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• Single Cell Dissection of the Tumour Microenvironment Reveals Dynamic Interplay Shaping the Tumour Immunity Continuum in Ovarian Cancer

  Diverse tumour immune phenotypes with distinct T cell infiltration patterns result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these phenotypes remain elusive. Here, we provide a high-resolution dissection of the tumour microenvironment representative of different tumour immune phenotypes. By performing single-cell RNA sequencing (scRNAseq) of the tumour, immune, and stromal compartments from 15 ovarian cancer patients, we characterized the diverse cellular and functional phenotypes, as well as dynamic interplay within and between these components. Infiltrated and excluded tumours markedly differed from desert tumours in several tumour cell intrinsic features, including high interferon response, antigen presentation and oxidative phosphorylation. Moreover, these tumours were characterized by tumour associated macrophage (TAM)-like myeloid subsets, while desert tumours were enriched in myeloid derived suppressive cell (MDSC)-like myeloid subsets. Infiltrated and excluded tumours differed in their T cell composition and fibroblast subsets. While dysfunctional CD8+ GZMB T cells and IL1-activated fibroblasts (IL1 CAFs) were associated with infiltrated tumours, pre-dysfunctional CD8+ GZMK T cells and TGFB-activated fibroblasts (TGFB CAFs) were enriched in excluded tumours. These findings validated in bulk transcriptomic profiles of 1071 ovarian tumours and using in situ hybridization. Furthermore, our study revealed chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumour cell-T cell crosstalk via a CXC16-CXCR6 axis, stromal-immune cell crosstalk via CXCL12/14-CXCR4 signalling, and TAM-like macrophage-T cell crosstalk through CXCR3-CXCL9/10/11 signalling. Our in-depth characterization of the tumour environment and intercellular interactions provides novel insights into potential molecular mechanisms that shape the distinct biology of tumour immune phenotypes. Our findings may inform novel therapeutic strategies for potentially shifting tumours along the immunity continuum to improve clinical benefit from cancer immunotherapies.

  Study EGAS00001004935

• OxyTarget mtDNA seq

  We studied 44 rectal cancer patients enrolled onto a prospective population-based biomarker study, who were planned for curative-intent radiation therapy before definitive surgery, yet at high risk of metastatic progression beyond the pelvic cavity. The patients had full-length mtDNA sequencing of whole blood (WB) and peripheral blood mononuclear cells (PBMC), sampled at the time of diagnosis. Metastatic events were recorded up to 60 months of follow-up after completion of the multimodal treatment.

  Dataset EGAD00001007992

• Psoriatic_arthritis

  This is a pilot single cell mRNA sequencing experiment to study immune cells in psoriatic arthritis.

  Study EGAS00001002104

• Benchmarking_CRISPR_Whole_genome_Drop_out_Screen___B_S

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries.

  Study EGAS00001002931

• Canadian prostate cancer samples (CPC-GENE) for PanProstate study

  CPC-GENE has sequenced the genomes of 350 intermediate risk prostate cancers to identify genetic signatures that differ in cancers that responded well to treatment compared with those that did not. CPC-GENE also has sequenced multiple regions of prostate cancer from the same gland to determine if and how the genetic make-up of prostate cancer varies within an individual man’s prostate

  Study EGAS00001003037

• Patient tumour data (RNAseq, WGBS, ChIPseq, WGS)

  Content: 60 GB patient tumours and 4 normal brain samples combined in pairs by region (x2=8 total input samples). RNAseq: 1 lane per sample, total strand-specific rRNA-depleted (normal samples were combined = 2 lanes/samples per brain region). WGBS: 2 lanes per sample (normal samples were combined = 2 lanes/samples per brain region). ChIPseq (histone mark): a subset of 20 GB samples were profiled. For the same modification were multiplexed and sequenced on 4 lanes each (H3K27ac, H3K4me1) or a single lane (all others). WGS: used as matching input control for the 20 ChIPseq samples. Data type and technology: RNA-seq: PE 100bp sequenced on HiSeq2000. WGBS: PE 100bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000. WGS: PE 150bp sequenced on HiSeq X.

