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• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Whole exome and targeted DNA sequencing data for formalin-fixed paraffin embedded tissue from de novo small cell prostatic carcinoma cases

  This dataset consists of 44 compressed paired fastq files, 15 of which are generated from whole exome sequencing, and 29 of which are generated from DNA sequencing using a targeted gene panel capturing the exonic regions of 73 prostate cancer driver genes. Targeted DNA sequencing was performed on an Illumina MiSeq (v3 600 cycle kit), and exome sequencing was done using an Illumina HiSeq 2500 (v4 250 cycle kit) machine. The fastq files are named in accordance with the sample aliases provided, which reflect the pathology of interest to this study (small cell prostatic carcinoma--SCPC), whether it was sequenced using an exome or targeted gene panel, whether the FFPE sample was sourced from tumor or benign tissue (labeled T or B, respectively), and whether there exists multiple samples belonging to a single patient.

  Dataset EGAD00001004139

• Chromosome Segregation Errors Promote a Diverse Spectrum of Simple and Complex Genomic Rearrangements

  Cancer genomes are frequently characterized by numerical and structural karyotypic abnormalities. Here we combined an inducible centromere-specific inactivation approach with selection for a conditionally essential gene, a strategy we term ‘CEN-SELECT’, and show that single-chromosome missegregation during cell division can directly drive a broad spectrum of structural rearrangement types. Cytogenetic profiling revealed that missegregated chromosomes are 120-fold more susceptible to developing seven major categories of structural variants, including translocations, insertions, deletions, and reassembly into chromothriptically rearranged chromosomes. Whole-genome sequencing of clones with genetically propagatable derivative chromosomes identified complex rearrangements and copy-number alterations that can result in gene inactivation or extrachromosomal gene amplification. We conclude that chromosome segregation errors are sufficient to drive extensive structural variation that recapitulates those commonly associated with human cancers.

  Dataset EGAD00001004163

• Undifferentiated sarcomas develop through distinct evolutionary pathways

  Undifferentiated sarcomas (USARC) of adults are diverse, rare and aggressive soft tissue cancers. Recent efforts have confirmed that USARC exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the genomic basis of this structural complexity by integrating whole genome sequencing, ploidy analysis and methylation profiling of 53 USARC. We identified whole genome doubling as a prevalent and pernicious force in USARC tumourigenesis. Deconvolution of the complex copy number and rearrangement landscapes show distinct signatures associated with chromothripsis, early-haploidy, and successive whole-genome-doubling events, suggesting four divergent models of sarcoma development. We show similar distinct evolutionary tumourigenic pathways in different sarcoma subtypes from the Cancer Genome Atlas. Thirteen percent of tumours exhibited a hypermutator phenotype, opening new avenues for clinical management such as immunotherapy, whilst the period prior to and between genome doubling events may represent clinically relevant interventional points in USARC.

  Dataset EGAD00001004162

• RRBS data (cfSort study) from noncancer tissue DNA

  The RRBS libraries of the genomic DNA from the 521 tissue samples were constructed following the standard RRBS protocol. 100-200 ng of intact genomic DNA in the volume of 21.5 µl was used as input material. Restriction digestion was done with 2.5 µl 10xCutSmart buffer and 1 µl MspI (NEB) for 18 h at 37 oC and 20 min at 65 oC. 0.5 µl 10xCutSmart buffer, 0.3 µl dACGTP mixture (100 mM dATP, 10 mM dCTP, 10 mM dGTP), 1 µl Klenow (exo-, 5U/µl, NEB) and 2.6 µl RT-PCR water, 0.6 µl 50 mM DTT (ThermoFisher) was added to the mixture for end repair and A-overhang addition with the program 30 oC for 20 min, 37 oC for 1 h and 75 oC for 20 min. Adapter ligation was then performed with 1 µl 10xThermoFisher HC T4 ligase buffer, 0.4 µl 100 mM ATP (ThermoFisher), 0.2 µl 50 mM DTT, 1 µl ThermoFisher HC T4 DNA ligase (30 Weiss Unit/µl), 30 ng home-made duplex UMI adapter with all the cytosines methylated (protocol adopted from Kennedy et al.) at 16 oC for 20 h and 65 oC for 20 min. Bisulfite conversion of the adapter-ligated product was carried out with QIAGEN EpiTect plus DNA bisulfite kit following their protocol for two rounds of conversion. The converted product was purified with Qiagen MinElute spin column and eluted with 20 µl RT-PCR water. PCR amplification was done using the NEBNext Multiplex Oligos for Illumina (2.5 µl of universal and index primer each) and 25 µl KAPA HiFi HotStart Uracil+ ReadyMix (Roche) with the following cycling conditions: 98 oC for 45 s, 9 cycles of 98 oC for 15 s, 60 oC for 30 s and 72 oC for 30 s, followed by a final extension at 72 oC for 5 min. The PCR product was purified with 1x AmpureXP beads and eluted with 30 µl EB buffer. DNA concentration was measured by Qubit 1xdsDNA HS assay. 5% TBE-UREA PAGE and bioanalyzer assay was performed as quality control on each library before sequencing.

