516 results for "cancer rna-seq"

in 28.81 milliseconds.

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) to identify bivalently marked genes (H3K4me3 and H3K27me3 ChIP-seq), and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Epigenetic regulation of transcription plays a crucial role in lineage commitment of embryonic stem cells. Promoters of key lineage-specific differentiation genes are found in a repressed bivalent state, having both activating H3K4me3 and repressive H3K27me3 histone marks, making them poised for transcription upon loss of H3K27me3 in response to environmental cues. Whether the tumour-initiating, self-renewing, cancer-initiating cells (C-ICs) have similar epigenetic regulatory mechanism that prevent lineage commitment is unknown. In order to investigate bivalently marked and repressed promoters, we used a patient-derived CC-IC enriched model to identify the changes in transcriptome following inhibition of EZH2, the H3K27 methyltransferase. We also performed ChIP-seq for H3K27me3 and H3K4me3 at baseline in order to identify repressed and bivalently marked promoters.

  Study EGAS00001003003

• Genomic and Immune Profiling of Breast Cancer Brain Metastases

  Previous work has shown that breast cancer brain metastases (BCBrM) can have unique molecular profiles compared to extracranial tumors (ECTs), resulting in some patients demonstrating subtype switching between primary/extracranial tumors and brain metastases. Description of the biology of BCBrM and associations between biological features and clinical outcomes, particularly between molecular intrinsic subtypes, will facilitate the design of rational therapies for patients with BCBrM. To better characterize the molecular profiles of BCBrM, we conducted whole exome sequencing (WES) and total RNA sequencing (RNA-Seq) on BCBrM tissues, regardless of clinical or molecular subtype, obtained from a cohort of 42 patients from Duke University Medical Center. This cohort adds valuable patient samples to the field and enables strengthened investigation of somatic mutations, copy number alterations, gene expression profiles, and immune populations within and between BCBrM patients and other similar cohorts. The Duke BCBrM cohort includes clinical and molecular annotation of the 42 patient specimens and their associated WES and RNA-Seq data. Clinical and molecular (PAM50) intrinsic subtypes in ECTs and brain metastases were largely concordant within patients. There were observed differences in intrinsic subtype calls between frozen and FFPE specimens of the same tissue, with discordance mostly observed with LumB calls. Copy number alterations in chromosomal regions included clinically relevant genes, and somatic alterations were largely conserved within patients across matched samples, with few genes, including TP53, being recurrently altered in the majority of patient specimens. In matched FFPE brain metastasis and ECT samples, we observed differentially expressed genes and pathways that had increased or decreased expression in brain metastasis, including in oxidative phosphorylation and DNA repair. Survival outcomes for patients differed by intrinsic molecular subtypes, with some association between expression of select gene pathways and survival. Data available through dbGaP will be the sequencing data and sample attributes from BCBrM tissues obtained from 42 patients from Duke University Medical Center.

  Study phs003673

• Exploring_the_heterogeneity_of_sarcoma_using_single_cell_sequencing_

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002866

• Transcriptional Profiling of Macrophages In Situ in Metastatic Melanoma Reveals Localization-Dependent Phenotypes and Function

  Therapeutic interventions modulating immune function at the tumor site could improve outcomes in cancer. Here we analyzed metastatic melanoma, a tumor type highly responsive to T-cell based therapies, and found that the tumor-infiltrating T cells are localized closely to CD14+ monocytes/macrophages rather than to melanoma cells. Using novel immunofluorescence-guided laser capture micro-dissection, we analyzed transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages and melanoma cells in non-dissociated tissue. CD14+ cells localized in tumors beds displayed specific transcriptional signatures distinct from CD14+ cells that were localized in tumor stroma.The 8 distinct metastatic melanoma samples are from the Cooperative Human Tissue Network (CHTN). 64 RNA-seq files are available from 16 intraCD14+, 16 stromaCD14+, 16 cancer cells, 8 intraCD3+ and 8 stromaCD3+ cells. 2 LCM harvests were completed for the CD14+ and cancer cells on two sections of the samples. One harvest was done for the CD3+ samples.The processed data (TPM/raw counts tables) are available on GEO under GSE180124. 

  Study phs002564

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• Development of the prevention and therapy of CRC using patient derived culture tissues.

