Research Vision
Research Vision
Embedded Files
The CCG research group specializes in the design, development, and application of computational methods to investigate cancer evolution and related biological processes using data from various sequencing technologies. A core value of the CCG Lab is its translational goal; therefore, most projects are based on data from clinical, human samples, with the goal of identifying fundamental biological information, or applications ready for clinical use, that can be translated for the benefit of patients. In fact, CCG’s research is inspired by the fundamental belief that using formal, consolidated, and robust methodologies is key to accurately addressing important unanswered questions on complex cancer evolutionary processes, and that accuracy is necessary to identify opportunities for translation. In addition to these research goals, the CCG Lab is committed to training the next generation of translational scientists in computational biology equipped with the cross-disciplinary skillset required to develop sophisticated algorithms for complex biological and clinical questions.
Research Focus
Research Focus
The research of the CCG Lab is currently focused on understanding the evolutionary origins and dissemination patterns of metastasis, the complex process of cancer-cell spread. An in-depth understanding of this process would provide insights into the cellular mechanisms enabling cancer-cell dissemination and might lead to new therapeutic strategies1-3. However, thus far, this endeavour has been constrained by the limited resolution of standard bulk DNA sequencing technologies4-9, particularly the inability to unambiguously identify distinct, small subpopulations of cancer cells that play a crucial role in metastasis. In fact, metastasis is the result of a complex, highly-selective evolutionary process in which varied somatic alterations accumulate in the genome of distinct cancer cell subpopulations, leading to highly heterogeneous tumours both within the primary tumour and across metastases1,3,10-14. In this stochastic process, pioneering experimental studies have revealed that only small subpopulations of cancer cells often harbour disseminating and metastatic potential4,10,12,15-18. Consequently, little is currently known about the evolutionary origins of metastatic cells and their migration patterns.
To overcome these challenges, the CCG Lab leads a cross-disciplinary team (including clinicians, bioinformaticians, statisticians, sequencing and molecular technologists, etc.) aiming to generate a longitudinal and metastatic clinical dataset using cutting-edge single-cell whole-genome DNA sequencing (scDNA-seq) technologies19-21. These technologies provide the in-depth resolution required to investigate the high complexity of metastasis. Specifically, we are applying these technologies to the UK-national TRACERx and PEACE studies14,22, which together offer access to an unparalleled number of paired primary and metastatic tumour samples (>20 per case) collected from patients with non-small cell lung cancer throughout treatment to autopsy. By combining these opportunities, we are generating an unprecedented scDNA-seq dataset of ~192,000 metastatic single cells from 96 tumour samples in 20 TRACERx and PEACE patients with detailed clinical annotations that will be made publicly available.
Page updated
Google Sites
Report abuse