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• Massive Genomic Rearrangment Acquired in a Single Catastrophic Event During Cancer Development

  Cancer is driven by mutation. Using Agilent exome hybridisation capture and Illumina GA massively parallel sequencing technology, we aim to sequence ~1600 microRNAs plus the protein coding genome of 25 matched human renal cancer samples. Bespoke algorithms are being developed to identify the somatically acquired point mutations, insertions and deletions in these samples. This project will give unprecedented insights into mutational processes, cellular repair pathways and gene networks associated with renal cancer development.Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00000000029

• Sequence data to study genomic CNVs that drive apoptotic resistance and relapses on immune checkpoint inhibitors

  This project investigates the genomic mechanisms underlying acquired resistance to immune checkpoint inhibitors (ICIs) across tumor types, addressing the critical clinical problem of treatment relapses where the molecular basis remains poorly understood. Through integrative genomic analyses of longitudinal clinical melanomas, functional CRISPR-Cas9 screens, and human and murine melanoma models, the study demonstrates that copy-number variant (CNV)-driven subclonal evolution is a primary driver of clinical relapses. The research identifies resistance-driver genes targeted by CNVs, including pro-apoptotic gene deletions and anti-apoptotic gene amplifications, which collectively downregulate apoptotic priming in resistant cells. The findings establish that modulating the apoptotic threshold can prevent or reverse ICI resistance, positioning CNV evolution as a key driver of acquired resistance and identifying apoptotic regulation as a therapeutic target to combat resistance evolution.

  Study EGAS50000001055

• Deregulation of FOXF1/FENDRR from t(14;16)(q32;q24) defines a subtype of high risk lineage ambiguous leukemia

  Despite great progress in understanding the genomic basis of immature T-cell acute lymphoblastic leukemia/lymphoblastic lymphoma (T-ALL) and acute leukemias of ambiguous lineage (ALAL), there are still cases that lack defining genetic markers, complicating risk stratification and limiting targeted therapeutic options. Here, we describe a subtype of leukemia defined by the t(14;16)(q32;q24) translocation, which places the FOXF1 gene and its antisense long noncoding RNA gene FENDRR under the regulatory control of the BCL11B enhancer, leading to their ectopic transcriptional activation. Analysis of different high-throughput sequencing data, including WGS, RNA-seq, scDNA-seq, scRNA-seq, ChIP-seq, ATAC-seq, and HiChIP-seq, identified BCL11B-enhancer mediated deregulation of FOXF1/FENDRR as a hallmark of a subtype of high-risk lineage ambiguous leukemia that is potentially amenable to targeted therapeutic intervention.

  Study EGAS50000001255

• Single-cell RNA sequencing of 16 NPM1 mutated AML patients

  NPM1 mutated AML is the largest class in WHO classification, however several subtypes within NPM1 were already reported. Here, we sequence 16 NPM1 mutated AML samples with single-cell RNA-sequencing and multi-color flow cytometry from three major NPM1 subtypes we previously identified, totaling more than half a million cells. We show that the differences among three NPM1 subtypes are mainly driven by cell composition, and these differences are also reflected at cell surface protein level. With the re-analysis of CITE-seq data from another cohort and single cell variant calling on our data, we also report two distinct stem cell phenotypes: one with leukemic (CD34dimCD38-CD45RA+) and another with pre-leukemic (CD34+CD38-CD45RA-) origin. We believe that our data and findings provide novel insights regarding the etiology of NPM1 mutated AML.

  Study EGAS50000000332

• "Distinct immunometabolic signatures in circulating immune cells define disease outcome in acute-on-chronic liver failure"

  We performed single-cell transcriptomics of PBMC’s from healthy (n= 3), acute decompensated (AD) (n= 3) and Acute-on-chronic liver failure (ACLF) patients. Lay Summary: Acute-on-chronic liver failure (ACLF) develops in cirrhotic patients and is characterized by an hyper-inflammatory immune state driving multiple organ failure(s). As a paradox, circulating immune cells also show transcription and metabolic evidence of exhaustion, explaining why these patients are often susceptible to secondary infections. We characterized at a transcriptional level all circulating immune cells of ACLF patiens, and specifically unraveled a distinct recovery and non-recovery ACLF signature within the monocyte population. Moreover, these changes were closely linked to metabolic differences within these cells. The described alterations allowed for a robust prediction of recovery and non-recovery of patients at admission to the hospital.

  Study EGAS50000000391

• Transcriptomic profiles of tumor samples from patients with stage I-III TNBC treated with anthracycline-taxane chemotherapy plus fasting-mimicking diet plus/minus metformin in the context of the BREAKFAST trial (NCT04248998)

  BREAKFAST is a randomized, non-comparative, phase II trial enrolling stage I-III (cT>1cm) TNBC pts treated with neoadjuvant doxorubicin-cyclophosphamide q3w for 4 cycles, followed by weekly paclitaxel for 12 cycles. Pts were randomized 1:1 to receive: CT + triweekly 5-day FMD cycles (arm A), or CT + FMD + daily metformin (1700 mg) (arm B). The primary study objective was to investigate if one or both experimental treatments were able to increase pCR rates when compared to anthracycline-taxane CT alone according to historical data. Secondary/exploratory endpoints included biomarker analyses based on tumor transcriptomics analyses. Specifically, we collected fresh-frozen tumor samples at baseline and 14-21 days after the first treament cycle and we analyzed the RNA-seq profiles to identify early predictors of treatment activity.

