7147 results for "canc*"

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• CPTAC Proteogenomic Study

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.) The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein=protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the third phase of the CPTC initiative in September 2016. As the Clinical Proteomic Tumor Analysis Consortium, CPTAC continues to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach was to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. In this third phase of CPTAC, the program aims to expand on CPTAC II and genomically and proteomically characterize over 2000 samples from 10 cancer types (Lung Adenocarcinoma, Pancreatic Ductal Adenocarcinoma, Glioblastoma Multiforme, Acute Myeloid Leukemia, Clear cell renal Carcinoma, Head and Neck Squamous Cell Carcinoma, Cutaneous Melanoma, Sarcoma, Lung Squamous Cell Carcinoma, Uterine Corpus Endometrial Carcinoma) .Germline DNA is obtained from blood and Normal control samples for proteomics varied by organ site. All cancer samples were derived from primary and untreated tumor.

  Study phs001287

• Systematic Growth Factor Profiling Platform for 3D Tumor Models Reveals EstradiolResponsive Cellular Mechanisms of Immunotherapy Resistance

  Epithelial ovarian cancer (EOC) exhibits significant molecular heterogeneity, which is thought to be influenced by the tumor microenvironment (TME). However, the specific factors driving this heterogeneity remain poorly understood. In this study, we integrated growth factoromics and genomic data to identify TME factors contributing to EOC heterogeneity and immunosuppression. Our analysis revealed distinct subgroups of EOC samples with differential responsiveness to specific growth factors, particularly estradiol and R-spondin. Notably, samples with high responsiveness to estradiol and Wnt (C1 cluster) were enriched in the Mesenchymal (MES) molecular subtype, while samples with high responsiveness to R-spondin (C2 cluster) were associated with the Differentiated (DIF) and Immunoreactive (IMR) subtypes. We discovered that the G protein-coupled estrogen receptor (GPER), rather than the classical estrogen receptor alpha (ERα), was the key mediator of estrogen responsiveness and a determinant of molecular subtype classification. Single-cell sequencing analysis identified subsets of estrogen-responsive malignant cell (MAL.PDCD5) and cancer-associated fibroblast (FB.TNFSF10), which were associated with immunosuppressive patterns in the TCGA cohort. Importantly, the interaction between these cell populations significantly increased upon estrogen treatment, suggesting a potential mechanism by which estrogen signaling may contribute to the development of an immunosuppressive TME. Our findings highlight the critical role of estrogen signaling in shaping the molecular heterogeneity and immunosuppressive TME of EOC and provide novel insights into potential therapeutic targets for overcoming immunosuppression in this malignancy.

  Study EGAS50000000422

• ovarian cancer sample RNA-seq

  Tissue samples were collected from 18 ovarian cancer patients. After mechanical and enzymatic dissociation, a part of these tissues underwent growth factoromics analysis. For four cases, single-cell sequencing analysis was conducted under conditions with or without estradiol. Additionally, the remains of the tissues were frozen and subsequently subjected to bulk RNA-sequencing on 17 of these samples. Sixteen cases were diagnosed as HGSOC, while two samples were clear cell or mucinous type (Extended Data Table 1). All cases were grade 3, and none had received neoadjuvant chemotherapy. - Group C1, Epithelial Ovarian Cancer(EOC) patients with estrogen responsiveness : 6 samples - Group C2, Epithelial Ovarian Cancer(EOC) patients with estrogen non-responsiveness : 10 samples - non-classified 1-sample

  Dataset EGAD50000000613

• ovarian cancer sample exome seq

  Tissue samples were collected from 18 ovarian cancer patients. After mechanical and enzymatic dissociation, a part of these tissues underwent growth factoromics analysis. For four cases, single-cell sequencing analysis was conducted under conditions with or without estradiol. Additionally, the remains of the tissues were frozen and subsequently subjected to exome sequencing on 16 of these samples. Sixteen cases were diagnosed as HGSOC, while two samples were clear cell or mucinous type (Extended Data Table 1). All cases were grade 3, and none had received neoadjuvant chemotherapy.

  Dataset EGAD50000002057

• scRNAseq of ovarian cancer patient derived organoids

  scRNAseq of ovarian cancer patient derived organoids with or without estradiol

  Dataset EGAD50000002058

• bulkRNAseq of ovarian cancer cell lines

  bulkRNAseq of four ovarian cancer cell lines (PA-1, A2780, A2780/CP20, TOV-21G)

  Dataset EGAD50000002059

• Axes of Biological Variation in Diffuse Large B-Cell Lymphoma

  To explore the DLBCL molecular and genetic environment, we conducted genome-wide NGS sequencing on 103 DLBCL biopsy samples (named as Cornell-NCI cohort) with NGS platforms, including bulk WES, etc. The raw fastq files of the bulk WES were deposited on the EGA for user access. To obtain other genomic data from the study, please see the data links described in the paper.

