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.

Cardiff Crock of Gold?

 

One of the oddities of science is that we are aware that we know little and understand less and yet manage to be surprised at frequent intervals when some bright spark discovers something new. So, surprised most of us indeed were by a paper from Andrew Sewell and colleagues at Cardiff University who have tracked down a hitherto unknown sub-population of white blood cells that may turn out to be extremely useful.

Before we get to the really exciting bit we need a follow-up word on CRISPR-Cas9, because that was what the Cardiff group used, and a clear picture of how the immune system works in cancer.

CRISPR-Cas in short

This method adapts a bacterial defence system for detecting and destroying invading viruses. It uses RNA guides to locate specific bits of DNA inside a cell, enabling molecular scissors to cut that section of DNA. This can disable a specific gene or allow a new gene to be inserted — described in Sharpening CRISPR and Re-writing the Manual of Life.

However, as well as being able to knock out genes or insert new ones, CRISPR has another feature. By using designer guide RNAs, CRISPR can scan the entire range of the genome. This DNA scanning feature can be scaled up to screen many genomic sites in parallel in one experiment. Synthesis of short fragments of nucleic acids (oligonucleotides) is carried out automatically using computer-controlled instruments (oligonucleotide synthesizers). The scale is astonishing: high-throughput DNA synthesis platforms can produce libraries of oligos (millions of them), each encoding a different guide RNA sequence and hence a different DNA target. Oligo libraries can be cloned into a lentiviral (a retrovirus) vector system for delivery to cells. This generates parallel, high-throughput, loss-of-function of specific genes from which their function can be inferred.

The immune system and cancer

The immune system can recognise cancer cells as abnormal and kill them. This happens because cancer cells (and cells infected by pathogens) break down proteins made within the cell and display those fragments on their surface. Thus cancer cells can ‘present’ their own antigens thereby stimulating an immune response that leads to their elimination by the immune system. Antigens on the cell surface bind to killer T cells (aka cytotoxic T cells) via the T-cell receptor (a complex of proteins on the T cell surface). This provokes the release of perforin that makes a pore, or hole, in the membrane of the infected cell. Cytotoxins then pass into the cell through this pore, destroying it. Almost all cell types can present antigens in some way and the loss of ‘antigen presentation’ is a major escape mechanism in cancer. It allows tumour cells to become ‘invisible’ and avoid immune attack by anti-tumour white blood cells.Scheme showing a cytotoxic T cell, (a type of lymphocyte aka a killer T cell, cytolytic T cell or CD8+ T cell), that kills cancer cells, interacting via its TCR with an antigenic peptide attached to an MHC molecule on the surface of a target cell. Granzymes are enzymes that cause apoptosis in targets cells.

What is the major histocompatibility complex?

Antigen-presenting cell (APCs) display antigen on their surface attached to major histocompatibility complexes (MHCs). MHCs are essential for the adaptive immune system to work, i.e. the sub-system of the immune response that eliminates pathogens. Human MHCs are also called the HLA (human leukocyte antigen) complex to distinguish it from other vertebrates. They’re encoded by a group of genes that are highly polymorphic — meaning that there are many different variant forms of the genes (alleles). The upshot of this is that no two individuals have exactly the same set of MHC molecules, with the exception of identical twins. This is the cause of transplant rejection wherein an immune response is switched on against HLA antigens expressed on APCs transferred along with the transplanted organ.

And now for the exciting news

The CRISPR screen used by Andrew Sewell and colleagues turned up a new type of T cell — one that differs from conventional T cells by presenting fragments of tumour proteins attached not to HLA proteins but to a different a receptor called MR1. The difference is critical because MR1 doesn’t vary between humans, unlike the highly variable HLAs. This appears to be why, in laboratory experiments, T cells with the MR1-seeking receptor can mediate killing of most types of human cancer cells without damaging healthy cells.

What they did was to take a sample of peripheral blood and select lymphocytes that proliferated in the presence of a cancer cell line (derived from a human lung cancer). They found that this cell clone kills a wide range of cancer cells in culture — so they used the CRISPR screening method to track down what the clone was targetting on cancer cells. Answer: MR1.

