9903 results for "cancer rna-seq"

in 50.03 milliseconds.

• DNA sequencing for human normal endometrial glands

  To elucidate the timing and mechanism of the clonal expansion of somatic mutations in cancer-associated genes in the normal endometrium, we conducted whole-exome and whole-genome sequencing for 56 endometrial glands and matched blood samples from 4 women. By collecting endometrial glands from different parts of the endometrium, we showed that multiple glands with the same somatic mutations occupied substantial areas of the endometrium.

  Study EGAS00001005822

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (Targeted) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005925

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (Targeted) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006929

• Lung cancer and non-cancerous plasma cfDNA samples

  The dataset contains 90 lung cancer and 5 non-cancerous lung lesion plasma cfDNA samples collected in EDTA blood collection tubes. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001008666

• Detection of cancer cell transcriptomes

  Single cell transcriptomes, generated using chromium 10X 3' sequencing, for two tumour types (AT/RT, and Ewing's sarcoma). For each individual, tumour and normal whole genome sequencing was also obtained using Illumina short read sequencing to an average depth of 30X. These data were used to validate the accuracy of a method for identifying cancer cell transcriptomes based on the allelic shift produced by copy number changes.

  Dataset EGAD00001009005

• WES and RNAseq of Simultaneous Bilateral Breast Cancer

  This dataset includes NGS profiling of 13 women with simultaneous bilateral breast cancer. Seven women have WES of untreated surgical resections and matched healthy tissue. The six other women have WES of healthy tissue, WES+RNAseq of pre-neoadjuvant tumor biopsies, and when residual disease was present (6 tumors in 4 patients), WES+RNAseq of residual disease from post-neoadjuvant therapy surgery. One patient from the WES+RNAseq cohort had multifocal bilateral disease at diagnosis so there are 2 pre-neoadjuvant biopsy samples from each breast.

  Dataset EGAD00001009987

• Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect the cell type heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Whole exome sequencing and transcriptome analysis in various in vitro and in vivo contexts was performed to study the influence of the TME on the CRC phenotype.

  Dataset EGAD00001011173

• 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

• Exome sequencing of early and late passage Patient Derived Xenogratf Tumoroids with matched Patient Derived Xenogratfs and matched normal liver

  The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. In this specific dataset we focused our attention on early (passage 3) and late (passage 8-12) PDXTs with their matched PDXs and normal liver

  Dataset EGAD50000000266

• Acral melanoma targeted exome sequencing study (UCSF)

  Acral melanoma affects world populations irrespective of skin color. It has comparatively few single nucleotide mutations, but exhibits genomic instability characterized by structural rearrangements and amplifications. As acral melanoma harbors BRAF (GeneID:673) mutations at low frequencies, we searched for alternative therapeutic targets. We performed targeted deep sequencing of cancer-related genes on 37 acral melanomas and identified point mutations, structural rearrangements and copy number alterations.

  Study phs001596

• Sequencing_Acute_Myeloid_Leukaemia_

  This project will aim at sequencing and analysing three samples from a patient with acute myeloid leukaemia (AML) with t(15;17) translocation (acute promyelocytic leukaemia). The patient was treated with standard chemotherapy and samples (blood and bone marrow) taken for minimal residual disease measured during and after chemotherapy. 2-3years later the patient presented a second AML containing inv (16).In this project we will sequence both AML and normal genomes to find associated mutations This will allow unprecedented insights into the dynamics of appearance of secondary AML, since we will be able to use the MRD samples to track the emergence of the inv(16) leukaemia. We will also be able to distinguish whether the 2 leukaemias are clonally related or not. This project will entail sequencing and analysis of three samples (whole genome 30x coverage) using Hi-Seq. The funds from this grant will cover the cost of sequencing 9 lanes from the AML t(15;17) sample, 9 lanes from AML inv(16) sample and 8 lanes from the normal genome.