  Study EGAS50000000690

• SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population

  The SweGen project represents a comprehensive map of genetic variation in the Swedish population. This Study contains four datasets where the first one contains whole-genome sequencing data in CRAM-format for 942 individuals from the Swedish Twin Registry, the second one contains genetic variant frequencies in VCF-format for the same individuals, the third one contains whole-genome sequencing data in CRAM-format for 58 individuals from the Northern Sweden Population Health Study and the fourth one contains genetic variant frequencies in VCF-format for the same individuals. The data, serving as a reference dataset, is a valuable and national resource for genetics research and clinical diagnostics and can be used, for instance, to increase understanding of both rare and complex disorders. It also serves as an international resource for larger studies of human population genetics.

  Study EGAS50000000906

• Whole genome sequencing data from tumor and normal samples

  Whole genome sequencing FASTQ files from tumor and normal samples from 202 patients. All experiments reported in this article were performed in the Clinical Laboratory Improvement Amendments (CLIA)-certified and College of American Pathologists (CAP)-accredited laboratories at Personalis Inc., as guided by the Association for Molecular Pathology (AMP) and CAP’s joint recommendations52. Preferred input material consisting of FFPE slides (enabling H&E and macrodissection which is part of the standard NeXT Personal process) was not available for the majority (94%) of tumor samples. Most tumor samples (72%) were processed from FFPE curls, with the remaining processed from pre-extracted DNA and fresh frozen material. Where FFPE material on slide was available, tumor sections were macrodissected to increase tumor content, with a minimum allowable cellularity threshold of 20% determined by pathological review. The tumor cellularity threshold of 20% was chosen based on prior work demonstrating that no significant correlation is observed between tumor purity and assay limit of detection (LOD) at this threshold31. Genomic DNA was isolated from tumor and normal samples and WGS libraries prepared as previously described31. Genomic DNA was isolated from matched tumor and normal samples using the Qiagen AllPrep DNA/RNA FFPE Tissue Kit or the QIAamp DNA Mini Kit (QIAGEN, Germantown, MD, USA) using internally optimized workflows. WGS sequencing libraries were prepared with 120-500 ng of acoustically sheared genomic DNA (Covaris LLC, Woburn, MA, USA) using the KAPA HyperPrep Kit (Roche Sequencing Solutions, Pleasanton, CA, USA) and customized methods. Libraries were cleaned-up using AMPure XP beads and then quantified using the KAPA Library Quantification Kit (Roche Sequencing Solutions, Pleasanton, CA, USA), before being sequenced to 30X depth of coverage using a NovaSeq 6000 instrument (Illumina, San Diego, CA, USA).

  Dataset EGAD50000001909

• Somatic mutations, clonal architecture and genomic evolution in multiple myeloma

  Multiple myeloma is an incurable plasma cell malignancy whose molecular pathogenesis is incompletely understood. We used whole exome sequencing, copy number profiling and cytogenetic to analyses 84 samples from 67 patients with myeloma. In addition to known myeloma genes, we identify new candidate genes, including truncations of SP140, ROBO1 and FAT3 and clustered missense mutations in EGR1. We find oncogenic mutations in cancer genes not previously implicated in myeloma, including SF3B1, PI3KCA and PTEN. We define diverse processes contributing to the mutational repertoire, including kataegis and somatic hypermutation. Most cases have at least one cluster of subclonal variants, including subclonal driver mutations, implying on-going tumor evolution. Serial samples revealed diverse patterns of clonal evolution, including linear evolution, differential clonal response and branching evolution. Our findings reveal the myeloma genome to be heterogeneous across patients and, within individual patients, to exhibit diversity in clonal admixture and dynamics in response to therapy.

  Dataset EGAD00001000339

• Adipose transcriptome and plasma metabolome responses after a 6-day very-low energy fast in obesity: a single-arm feeding trial (FASTOMICS-6)

  Background: Fasting and ketogenic diets have gained popularity due to potential health benefits, in part via autophagy and other protective processes. However, although the basic physiology of fasting is well-established, we lack a deeper understanding of mechanisms on the tissue level and associated metabolome changes, particularly in humans. Method: 4 males and 9 females with severe obesity underwent a very-low-energy in-hospital feeding study (600 kcal/day). Plasma (n=13) and subcutaneous adipose tissue (sAT) samples (n=12) were collected in the morning before and after 6 days and analysed by GC-MS/MS and RNA-sequencing, respectively. Gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis were used to identify biological pathways and modules of affected genes and their correlation with plasma ketones and metabolites.

  Study EGAS50000001015