Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___DNA_sequencing

This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

Type: Whole Genome Sequencing
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 2 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001008029	The dataset comprises whole exome sequences from laser capture micro-dissected biopsies of 10 patients diagnosed with clear cell renal cell carcinoma. In total over 100 regions are sampled to allow 'focally exhaustive' sequencing and explore the limits of intra-tumoural heterogeneity.	Illumina HiSeq 4000	117

Publications	Citations
Mapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer. Li R, Ferdinand JR, Loudon KW, Bowyer GS, Laidlaw S, Muyas F, Mamanova L, Neves JB, Bolt L, Fasouli ES, Lawson ARJ, Young MD, Hooks Y, Oliver TRW, Butler TM, Armitage JN, Aho T, Riddick ACP, Gnanapragasam V, Welsh SJ, Meyer KB, Warren AY, Tran MGB, Stewart GD, Cortés-Ciriano I, Behjati S, Clatworthy MR, Campbell PJ, Teichmann SA, Mitchell TJ. Cancer Cell 40: 2022 1583-1599.e10	43
De novo detection of somatic mutations in high-throughput single-cell profiling data sets. Muyas F, Sauer CM, Valle-Inclán JE, Li R, Rahbari R, Mitchell TJ, Hormoz S, Cortés-Ciriano I. Nat Biotechnol 42: 2024 758-767	18

Publications

Citations

Mapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer.
Li R, Ferdinand JR, Loudon KW, Bowyer GS, Laidlaw S, Muyas F, Mamanova L, Neves JB, Bolt L, Fasouli ES, Lawson ARJ, Young MD, Hooks Y, Oliver TRW, Butler TM, Armitage JN, Aho T, Riddick ACP, Gnanapragasam V, Welsh SJ, Meyer KB, Warren AY, Tran MGB, Stewart GD, Cortés-Ciriano I, Behjati S, Clatworthy MR, Campbell PJ, Teichmann SA, Mitchell TJ. Cancer Cell 40: 2022 1583-1599.e10

De novo detection of somatic mutations in high-throughput single-cell profiling data sets.
Muyas F, Sauer CM, Valle-Inclán JE, Li R, Rahbari R, Mitchell TJ, Hormoz S, Cortés-Ciriano I. Nat Biotechnol 42: 2024 758-767