14983 results for "cancer studies using rna-seq"

in 24.54 milliseconds.

• Amplicon sequencing data from organoids of colorectal cancer patients.

  The dataset includes 13 bam files. Each bam file is a different colorectal cancer patient organoid.

  Dataset EGAD00001004313

• EORTC RP1335 SPECTA Lung cancer data - Oncomine

  EORTC RP1335 SPECTA Lung cancer data - Oncomine dataset

  Dataset EGAD00001006594

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• Base-excision repair pathway shapes 5-methylcytosine deamination signatures in pan-cancer genomes

  Transition of cytosine to thymine in CpG dinucleotides is the most frequent type of mutation in cancer. This increased mutability is commonly attributed to spontaneous deamination of 5-methylcytosine (5mC), which is normally repaired by the base-excision repair (BER) pathway. However, the contribution of 5mC deamination in the increasing diversity of cancer mutational signatures remains poorly explored. Here, we integrate mutational signatures analysis in a large series of tumor whole genomes with lineage-specific epigenomic data to draw a detailed view on 5mC deamination in cancer. We uncover tumor type-specific patterns of 5mC deamination signatures in CpG and non-CpG contexts. We demonstrate that the BER glycosylase MBD4 preferentially binds to open chromatin domains, which correlates with lower mutational burden in these domains. We validate our findings by modelling BER deficiencies in isogenic cell models. Overall, we establish MBD4 as the main actor responsible for 5mC deamination repair in humans.

  Study EGAS50000000536

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - RNAseq

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000977

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - WES

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000976

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty___WG__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 EGAS00001003524

• MutWP5__CRUK_Mutographs_of_Cancer__BRCA_Carriers___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 EGAS00001003526

• Somatic_mutation_and_clonal_evolution_normal_breast_tissue_WGS

  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 >70 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 tumour development.

  Study EGAS00001002857

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty__WG_

  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 EGAS00001003311

• 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

• 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

• MutWP5__CRUK_Mutographs_of_Cancer__BRCA_Carriers___WG__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 EGAS00001003523

• MutWP5__CRUK_Mutographs_of_Cancer__Cancer_Mastectomy__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 EGAS00001003528

• GENOMIC MUTATION LANDSCAPE OF SKIN CANCERS FROM DNA REPAIR-DEFICIENT XERODERMA PIGMENTOSUM PATIENTS

  Xeroderma pigmentosum (XP) is a genetic disorder caused by mutations in genes of the Nucleotide Excision Repair (NER) pathway (groups A-G) or in Translesion Synthesis (TLS) DNA polymerase η (group V). XP is associated with an increased skin cancer risk, reaching, for some groups, several thousand-fold compared to the general population. Here, we analyzed 38 skin cancer genomes from five XP groups. We found that the activity of NER determines heterogeneity of the mutation rates across skin cancer genomes and that transcription-coupled NER extends beyond the gene boundaries reducing the intergenic mutation rate. Mutational profile in XP-V tumors revealed the role of polymerase η in the error-free bypass of (i) rare TpG and TpA DNA lesions, (ii) 3’ nucleotides in pyrimidine dimers, and (iii) TpT photodimers. Our study unravels the genetic basis of skin cancer risk in XP and provides insights into the mechanisms reducing UV-induced mutagenesis in the general population.

  Study EGAS00001006732

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  Phytocannabinoids Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) have been demonstrated to exhibit anti-cancer activity in preclinical models of brain cancer leading to new clinical trials for adults with glioblastoma. We describe here the first report that has investigated a role for THC and CBD in paediatric brain cancer. Cannabinoids had cytotoxic activity against medulloblastoma and ependymoma cells in vitro, functioning in part through the inhibition of cell cycle progression and the induction of autophagy. Despite these effects in vitro, when tested in orthotopic mouse models of medulloblastoma or ependymoma, no impact on animal survival was observed. Furthermore, cannabinoids neither enhanced nor impaired conventional chemotherapy in a medulloblastoma mouse model. These data show that while THC and CBD do have some effects on medulloblastoma and ependymoma cells, are well tolerated and have minimal adverse effects, they do not appear to elicit any survival benefit in preclinical models of paediatric brain cancer.