The novel T cell clone kills a broad range of tumour cells but does not kill cancer cell lines lacking MR1 or a range of healthy cells from various tissues. From Crowther et al., 2020.

The Cardiff group were further able to show that T-cells of melanoma patients modified to express this new TCR could destroy not only the patient’s own cancer cells, but also other patients’ cancer cells in the laboratory, regardless of HLA type (see Self Help – Part 2 and Gosh! Wonderful GOSH for how adoptive cell transfer works).

Transfer of the clone carrying the novel T cell receptor redirects patient T cells to recognize their own melanoma cells. Normal cells are unaffected. Black dots: + MR1; Grey dots: – MR1. From Crowther et al., 2020.

The data show (left) two T cell populations from two patients with metastatic melanoma. T cells transduced with the T cell receptor that binds MR1 recognized their own melanoma cells and killed them. Normal cells were unaffected regardless of MR1 expression.

These findings describe a TCR that exhibits pan-cancer cell recognition via the invariant MR1 molecule. Engineering T cells from patients that lacked detectable anti-cancer cell activity rendered them capable of killing the patients’ melanoma cells. However, these cells did not attack healthy cells so this method of genetic engineering, coupled with adoptive cell transfer, offers exciting opportunities for pan-cancer, T cell–mediated immunotherapy.

This discovery is most timely because, although CAR-T therapy is personalised to each patient, it targets only a few types of cancers and thus far has not worked for solid tumours.

CRISPR and related technologies are leading us into a new world in which Chinese scientists have already made the first CRISPR-edited human embryos and the first CRISPR-edited monkeys and, very recently in the first human trial of cells modified with CRISPR gene-editing technology, shown that the treatment is safe and lasting. This work, by You Lu at the West China Hospital in Chengdu, took immune cells from people with aggressive lung cancer and disabled the PD-1 gene. The PD-1 protein normally attenuates the immune system to prevent it attacking its own tissues but, as this reduces its anti-cancer capacity, knocking out PD-1 should overcome that restriction.

These advances are remarkable but we are still at the very beginning of gene therapy for cancer and the promise is almost limitless.

Reference

Crowther, M.D., Sewell, J.D. et al., (2020). Genome-wide CRISPR–Cas9 screening reveals ubiquitous T cell cancer targeting via the monomorphic MHC class I-related protein MR1. Nature Immunology  21,  178–185.

Sharpening CRISPR

 

The huge publicity given recently to genetic manipulation has meant that almost everyone has heard of CRISPR-Cas — it’s rapidly become the most popular way of editing genes from any organism. Guide RNA is designed to bind to a specific DNA sequence whereupon the recruitment of molecular scissors (the Cas9 enzyme) cuts the DNA at that sequence. The cell’s repair mechanisms will either glue the cuts back together or insert a novel stretch of DNA if that is delivered to the cell — we outlined the basic idea in Re-writing the Manual of Life.

There’s no doubt that, versatile and precise, the development of CRISPR in the last decade or so has been one of the great advances in the life sciences and in medicine it has led to ‘designer’ immune cells with enhanced abilities to seek and attack tumours, as we described in Gosh! Wonderful GOSH.

Seeing a New World described a rat model of retinitis pigmentosa, a genetic disease that is a major cause of inherited blindness and afflicts about one and a half million people worldwide (one in 4,000 in the UK). In this model it’s now possible to inject under the retina of rats with the disease an inert virus carrying the bits of CRISPR-Cas plus a replacement gene for the one damaged in retinitis pigmentosa. The eyesight of these treated mice recovered substantially in response to CRISPR.

Along the way George Church and colleagues have used the CRISPR-Cas system in bacteria to write Shakespeare’s sonnets in DNA and, for good measure, to make DNA movies (Making Movies in DNA).

Almighty Power showed how CRISPR could make almost 4,000 different versions (variants) of the BRCA1 protein and Shifting the Genetic Furniture described using the method to move DNA around within the nucleus.

Wonderful though all this is, CRISPR is not without its problems, most notably that it is not 100% efficient, there can be off-target effects and, as might be predicted, the act of cutting DNA activates TP53 which can be toxic to the cell (Caveat Emptor).