  Tumor tissues consist of functionally heterogeneous cells including those with high clonogenic potential called cancer stem cells (CSCs) which produce differentiated non-tumorigenic progenies. Transplantation assays have been performed to identify cell surface markers in solid tumors including colorectal cancers, which identified several CSC markers such as CD133 and CD44. In addition to the transplantation, the lineage tracing of genetically labelling cells in animal models of cancer qhas been employed to explore the cellular heterogeneity of tumors by identifying the CSCs and its progenies. This approach is particularly useful to investigate solid tumors, where cellular proliferation and differentiation are controlled by niche factors and cell-cell contact with adjacent cells. Lineage tracing of mouse model of cancer unravel the mode of growth of autochthonous tumor in their native environment. In this study, we used patient derived organoids (PDO) established from surgically resected CRC patients to identify the CSC. Single cell RNA-seq analysis identified potential CRC markers, which may exhibit self-renewal activity and produce progenitors

  Study JGAS000139

• single cell RNA-seq of small cell lung cancer circulating tumor cells

  This study investigated the transcriptomic profile of circulating tumor cells from three small cell lung cancer patients. CTCs were enriched from the blood of three SCLC patients using the CTC-iChip followed by magnetic depletion of RBCs. The enriched samples were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system.

  Study EGAS50000001401

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• Epigenome and transcriptome profiling of chronic lymphocytic leukemia patients

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Study EGAS00001001821

• Inferring expressed genes by whole-genome sequencing of plasma DNA

  The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine. cfDNA consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. We performed whole-genome sequencing (WGS) of plasma DNA and identified two discrete regions at transcription start sites (TSS) where the nucleosome occupancy results in different read-depth coverage patterns in expressed and silent genes. By employing machine learning for gene classification we found that the plasma DNA read depth patterns from healthy donors reflected the expression signature of hematopoietic cells. In cancer patients with metastatic disease, we were able to classify expressed cancer driver genes in regions with somatic copy number gains with high accuracy. We could even determine the expressed isoform of genes with several TSSs as confirmed by RNA-Seq of the matching primary tumor. Our analyses provide functional information about the cells releasing their DNA into the circulation.

  Study EGAS00001001754

• Integrative analysis reveals a macrophage-predominant, immunosuppressive immune microenvironment and subtype-specific therapeutic vulnerabilities in advanced salivary gland cancer

  Background Salivary gland cancers (SGC) are rare and heterogeneous malignant tumors. Advanced SGC lack established treatment options and show poor response to immunotherapy. Here, an integrative multi-omics analysis in a large cohort of advanced SGC revealed insights into the tumor immune microenvironment (TIM) and distinct mechanisms of immune evasion. Methods A total of 104 patients with recurrent/metastatic SGC from the DKTK MASTER program were included in this study. Whole-exome or whole-genome sequencing and RNA-sequencing was performed on fresh frozen tumor tissue. The tumor immune microenvironment was analyzed using CIBERSORT deconvolution analysis and immune gene expression scores in bulk RNA-sequencing data. Single-nuclei sequencing and immunohistochemistry analyses were performed in selected samples. Results were validated in bulk RNA-sequencing data of a previously published independent dataset. Results Bulk transcriptome analysis revealed an immune-deserted TIM in the majority of advanced SGC samples. Immune exclusion was most prominent in adenoid cystic carcinoma (ACC) subgroup 1 exhibiting a downregulation of the antigen processing machinery. Only a small subset of advanced SGC, including few adenoid cystic carcinoma, exhibited T-cell inflammation, which was correlated with tumor mutational burden in Non-ACC samples. Subtype specific expression of immune checkpoints as well as cancer testis antigens were identified with prominent expression of VTCN1 in luminal cells within ACC. Single-cell RNA-sequencing and bulk RNA-seq deconvolution analysis validated immune cell exclusion and revealed a TIM that was dominated by M2 macrophages across SGC subtypes. Among evaluable patients treated with immune checkpoint inhibitors, a high T-cell to macrophage ratio was associated with clinical benefit. Conclusions These data support biomarker-based development of immune-checkpoint inhibition and the development of novel immune-checkpoint inhibitors and cellular therapies in SGC.

  Study EGAS50000000809

• Human Pilocytic Astrocytoma Single Cell RNA Sequencing

  Pilocytic astrocytoma (PA), the most common childhood brain tumor, is a low-grade glioma with a single driver BRAF rearrangement. Here, we perform scRNAseq in six PAs using methods that enabled detection of the rearrangement. When compared to higher-grade gliomas, a strikingly higher proportion of the PA cancer cells exhibit a differentiated, astrocyte-like phenotype. A smaller proportion of cells exhibit a progenitor-like phenotype with evidence of proliferation. These express a mitogen-activated protein kinase (MAPK) program that was absent from higher-grade gliomas. Immune cells, especially microglia, comprise 40% of all cells in the PAs and account for differences in bulk expression profiles between tumor locations and subtypes. These data indicate that MAPK signaling is restricted to relatively undifferentiated cancer cells in PA, with implications for investigational therapies directed at this pathway. Note that 931 out of 1234 samples in the Sequence Read Archive (SRA) passed QC and have transcript count data available from the Broad Institute Single Cell Portal. The transcript count data can be found at https://singlecell.broadinstitute.org/single_cell/study/SCP271/pilocytic-astrocytoma-single-cell-rna-seq#study-download

