12312 results for "cancer rna-seq"

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• Expression data from the Neo-CheckRay trial

  ER+/HER2- early breast cancer were treated with neoadjuvant immune-modulating SBRT and anti-CD73. The RNAseq dataset contains fastq files for 234 samples corresponding to 134 patients. There are 208 breast cancer samples, taken at screening (N=136) or week 6 (N=76). In addition, there are 26 lymph node samples taken at screening.

  Dataset EGAD50000002552

• Whole-genome sequencing data of metastatic salivary gland cancer

  This dataset contains whole-genome sequencing data of three patients with metastatic salivary gland cancer who underwent autopsy to harvest tumor biopsies from spatially separated metastatic sites and biopsies from healthy skin as a control. Two patients had the subtype adenoid cystic carcinoma (patients 1 and 4) and one patient had the subtype myoepithelial carcinoma.

  Dataset EGAD50000002056

• lpWGS of solid and liquid samples from female patients with metastatic breast cancer

  low-pass Whole Genome Sequencing (lpWGS) to assess the representativeness of seven body liquids from female patients with metastatic breast cancer. 20 patients. 216 liquid samples, 745 solid samples, 20 matched normal samples. 0.5X coverage. Illumina single read sequencing. Fastq files are provided. lpWGS from Richard et al., Nature Communications, 2025.

  Dataset EGAD50000001851

• Targeted sequencing data on sequential liquid biopsy samples from CSPC patients

  Sequencing data from newly diagnosed high emtastatic burder prostate cancer patients receiving an AR pathway inhibitor (ARPI) or docetaxel. Targeted sequencing data of prostate cancer relevant genes using the PCF-SELECT capture panel. cfDNA from PreADT, baseline, on-treatment (Cycle1 to 6) taken on ARPI or Docetaxel were sequenced as well as patient-matched WBC DNA

  Dataset EGAD50000001960

• cfDNA sWGS BAM — Breast cancer stage II-III (HR+/HER2−)

  Plasma cfDNA sWGS for breast cancer patients (HR+/HER2−, stage II–III), blood drawn pre-operatively (no neoadjuvant), Centre Léon Bérard/MyProbe (France). Libraries: DSP and/or SSP as recorded. Sequencing by IntegraGen (2022–2024); alignment to GRCh38 with BWA-MEM; BAMs sorted/indexed; primary mapped reads only (see analysis metadata for exact filters/MAPQ). Controlled access.

  Dataset EGAD50000001877

• MET amplification in gastric cancer

  WES sequencing of two cases of MET amplified gastric cancer. Six unfixed fresh frozen samples were obtained from the primary tumors (three samples from each) and three samples from corresponding non-neoplastic mucosa. In addition, formalin-fixed and paraffin-embedded (FFPE) samples were obtained from the primary tumors (n=2), lymph node metastases (n=7) and non-neoplastic mucosa (n=2).

  Dataset EGAD50000001099

• Whole genome shotgun sequencing and somatic mutations data in Hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy.

  Study EGAS00001002578

• Dataset for Direct Detection of Early-Stage Cancers using Circulating Tumor DNA

  The dataset for Direct Detection of Early-Stage Cancers using Circulating Tumor DNA includes 602 bam files from next-generation sequencing on the Illumina HiSeq2500 or MiSeq. The samples analyzed include cancer cell lines as well as plasma and tissue specimens from healthy individuals and patients with cancer.

  Dataset EGAD00001003601

• Whole exome profiling of spatial biopsies of high grade serous epithelial ovarian cancer patients

  This data set is comprised of data from seven distinct high grade serous epithelial ovarian cancer (HGS-EOC) partients, from whom multiple biopsies were taken at the time of surgery, from the ovary and from different locations in the peritoneal cavity. This data set contains 28 samples, sequenced with a whole exome sequencing approach.

  Dataset EGAD00001004154

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

  Genomic determination for Homologous Recombination Deficiency (HRD) by shallow Whole Genome Sequencing (sWGS) with shallowHRD (PMID : 32315385) on 55 triple-negative breast cancer Patient Derived-Xenograft (PDX) treated with platinum.