CRISPR base editing

The most recent advance in genome editing uses parts of CRISPR together with other enzymes to insert point mutations into cellular DNA or RNA directly without making double-stranded DNA breaks. The method still uses guide RNAs for targeting but adds a second enzyme to Cas9. Depending on the enzyme either cytidine is converted to thymidine or adenosine to guanosine (A to G mutation).

Base editing by CRISPR. The CRISPR system is modified by coupling another enzyme to Cas9 (or to ‘dead’ Cas9 — dCas9). The enzyme shown is cytidine deaminase. The PAM site (protospacer adjacent motif) is a short DNA sequence following the cleavage site and is required for a Cas nuclease to cut. Alternatively, an E.coli enzyme can be used to make an adenine base editor. From https://www.addgene.org/crispr/base-edit/

Treating human disease by CRISPR

Leber Congenital Amaurosis (LCA) is a spectrum of inherited conditions that cause poor vision due to a defect in the cells that detect light in the retina (rods and cones). A press release on October 10, 2019 described LCA patients treated with sepofarsen (QR-110) experiencing a rapid and durable improvement in vision. Sepofarsen uses chemically modified nucleotides complementary to specific mRNAs in the cell (it’s an ‘antisense’ therapy). Sepofarsen tackles a specific mutation in the CEP20 gene by repairing the mRNA, hence permitting a normal CEP20 protein to be made. The drug is administered by injections into the vitreous of the eye (intra-vitreal injections).

A further step in using direct administration of CRISPR–Cas9 gene therapy into the body to treat LCA has come in the form of a trial named BRILLIANCE. Two pharmaceutical companies, Editas and Allergan, are co-operating in this endeavour using EDIT-101, a CRISPR-based gene-editing treatment delivered by an adeno-associated virus, AGN-151587. As with sepofarsen, the components of the gene-editing system are injected directly into the eye, near photoreceptor cells. The first patient has been treated in a phase 1/2 trial of AGN-151587, receiving a single subretinal injection of AGN-151587 and details of the ongoing trial can be found on www.clinicaltrials.gov.

These early trials are not, of course, ‘fixing’ cancer but they do appear to give a ‘proof of principle’ that it should be possible to use gene editing to re-activate, for example, mutated tumour suppressors. Watch this space!!

 

 

Be amazed

 

Back in May 2018 we reported the first output from the Pan-Cancer Atlas, a massive undertaking that evolved from The Cancer Genome Atlas, itself a huge project aiming to set up a genetic data-base for three cancer types: lung, ovarian, and glioblastoma.

The next instalment from the Pan-Cancer Analysis of Whole Genomes (PCAWG) has just appeared featuring the analysis of a staggering 2,658 whole-cancer genomes and their matching, normal tissues across 38 tumour types and it has reminded us, yet again, of nature’s capacity to surprise. The first finding was that, on average, cancer genomes contained four or five driver mutations when coding and non-coding genomic elements were combined. That’s roughly consistent with the accepted estimate over the last few decades. What was unexpected, however, was that in around 5% of cases no drivers were identified, suggesting that there are more of these mutations to be discovered. Also somewhat surprising is that chromothripsis, the single catastrophic event producing simultaneously many variants in DNA, is frequently an early event in tumour evolution.

The analyses also revealed several mechanisms by which the ends of chromosomes in cancer cells are protected from telomere attrition and that variants transmitted in the germline can affect subsequently acquired patterns of somatic mutation.

A glimpse of the data

The panorama of driver mutations includes the summary below of tumour-suppressor genes with biallelic inactivation (i.e., mutation of one allele (copy) followed by gene deletion of the remaining allele) in 10 or more patients. Familiar tumour suppressors are prominent on the left hand side, as expected. These include TP53 (the guardian of the genome) and the tumour suppressors CDKN2A and CDKN2B (cyclin-dependent kinase inhibitors 2A and 2B) that regulate the cell cycle.

Tumour-suppressor genes for which both copies of the gene (alleles) are inactivated in 10 or more patients. GR = genomic rearrangement, i.e. chromosome breakage. From The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium.

