7182 results for "canc*"

in 191.20 milliseconds.

• High-throughput sequencing data for study of molecular drivers of resistance to castration in localised prostate cancer

  Aligned whole-genome sequencing and RNA-seq of localised prostate cancer for study 'Loss of SNAI2 in prostate cancer correlates with clinical response to androgen deprivation therapy'.

  Dataset EGAD00001006640

• Concatenated long-read single-cell RNA sequencing of momentum biopsies of ovarian cancer patients

  Concatenated long-read single-cell RNA sequencing samples prepared using 10X and the HIT-scIsoSeq protocol. The sequencing was performed on Sequel II Pacbio machine. 3 ovarian cancer patients, 5 omentum biopsies samples: 3 metastasis samples (one per patient), 2 healthy samples (one per patient except Patient2). 4 bam files per metastasis sample, 2 bam files per healthy sample.

  Dataset EGAD00001009814

• Pre-post neoadjuvant chemotherapy breast cancer dataset- RNAseq data

  This dataset contains RNAseq data of 20 paired pre-post neoadjuvant chemotherapy breast cancer samples. In total the set contains n=20 biopsies, n=20 surgery specimens. Each sample has 2 fastq files, so n=80 fastq files are uploaded in total.

  Dataset EGAD00001008421

• GELATO clinical trial whole exome sequencing data (primary tumors and local recurrences)

  Paired-end whole exome sequencing of 10 lobular breast cancer primary tumors, 3 local recurrences and matched normal samples obtained from 10 unique patients from the GELATO clinical trial. The included raw sequencing data in fastq format was generated using Illumina NovaSeq 6000 from archived FFPE material (tumor data) and fresh frozen material (matched normal data).

  Dataset EGAD00001009836

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010114

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001010951

• Precise reconstruction of the tumor microenvironment using bulk RNA-seq and a unique machine learning-based algorithm trained on artificial transcriptomes

  Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. Here, we present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of > 9,400 tissue and blood sorted cell RNA profiles to accurately reconstruct the tumor microenvironment (TME). Bioinformatic correction for technical and biological variability, aberrant cancer cell expression inclusion, and the accurate quantification and normalization of transcript expression increased the stability and robustness of Kassandra. Performance was validated on over 4,000 H&E tissue slides and more than 1,000 normal and tumor tissues by comparison with cytometric, immunohistochemical or single-cell RNA-seq measurements. Kassandra accurately deconvolved stromal and immune elements of blood and tumors, revealing the role of the TME in tumor pathogenesis. Digital TME reconstruction revealed that the presence of PD1-positive CD8+ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

  Dataset EGAD00001008776

• Targeted and shallow whole genome sequencing identifies therapeutic opportunities in p53abn endometrial cancers

  Targeted panel sequencing of 188 formalin-fixed paraffin-embedded p53abn endometrial cancer samples.

  Dataset EGAD00001015349

• Dataset for breast_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 12 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008867

• Pre-clinical evolution of haematological malignancies_TGS

  Leukaemia and related blood cancers occur due to genetic changes that typically accumulate over many years. This study will employ targeted next-generation sequencing to retrace the preclinical evolution of several types of haematological malignancy. Investigating the progression of the earliest pre-malignant ancestral clones promises to offer valuable insights into early leukaemia evolution and therapeutic vulnerabilities of leukaemia stem cells.

  Dataset EGAD00001006424

• IBD-dysplasia

  This data set concerns DNA copy number alterations and mutation data from 30 IBD-associated dysplastic lesions and 13 IBD-associated cancers. DNA was isolated from formalin-fixed, paraffin-embedded material. Whole-genome shallow seq and Truseq amplicon cancer panel (Illumina) were used for detection of DNA copy number alterations and gene mutations, respectively.

  Dataset EGAD00001005196

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

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

  Dataset EGAD00001010946

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• Sequencing of Plasma DNA from breast cancer patients

  Dataset contains plasma DNA whole genome sequencing on 4 breast cancer patients. It also includes matched germline and tumour whole genome sequencing data. Two benign cancer patients were also sequenced and their plasma DNA and matched germline whole genome sequencing data are included in the dataset. Samples were sequenced on Illumina HiSeqX Ten.