  Study phs001854

• International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

  Oral cavity squamous cell carcinoma (OSCC) is the major subtype (~90%) of oral cancer, which is leading cancer with high mortality worldwide. The environmental risk factors associated with OSCC are quite different in Taiwan as compared to other populations. In most non-Taiwanese populations, OSCC is often associated with tobacco chewing, cigarette smoking, alcohol drinking, or human papillomavirus (HPV) infection. In Taiwan, in contrast, the OSCC occurs mainly in males aged 30 years or older who have habitual betel nut chewing, cigarette smoking, and alcohol drinking. To uncover molecular mechanisms and identify new therapeutic strategies of oral squamous cell carcinoma, this study recruited 112 treatment-naïve OSCC patients and generated multi-omics data, including WES, RNA-Seq, TMT-labeled proteomes, and phosphoproteomes from paired normal/tumor tissues. We have investigated our multi-omics data, covering molecular characterizations such as mutation signatures, impacts of mutations on RNA/protein/phosphoprotein, RNA-protein correlation, somatic copy number alteration, and the relationship with RNA & protein, proteome, and phosphoproteome analysis (T vs NAT), novel peptides (somatic variants, neoantigens, CT antigens, T cell receptors, etc.), as well as molecular subtyping (& pathway analysis). Notably, we have discovered a higher frequency of APOBEC3B deletion polymorphism in the Taiwanese population, and APOBEC3A is a potential prognostic biomarker. Our proteogenomic data enable us to further stratify patients into four groups based on APOBE3A expression level, which is found inversely correlated with EGFR expression. Therefore, the patients with high EGFR and low APOBEC3A expression may benefit from anti-EGFR therapy, while those with low EGFR and high APOBEC3A expression may benefit from immunotherapy. To clarify if there is an interaction between genetic polymorphisms and betel nut chewing habit in Taiwanese OSCC, we plan to concurrently evaluate the effect of habitual betel nut chewing on the gene mutation pattern, the dysregulated protein/phosphoproteins as novel biomarkers and/or therapeutic targets, and the molecular subtyping of patients for effective treatments. 

  Study phs002580

• Case Report: Pre-Clinical Combination Targeting VEGF and PI3K in a Rare, Aggressive Mixed Endometrial Carcinoma

  We report a rare case of a young patient (VENUS 167) initially diagnosed with grade 1 endometrioid endometrial cancer, which, following endocrine treatment, presented with mixed aggressive carcinoma with three distinct histologic patterns: grade 1 endometrioid, large cell neuroendocrine, and undifferentiated carcinoma. The surgical specimen at the time of disease progression was used to establish OPTO.85, a patient-derived organoid (PDO), followed by a corresponding organoid-derived xenograft (ODX). Multi-omic analyses confirmed that OPTO.85 accurately reflected the patient’s tumor characteristics. WES analysis identified oncogenic alterations in PIK3CA, ARID1A, and CTNNB1. Further RNA-seq and ATAC-seq analyses revealed enrichment in VEGF and Wnt signaling pathways, suggesting therapeutic vulnerabilities. A high-throughput drug screen was conducted using ApexBio-Approved and Epigenetic Drug Libraries, along with Kinase Inhibitor and Tool Compound Libraries developed at the Ontario Institute of Cancer Research. The OPTO.85 PDO exhibited sensitivity to PI3K inhibitors and responsiveness to VEGF inhibition. Cediranib demonstrated synergy with BKM120, significantly reducing organoid growth. This combination also showed in vivo efficacy in the ODX model, where dual inhibitors significantly suppressed tumor growth compared to single compounds. This case exemplifies the impact of genomic profiling and patient-derived models in identifying actionable molecular changes in rare cancers with limited therapeutic options and poor prognosis. It highlights that high-throughput sequencing for individual patient tumors and generation of patient-derived models are feasible in endometrial cancer. This preclinical model may assist clinical decision and personalized therapy requiring validation in prospective studies.

  Study EGAS50000001665

• Arriba: accurate and efficient detection of gene fusions from RNA-Seq (H021)

  The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n=803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS. In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results demonstrate Arriba’s utility in both basic cancer research and clinical translation.

  Study EGAS00001003554

• High-coverage whole exome sequence in non-TRU-type lung adenocarcinomas

  In order to elucidate the key genetic events in non-TRU-type lung cancer, we selected 43 non-TRU-type lung adenocarcinomas and performed a whole exome sequence and RNA-seq analysis using a next-generation sequencer. The results of the analysis identified mutations in TP53, KRAS and NKX2-1 as the top three significantly mutated genes, while the EGFR mutation was rare in this cohort. Eight NKX2-1 mutations (5 frameshift, 2 nonsense, and one missense) were identified, with one case harboring two distinct NKX2-1 mutations (missense and frameshift). All NKX2-1 mutants were transcriptionally inactive in reporter assays. Histologically, invasive mucinous adenocarcinomas accounted for most of the NKX2-1 mutations (5 cases), while 1 enteric and 1 acinar adenocarcinoma harbored the NKX2-1 mutation.

