10164 results for "cancer rna-seq"

in 44.09 milliseconds.

• WGS data for 67 patient cohort

  This dataset includes WGS data of samples from our paper titled "Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: The PLANET study." (National Science Review, nwab192. https://doi.org/10.1093/nsr/nwab192)

  Dataset EGAD00001008647

• MPM patients

  - RNA-sequencing data: 5 normal pleurae and 40 malignant pleural mesotheliomas - Targeted DNA-sequencing of the 165 genes included in the “Solid and Haematological tumors” panel (BRIGHTCore, Brussels, Belgium): 6 MPM samples. 2 FASTQ files for each sample (paired).

  Dataset EGAD00001008740

• RNAseq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing. Files were processed and quantified with kallisto v0.42.5 using the human reference transcriptome (Gencode Release 28). Countdata was rlog-transformed.

  Dataset EGAD00001009649

• TRACERx NSCLC - Multiregion RNA sequencing data from the 421 cohort

  RNAseq data from the TRACERx 421 cohort

  Dataset EGAD00001009862

• SMARTer bulk RNA sequencing for highly purified CD271+ BMSCs from NBM and AML

  bulk RNAseq was conducted on highly purified CD45 - CD71 - CD235a - CD31 - CD271 + BMSCs isolated from a cohort of newly diagnosed 62 AML patients, uniformly treated within an intensive chemotherapy clinical trial and selected to represent the mutational landscape of AML

  Dataset EGAD00001011056

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (scRNA)

  Data supporting: “Single-cell RNA sequencing unifies developmental programs of Esophageal and Gastric Intestinal Metaplasia.” Nowicki-Osuch, Zhuang et al. scRNAseq (FASTQ files) 59 samples

  Dataset EGAD00001010074

• nanostring_gene_expression

  Two to four sections of 10 µm thickness each (depending on sample size) from the respective formalin-fixed paraffin-embedded (FFPE) tissue sample were used for RNA isolation on 46 resected tumors as well as 17 paired biopsies. Digital gene expression analysis was performed on the NanoString nCounter platform, utilizing the NanoString MAX/FLEX system, with the PanCancer Immune Profiling panel as well as the PanCancer Pathway panel provided by NanoString.

  Dataset EGAD00010002654

• Single-sell RNA sequencing counts from 7 acute myeloid leukemia patients and 3 healthy donors

  This dataset contains count data (from 10X CellRanger) and metadata from 7 acute myeloid leukemia subjects treated with chemotherapy, as well as data from 3 healthy donors. Additionally, the dataset includes VDJ data for all subjects except for 31_base and the 3 healthy donors (TCRseq not performed).

  Dataset EGAD50000000525

• CRC GWAS on the Spanish population

  Genome-wide association study performed on the EPICOLON2 cohort, comprising colorectal cancer cases and matched controls of Spanish origin.

  Study EGAS00001003633

• Testing the feasibility of genome scale sequencing in routinely collected FFPE cancer specimens versus matched fresh frozen samples

  Testing the feasibility of genome scale sequencing in routinely collected FFPE cancer specimens versus matched fresh frozen samples

  Dataset EGAD00001000255

• Deep Sequencing of somatic cancer mutations

  We enriched a panel of cancer associated genes using the Custom Sure Select Target Enrichment Kit. Identified mutations were validated with deep sequencing in order to assess mutated allele frequencies more accurately.

  Dataset EGAD00001001313

• Whole genome sequencing data of 15 French Caucasian and 10 African-Caribbean men with prostate Cancer.

  Whole genome sequencing data of 15 French Caucasian and 10 African-Caribbean men with prostate Cancer.