  Dataset EGAD00001006869

• Deep sequencing of 151 cancer genes

  Deep sequencing of 151 cancer genes in 6 synchronous CRC of 3 patients

  Dataset EGAD00001001870

• Comparison of single/pooled CTCs and bulk exome sequencing

  Single cell technologies allow the interrogation of tumor heterogeneity, providing insights into tumor evolution and treatment resistance. To better understand whether circulating tumor cells (CTCs) could complement metastatic biopsies for tumor genomic profiling, we characterized 11 single CTCs and 10 pooled CTC samples at the mutational and copy number aberration (CNA) levels, and compared these results with matched synchronous tumor biopsies from 3 metastatic breast cancer patients with triple-negative (TNBC), HER2-positive and estrogen receptor-positive (ER+) tumors. Similar CNA profiles and the same patient-specific driver mutations were found in bulk tissue and CTCs for the HER2-positive and TNBC tumors, whereas different CNA profiles and driver mutations were identified for the ER+ tumor, which presented two distinct clones in CTCs defined by mutations in ESR1 Y537N and TP53, respectively. Furthermore, de novo mutational signatures derived from CTCs described patient-specific biological processes. These data suggest that tumor tissue and CTCs provide complementary clinically relevant information to map tumor heterogeneity and tumor evolution.

  Dataset EGAD00001009052

• Genome and transcriptome sequence data from an uveal melanoma patient

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

  Dataset EGAD00001005824

• Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

  Molecular cancer paper (https://doi.org/10.1186/s12943-021-01327-5): This dataset contain shallow whole-genome sequencing (sWGS) of plasma cell-free DNA from cancer patients and healthy subjects, obtained with both Nanopore and Illumina technology. A total of 6 cancer patients and 5 healthy subjects have been sequenced with Nanopore; 4 of the cancer patients have been also sequenced with Illumina. In addition, genomic DNA from white blood cells of one healthy subjects, genomic and 160bp DNA from HEK cells have been sequenced with Nanopore. Genome Biology paper: 3 additional healthy samples have been sequenced (HU), two different bioinformatic pipeline were applied. 2019: Fastqs from the molecular cancer paper were re-demultiplexed and adapter-trimmed (using guppy for multiplex samples, and porechop for singleplex) preserving 5' ends to allow fragmentomics analysis. HAC: All the samples were basecalled with the same updated High Accuracy model (the latest at the time of the analysis) and post-processed as the 2019 dataset. Raw FAST5 are currently available upon request, but will be uploaded soon.

  Dataset EGAD00001006888

• Targeted sequencing data of breast tumors with germline BRCA1/2 mutations

  This dataset contains targeted sequencing of breast tumors with germline BRCA1/2 mutations (n = 30) and those without. Breast cancer related genes (n = 115) have been captured and sequenced.

  Dataset EGAD00001005802

• RNA of peripheral blood for pancreatic cancer and chronic pancreatitis

  Samples of nucleated cells found in peripheral blood from over 300 patients suffering from resectable pancreatic ductal adenocarcinoma, non-resectable pancreatic cancer, chronic pancreatitis, or none of these. Please cite this article when using data: Al-Fatlawi, A.; Malekian, N.; García, S.; Henschel, A.; Kim, I.; Dahl, A.; Jahnke, B.; Bailey, P.; Bolz, S.N.; Poetsch, A.R.; Mahler, S.; Grützmann, R.; Pilarsky, C.; Schroeder, M. Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants. Cancers 2021, 13, 2654. https://doi.org/10.3390/cancers13112654

  Dataset EGAD00001006915

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of unknown primary (upper GI?) patient

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

  Dataset EGAD00001005837

• Genome and transcriptome sequence data from a colon adenocarcinoma patient

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

  Dataset EGAD00001005911

• pancreatic ductal adenocarcinoma exomes in study: Pro-immunogenic Impact of MEK inhibition combined with an anti-CD40 immunostimulatory antibody