Aneuploidy in the genome of a tumour without known drivers. Each row is an individual tumour: the boxes show chromosome loss (blue) or gain (red). The cancer is a rare kidney tumour (chromophobe renal cell carcinoma). From The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium.

Two tumour types had a surprisingly high fraction of patients without identified driver mutations: 44% for a rare type of kidney cancer (chromophobe renal cell carcinoma) and 22% in a rare pancreatic neuroendocrine cancer. It turned out (as shown in the above figure) that there was a striking loss or gain of chromosomes — called aneuploidy — in the cells of these cancers. This suggests that wholesale loss of tumour suppressor genes or gain of oncogenic function was providing the ‘drivers’ for these cancers.

The genomic cancer message

We should first acknowledge the mind-boggling effort and organization involved in collecting thousands of paired samples, sequencing them and analyzing the output. However, the value of these massive projects is beginning to emerge — and the news is mixed.

One critical trend is that genomic analysis is re-defining the way cancers are classified. Traditionally they have been grouped on the basis of the tissue of origin (breast, bowel, etc.) but this will gradually be replaced by genetic grouping, reflecting the fact that seemingly unrelated cancers can be driven by common pathways.

Perhaps the most encouraging thing to come out of the genetic changes driving these tumours is that for about half of them potential treatments are already available. That’s quite a surprise but it doesn’t mean that hitting those targets will actually work as anti-cancer strategies. Nevertheless, it’s a cheering point that the output of this phenomenal project may, as one of the papers noted, serve as a launching pad for real benefit in the not too distant future.

On the other hand, the intention of precision medicine is to match patients to therapies on the basis of genomics and, notwithstanding the above point, the consortium notes that “A major barrier to evidence-based implementation is the daunting heterogeneity of cancer chronicled in these papers, from tumour type to tumour type, from patient to patient, from clone to clone and from cell to cell. Building meaningful clinical predictors from genomic data can be achieved, but will require knowledge banks comprising tens of thousands of patients with comprehensive clinical characterization. As these sample sizes will be too large for any single funding agency, pharmaceutical company or health system, international collaboration and data sharing will be required.”

See for yourself

The PCAWG landing page (http://docs.icgc.org/pcawg/) provides links to several data resources for interactive online browsing, analysis and download of PCAWG data.

Reference

The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes.

 

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

Non-Container Ships

 

A question often asked about cancer is: “Can you catch it from someone else?” Answer: “No you can’t.” But as so often in cancer the true picture requires a more detailed response — something that may make scientists unpopular but it’s not our fault! As Einstein more or less said “make it as simple as possible but no simpler.”

No … but …

So we have to note that some human cancers arise from infection — most notably by human immunodeficiency viruses (HIV) that can cause acquired immunodeficiency syndrome (AIDS) and lead to cancer and by human papillomavirus infection (HPV) that can give rise to lesions that are the precursors of cervical cancer. But in these human cases it is a causative agent (i.e. virus) that is transmitted, not tumour cells.

However, there are three known examples in mammals of transmissible cancers in which tumour cells are spread between individuals: the facial tumours that afflict Tasmanian devils, a venereal tumour in dogs and a sarcoma in Syrian hamsters.

Not to be outdone, the invertebrates have recently joined this select club and we caught up with this extraordinary story in Cockles and Mussels, Alive, Alive-O! It’s a tale of clams and mussels and various other members of the huge family of bivalve molluscs — (over 15,000 species) — that began 50 years ago when some, living along the east and west coasts of North America and the west coast of Ireland, started to die in large numbers. It turned out that the cause was a type of cancer in which some blood cells reproduce in an uncontrolled way. It’s a form of leukemia: the blood turns milky and the animals die, in effect, from asphyxiation. In soft-shell clams the disease had spread over 1,500 km from Chesapeake Bay to Prince Edward Island but the really staggering fact came from applying the power of DNA sequencing to these little beach dwellers. Like all cancers the cause was genetic damage — in this case the insertion of a chunk of extra DNA into the clam genome. But amazingly this event had only happened once: the cancer had spread from a single ‘founder’ clam throughout the population. The resemblance to the way the cancer spreads in Tasmanian devils is striking.