  Study EGAS00001005926

• 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 EGAD00001001338

• Shallow whole genome sequencing on stage 1 epithelial ovarian cancer

  BAM files (aligned against the hg38 genome) from a shallow whole-genome sequencing experiment (median depth 0.5X) on 218 samples from Stage 1 epithelial ovarian cancer biopises. Samples labeled "bis" or "tris" with the same ID are relapses; "left" or "right" samples indicate, in the case of bilateral tumor, from which ovary the sample was taken.

  Dataset EGAD00001006881

• Sequencing of longitudinal glioma pairs

  Clonal evolution drives cancer progression and therapeutic resistance. Recent studies revealed divergent longitudinal trajectories in gliomas, but early molecular traits steering post-treatment cancer evolution remain unclear. We analyzed sequencing data of 544 initial-recurrent adult diffuse glioma pairs to identify genomic and transcriptomic early predictors of tumor evolution in each molecular subtype.

  Dataset EGAD00001009845

• Bulk BCR NGS data from metastatic breast tumours from donors with therapy-resistant lethal metastatic breast cancer.

  Bulk B Cell Receptor high-throughput sequencing data across 27 metastatic breast tumours obtained from 8 donors with therapy-resistant lethal metastatic breast cancer at the time of a warm autopsy. The 35 samples were sequenced on an Illumina MiSeq instrument and their raw FastQ files deposited here.

  Dataset EGAD00001010023

• Genomic data used in "ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA"

  Genomic data used in "ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA"

  Dataset EGAD00001010250

• Illumina TSO500 DNA Dataset for Manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  Illumina TSO500 DNA Dataset for Manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  Dataset EGAD00001015396

• Esophageal Squamous Cell Carcinoma Precursor Study

  Esophageal cancer is the sixth most common cause of cancer death in the world. High-risk areas occur across central Asia and from eastern to southern Africa, and in these populations, nearly all of the cases are esophageal squamous cell carcinoma (ESCC). ESCC has a dismal prognosis, largely because symptoms usually appear late in the course of the disease, when the tumors are incurable. Early detection and treatment of curable precursor lesions and early invasive ESCC in asymptomatic high-risk adults offers the potential for long-term survival and reduced mortality from this disease. Previous studies have shown that routine cytology of non-endoscopically collected esophageal cell samples is not sensitive and specific enough to be clinically useful, so we are now looking for molecular markers of high-grade esophageal squamous dysplasia (HGD), the proven clinically important precursor lesion of ESCC, that can be used to increase the accuracy and utility of this initial screening exam. National Cancer Institute (NCI) and Cancer Institute and Hospital, Chinese Academy of Medical Sciences (CAMS) began collaborative studies of ESCC since the mid-1980s in China. The present proposal is designed to characterize the type and prevalence of DNA mutations in tissue samples of HGD and to establish biologic and questionnaire resources for further study. The proposed study has two components, a field study to obtain questionnaire data and biological samples, and a genomic analysis to perform sequencing of the biological samples and bioinformatics analysis of the sequencing. 

  Study phs002814

• Decoding Human Endogenous Retrovirus Expression in Liver Metastatic Colorectal Cancers: Implications for Diagnosis and Prognosis

  The association between Human Endogenous RetroVirus (HERV) expression and cancer can be considered to both reflect the epigenetic deregulation of cancer and facilitate oncogenesis through its promoter/enhancer action on genes. More than 50% of colorectal cancers develop liver metastases and HERV has never been studied in this setting. We collected 400 RNAseq samples from more than 200 patients with primary and liver metastases from published and unpublished databases. We corroborated our findings with tandem mass spectrometry from primary colorectal cancer and single-cell RNAseq from liver metastatic colorectal cancer (lmCRC). We identified global stability in HERV expression between liver metastases and primary colorectal cancers, suggesting an early oncogenic footprint. Therefore, we proposed a list of seventeen HERV loci for lmCRC characterization with ERV-derived peptides but no expression in normal tissues. Among them, we discovered six prognostic markers after surgical resection of lmCRC. Four of them, HERVH_Xp22.32a, HERVH_20p11.23b, HERVH_13q33.3, HERVH_13q31.3, showed poor prognostic value when expressed (log-rank p-value 0.028, 0.0083, 9e-4, 0.05, respectively). HERVH_Xp22.2c (log-rank p-value 0.032) and HERVH_8q21.3b (only in multivariate models) were associated with better prognosis when expressed. These markers showed a cumulative effect on survival when expressed. Some HERVs were associated with decreased cytotoxic immune cells and most of them correlated with cell cycle pathways. Our findings provide new insights into lmCRC classification and suggest novel prognostic biomarkers and potential therapeutic targets.