  Dataset EGAD00001010880

• Non-viral precision T cell receptor replacement for personalized cell therapy

  The T cell receptor (TCR) provides the fine specificity of T cells to recognize mutations in cancer cells 1-3. We developed a clinical-grade approach based on CRISPR/Cas9 non-viral precision genome editing to simultaneously knock-out the two endogenous TCR genes, TCRα (TRAC) and TCRβ (TRBC), and insert in the TRAC locus the two chains of a neoantigen-specific TCR (neoTCR), isolated from the patient’s own circulating T cells using a personalized library of soluble predicted neoantigen-HLA capture reagents. Sixteen patients with refractory solid cancers received up to three distinct neoTCR-transgenic cell products, each expressing a patient-specific neoTCR, in a cell dose-escalation, first-in-human phase 1 clinical trial (NCT03970382). One patient had grade 1 cytokine release syndrome, and one grade 3 encephalitis. All had the expected side effects from the lymphodepleting chemotherapy. Five patients had stable disease, and the other 11 had disease progression as best response on therapy. NeoTCR-transgenic T cells were detected in tumour biopsies post-infusion at frequencies higher than the native TCRs pre-infusion. This study demonstrates the feasibility of isolating and cloning multiple TCRs recognizing mutational neoantigens, the simultaneous knock-out of the endogenous TCR and knock-in of the neoTCRs using single-step, non-viral precision genome editing, the manufacturing of neoTCR engineered T cells at clinical grade, the safety of infusing up to three gene edited neoTCR T cell products, and the ability of the transgenic T cells to traffic to the patients’ tumours.

  Study EGAS00001006898

• Inferring causal genes at type 2 diabetes GWAS loci through chromosome interactions in islet cells

  Resolving causal genes for type 2 diabetes at loci implicated by genome-wide association studies (GWAS) requires integrating functional genomic data from relevant cell types. Chromatin features in endocrine cells of the pancreatic islet are particularly informative and recent studies leveraging chromosome conformation capture (3C) with Hi-C based methods have elucidated regulatory mechanisms in human islets. However, these genome-wide approaches are less sensitive and afford lower resolution than methods that target specific loci. Methods: To gauge the extent to which targeted 3C further resolves chromatin-mediated regulatory mechanisms at GWAS loci, we generated interaction profiles at 23 loci using next-generation (NG) capture-C in a human beta cell model (EndoC-βH1) and contrasted these maps with Hi-C maps in EndoC-βH1 cells and human islets and a promoter capture Hi-C map in human islets. Results: We found improvements in assay sensitivity of up to 33-fold and resolved ~3.6X more chromatin interactions. At a subset of 18 loci with 25 co-localised GWAS and eQTL signals, NG Capture-C interactions implicated effector transcripts at five additional genetic signals relative to promoter capture Hi-C through physical contact with gene promoters. Conclusions: High resolution chromatin interaction profiles at selectively targeted loci can complement genome- and promoter-wide maps.

