is a major improvement on the 11% to 25% obtained by the biotech companies. The most obvious explanation is that the massive, collaborative effort to tighten up the experimental procedures paid dividends.

The second point to note is that even when a replication attempt fails it cannot be concluded that the original data were wrong. The discrepancy may merely have highlighted how fiendishly tricky biological experimentation can be. The problem is that with living systems, be they cells or animals, you never have complete control. Ask anyone who has a cat.

More likely, however, than biological variation as a cause of discrepancies between experiments is human variation, aka personal bias.

This may come as a surprise to some but, rather than being ‘black and white’ much of scientific interpretation is subjective. Try as I might, can I be sure that in, say, counting stained cells I don’t include some marginal ones because that fits my model? OK: the solution to that is get someone else to do the count ‘blind’ — but I suspect that quite often that’s not done. However, there are even trickier matters. I do half a dozen repeats of an experiment and one gives an odd result (i.e., differs from the other five). Only I can really go through everything involved (from length of coffee breaks to changes in reagent stocks) and decide if there are strong enough grounds to ignore it. I do my best to avoid personal bias but … scientists are only human (fact!).

A closer look at failure

One of the failed replications is a particularly useful illustration for this blog. The replication study tackled a 2012 report that bacterial infection (specifically a bacterium, Fusobacterium nucleatum, that occurs naturally in the human oral cavity) is present in human colon cancers but not in non-cancerous colon tissues. It hit the rocks. They couldn’t detect F. nucleatum in most tumour samples and, when they did, the number of bugs was not significantly different to that in adjacent normal tissue.

Quite by chance, a few months ago, I described some more recent research into this topic in Hitchhiker or Driver?

I thought this was interesting because it showed that not only was F. nucleatum part of the microbiome of bowel cancer but that when tumour cells spread to distant sites (i.e., underwent metastasis) the bugs went along for the ride — raising the key question of whether they actually helped the critical event of metastasis.

So this latest study was consistent with the earlier result and extended it — indeed they actually showed that antibiotic treatment to kill the bugs slowed the growth of human tumour cells in mice.

Where does that leave us?

Well, helpfully, the Reproducibility Project also solicits comments from independent experts to help us make sense of what’s going on. Step forward Cynthia Sears of The Johns Hopkins Hospital. She takes the view that, although the Replication Study didn’t reproduce the original results, the fact that numerous studies have already found an association between F. nucleatum and human colon cancer means there probably is one — consistent with the work described in Hitchhiker or Driver?

One possible explanation for the discrepancy is that the original report studied colon tissue pairs (i.e., tumour and tumour-adjacent tissues) from colon cancer patients but did not report possibly relevant factors like age, sex and ethnicity of patients. In contrast, the replication effort included samples from patients with cancer (tumour and adjacent tissue) and non-diseased control tissue samples from age, sex and ethnicity matched individuals.

So we now know, as Dr. Sears helpfully remarks, that the association between F. nucleatum bugs and human colon cancer is more complicated first appeared! Mmm. And, just in case you were in any doubt, she points out that we need to know more about the who (which Fusobacterium species: there are 12 of them known), the where (where in the colon, where in the world) and the how (the disease mechanisms).

Can we do better?

In the light of all that the obvious question is: what can we do about the number of pre-clinical studies that are difficult if not impossible to reproduce? Answer, I think: not much. Rather than defeatist this seems to me a realistic response. There’s no way we could put in place the rigorous scrutiny of the Reproducibility Project across even a fraction of cancer research projects. The best we can do is make researchers as aware as possible of the problems and encourage them towards the very best practices — and assume that, in the end, the solid results will emerge and the rest will fall by the wayside.

Looking at the sharp end, it’s worth noting that, if you accept that some of the variability in pre-clinical experiments is down to the biological variation we mentioned above, it would at least be consistent with the wide range of patient responses to some cancer treatments. The reason for that, as Cynthia Sears didn’t quite put it, is that we just don’t know enough about how the humans we’re tinkering with actually work.

References

Baker, M. (2016). Is There a Reproducibility Crisis? Nature 533, 452-454.