  Study EGAS50000000307

• Cistrome-partitioning reveals convergence of somatic mutations and risk-variants on master transcription regulators in primary prostate tumors

  Thousands of noncoding somatic Single Nucleotide Variants (SNVs) of unknown function are reported in tumors. Partitioning the genome according to cistromes, reveals the enrichment of somatic SNVs in prostate tumors as opposed to adjacent normal tissue cistromes of master transcription regulators, including AR, FOXA1 and HOXB13. This parallels enrichment of prostate cancer genetic predispositions over these transcription regulators’ tumor cistromes, exemplified at the 8q24 locus harboring both risk-variants and somatic SNVs in cis-regulatory elements, upregulating MYC expression and altering the binding of transcription regulators to DNA. However, Massively-Parallel Reporter Assays reveal that few SNVs can alter the transactivation potential of individual CREs. Instead, SNVs accumulate, similarly to inherited riskvariants, in cistromes of master transcription regulators required for prostate cancer development. Difficulties in inferring the biological significance of noncoding mutations have limited their inclusion in precision genomics medicine pipelines. Most attempts to delineate a role for noncoding mutations relied on detecting evidence for positive selection within individual CREs, such as reported for the TERT gene promoter. By considering the enrichment of noncoding mutations in cistromes as opposed to individual CREs, we reveal their specificity towards master transcription regulators that promote prostate cancer development, a feature shared with inherited risk-variants. Overall, our work provides a blueprint for the functional interpretation of noncoding mutations in genomic tests relying on defining cis-regulatory units according to cistrome-partitioning to identify cancer driver transcription regulators.

  Study EGAS00001003928

• Identification of the mutational consequences of precancerous liver disease (including alcohol abuse) on the genomes of human adult stem cells.

  Stem cells are believed to be the cells-of-origin cancer. Nevertheless, their genome remains remarkably stable during life. To increase insight into how these cells can drive tumorigenesis, we set out to determine the genomic integrity of human adult stem cells from patients with liver disease associated with increased cancer risk. To this end, we characterized genome-wide mutation profiles of single ASCs from livers of patients with alcoholic liver disease, non-alcoholic liver disease and primary sclerosing cholangitis. The patients included in our study received a liver transplant due to their liver disease. Strikingly, we found that ASCs in these livers maintain a stable genome and have comparable mutation rates as healthy human liver ASCs. We did observe more nonsense and nonsynonymous mutations in COSMIC cancer genes that are hit by dominant mutations in tumors in comparison to healthy ASCs (n.s.), including two ASCs in alcoholic liver disease patients with a nonsense mutation in PTPRK. Next, we sequenced 5 biopsies of an alcoholic tumour to identify the mutational patterns in the tumour-initiating ASC. We found that the mutational patterns are, again, similar to healthy liver, but the mutational load is slightly higher. This suggests that the increased cancer risk in the liver disease patients is not caused by an increased mutational load, but rather that the precancerous liver environment promotes outgrowth of cells that would normally be selected against.

