7262 results for "canc*"

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• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  This dataset consists of RNA-seq CRAM raw-data files of 1063 primary colorectal cancer and 120 adjacent normal tissue samples. The expression profiles for these samples can be found at the ArrayExpress with accession number E-MTAB-12862.

  Dataset EGAD50000000169

• WES and RNAseq dataset

  This dataset includes WES and RNAseq for 7 patients with metastatic melanoma (4), non-small cell lung adenocarcnioma (1), cervix adenocarcinoma (1), and Epidermoid nasophaeyngeal carcinoma (1), enrolled in phase I clinical trials (NCT03475134m NCT04643574 and NCT05195619). WES was performed on matched cancer and healthy tissues, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 4000/6000 and Illumina NextSeq 500/550 systems.

  Dataset EGAD50000000337

• Whole genome and transcriptome sequencing of cancer of unknown primary tumours

  Whole genome and transcriptome sequencing of cancer of unknown primary tumours was used to determine yield of clinical biomarkers for a molecular guided trial or for resolving cancer type of origin. This study includes profiling of germline DNA and tumour DNA and RNA by whole genome and transcriptome sequencing. All samples are in BAM format aligned with GRCh38 reference genome. This dataset includes: 1. Whole genome sequencing (WGS) of 78 cancer of unknown primary tumour samples and 73 matched germline DNA. 2. Whole transcriptome sequencing (WTS) of 69 cancer of unknown primary tumour samples (matched to WGS cases) 3. Whole genome sequencing of 22 cell-free DNA samples from cancer of unknown primary patients and matched Germaine DNA(8 samples matched to tumour WGS)

  Dataset EGAD50000000656

• Non-KMT2Ar infant Acute Lymphoblastic Leukemia Sequencing

  Integrated genomic analysis of non-KMT2A rearranged infant ALL reveals clinically relevant alterations and common disease origins with childhood ALL. Whole genome and whole transcriptome sequencing from 21 infant ALL patients with no matched normal DNA sequencing.

  Study EGAS50000000405

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  Colorectal cancer (CRC) is caused by a sequence of somatic genomic alterations affecting driver genes in core cancer pathways1. To understand the functional and prognostic impact of cancer-causing somatic mutations, we analysed the whole genomes and transcriptomes of 1,063 primary CRCs in a population-based cohort with long-term follow-up. This study constitutes the largest integrated genome and transcriptome analysis of CRC to date, and links mutations, gene expressions and patient outcomes.

  Study EGAS50000000124

• Plasma mutation profile of precursor lesions and colorectal cancer using the Oncomine Colon cfDNA Assay

  Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. Early detection of precursor lesions or early-stage cancer could hamper cancer development or improve survival rates. Liquid biopsy, which detects tumor biomarkers, such as mutations, in blood, is a promising avenue for cancer screening. To assess the presence of genetic variants in plasma cell-free tumor DNA from patients with precursor lesions and colorectal cancer using the commercial Oncomine Colon cfDNA Assay. Cell-free DNA (cfDNA) samples from the blood plasma of 52 Brazilian patients were analyzed. Eight patients did not have any significant lesions (five normal colonoscopies and three hyperplastic polyps), 24 exhibited precursor lesions (13 nonadvanced adenomas, ten advanced adenomas, and one sessile serrated lesion), and 20 patients with cancer (CRC). The mutation profile of 14 CRC-associated genes were determined by next-generation sequencing (NGS) using the Oncomine Colon cfDNA Assay in the Ion Torrent PGM/S5 sequencer.

  Dataset EGAD50000000679

• Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

  Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

  Study EGAS50000000470

• EC IO Data Access Committee UMCG

  Endometrial Cancer Immuno-Oncology DAC UMCG

  Dac EGAC50000000334

• Breast Cancer bulk RNA-Seq Dataset

  Bulk RNA-Sequencing of 18 primary breast cancers from Wu et al. (2021) study.

  Dataset EGAD50000000649

• DIAMOND PCR : plasma DNA LINE-1 targeted bisulfite sequencing, a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Dataset EGAD50000000646

• TSO500 STJAN33, BRAF mutated CUP

  The data set contains FASTQ files (filetype) of a NEXTSEQ550DX run (instrument). De FASTQ files are from DNA and RNA sample. The Library prep is a NGS TSO500 library prep (Illumina) (technology). A Study to Examine the Clinical Value of Comprehensive Genomic Profiling Performed by Belgian NGS Laboratories: a Belgian Precision Study of the BSMO in Collaboration With the Cancer Centre (BALLETT) This 2-year study involves the consortium of 9 cooperating Belgian NGS laboratories and will enroll 936 metastatic or locally advanced cancer patients coming from 13 different Belgian hospitals and cancer centers. Upon inclusion, all cancer patients will be offered 'comprehensive genomic profiling' (CGP) using Illumina's TSO500 NGS panel. This targeted NGS panel of 523 genes allows for the detection of single nucleotide variants, small indels, copy number variations and fusions, as well as for the determination of the 'tumor mutational burden' (TMB) and the 'microsatellite-instability' status (MSI). Both the wet lab execution of the CGP as well as the biological and clinical classification of the variants will be performed in a fully standardized way among the 9 participating Belgian local NGS laboratories.

  Dataset EGAD50000000689

• The dataset for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  The dataset for “Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers” includes 409 cram files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000000695

• GIST Comprehensive Cancer Panel

  DNA Sequencing of 864 genes from KiCS cancer panel. Multiple family members affected with multifocal GIST who underwent whole genome sequencing of the germline and tumor. Affected individuals with GIST harbored a germline variant found within exon 13 of the KIT gene, (c.1965T>G; p.Asn655Lys, p.N655K) and a variant in the MSR1 gene (c.877C>T; p.Arg293*, pR293X).