  Dataset EGAD00001003115

• Genomic Profiling of Advanced Pancreatic Cancer to inform therapy - WGS mapped reads

  Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer - Early Results from the COMPASS Trial - WGS mapped reads

  Dataset EGAD00001003585

• Breast cancer PDTX sequencing data from Bruna et al, Cell 2016

  Breast cancer PDTX sequencing data from Bruna et al, Cell 2016 - Exome Sequencing - Shallow Whole Genome Sequencing - RRBS Methylation Sequencing

  Dataset EGAD00001002685

• Whole exome sequencing of breast cancer samples pre- and post-neoadjuvant chemotherapy (NAC)

  Fastq files resulting from whole exome sequencing of trios of samples from 6 breast cancer patients: normal breast, pre-NAC biopsy and post-NAC surgical resection.

  Dataset EGAD00001004984

• Whole genome sequencing of cfDNA

  random whole-genome shotgun sequencing of cfDNA in control samples (NPH*) and late-stage cancer samples. First letter denotes primary cancer tissue (C: Colon, B: Breast, P: Prostate)

  Dataset EGAD00001005343

• MDA whole exome sequencing data for bladder cancer

  46 BAM files from 23 urothelial bladder cancer patients on an immunotherapy clinical trial. PBMC normal samples and solid tumor samples are paired. Alignment was done by BWA with reference genome hg19.

  Dataset EGAD00001005712

• Colorectal-Cancer-Tumor-Spheres-H012-Microarray_Expression

  Gene expression of 12 colon cancer TSCs (sensitive or resistant) after 12h treatment with 3µM NCT02 or DMSO (control) was analyzed using Illumina microarrays (HumanHT-12 v4 BeadChip).

  Dataset EGAD00010001936

• Whole-exome sequencing data from a head and neck cancer patient

  This dataset contains paired-end whole-exome sequencing data (2x50 bp) from the normal sample, three synchronous primary tumors and the recurrence of a head and neck cancer patient.

  Dataset EGAD00001006653

• The genomic VCF data of the Integrative proteogenomic characterization of early esophageal cancer project

  The genomic VCF data of the Integrative proteogenomic characterization of early esophageal cancer project ,this dataset contains 90 VCF files.

  Dataset EGAD00001008672

• 18 plasma samples and their paired 18 urinary cfDNA samples without cancer

  18 plasma samples and their paired 18 urinary cfDNA samples without cancer

  Dataset EGAD00001009839

• Human primary and metastatic colorectal cancer (CRC) samples

  Bank of human both primary and metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001009712

• patient-derived head and neck cancer organoids

  patient-derived head and neck cancer organoids

  Dataset EGAD00001010134

• Genotype data for African Esophageal squamous cell cancer cases and controls from South Africa

  This dataset contains the cleaned genotype data from 2173 African eosphageal squamous cell cancer cases and population controls. The genotype data was generated using the H3Africa Illumina Custom microarray.

  Dataset EGAD00010002575

• Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Dataset EGAD00001000002

• Her2 BC WGS dataset

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

  Dataset EGAD00001001334

• Gastric Cancer sWGS

  Shallow Whole Genome Sequencing of two (2) Gastric Cancer samples from the same subject. sWGS was used for Copy number aberration analysis to assess clonal relationship of the collision of two independent EBV+ and EBV- tumors.

  Dataset EGAD50000000987

• Somatic_mutation_and_clonal_evolution_in_premalignant_lung_disease___WGS

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients.

  Study EGAS00001002747

• ENU_CCK_81_cetuximab_pilot_project

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC.

  Study EGAS00001001743

• ENU_NCI_H508_Cetuximab_SecondRound

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Study EGAS00001001745

• ENU_NCI_H508_cetuximab_fixed_concentration_project

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Study EGAS00001001744

• A Study to Evaluate Denosumab in Young Patients With Primary Breast Cancer (D-Beyond)

  This is a prospective, single arm phase IIa trial in which patients with early breast cancer will receive pre-operatively two doses of denosumab 120mg subcutaneously one week apart (maximum 12 days) followed by surgery. Tumor, normal breast tissue and blood samples will be collected at baseline and at surgery. Post-operative treatment will be at the discretion of the investigator.Primary objective: to determine if a short course of RANKL inhibition with denosumab can induce a decrease in tumor proliferation rates as determined by Ki67 immunohistochemistry (IHC) in newly diagnosed, early stage breast cancer in pre-menopausal women.