  Study JGAS000105

• Data Access Committee for the DNA sequencing data included in the study "Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer".

  A data transfer agreement (DTA), based on the example DTA provided by UZ Gent, is to be filled out by the requester and Multifocal RNA-seq and tNGS data from primary and metastatic tissues of locally advanced and de novo metastatic cohorts - Data Access Committee. https://www.uzgent.be/nl/over-uz-gent/organisatie/data-access-comite/wat-zijn-de-opdrachten-van-het-data-access-comite Coordinator: Muriel Fouquet E-mail: dataaccesscommittee@uzgent.be

  Dac EGAC50000000930

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011193

• Comprehensive single cell study of lung adenocarcinoma from early to metastatic stages

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001005054

• Breast Cancer FRT RNA seq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000338

• Leiomyosarcoma Cancer Transcriptome Sequencing

  RNA-Seq data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 75bp paired-end protocol to a minimum mean reads of 50 million.

  Dataset EGAD00001003192

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program –Sarcoma, Kidney, and Liver Cancers

  The goal was to complete whole exome sequencing (WES) and RNA sequencing (RNA-Seq) on patient derived xenograft samples. Cancer in children is rare with approximately 15,700 new cases diagnosed annually in children 21 years or younger in the U.S. Through use of multimodality therapy (surgery, radiation therapy, and aggressive chemotherapy), 70% of patients will be 'cured' of their disease, and 5-year Event-Free Survival (EFS) exceeds 80%. Consequently, the number of patients that can be enrolled in phase I/II clinical trials is small, and most patients will have been extensively treated, hence drug/radiation resistant. Thus, preclinical studies that accurately translate into effective clinical therapy are an essential component of pediatric drug development. Our group has contributed to studies in the Pediatric Preclinical Testing Program (PPTP) and Pediatric Preclinical Testing Consortium (PPTC) that have led to clinical studies through Children's Oncology Group (COG). Of importance, we have developed and characterized over 330 Patient Derived Xenografts (PDX), developed from tumors both at diagnosis and relapse, that can be used to facilitate pediatric drug development as directed by FDA under the Research to Accelerate Cures and Equity for Children Act (RACE for Children Act).

  Study phs003160

• Cancer and germline exomes, and cancer RNA-seq consisiting of FASTQ paired-end reads from melanoma, lung and colon cancer samples

  Discovery of patient-specific tumor antigens usually requires in vitro-expanded autologous tumor infiltrating lymphocytes (TILs), among which tumor antigen-specific T cells are however often rare, thus limiting sensitivity. We designed in vitro culture conditions to improve the identification of rare tumor antigen-specific CD8 TILs. This innovative yet accessible pipeline allows highly-sensitive identification of tumor antigens and cognate T cell receptors (TCRs), greatly improving the selection of candidates for personalized cancer vaccines and TCR-based cellular immunotherapies.

  Study EGAS00001005513

• RNA-seq analysis of metastatic prostate cancer solid tumor biopsies

  The prevalence and features of treatment-emergent small-cell neuroendocrine prostate cancer (t-SCNC) are not well characterized in the era of modern androgen receptor (AR)–targeting therapy. We sought to characterize the clinical and genomic features of t-SCNC in a multi-institutional prospective study. Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy and were followed for survival. t-SCNC is present in nearly one fifth of patients with mCRPC and is associated with shortened survival.

  Study EGAS00001006369

• Exploration of coding and non-coding variants in cancer using GenomePaint.

  GenomePaint (https://proteinpaint.stjude.org/genomepaint) is a dynamic visualization platform for whole-genome, whole-exome, transcriptome, and epigenomic data, featuring a novel design that captures the inter-relatedness between DNA variations and RNA expression. Regulatory non-coding variants can be inspected and discovered along with coding variants, and their functional impact further explored by examining 3D genome and/or ChIP-seq data generated from cancer cell lines. Further, GenomePaint correlates mutation and expression patterns with patient outcomes, and can display external data such as adult cancer datasets and user-provided custom tracks. We used GenomePaint to analyze multi-omics data from 3,652 pediatric cancers representing 16 histotypes, and demonstrate the visualization features through examples, including two that led to new insights into oncogenic mechanisms in pediatric cancer. The first is the discovery of a new class of pathogenic recurrent variants that cause aberrant splicing, disrupting the RING domain of CREBBP, a driver gene frequently mutated in relapsed pediatric leukemia. The second is the cis-activation of the MYC oncogene in a subset of B-lineage acute lymphoblastic leukemia (B-ALL) via duplication of the NOTCH1-MYC enhancer (N-ME), previously discovered only in T-lineage ALL. The regulatory impact of N-ME enhancer amplification was initially confirmed by allelic imbalance in published gene expression and ChIP-seq data and verified by additional Capture-C and fluorescence in situ hybridization data generated by follow-up experiments. These examples demonstrate the power of GenomePaint in enabling not only data visualization but also integrative genomic analysis that can lead to novel biological insight for follow-up experimental validation.

