A cross-disciplinary group developing and applying computational methods to analyse tumour sequencing data and cancer evolution at @uclcancer led by @ZaccaSimo
UCL Cancer Institute, LondonUK
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Computational Cancer Genomics (CCG) Research Group retweeted
🚨 PhD opportunity at @CCG_UCL!
Build AI & computational tools to catch ecDNA in single cells: rogue DNA circles that let cancer shapeshift & beat therapy
With Mariam & @BenjaminWerner_ via the @CRUKCOLcentre at @uclcancer Black Leaders in Cancer PhD
👇
colcc.ac.uk/2027-blic-phd-pr…
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Congratulations to our outstanding Drs!!
🎓 ABSOLUTELY BURSTING WITH PRIDE!
Huge congrats to our @CCG_UCL first doctoral graduates: Dr @Rija_Zaidi_, Dr @abi_bunkum & Dr @ojlucas! 🎉
Whatever pathways they choose next, I have no doubt these brilliant minds will lead critical advances in our society—we're all so lucky!✨
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Computational Cancer Genomics (CCG) Research Group retweeted
Excited to share our ‘Evolutionary characterization of #LungCancer metastasis’ in #TRACERx & #PEACE, published today in @Nature: a decade spanning effort led by the Jamal-Hanjani lab, @SwantonLab, @NickyMcGranahan & @ZaccaSimo at @uclcancer & @TheCrick. Link below
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Computational Cancer Genomics (CCG) Research Group retweeted
Online here: nature.com/articles/s41586-0…
Open access here: rdcu.be/ff6YJ
Key supporters of this work are @CR_UK , @CRUKLungCentre , @UCLHresearch alongside many others
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Computational Cancer Genomics (CCG) Research Group retweeted
Using MACHINA from @benjraphael's lab to infer metastatic migration patterns, we found that NSCLC primaries had multiple seeding subclones more often than a single seeding subclone. 4/9
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Computational Cancer Genomics (CCG) Research Group retweeted
Very fortunate to work alongside a fantastic team: @abi_bunkum @HaaseKerstin @AMIHuebner @KristianaGrigo4 Cristina Naceur-Lombardelli steered by: Mariam Jamal-Hanjani @CharlesSwanton @NickyMcGranahan @ZaccaSimo
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Computational Cancer Genomics (CCG) Research Group retweeted
Congratulations to @CharlesSwanton, Mariam Jamal-Hanjani and colleagues on their fascinating analysis of the evolution of lung cancer metastasis published in @Nature!
nature.com/articles/s41586-0…
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Computational Cancer Genomics (CCG) Research Group retweeted
Through the integration of the #PEACE autopsy programme, which allows high breadth metastasis sampling, with the #TRACERx lung study, we collected and studied 501 primary and metastatic tumour samples from 24 patients with #NSCLC enrolled in the both studies. 2/9
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Computational Cancer Genomics (CCG) Research Group retweeted
🚨 Huge honour to have helped supervise this landmark PEACE study!
New insights into metastasis + a unique dataset of unprecedented resolution on metastatic evolution and dissemination that we hope will drive future advances
🙏 @CR_UK @CRUKresearch.
Please take a look 👇
Through the integration of the #PEACE autopsy programme, which allows high breadth metastasis sampling, with the #TRACERx lung study, we collected and studied 501 primary and metastatic tumour samples from 24 patients with #NSCLC enrolled in the both studies. 2/9
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Huge congratulations Lucrezia!
Huge congratulations to @LucreziaPatruno from @CCG_UCL for being awarded one of the best abstract awards at AI in Oncology in Paris, we are so proud!
Join ISMB to hear her full story on the next advances in call CNAs from single cell seq!
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1 in 2 people will get cancer in their lifetime. Our
@CCG_UCL 'll still run @CR_UK Muddy Race also this May to highlight the importance of funding cancer research @CRUKresearch and improving patient outcomes
Please support us if you can! #RaceforLife
👉 fundraise.cancerresearchuk.o…
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Computational Cancer Genomics (CCG) Research Group retweeted
🚨Very proud of this commentary led by @Rija_Zaidi_ reasoning on the method and experimental design impact on cancer evolution understanding, motivated by the outstanding work of
@TheBoutrosLab, @VanLooLab, @kellrott et al
Orig. work 👉 doi.org/10.1038/s41587-024-0…
Our Commentary 👇
How much do algorithmic and experimental choices drive the accuracy of reconstructing tumour evolution?