  Study EGAS00001003252

• Comprehensive Analysis of the Immunogenomics of Triple Negative Breast Cancer Brain Metastases from LCCC1419

  Triple negative breast cancer (TNBC) is an aggressive subset of breast cancer that lacks expression of the estrogen and progesterone receptors (ER and PR) and HER2. Nearly 50% of patients with advanced TNBC will develop brain metastases (BrM), commonly with progressive extracranial disease. Immunotherapy has shown promise in the treatment of advanced TNBC; however, the immunogenomics of BrM remains largely unknown. Thus, we conducted a comprehensive analysis of TNBC BrM and matched primary tumors to characterize the genomic and immune landscape of TNBC BrM to foster the development of immunotherapy strategies in this aggressive and clinically unmet disease.  

  Study phs002457

• Extrachromosomal DNA Amplification Contributes to Small Cell Lung Cancer Heterogeneity and is Associated with Worse Outcomes

  Small-cell lung cancer (SCLC) is a very aggressive neuroendocrine lung cancer often associated with oncogenic MYC amplifications, which are known to drive SCLC heterogeneity marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states. The genetic mechanisms of MYC amplification and phenotypic plasticity between cell states is not known. Using data from cell-lines and a few patient-derived samples along with integrated whole-genome sequencing, long-range optical mapping, single-cell DNA sequencing, and fluorescence in situ hybridization, we have attempted to successfully characterize extrachromosomal DNA (ecDNA) as the primary source of MYC amplifications and driver fusions in SCLC.

  Study phs003190

• Advancing Precision Oncology in a Humanized, Fully Autologous Mouse Model

  Progress in the early detection and treatment of cancer requires accurate model systems to further evaluate new, promising discoveries. Small animal and, in particular, mouse model systems are attractive to researchers for numerous reasons, including their ease of use and well-described platforms. The ability to grow human tumors in immune-deficient mice (so-called patient-derived xenografts, or PDXs) allows researchers to work directly with human cancer tissue in a controlled setting. However, PDX models are limited by their lack of an intact immune system. Immunotherapy has revolutionized clinical oncology, but lacks pre-clinical models of the human immune system and human cancer to investigate new modalities and limitations/toxicities of treatment regimens. The broad objective of this study is to validate an in vivo model to evaluate human tumors in the context of a complete and intact human immune system in a completely personalized and autologous fashion to study cancer immunotherapy. Herein, we will: (1) validate the ability of our humanized system to serve as a model for cancer immunotherapy treatment response and toxicity in patients with melanoma, including immunotherapy checkpoint blockade and vaccine strategies, and (2) extend our current work in melanoma by validating the ability to establish humanized mice and evaluate tumor growth and leukocyte development in autologous human pancreatic and colorectal tumors established in humanized mice. In each of these areas, we will leverage our multi-institutional team's individual expertise along with our institutional infrastructure to maximize the success of the experimental aims. The results from this project will be widely available to the general research community for future, hypothesis-driven research. Taken together, our study will meet multiple goals and address several unmet needs in cancer immunotherapy, thus significantly enhancing the applicability of a fully autologous and immunocompetent precision model system for use in translational oncology research.

  Study phs003090

• Detection of mutational patterns in cell free DNA (cfDNA) of colorectal cancer by custom amplicon sequencing

  Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell free (cf) DNA offers a non-invasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatics workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our method to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from 34 patients with advanced colorectal cancer. Our data demonstrates that recurrent and patient-specific mutational patterns can be reliably detected for the majority of patients. Furthermore, we show that the allele frequency of mutations in cfDNA correlates well with disease progression. Finally, we demonstrate that monitoring of cfDNA can outperform the predictive power of currently used tumor markers and reveal mechanisms of resistance to anti-EGFR antibody treatment.