Join the club

In 2016 four more examples of transmissible cancer in bivalves were discovered — in mussels from British Columbia, in golden carpet shell clams from the Spanish coast and in two forms in cockles. As with the soft-shell clams, DNA analysis showed that the disease had been transmitted by living cancer cells, descended from a single common ancestor, passing directly from one animal to another. In a truly remarkable twist it emerged that cancer cells in golden carpet shell clams come from a different species — the pullet shell clam — a species that, by and large, doesn’t get cancer. So they seem to have come up with a way of resisting a cancer that arose in them, whilst at the same time being able to pass live tumour cells on to another species!!

Map of the spread of cancer in mussels. This afflicts the Mytilus group of bivalve molluscs (i.e. they have a shell of two, hinged parts). BTN = bivalve transmissible neoplasias (i.e. cancers). BTN 1 & BTN2 indicates that two separate genetics events have occurred, each causing a similar leukemia. The species involved are Mytilus trossulus (the bay mussel), Mytilus chilensis (the Chilean blue mussel) and Mytilus edulis (the edible blue mussel). The map shows how cancer cells have spread from Northern to Southern Hemispheres and across the Atlantic Ocean. From Yonemitsu et al. (2019).

Going global

In the latest instalment Marisa Yonemitsu, Michael Metzger and colleagues have looked at two other species of mussel, one found in South America, the other in Europe. DNA analysis showed that the cancers in the South American and European mussels were almost genetically identical and that they came from a single, Northern hemisphere trossulus mussel. However, this cancer lineage is different from the one previously identified in mussels on the southern coast of British Columbia.

Unhappy holidays

It seems very likely that some of these gastronomic delights have hitched a ride on vessels plying the high seas so that carriers of the cancer have travelled the oceans. Whilst one would not wish to deny them the chance of a holiday, this is serious news because of the commercial value of seafood.

It’s another example of how mankind’s advances, in this case being able to build things like container ships with attractive bottoms, for molluscs at least, can lead to unforeseen problems.

This really bizarre story has only come light because of the depletion of populations of clams and mussels in certain areas but it certainly carries the implication that transmissible cancers may be relatively common in marine invertebrates.

Reference

Yonemitsu, M.A. et al. (2019). A single clonal lineage of transmissible cancer identified in two marine mussel species in South America and Europe. eLife 2019;8:e47788 DOI: 10.7554/eLife.47788.

The Power of Flower

 

We know we don’t ‘understand cancer’ — for if we did we would at least be well on the way to preventing the ten million annual deaths from these diseases and perhaps even stymieing their appearance in the first place. But at least, after many years of toil by thousands of curious souls, we might feel brave enough to describe the key steps by which it comes about.

Here goes!

Our genetic material, DNA, carries a code of four different units (bases) that enables cells to make twenty-thousand or so different types of proteins. Collectively these make cells — and hence us — ‘work’. An indicator of protein power is that we grow from single, fertilized cells to adults with 50 trillion cells. That phenomenal expansion involves, of course, cells growing and dividing to make more of themselves — and, along the way, a bit of cell death too. The fact that there are nearly eight billion people on planet earth testifies to the staggering precision with which these proteins act.

Nobody’s perfect

As sports fans will know, the most successful captain in the history of Australian rugby, John Eales, was nicknamed ‘Nobody’ because ‘Nobody’s perfect’. Well, you might care to debate the infallibility of your sporting heroes but when it comes to their molecular machinery, wondrous though it is, perfect it is not.

Evidence: from the teeming eight billion there emerges every year 18 million new cancer cases (that’s about one in every 444). And cancers are, of course, abnormal cell growth: cells growing faster than they should or growing at the wrong time or in the wrong place — any of which means that some of the masterful proteins have suffered a bit of a malfunction, as the computer geeks might say.

How can that happen?

Abnormal protein activity arises from changes in DNA (mutations) that corrupt the normal code to produce proteins of greater or lesser activity or even completely novel proteins.

