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• Non-small cell lung cancer proteome subtypes expose targetable oncogenic drivers and immune evasion mechanisms

  Proteome-level data of non-small cell lung cancer remains limited. In this study, we have collected 141 cases, and performed histological review, methylation profiling (113), custom panel sequencing (140), microarray expression profiling (118) and mass-spectrometry based proteomics (141). We identified six distinct groups of patients driven by histology, growth pattern, immune cell infiltration, druggable driver mutations, and hypomethylation-associated neoantigen burden. We validated the subtypes in independent proteomics datasets. Proteomics can refine treatment-oriented subtyping of non-small cell lung cancer.

  Study EGAS00001005482

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD38234__WG_

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003324

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD43291_Novaseq__Exome_

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003503

• Human adipose tissue immune cells

  We describe a novel and conserved Trem2+ lipid-associated macrophage (LAM) subset and identify markers, spatial localization, origin, and functional pathways associated with these cells. Genetic ablation of Trem2 in mice globally inhibits the downstream molecular LAM program, leading to adipocyte hypertrophy as well as systemic hypercholesterolemia, body fat accumulation, and glucose intolerance. These findings identify Trem2 signaling as a major pathway by which macrophages respond to loss of tissue-level lipid homeostasis, highlighting Trem2 as a key sensor of metabolic pathologies across multiple tissues and a potential therapeutic target in metabolic diseases.

  Study EGAS00001003725

• scRNA-seq and scTCR-seq data IMCISION

  We performed single cell RNA and TCR sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and on-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset.

  Study EGAS00001007368

• AfricanNeo aDNA Study

  With the largest genomic dataset to date of Bantu-speaking populations, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we shed fresh light on the expansion of peoples speaking Bantu languages that started ~4000 years ago in western Africa. We have generated whole-genome sequences from 12 Late Iron Age individuals. Our comprehensive genetic analysis of the expansion of people speaking Bantu languages reveals a complex history of serial founder events, variable levels of contact with local groups, and spread-over-spread events.

  Study EGAS00001007519

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• GoNL release 5 haplotype panel

  The samples in this panel come from 250 families: 248 parents-child trios and 2 parent-child duos. As the children do not provide additional haplotypes or population information, they were excluded from the panel. The samples present in the release are composed of 248 couples, 2 single individuals and 1 sample composed from the 2 haplotypes from the duo's children transmitted by their missing parent. The composed sample is named gonl-220c_223c.The files contain a total of 18.9M SNVs and 1.1M INDELs in autosomal chromosomes. They were generated by phasing/imputing the SNVs (a) and INDELs (b) using MVNCall. Only sites passing filters are reported. Sites filtered as part of the GoNL inaccessible genome were kept (but flagged as filtered) and still may contain true positive calls but should be used with care as they are located in parts of the genome that are less well captured (systematic under or over-covered or low-mapping quality)

  Dataset EGAD00001000744

• RNA-seq of MPNSTs

  Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are highly aggressive soft-tissue sarcomas with a poor prognosis and a lack of therapeutic options. In this study, we analyse the whole-transcriptome MPNST and combine them with WGS data from a partially overlapping sample set. These analyses and the inclusion of another public dataset allow us to identify three genomic MPNST subgroups with distinct biological and clinicopathological features that can inform management and precision treatments. Published in "Identification of Malignant Peripheral Nerve Sheath Tumor (MPNST) subtypes with distinct genomic identities."

  Study EGAS50000001733

• Data Access Commitee for the project : Methylome profiling of human mesenchymal chondrosarcoma

  Dac EGAC00001003217