  Study EGAS50000001227

• Integrated genetic analysis of primary CNS lymphoma

  Study EGAS00001007222

• ProstOmics: spatial and bulk multi-omics of prostate cancer

  In this ERC-funded ProstOmics project we have used spatial and bulk multi-omics on fresh frozen prostate cancer samples to investigate cancer biology and find for biomarkers to improve patient treatment. All tissue material were collected from prostate cancer patients undergoing radical prostatectomy who had not received any prior cancer-specific treatment.Of the 498 prostate tissue samples (114 patients) included in our project, 176 samples (N=37 patients) have been analyzed with bulk transcriptomics (RNA-seq). Some of these 176 samples were also analyzed with spatial transcriptomics (n=32, N=8, Visium 10x RNA-seq) and DNA methylomics (n=96, N=24, array). All datasets include metadata for histopathological evaluation. Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Study EGAS50000000413

• Molecular classification of small intestinal adenocarcinomas

  In this study we analyzed genomic and transcriptomic data from 135 small intestinal adenocarcinoma (SIA) patients. Through this analysis, we identified three distinct subtypes based on gene expression patterns, revealing the diverse molecular characteristics among SIA patients. Our findings provide comprehensive insights into the unique features of each subtype.

  Study EGAS50000001238

• Intrapatient tumor heterogeneity and clonal evolution in metastatic salivary gland cancer: an autopsy study

  This data contains DNA sequencing data of an autopsy study in patients with salivary gland cancer. Whole-genome sequencing was performed on multiple spatially separated tumor samples per patient (4-7 per patient) and healthy control samples.

  Study EGAS50000001420

• 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

• Intrapatient tumor heterogeneity and clonal evolution in metastatic salivary gland cancer: an autopsy study: access to data

  Funded by the Radboud Oncology Fund and the Dr. C.J. Vaillant Fund, the Salivary Gland Cancer Autopsy research group (Research Group) has sequenced DNA of 17 salivary gland cancer samples of and three healthy control samples from three patients with salivary gland cancer. This research project is led by Carla M.L. van Herpen from Radboud University Medical Centre in Nijmegen, the Netherlands (“Radboudumc”). The DNA sequencing data have been used for an analysis of intrapatient tumor heterogeneity and clonal evolution of metastatic salivary gland cancer. The Research Group is willing to consider applications from third party researchers for access to the DNA sequence data. Access to the data will be granted to qualified researchers for approved use. Access to DNA Sequencing Data is available by application to the Data Access Committee (DAC). Researchers granted access to DNA Sequencing Data must feedback the results of their research to the Research Group, after publication in accordance with the Research Group publication policy set forth in the Data Access Agreement.

  Dac EGAC50000000792

• Clinical data of liver cancer patients from EuCanImage - Use case 1 Synthetic

  This study is part of EuCanImage project. It contains the standardized clinical information following FHIR model. The data was collected together with MRI of patients diagnosed with liver cancer (HCC) and controls (non-HCC). All data is synthetic.

  Study EGAS50000001444

• EuCanImage_DEMO_UC1

  This dataset contains the standardized clinical information related to the Use case 1 - Liver Cancer (HCC) from EuCanImage. The Data is Synthetic.

  Dataset EGAD50000002083

• SCANDARE TNBC transcriptomics data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 124 frozen samples (n=84 at baseline and n=40 paired at post-NAC surgery) from 91 TNBC patients using total RNAseq technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001416

• SCANDARE TNBC WES data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 247 frozen samples at baseline and 138 germline DNA from 139 TNBC patients using WES technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001661

• SCANDARE TNBC WGS data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 108 FFPE samples at baseline and 108 germline DNA from 108 TNBC patients using WGS technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001662

• Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

  In this study, we demonstrate that aberrant expression of SLAMF6 on acute myeloid leukemia (AML) cells serves as a novel immune escape mechanism that can be inhibited by antibodies against the SLAMF6 dimerization site. This constitutes a novel mechanism of checkpoint inhibition, which paves the way for immunotherapy in AML and other SLAMF6-expressing cancers. This study utilizes single cell sequencing data from the AML cell line HNT-34 co-cultured with normal T cells, with and without antibody targeting SLAMF6, as well as single cell data of 38 primary AML samples.

  Study EGAS50000001085

• Dynamic Evolution of Fibroblasts Revealed by Single Cell RNA Sequencing of Human Pancreatic Cancer

  Understanding the constituents of the pancreatic ductal adenocarcinoma (PDAC) microenvironment may illuminate more efficacious targets for treating this aggressive malignancy. However, the compositional changes occurring in untreated and treated PDAC relative to both normal and inflamed pancreas have not been well characterized. To provide a more comprehensive understanding of the PDAC tumor microenvironment relative to the non-cancerous pancreas, we performed single-cell expression profiling (10X Genomics Chromium) on samples of upfront resectable PDAC, FOLFIRINOX-based treated PDAC, chronic pancreatitis, and normal pancreas specimens from 19 patients. Spatial gene expression profiling (10X Genomics Visium) was performed to gain additional insight into cell populations. Our analysis revealed that fibroblasts are central mediators of cell-cell communication in both inflamed and malignant settings and defined unique roles for these cell populations in different disease contexts.

