7790 results for "canc*"

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• Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification (H021)

  Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates.

  Study EGAS00001006706

• Non-muscle Invasive Bladder Cancer Molecular Subtypes Predict Differential Response to Intravesical Bacillus Calmette-Guérin

  The recommended treatment for patients with high-risk non-muscle invasive bladder cancer (HR-NMIBC) is tumor resection followed by adjuvant Bacillus Calmette-Guérin (BCG) bladder instillations. However, only 50% of patients benefit from this therapy. In case of progression to advanced disease, patients must undergo a radical cystectomy with significant morbidity and have a poor clinical outcome. Identifying tumors least likely to respond to BCG can translate into alternative treatments, such as early radical cystectomy or novel targeted or immunotherapies. Here we present molecular profiling of 132 BCG-naive, HR-NMIBC patients, and 44 post-BCG recurrences (34 matched), which uncovered three distinct BCG Response Subtypes (BRS1-3). Patients with BRS3 tumors have reduced recurrence and progression-free survival compared to BRS1-2. BRS3 tumors expressed high EMT-basal markers and had an immunosuppresive profile, which was confirmed with spatial proteomics. Tumors which recurred post-BCG were enriched for BRS3. BRS stratification was validated in a second cohort of 151 BCG-naive HR-NMIBC patients and the molecular subtypes outperformed guideline recommended risk stratification based on clinicopathological variables. For clinical application, we validated that a commercially approved assay was able to accurately predict BRS3 tumors (AUROC 0.86). Our findings provide a potential clinical tool for improved identification of HR-NMIBC patients at the highest risk of progression, which can be used to select patients for early radical cystectomy or novel subtype-directed therapies.

  Study EGAS00001006879

• ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA

  Background Liquid biopsies, and the dynamic tracking of somatic mutations within circulating tumour DNA (ctDNA) can provide insight into the dynamics of cancer evolution and the intra-tumour heterogeneity that fuels treatment resistance. However, identifying and tracking dynamic changes in somatic copy-number alterations (SCNAs), which have been associated with poor outcome and metastasis, using ctDNA is challenging. Pancreatic adenocarcinoma is a disease which has been considered to harbour early punctuated events in its evolution, leading to an early fitness peak, with minimal further subclonal evolution. Methods To interrogate the role of SCNAs in pancreatic adenocarcinoma cancer evolution, we applied whole-exome sequencing of 55 longitudinal cell-free DNA (cfDNA) samples taken from 24 patients (including 8 from whom a patient-derived xenograft (PDX) was derived) with metastatic disease prospectively recruited into a clinical trial. We developed a method, Aneuploidy in Circulating Tumour DNA (ACT-Discover), that leverages haplotype phasing of paired tumour biopsies or PDXs to identify SCNAs in cfDNA with greater sensitivity. Results SCNAs were observed within 28 of 47 evaluable cfDNA samples. Of these events, 30% could only be identified by harnessing the haplotype-aware approach leveraged in ACT-Discover. The exceptional purity of PDX tumours enabled near-complete phasing of genomic regions in allelic imbalance, highlighting an important auxiliary function of PDXs. Finally, although the classical model of pancreatic cancer evolution emphasises the importance of early, homogenous somatic events as a key requirement for cancer development, ACT-Discover identified substantial heterogeneity of SCNAs, including parallel focal and arm-level events, affecting different parental alleles within individual tumours. Indeed, ongoing acquisition of SCNAs was identified within tumours throughout the disease course, including within an untreated metastatic tumour. Conclusions This work demonstrates the power of haplotype phasing to study genomic variation in cfDNA samples and reveals undiscovered intra-tumour heterogeneity with important scientific and clinical implications. Implementation of ACT-Discover could lead to important insights from existing cohorts, or underpin future prospective studies seeking to characterise the landscape of tumour evolution through liquid biopsy.