  Study EGAS00001000035

• Genes associated with pancreas development and function maintain open chromatin in iPSCs generated from human pancreatic beta cells

  Current in-vitro islet differentiation protocols suffer from heterogeneity and low efficiency. Induced-pluripotent stem cells (iPSCs) derived from pancreatic beta-cells (BiPSCs) preferentially differentiate towards endocrine pancreas-like cells versus those from fibroblasts (FiPSCs). We interrogated genome-wide open chromatin in BiPSCs and FiPSCs via ATAC-seq, and identified ~8.3k significant, differential open chromatin sites (DOCS) between the two iPSC subtypes (FDR<0.05). DOCS where chromatin was more accessible in BiPSCs (Bi-DOCS) were significantly enriched for known regulators of endodermal development, including bivalent and weak enhancers, and FOXA2 binding sites (FDR<0.05). Bi-DOCS were associated with genes related to pancreas development and beta-cell function, including transcription factors mutated in monogenic diabetes (PDX1, NKX2-2, HNF1A; FDR<0.05). Moreover, Bi-DOCS correlated with enhanced gene expression in BiPSC-derived definitive endoderm and pancreatic progenitor cells. Bi-DOCS therefore highlight genes and pathways governing islet-lineage commitment, which can be exploited for differentiation protocol optimisation, diabetes disease modelling, and therapeutic purposes.

  Study EGAS00001002591

• EPICC: Evolutionary Predictions in Colorectal Cancer

  ATAC-seq profiling bam files from colorectal carcinoma and adenoma.

  Dataset EGAD00001008140

• ICGC Breast Cancer Project

  A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches including genomics, transcriptomics and epigenomics.

  Study EGAS00001001195

• Mosaic_Colorectal_Metastasis

  A comparison of the somatic variation present in a primary colorectal tumour and three different liver metastases from the same patient.

  Study EGAS00001000613

• PREDICT___Whole_Genomes

  PREDICT/Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics.

  Study EGAS00001000934

• BASIS RNAseq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001264

• BASIS WGBS

  Whole-genome bisulfite sequencing (WGBS) on 30 breast cancer cases from the BASIS project.

  Dataset EGAD00001001388

• Illumina_RNA_MET-CELL-XEN

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

  Dataset EGAD00001002075

• RNAseq of LC2AD with AD80 or DMSO

  RNAseq of LC2AD with AD80 or DMSO Plenker et al., Mechanistic insight into RET kinase inhibitors targeting the DFG-out conformation in RET-rearranged cancer

  Dataset EGAD00001003316

• Anaplastic Thyroid Cancer somatic variants (SomaticSniper)

  Sequence was aligned to the GRCH38 reference genome. Aligned sequence was analyzed with SomaticSniper. Somatic variant calls are in VCF format. In total there are 94 tumour samples, each with a matched normal.

  Dataset EGAD00001004128

• PanCurX Translational Research Initiative - WGS mapped reads

  Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases - WGS mapped reads

  Dataset EGAD00001004551

• Single cell PDAC samples

  h5 files from 15 single cell PDAC samples described in "Transcription phenotypes of pancreatic cancer are driven by genomic events events during tumour evolution"

  Dataset EGAD00010001811

• Targeted sequencing of HGS-EOC samples

  A 19-sample data set containing data from FFPE high grade serous ovarian cancer biopsies. The library was made with a custom hybridization kit (EZ-Cap, Roche) spanning 7 genes.

  Dataset EGAD00001006064

• scRNA mCRC PDO

  Chromium 10x scRNA of 6 metastatic colorectal cancer organoids

  Dataset EGAD00001008734

• Sequencing data for the manuscript "Early on-treatment changes in circulating tumor DNA fraction and response to enzalutamide or abiraterone in metastatic castration-resistant prostate cancer"

  This submission contains gzipped fastq files from paired-end targeted sequencing.

  Dataset EGAD00001010105

• Breast cancer topographs

  Whole genome sequencing to identify subclonal variants for subsequent mapping back to fixed tissue specimens. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010124

• 10x Single Cell Gene Expression Library TENX048

  10x Single Cell Gene Expression library TENX048 for Triple negative breast cancer sample SA535X5XB02895

  Dataset EGAD00001011222

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Transcriptomic sequencing on pre-immunotherapy melanoma patients.

  Dataset EGAD00001007710

• Acquired RAD51C promoter methylation loss causes PARP inhibitor resistance in high grade serous ovarian carcinoma

  Analysis of RAD51C promoter methylation using targeted bisulfite sequencing (amplicon sequencing) in ovarian cancer pre-clinical models and patient samples.

  Dataset EGAD00001007799

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 2)

  Whole genome sequencing data of 35 high-grade serous carcinoma (HGSC) patients (112 samples) sequenced with Illumina Novoseq 6000

  Dataset EGAD00001011368

• Evolutionary Trajectories of Small Cell Lung Cancer under Therapy

  We performed whole exome sequencing, whole genome sequencing and transcriptome sequencing of multiple tumor regions from 65 patients with SCLC.

