CONIPHER, our method for automated reconstruction of tumour subclonal structure and phylogeny that we used in our recently published TRACERx studies, is now out in Nature Protocols! (). Welcome to the CONIPHER TREEtorial, just in time for Christmas! 🌲 1/n
Our paper together with
@SwantonLab
@CharlesSwanton
‘Genomic-transcriptomic evolution in lung cancer and metastasis’ comes out today
@Nature
. Read all about it 🚨👇 1/9
Very excited to share this review by
@jrm_black
We explore the importance of both genetic and non-genetic ITH and their role in tumour evolution, and argue for a broad research focus beyond the cancer genome:
Incredibly honoured that our work has been recognised! Our work is computational, focussing on using data to understand cancer - we are entirely reliant on wonderful collaborators and public data. (& generous funders
@wellcometrust
@CRUKCOLcentre
@CRUKLungCentre
@RosetreesT
)
🎉The Blavatnik Awards and
@nyasciences
are excited to announce the Honourees of the 2024 Blavatnik Awards in the UK! Please join us in congratulating these nine incredible scientists sparking innovations that will transform our future world. Learn more:
Excited to share out latest paper :
Do you want to infer T cell infiltrate, but only have bulk DNA-seq? Our tool, T Cell ExTRECT, provides a solution! And here's tweetorial about our serendipitous discovery 👇
Out now in
@nature
! Introducing our new method T cell ExTRECT that uses DNA sequencing data to directly quantify T cell fraction and its application in cancer. A quick thread 🧵 (1/20)
Exciting computational post-doc position available in our lab. Hate cancer? Love research? Enjoy harnessing computational tools to explore the interplay between cancer cell plasticity and cancer genome evolution? This job is made for you.
📢Our preprint ‘RNA allelic frequencies of somatic mutations encode substantial functional information in cancers’ is out today. Excited to tell you all about it, and our new tool, RVdriver: (1/8)
New position available to join
@NickyMcGranahan
Lab at UCL. Seeking collaborative
and self-motivated Research Fellow to work on cancer evolution - deciphering impact of treatment on acquisition of somatic alterations and immune microenvironment. ℹ️
Excited by exploring tumour evolution and how cancers evade the immune system? There’s still time to apply for a computational post doc position in our lab...
New computational post-doc positions available in my lab:
Interested in genome evolution and the interplay between the cancer cell and the immune microenvironment? working on large datasets? Please RT
#TRACERx
#CancerEvolution
#UCL
Can ctDNA can be harnessed to identify ongoing karyotype evolution and heterogeneity in pancreatic cancer? Great work from
@jrm_black
@AMIHuebner
…thread👇
📢Our paper ‘ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA’ is out in
@GenomeMedicine
.
Led by
@AMIHuebner
and myself, supervised by
@NickyMcGranahan
& a collaboration with Rodrigo Toledo &
@DrMhidalgo
. 🧵(1/9)
Very excited to share this work which we were fortunate to be involved with....
The effect of age on the acquisition and selection of cancer driver mu...
Excited to be speaking in this session today! Very much looking forward to learn about novel technologies to understand cancer development and the immune microenvironment at single cell resolution.
#AACR2022
Are you excited by the prospect of working on evolution and cancer? In a cutting edge biomedical research facility? On one of the largest datasets available? This jobs for you....
TRACERx Bioinformatics positions available to work on lung cancer evolution and the immune microenvironment in our lab
@TheCrick
please retweet or apply (or both!)
CAMDAC - Copy number Aware Methylation Deconvolution Analysis of Cancer now in preprint at ! Addressing methylation confounders copy number and purity, CAMDAC reveals (epi)genetic heterogeneity in TRACERx lung cancer, allele-specific methylation and more.
It was a pleasure to share some thoughts and science with
@NickyMcGranahan
! Meeting passionate young leaders who are doing amazing research is very inspiring
A huge milestone for our lab, first paper out today. Thank you so much to my lab for all the hard work and fantastic to collaborate with
@Foijer_lab
and
@ElinaVladimirou
📢We are hiring 2 Research IT Engineers! Exciting opportunities to support core
#HPC
cluster facility and and join us at the City of London Centre - world class hub for cancer biotherapeutics! Please share and apply by 5 Dec👇
@CRUKresearch
@CharlesSwanton
Perhaps a great example of fantastic mentorship. And the value of being lucky- joining the right lab at the right time! Talking of which, currently plenty of post-doc positions available in TRACERx team!
CONIPHER is a user-friendly package and can be installed through conda (). An example wrapper script to run from command line (). See the protocol for a full description of the method and how to run it! (). 11/n
📢With just over 1 week to go until
#ICBG2022
we are delighted to share our schedule featuring a fantastic line-up of keynote speakers, contributed talks and poster presentations.