These mutations may be great or small: changes in just one base or seismic fragmentation of entire chromosomes. But the key upshot is that the cell grows abnormally because regulatory proteins within the cell have altered activity. Mutations can also affect how the cell ‘talks’ to the outside world, that is, the chemical signals it releases to, for example, block immune system killing of cancer cells.

Clear so far?

Mutations can change how cells proliferate, setting them free of normal controls and launching their career as tumour cells and, in addition, they can influence the cell’s environment in favour of unrestricted growth.

The latter tells us that cancer cells cooperate with other types of cell to advance their cause but now comes a remarkable discovery of a hitherto unsuspected type of cellular collaboration. It’s from Esha Madan, Eduardo Moreno and colleagues from Lisbon, Arkansas, St. Louis, Indianapolis, Omaha, Dartmouth College, Zurich and Sapporo who followed up a long-known effect in fruit flies (Drosophila) whereby the cells can self-select for fitness to survive.

Notwithstanding the fact that flies do it, the idea of a kind of ‘cell fitness test’ is novel as far as human cells go — but it shouldn’t really surprise us, not least because our immune system (the adaptive immune system) features much cooperation between different types of cell to bring about the detection and removal of foreign or damaged cells.

Blooming science

So it’s been known for over forty years that Drosophila carries out cell selection based on a ‘fitness fingerprint’ that enables it to prevent developmental errors and to replace old tissues with new. However, it took until 2009 before the critical protein was discovered and, because mutant forms of this protein gave rise to abnormally shaped nerve cells that looked like bunches of flowers, Chi-Kuang Yao and colleagues called the gene flower‘.

Cells can make different versions of flower proteins (by alternative splicing of the gene) the critical ones being termed ‘winner’ and ‘loser’ because when cells carrying winner come into contact with cells bearing loser the latter die and the winners, well, they win by dividing and filling up the space created by the death of losers.

The effect is so dramatic that Madan and colleagues were able to make some stunning movies of the switch in cell populations that occured when they grew human breast cancer cells engineered to express different version of flower tagged with red or green fluorescent labels.

Shift in cell populations caused by two types of flower proteins. 

Above are images at time zero and 24 h later of co-cultures of cells expressing  green and red proteins (losers and winners). From Madan et al. 2019.

Click here to see the movie on the Nature website.

Winner takes almost all

The video shows high-resolution live cell imaging over a 24 hour period compressed into a few seconds. Cells expressing the green protein (hFwe1 (GFP)) were co-cultured with red cells (hFwe2 (RFP)). Greens are losers, reds winners. As the movie progresses you can see the cell population shifting from mainly green to almost entirely red, as the first and last frames (above) show.

How does flower power work?

Flower proteins form channels across the outer membrane of the cell that permit calcium flow, and it was abnormal calcium signalling that caused flowers to bloom in Drosophila nerves. It would be reasonable to assume that changes in calcium levels are behind the effects of flower on cancer cells. Reasonable but wrong, for Madan & Co were able to rule out this explanation. At the moment we’re left with the rather vague idea that flower proteins mediate competitive interactions between cells and these determine whether cells thrive and proliferate or wither and die.

Does this really happen in human cancers?

Madan and colleagues looked at malignant and benign human tumours and found that there was more ‘winner’ flower protein in the former than the latter and that ‘loser’ levels were higher in normal cells next to a tumour than further away. Both consistent with the notion that tumour cells express winner and this induces loser in nearby normal cells leading to their death. What’s more they reproduced this effect in mice by transplanting human breast cancer cells expressing winner.

So there we are! After all this time a variant on how cancer cells can manipulate their surroundings to promote the development of tumours. Remarkable though this finding is, in a way that is familiar it’s just the beginning of this story. We don’t know how flower proteins work in giving cancers a helping hand and we don’t know how effective they are. Until we answer those questions it would be premature to try to come up with therapies to block their effect.

But it is a moment to sit back and reflect on the astonishing complexity of living organisms and their continuing capacity to surprise.

Reference

Madan, E. et al. (2019). Flower isoforms promote competitive growth in cancer. Nature 572, 260-264.

Yao, C-K., et al., (2009). A synaptic vesicle-associated Ca2+ channel promotes endocytosis and couples exocytosis to endocytosis. Cell 138, 947–960.