  Dataset EGAD50000000243

• Whole genome analysis of liver cancer by long-read sequencing

  Aberrant integration of Hepatitis B virus DNA promotes major restructuring of human hepatocellular carcinoma genome architecture

  Study JGAS000361

• Genome and transcriptome sequence data from a diffuse aarge B-cell lymphoma (relapse) tumor patient

  Genome and transcriptome sequence data from a diffuse large B-cell lymphoma (relapse) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015308

• Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm tumor patient

  Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015312

• Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor tumor patient

  Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015322

• Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour tumor patient

  Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015327

• Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness

  RNAseq from patient-derived primary tumor cells, cultured or not on organotypic cultures mimicking the tumor microenvironment

  Study EGAS50000000355

• The University of Hong Kong Gastric Cancer XClone Study WES Data

  Exome capturing was performed using xGen Exome Research Panel v1.0 based on standard protocols. Paired-end sequencing (2 x 151 bp) was performed using Illumina NovaSeq6000.

  Dataset EGAD00001015382

• Whole genome and transcriptome analysis of a sporadic and recurring parathyroid carcinoma

  Parathyroid carcinoma is an extremely rare endocrine malignancy with an estimated incidence of less than 1 per million population. Excessive secretion of parathyroid hormone, extremely high serum calcium level and the deleterious effects of hypercalcemia are the clinical manifestations of the disease. Up to 60% of patients develop multiple disease recurrences and although long-term survival is possible with palliative surgery, permanent remission is rarely achieved. Molecular drivers of sporadic parathyroid carcinoma have remained largely unknown. Previous studies, mostly based on familial cases of the disease, suggested a potential role for the tumor suppressor MEN1 and proto-oncogene RET in benign parathyroid tumorigenesis while the tumor suppressor HRPT2 and proto-oncogene CCND1 may also act as drivers in parathyroid cancer. Here, we report the complete genomic analysis of a sporadic and recurring parathyroid carcinoma. Mutational landscapes of the primary and recurrent tumor specimens were analyzed using high throughput sequencing technologies. Such molecular profiling allowed for identification of somatic mutations never previously identified in this malignancy. These included single nucleotide point mutations in well characterized cancer genes such as mTOR, MLL2, CDKN2C and PIK3CA. Comparison of acquired mutations in patient-matched primary and recurrent tumors revealed loss of PIK3CA activating mutation during the evolution of the tumor from the primary to the recurrence. Structural variations leading to gene fusions and regions of copy loss and gain were identified at a single-base resolution. Loss of short arm of chromosome 1 along with somatic mis-sense and truncating mutations in CDKN2C and THRAP3, respectively, provide new evidence for the potential role of these genes as tumor suppressors in parathyroid cancer. The key somatic mutations indentified in this study can serve as novel diagnostic markers as well as therapeutic targets.

  Study EGAS00001000484

• Similarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer.

  The tumor microenvironment is pivotal in influencing cancer progression and metastasis. Different cells co-exist with high spatial diversity within a patient, yet their combinatorial effects are poorly understood. We investigate the similarity of the tumor microenvironment of 192 local metastatic lesions in 61 ovarian cancer patients. An ecologically inspired measure of microenvironmental diversity derived from multiple metastasis sites is correlated with clinicopathological characteristics and prognostic outcome. We demonstrate a high accuracy of our automated analysis across multiple sites. A low level of similarity in microenvironmental composition is observed between ovary tumor and corresponding local metastases (stromal ratio r = 0.30, lymphocyte ratio r = 0.37). We identify a new measure of microenvironmental diversity derived from Shannon entropy that is highly predictive of poor overall (p = 0.002, HR = 3.18, 95% CI = 1.51-6.68) and progression-free survival (p = 0.0036, HR = 2.83, 95% CI = 1.41-5.7), independent of and stronger than clinical variables, subtype stratifications based on single cell types alone and number of sites. Although stromal influence in ovary tumors is known to have significant clinical implications, our findings reveal an even stronger impact orchestrated by diverse cell types. Quantitative histology-based measures can further enable objective selection of patients who are in urgent need of new therapeutic strategies such as combinatorial treatments targeting heterogeneous tumor microenvironment.

