7147 results for "canc*"

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• 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

• Targeted DNA sequencing

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 243 HGSC tumours (15 primary, 3 relapse, 225 end-stage) and 15 normals from 15 HGSC patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Dataset EGAD00001009747

• cfDNA from fractionated and paired unfractionated plasma samples of lung cancer patients

  Plasma from lung cancer patients from EDTA tubes was fractionated using size exclusion chromatography. Fractions 1-5, 7-11, 12-15, 16-20 were pooled, cfDNA was extracted from the fractions and paired unfractionated samples and PE150bp sequencing was performed on an Illumina Novaseq S4 flowcell. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001009780

• Single cell RNA-sequencing of tissues from NSCLC patients treated with chemoimmunotherapy

  The goal of this study is to characterize immune cell populations by single cell RNA-sequencing (scRNA-seq) in tumor and uninvolved normal tissues from non-small cell lung cancer (NSCLC) patients with resectable non-small cell lung cancer and who received neoadjuvant chemoimmunotherapy. scRNA-seq was performed on seven pairs of tumor and normal tissues as well as one lymph node (LN) sample. Data set includes pair-end fastq files for single cell RNA sequencing of 7 neo-immuno patients. (Total 15 samples and 50 runs).

  Dataset EGAD00001009778

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015302

• MethylScan data of plasma samples

  10ng from each cfDNA sample was used as the input material. For gDNA samples, 1.5-2ug each was first sonicated by Covaris R230 system (Woburn, MA). Next, size-selection with 0.8x-1.5x two-step Ampure XP beads was performed to enrich the 150-200bp fragments. 200ng of the size-selected gDNA was used as input material. The pre-capture library construction was performed with NEB UltraII DNA library prep kit for Illumina (Ipswich, MA) and the adapter was the methylated EM-seq adapter. Before the first PCR amplification, the gDNA samples were subjected to bisulfite conversion by QIAGEN Epitect kit, and cfDNA samples were subjected to enzymatic conversion by NEBNext enzymatic methyl-seq kit if the hybrid capture panel designed for converted DNA was used downstream. Twist panel hybrid capture was performed with their standard protocol (Twist Bioscience, South San Francisco, CA). The concentration of the post-capture library after the second PCR amplification was measured by Qubit 1xdsDNA HS kit (ThermoFisher, Waltham, MA). Their quality was examined by TBE-UREA PAGE and Bioanalyzer before sequencing. Libraries were then sequenced with 150bp paired-end reads on Illumina machines by Genewiz, Inc. (South Plainfield, NJ, USA). This dataset contains MethylScan data of the plasma samples from 248 noncancer individuals and 27 cancer patients (17 liver and 10 GI-tract cancers).

  Dataset EGAD00001015815

• Myeloma Genome Project Targeted Panel Validation dataset

  372 samples consisting of 185 patient paired CD138+ tumor and non-involved DNA pairs, plus 5 Horizon Diagnostic known mutation standards (HD). Samples were processed using the KAPA HyperCap protocol and hybridized onto a targeted panel for multiple myeloma and associated diseases. Reference Sudha et al Clinical Cancer Research, 2022.

  Dataset EGAD00001008689

• November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001007529

• Tumour sample for patient SA601

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA601

  Dataset EGAD00001009205

• Normal sample for patient SA604

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA604

  Dataset EGAD00001009217

• Tumour sample for patient SA590

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA590

  Dataset EGAD00001009196

• Tumour sample for patient SA588

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA588

  Dataset EGAD00001009194

• PELICAN33 Phenomic Dataset

  To better understand variation in metastatic prostate cancer behaviour, we assembled and analyzed longitudinal clinical and autopsy records in 33 men. The dataset is contained in a self-explanatory Excel Workbook, with each patient identified as A1, A2, etc. as listed in the "Combined longitudinal clinical and autopsy phenomic assessment in lethal metastatic prostate cancer: recommendations for advancing precision medicine" publication in European Urology Open Science. Please see Jasu J, Tolonen T, Antonarakis ES, Beltran H, Halabi S, Eisenberger MA, Carducci MA, Loriot Y, Van der Eecken K, Lolkema M, Ryan CJ, Taavitsainen S, Gillessen S, Högnäs G, Talvitie T, Taylor RJ, Koskenalho A, Ost P, Murtola TJ, Rinta-Kiikka I, Tammela T, Auvinen A, Kujala P, Smith TJ, Kellokumpu-Lehtinen PL, Isaacs WB, Nykter M, Kesseli J, Bova GS. Combined Longitudinal Clinical and Autopsy Phenomic Assessment in Lethal Metastatic Prostate Cancer: Recommendations for Advancing Precision Medicine. Eur Urol Open Sci. 2021 Jul 2;30:47-62. doi: 10.1016/j.euros.2021.05.011. PMID: 34337548; PMCID: PMC8317817. for more details.