In conclusion, to understand a cancer’s evolution and trajectory we need to consider both genetic and non-genetic diversity. Lots more to enjoy in the paper so please read! Code is available here and the data is on EGA 8/9
The future of UK medical research is at risk, including pioneering projects that I work on for
@CRUK_Policy
.
@stellacreasy
as my MP, please sign this letter to show your support and help us continue to make progress for patients
#ResearchAtRisk
@uclcancer
To address these TREEmendous challenges and help in analysing the large TRACERx cohort we developed CONIPHER, a tool to automate tumour phylogenetic reconstruction while dealing with various sources of noise and errors, and scaling to large numbers of samples and mutations. 3/n
@SafiaDanovi
@imartincorena
Critical question (or hope it is, as we’re devoting a lot of time to it). WGD may increase evolutionary potential of tumour - allowing elevated mutation rate and copy number changes.
@sal_dewhurst
may have answer!
Are naked mole rats the only mammals that don’t age? A new study in
@eLife
suggests they are. Unlike other animals their risk of dying does not increase over time.
The
@CRUKLungCentre
Conference is back this year!
We're bringing together leading experts to discuss some of the most thought provoking topics in lung cancer research.
Register now for early-bird discount and join us in Manchester this November:
Finally, we used genomic and transcriptomic features to predict which region of the primary would go on to seed metastasis. Both genomic (especially relating to recent subclonal expansions) and transcriptional features were predictive. 7/9
CONIPHER enabled us to identify expanded subclones dominating an entire sample. Recent subclonal expansions were found to be associated with poor outcome in primary tumours, and subclones seeding metastasis were found to dominate several regions of the primary tumour. 10/n
We used CONIPHER to reconstruct phylogenies for the full TRACERx421 primary () and paired primary-metastasis cohort (). A full wiki for exploring the data (using either R or Python) is publicly available (). 9/n
Genetic diversity and its role in shaping how tumours evolve has been well studied. However, we don’t have a full picture of how non-genetic variation affects tumour evolution. 2/9
Second, we looked at allele-specific expression. By controlling for the influence of copy-number, ASE could be used as a window into the methylome, revealing expression that was influenced by non-genetic means, and which genes when mutated have global effects on transcription 5/9
Ironically, after having read the article in the link below, you might be less likely to read this tweet... In a world of online everything, a real
#PeriodOfReflection
could benefit us all.
Next - we focussed on RNA variants not found in DNA. We identified five RNA variant signatures, including two underpinned by the activity of known editing enzymes - ADAR and APOBEC3A. Activity of these two signatures was preserved from primary to metastatic disease 6/9
Stage 1: CONIPHER aims to cluster mutations to identify tumour subclones, which reflect the different branches of the tumour’s phylogeny. Critically, CONIPHER takes into account that the frequency of a mutation may reflect its copy number state. 4/n
Stage 4: using the final subclones identified, CONIPHER can then enumerate all possible phylogenies, and rank which trees have the lowest error. CONIPHER also automatically outputs clone proportions in each sample. 7/n
Stage 3: CONIPHER uses inferred evolutionary relationships between clones to create a tree. It removes erroneous clones leading to tree cycles and those breaking the pigeonhole principle & crossing rules, resulting in a phylogeny maximising no. mutations retained on the tree. 6/n
Based on simulations, we find CONIPHER performs well for a high number of samples, correctly classifies truncal and subclonal mutations and correctly identifies erroneous clusters to remove. 8/n
Tumours are heterogeneous mixtures of distinct tumour clones as a result of a complex evolutionary process. Reconstructing tumour phylogenies from many samples, affected by complex structural alterations, and with variable levels of noise remains difficult. 2/n
@manojit_ms
@JSheltzer
@BarryTaylorLab
Really cool paper
@JSheltzer
! Sex for cancer! We certainly see elevated losses following WGD, indicating ongoing instability. But, little evidence so far of repeated to and fro in many cases.
Stage 2: CONIPHER enumerates the all evolutionary plausible ancestral/descendent relationships between subclones. In this stage, false subclones likely driven by missed copy number events are removed. 5/n
First up, we looked at whether patterns of gene expression within tumours (intratumour heterogeneity, ITH) can tell us about the forces shaping evolution prior to sampling. By focussing on highly expressed, low ITH non-cancer genes, we saw signals of weak negative selection 4/9
We investigated this in the
#TRACERx
cohort of non-small cell lung cancers: 947 tumour regions from 354 patients- all with paired DNA and RNA sequencing data - as well as 96 paired normal tissue samples 3/9