  Study EGAS00001002065

• Oncogenic Ectodomain deletion of FGFR1 caused by Breakage-Fusion-Bridges in Squamous Cell lung Cancer

  The identification of recurrent 8p11.23 amplifications including FGFR1 raised the hope of a treatable target in squamous cell lung cancer (SQLC). However, only a minority of patients with FGFR1-amplified tumors respond to single agent inhibitor therapy targeting FGFR. To understand the underlying mechanism of FGFR1 dependency, we performed whole genome and transcriptome sequencing of 25 FGFR1-amplified primary tumors with unknown response upon FGFR inhibition. In addition, we performed deep sequencing of 26 FGFR1-amplified samples whereof the response upon FGFR inhibition was known for 25 samples. In both cohorts we identified intra-chromosomal tail-to-tail breaks close to the FGFR1 transcription start site, being responsible for focal amplification of FGFR1. These specific breaks are caused by a Breakage-Fusion-Bridge-like (BFB-like) mechanism. Here, we associate these breaks with FGFR inhibitor sensitivity. Moreover, in some cases these breaks are located within the open reading frame of FGFR1, which leads to the expression of an ΔEC-FGFR1 transcript that lacks the ecto-domain. Overexpression of ΔEC-FGFR1 transforms Baf3 cells and lead to an FGFR1-dependent phenotype. Our results demonstrate that the truncation of the FGFR1 ectodomain is a frequent event in 8p11.23-amplified squamous cell lung cancer caused by tail-to-tail breaks. These breaks might be used as a predictive therapeutic marker to stratify patients for FGFR-inhibitor therapy.

  Study EGAS00001005059

• Localised colon cancer WES study contaning WBCs, tissue and plasma samples at different time points

  Decision-making based on circulating tumor DNA (ctDNA) status following curative-intent surgery in stage II-III colon cancer (CC) is where the strongest clinical evidence lies. Commercial or academic assays are predominantly used to detect ctDNA, aiming to reveal minimal residual disease (MRD) and identify patients at high risk of recurrence. However, while current tests demonstrate exceptional specificity in detecting MRD among patients who later experience recurrence, their sensitivity is notably limited, particularly immediately after surgery when decisions regarding ACT are crucial. Additionally, up to 70% of patients with stage II-III colon cancer fail to clear ctDNA after standard adjuvant treatment (ACT) and subsequently experience recurrence. In this study, we performed whole exome sequencing (WES) of ctDNA at different timepoints in relapsed CC patients using two independent cohorts, alongside transcriptomic and proteomic analyses of metastases to gain a deeper understanding of progression mechanisms. An assay based on a tumor-agnostic approach from WES could enhance sensitivity in detecting MRD disease compared to current assays. Immune evasion appears to be the primary driver of progression in the localized CC setting, facilitated by a functional mutational burden at relapse. This suggests that immunotherapy could extend its efficacy to patients with microsatellite stability, broadening treatment options. Moreover, organoid modeling affirms the promising potential of targeted therapy to surpass conventional treatments in eradicating MRD.

  Study EGAS50000000204

• Genome-wide mutational consequences of nucleotide excision repair-deficiency through XPC deletion in a human adult stem cell culture

  Nucleotide excision repair (NER) is one of the main DNA repair pathways that protect cells against genomic damage. Deficiency in this pathway can contribute to the development of cancer and accelerate aging. NER-deficiency is an important determinant for cancer treatment outcome, as NER-deficient tumors are selectively sensitive to cisplatin treatment. While NER-deficiency has been linked to mutational Signature 5, not all NER-deficient tumors are characterized by a high Signature 5 contribution, illustrating the importance to further characterize the mutational consequences of NER-deficiency. Here, we analyzed the mutational profile of a human adult stem cell (organoid) culture that is deficient in NER through XPC deletion by CRISPR-Cas9 gene-editing, and subsequent whole-genome sequencing analysis of a clonally derived organoid. We found that XPC deletion results in an increase in base substitution load and specifically induces Signature 8 mutations, a mutational signature with previously unknown etiology. Presence of Signature 8 may, therefore, serve as a novel biomarker for NER-deficient tumors and could improve personalized treatment strategies.

  Study EGAS00001002681

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures (Hipo_021)

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which escape discovery using short-read sequencing. We employed Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed ‘templated insertion thread’ (TI thread), characterized by short (mostly <1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. TI threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in cancer-driver genes. Our study shows the advantage of long-read sequencing in the discovery and characterization of complex somatic rearrangements.