  Study EGAS00001004963

• NCI CCSG CCDI Supplement Additional Genomic Submission

  The implementation of targeted therapies for acute myeloid leukaemia (AML) has been challenging because of the complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. This supplement data from the Beat AML program provides Adolescent and Young Adult (AYA) and pediatric tumor specimens not previously released. These data include exome and RNA level characterization as well as analyses of ex vivo drug sensitivity. Collectively, this data can be leveraged to address clinical, genomic, transcriptomic and functional analyses of the biology of leukemia in pediatric and AYA populations.

  Study phs002599

• Novel APC Promoter and Exon 1B Deletion and Allelic Silencing in Three Mutation-Negative Classic Familial Adenomatous Polyposis Families

  The ~80% of individuals with classic familial adenomatous polyposis (FAP) have detectable mutations in the coding sequence of the adenomatous polyposis coli (APC) gene. To investigate the 20% of families without detectable causative mutations, we used exome sequencing and second-generation sequencing of the APC locus including non-coding regions. We identified a novel ~11kb deletion 44kb upstream of APC that was present only in affected individuals of three kindreds. SNP analysis showed that this ~11kb deletion was accompanied by silencing of one of the APC alleles in blood-derived RNA of affected individuals.

  Study phs000904

• Circulating RNAs in Acute Heart Failure (CRUCIAL)

  The purpose of this American Heart Association-funded and NIH-funded study is to examine circulating RNAs in the acute congestive heart failure (CHF) setting, and how they change with decongestive therapy, and their function in vitro and in vivo. The investigators are testing the hypothesis that ex-RNA levels change significantly during decongestion therapy and can be used as a marker of those individuals who respond to CHF therapy (in terms of cardiac structure or outcome). Additionally, the translational research design allows the investigators to assay the effects of these RNAs on tissue phenotypes in vitro.

  Study phs003403

• High-resolution profile of neoantigen-specific TCR activation links moderate stimulation to increased resilience of engineered TCR-T cells

  Neoantigen-specific T cell receptors (neoTCRs) promise safe, personalized anti-tumor immunotherapy. Previously, we identified diverse neoTCRs restricted to different neoantigens in a melanoma patient. In this work, we now combined single-cell TCR- and RNA-sequencing after neoantigen-specific restimulation of peripheral blood-derived CD8+ T cells of this patient. We detected novel neoTCRs with specificity to the previously detected neoantigens and observe a heterogeneous spectrum of TCR-intrinsic activation patterns in response to a shared neoepitope ranging from previously detected higher frequent neoTCRs with moderate activation to rare ones with initially stronger activation.

  Study EGAS50000000600

• Systematic Analysis of Transcription Program Regulation by Transcription Factor EB (TFEB)

  In order to evaluate the effects of TFEB, a master regulator of autophagy and lysosomal biogenesis, CRISPR-Cas9 TFEB knock out cell lines were generated and reconstituted with wild-type TFEB (TFEB-WT), a vector control (TFEB-KO) or TFEB engineered to remain localized to the cytosol (TFEB-cyto) or to the nucleus (TFEB-nuc). RNA sequencing was performed on engineered cell lines at steady-state or following exogenous stimulation with autophagy inducer (Torin1 or Salmonella bacterial infection). Comparative analyses were performed to identify TFEB-dependent transcriptional response to subcellular localization at steady-state or to exogenous stimuli.

  Study phs002099

• RNAseq profile of monomorphic epitheliotropic intestinal T-cell lymphoma and enteropathy associated T-cell lymphoma

  Background : Enteropathy-associated T-cell lymphoma (EATL) and monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL) are aggressive malignancies with limited treatment options and poor prognosis. Our research on MEITL has uncovered its genetic portrait including hallmark SEDT2 mutations, expanded its pathological spectrum, and identified molecular biomarkers influencing patients’ outcome. In this study, we aimed to establish and clarify the similar and diverging features of EATL. Methods : A large combined cohort of patients with EATL (n=30) and MEITL (n=52) was assembled and tumor samples were used for whole-exome and RNA sequencing profiling.