  Study EGAS00001004669

• Microbiome-Host Interactions in Oral Squamous Cell Carcinoma: a Metatranscriptomic Exploratory Study

  Oral cancer (predominantly squamous cell carcinoma; OSCC) is the 14th most prevalent malignancy worldwide, accounting for more than 300,000 new cases and 145,000 deaths annually. Despite advances in cancer treatment modalities, OSCC continues to have poor prognosis with 5-year survival rates less than 50%. Although use of tobacco and alcohol consumption constitute the major risk factors, there is emerging evidence for the role of the microbiome in OSCC. However, studies on the association between the microbiome and OSCC has so far focused on compositional analysis and has been largely limited to the bacterial component of the microbiome. The aim of this study is to characterize the transcriptional activity (function) as well as composition of the multi-kingdom microbiome associated with OSCC and correlate it with the gene expression of the host using ultra-deep metatranscriptome sequencing, which will provide new insight into the role of the microbiome in OSCC and the possible mechanisms by which the tumor’s microbial community may influence on its behavior. This project comprises RNA-Seq data from twenty OSCC tumor/normal tissue pairs and twenty tongue scraping samples from healthy controls. However, due to consent constraints, the human sequences from the control data are filtered out.

  Study phs002678

• Evolutionary Analysis of Chronic Lymphocytic Leukemia Cells During Relapse After Allogeneic Hematopoietic Stem Cell Transplant

  We investigated the molecular dynamics driving relapse of chronic lymphocytic leukemia (CLL) following allogeneic hematopoietic stem cell transplant (allo-HSCT) through an integrated analysis of whole exome, bulk transcriptome, bulk methylome and single cell transcriptional data from paired leukemic samples representing 19 patients. We found that their clinical kinetics corresponded to distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are distinct from those imposed by chemotherapy.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out ribosome profiling (Ribo-seq) and RNA-sequencing on CLL samples and isolated primary B cells from healthy donors. We discovered novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001998

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

  Study EGAS00001005066

• Luminal progenitor cell line iHBEC(CD117)

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

  Dataset EGAD50000000723

• The Role of E2F4 in Controlling Resistance to Irinotecan (CPT-11) in Human Colon Cancer

  This study reports the results of RNA sequencing (RNA-seq) experiments performed on three isogenic clones of the human HT29 colon cancer cell line, genetically engineered to achieve the selective inactivation of the adenovirus early 2 (E2) gene transcription factor 4 (E2F4) protein, a key functional component of the multimeric transcriptional repression complex known as the dimerization partner (DP), retinoblastoma-like (RB-like), E2F and multi-vulva class B (MuvB) complex (DREAM). In previous studies, we identified E2F4 as a key regulator of colorectal cancer (CRC) resistance to irinotecan (CPT-11), a cytotoxic agent that stands at the backbone of multiple chemotherapy regimens for the treatment of metastatic CRCs. The molecular mechanisms linking E2F4 to irinotecan resistance, however, remain poorly understood. The present study was designed to identify which genes are under the transcriptional control of E2F4, either at baseline or following exposure to SN38 (i.e., the active metabolite of irinotecan, generated in vivo by biotransformation in the liver) in order to clarify the role played by E2F4 in shaping colon cancer resistance to chemotherapy. The cell line used for this study (HT29) is aneuploid and contains three copies of the E2F4 gene, because of a trisomy of chromosome 16, where the E2F4 gene is located (Kawai et al., Genes, Chromosomes & Cancer, 34:1-8, 2002; PMID: 11921276). HT29 cells were infected with lentivirus vectors encoding for CRISPR/Cas9 constructs designed to selectively inactivate the E2F4 gene, using three distinct guide-RNAs (gRNAs), each targeting a different sequence within the proximal exons of the E2F4 gene (exon 1, exon 2). Lentivirus-infected cells were sub-cloned by single-cell fluorescence-activated cell sorting (FACS), based on the differential expression of a fluorescent reporter (EGFP) expressed in tandem with the gRNAs. Isogenic clones (EGFP+) were then screened to identify those with a tri-allelic knock-out, as revealed by both genetic sequencing of the E2F4 gene (revealing the presence of three distinct frameshift mutations) and Western blot (revealing complete loss of E2F4 protein expression). The study includes twelve (n=12) RNA-seq experiments, representative of 3 experimental replicates (i.e., three distinct isogenic clones of the HT29 cell line, each displaying complete loss of E2F4 expression) and 3 negative controls (i.e., three independent preparations of the parent HT29 cell line, infected with a lentivirus vector encoding for a non-targeting gRNA) exposed to 2 distinct in vitro cell culture conditions: a) treatment with SN38 resuspended in dimethyl sulfoxide (DMSO); or b) treatment with DMSO alone (negative control). The in vitro treatment regimen used for SN38 (32 nM, 24 hours) was designed so that the exposure to SN38 experienced in vitro by HT29 cells would mirror the exposure to SN38 experienced in vivo by malignant tissues, as measured, for example, in metastatic CRC patients receiving a standard dose of irinotecan (180 mg/m2) administered by intravenous infusion over 90 minutes (Deyme et al., Cancer Chemotherapy and Pharmacology, 88:247-258, 2021; PMID: 33912999).