  Dataset EGAD00001007800

• Normal sample for patient SA398

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009231

• Tumour sample for patient SA654

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA654

  Dataset EGAD00001009206

• Clonal dynamics of normal haematopoiesis across the human lifespan

  Age-related loss of function in the human haematopoietic system is well documented, manifesting as reduced regenerative capacity, age-related cytopenias and immune dysfunction. However, the cellular and population level changes that underpin both this functional decline and the increased risk of clonal haematopoiesis and blood cancer in the elderly remain elusive. Here we performed whole genome sequencing on >3350 single haematopoietic stem cell / multipotent progenitors (HSC/MPP) derived colonies across 10 haematologically normal subjects aged 0 to 81. We found that HSC/MPPs accumulated 17 single nucleotide variants per year post birth and had a reduction in telomere length of 50bp per year throughout young adult life. We reconstructed phylogenies of the sampled HSC/MPPs to interrogate changes in clonal dynamics through life. Haematopoiesis in adults aged less than 65 was predominantly polyclonal, with few known driver mutations. In contrast, individuals aged over 75 displayed a profound change in clonal structure, with frequent clonal expansions, many unexplained by known driver mutations. The ratio of non-synonymous to synonymous mutations revealed widespread positive selection, estimating around 1000 driver mutations in the dataset (10-fold more than the number of known drivers). We identified novel genes ZNF318 and HIST2H3D as being under positive selection, despite not being enriched in myeloid malignancies. Our data show that HSC clonal dynamics is more complex than previously thought. One implication is that by old age, the majority of HSCs carry at least one of a number of largely undescribed driver mutations, which may underlie aspects of their functional decline.

  Dataset EGAD00001007851

• Genomic characterization of co-existing biliary tract intraepithelial neoplasia and carcinoma lesions reveals distinct evolutionary paths of gallbladder cancer

  Gallbladder carcinoma is the most common cancer of the biliary tract with dismal survival largely due to delayed diagnosis. Biliary tract intraepithelial neoplasia (BilIN) is the common benign tumor that is suspected to be precancerous lesions. However, the genetic and evolutionary relationships between BilIN and carcinoma remain unclear. Here we performed whole-exome sequencing of coexisting low-grade BilIN (adenoma), high-grade BilIN, and carcinoma lesions, and normal tissues from the same patients.

  Dataset EGAD00001007792

• Somatic mutation rates scale with lifespan across mammals

  The rates and patterns of somatic mutation in normal tissues are largely unknown outside of humans. Comparative analyses can shed light on the diversity of mutagenesis across species and on long-standing hypotheses regarding the evolution of somatic mutation rates and their role in cancer and ageing. Here, we used whole-genome sequencing of 208 intestinal crypts from 56 individuals to study the landscape of somatic mutation across 16 mammalian species. We found somatic mutagenesis to be dominated by seemingly endogenous mutational processes in all species, including 5-methylcytosine deamination and oxidative damage. With some differences, mutational signatures in other species resembled those described in humans, although the relative contribution of each signature varied across species. Remarkably, the somatic mutation rate per year varied greatly across species and exhibited a strong inverse relationship with species lifespan, with no other life-history trait studied displaying a comparable association. Despite widely different life histories among the species surveyed, including ~30-fold variation in lifespan and ~40,000-fold variation in body mass, the somatic mutation burden at the end of lifespan varied only by a factor of ~3. These data unveil common mutational processes across mammals and suggest that somatic mutation rates are evolutionarily constrained and may be a determinant of lifespan.

  Dataset EGAD00001008032

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  HSPCs were sorted as CD34+ cells from bone marrow of patients with Hodgkin Lymphoma (HL). Control samples were isolated before initiating treatment.These were compared to samples from two additional HL patients who had relapsed and were being treated with nivolumab. Nivolumab was administered at a dose of 240 mg every two weeks, with BM samples collected the day before the scheduled dose. The patients receiving nivolumab were in remission at the time of BM collection. RNA was extracted using Arcturus™ PicoPure™ RNA Isolation Kit (Thermo Fisher Scientific, #12204-01) ` instructions. Paired-end sequencing was reads were generated for each sample in the Illumina Novaseq 6000 system.