  This dataset contains 3 pairs of exomes, germline (from whole blood) and patient-derived xenograft (PDX), from human pancreatic durctal adenocarcinoma patients. The data is referred to in the publication: "Pro-immunogenic impact of MEK inhibition synergizes with agonist anti-CD40 immunostimulatory antibodies in tumor therapy" (Nature Communications, 2020) Abstract: Cancer types with lower mutational load and a non-permissive tumor microenvironment are intrinsically resistant to immune checkpoint blockade. While the combination of cytostatic drugs and immunostimulatory antibodies constitutes an attractive concept for overcoming this refractoriness, suppression of immune cell function by cytostatic drugs may limit therapeutic efficacy. Here we show that targeted inhibition of mitogen-activated protein kinase (MAPK) kinase (MEK) does not impair dendritic cell-mediated T-cell priming and activation. Accordingly, combining MEK inhibitors (MEKi) with agonist antibodies (Abs) targeting the immunostimulatory CD40 receptor resulted in potent synergistic anti-tumor efficacy. Detailed analysis of the mechanism of action of MEKi GDC-0623 by means of flow cytometric analysis of the tumor immune infiltrate and whole tumor transcriptomics showed that, in addition to its cytostatic impact on tumor cells, this drug exerts multiple pro-immunogenic effects, including the suppression of M2-type macrophages, myeloid derived suppressor cells and CD4+ T-regulatory cells. In addition, MEKi was found to induce tumor-cell intrinsic interferon signaling, which contributed to antigen presentation by tumor cells. Finally, the tumoridical impact of MEKi involves the activation of multiple pro-inflammatory pathways involved in immune cell effector function in the tumor microenvironment. Our data therefore indicate that the combination of MEK inhibition with agonist anti-CD40 Ab is a promising therapeutic concept, especially for the treatment of mutant Kras-driven tumors such as pancreatic ductal adenocarcinoma.

  Dataset EGAD00001005938

• Illumina short-reads and 10X Genomics linked-reads sequencing data for MCF7 and a primary breast tumor sample

  This dataset contains whole genome sequencing data from Illumina short-reads sequencing (2X150bp) and 10X Genomics linked-reads sequencing. Both the sequencing technologies were used to sequence MCF7 cell line and a primary breast triple-negative cancer sample. The fastq of paired-end reads for both the samples sequenced with both the technologies is available.

  Dataset EGAD00001005724

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

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

  Dataset EGAD00001004596

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

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

  Dataset EGAD00001003051

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009304

• Guardians of the genome: protecting DNA from endogenous sources of damage

  Mutational signatures are imprints of cell-intrinsic and extrinsic pathophysiological processes that have occurred through tumorigenesis. Experimental efforts to explore signature etiologies have produced a compendium of signatures of exogenous mutagens previously. Here, we unearth major sources of endogenous DNA damage and the genes that are critical to mitigating this innate stream of DNA damage under normal, physiological circumstances. We performed whole genome sequencing of 173 subclones of CRISPR-Cas9 knockouts of 43 genes in a human induced pluripotent stem cell system, in the absence of any added DNA damage. We reveal substitution and indel signatures that arise from those genes which are essential guardians of the genome. By detailed dissection and comparisons to cancer-derived signatures, we demonstrate interminable sources of constitutive DNA damage, and some mechanistic knowledge into how guardian genes preserve the genome. Based on these experimental insights, we develop and benchmark a tool for clinical classification of tumor samples.

  Dataset EGAD00001006055

• Genome and transcriptome sequence data from a breast cancer patient

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

  Dataset EGAD00001002532

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia - RNA

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009305

• WES and RNA-seq of triple-negative breast cancers from the MyBrCa cohort

  The dataset contains a genomics characterization of 35 triple-negative Asian breast tumours from the Malaysian Breast Cancer cohort. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a NovaSeq 6000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a NovaSeq 6000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001009311

• Illumina_WXS_T-CELL-XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from PDO culture derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002101

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Gastric Organoids (2019-08-07)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005234

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

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

  Dataset EGAD00001002537

• RNAseq of human breast cancer tumors from the PEARL study

  Formalin fixed, paraffin-embedded human breast cancer tumor samples had RNA extracted using the Thermo Scientific KingFisher Flex instrument and the Applied Biosystems MagMAX FFPE DNA/RNA Ultra Kit; Total RNA libraries were created using the Bravo Automated Liquid-Handling Platform and the TruSeq Stranded Total RNA Library Prep Gold Kit; libraries were sequenced on the Illumina NovaSeq 6000 machine using a 2x50 bp paired-end configuration to target a read depth of 120 million clusters per library.