  Study EGAS00001002983

• Carolina Breast Cancer Study (CBCS)

  The Carolina Breast Cancer Study (CBCS), phase III, is a population-based study aiming to understand the social and molecular correlates of breast cancer outcomes, particularly among Black and young women. CBCS recruited first primary breast cancer cases from 44 North Carolina counties between 2008-2013. All cases were between age 20 and 74 and self-identified as female. Black women and young women were systematically oversampled by randomized recruitment such that the study includes approximately 50% Black women and approximately 50% women diagnosed before age 50. A total of 2,998 participants were enrolled. In the ten years following diagnosis, women completed surveys approximately every 1-2 years and diagnoses of subsequent distant local recurrence and second primary tumors were ascertained via linked medical records. We identified records of women who developed secondary breast tumors (including second primary tumors, contralateral breast cancers, and locoregional recurrences), and these participants were oversampled for targeted DNA sequencing using the UNCseq panel (~1200 genes).CBCS germline pathogenic mutations cannot be investigated because participants were consented between 2008 and 2013 with specific language prohibiting this. However, germline data can be used to call somatic mutations or to standardize somatic genomic data.For sharing of study data not included here, please visit unclineberger.org for instructions on submitting a data use agreement.

  Study phs003725

• CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

  Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

  Study EGAS00001002211

• CancerDetector: Ultrasensitive and Non-Invasive Cancer Detection at the Resolution of Individual Reads using Cell-free DNA Methylation Sequencing Data

  The detection of tumor-derived cell-free DNA in plasma is one of the most promising directions in cancer diagnosis. The major challenge in such approach is how to identify the tiny amount of tumor DNAs out of total cell-free DNAs in blood. Here we propose an ultrasensitive cancer detection method, termed “CancerDetector”, using the DNA methylation profiles of cell-free DNAs. The key of our method is to probabilistically model the joint methylation patterns of multiple adjacent CpG sites on an individual sequencing read, in order to exploit the pervasive nature of DNA methylation for signal amplification. Therefore, CancerDetector can sensitively identify a trace amount of tumor cfDNAs in plasma, at the level of individual reads. We evaluated CancerDetector on the simulated data, and showed a high concordance of the predicted and true tumor burden. Testing CancerDetector on real plasma data demonstrated its high sensitivity and specificity in detecting tumor DNAs. In addition, the predicted tumor burden showed great consistency with tumor size and survival outcome. Note that all of those testing were performed on sequencing data at low to medium coverage (1X to 10X). Therefore, CancerDetector holds the great potential to detect cancer early and cost-effectively.

  Study EGAS00001002728

• Exome sequencing of a novel cervical cancer cell line

  Human cancer cell lines are largely used in the searching for new antineoplastic agents. However, due to the artifacts of a long-term in culture, cell lines do not always represent the realistic tumor cell behavior. This has motivated the development of models that better mimetics the tumor tissue, among them, the establishment of primary cell cultures. In this work, we establish and characterized a low-passage cervix cancer cell line from a Brazilian patient with squamous cell carcinoma. The phenotype confirms the epithelial and tumor origin, through cytokeratins, EpCAM, and p16 staining. Whole exome sequencing showed relevant somatic mutations in several genes including BRCA2, TGFBR1, and IRX2 genes. CNV analysis by nanostring and WGS revealed amplification in genes related mainly with kinases proteins, involved in proliferation, migration and cell differentiation, such as EGFR, PIK3CA, and MAPK7. Overexpression of EGFR was confirmed by phospho RTK-array and western blot analysis. Furthermore, the cell was sensitivity to cisplatin, with IC50 13 times lower than SiHa cell line. In conclusion, this cervical cancer cell line presents molecular alterations that are an important tool for leading pre-clinical studies of new drugs that target one or more of the altered pathways.

  Study EGAS00001003343

• A system-wide approach to monitor responses to synergistic BRAF and EGFR inhibition in colorectal cancer cells

  Molecular heterogeneity of tumors, epigenetic changes and a diverse range of molecular mechanisms are main contributors to drug resistance, which represents one of the great challenges in cancer treatment. A deeper understanding of the molecular biology of cancer has resulted in better targeted therapies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has to some extent also been observed in colorectal cancer (CRC) patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block resistance. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant CRC cells as a well-define model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both well-known and novel responses. We primarily observe widespread upregulation of tyrosine kinases (RTKs) and and metabolic pathways. This points to by which the treated cells switch energy sources as a defensive response entering a quiescent like state, while activating signalling to re-activate the MAPK pathway.

  Study EGAS00001002654