  Study EGAS00001006629

• The miR-185/PAK6 Axis Predicts Therapy Response and Regulates Survival of Drug-Resistant Leukemic Stem Cells in Chronic Myeloid Leukemia

  Overcoming drug resistance and targeting cancer stem cells remain challenges for curative cancer treatment. To investigate the role of miRNAs in regulating drug resistance and leukemic stem cell (LSCs) fate, we performed global transcriptome profiling in treatment-naïve chronic myeloid leukemia (CML) stem/progenitor cells and identified that miR-185 levels anticipate their response to ABL tyrosine kinase inhibitors (TKIs). miR-185 functions as a tumor suppressor; its restored expression impaired survival of drug-resistant cells, sensitized them to TKIs in vitro, and markedly eliminated long-term repopulating LSCs and infiltrating blast cells, conferring a survival advantage in pre-clinical xenotransplantation models. Integrative analysis with mRNA profiles uncovered PAK6 as a crucial target of miR-185 and pharmacological inhibition of PAK6 perturbed the RAS/MAPK pathway and mitochondrial activity, sensitizing therapy-resistant cells to TKIs. Thus, miR-185 presents as a potential predictive biomarker, and dual targeting of miR-185-mediated PAK6 activity and BCR-ABL may provide a valuable strategy for overcoming drug resistance in patients.

  Study EGAS00001004153

• Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection

  Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. We Here we developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

  Study EGAS00001003206

• Functional screening on patient-derived organoids identifies a therapeutic bispecific antibody that triggers EGFR degradation in LGR5+ tumor cells

  Patient-derived organoids (PDOs) have demonstrated predictive value in prospective clinical trials supporting selection of personalized treatments. Because PDOs retain the organization and physiological functions of their source tissue, PDO biobanks could also be an ideal substrate to screen for novel therapeutic interventions. Here we describe a large-scale functional screen of dual targeting bispecific antibodies (bAbs) on a colorectal cancer (CRC) PDO biobank to target their dependency on cancer stem cells. A novel drug discovery pipeline was assembled where therapeutic bAb panels generated against WNT and receptor tyrosine kinases (RTK) targets were functionally evaluated by high content imaging to capture the complexity of PDO responses across a wide range of different CRCs and paired normal colonic mucosa samples. Our strategy resulted in a bAb that specifically triggers EGFR degradation in LGR5+ CSCs and that exhibits unique therapeutic properties such as potent growth inhibition of KRAS mutant CRCs, blockade of metastasis initiation in preclinical models and minimal toxicity towards normal LGR5+ colon stem cells.

  Study EGAS00001004584

• Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones

  The molecular mechanisms underlying lethal castration-resistant prostate cancer remain poorly understood, with intratumoral heterogeneity a likely contributing factor. To examine the temporal aspects of resistance, we analyzed tumor heterogeneity in needle biopsies collected before and after treatment with androgen deprivation therapy. By doing so, we were able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome-wide data. Our data-driven analysis of transcriptomes identified several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Strikingly, certain cell populations present before treatment exhibited gene expression profiles that matched those of resistant tumor cell clusters, present after treatment. We confirmed that these clusters were resistant by the localization of active androgen receptors to the nuclei in cancer cells post-treatment. Our data also demonstrated that most stromal cells adjacent to resistant clusters do not express the androgen receptor, and we identified differentially expressed genes for these cells. Altogether, this study shows the potential to increase the power in predicting resistant tumors.

  Study EGAS00001006113

• Deep whole genome ctDNA chronology of treatment-resistant prostate cancer

  Circulating tumor DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring. We performed deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and demonstrate that ctDNA harbors multiple dominant populations whose evolutionary histories frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally-expanded cancer driver alterations, each individual metastasis contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent androgen receptor (AR) pathway inhibitors, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment-resistance. Finally we leverage nucleosome footprints in ctDNA to infer mRNA abundance in synchronously biopsied metastases, including treatment-induced changes in AR pathway transcriptional activity.