  Study EGAS00001003382

• Drug-perturbation-based stratification of blood cancer

  As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

  Study EGAS00001001746

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178

• Gabriella Miller Kids First (GMKF) Pediatric Research Program in Susceptibility to Ewing Sarcoma Based on Germline Risk and Familial History of Cancer

  Ewing sarcoma (EWS) is a deadly bone cancer that occurs in children and adolescents. Mounting evidence suggests that a genetic predisposition exists for this pediatric cancer, although the specific genetic contribution has yet to be identified. EWS has never been linked to a specific cancer predisposition syndrome, although several case reports have been published that describe siblings and cousins with EWS. Furthermore, neuroectodermal tumors appear to occur more commonly in families with EWS. The two consistent epidemiology findings in EWS include a very strong Caucasian predilection and increased rates of hernia in EWS patients and their family members. Finally, the role of genetic microsatellite repeats in EWS tumorigenesis has been recently described, and these GGAA microsatellites are polymorphic in repeat size and location across the genome. The study goals of this Kids First project include (1) To identify cancer predisposition genes in EWS trios increasing disease risk, (2) To identify genome-wide GGAA microsatellite repeats in EWS trios increasing disease risk, and (3) To identity de novo mutation and structural variant rates in EWS trios reflecting underlying DNA repair defects that increase disease risk. As part of the Kids First Common Fund initiative, this study proposal will further elucidate the genetic contribution to pediatric cancer development. Around 375 of these trios were selected for whole genome sequencing as part of the Gabriella Miller Kids First fund. The EWS trios have been collected as part of the Children's Oncology Group's AEPI10N5 Study ("Genetic Epidemiology of Ewing Sarcoma"), and each trio has associated phenotypic data including a detailed family history. We will interrogate the sequence data using our genomic analysis pipeline at the University of Utah and the Utah Science Technology and Research initiative's (USTAR) Center for Genetic Discovery. We will look for the genetic contribution to EWS and the sequence data with be shared in a repository designated by the Kids First Common Fund. The WGS of these ~375 EWS trios will help us to understand the genetic origins of a deadly childhood cancer and may lead to novel strategies for prevention and treatment.

  Study phs001228

• Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Dataset EGAD00001000284

• Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Dataset EGAD00001000290

• Cancer Cell Line Exome Sequencing

  Genomic characterisation of a large series of cancer cell lines.

  Dataset EGAD00001001039

• WGS on patients 1-4, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of fifteen samples, tumour and whole blood, from the four initial patients.

  Dataset EGAD00001001343

• Reference DNA standards for GCLP pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Dataset EGAD00001002015

• Exome and Transcriptome for pan-cancer gene-drug analysis

  Total of 584 tumor specimens and/or patient-derived cells across 14 cancer types were subjected for whole-exome/targeted-exome and/or whole-transcriptome sequencing.

  Dataset EGAD00001003441

• Sci Trans Med - Mouliere et al, 2018. Non-ovarian cancer samples - STM4

  fastq files for shallow whole genome sequencing data as described in Mouliere et al, 2018. Files are those not included in STM2 i.e. these are largely non-ovarian cancer samples

  Dataset EGAD00001006132

• Whole-genome sequencing of gastric cancer with peritoneal metastasis

  Whole-genome sequencing of 135 tumor samples and 98 normal samples of gastric cancer with peritoneal metastasis

  Dataset EGAD00001006963

• Cell-free DNA TAPS provides multimodal information for early cancer detection

  TAPS data from 21 patients with HCC, 23 patients with PDAC, 30 non-cancer controls, 4 patients with cirrhosis, and 7 patients with pancreatitis.

  Dataset EGAD00001006871

• Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Dataset EGAD00001011123