Very proud of this work led by @nguyenlab.bsky.social ! Massive effort to characterise clonal diversity in PDTXs from breast cancer
Happy #WorldStatisticsDay2025! 🎉
At the BSU, you can find a fantastic group of passionate people driven to improve the way we look at scientific problems and design methods to help us understand the deluge of data we are surrounded by.
Indeed, very happy to see our paper highlighted by EACR!!!
Fantastic paper by the very talented Kevin Tu! An impressive analysis of the breast cancer TME in a meta cohort of thousands of tumours
🔈New research published in Statistics in Medicine, led by @ruedalab.bsky.social, Valeria Leiva and colleagues.
Novel Influence Diagnostics in Multistate Models for Breast Cancer
Read full paper 👇
onlinelibrary.wiley.com/doi/10.1002/...
#BreastCancer #Biostatistics #DataScience #Diagnosis
We had a fantastic away day yesterday, bringing together our amazing and talented staff and students for a day of sharing, learning and recognising the great people who work at the BSU.
Big thanks to the organising team for creating a brilliant day for us all 🤩
Are you looking for a statistics/ML postdoc? Come to work with @antonis02.bsky.social and me in the NEMO study, an international collaboration aiming to detect ovarian cancer earlier through cutting-edge multi-omics, funded by the Alliance for Cancer Early Detection.
www.cam.ac.uk/jobs/researc...
One of the greatest privileges of my career has been to mentor amazing researchers that now run their own labs. Four of them just sent me this picture:
@hrazaalilab.bsky.social
@ruedalab.bsky.social
@stephensammut.bsky.social
and Alex Bruna @icr.ac.uk
@ruedalab.bsky.social and @caldaslab.bsky.social with Christina Curtis reported this 6 years ago: genomic subtypes of both ER+ and TNBC determine pattern of late relapse. Theme: some tumors are born to be bad! >300 citations!
www.nature.com/articles/s41...
A paper in Nature Communications presents algorithms to estimate the chances of a person having an existing, as yet undiagnosed cancer. These algorithms can be used to triage patients for further assessment to improve chances of an earlier diagnosis. #medsky 🧪
Oscar M Rueda
Oscar M Rueda
Oscar M Rueda
MRC Biostatistics Unit
MRC Biostatistics Unit
MRC Biostatistics Unit
Oscar M Rueda
Carlos Caldas 🇵🇹🇮🇱🇪🇺🇬🇧
Carlos Caldas 🇵🇹🇮🇱🇪🇺🇬🇧
Nature Portfolio
We are very proud that our paper on using ML and ctDNA tumor burden quantitation to predict survival in metastatic breast cancer has been highlighted by @helloeacr.bsky.social!
Work led by @emmajb001.bsky.social in close collaboration with @ruedalab.bsky.social!
magazine.eacr.org/highlights-i...
I am excited to share the latest publication from the Nguyen, Caldas @carloscaldas1960.bsky.social and Rueda labs @ruedalab.bsky.social. This was a massive effort from a fantastic team and I’m grateful to everyone on the paper for their work on this project! doi.org/10.1016/j.ce...
#bcsm #PDTX
My poor laptop wishes I learned how to use the cluster earlier, but it’s sacrifice was not in vain! We learned some important things about the breast cancer tumor microenvironment, described in our paper published today:
www.cell.com/cell-reports...
Here's the 🧵
Long V. Nguyen
Caldas Lab 🇵🇹🇮🇱🇪🇺🇬🇧
An exciting opportunity has arisen for a highly motivated Research Associate to join the Centre for Cancer Genetic Epidemiology (CCGE) at the Department of Public Health & Primary Care, University of
Diagnosing cancer early and accurately is key to improving patient outcome. Here, the authors have developed algorithms to estimate the chances of having a person having an existing, as yet undiagnosed cancer. These algorithms can be used to triage patients for further assessment to improve chances of an earlier diagnosis.
Multistate models were developed to model survival data where several midpoints and endpoints are of interest; and they have been particular successful in modeling dynamics of cancer. As in any stati....
A statistical framework for breast-cancer recurrence uses long-term follow-up data and a knowledge of molecular subcategories to model distinct disease stages and to predict the risk of relapse.