  Dataset EGAD00001015613

• Genome and transcriptome sequence data from a Ewing sarcoma patient

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

  Dataset EGAD00001005894

• 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 oligodendroglioma patient

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

  Dataset EGAD00001002539

• Genome and transcriptome sequence data from a breast cancer patient

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

  Dataset EGAD00001002540

• 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 EGAD00001003058

• Genome and transcriptome sequence data from a melanoma patient

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

  Dataset EGAD00001002546

• Exome and transcriptome sequence data from a breast cancer patient

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

  Dataset EGAD00001002547

• Genome and transcriptome sequence data from a cervical cancer patient

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

  Dataset EGAD00001002560

• CRUK Accelerator: oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Whole exome and RNASeq raw sequencing data for a cohort of 7 male patients with oesophageal adenocarcinoma. Median age at diagnosis was 68. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001008489

• Single Cell Genome Sequence for DLP+ library A95670B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6 on DLP+ library A95670B

  Dataset EGAD00001009449

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• Genome and transcriptome sequence data from a ductal carcinoma of left breast patient

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

  Dataset EGAD00001002574

• Normal sample for patient SA224

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA224

  Dataset EGAD00001009548

• Genome and transcriptome sequence data from a breast cancer patient

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

  Dataset EGAD00001002576

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• MutWP5: CRUK Mutographs of Cancer: Breast: BRCA Carriers (Exome) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005921

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• Single-cell RNA-sequencing of CD19 Chimeric Antigen Receptor (CAR) T-cells (CD19 CAR T-cells) from a Phase I clinical study in paediatric ALL: CARPALL

  Chimeric antigen receptor (CAR)-modified T-cells have become established as an effective treatment of haematological cancers. In the context of relapsed and refractory childhood pre-B cell acute lymphoblastic leukaemia (B ALL), CD19 targeting CAR T-cells often induce durable remissions. Previously, we generated a novel low-affinity CAR incorporating a CD19-specific single-chain variable fragment (scFV) called CAT, displaying a faster off-rate of interaction than the FMC63 CD19 binder used in prior clinical studies. Here, we systematically analysed CD19 CAR T-cells of ten children with relapsed or refractory B ALL enrolled in the CARPALL trial (NCT02443831). To characterize persisting CD19 CAR T-cells, we performed high throughput single-cell gene expression and T-cell receptor (TCR) sequencing of infusion products and serial blood and bone marrow samples up to five years post-infusion. We isolated CAR T-cells from peripheral blood or bone marrow by flow cytometry for CD3 and CAR expression, prior to single cell sequencing (Chromium 10X) platform.

  Dataset EGAD00001010018

• Chordoma Extension (known cancer genes)

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001239

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient

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

  Dataset EGAD00001002595

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010112

• MED12L Gene Alterations Define Aggressive BRCA2-Mutant Prostate Cancers

  Aligned sequence data from 14 Prostate cancer samples with BRCA2 mutations

  Dataset EGAD00001002739

• RNA sequencing data of 257 samples from the CORALLEEN trial

  Early-stage Luminal B breast cancer is frequent and is a major cause of breast cancer death due to its poor prognosis. Our proposal aims to study the biology behind the sensitivity and resistance of Luminal B breast cancer to chemotherapy (CHT) or a non-CHT regimen composed of hormone therapy in combination with ribociclib, a CDK4/6 inhibitor. To accomplish this, we first completed the SOLTI-1402 CORALLEEN phase II trial, a study where 106 patients with early-stage Luminal B breast cancer were randomized to standard neoadjuvant CHT for 6 months, or neoadjuvant letrozole and ribociclib for 6 months. After treatment, patients underwent surgery. The primary results of the study, which showed that the response rate to letrozole+ribociclib was similar to CHT, was reported (Prat et al; Lancet Oncol). Tumor biopsies were available at baseline, week 3 and surgery. A total of 257 samples were analyzed using the Illumina TruSeq Stranded Total RNA w/Ribo Zero Gold with MiSeq in TGL (Sequencer NovaSeq S4/PE/100x)