  Study EGAS50000001125

• Whole Exome Sequencing of monomorphic epitheliotropic intestinal T-cell lymphoma and enteropathy associated T-cell lymphoma

  Background : Enteropathy-associated T-cell lymphoma (EATL) and monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL) are aggressive malignancies with limited treatment options and poor prognosis. Our research on MEITL has uncovered its genetic portrait including hallmark SEDT2 mutations, expanded its pathological spectrum, and identified molecular biomarkers influencing patients’ outcome. In this study, we aimed to establish and clarify the similar and diverging features of EATL. Methods : A large combined cohort of patients with EATL (n=30) and MEITL (n=52) was assembled and tumor samples were used for whole-exome and RNA sequencing profiling.

  Study EGAS50000001126

• Whole blood RNA-sequencing of covid-19 patients and healthy controls

  This dataset contains whole blood transcriptome data generated from 93 patients with COVID-19 across a range of severities and 23 healthy controls. All patients were PCR positive for SARS-CoV-2 and disease severity ranged from asymptomatic to severe disease requiring ventilation. Individuals without symptoms, or with mild symptoms, were recruited from routine screening of healthcare workers, while COVID-19 patients were recruited at or soon after admission to Addenbrooke’s or Royal Papworth hospitals. Blood samples were taken at recruitment and then again four weeks later. Further details of the cohort and the generation of the RNA-Sequencing data can be obtained from Bergamaschi, L. et al. Longitudinal analysis reveals that delayed bystander CD8+ T cell activation and early immune pathology distinguish severe COVID-19 from mild disease. Immunity 54, 1257-1275 e8 (2021).

  Dataset EGAD00001007776

• Multiregional single cell RNA sequencing of human renal cell carcinoma

  The dataset comprises of 5' single cell RNA sequencing with TCR enrichment with 10x Genomics' Chromium technology of multiregional biopsies of human renal cell carcinomas. Biopsies from different tumour regions, the tumour-normal interface, normal kidney, normal adrenal, metastatic regions, peri-nephric fat, and peripheral blood were sequenced from 12 patients with kidney tumours.

  Dataset EGAD00001008030

• The molecular landscape of glioma in patients with Neurofibromatosis 1.

  Neurofibromatosis type 1 (NF1) is a common tumor predisposition syndrome in which glioma is one of the most prominent tumor type. Gliomagenesis in NF1 results in heterogeneous spectrum of tumors, from low grade to high grade glioma, occurring during the entire patient lifespan. In this study, we present the molecular landscape of low- and high-grade glioma in children and adults affected by NF1 (NF1-glioma). 59 tumor samples from 56 NF1-glioma patients with 43 matched normal were profiled with Whole Exome Sequencing, DNA Methylation array (31 tumors) and RNA sequencing (29 tumors).

  Study EGAS00001003186

• Stage-specific gene and transcript dynamics in human male germ cells

  The testis is one of the most transcriptionallyactive organs, however how germ cell differentiation is controlled at the molecular level remains largely unknown. To study global transcriptional dynamics during human spermatogenesis we sequenced total RNA of human testicular biopsies with 5 specific histological phenotypes: Sertoli cell-only (SCO, n=3), spermatogenic arrests at the spermatogonial (SPG, n=4), spermatocyte (SPC, n=3), and spermatid (SPD, n=3) level, as well as normal spermatogenesis (Normal, n=3). To our knowledge, this work provides the most complete capture of the transcriptome and its dynamics during human spermatogenesis to date.

  Study EGAS00001006135

• Multiple Tissue Monitoring in Huntington disease - RNAseq skeletal muscle

  We examined whether peripheral tissues can serve as a source of readily accessible biological signatures at the RNA and protein level in Huntington disease (HD) patients. Under the MTM-HD study we generated large, high-quality human datasets from skeletal muscle, skin and adipose tissue, as well as primary human fibroblast lines to probe molecular changes in human pre-manifest and early manifest HD patients. We document the involvement of inflammation, energy metabolism and extracellular vesicle homeostasis. This demonstrates the potential to identify biological signatures from peripheral tissues in HD suitable as biomarkers in clinical trials.