  Dataset EGAD00001015403

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• CITE-seq for peripheral blood samples of 5 breast cancer patients

  We have 5 breast cancer patients who received VEN therapy. We collected their peripheral blood samples before and after long-term Venetoclax treatment. We apply CITE-seq protocol to these samples. This collection contains the all CITE-seq data for patients.

  Dataset EGAD00001008751

• Spatially confined sub-tumor microenvironments in pancreatic cancer

  Intratumoral heterogeneity is a critical frontier in understanding how the tumor microenvironment (TME) propels malignant progression. Here, we deconvolute the human pancreatic TME through large-scale integration of histology-guided regional multiOMICs with clinical data and patient-derived preclinical models. We discover subTMEs, histologically definable tissue states anchored in fibroblast plasticity, with regional relationships to tumor immunity, subtypes, differentiation, and treatment response. Reactive subTMEs rich in complex but functionally coordinated fibroblast communities were immune-hot and inhabited by aggressive tumor cell phenotypes. The matrix-rich deserted subTMEs harbored less activated fibroblasts and tumor- suppressive features yet were markedly chemoprotective and enriched upon chemotherapy. SubTMEs originated in fibroblast differentiation trajectories and transitory states were notable both in single cell transcriptomics and in situ. The intratumoral co-occurrence of subTMEs produced patient-specific phenotypic and computationally predictable heterogeneity tightly linked to malignant biology. Therefore, heterogeneity within the plentiful, notorious pancreatic TME is not random but marks fundamental tissue organizational units.

  Dataset EGAD00001008155

• Clinical data

  Clinical data from this cohort of patients, including hormone sensitive or castration resistant prostate cancer, overall survival, NMF subtypes, tumor TMB, prior treatment status, PD-L1 IC and TC scores from SP142 and SP263 as well as percentage of CD8 IHC at tumor center.

  Dataset EGAD00001008761

• Whole Exome Sequencing of Localized Prostate Cancer Patients

  Whole exome sequencing of localized prostate cancer patients in this study contained pair tumor-normal samples and validated tumor content.

  Dataset EGAD00001008274

• Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens

  Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor “purity.” Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling.

  Dataset EGAD00001008344

• Healthy control and lung cancer plasma cfDNA samples from various collection tubes

  The dataset contains 6 lung cancer and 60 healthy control plasma cfDNA samples collected in EDTA, PAXGene and Norgen blood collection tubes at various locations. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001008322

• SGCC GASCAD-II dataset

  The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

  Dataset EGAD00001015433

• Targeted Myeloid DNA-Panelsequencing, MLL

  Sequencing data from a targeted myeloid DNA-Panelsequnencing at the MLL Dx, Munich lab. Targeted sequencing was performed using the Nextera DNA Flex library preparation kit, starting with 100ng of genomic DNA (Illumina, San Diego, CA, USA). The target regions were enriched by a custom xGen Lockdown panel using a hybridization capture workflow (IDT Integrated DNA Technologies, Coralville, IA, USA). All libraries were sequenced with 100bp paired-end reads on a NovaSeq6000 (Illumina) with a mean coverage of 3206x. Somatic variant calling was performed with Pisces and a sensitivity cut off of 2%. Large deletions and medium-sized insertions, as they are for example found in CALR and FLT3, were called with Pindel. Variant annotation considered the publicly available data bases Cosmic (v91), ClinVar (2020-03), gnomAd (non-cancer, v2.1.1), dbNSFP (v3.5) and UMD TP53 (2017_R2). Variants that are described as somatic, protein truncating or affecting splice sites were considered as mutations while variants with no or discrepant data base information were considered as variant of uncertain significance.

  Dataset EGAD00001008485

• Tumour sample for patient SA226

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA226

  Dataset EGAD00001009532

• Tumour sample for patient SA231

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA231

  Dataset EGAD00001009535

• Tumour sample for patient SA234

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA234

  Dataset EGAD00001009525

• Exome and RNA sequencing of pancreatic cancer biopsies and PDX models

  Pancreatic cancer biopsies and matching normal controls from 10 patients were exome sequenced. The same biopsies and PDX models derived from these were also subject to RNA sequencing.

  Dataset EGAD00001008113

• Targeted seqencing of serrated lesions of the colorectum

  Dataset consists of Oncomine Comprehensive Cancer Panel v3 sequencing of 16 tumor-normal mucosa pairs. Tumors include 8 sessile serrated lesions (SSL), 3 sessile serrated lesions with dysplasia (SSL/D), 2 traditional serrated adenomas (TSA) and 3 tubular adenoma s(TA).

  Dataset EGAD00001008191

• Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor infiltrating T cells.

  Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying functional and dysfunctional states of human tumor infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify tissue-specific and general gene-regulatory landscapes in the wide breadth of CD8+ TIL functional states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor entity-matching samples and prioritize key elements by super enhancer analysis. Our analysis reveals a human core chromatin trajectory to TIL dysfunction and identifies key enhancers, transcriptional regulators, and deregulated target genes involved in this process. Finally, we validate enhancer regulation at loci encoding PD1, TCF1, and TIM3 by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study advances the understanding of molecular regulation of TIL (dys-)function and provides a framework for modulating immunotherapeutic relevant TIL genes via their enhancers.

  Dataset EGAD00001008662

• Pre-neoadjuvant treatment biopsy RNAseq breast cancer dataset

  This dataset contains RNAseq data of n=87 pre-treatment biopsies of triple negative and luminal- type breast cancer patients, all scheduled to receive neoadjuvant chemotherapy. Gene expression data is linked with treatment response and survival.

  Dataset EGAD00001008433

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination.

  Dataset EGAD00001008696

• 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

• Normal sample for patient SA591

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA591

  Dataset EGAD00001009241

• Bulk RNA sequencing of Singapore colorectal cancer patients (SG-BULK)

  RNA-seq libraries were prepared using the KAPA Stranded RNA-Seq Kit with RiboErase (Kapa Biosystems, Wilmington, MA) and sequenced to a target depth of 200-M reads on the Illumina HiSeq platform (Illumina, San Diego, CA).

  Dataset EGAD00001008512

• Tumor/Normal WXS and RNASeq from patients dosed with neoTCR T-cell therapy

  Sixteen patients with refractory solid cancers received up to three distinct neoTCR-transgenic cell products, each expressing a patient-specific neoTCR, in a cell dose-escalation, first-in-human phase 1 clinical trial (NCT03970382). Included are the tumor and normal WXS and tumor RNAseq for dosed patients.

  Dataset EGAD00001009830

• Single cell RNA sequencing of colorectal cancer patients (CRC-SG1)

  Raw sequencing reads were processed as single end sequencing, aligned to the human reference genome GRCh38 and processed using CellRanger 3.1.

  Dataset EGAD00001008555

• Evolutionary trajectories and clonal migration underlying tumor progression and lymph node metastasis in resectable lung cancer

  In this prospective study, targeted deep sequencing was performed on a total of 160 primary tumors (474 regions) and 112 lymph nodes from 125 patients with stage I-III lung cancer (LuCaTH). Progressive evolution at clonal divergence scale was observed while specific driver events were positively selected for clonal sweeps during tumor development. Between-region genetic divergence (BRGD) of tumors were assessed and positively correlated with tumor differentiation. A machine learning algorithm was employed to evaluate clinicopathological and molecular parameters of primary tumors underlying lymph node metastasis. By analyzing clonal lineages and metastatic trajectories across multiple nodal stations, we unraveled a common sequential LNM seeding pattern but with divergent modes of clonal spread.

  Dataset EGAD00001007587

• Genome and transcriptome sequence data from a uveal melanoma patient

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

  Dataset EGAD00001010956

• Mutation analysis of core biopsies from localized breast cancer patients

  Targeted next-generation sequencing (NGS) of 93 frequently mutated genes in breast cancer using the QIAseq Human Breast Cancer Targeted Panel (QIAGEN), which uses digital sequencing by incorporating unique molecular barcodes (UMI).

  Dataset EGAD00001008396

• cfMeDIP data for 22 WCDT samples

  We analyzed the cell free DNA methylomes using 22 plasma samples from patients with mCRPC prostate cancer in the WCDT project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008713

• TGL49_HBC CHARM panel

  Targeted panel sequencing of hereditary cancer syndrome-associated genes (TP53, BRCA1, BRCA2, PALB2, MLH1, MSH2, MSH6, PMS2, EPCAM, and APC) in plasma and buffy coat samples from healthy control patients.

  Dataset EGAD00001010001

• 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

• Tumour sample for patient SA591

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA591

  Dataset EGAD00001009197

• 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

• META-PRISM

  A pan-cancer cohort of 1031 patients resistant to systemic therapies or with no approved therapeutic options. It includes whole-exome sequencing of 571 tumor and matched-normal samples, and transcriptome sequencing of 947 tumor samples. Biopsies were taken at entry into precision medicine trials, often after diagnosed resistance. Comprehensive clinical information is available for all patients and include patient age at biospy, tumor primary site and histological subtype, biopsy site, treatments received prior to biopsy, blood assessment results at biopsy, metastatic sites at biopsy, and survival time from the biopsy date.

  Dataset EGAD00001009684