  Dataset EGAD00001005492

• RNAseq of GEPARSIXTO

  294 formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer’s protocol (Promega 9FB167). 279 total RNA sequencing libraries were prepared at TGL using a Bravo Automated Liquid-Handling Platform (Agilent G5562A) and the TruSeq Stranded Total RNA Library Prep Gold Kit (Illumina 20020599) following the manufacturer’s protocol (Illumina 1000000040499). RNAseq library quality and quantity were measured using a TapeStation 4200 (Agilent G2991AA) and Qubit 3.0 fluorometer (Life Technologies Q33216), pooled at equal molar ratios, and denatured following the manufacturer’s protocol (Illumina 1000000106351). 271 total RNA sequencing libraries were sequenced at TGL on NovaSeq 6000 (Illumina 20012850) S4 flow cells (Illumina 20028313) following the manufacturer’s protocol (Illumina 1000000019358) using a 2x50 bp paired-end configuration and pool sizes of 91 libraries to target a read depth of 110 million clusters per library on average.

  Dataset EGAD00001010201

• BAM files from whole-genome sequencing of 3 agressive B-cell lymphoma tumour and non-tumor samples

  This dataset contains BAM files from whole-genome sequencing (WGS) of 3 agressive B-cell lymphoma tumour samples for cases 1, 6, and 7 as well as the corresponding non-tumor whole-genome sequencing BAM files.

  Dataset EGAD50000000800

• Colorectal organoids and tumoroids - pulldown (2018-08-13)

  Targeted capture of cancer gene panel bait set in single cell derived organoids from colon tissue and colorectal cancer from 1 patient. . This dataset contains all the data available for this study on 2018-08-13.

  Dataset EGAD00001004292

• Whole-exome sequencing of additional thyroid disease cases (2015-08-05)

  Whole-exome sequencing of a cohort of families (probands and affected/unaffected relatives) suffering from one of two rare thyroid disorders: congenital hypothyroidism (CH) and resistance to thyroid hormone (RTH). This dataset contains all the data available for this study on 2015-08-05.

  Dataset EGAD00001001460

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 1.

  Dataset contains Exome sequencing data (aligned and base quality score recalibrated BAM files) for 236 tumor samples + matched normal from blood, collected from 21 patients with adult diffuse glioma. The majority of these samples were spatially-mapped during sample collection, enabling the genomic information derived from them to be mapped in 3D space.

  Dataset EGAD00001005221

• analysis of the off target effect after Prime editing in IPSC line KCNQ2 R201C. Comparison of parental KCNQ2 R201C with two corrected clonal lines.

  Short read whole genome sequencing analysis of the off target effect after Prime editing in IPSC line KCNQ2 R201C. Comparison of parental KCNQ2 R201C with two corrected clonal lines (3samples in total). Dataset contains CRAM files and VCF files for the respective samples.

  Dataset EGAD00001010904

• cfDNA sWGS BAM — Healthy donors

  Paired-end shallow whole-genome sequencing (sWGS) of plasma cfDNA from healthy donors recruited at EFS Montpellier (France). Libraries: DSP (NEBNext Ultra II) and/or SSP (IDT/Swift Accel-NGS 1S Plus). Sequencing by IntegraGen (France, 2022–2024). Reads aligned to GRCh38 (hg38 canonical) with BWA-MEM; BAMs coordinate-sorted and indexed; submission contains primary mapped reads only (unmapped/secondary/supplementary/duplicates removed; typical filter “-F 3332”, MAPQ threshold as noted in analysis records). Each BAM/BAI pair is linked to its Sample and Experiment. Data Use: controlled access.

  Dataset EGAD50000001880

• Whole-genome and single-cell sequencing of lethal metastatic castration resistant prostate cancer

  Contains a total of 9 patients with whole-genome sequencing of 30 tumours or germline samples, 10X single-cell multiome RNA-seq + ATAC-seq of 24 tumours, 10X 5' single-cell RNA-seq of 10 tumours, and snPATHO-seq of 2 primary tumours. All single-cell experiments have matched whole-genome sequencing. When matched tumour (and germline) whole-genome sequencing is missing, it can be found under EGAS00001006598.