  Study phs003560

• 10x genomics single cell RNA-seq and ATAC-seq from 10 pre-menopausal patients fimbriae and ampullary part of the fallopian tube

  The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.

  Study EGAS50000000628

• UROMOL 2020 - RNA-seq data

  The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters.

  Study EGAS00001004693

• Single MII oocyte mRNA expression from women

  This dataset contains 14 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from ovarian tissue from unstimulated patients undergoing fertility preservation treatments due to cancer diagnoses, which did not influence ovarian function. Cumulus-oocyte-complexes were matured in vitro according Gruhn et al (Science 365: 1466-1469) and short term flash frozen prior to lysis, RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina

  Dataset EGAD00001005971

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• ProstOmics - Spatial Transcriptomics

  Spatial transcriptomics data (ST) from 32 human prostate tissue samples originating from 8 prostate cancer patients (5 patients with post-surgery relapse). The ST data was acquired using the Visium Spatial Gene Expression kit which resulted in over 20 000 spatially defined spots for the 32 tissue samples. The raw transcriptomics data is RNA-seq. The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Each ST spot has metadata such as sample origin, histology class (stroma, normal epithelium, cancer of various grading etc), number of cells and estimated cell type fractions. Patient metadata include information of age at surgery, time (months) until reported relapse, total follow-up time, pre-surgery PSA, post-surgery T-stage and metastasis status.

  Dataset EGAD50000000603

• Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

  Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, and integrative models using DNA and RNA have improved predictions of clinical benefit. However, identification of immune and tumor-intrinsic features in models using DNA or RNA alone have not been comprehensively explored in melanoma. In this study, we sequenced DNA and RNA of tumors from 67 melanoma patients receiving CPB, and aggregated this cohort with previously published data, yielding whole exome sequencing (WES) data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences, and found that melanoma patients with high TMB and either high TCB or high BCB survived longer and had higher response rates, as compared to patients with low TMB and either low TCB or low BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes which are associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs which are associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Gene ID: 11184) and the transcription factor TBX3 (Gene ID: 6926) which is overexpressed in poorly differentiated melanomas. We concluded that RNA-based (MAP4K1 and TBX3) or DNA-based (TCB and TMB) models combining with immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

  Study phs002683

• Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

  Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we found a significant B cell association with extended OS with PD-L1 blockade, independent of CD8+ T cell signals. We then derived gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA-seq data. Importantly, we found increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B cells were also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to PD-L1 blockade efficacy in NSCLC.