Breaking Up Is Hard To Do

 

Thus Neil Sedaka, the American pop songster back in the 60s. He was crooning about hearts of course but since then we’ve discovered that for our genetic hearts — our DNA — breaking up is not that tough and indeed it’s quite common.

A moving picture worth a thousand words

When I’m trying to explain cancer to non-scientists I often begin by showing a short movie of a cell in the final stages of dividing to form two identical daughter cells. This is the process called mitosis and the end-game is the exciting bit because the cell’s genetic material, its DNA, has been duplicated and the two identical sets of chromosomes are lined up in the middle of the cell. There ensues a mighty tug-of-war as cables (strands of proteins) are attached to the chromosomes to rip them apart, providing a separate genome for each new cell when, shortly after, the parent cell splits into two. When viewed as a speeded-up movie it’s incredibly dramatic and violent — which is why I show it because it’s easy to see how things could go wrong to create broken chromosomes or an unequal division of chromosomes (aneuploidy). It’s the flip side if you like to the single base changes (mutations) — the smallest damage DNA can suffer — that are a common feature of cancers.

In Heir of the Dog we showed pictures of normal and cancerous chromosomes that had been tagged with coloured markers to illustrate the quite staggering extent of “chromosome shuffling” that can occur.

Nothing new there

We’ve known about aneuploidy for a long time. Over 20 years ago Bert Vogelstein and his colleagues showed that the cells in most bowel cancers have different numbers of chromosomes and we know now that chromosomal instability is present in most solid tumours (90%).

Knowing it happens is one thing: being able to track it in real time to see how it happens is another. This difficulty has recently been overcome by Ana C. F. Bolhaqueiro and her colleagues from the Universities of Utrecht and Groningen who took human colorectal tumour cells and grew them in a cell culture system in the laboratory that permits 3D growth — giving rise to clumps of cells called organoids.

Scheme representing how cells grown as a 3D clump (organoid) can be sampled to follow chromosomal changes. Cells were taken from human colon tumours and from adjacent normal tissue and grown in dishes. The cells were labelled with a fluorescent tag to enable individual chromosomes to been seen by microscopy as the cells divided. At time intervals single cells were selected and sequenced to track changes in DNA. From Johnson and McClelland 2019.

Genetic evolution in real time

As the above scheme shows, the idea of organoids is that their cells grow and divide so that at any time you can select a sample and look at what’s happening to its DNA. Furthermore the DNA can be sequenced to pinpoint precisely the genetic changes that have occurred.

It turned out that cancer cells often make mistakes in apportioning DNA between daughter cells whereas such errors are rare in normal, healthy cells.

It should be said that whilst these errors are common in human colon cancers, a subset of these tumours do not show chromosomal instability but rather have a high frequency of small mutations (called microsatellite instability). Another example of how in cancer there’s usually more than one way of getting to the same end.

Building bridges …

The most common type of gross chromosomal abnormality occurs when chromosomes fuse via their sticky ends to give what are called chromatin bridges (chromatin just means DNA complete with all the proteins normally attached to it). Other errors can give rise to a chromosome that’s become isolated — called a lagging chromosome, it’s a bit like a sheep that has wandered off from the rest of the flock. As the cell finally divides and the daughter cells move apart, DNA bridges undergo random fragmentation.

… but where to …

Little is known about how cells deal with aneuploidy and the extent to which it drives tumour development. This study showed that variation in chromosome number depends on the rate at which chromosomal instability develops and the capacity of a cell to survive in the face of changes in chromosome number. More generally for the future, it shows that the organoid approach offers an intriguing opening for exploring this facet of cancer.

Reference

Bolhaqueiro, A.C.F. et al. (2019). Ongoing chromosomal instability and karyotype evolution in human colorectal cancer organoids. Nature Genetics 51, 824–834.

Lengauer, C. et al., (1997). Genetic instability in colorectal cancers. Nature 386, 623-627.

Johnson, S.C. and McClelland, S.E. (2019). Watching cancer cells evolve. Nature 570, 166-167.

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.