  Dataset EGAD00001010121

• Genome and transcriptome sequence data from a testicular cancer patient

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

  Dataset EGAD00001002632

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 30 women who mastectomies due to Breast Cancer. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005923

• Genome and transcriptome sequence data from a porocarcinoma patient

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

  Dataset EGAD00001002596

• WGS from PDAC samples

  Bam files from WGS of PDAC samples described in: Transcription phenotypes of pancreatic cancer are driven by genomic events events during tumour evolution

  Dataset EGAD00001006152

• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. Finally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Dataset EGAD00001005524

• RNA-seq data from 121 tumor samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). RNA-seq was performed using the QuantSeq kit FWD HT kit (Lexogen) using 500 ng input RNA from 121 tumor samples. Data provided here consist of 780 fastq files for RNA-seq.

  Dataset EGAD00001006238

• Genome and transcriptome sequence data from a multiple myeloma patient

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

  Dataset EGAD00001008947

• 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. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010123

• Colon Cancer Organoid Cultures and Tumors Whole Genome Sequencing Data

  Five hundred nanograms of genomic DNA was fragmented by Covaris S2, the fragmented DNAs were performed end-repair, A-tailing at the 3 prime end, adaptors ligation with an IDT dual-indexed UMI adaptor system at the terminal ends. The adapter ligated library with size range 300-750bp were selected by dual-SPRI method. Twenty percent of the size selected PCR-free libraries were enriched by 5 PCR cycles prior to library size assessment by Bioanalyzer Fragment Analyzer. The PCR-free libraries were quantified by qPCR.The PCR-free libraries were denatured and diluted to optimal concentration. Illumina NovaSeq 6000 was used for Pair-End 151bp sequencing.

  Dataset EGAD00001005759

• Tumour sample for patient SA720

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009585

• hereditary BrEAst Case CONtrol study (BEACCON)

  The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC.

  Dataset EGAD00001007025

• cfDNA analysis reveals relation of POLR1D amplification to bevacizumab resistance in colorectal cancer patients

  Bevacizumab is an approved anti-angiogenic drug for patients with metastasized colorectal cancer (mCRC) targeting VEGF. The survival benefit of anti-VEGF therapy in mCRC patients is limited to a few months and acquired resistance mechanisms are greatly unknown. Using plasma DNA, we studied the evolution of tumor genomes in a cohort of patients with mCRC (n=150) and observed a recurrent focal amplification (8.7% of cases) on chromosome 13q12.2. Analysis of TCGA data (n=619) suggested an association with later stages, which we confirmed by longitudinal plasma analyses. We defined the minimally amplified region and studied the mechanistic consequences of copy number gain of the involved genes. The amplification of one gene, POLR1D, impacted cell proliferation, resulting in upregulation of VEGFA, an important regulator of angiogenesis which has been implicated in the resistance to bevacizumab. In several patients, we observed the emergence of this 13q12.2 amplicon under bevacizumab treatment, which was invariably associated with evolution of therapy resistance. Hence, we describe a novel resistance mechanism against a widely applied treatment in mCRC patients which will impact clinical management .

  Dataset EGAD00001005761

• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 34 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&sE staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001010135

• 10x Single Cell Gene Expression Library TENX069

  10x Single Cell Gene Expression library TENX069 for Triple negative breast cancer patient-derived xenograft SA609X4XB03083

  Dataset EGAD00001011211

• Genome and transcriptome sequence data from a colorectal cancer patient

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

  Dataset EGAD00001002025

• Genome and transcriptome sequence data from a breast cancer patient

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

  Dataset EGAD00001002026

• 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

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. This dataset contains all the data available for this study on 2021-09-27.

  Dataset EGAD00001006083

• Genome and transcriptome sequence data from a breast cancer patient

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

  Dataset EGAD00001002635

• Genome and transcriptome sequence data from a metastatic adenocarcinoma patient

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

  Dataset EGAD00001003077

• Somatic mutation and clonal evolution in the human bladder WES-NOVASEQ (2020-05-05)

  n this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The study includes targeted sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer. . This dataset contains all the data available for this study on 2020-05-05.

