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Calum Gabbutt @calumgabbutt.bsky.social · Sep 12

Thanks Marc!

Reposted by Calum Gabbutt

Trevor Graham @trevorgraham.bsky.social · Sep 10

Studying cancer evolution needs multi-region or single cell seq for phylogenetics, right? Amazingly (I think!) we found single-sample bulk methylation suffices, via analysis of "fluctuating methylation". In @nature.com today led by brilliant @calumgabbutt.bsky.social www.nature.com/articles/s41...

Fluctuating DNA methylation tracks cancer evolution at clinical scale - Nature

Cancer evolutionary dynamics are quantitatively inferred using a method, EVOFLUx, applied to fluctuating DNA methylation.

www.nature.com

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Calum Gabbutt @calumgabbutt.bsky.social · Sep 10

This was a massively collaborative project and it was a pleasure to work with such amazing researchers, but particular thanks to Inaki Martin-Subero, Martí Duran-Ferrer @idibaps.bsky.social and @trevorgraham.bsky.social

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Calum Gabbutt @calumgabbutt.bsky.social · Sep 10

Finally, fCpGs record clonal dynamics over time. In two patients with Richter transformation (RT), the emergence of an altered phenotype with dismal outcomes, we inferred that the RT clone diverged from the non-RT lineage over 30 years prior to its clinical manifestation! (6/7)

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Calum Gabbutt @calumgabbutt.bsky.social · Sep 10

In chronic lymphocytic leukaemia (CLL) the high-risk U-CLL subtype had much higher growth rates than the low-risk M-CLL subtype. Stratifying by growth rate within these groups was highly prognostic of the time to first treatment. (5/7)

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Calum Gabbutt @calumgabbutt.bsky.social · Sep 10

Across 2000 lymphoid cancer samples, we found staggering heterogeneity between different diseases and molecular subtypes! Paediatric (ALL) grew much more rapidly than adult cancers, and the aggressive 11q23/MLL subtype grew even faster than the other subtypes. (4/7)

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Calum Gabbutt @calumgabbutt.bsky.social · Sep 10

We designed a computational method, EVOFLUx, to infer the early evolutionary history of a cancer from these data. For instance: when did the most recent common ancestor emerge and how rapidly was the cancer growing at that time? Is the cancer undergoing a subclonal expansion? (3/7)

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Calum Gabbutt @calumgabbutt.bsky.social · Sep 10

We used DNA methylation “evolving barcodes” to record the lineage of cells, which we termed fCpGs. These could be measured using low-cost, bulk methylation arrays. The clonal dynamics of cells are recorded in the patterns of these fCpGs (2/7)

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Calum Gabbutt @calumgabbutt.bsky.social · Sep 10

Cancer is an evolutionary disease, but does knowing a cancer’s evolutionary past help predict its future? Out today in @nature, we learnt the evolution of 2000 lymphoid cancers and found it was highly correlated with clinical outcomes! (1/7)
rdcu.be/eFrrc

Fluctuating DNA methylation tracks cancer evolution at clinical scale

Nature - Cancer evolutionary dynamics are quantitatively inferred using a method, EVOFLUx, applied to fluctuating DNA methylation.

rdcu.be

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Reposted by Calum Gabbutt

I-X @imperial-ix.bsky.social · Jul 18

🚀 AI in Science Fellowships – Applications Now Open!

The I-X Centre for AI in Science is recruiting up to 19 fellows to join their prestigious programme and accelerate artificial intelligence research in Engineering, Natural and Mathematical Sciences.

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This link will take you to a page that’s not on LinkedIn

lnkd.in

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Calum Gabbutt @calumgabbutt.bsky.social · Jul 18

Imperial's Schmidt AI in Science fellowships are now open! As a current fellow, I can highly recommend applying for these prestigious and enriching awards. No prior AI experience needed, just a scientific problem suited to AI. For cancer researchers there are dedicated joint positions with the ICR.

Apply | Research groups | Imperial College London

www.imperial.ac.uk

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Reposted by Calum Gabbutt

Trevor Graham @trevorgraham.bsky.social · Jul 15

Schmidt Fellowships for #AI in #cancer research 2025 round is now open. These are pathway to independence fellowships between @icr.ac.uk & @imperialcollegeldn.bsky.social that support fellows to be competitive for faculty jobs at the end of the 2 year funding. www.imperial.ac.uk/jobs/search-...

Search jobs for external candidates | Jobs | Imperial College London

www.imperial.ac.uk

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Reposted by Calum Gabbutt

Rob Noble @robjohnnoble.bsky.social · Jul 14

New preprint! Let me tell you a story about trees, caterpillars, brooms, entropy, and getting scooped by 50 years.

Rooted trees of all shapes and sizes crop up all over biology, computing and elsewhere. How can we best compare the shapes of these myriad trees? 1/14

arxiv.org/abs/2507.08615

Darwin's famous sketch of a rooted tree, representing speciation

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Reposted by Calum Gabbutt

Alexander Stein @alexsteinresearch.bsky.social · May 29

Interested in population genetics of cancer?

If so, have a look at our manuscript accepted by @genetics-gsa.bsky.social, in which we provide a theoretical assessment of the genetic makeup of cancers before and after treatment!

Benjamin Werner @benjaminwerner.bsky.social · May 29

Very happy that @alexsteinresearch.bsky.social manuscript on the patterns of genetic heterogeneity before and after treatment is out now:

academic.oup.com/genetics/adv...

