5707 results for "canc*"

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• Cancer Genome Database Data Access Committee (CGDB_DAC)

  Dac EGAC00001000033

• T-cell receptor sequencing of tumor-infiltrating lymphocytes (TIL) in breast cancer

  The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing patients’ tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating widely available archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of various tumor environments. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and revealed higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top ten dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is readily applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

  Study EGAS00001007125

• Spatial and temporal intra-tumoural heterogeneity in advanced High-Grade Serous Ovarian Cancer: implications for surgical and clinical outcomes

  Limited evidence exists on the extent and impact of spatial and temporal heterogeneity of high grade serous ovarian cancer (HGSOC) on tumour evolution and patients surgical and clinical outcome. We investigated this through systematic mapping of multi-site tumours at initial presentation and matched relapse from 49 chemo-naïve HGSOC patients with high tumour load, operated upfront. Our data provides a unique insight into the tumour evolution and metastatic pathways of HGSOC across time and space, how this complexity relates to surgical and clinical outcome and its consequences on clinical decision-making.

  Study EGAS00001007164

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

  Purpose: Current diagnostic methods for endometrial cancer lack specificity, leading to many women undergoing invasive procedures. The aim of this study was to evaluate somatic mutations in urine to accurately discriminate endometrial cancer patients from controls. Experimental Design: Overall, 72 samples were analyzed using next-generation sequencing with molecular identifiers targeting 47 genes. We evaluated urine supernatant samples from women with endometrial cancer (n=19) and age-matched controls (n=20). Cell pellets from urine and plasma samples from seven cases were sequenced; further, we also evaluated paired tumor samples from all cases. Finally, immunohistochemical markers for molecular profiling were evaluated in all tumor samples. Results: Overall, we were able to identify mutations in DNA from urine supernatant samples in 100% of endometrial cancers. In contrast, only one control (5%) showed variants at a variant allele frequency (VAF)≥2% in the urine supernatant samples. The molecular classification obtained by using tumor samples and urine samples showed good agreement. Analyses in paired samples revealed a higher number of mutations and VAFs in urine supernatants than in urine cell pellets and blood samples. Conclusions: Evaluation of somatic mutations using urine samples may offer a user-friendly and reliable tool for endometrial cancer detection and molecular classification. The diagnostic performance for endometrial cancer detection was very high, and cases could be molecularly classified using these noninvasive and self-collected samples. Additional multi-center evaluations using larger sample sizes are needed to validate the results and understand the potential of urine samples for the early detection and prognosis of endometrial cancer.

  Study EGAS00001007396

• Data access committee of the Prostate Cancer Research Center, University of Tampere, Finland.

  Dac EGAC00001000423

• St. Jude Children’s Research Hospital – Washington University Pediatric Cancer Genome Project Steering Committee

  Dac EGAC00001000044

• St. Jude Children’s Research Hospital – Washington University Pediatric Cancer Genome Project Steering Committee

  Dac EGAC00001000045

• Barts Cancer Institute - Follicular Lymphoma Whole Genome Sequencing Project Data Access Committee

  Dac EGAC00001000086

• Cancer genomics project, the University of Tokyo Data Access Committee

  Dac EGAC00001000087

• Asian lung cancer genome data

  Dac EGAC00001000248

• MDACC-Yale-breast-cancer

  Dac EGAC00001000298

• Memorial Sloan Kettering Cancer Center - Human Oncology & Pathogenesis Program (HOOP) - Data Access Committee

  Dac EGAC00001000305

• DAC for the study of response to EGFR Blockade in Colorectal Cancer

  Dac EGAC00001000360

• Radboud Pediatric Cancer Data Access Committee

  Dac EGAC00001000369

• DAC of Synergie Lyon Cancer

  Dac EGAC00001000382

• Data Access Committee for COLO829 Somatic reference standard for cancer genome sequencing

  Dac EGAC00001000408

• Data Access Committee for the Metastatic Breast Cancer Whole-exome sequencing study

  Dac EGAC00001000434

• Genetic predisposition to cancer, University of Tampere

  Dac EGAC00001000488

• Ludwig Center for Cancer Genetics and Therapeutics at Johns Hopkins

  Dac EGAC00001000507

• The Institute of Cancer Research - Endocrinology Team

  Dac EGAC00001000532

• Data access policy for PDTX Breast Cancer data from Bruna et al (2016), Cell.

  Dac EGAC00001000540

• DAC for Single Cell Transcriptomics of Colorectal Cancer

  Dac EGAC00001000550

• Peking University BIOPIC Data Access Committee (PUBDAC).The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any academic research institutions complying with the laws and bioethic regulation policies of China will be approved.

  Dac EGAC00001000551

• Data access committee for study - The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program "CASCADE".

  Dac EGAC00001000574

• Dr. Fatima Mechta-Grigoriou, PhD, DR1 Head of Stress and Cancer Laboratory Deputy Director Genetic and Biology of Cancer Dpt Institut Curie - Inserm U830

  Dac EGAC00001000581