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• Breast Cancer - immune clusters - RNA-seq

  In this study we use expression data from breast cancer tumors to define immune clusters in breast cancer. Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further using gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.

  Dataset EGAD00001004985

• Circulating Tumor DNA in Intermediate Risk Rhabdomyosarcoma

  In this study, we evaluated circulating tumor DNA (ctDNA) as a biomarker in the serum of 124 patients with newly diagnosed intermediate risk rhabdomyosarcoma (IR RMS) from the Children's Oncology Group (COG) biorepository. In addition to pre-treatment serum, we also analyzed matched tumor tissue and germline in a subset of patients. We profiled samples using ultra-low passage whole genome sequencing (ULP-WGS) and a new custom hybrid-capture sequencing assay, Rhabdo-Seq, to detect copy number alterations, rearrangements, and single nucleotide variants. We found that patients with detectable ctDNA at diagnosis had significantly worse outcomes than those without detectable levels of ctDNA. Our study demonstrates that baseline ctDNA detection is feasible and prognostic in IR RMS. The ULP-WGS and targeted next-generation sequencing (Rhabdo-Seq and TranSS-Seq) data are available in this study.  

  Study phs002866

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. The repository includes the raw mass spectrometry-based proteomics data

  Study EGAS00001006712

• Data access committee for "Detection of brain cancer using genome-wide cell-free DNA fragmentomes"

  The data access committee for “ Detection of brain cancer using genome-wide cell-free DNA fragmentomes”. The DAC is comprised of Drs. Dimitrios Mathios, Jillian Phallen, Victor Velculescu, Robert Scharpf, Noushin Niknafs, and Shashikant Koul, and can be contacted at skoul3@jh.edu.

  Dac EGAC50000000605

• 2014 AML WES analysis result

  This data is belong to 2014 AML patients' exome data which is aligned to human reference(human_g1k_v37.fasta). There are 51 paired tumor/normal samples from SNUH. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001003932

• The Dynamic Immune Behavior of Primary and Metastatic Ovarian Carcinoma

  Patients with high-grade serous ovarian carcinoma are usually diagnosed at an advanced stage and often develop resistance to conventional therapy. Epithelial ovarian tumors have been shown to be rich in CD8+ lymphocytes, which infiltrate both primary and omental sites. In recent years, several prominent studies have highlighted a positive association between the presence of these immune cells and a good prognosis; however, clinical trials of immune checkpoint inhibitors have so far shown unsatisfactory results in ovarian cancer. In this study, we used an innovative combination of single-cell sequencing and spatial transcriptomics to identify the molecular mechanisms that lead to immunosuppression in primary and metastatic HGSC. Primary tumors consistently showed a more active immune microenvironment than did omental tumors. In addition, while several immune cell subtypes were present in all samples, their relative abundance differed between primary and omental tumors. Finally, we found that primary tumors were mostly populated by dysfunctional CD4 and CD8 T cells in later stages of differentiation, while omental tumors were mostly populated by naïve immune cells; this, in turn, was correlated with expression changes in the interferon α and γ pathways in epithelial cells, showing that cross-communication between the epithelial and immune compartments is important for immune suppression in ovarian cancer. These findings can impact the timing and choice of immune-modulating drugs and should be considered when planning treatment for patients with high-grade serous ovarian carcinoma.

  Study EGAS50000000038

• The Genomic Map of Poland in Open Access

  The main goal is to prepare and share WGS/WES of Polish population

  Study EGAS50000000092

• The Genomic Map of Polad in Open Access

  The main goal is to prepare and share WGS/WES of Polish population

  Study EGAS50000000095

• The Genomic Map of Polad in Open Access

  The main goal is to prepare and share WGS/WES of Polish population

  Study EGAS50000000093

• The Genomic Map of Polad in Open Access

  The main goal is to prepare and share WGS/WES of Polish population

  Study EGAS50000000118