  Dataset EGAD00001008460

• 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

• Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

  No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

  Study EGAS50000000211

• Whole Exome Sequencing of Pancreatic Neuroendocrine Tumors at The Human Genome Sequencing Center, Baylor College of Medicine (HGSC-BCM)

  Pancreatic neuroendocrine tumors (PNETs), often referred to as "islet cell tumors", are neuroendocrine neoplasms that arise from cells of the endocrine and nervous system within the pancreas. These rare tumors which originate from the pancreatic islet are divided into many categories and are often classified by the hormone most strongly secreted. With the collaboration of the Elkins Pancreatic Center, the Human Genome Sequencing Center (HGSC) at Baylor College of Medicine had access to approximately 30 untreated tumor specimens and matched normal blood samples. Since the onset and progression of cancer is driven by extensive mutation of the genome, we are combining enrichment of exonic DNA with next generation sequencing to detect and characterize the somatic mutation profile of patients with pancreatic neuroendocrine cancer. This work was done at the Human Genome Sequencing Center (HGSC) in collaboration with the Elkins Pancreatic Center at Baylor College of Medicine in Houston, TX and was supported by grant number 5U54HG003273 from National Human Genome Research Institute (NHGRI).

  Study phs000871

• International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

  The incidence of invasive breast cancer is rapidly increasing in East Asia, enriching in younger patients and luminal disease. We presented a deep proteogenomic landscape of a prospectively enrolled early-stage cohort in Taiwan to uncover the etiology, age-related subtype and oncogenic vulnerabilities underlying the heterogeneous disease. Multilayer proteogenomic architecture revealed distinct endogenous and environmental carcinogen-associated mutagenesis, linking APOBEC (apolipoprotein-B mRNA editing enzyme, catalytic polypeptide-like) cytidine deaminase and DBAC (dibenz[a,j] acridine) signatures to significantly elevated hormone biosynthesis and chemical carcinogenesis in younger patients, and identifying a novel subset of high mutation burden and immune escape potentially beneficial from combined epigenetic therapy and immunotherapy. A proteomics-informed classification resolves luminal heterogeneity, defines high-risk recurrent luminal disease and nominates biomarkers and actionable druggable pathways. Furthermore, proteogenomics profile distinguished a young luminal population susceptible to exogenous carcinogen and having DNA repair deficiency. This study illuminates the age-related molecular subtypes and oncogenic vulnerabilities, providing a proteogenomics-transformative guide for patient stratification and precision therapeutics beyond clinical staging.

  Study phs003150

• A Multi-Gene Mutation Classification of 468 Colorectal Cancers Reveals a Prognostic Role for APC

  Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinic-pathologic staging for decades. There is a need to molecularly stratify subpopulations of CRC to better predict outcome and assign therapies. Here we report targeted exome sequencing of 1,321 cancer-related genes on 468 tumor specimens, which identified a subset of 17 genes that best classify CRC, with APC (Gene ID: 324) playing a central role in predicting overall survival. APC may assume 0, 1, or 2 truncating mutations, each with a striking differential impact on survival. Tumors lacking any APC mutation carry a worse prognosis than single APC mutation tumors, but tumors with two APC mutations and KRAS (Gene ID: 3845) and TP53 (Gene ID: 7157) mutations confer the poorest survival among all the subgroups examined. Our study demonstrates a substantial prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.

  Study phs001111

• Retinoblastoma Aqueous Humor Liquid Biopsy Repository

  This study involves the use of the aqueous humor (AH, the clear fluid in the front of the eye) as an organ specific liquid biopsy for retinoblastoma. This relatively new liquid biopsy platform was started at CHLA/USC and was developed to overcome the lack of tumor tissue -- due to contraindication to biopsy -- for this cancer. We have demonstrated that the aqueous humor is an enriched source of tumor DNA. Previously tumoral information was only available after the eye was removed for treatment failure. Due to the AH liquid biopsy, we are now able to assay tumor derived molecular information from these eyes at diagnosis and longitudinally during treatment -- as opposed to only eyes that have failed therapy. We have demonstrated that using the platform we can identify the specific mutations in the RB1 gene that initiate tumorigenesis in this cancer as well as the secondary chromosomal alterations the drive further tumor growth. This database will provide sequencing information as well as associated clinical information and globe salvage outcomes.

  Study phs003077

• Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration.

  The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines revealed a unique form of structural variation, termed heterocateny here, characterized by heterogeneous, interrelated, and repetative patterns of concatemerized virus and host DNA segments. Evidence of heterocateny was detected in extrachromosomal and/or intrachromosomal DNA in all cases. Unique breakpoint sequences shared across structurally heterogeneous virus-host concatemers within each cancer facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that unstable virus and virus-host concatemers in ecDNA or integrated form mediate insertion into and excision from chromosomes, capture, rearrangement, and rolling-circle amplification of host DNA, and chromosomal rearrangements. The data indicate that heterocatena is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intra-tumoral heterogeneity and clonal evolution.