  Study EGAS00001007077

• Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment. From April 2017 to April 2021, 302 samples of 253 patients were included. Comprehensive molecular profiling utilizing lcWGS, WES, RNAseq, Affymetrix, and/or 850k methylation profiling was performed for 226 samples. Germline pathogenic variants were identified in 16% of patients. At least one somatic alteration was detected in 204 (90.3%), and 185 (81.9%) were considered druggable, with priority levels very high (6.1%), high (21.3%), moderate (26.0%), intermediate (36.1%), and borderline (10.5%). Diagnosis was revised or refined in 8 patients (3.5%). Spatial and temporal heterogeneity was observed in paired samples of 15 patients, indicating the value of sequential analysis. Of 137 patients with follow-up beyond 12 months, 21 molecularly matched treatments were applied in 19 patients (13.9%) with modest response. Most relevant barriers to not applying targeted therapies included poor performance status, as well as limited access to drugs within clinical trial. iTHER demonstrates feasibility of comprehensive molecular profiling across all ages, tumor types and stages in pediatric cancers, informing of diagnostic, prognostic, and targetable alterations as well as reportable germline variants within a clinically relevant timeframe. Therefore, WES and RNAseq is implemented into standard clinical care at the Princess Máxima Center for all children. Improved access to targeted treatments within biology-driven combination trials is required to eventually improve survival.

  Study EGAS00001007099

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

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

  Dataset EGAD00001016184

• Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

  Background The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug associated transcriptional cell states. Results We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure. Conclusions Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration and re-treatment strategies.

  Study EGAS00001007242

• Clinical outcomes and immune correlates of response to nivolumab plus chemoradiotherapy in women with locally-advanced cervical cancer – NiCOL study

  Concurrent chemoradiotherapy (CRT) with blockade of the PD-1 pathway may enhance immune-mediated tumor control through increased phagocytosis, cell death, and antigen presentation. The NiCOL phase 1 trial was designed to determine safety, tolerance, and immune correlates of response to the PD-1 blocking antibody, nivolumab, with and following concurrent CRT in 16 women with locally advanced cervical cancer (LACC). Three patients experienced grade 3 dose-limiting toxicities. The overall response rate was 93.8% [95%CI: 69.8%-99.8%] with a 2-year PFS of 75% [95% CI: 56.5%-99.5%]. Compared to patients with progressive disease (PD), progression-free (PF) subjects showed a brisker stromal immune infiltrate, higher proximity of tumor-infiltrating CD3+ T cells to PD-L1+ tumor cells and of Foxp3+ T cells to proliferating CD11c+ myeloid cells. PF had higher baseline levels of PD-1 on EMRA CD4+ T cells and ICOS-L on tumor-associated macrophages (TAMs) vs PD, which instead displayed enhanced PD-L1 expression on TAMs and higher, circulating frequencies of proliferating Tregs at baseline. Concomitant nivolumab plus definitive CRT is safe and associated with encouraging PFS rates. Further validation in the subset of LACC displaying pre-existing, adaptive immune activation is warranted.

  Study EGAS00001007297

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Study EGAS00001007327

• Genome-wide cell-free DNA biological patterns in patients with cancer

  The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

  Study EGAS00001007400

• SMARCB1 loss activates patient-specific distal oncogenic enhancers in malignant rhabdoid tumors

  Malignant rhabdoid tumor (MRT) is a highly malignant and often lethal childhood cancer. MRTs are genetically defined by bi-allelic inactivating mutations in SMARCB1, a member of the BRG1/BRM-associated factors (BAF) chromatin remodeling complex. Mutations in BAF complex members are common in human cancer, yet their contribution to tumorigenesis remains in many cases poorly understood. Here, we studied derailed regulatory landscapes as a consequence of SMARCB1 loss in the context of MRT. Our multi-omics approach on patient-derived MRT organoids revealed a dramatic reshaping of the regulatory landscape upon SMARCB1 reconstitution. Chromosome conformation capture experiments subsequently revealed patient-specific looping of distal enhancer regions with the promoter of the MYC oncogene. This intertumoral heterogeneity in MYC enhancer utilization is also present in patient MRT tissues as shown by combined single-cell RNA-seq and ATAC-seq. We show that loss of SMARCB1 drives patient-specific epigenetic reprogramming underlying MRT tumorigenesis.