We build on and expand the population genetics theory of gITH.

Very worth a read if you are interested in somatic evolution.

On the patterns of genetic intra-tumour heterogeneity before and after treatment

Abstract. Genetic intra-tumour heterogeneity (gITH) is a universal property of all cancers. It emerges from the interplay of cell division, mutation accumu

academic.oup.com

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Reposted by Calum Gabbutt

Trevor Graham @trevorgraham.bsky.social · May 22

Calling data scientists: we have opening in our Data Science core @icr.ac.uk to lead work around cancer spatial biology and single cell analysis. These are staff scientist type positions, ideal for someone who wants to help drive computational research. Apply here: jobs.icr.ac.uk/vacancies/12...

Data Scientist in Sutton | The Institute of Cancer Research

View details and apply for this Data Scientist vacancy in Sutton. Salary : Salary range £39,805 to £49,023 (depending on the experience) Reporting to: Professor Trevor Graham ...

jobs.icr.ac.uk

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Calum Gabbutt @calumgabbutt.bsky.social · Mar 24

If you're a PhD student interested in using maths to understand cancer, this HCEMM summer school in Szeged, Hungary, is an excellent opportunity.

Registration is free and local costs are covered, so apply before 15th April.

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Calum Gabbutt @calumgabbutt.bsky.social · Mar 12

This week-long summer school looks set to be an excellent opportunity for to learn about cancer evolution!

Bursaries are available for those who require financial assistance, deadline 1st April.

Wellcome Connecting Science Learning and Training @eventswcs.bsky.social · Feb 13

Working in #CancerBiology?

Join us at our expert-led #EBECancer25 course, to discover how insights on the #evolutionary and ecological aspects of #cancer are shaping the future for improved clinical treatments.💊

📅 30 June-3 July 2025

⏰Apply by 1 April!
📎bit.ly/40nLdDD

@sysbiocurie.bsky.social

Wellcome Connecting Science discussion course
Evolutionary Biology and Ecology of Cancer
Course dates: 30 June-3 July 2025
Location: Wellcome Genome Campus, UK

Application and bursary deadline: 1 April 2025

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 14

Darryl never even made it to Twitter, so Bluesky may be a stretch! Really glad you liked the pre-print, if you've got any questions or would like to chat, please feel free to email me at [email protected]

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 13

And of course, thanks to all our institutes: the ICR, BCI, IDIBAPS, ASU, CIBERONC, Hospital Clínic de Barcelona, Uppsala University, USZ, Universitat de Barcelona, UCL, USC and ICREA. (9/9)

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 13

A big thanks to Martí Duran Ferrer, Heather Grant, Diego Mallo, Ferran Nadeu, Jacob Househam, Neus Villamor, Olga Krali, Jessica Nordlund, Thorsten Zenz, Elias Campo, Armando Lopez-Guillermo, Jude Fitzgibbon, Chris P Barnes, Darryl Shibata, José I Martin-Subero and @trevorgraham.bsky.social! (8/9)

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 13

To conclude, we present a cheap and general new technique to measure evolution in cancer from single-timepoint, bulk samples. This links basic cancer evolution research directly to translational medicine and may allow us to focus treatment on just those who need it. (7/9)

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 13

In B-ALL, MCL and CLL, different clinical subtypes had markedly different growth rates and effective pop sizes. In CLL, the growth rate was highly prognostic of time to first treatment, whilst the pop size was a better predictor of over survival. (6/9)

The inferred growth rate of the typically more aggressive U-CLL cancers is greater than that of the often indolent M-CLL cancers.

A Kaplan Meier curve showing the inferred growth rate stratifies time to first treatment in CLL patients, controlling for IGHV mutational status.

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 13

We also able to infer the phylogenetic relationship between longitudinal samples. In CLL, some patients undergo Richter transformation (RT), the emergence of an aggressive phenotype – this lineage diverged >30 years prior to clinical detection in 2 CLL patients. (5/9)

$A: Timeline of two CLL patients with samples collected longitudinally, annotated with treatment received. Circles represent methylation array (blue: 450K, orange EPIC), squares represent whole genome sequencing, treatment is represented with a green vertical line and Richter transformation (RT) is represented with a vertical pink line. B: (left) The reconstructed phylogenies of the relationship between samples, annotated with the clinical classification of each sample. The black triangles represent the time that occurred since the most recent common ancestor, taken as the posterior median of T-τ from the single-sample EVOFLUx inferences. (right) A heatmap representing the 978 fCpG loci, with the colour a representing the fraction methylated (0% blue, 100% red).$

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 13

Applying EVOFLUx to quantify the evolution of 1,976 lymphoid malignancies, we found widespread heterogeneity between and within cancer types. Our subclonal inference was validated with matched deep whole exome sequencing. (4/9)

A scatterplot showing the inferred evolutionary parameters of 1,976 lymphoid malignancies.

Boxplots comparing the distribution of subclonal weightings inferred by EVOFLUx in samples called as neutral vs under subclonal selection via the WES data.

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Calum Gabbutt @calumgabbutt.bsky.social · Nov 13

We developed a new computational method (EVOFLUx) to infer a cancer’s evolutionary history from methylation data. We can learn how quickly a cancer is growing, when its most recent common ancestor existed, its effective pop size and the presence of subclonal expansions. (3/9)

An example of our model's fit (posterior predictive) to real patient fCpG methylation data.

A pairs plot of the posterior of the inference run on simulated data, with the ground truth values used to generate the simulated data highlighted in red.

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