  Study EGAS00001006474

• Multiple Tissue Monitoring in Huntington disease - RNAseq fibroblasts

  We examined whether peripheral tissues can serve as a source of readily accessible biological signatures at the RNA and protein level in Huntington disease (HD) patients. Under the MTM-HD study we generated large, high-quality human datasets from skeletal muscle, skin and adipose tissue, as well as primary human fibroblast lines to probe molecular changes in human pre-manifest and early manifest HD patients. We document the involvement of inflammation, energy metabolism and extracellular vesicle homeostasis. This demonstrates the potential to identify biological signatures from peripheral tissues in HD suitable as biomarkers in clinical trials.

  Study EGAS00001006472

• Multiple Tissue Monitoring in Huntington disease - RNAseq adipose tissue

  We examined whether peripheral tissues can serve as a source of readily accessible biological signatures at the RNA and protein level in Huntington disease (HD) patients. Under the MTM-HD study we generated large, high-quality human datasets from skeletal muscle, skin and adipose tissue, as well as primary human fibroblast lines to probe molecular changes in human pre-manifest and early manifest HD patients. We document the involvement of inflammation, energy metabolism and extracellular vesicle homeostasis. This demonstrates the potential to identify biological signatures from peripheral tissues in HD suitable as biomarkers in clinical trials.

  Study EGAS00001006473

• Primary Lung Cancer whole genome study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000388

• Comprehensive genomic characterization of early stage bladder cancer - whole exome sequencing data

  For this project about non-muscle invasive bladder cancer (NMIBC), we analysed WES data from 438 patients. The dataset is composed of 876 BAM files: 438 tumor samples and 438 paired blood samples.

  Study EGAS50000000511

• Exome Recapture and Sequencing of Prospectively Characterized Clinical Specimens From Cancer Patients

  The study cohort comprises samples from patients whose tumors have been prospectively characterized as part of their care at Memorial Sloan Kettering Cancer Center. This includes a variety of distinct tumor type and molecular subtypes.

  Study phs001783

• The dataset for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  The dataset for “Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer” includes 496 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor tissue, matched buffy coat and longitudinal plasma samples from individuals with pancreatic cancer.

  Dataset EGAD50000001353

• Tumor gene project

  The study focuses on human tumor susceptibility as well as somatic cancer genomics. We use high-throughput sequencing approaches to achieve a comprehensive molecular characterization of tumors. Our goal is to better understand their genesis and management opportunities.

  Study EGAS50000000984

• Genome and transcriptome sequence data from a metastatic serous ovarian cancer patient

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

  Dataset EGAD00001004909

• Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient

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

  Dataset EGAD00001002567

• Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002577

• Genome and transcriptome sequence data from a GI primary (prev breast cancer) patient

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

  Dataset EGAD00001002979

• Genome and transcriptome sequence data from a metastatic breast cancer patient

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

  Dataset EGAD00001004923

• Genome and transcriptome sequence data from a large intestine-colon cancer patient

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

  Dataset EGAD00001005885

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001969

• Genome and transcriptome sequence data from a metastatic medullary thyroid cancer patient

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

  Dataset EGAD00001003006

• Genome and transcriptome sequence data from a low grade serous ovarian cancer patient

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

  Dataset EGAD00001003680

• Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003713

• Genome and transcriptome sequence data from a metastatic collecting duct kidney cancer patient

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

  Dataset EGAD00001003031

• Genome and transcriptome sequence data from a metastatic cancer to the breast patient

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

  Dataset EGAD00001010959

• Genome and transcriptome sequence data from a metastatic triple negative breast cancer patient

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

  Dataset EGAD00001010980

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002611

• Genome and transcriptome sequence data from a metastatic unknown primary cancer patient

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

  Dataset EGAD00001005845