Sticky Cancer Genes

 

In the previous blog I talked about Breath Biopsy — a new method that aims to detect cancers from breath samples. I noted that it could end up complementing liquid biopsies — samples of tumour cell DNA pulled out of a teaspoon of blood — both being, as near as makes no difference, non-invasive tests. Just to show that there’s no limit to the ingenuity of scientists, yet another approach to the detection problem has just been published — this from Matt Trau and his wonderful team at The University of Queensland.

This new method, like the liquid biopsy, detects DNA but, rather than the sequence of bases, it identifies an epigenetic profile — that is, the pattern of chemical tags (methyl groups) attached to bases. As we noted in Cancer GPS? cancer cells often have abnormal DNA methylation patterns — excess methylation (hypermethylation) in some regions, reduced methylation in others. Methylation acts as a kind of ‘fine tuner’, regulating whether genes are switched on or off. In the methylation landscape of cancer cells there is an overall loss of methylation but there’s an increase in regions that regulate the expression of critical genes. This shows up as clusters of methylated cytosine bases.

Rather helpfully, a little while ago in Desperately SEEKing … we talked about epigenetics and included a scheme showing how differences in methylation clusters can identify normal cells and a variety of cancers and how these were analysed in the computer program CancerLocator.

The Trau paper has an even better scheme showing how the patterns of DNA decoration differ between normal and cancer cells and how this ‘methylscape’ (methylation landscape) affects the physical behaviour of DNA.

How epigenetic changes affect DNA. Scheme shows methylation (left: addition of a methyl group to a cytosine base in DNA) in the process of epigenetic reprogramming in cancer cells. This change in the methylation landscape affects the solubility of DNA and its adsorption by gold (from Sina et al. 2018).

Critically, normal and cancer epigenomes differ in stickiness — affinity — for metal surfaces, in particular for gold. In a clever ploy this work incorporated a colour change as indicator. We don’t need to bother with the details — and the result is easy to describe. DNA, extracted from a small blood sample, is added to water containing tiny gold nanoparticles. The colour indicator makes the water pink. If the DNA is from cancer cells the water retains its original colour. If it’s normal DNA from healthy cells the different binding properties turns the water blue.

By this test the Brisbane group have been able to identify DNA from breast, prostate and colorectal cancers as well as from lymphomas.

So effective is this method that it can detect circulating free DNA from tumour cells within 10 minutes of taking a blood sample.

The aim of the game — and the reason why so much effort is being expended — is to detect cancers much earlier than current methods (mammography, etc.) can manage. The idea is that if we can do this not weeks or months but perhaps years earlier, at that stage cancers may be much more susceptible to drug treatments. Trau’s paper notes that their test is sensitive enough to detect very low levels of cancer DNA — not the same thing as early detection but suggestive none the less.

So there are now at least three non-invasive tests for cancer: liquid biopsy, Breath Biopsy and the Queensland group’s Methylscape, and in the context of epigenetics we should also bear in mind the CancerLocator analysis programme.

Matt Trau acknowledges, speaking of Methylscape, that “We certainly don’t know yet whether it’s the holy grail for all cancer diagnostics, but it looks really interesting as an incredibly simple universal marker for cancer …” We know already that liquid biopsies can give useful information about patient response to treatment but it will be a while before we can determine how far back any of these methods can push the detection frontier. In the meantime it would be surprising if these tests were not being applied to age-grouped sets of normal individuals — because one would expect the frequency of cancer indication to be lower in younger people.

From a scientific point of view it would be exciting if a significant proportion of ‘positives’ was detected in, say, 20 to 30 year olds. Such a result would, however, raise some very tricky questions in terms of what, at the moment, should be done with those findings.

Reference

Abu Ali Ibn Sina, Laura G. Carrascosa, Ziyu Liang, Yadveer S. Grewal, Andri Wardiana, Muhammad J. A. Shiddiky, Robert A. Gardiner, Hemamali Samaratunga, Maher K. Gandhi, Rodney J. Scott, Darren Korbie & Matt Trau (2018). Epigenetically reprogrammed methylation landscape drives the DNA self-assembly and serves as a universal cancer biomarker. Nature Communications 9, Article number: 4915.