In this @CR_AACR commentary, @ZaccaSimo and I discuss a recent @NatureBiotech benchmarking paper exploring this question:
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Computational Cancer Genomics (CCG) Research Group retweeted
How much do algorithmic and experimental choices drive the accuracy of reconstructing tumour evolution?
In this @CR_AACR commentary, @ZaccaSimo and I discuss a recent @NatureBiotech benchmarking paper exploring this question:
#TumorEvolution reconstruction is heavily influenced by algorithmic & experimental choices—this In the Spotlight commentary by @Rija_Zaidi_ & @ZaccaSimo highlights a recent @NatureBiotech paper by @TheBoutrosLab, @VanLooLab, @kellrott, @MaxGalder, et al.
bit.ly/3VAMRQs
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Computational Cancer Genomics (CCG) Research Group retweeted
#TumorEvolution reconstruction is heavily influenced by algorithmic & experimental choices—this In the Spotlight commentary by @Rija_Zaidi_ & @ZaccaSimo highlights a recent @NatureBiotech paper by @TheBoutrosLab, @VanLooLab, @kellrott, @MaxGalder, et al.
bit.ly/3VAMRQs
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Computational Cancer Genomics (CCG) Research Group retweeted
#CRUKFunded scientists published a paper in Nature Genetics unveiling the first computational algorithm capable of identifying which cell populations within a tumour drive aggressive growth.
SPRINTER is @ZaccaSimo's first output as part of their Career Development Fellowship.
🚨So proud to present the first study from our @CCG_UCL group together with @CharlesSwanton @NnennayaKanu and led by @ojlucas with key collaboration @Ward__Sophie and fundamental support @Rija_Zaidi_ @abi_bunkum & many others
Out in @NatureGenet 👇
doi.org/10.1038/s41588-024-0…
🧵👇
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Computational Cancer Genomics (CCG) Research Group retweeted
Researchers at the Crick and @UCL have developed an algorithm that can identify which cell populations within a tumour are growing the fastest.
The findings are part of the @CR_UK-funded TRACERx study and were overseen by @CharlesSwanton and @ZaccaSimo
crick.ac.uk/news-and-reports…
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Computational Cancer Genomics (CCG) Research Group retweeted
A pleasure to collaborate on this work with the outstanding @ZaccaSimo, @ojlucas and many others. SPRINTER is an outstanding and diligently constructed tool which I’m sure will be useful for many of other research projects.
🚨So proud to present the first study from our @CCG_UCL group together with @CharlesSwanton @NnennayaKanu and led by @ojlucas with key collaboration @Ward__Sophie and fundamental support @Rija_Zaidi_ @abi_bunkum & many others
Out in @NatureGenet 👇
doi.org/10.1038/s41588-024-0…
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Computational Cancer Genomics (CCG) Research Group retweeted
Our paper is out! We introduce the SPRINTER algorithm to infer clone proliferation rates from scDNAseq data 🧬
Great to work with the excellent @ojlucas, @Ward__Sophie, @abi_bunkum, @AFrankell, @MarksHilly, @NnennayaKanu, @CharlesSwanton, @ZaccaSimo & others!
🚨So proud to present the first study from our @CCG_UCL group together with @CharlesSwanton @NnennayaKanu and led by @ojlucas with key collaboration @Ward__Sophie and fundamental support @Rija_Zaidi_ @abi_bunkum & many others
Out in @NatureGenet 👇
doi.org/10.1038/s41588-024-0…
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Computational Cancer Genomics (CCG) Research Group retweeted
What an absolute pleasure to be collaborating with such an incredibly talented team!!
SPRINTER out today in @NatureGenet 🧬
🚨So proud to present the first study from our @CCG_UCL group together with @CharlesSwanton @NnennayaKanu and led by @ojlucas with key collaboration @Ward__Sophie and fundamental support @Rija_Zaidi_ @abi_bunkum & many others
Out in @NatureGenet 👇
doi.org/10.1038/s41588-024-0…
🧵👇
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Computational Cancer Genomics (CCG) Research Group retweeted
🚨So proud to present the first study from our @CCG_UCL group together with @CharlesSwanton @NnennayaKanu and led by @ojlucas with key collaboration @Ward__Sophie and fundamental support @Rija_Zaidi_ @abi_bunkum & many others
Out in @NatureGenet 👇
doi.org/10.1038/s41588-024-0…
🧵👇
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