  Dataset EGAD50000000517

• Nala TAS-LRS PGx Study

  Sequencing was performed on the PromethION Flow Cell R10 (M version) using the P2 Solo Sequencer (MinION release 24.02.16). The library was divided into three portions and loaded in a tapered manner across three time points. At the first time point, the initial portion of the library was loaded, and sequencing began in whole-genome mode (without adaptive sampling), to monitor QC (N50 within the expected range). After one hour, adaptive sampling was activated. A custom BED file was used to define the target regions (N=326). Each region was extended by 20 kb upstream and downstream, and overlapping regions were merged into non-redundant intervals using bedtools43, covering a total of 1.3% of the human genome. At the second time point (20–24 hours after sequencing began, or when fewer than 2000 pores remained active), the flow cell was washed following ONT’s Flow Cell Wash Kit protocol, and the second portion of the library was loaded. At the third time point (40–48 hours), the second portion of the library was retrieved, and merged with the third portion. The flow cell was washed and reloaded with the mixed library. POD5 files were basecalled using Dorado v0.8.1 in super-accuracy (SUP) mode with the dna_r10.4.1_e8.2_400bps_SUP@v5.0.0. Reads from the initial 1 h Whole Genome Sequencing (WGS) and subsequent 72 h adaptive sampling were filtered for Q-scores >10. Passing reads were demultiplexed using Dorado’s demux function, then combined per sample and mapped to the GRCh38 reference genome using Minimap2 v2.22. Files were converted to CRAM using samtools.

  Dataset EGAD50000001609

• Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma

  Atezolizumab (anti–programmed death-ligand 1 [anti-PD-L1]) and bevacizumab (anti-vascular endothelial growth factor [anti-VEGF]) combination therapy has become the new standard of care in patients with unresectable hepatocellular carcinoma. However, potential predictive biomarkers and mechanisms of response and resistance remain less understood. We report integrated molecular analyses of tumor samples from 358 patients enrolled in the GO30140 phase 1b or IMbrave150 phase 3 trials who were treated with atezolizumab combined with bevacizumab, atezolizumab alone, or sorafenib. Pre-existing immunity assessed by high expression of CD274 (PD-L1 mRNA), T-effector signature, and intratumoral CD8+ T cell density were associated with response and better clinical outcomes with the combination treatment. Less clinical benefit was associated with high regulatory T cell (Treg) to effector T-cell ratio and high expression of oncofetal genes such as GPC3 and AFP. Improved outcomes from the combination vs atezolizumab alone appeared to be associated with high expression of KDR (VEGFR2), Treg, and myeloid inflammation signatures, indicating anti-VEGF may contribute by targeting these axes. These findings were further validated by transcriptome analysis of paired pre- and post-treatment biopsies, in situ analysis by multiplex IHC and digital pathology, and in vivo study of an immunogenic hepatocellular carcinoma mouse model. Our findings highlight that anti-VEGF therapy might augment antitumor immunity and enhance anti–PD-L1 immunotherapy by targeting VEGF-mediated angiogenesis, Treg proliferation, and myeloid cell inflammation. Furthermore, our study identified candidate biomarkers for predicting response and resistance to anti–PD-L1 and anti-VEGF combination therapy.

  Study EGAS00001005503

• Targeted sequencing of candidate regions on chromosome 22q predisposing to multiple schwannomas

  Constitutional LZTR1 or SMARCB1 pathogenic variants have been found in ~86% of familial and ~40% of sporadic schwannomatosis cases. Hence, we performed massively parallel sequencing of the entire LZTR1, SMARCB1 and NF2 genomic loci in 35 individuals with schwannomas negative for constitutional first-hit pathogenic variants in the LZTR1/SMARCB1/NF2 coding sequences, however with 22q deletion and/or a different NF2 pathogenic variant in each tumor, including six cases with only one tumor available. Furthermore, we verified whether any other LZTR1/SMARCB1/NF2 (likely) pathogenic variant(s) could be found in 16 cases carrying a SMARCB1 constitutional variant in the 3’ untranslated region (3’-UTR) c.*17C>T, c.*70C>T or c.*82C>T. As no additional variants were found, functional studies were performed to clarify the effect of these 3’-UTR variants on the transcript. The 3’-UTR variants c.*17C>T and c.*82C>T showed pathogenicity by negatively affecting SMARCB1 transcript level. Two novel deep intronic SMARCB1 variants, c.500+883T>G and c.500+887G>A, resulting in out-of-frame missplicing of intron 4, were identified in two unrelated individuals. Further resequencing of the entire repeat - masked genomics sequences of chromosome 22q in individuals negative for pathogenic variants in the SMARCB1/LZTR1/NF2 coding- and non-coding regions revealed five potential schwannomatosis-predisposing candidate genes, i.e. MYO18B, NEFH, SGSM1, SGSM3 and SBF1, pending further verification.

  Study EGAS00001005680