  Study EGAS00001007590

• Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Malignant rhabdoid tumor (MRT) is one of the most aggressive childhood cancers for which no effective treatment options are available. Reprogramming of cellular metabolism is an important hallmark of cancer, with various metabolism-based drugs being approved cancer treatment. In this study, we use patient derived tumor organoids (tumoroids) to map the metabolic landscape of several pediatric cancers. Combining gene expression analyses and metabolite profiling using mass spectrometry, we find nucleotide biosynthesis to be a particular vulnerability of MRT. Treatment of MRT tumoroids with de novo nucleotide synthesis inhibitors lowers nucleotide levels in MRT tumoroids and induces apoptosis. Lastly, we demonstrate invivo efficacy of methotrexate in an MRT PDX mouse model. Our study revealsnucleotide biosynthesis as an MRT-specific metabolic vulnerability, which can ultimately lead to better treatment options for children suffering from this lethal pediatric malignancy.

  Study EGAS00001007877

• Genome-wide association study identifies common variants associated with breast cancer in South African Black women

  Genome-wide association studies (GWAS) have characterized the contribution of common variants to the development of breast cancer (BC) in populations of European descent, however no GWAS have been reported in resident African populations. This GWAS included 2,485 resident African BC cases and 1,101 population matched controls. Two risk loci were identified, one on chromosome 15, located between UNC13C and RAB27A (rs7181788, p = 1.01x10-08) and a second in an intron of USP22 on chromosome 17 (rs899342, p = 4.62x10-08). RAB27A is a member of the RAS oncogene family associated with invasive growth and metastasis, and UNC13C is involved in tumor progression. The rs899342 SNP is an eQTL for expression of USP22 in a wide range of tissues. Several genome-wide significant signals were detected in a hormone receptor subtype analysis. Comparison of a meta-analysis of other African ancestry BC GWAS datasets predominantly of West African ancestry with our South African data showed limited evidence of shared risk loci, suggesting potential heterogeneity in genetic risk factors for breast cancer in different African populations. A European ancestry derived polygenic risk model for BC was applied to our data, explaining only 0.79% of variance, with an area under the curve of 0.56. This study identified genetic risk factors for BC in a resident African population, but larger studies in this and other African populations are needed to further define the contribution of common variants to BC risk.

  Study EGAS00001008032

• Cancer of Low survival and UnMet Need – Pathologist Initiated

  Despite significant advances in diagnostic cancer histopathology, a subset of tumors remain unable to be classified using WHO criteria. The resulting diagnostic uncertainty can result in inappropriate clinical management and negative patient outcomes. We investigated whether combining histopathology with whole genome and transcriptome sequencing (WGTS) could improve the classification of tumors that posed diagnostic dilemmas despite extensive histopathology and standard molecular work-up at a quaternary oncology center. We successfully sequenced 45 tumors from an initial set of 54 unclassified tumors (83% success rate). A confident diagnosis was made for 38/45 tumors (84%). Additionally, potential treatment targets were identified in 21/45 tumors (47%). Theoretical comparison with alternative assays demonstrated that WGTS was uniquely capable of detecting critical diagnostic findings in 15/38 tumors (39%). This work supports augmenting histopathology and standard molecular pathology with WGTS in the classification of difficult-to-diagnose tumors.

  Study EGAS00001008112

• Sequencing data from MethylScan assay on plasma

  Machine learning models in biomedical research are often hindered by demographic imbalances in clinical datasets, leading to biased predictions that disadvantage minority populations. Existing bias correction methods face limitations in handling the heterogeneity of biomedical data and the complexity of demographic influences. Here, we present DeBias, a computational framework for mitigating demographic biases in high-dimensional biomedical datasets. DeBias eliminates bias-associated subspaces within the entire feature space using control samples and enables global bias correction across all features, effectively preserving disease-specific signals while minimizing demographic distortions. To demonstrate its effectiveness, we applied DeBias to cfDNA methylation data for cancer detection. It achieved a >6-fold reduction in the number of features containing biases and outperformed existing methods in improving the cancer detection performance for minority populations. Our method represented a promising step toward developing machine learning models that are more accurate, reliable, and equitable for minority populations.

