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• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty__Exome_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003313

• Recurrent mTORC1-activating RRAGC mutations in follicular lymphoma

  Follicular lymphoma (FL) is an incurable B-cell malignancy characterized by the t(14;18) and mutations in one or more components of the epigenome. Whilst frequent gene mutations in signaling pathways, including JAK-STAT, NOTCH and NF-κB, have also been defined, the spectrum of these mutations typically overlap with the closely-related diffuse large B cell lymphoma (DLBCL). A combination of discovery exome and extended targeted sequencing revealed recurrent somatic mutations in RRAGC uniquely enriched in FL patients (17%). More than half of the mutations preferentially co-occurred with ATP6V1B2 and ATP6AP1 mutations, components of the vacuolar H+-adenosine triphosphate ATPase (v-ATPase) known to be necessary for amino acid-dependent mTORC1 activation. RagC mutants increased raptor binding whilst rendering mTORC1 signaling resistant to amino acid deprivation through nucleotide-independent mechanisms. Collectively, the activating nature of the RRAGC mutations, their existence within the dominant clone and stability during disease progression supports their potential as an excellent candidate to be therapeutically exploited.

  Study EGAS00001001190

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty___Exome__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003527

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• Barcoding reveals complex clonal dynamics of de novo transformed human mammary cells

  Most human breast cancers have already diversified genomically when they first become clinically evident, by which time extensive heterogeneous histopathologies, transcriptomes and growth patterns are also apparent. Accordingly, important initial events and the cellular context in which they occur have been difficult to characterize. Using DNA barcoding, we now demonstrate the high efficiency with which both purified basal and luminal cells isolated directly from normal adult human mammary tissue can be rapidly transformed by a single oncogene (KRASG12D) resulting in the production within 8 weeks in vivo of serially transplantable, polyclonal, invasive ductal carcinomas that are phenotypically heterogeneous and transcriptionally distinct from the initial cells transduced. Barcoding also revealed a consistent dramatic change in the clonal content of passaged tumours. This system thus provides a powerful new platform for examining early events in the genesis, evolution and treatment response of malignant human mammary cells generated using defined mutations.

  Study EGAS00001001310

• Subtype specific progression from DCIS to invasive breast cancer

  Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.

  Study EGAS00001001866

• Hi-C dataset for testicular germ cell tumour GWAS risk loci, as described in the Oncoarray Litchfield et al. 2016 paper.

  Genome-wide association studies (GWAS) have transformed our understanding of testicular germ cell tumour (TGCT) susceptibility but much of the heritability remains unexplained. Here we report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, approximately doubling the number of known TGCT risk loci to 44. By performing in-situ Hi-C in TGCT cells, we establish a network of physical interactions between all 44 TGCT risk SNPs and candidate causal genes. Our findings reveal widespread disruption of developmental transcriptional regulators as a basis of disease susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in TGCT oncogenesis1. Defective microtubule assembly and dysregulation of KIT-MAPK signalling also feature as recurrently disrupted pathways. Our findings support a polygenic model of disease risk and provide insight into the biological basis of TGCT.

  Study EGAS00001001930

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in non-responding tumors in three immunotherapy-treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature, and HLA status provided an improved predictor of response to immunotherapy that was independently validated.

  Study EGAS00001003892

• Contribution of allelic imbalance to colorectal cancer

  Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge, and unbiased CRISPR-Cas9 knockout and activation screens identified altogether 79 genes within AI peaks regulating cell growth. Genetic and functional data implicates loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers.

  Study EGAS00001002966

• Interethnic comparability in blood pressure GWAS

  We carried out a genome-wide association and replication study for blood pressure in a two-stage approach (max N = 289,038) with a discovery stage sample of 130,777 East Asian individuals, identifying 19 new genetic loci. We found a significant genetic heterogeneity between East Asian and European-descent populations at several blood pressure loci, conforming to “a common ancestry-specific variant association model”. At 6 unique loci, distinct non-rare (or common) ancestry-specific variants co-localized within the same linkage disequilibrium block despite the significantly discordant direction of effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect sizes is 0.898 and 0.851 for systolic and diastolic blood pressure, respectively. Some of the ancestry-specific association signals were also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in the occurrence of ethnic differences in complex traits such as blood pressure.

  Study EGAS00001002991