  Dataset EGAD00001006117

• 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 EGAD00001003078

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

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

  Dataset EGAD00001003084

• Genome and transcriptome sequence data from a pancreatic cancer patient

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

  Dataset EGAD00001005893

• Dataset for melanoma-EXON

  Rare cancer sequencing data of 76 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008890

• 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 EGAD00001004898

• Dataset for melanoma-WHOLE_GENOME

  Rare cancer sequencing data of 22 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008889

• RNAseq of GEPARSIXTO

  294 formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer’s protocol (Promega 9FB167). 279 total RNA sequencing libraries were prepared at TGL using a Bravo Automated Liquid-Handling Platform (Agilent G5562A) and the TruSeq Stranded Total RNA Library Prep Gold Kit (Illumina 20020599) following the manufacturer’s protocol (Illumina 1000000040499). RNAseq library quality and quantity were measured using a TapeStation 4200 (Agilent G2991AA) and Qubit 3.0 fluorometer (Life Technologies Q33216), pooled at equal molar ratios, and denatured following the manufacturer’s protocol (Illumina 1000000106351). 271 total RNA sequencing libraries were sequenced at TGL on NovaSeq 6000 (Illumina 20012850) S4 flow cells (Illumina 20028313) following the manufacturer’s protocol (Illumina 1000000019358) using a 2x50 bp paired-end configuration and pool sizes of 91 libraries to target a read depth of 110 million clusters per library on average.

  Dataset EGAD00001010201

• Illumina_WXS_MET-CELL-XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from PDO culture derived from colorectal cancer metastasis sample

  Dataset EGAD00001002097

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001005907

• Genome and transcriptome sequence data from a pancreatic acinar cell adenocarcinoma patient

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

  Dataset EGAD00001008934

• Single cells of colorectal cancer organoids

  Dataset contains 854 single cell sequenced colorectal cancer organoids.

  Dataset EGAD00001005422

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001008933

• cfRRBS on cfDNA from pediatric cancer patients

  This dataset contains cell-free reduced representation bisulfite sequencing data from 60 pediatric cancer samples. Files are provided in fastq format. Samples were sequenced on a NextSeq 500.

  Dataset EGAD00001005928

• Molecular Characterization for Nasopharyngeal Carcinoma (NPC)

  Total RNA was isolated from 50 formalin-fixed paraffin-embedded nasopharyngeal cancer (NPC) specimens using the RecoverAll Total Nucleic Acid Isolation kit (Ambion). Tumor RNA libraries were prepared with 200ng RNA using the Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold, and sequenced with >80 million 100 bp paired-end reads.

  Dataset EGAD00001009047

• Congenital mesoblastic nephroma and infantile fibrosarcoma

  The genetic basis of many rare childhood cancers remains unknown. These include a spectrum of infant soft tissue tumors without canonical gene fusions, encompassing congenital mesoblastic nephroma (CMN) of the kidney and infantile fibrosarcoma (IFS). Here, we integrated whole genome and transcriptome sequencing and identified diagnostic markers and novel therapeutic strategies.

  Dataset EGAD00001003884

• Early breast cancer (WES)

  Whole-exome sequencing of 30 early breast cancer samples.

  Dataset EGAD00001007057

• TONIC study Whole Exome Sequencing

  Paired-end whole exome sequencing of 50 TNBC breast cancer metastasis samples and matched normal samples obtained from 50 unique patients assayed at study baseline (directly after patient randomization). The included raw sequencing data (fastq-format) were generated using Illumina HiSeq2500 instruments.

  Dataset EGAD00001004857

• CITE-seq of early breast cancer

  CITE-seq of early breast cancer samples.

  Dataset EGAD00001007058

• The University of Hong Kong Gastric Cancer RHOA Study RNASeq Data

  RNAseq data generated from paired tumor frozen tissues in which the tumor organoids were established for cell-cell or cell-matrix adhesion dependency assay.

  Dataset EGAD00001008830

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Genome and transcriptome sequence data from a metastatic melanoma patient

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

  Dataset EGAD00001004931