  Study EGAS00001005013

• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

  The Office of Cancer Genomics at the National Cancer Institute sponsored a series of studies as part of the Cancer Genome Characterization Initiative (CGCI) to assess novel emerging sequencing technologies in cancer. The CGCI program included comprehensive characterization of the genetic aberrations found in different pediatric and/or adult tumors. CGCI characterized a number of B-cell non-Hodgkin lymphomas (including diffuse large B-cell lymphoma (DLBCL) from patients with and without HIV+ infection, follicular lymphoma (FL), as well as adult and pediatric Burkitt lymphomas), and additional HIV-associated tumors (including DLBCL, lung, and cervical cancers). All data from these projects is available at the NCI Genomic Data Commons. Individual project descriptions are available by disease on the substudy pages (links are included at the top of this page). Brief summaries are as follows: Non-Hodgkin Lymphoma (NHL) - CGCI investigators probed genomic alterations more deeply than had previously been possible by using state-of-the-art RNA sequencing (mRNA-seq) and whole genome shotgun sequencing (WGS) coupled with leading edge bioinformatics, data management and analysis approaches. The project sequenced tumor DNA and/or RNA from 117 NHL tumor samples and 10 cell lines. This included the genomes or exomes of 1 Follicular Lymphoma (FL) and 13 diffuse large B-cell lymphoma (DLBCL) cases, all with matched constitutional DNA sequenced to comparable depths, RNA-sequencing (mRNA-seq) of 92 DLBCL, 12 FL and 8 B-cell NHL cases with other histologies and 10 DLBCL-derived cell lines. The DLBCL cases and cell-lines are from the two major subtypes of DLBCL: germinal center B-cell (GCB) and activated B-cell (ABC). HIV+ Tumor Molecular Characterization Project (HTMCP) - This project was a joint effort of the Office of Cancer Genomics (OCG) and the Office of HIV and AIDS Malignancy (OHAM). Its goals were to characterize HIV-associated cancers (obtained from HIV-infected patients) and compare them to the same types of cancers from patients without HIV infection. Investigators performed 30X genome sequencing of 100 cases of paired tumor and germline DNA, along with transcriptome sequencing in each of 3 types of HIV+ tumors (DLBCL, lung and cervical cancers). These platforms allow discovery of mutations both in coding and non-coding genomic regions, gene expression and genomic alterations (including translocations, insertions and deletions). Comparing tumors of cancer patients both with and without HIV-infection provides insight into the potential function of this virus in certain cancers. Burkitt Lymphoma Genome Sequencing Project (BLGSP) - This project was a collaborative effort between the National Cancer Institute and the Foundation for Burkitt Lymphoma Research to develop a databank of the many alterations found in Burkitt lymphoma (BL), an uncommon type of Non-Hodgkin lymphoma that occurs most often in children and young adults. The goal of the BLGSP was to explore potential genetic changes in patients with BL that could lead to better prevention, detection and treatment of the cancer. The project characterized the alterations of the tumors' genomes (with matched normal as control) and transcriptomes by sequencing the DNA and RNA of each case. Using the data generated, the ultimate goals of the project was to discover the molecular changes that are present in BL patients and then determine how those changes correlate with treatment regimen and outcome. CGCI data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the CGCI Publication Pages at the GDC (Please see the "Supplemental Links" section of any CGCI publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original CGCI research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data), as well as higher level data generated by the GDC. Please see the CGCI Use and Publication Guidelines for updated details on the sharing of any CGCI substudy data, including how to cite CGCI.To learn more about the CGCI studies, please visit the CGCI Program website.

  Study phs000235

• Molecular profiling of tissue autopsies and ctDNA

  The dataset contains high-throughput sequencing data derived from a cancer autopsy series of 10 patients. As part of this study, whole-exome sequencing and RNA-seq were performed for spatially distinct tissue biopsies from the patients. In addition, plasma samples from the patients were sequenced using a custom panelt to profile ctDNA. There are 106 files containing whole-exome sequencing data, 107 files containing RNA-seq data, and 9 files containing plasma sequencing data.

  Dataset EGAD00001007040

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• Ipilimumab and Decitabine in Treating Patients With Relapsed or Refractory Myelodysplastic Syndrome or Acute Myeloid Leukemia

  The NCI Experimental Therapeutics Clinical Trials Network (ETCTN)/Cancer Therapy Evaluation Program (CTEP) 10026 study (NCT02890329) tested combined ipilimumab and decitabine treatment in two cohorts: Arm A consisted of patients with relapsed acute myeloid leukemia (AML) after allogeneic hematopoietic stem cell transplantation. Arm B consisted of patients with advanced myelodysplastic syndrome (MDS) or AML that did not previously undergo stem cell transplantation. During the study, peripheral blood and bone marrow samples were obtained from study participants at study entry (screening), following the first lead-in cycle of decitabine monotherapy, during combined treatment with decitabine and ipilimumab, and at the end of treatment.This study tested the combination of the CTLA-4 blocking antibody ipilimumab and the DNA methyltransferase inhibitor decitabine in advanced myeloid disease in the transplant-naive and post-transplant context. The samples were used for bulk and single cell RNA sequencing (scRNA-seq) as well as whole exome sequencing (WES).

  Study phs003015

• Spatial Transcriptomics Uncovers Tumor Microenvironment-Based Subtypes in Invasive Lobular Carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer (BC); however, little is known about its tumor microenvironment (TME). Here, we investigated the spatial architecture of 43 hormone-receptor-positive, HER2-negative (HR+/HER2-) primary ILC samples, using spatial transcriptomics and detailed morphological annotation. By integrating morphology, spatial, and single-cell data, we mapped TME-related cell types, exploring their proximity to tumor cells and their enrichment in specific compartments. Clustering of spatial transcriptomics spots revealed significant inter- and intra-tumor heterogeneity, identifying pathways and cell types linked with disease outcomes. Morphological and gene expression data were finally integrated with a multimodal approach, leading to the identification of 4 new ILC subtypes based on TME heterogeneity. By using derived, specific gene expression signatures, these subtypes were identified and validated in external bulk RNA-seq/microarray datasets (SCAN-B and METABRIC), where differences in prognosis emerged.