  Dataset EGAD50000001869

• RNA-sequencing of ex vivo exhausted human antigen-specific T cells

  Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level. Four human healhy donor CD8+ T cells were isolated, transduced with an NY-ESO-1 TCR lentivirus construct, stimulated in four different conditions (Trested, Ttumor, Tex, Teff) with T2 tumor cells and specific peptides over 12 days. Cells were then sorted for TCR Vbeta 13.1+ (NY-ESO-1 TCR) CD8+ CD3+ CD56- CD4- DAPI- cells. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode (2x51bp) on 2 lanes of an Illumina NovaSeq 6000 flow-cell. FASTQ sequence files were generated with the Illumina RTA version 3.4.4 and Base-calling Version bcl2fastq-2.20.0.422.

  Dataset EGAD00001009754

• Multi-Omic Profiling of Glioma Patient Tumors and Patient-Derived Model Systems

  We have created a resource of transcriptomic (RNAseq), genomic (whole-exome seq), and lipidomic (untargeted shotgun) profiling data from over 175 molecularly diverse glioma tumors and derivative models in orthotopic mouse xenografts and gliomasphere cultures from over 110 unique patient tumor lines. Provided in this dataset are matched bulk RNA and whole-exome paired-end sequencing data from resected gliomas and derived model systems performed on Illumina HiSeq and NovaSeq sequencing instruments. This comprehensive dataset powers multiple studies aiming to derive molecular signatures of intertumoral heterogeneity and perturbation responses in glioma. Through integrative multi-omic analyses in Minami, et al., 2023, PMID: 37236196, we identified that CDKN2A deletion remodels the GBM lipidome and consequently primes CDKN2A-deleted tumors for ferroptosis. Lipidomics data related to this study are publicly available here. In another study, we used a combination of molecular profiling and functional profiling of apoptotic potential to stratify patients into groups with differential vulnerability to the current standard-of-care in gliomas, and in combination with drugs targeting intrinsic apoptosis, largely informed but not limited to TP53 mutation status.

  Study phs003286

• XClone for analyzing somatic copy number alterations

  Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

  Study EGAS00001007854

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (WG) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastectomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. 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 women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005922

• Predictor_RIO_TNBC (2019-04-03)

  In this study, samples fom a window study of the PARP inhibitor rucaparib in patients with primary triple negative or BRCA1/2 related breast cancer (RIO trial) will be investigated. Samples will undergo whole genome sequence and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004894

• Wilms Tumour organoid sequencing WGS (2019-09-05)

  This study investigates the genomic and transcriptomic characteristics of Wilm's tumour organoids . This dataset contains all the data available for this study on 2019-09-05.

  Dataset EGAD00001005312

• Sequencing of patient samples who received immune checkpoint inhibition - WES - NKI (2019-08-07)

  DNA and RNA isolated from FFPE blocks of patients who received immune checkpoint inhibition (ICI) are sequenced with the aim to identify therapeutically tractable vulnerabilities in tumors to prevent ICI resistance. . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005235

• WGS data for 67 patient cohort

  This dataset includes WGS data of samples from our paper titled "Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: The PLANET study." (National Science Review, nwab192. https://doi.org/10.1093/nsr/nwab192)

  Dataset EGAD00001008647

• RNA-seq data for 67 patient cohort

  This dataset includes RNA-seq data of samples from our paper titled "Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: The PLANET study." (National Science Review, nwab192. https://doi.org/10.1093/nsr/nwab192)

  Dataset EGAD00001008648

• Tumor Educated Platelets (TEPs) for breast cancer detection

  The TEP dataset consists of 549 Fastq samples which are divided into two experiments: a training data cohort, used to train the classifier, and a validation data cohort, used to assess classifier performance

  Dataset EGAD00001009790

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287