  Study phs003751

• A Therapeutic Vaccine for Fibrolamellar Hepatocellular Carcinoma

  Fibrolamellar hepatocellular carcinoma (FLC) is a rare form of liver cancer affecting 33 children and young adults that is driven by a chimeric protein, DNAJ-PKAc. We conducted a phase 1 clinical trial of a therapeutic vaccine targeting DNAJ-PKAc 38 (FLC-Vac), in combination with nivolumab and ipilimumab, in children and adults with advanced FLC. Among 16 patients enrolled, 12 completed the vaccine priming phase and were evaluable for both immunological and clinical endpoints. Grade 3 treatment-related adverse events were reported by six patients (37.5%). DNAJ43 PKAc-specific T cell responses were detected in 9/12 patients after treatment. In the subset of patients who completed the initial priming phase the disease control rate (DCR) was 75% (9/12), with three partial responses (25%). All patients with clinical responses also had DNAJ-PKAc specific T cell responses, from which we identified multiple class II-restricted T cell receptors (TCRs) with specificity for DNAJ-PKAc. Correlates of response included both functional neoantigen reactivity and changes in TCR repertoire features over time. Immune escape in two patients corresponded with immune exhaustion rather than neoantigen escape or HLA loss.

  Study phs003970

• Single-cell Transcriptome Profiling of Treatment-naïve and Post-treatment Colorectal Cancer: Insights into Putative Mechanisms of Chemoresistance

  Drug resistance remains a major clinical challenge in the treatment of colorectal cancer (CRC) with conventional chemotherapy. Investigation of cancer cells and tumor microenvironment (TME) following chemotherapy is critical for unraveling the mechanisms of resistance. In this study, we analyzed scRNA-Seq data from 56 CRCs including treatment-naïve tumors (25 microsatellite stable (MSS) tumors and 7 tumors with microsatellite instability (MSI)); and tumors treated with standard chemotherapy with the known response status (18 responders and 6 progressors). We observed in treatment-naïve MSS CRC that right-sided tumors are more immunogenic with higher numbers of B cells and CD8+ T memory effector cells than left-sided tumors. MSI CRC were even more immunogenic then MSS CRC and were characterized by elevated Tregs in their TME. In the post-treatment CRC there was a high prevalence of dendritic cells (DC) in the TME in the response group. The DC-derived signature was associated with better survival in a large CRC cohort from the TCGA. We also observed two fibroblast subtypes in CRC, one of which was enriched in progressors and was associated with poor survival in a CRC-TCGA cohort. Progressors also showed elevated exhausted CD8+ T memory cells and monocytes suggesting a pro-inflammatory TME. In tumor cells in progressor group we identified specific expression of chemo-protective markers MTRNR2L1 and CDX1; and their co-expression with stemness-related marker CD24. In summary, scRNA-Seq provides a valuable information for the discovery of prognostic markers, and reveals distinct features of CRC based on location, metastasis status, MSI status and treatment response status.

  Study EGAS50000000830

• Dataset of scRNAseq from 56 CRC, treatment-naive and post-chemotherapy

  The dataset includes FASTQ source files of scRNA-seq for 56 CRC patients, sequenced with Illumina 10x platform. All patients were diagnosed with colorectal cancer between 2014 and 2022 at the Gustave Roussy Institute. Cohort includes 32 samples from untreated patients and 24 samples from patients who received chemotherapy. Chemotherapy included FOLFOX or FOLFIRI as first line, in some cases in combination with anti-VEGF or anti-EGRF drugs (avastin, bevacizumab or cetuximab) as the second and third lines. The post-treatment cohort included 18 responders (partial response, stable disease and complete response) and 6 progressors (progressive disease).

  Dataset EGAD50000001218

• Single-cell Transcriptome Profiling of Treatment-naïve and Post-treatment Colorectal Cancer: Insights into Putative Mechanisms of Chemoresistance

  These terms and conditions govern access to the managed access datasets to which the User Institution has requested access. The User Institution agrees to be bound by these terms and conditions.

  Dac EGAC50000000482

• Fragmentomics analyses of urinary cell-free DNA permit multi-urologic cancer detection and reduction in tissue biopsies for prostate cancer

  This study demonstrated the close association between urinary cell-free DNA (cfDNA) methylation status and the fragmentation patterns in healthy controls and patients with various diseases. Fragmentomics-based methylation analysis (FRAGMA) enables accurate estimation of methylation levels in urinary cfDNA, which is proved by paired bisulfite sequencing and non-bisulfite sequencing data. FRAGMA showed high accuracy in deducing tissue-of-origin of urinary cfDNA in transplantation patients and pregnant women. Moreover, FRAGMA showed great potential in the detection and classification of multiple cancers from the urinary system, including bladder, kidney, and prostate cancer. This study demonstrated that FRAGMA could be applied to improve current diagnostic strategies based on urine samples.

  Study EGAS50000001431