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TRACERx Non-small cell lung cancer

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TRACERx DAC
ctc.tracerx@ucl.ac.uk

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This DAC controls 10 datasets

Dataset ID	Description	Technology	Samples
EGAD00001003206	BACKGROUND TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). METHODS Multiregion high-depth whole-exome sequencing (M-seq) was performed on 100 early stage NSCLC tumors resected prior to systemic therapy. A total of 327 tumor regions were sequenced and analyzed to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between ITH and recurrence-free survival (RFS). RESULTS Widespread ITH was observed for both somatic copy number alterations (median 48% [0.03-88%]) and mutations (median 30% [0.5-93%]). Driver mutations in EGFR, MET, BRAF and TP53 were almost always clonal. However, heterogeneous driver alterations occurring later in evolution were found in over 75% of tumors and were common in PIK3CA, NF1 and genes involved in chromatin modification and DNA response and repair. Genome doubling and ongoing dynamic chromosomal instability (CIN), illustrated by mirrored subclonal allelic imbalance, were identified as causes of ITH resulting in parallel evolution of driver copy number events, including amplifications of CDK4, FOXA1, and BCL11A. Elevated copy number heterogeneity was associated with shorter RFS (HR=4.9, P=0.00044), which remained significant in a multivariate analysis. CONCLUSIONS ITH mediated through CIN, rather than point mutational heterogeneity, was associated with increased risk of relapse, supporting its value as a prognostic predictor, and the need to target this high-risk phenotype.		427
EGAD00001003301	Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature, http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.		10
EGAD00001003404	RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.	Illumina HiSeq 2500	8
EGAD00001004591	TRACERx 100: RNAseq data from the first 100 TRACERx tumours (164 tumor regions from 64 patients)	Illumina HiSeq 4000	164
EGAD00001004798	TRACERx 100: RRBS data from a subset of the first 100 TRACERx tumours	Illumina HiSeq 2500	98
EGAD00001009707	RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue. TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).	Illumina HiSeq 2500	155
EGAD00001009825	TRACERx NSCLC - Whole exome multiregion sequencing data from the 421 cohort	Illumina HiSeq 2000	2193
EGAD00001009862	RNAseq data from the TRACERx 421 cohort	Illumina HiSeq 4000	1051
EGAD00001010031	Whole-exome sequencing of tumour regions and deep targeted sequencing of plasma samples.	Illumina HiSeq 2000 unspecified	1106
EGAD00001012228	Data from Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models	Illumina HiSeq 2000	237