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• Analysis of T-cell receptor clonotypes in tumor micro-environment identifies shared cancer type-specific signatures

  Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias towards the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T-cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus- driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T-cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (ie viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer, but in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific motifs that were unique to each cancer type, suggesting they may be enriched for specificity to common antigens found in the tumor microenvironment. The identification of shared TCRs in infiltrating tumor T-cells not only adds to our understanding of the tumor adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

  Study EGAS00001005480

• UniKilinikum Wuerzburg MSNZ AGRasche/AG Riedel EMD DAC

  This is a Data access committee for the Data presented in the paper tilted "Spatially resolved transcriptomics reveals profound subclonal heterogeneity and T cell dysfunction in extramedullary myeloma"

  Dac EGAC50000000173

• Helse Bergen HF Data Access Committee for the MetBreCS trial dataset submitted to Federated EGA Norway

  This Data Access Committee is appointed by Helse Bergen HF to administer access requests for the MetBreCS trial dataset submitted to Federated EGA Norway.

  Dac EGAC50000000523

• GEOCODE data access policy

  The GEOCODE Data Access Policy ensures the responsible use, security, and compliance of GEOCODE data. Access to GEOCODE data is restricted to authorized users based on role-based permissions, ensuring compliance with data protection regulations.

  Dac EGAC50000000574

• TenK10K project

  This DAC handles access to data from the TenK10K project, which is comprised of matched whole-genome sequencing (WGS), single cell RNA-sequencing (scRNA-seq), single nuclei ATAC-sequencing, and single cell Multiome datasets.

  Dac EGAC50000000931

• Legal Notice EGA is a joint effort by the EBI and CRG. Please, check their terms of use and legal notice in order to follow them in the usage of the EGA website. EBI terms of use CRG terms of use

  Documentation legal-notice

• Paediatric glioma cell line WGS

  Whole genome sequencing of 5 paediatric glioma cells lines - KNS42, SF188, UW479, RES186 and RES259. Illumina paired end sequencing is provided as 5 BAM files aligned to hg19 with bwa.

  Dataset EGAD00001004123

• Liver Tumours WGS (2020-02-20)

  The aim of this study is to define the mutational landscape of human liver tumours. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005993

• TCRab sequencing of RCC patients

  TCRab sequencing was performed on viable frozen tumor dissociated cells from three RCC patients. The raw data is available as fastq files.

  Dataset EGAD00001011046

• CHEWIE ctDNA in Rhabdomyosarcoma

  Targeted DNA based panel of multiple ctDNA samples from 10 patients througout clinical care to assess treatment response. The panel is custom-designed and property of UGS, IC.

  Dataset EGAD00001011127