  Study EGAS50000001001

• Systematic kinase inhibitor profiling identifies CDK9 as a synthetic lethal target in NUT midline carcinoma

  Kinase inhibitors represent the backbone of targeted cancer therapy, yet only a limited number of oncogenic drivers are directly druggable. By interrogating the activity of 1,505 kinase inhibitors we found that BRD4-NUT-rearranged NUT midline carcinoma (NMC) cells are specifically killed by CDK9 inhibition (CDK9i) and exhibit a unique dependency on CDK9 and Cyclin-T1 expression. We show that CDK9i leads to robust induction of apoptosis and of markers of DNA damage response in NMC cells. While both CDK9i and bromodomain inhibition over time result in reduced Myc protein expression, only bromodomain inhibition induces cell differentiation and a p21-induced cell cycle arrest in these cells. Finally, RNA-Seq and ChIP-based analyses reveal a BRD4-NUT specific CDK9i-induced perturbation of transcriptional elongation. Thus, our data provide a mechanistic basis for the genotype-dependent vulnerability of NUT midline carcinoma cells to CDK9i that may be of relevance for the development of targeted therapies for NMC patients.

  Study EGAS00001002588

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• Exome-seq, RNA-Seq, SNP array profiling of gastric tumor samples and cell lines.

  Gastric cancer is the second leading cause of worldwide cancer mortality, yet the underlying genomic alterations remain poorly understood. Here we performed exome and transcriptome sequencing and SNP array assays to characterize 51 primary gastric tumors and 32 cell lines. Meta-analysis of the exome data and previously published data sets revealed 24 significantly mutated genes in MSS tumors, and 16 in MSI tumors. More than half of the patients in our collection could potentially benefit from targeted therapies. We identified 55 splice-site mutations accompanied by aberrant splicing products, in addition to mutation-independent differential isoform usage in tumors. The ZAK kinase isoform TV1 is preferentially upregulated in gastric tumors and cell lines relative to normal samples. This pattern is also observed in colorectal, bladder, and breast cancers. Overexpression of this particular isoform activated multiple cancer-related transcription factor reporters, while depletion of ZAK in gastric cell lines inhibited proliferation. These results reveal the spectrum of genomic and transcriptomic alterations in gastric cancer, and identify isoform-specific oncogenic properties of ZAK.

  Study EGAS00001000736

• On-target mutations confer resistance to WRN helicase inhibitors in Microsatellite Unstable Cancer Cells

  This study investigates genetic dependencies and resistance mechanisms to Werner helicase inhibitors (WRNi) in microsatellite-unstable (MSI) cancer models. To define determinants of WRN dependency and acquired resistance, we performed genome-wide CRISPR-Cas9 knockout screens, CRISPR base-editing mutagenesis screens targeting WRN, targeted sequencing of resistance-associated variants, bulk RNA sequencing, and whole-genome sequencing. The datasets deposited in EGA comprise raw sequencing files from CRISPR-Cas9 knockout screens, CRISPR base-editing screens, targeted DNA sequencing, RNA-seq experiments, and whole-genome sequencing of parental and drug-treated cell populations, including models with spontaneously acquired resistance. These data enable investigation of WRN synthetic lethality, genetic modifiers of WRNi response, and genomic alterations emerging under selective pressure.

  Dataset EGAD00001015822

• Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

  Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

  Study EGAS00001003753

• Genomic Profiling of Pediatric B-cell Acute Lymphoblastic Leukemia

  Pediatric leukemia is the most common type of childhood cancer and, despite tremendous progress in treatment, remains the second leading cause of cancer deaths in children. B-cell acute lymphoblastic leukemia (B-ALL) is the most common type of pediatric leukemia. Recent studies using transcriptional profiling of large cohorts of pediatric B-ALL have shown that patients can be grouped into transcriptional subtypes that are often defined by specific driver mutations. Interestingly, many of these mutational subtypes are defined by gene fusions or rearrangements that drive altered expression of transcription factors (ETV6-RUNX1, PAX5, DUX4, TCF3-PBX1, ZNF384) or in chromatin regulatory machinery (KMT2A), suggesting that transcriptional dysregulation is a major driver of B-ALL. While the transcriptional distinctions are clear, the relationship between patients in terms of their chromatin regulatory landscape remains unclear. To address this, we profiled gene expression, open chromatin, and 3D genome folding in patient derived B-ALL samples. We identified that at the level of 3D genome organization, many chromatin interactions and looping events are shared across mutational subtypes, suggesting that shared transcriptional programs, in addition to group specific driver mutations, possibly regulate the chromatin landscape in B-ALL. Using RNA-seq and ATAC-seq data, we were able to identify "latent" signatures of expression related to non-mutant transcription factors (TFs) that also contribute to expression heterogeneity across TF subtypes. These are related to patient specific patterns of 3D genome folding, and in some cases, are predictive of disease outcomes. This study helps shed light on the chromatin landscape in B-ALL and furthers our understanding of the interactions between diverse mutant TFs that drive B-ALL and non-mutant TFs that help shape the B-ALL chromatin landscape.

  Study phs003226