  Study EGAS00001006652

• Primary prostate Hi-C

  Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. Despite large-scale tumour sequencing efforts, the impact of mutations on the genetic architecture in cancer remains ill-defined due to limited integration of genomics data across dimensions. We addressed this limitation by assessing the impact of structural variants on the chromatin states and the three-dimensional organization across benign and malignant primary prostate genomes. We find high concordance in the three-dimensional genome organization between malignant and benign prostate tissues, arguing for constraints to the three-dimensional genome of prostate tumours. Moreover, we identify structural variants as effectors of changes to focal chromatin interactions, guiding cis-regulatory element hijacking that imposes opposing expression changes on genes found at antipodes of a rearrangement. This leads to the repression of tumour suppressor gene expression and up-regulation of oncogenes, such as at the TMPRSS2-ERG and PMEPA1-ZNF156 loci. Collectively, our results argue that cis-regulatory element hijacking by structural variants overshadows large-scale topological changes to alter gene regulation and promote oncogenesis.

  Study EGAS00001005014

• Rapid brain tumor classification from sparse epigenomic data

  Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.

  Study EGAS50000000559

• Melanoma_C32_ENU_resistance_to_Combination_Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Study EGAS00001001614

• Melanoma_C32_ENU_Resistance_to_Single_Agent_Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Study EGAS00001001697

• BIG MS Pilot

  Testing logistics and infrastructure of molecular screening program. Core biopsies taken from invasive recurrent or metastatic breast cancer to evaluate and identify molecular traits rendering them suitable for clinical trials

  Dataset EGAD00001000870

• Validation for human early embryonic substitutions (2015_09_03)

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients. This dataset contains all the data available for this study on 2015-09-03.

  Dataset EGAD00001001600

• Whole exome sequencing of Finnish hereditary breast cancer families

  Dataset contains Whole Exome Sequencing(WES) data from 37 individuals as aligned bam-files. The reads have been aligned using bowtie2 to human genome hg19 build.

  Dataset EGAD00001002133

• Locally advanced rectal cancer samples

  Fastq files from exome sequencing of paired normal/tumor (pre and post-nCRT) samples from 7 patients with rectal tumors. All samples were sequenced on a 5500xl SOLiD sequencing platform (Thermo Fisher Scientific).

  Dataset EGAD00001004378

• Molecular Profiles of BRCA1-Associated Ovarian Cancer Treated by Platinum-Based Therapy

  Whole-exome sequencing data from Illumina NextSeq 500. It consists of 88 paired-end FASTQ files from 44 primary, residual, relapsed tumors and normal samples from the blood.

  Dataset EGAD00001005470

• Bulk RNAseq fastq files

  RNAseq FASTq files from 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert).

  Dataset EGAD00001006975

• Genomic determination for Homologous Recombination Deficiency (HRD) by shallow Whole Genome Sequencing (sWGS)

  Homologous recombination deficiency (HRD) score in a large cohort of 55 triple-negative breast cancer PDX

  Dataset EGAD00001008839

• Dataset for synovial_sarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 6 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008899

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0172_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0172_001 for Triple negative breast cancer sample SA609X6XB03447

  Dataset EGAD00001011217

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0163_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0163_002 for Triple negative breast cancer sample SA609X7XB03510

  Dataset EGAD00001011218

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0063_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0063_000 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011209

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0150_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0150_001 for Triple negative breast cancer sample SA609X5XB03230

  Dataset EGAD00001011212

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_006

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_006 for Triple negative breast cancer sample SA535X6XB03099

  Dataset EGAD00001011223

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_004 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011228

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0182_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0182_002 for Triple negative breast cancer sample SA535X8XB03431

  Dataset EGAD00001011230

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0206_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0206_001 for Triple negative breast cancer sample SA535X10XB03693

  Dataset EGAD00001011236

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0142_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0142_004 for Triple negative breast cancer sample SA1035X6XB03209

  Dataset EGAD00001011243

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0145_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0145_001 for Triple negative breast cancer patient-derived xenograft SA1035X7XB03338

  Dataset EGAD00001011244

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0145_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0145_002 for Triple negative breast cancer patient-derived xenograft SA1035X7XB03340

  Dataset EGAD00001011245

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_002 for Triple negative breast cancer sample SA1035X7XB03502

  Dataset EGAD00001011246

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_001 for Triple negative breast cancer sample SA1035X8XB03420

