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• Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

  While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

  Study EGAS00001002499

• Circulating tumor cell copy-number heterogeneity in ALK-rearranged non-small-cell lung cancer resistant to ALK inhibitors

  Gatekeeper mutations are identified in only 50% of the cases at resistance to Anaplastic Lymphoma Kinase (ALK)-tyrosine kinase inhibitors (TKIs). Circulating tumor cells (CTCs) are relevant tools to identify additional resistance mechanisms and can be sequenced at the single-cell level. Here, we provide in-depth investigation of copy number alteration (CNA) heterogeneity in phenotypically characterized CTCs at resistance to ALK-TKIs in ALK-positive non-small cell lung cancer.

  Study EGAS00001005301

• Whole-exome sequencing (WES) analysis of untreated head and neck cancer patient-derived xenografts (PDXs) matched patient tumor tissue and normal mucosa tissue.

  WES analysis was performed on untreated patient tumor/normal mucosa tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC) to investigate the preservation of tumor-specific genomic alterations in the in vivo context. 183 total samples were sequenced with paired reads on 8-10 lanes from different flowcells. They were loaded as 3538 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 2-4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002325

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting. 117 total samples were sequenced with paired reads on 10 lanes from different flowcells. They were loaded as 2400 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002278

• 13K T2D-GENES analysis files

  This data set includes the following summary level data files used for the 13k analysis of T2D-GENES data: wes.variants.list: list of variants to keep for any analysis of the exomes data wes.assoc.samples.list: list of samples to keep for association analysis wes.assoc.variants.list: list of variants to keep for association analysis wes.sv.assoc.txt: single variant association analysis results wes.gene.ptv.variants.list.txt: list of protein truncating variants to use in gene-level analysis wes.gene.ptv.assoc.txt: results from gene-level tests of protein truncating variants wes.gene.nsstrict.variants.list.txt: list of NSstrict variants to use in gene-level analysis wes.gene.nsstrict.assoc.txt: results from gene-level tests of NSstrict variants wes.gene.nsbroad.variants.list.txt: list of NSbroad variants to use in gene-level analysis wes.gene.nsbroad.assoc.txt: results from gene-level tests of NSbroad variants wes.gene.ns.variants.list.txt: list of non synonymous variants to use in gene-level analysis wes.gene.ns.assoc.txt: results from gene-level tests of non synonymous variants

  Dataset EGAD00010001188

• Peripheral immunoprofiling of stratifies COVID-19 patients based on disease-specific neutrophil signatures

  The SARS-CoV-2 pandemic has led to increasing numbers of COVID-19 patients all over the world. Aetiopathologies range from no symptoms, mild flu-like to severe cases succumbing to respiratory failure. Reports on a dysregulated immune system in the severe cases, showing similarities to cytokine release syndrome, calls for better characterization and understanding of the changes in the immune system as well as their variance across COVID-19 patients in order to be able to design according to host-directed therapies. Here, we profiled blood transcriptomes of 39 COVID-19 patients and 10 control donors. Enriched granulocyte signatures in whole blood samples were verified in granulocyte samples from 49 COVID-19 patients in a second cohort.

  Dataset EGAD00001006326

• Peripheral immunoprofiling of stratifies COVID-19 patients based on disease-specific neutrophil signatures

  The SARS-CoV-2 pandemic has led to increasing numbers of COVID-19 patients all over the world. Aetiopathologies range from no symptoms, mild flu-like to severe cases succumbing to respiratory failure. Reports on a dysregulated immune system in the severe cases, showing similarities to cytokine release syndrome, calls for better characterization and understanding of the changes in the immune system as well as their variance across COVID-19 patients in order to be able to design according to host-directed therapies. Here, we profiled blood transcriptomes of 39 COVID-19 patients and 10 control donors. Enriched granulocyte signatures in whole blood samples were verified in granulocyte samples from 49 COVID-19 patients in a second cohort.

  Dataset EGAD00001006671

• This committee is composed on individuals who have access to the data corresponding to this project: Gut microbiome modulates response to anti PD-1 immunotherapy in melanoma patients

  Dac EGAC00001000758

• Netherlands Cancer Institute (NKI-AVL) general DAC

  Data is available under reasonable request. All data requests will be reviewed by the NKI IRB and must be supported by the Principal Investigator of the study. The researcher will need to sign a data access agreement with the NKI after approval. Go to https://ega.nki.nl to fill out the form to request access.

  Dac EGAC50000000055

• Whole exome sequencing, RNA sequencing and single-cell RNA sequencing of 4 melanoma patients

  We perfomed whole exome sequencing and RNA sequencing of 4 melanoma patients to assess the detailed biological mechanisms of resistance to immune checkpoint inhibitors.

  Study JGAS000285