  Study EGAS00001008127

• Single-cell and spatial transcriptomic profiling of hormone-naïve localised prostate cancer

  Localised prostate cancers (PCa) are heterogeneous and multifocal, with diverse outcomes. Current prognostic methods are epithelium-centric, overlooking the complex cellular landscape within the tumour microenvironment (TME), which remains incompletely characterised. We performed a comprehensive analysis of cancerous and adjacent-benign cores from 24 patients with hormone therapy-naïve localised PCa using single-cell RNA-sequencing. By integrating copy number variation and transcriptional signatures, we classified epithelial cells across a malignant spectrum, revealing widespread molecular perturbation. We found an expansion of Club cell phenotypes, suggestive of Luminal dedifferentiation. We also performed a detailed annotation of stromal phenotypes, focusing on fibroblasts, and identified a novel peri-neural fibroblast population. Spatial transcriptomics elucidated the precise anatomical distribution of CAFs within the PCa TME. This study provides a valuable foundation for advancing our understanding of PCa pathobiology and developing a comprehensive cellular model of the disease.

  Study EGAS00001008332

• 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 EGAD00001016385

• 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 EGAD00001016386

• Genome and transcriptome sequence data from a metastatic sigmoid colon cancer patient

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

  Dataset EGAD00001016390

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

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

  Dataset EGAD00001016391

• Genome and transcriptome sequence data from a peritoneal mesothelioma, epithelioid type patient

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

  Dataset EGAD00001016392

• Genome and transcriptome sequence data from a metastatic kras mutant colon cancer patient

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

  Dataset EGAD00001016393

• Genome and transcriptome sequence data from a thoracic/ mediastinal paraganglioma patient

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

  Dataset EGAD00001016394

• Genome and transcriptome sequence data from a metastatic osteosarcoma (left radius primary, lungmetastasis patient

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

  Dataset EGAD00001016395

• Genome and transcriptome sequence data from a recurrent uterine tumor resembling ovarian sex cord tumor (utrosct) patient

  Genome and transcriptome sequence data from a recurrent uterine tumor resembling ovarian sex cord tumor (utrosct) patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016396

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

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

  Dataset EGAD00001016397

• Genome and transcriptome sequence data from a metastatic sigmoid colon cancer patient

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

  Dataset EGAD00001016398

• Genome and transcriptome sequence data from a triple negative breast cancer (ductal) patient

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

  Dataset EGAD00001016399

• Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the right parotid gland to lymph nodes, lungs and bone patient

  Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the right parotid gland to lymph nodes, lungs and bone patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016400

• Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient

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

  Dataset EGAD00001016401

• Genome and transcriptome sequence data from a braf wild-type malignant melanoma with cns metastasis patient

  Genome and transcriptome sequence data from a braf wild-type malignant melanoma with cns metastasis patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016402

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

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

  Dataset EGAD00001016403

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

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

  Dataset EGAD00001016404

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

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

  Dataset EGAD00001016405

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

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

  Dataset EGAD00001016406

• Genome and transcriptome sequence data from a metastatic distal esophageal adenocarcinoma with nodal and liver metastasis patient

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

  Dataset EGAD00001016407

• Genome and transcriptome sequence data from a metastatic breast ca to liver, er+, her2 low (ductal) patient

  Genome and transcriptome sequence data from a metastatic breast ca to liver, er+, her2 low (ductal) patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016408

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

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

  Dataset EGAD00001016409

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

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

  Dataset EGAD00001016410

• Genome and transcriptome sequence data from a metastatic recurrent rectal cancer patient

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

  Dataset EGAD00001016411

• Dataset for Genomic and fragmentomic landscapes of cell-free DNA in aging and disease : MICA Morbidity Cohort

  This dataset contains 570 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000 with 1-2x coverage. The samples analyzed include plasma samples from non-cancer patients from MICA cohort.

  Dataset EGAD00001016584