  Dataset EGAD00001011248

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0164_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0164_002 for Triple negative breast cancer sample SA530X3XB03295

  Dataset EGAD00001011250

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0019_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0019_001 for Triple negative breast cancer patient-derived xenograft SA604X7XB02089

  Dataset EGAD00001011253

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0184_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0184_001 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011227

• 10x Single Cell Gene Expression Library TENX063

  10x Single Cell Gene Expression library TENX063 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011268

• 10x Single Cell Gene Expression Library TENX068

  10x Single Cell Gene Expression library TENX068 for Triple negative breast cancer patient-derived xenograft SA609X4XB03080

  Dataset EGAD00001011210

• 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

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0152_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0152_002 for Triple negative breast cancer sample SA609X6XB03404

  Dataset EGAD00001011216

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0172_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0172_002 for Triple negative breast cancer sample SA609X7XB03554

  Dataset EGAD00001011220

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0142_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0142_002 for Triple negative breast cancer sample SA1035X4XB02879

  Dataset EGAD00001011238

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0071_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0071_000 for Triple negative breast cancer sample SA1035X5XB03015

  Dataset EGAD00001011239

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0076_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0076_000 for Triple negative breast cancer sample SA1035X5XB03021

  Dataset EGAD00001011240

• WES melanoma biopsies (UV1-hTERT-mm)

  The dataset contains phenotypes of 14 melanoma biopsies sequenced in connection with the study UV1-hTERT-mm, where the thereapeutic cancer vaccine UV1 is combined with ipilimumab in treatment of melanoma patients.

  Dataset EGAD00001007648

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8b)

  Whole genome sequencing data of 19 high-grade serous carcinoma (HGSC) patients (48 samples) sequenced with MGISEQ-2000

  Dataset EGAD50000000177

• Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) tumor patient

  Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015291

• The University of Hong Kong Gastric Cancer XClone Study Single Cell CNV Data

  Single cell encapsulation and DNA libraries were prepared by Chromium™ Single Cell DNA Reagent Kits and Chromium™ Single Cell C and D Chip Kits.

  Dataset EGAD00001015383

• TGS___Comprehensive_Molecular_Characterization_of_Colorectal_Cancer_Metastases__MOSAIC_

  Systematic next generation sequencing efforts are beginning to define the genomic landscape across a range of primary tumours, but we know very little of the mutational evolution that contributes to disease progression.We therefore propose to obtain a comprehensive description of genomic, transcriptomic and epigenomic changes in a cohort of matched primary and metastatic colorectal cancers, and additionally to explore the extent to which those mutations identified as recurrent in the metastatic setting are able to subvert normal biological processes using both genetically engineered mouse models and established cancer cell lines. This study will enable us to define to what extent primary tumour profiling can capture the biological processes operative in matched metastases as well as the significance of intratumoural heterogeneity.

  Study EGAS00001000958

• Integrative analysis of small cell lung cancer

  Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype. We conducted integrated analysis of genome sequencing, transcriptome, and copy number analysis and found an extremely high mutation rate of 7.4±1 protein-changing mutations per million basepairs. Evidence for inactivation of TP53 and RB1 was found in all sequenced cases. Furthermore, we identified recurrent mutations in CREBBP, EP300, and MLL, observed mutations in PTEN, in SLIT2, and EPHA7, as well as focal amplifications of the FGFR1 locus. As a major feature of SCLC we found mutation in histone modifying genes, observed genome alterations that are therapeutically tractable, and provide a framework for identifying biologically relevant genes in the context of a high mutation rate. Peifer et al., 2012, Nature Genetics.

  Study EGAS00001000299

• Clonal dominance defines metastatic dissemination in pancreatic cancer

  Using patient-derived cells from a pancreatic ductal adenocarcinoma, we created orthotopic clonal replica tumors to trace in an unbiased fashion clonal lineage dynamics of unperturbed tumor expansion and dissemination over time. The model revealed the complex multifaced nature of tumor clonal expansion and uncovered brisk changes in fitness that lead to a continuous reshuffling of tumor clonal architecture and alternating clonal dominance as a distinct feature of cancer growth. Paired analysis of clonal lineages in primary and secondary sites revealed fitness in the primary tumor as a major contributor to dissemination, although other clonal intrinsic and extrinsic factors may contribute to metastatic process. Molecular characterization of lineages with differential metastatic potential identified actionable strategy to suppress dissemination at the subclonal level.

  Study EGAS00001006358