Jarvis, G.E. (2017). Early embryo mortality in natural human reproduction: What the data say [version 2; referees: 1 approved, 2 approved with reservations] F1000Research 2017, 5:2765 (doi: 10.12688/f1000research.8937.2).

Monya Baker & Elie Dolgin (2017). Cancer reproducibility project releases first results. Nature 541, 269–270. doi:10.1038/541269a.

Begley, C.G. and Ellis, L.M. (2012). Drug development: Raise standards for preclinical cancer research. Nature 483, 531–533.

Prinz,F., Schlange,T. and Asadullah, K. (2011). Believe it or not: how much can we rely on published data on potential drug targets? NatureRev. Drug Discov. 10, 712.

Caveat Emptor

 

It must be unprecedented for publication of a scientific research paper to make a big impact on a significant sector of the stock market. But, in these days of ‘spin-off’ companies and the promise of unimaginable riches from the application of molecular biology to every facet of medicine and biology, perhaps it was only a matter of time. Well, the time came with a bang this June when the journal Nature Medicine published two papers from different groups describing essentially the same findings. Result: three companies (CRISPR Therapeutics, Editas Medicine and Intellia) lost about 10% of their stock market value.

I should say that a former student of mine, Anthony Davies, who runs the Californian company Dark Horse Consulting Inc., mentioned these papers to me before I’d spotted them.

What on earth had they found that so scared the punters?

Well, they’d looked in some detail at CRISPR/Cas9, a method for specifically altering genes within organisms (that we described in Re-writing the Manual of Life).

Over the last five years it’s become the most widely used form of gene editing (see, e.g., Seeing a New World and Making Movies in DNA) and, as one of the hottest potatoes in science, the subject of fierce feuding over legal rights, who did what and who’s going to get a Nobel Prize. Yes, scientists do squabbling as well as anyone when the stakes are high.

Nifty though CRISPR/Cas9 is, it has not worked well in stem cells — these are the cells that can keep on making more of themselves and can turn themselves in other types of cell (i.e., differentiate — which is why they’re sometimes called pluripotent stem cells). And that’s a bit of a stumbling block because, if you want to correct a genetic disease by replacing a defective gene with one that’s OK, stem cells are a very attractive target.

Robert Ihry and colleagues at the Novartis Institutes for Biomedical Research got over this problem by modifying the Cas9 DNA construct so that it was incorporated into over 80% of stem cells and, moreover, they could switch it on by the addition of a drug. Turning on the enzyme Cas9 to make double-strand breaks in DNA in such a high proportion of cells revealed very clearly that this killed most of them.

When cells start dying the prime suspect is always P53, a so-called tumour suppressor gene, switched on in response to DNA damage. The p53 protein can activate a programme of cell suicide if the DNA cannot be adequately repaired, thereby preventing the propagation of mutations and the development of cancer. Sure enough, Ihry et al. showed that in stem cells a single cut is enough to turn on P53 — in other words, these cells are extremely sensitive to DNA damage.

Gene editing by Cas9 turns on P53 expression. Left: control cells with no activation of double strand DNA breaks; right: P53 expression (green fluorescence) several days after switching on expression of the Cas9 enzyme. Scale bar = 100 micrometers. From Ihry et al., 2018.

In a corresponding study Emma Haapaniemi and colleagues from the Karolinska Institute and the University of Cambridge, using a different type of cell (a mutated line that keeps on proliferating), showed that blocking P53 (hence preventing the damage response) improves the efficiency of genome editing. Good if you want precision genome editing by risky as it leaves the cell vulnerable to tumour-promoting mutations.

Time to buy?!

As ever, “Let the buyer beware” and this certainly isn’t a suggestion that you get on the line to your stockbroker. These results may have hit share prices but they really aren’t a surprise. What would you expect when you charge uninvited into a cell with a molecular bomb — albeit one as smart as CRISPR/Cas9. The cell responds to the DNA damage as it’s evolved to do — and we’ve known for a long time that P53 activation is exquisitely sensitive: one double-strand break in DNA is enough to turn it on. If the damage can’t be repaired P53’s job is to drive the cell to suicide — a perfect system to prevent mutations accumulating that might lead to cancer. The high sensitivity of stem cells may have evolved because they can develop into every type of cell — thus any fault could be very serious for the organism.

