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• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004932

• Genome and transcriptome sequence data from a metastatic sarcomatoid carcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic sarcomatoid carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004933

• Genome and transcriptome sequence data from a oligometastatic colorectal cancer patient

  Genome and transcriptome sequence data from a oligometastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004935

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004936

• Genomic characterisation of MGUS

  The hematological malignancy multiple myeloma (MM), also called Kahler's disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Dataset EGAD00001006363

• Metabolic context regulates the competitive fitness of oncogenic PIK3CA mutant clones in the normal esophagus

  Activating mutations in PIK3CA generate large clones in the aging human esophagus. Here we investigate the underlying cellular mechanisms regulating their expansion by lineage tracing. Expression of an activating heterozygous Pik3caH1047R mutation in single progenitor cells of the mouse esophagus tilts cell fate towards proliferation, generating mutant clones that outcompete their wild type neighbours. The mutation leads to increased aerobic glycolysis through the activation of Hif1α transcriptional targets. In vitro and in vivo interventions that level out differences in activation of the PI3K/HIF1α/aerobic glycolysis axis between wild type and Pik3caH1047R cells attenuate the competitive advantage of the mutants. In contrast, metabolic conditions that alter Insulin/PI3K signalling, such as type-1 diabetes or diet-induced insulin resistance, further increase Pik3caH1047R mutant competitiveness in mice. Consistently, the density of activating PIK3CA mutations in human esophagus is increased in overweight individuals. We conclude that the metabolic environment influences the mutational landscape of normal epithelia. Clinically feasible interventions that even out signalling imbalances between wild type and mutant cells may therefore limit the expansion of oncogenic mutants in normal tissues.

  Dataset EGAD00001008281

• Distinct embryonic phylogenies and driver events of infant Wilms tumor - DNA

  Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

  Dataset EGAD00001009812

• Targeted capture ctDNA Library CRCQV40Run027-7

  Targeted capture ctDNA Library CRCQV40Run027-7 from patient PBC0003364, saliva sample

  Dataset EGAD00001010396

• Targeted capture ctDNA Library CRCQV40Run027-8

  Targeted capture ctDNA Library CRCQV40Run027-8 from patient PBC0004076, saliva sample

  Dataset EGAD00001010397

• Targeted capture ctDNA Library CRCQV40Run027-9

  Targeted capture ctDNA Library CRCQV40Run027-9 from patient PBC0004350, saliva sample

  Dataset EGAD00001010398

• Targeted capture ctDNA Library CRCQV42Run016-11

  Targeted capture ctDNA Library CRCQV42Run016-11 from patient PBC0001467, plasma baseline sample

  Dataset EGAD00001010399

• Targeted capture ctDNA Library CRCQV42Run016-16

  Targeted capture ctDNA Library CRCQV42Run016-16 from patient PBC0001396, saliva sample

  Dataset EGAD00001010400

• Targeted capture ctDNA Library CRCQV42Run016-17

  Targeted capture ctDNA Library CRCQV42Run016-17 from patient PBC0001467, saliva sample

  Dataset EGAD00001010401

• Targeted capture ctDNA Library CRCQV42Run016-9

  Targeted capture ctDNA Library CRCQV42Run016-9 from patient PBC0001396, plasma baseline sample

  Dataset EGAD00001010402

• Targeted capture ctDNA Library CRCQV42Run017-10

  Targeted capture ctDNA Library CRCQV42Run017-10 from patient PBC0002255, plasma 12 month sample

  Dataset EGAD00001010403

• Targeted capture ctDNA Library CRCQV42Run017-11

  Targeted capture ctDNA Library CRCQV42Run017-11 from patient PBC0001845, plasma 6 month sample

  Dataset EGAD00001010404

• Targeted capture ctDNA Library CRCQV42Run017-12

  Targeted capture ctDNA Library CRCQV42Run017-12 from patient PBC0002429, plasma 9 month sample

  Dataset EGAD00001010405

• Targeted capture ctDNA Library CRCQV42Run017-13

  Targeted capture ctDNA Library CRCQV42Run017-13 from patient PBC0002383, plasma 12 month sample

  Dataset EGAD00001010406

• Targeted capture ctDNA Library CRCQV42Run017-15

  Targeted capture ctDNA Library CRCQV42Run017-15 from patient PBC0001673, plasma 24 month sample

  Dataset EGAD00001010407

• Targeted capture ctDNA Library CRCQV42Run017-16

  Targeted capture ctDNA Library CRCQV42Run017-16 from patient PBC0002816, plasma 6 month sample

  Dataset EGAD00001010408

• Targeted capture ctDNA Library CRCQV42Run017-17

  Targeted capture ctDNA Library CRCQV42Run017-17 from patient PBC0002062, plasma 6 month sample

  Dataset EGAD00001010409

• Targeted capture ctDNA Library CRCQV42Run017-18

  Targeted capture ctDNA Library CRCQV42Run017-18 from patient PBC0002294, plasma 12 month sample

  Dataset EGAD00001010410

• Targeted capture ctDNA Library CRCQV42Run017-19

  Targeted capture ctDNA Library CRCQV42Run017-19 from patient PBC0001432, plasma 18 month sample

  Dataset EGAD00001010411

• Targeted capture ctDNA Library CRCQV42Run017-20

  Targeted capture ctDNA Library CRCQV42Run017-20 from patient PBC0001051, plasma 18 month sample

  Dataset EGAD00001010412

• Targeted capture ctDNA Library CRCQV42Run017-22

  Targeted capture ctDNA Library CRCQV42Run017-22 from patient PBC0001627, plasma 6 month sample

  Dataset EGAD00001010413