It’s nearly 40 years since P53 was discovered but for all the effort (over 45,000 research papers with P53 in the title) we’re still remarkably ignorant of how this “Guardian of the Genome” really works. By comparison gene editing, and CRISPR/Cas9 in particular, is in its infancy. It’s a wonderful technique and it may yet be possible to get round the problem of the DNA damage response. It may even turn out that DNA can be edited without making double strand breaks.

So maybe don’t rush to buy gene therapy shares — or to sell them. As the Harvard geneticist George Church put it “The stock market isn’t a reflection of the future.” Mind you, as a founder of Editas Medicine he’d certainly hope not.

References

Ihry, R.J. et al. (2018). p53 inhibits CRISPR–Cas9 engineering in human pluripotent stem cells. Nature Medicine, 1–8.

Haapaniemi, E. et al. (2018). CRISPR–Cas9 genome editing induces a p53-mediated DNA damage response. Nature Medicine (2018) 11 June 2018.

Fantastic Stuff

 

It certainly is for Judy Perkins, a lady from Florida, who is the subject of a research paper published last week in the journal Nature Medicine by Nikolaos Zacharakis, Steven Rosenberg and their colleagues at the National Cancer Institute in Bethesda, Maryland. Having reached a point where she was enduring pain and facing death from metastatic breast cancer, the paper notes that she has undergone “complete durable regression … now ongoing for over 22 months.”  Wow! Hard to even begin to imagine how she must feel — or, for that matter, the team that engineered this outcome.

How was it done?

Well, it’s a very good example of what I do tend to go on about in these pages — namely that science is almost never about ‘ground-breaking breakthroughs’ or ‘Eureka’ moments. It creeps along in tiny steps, sideways, backwards and sometimes even forwards.

You may recall that in Self Help – Part 2, talking about ‘personalized medicine’, we described how in one version of cancer immunotherapy a sample of a patient’s white blood cells (T lymphocytes) is grown in the lab. This is a way of either getting more immune cells that can target the patient’s tumour or of being able to modify the cells by genetic engineering. One approach is to engineer cells to make receptors on their surface that target them to the tumour cell surface. Put these cells back into the patient and, with luck, you get better tumour cell killing.

An extra step (Gosh! Wonderful GOSH) enabled novel genes to be engineered into the white cells.

The Shape of Things to Come? took a further small step when DNA sequencing was used to identify mutations that gave rise to new proteins in tumour cells (called tumour-associated antigens or ‘neoantigens’ — molecular flags on the cell surface that can provoke an immune response – i.e., the host makes antibody proteins that react with (stick to) the antigens). Charlie Swanton and his colleagues from University College London and Cancer Research UK used this method for two samples of lung cancer, growing them in the lab to expand the population and testing how good these tumour-infiltrating cells were at recognizing the abnormal proteins (neo-antigens) on cancer cells.

Now Zacharakis & Friends followed this lead: they sequenced DNA from the tumour tissue to pinpoint the main mutations and screened the immune cells they’d grown in the lab to find which sub-populations were best at attacking the tumour cells. Expand those cells, infuse into the patient and keep your fingers crossed.

Adoptive cell transfer. This is the scheme from Self Help – Part 2 with the extra step (A) of sequencing the breast tumour. Four mutant proteins were found and tumour-infiltrating lymphocytes reactive against these mutant versions were identified, expanded in culture and infused into the patient.

 

What’s next?

The last step with the fingers was important because there’s almost always an element of luck in these things. For example, a patient may not make enough T lymphocytes to obtain an effective inoculum. But, regardless of the limitations, it’s what scientists call ‘proof-of-principle’. If it works once it’ll work again. It’s just a matter of slogging away at the fine details.

For Judy Perkins, of course, it’s about getting on with a life she’d prepared to leave — and perhaps, once in while, glancing in awe at a Nature Medicine paper that does not mention her by name but secures her own little niche in the history of cancer therapy.

References

McGranahan et al. (2016). Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 10.1126/science.aaf490 (2016).

Zacharakis, N. et al. (2018). Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer. Nature Medicine 04 June 2018.