  Dataset EGAD50000000548

• Circulating tumor DNA dynamics reveal KRAS G12C mutation heterogeneity and response to treatment with the KRAS G12C inhibitor divarasib in solid tumors

  Purpose: To inform prognosis, treatment response, disease biology, and KRAS G12C mutation heterogeneity, we conducted exploratory circulating tumor DNA (ctDNA) profiling on 134 patients with solid tumors harboring a KRAS G12C mutation treated with single-agent divarasib (GDC-6036) in a phase 1 study. Experimental design: Plasma samples were collected for serial ctDNA profiling at baseline (Cycle 1 Day 1 prior to treatment) and multiple on-treatment time points (Cycle 1 Day 15 and Cycle 3 Day 1). Results: KRAS G12C ctDNA was detectable from plasma samples in 72.9% (43/59) and 92.6% (50/54) of patients with non-small cell lung cancer and colorectal cancer, respectively, the majority of whom were eligible for study participation based on a local test detecting the KRAS G12C mutation in tumor tissue. Baseline ctDNA tumor fraction was associated with tumor type, disease burden, and metastatic sites. A decline in ctDNA level was observed as early as Cycle 1 Day 15. Serial assessment showed a decline in ctDNA tumor fraction associated with response and progression-free survival. Except for a few cases of KRAS G12C sub-clonality, on-treatment changes in KRAS G12C variant allele frequency mirrored changes in the overall ctDNA tumor fraction. Conclusion: Across tumor types, the KRAS G12C mutation likely represents a truncal mutation in the majority of patients. Rapid and deep decline in ctDNA tumor fraction was observed in patients responding to divarasib treatment. Early on-treatment dynamics of ctDNA were associated with patient outcomes and tumor response to divarasib treatment.

  Study EGAS50000000315

• First in vivo investigation of the impact of PARP inhibition with rucaparib alone and in combination with atezolizumab: results of the phase Ib COUPLET clinical study in advanced gynecologic and triple-negative breast cancers

  Study EGAS00001006100

• Neoadjuvant immune checkpoint blockade in women with mismatch repair deficient endometrial cancer

  Neoadjuvant immune checkpoint blockade (ICB) has shown unprecedented activity in mismatch repair deficient (MMRd) colorectal cancers, but its effectiveness in MMRd endometrial cancer (EC) remains unknown. In this investigator-driven, phase I, feasibility study (NCT04262089), 10 women with MMRd EC of any grade, planned for primary surgery, received two cycles of neoadjuvant pembrolizumab (200 mg IV) every three weeks. A pathologic response (primary objective) was observed in 5/10 patients, with 2 patients showing a major pathologic response. No patient achieved a complete pathologic response. A partial radiologic response (secondary objective) was observed in 3/10 patients, 5/10 patients had stable disease and 2/10 patients were non-evaluable on Magnetic Resonance Imaging (MRI). All patients completed treatment without severe toxicity (exploratory objective). At median duration of follow-up of 22.5 months, two non-responders experienced disease recurrence. In-depth analysis of the loco-regional and systemic immune response (predefined exploratory objective) showed that monoclonal T cell expansion significantly correlated with treatment response. Tumour-draining lymph nodes displayed clonal overlap with intra-tumoural T cell expansion. All pre-specified endpoints, efficacy in terms of pathologic response as primary endpoint, radiologic response as secondary outcome and safety and tolerability as exploratory endpoint, were reached. Neoadjuvant ICB with pembrolizumab proved safe and induced pathologic, radiologic, and immunologic responses in MMRd EC, warranting further exploration of extended neoadjuvant treatment.

  Study EGAS50000000483

• Lactate metabolism in cancer stem cell fate regulation

  Tumors arise as a result of uncontrolled cell proliferation driven by mutations in the signaling pathways that regulate the balance between cell division and differentiation. Despite of that, in the tumor, cancer stem cells seem to retain their capability to differentiate, which can lead to differential chemotherapy response. We previously showed that intestinal stem cells and differentiated cells display specific metabolic features and that they interact through metabolites. Moreover, we found that altering mitochondrial metabolism is sufficient to lead and define stem cell differentiation. In cancer, cellular metabolism is highly derailed. However, how metabolic changes in the cancer cell contribute to cell fate decisions remains unknown. Recently, the crosstalk between metabolism and epigenetics has emerged as one of the players in tumor development. Here we aim to address the impact of the altered metabolism of cancer cells on their epigenome as a regulatory axis of cell identity and fate. We use human-derived tumor organoids where we introduce genetic encoded fluorescent-based reporters to visualize cell identity and metabolism at single cell level. We combine 4D live imaging with a recently developed machine learning method to re-construct cell-lineages, trace stem cell state and metabolic changes during tumor organoid development. We find that, mimicking the tumor metabolic microenvironment (Warburg effect-driven low-glucose high-lactate) leads to changes cellular metabolism and histone acetylation. Strikingly, these alterations provoke profound changes in tumor development by increasing the population of cancer stem cells and their proliferation and differentiation dynamics.

  Study EGAS50000000063

• SCLC MeDIP-seq

  Methylation profile of 33 patients with small cell lung cancer (SCLC) for both, tumour and normal lung samples using MeDIP-seq.

  Dataset EGAD50000000724

• BELLINI clinical trial bulk RNA-Seq data: cohorts A, B & С

  RNA-Seq data of 78 breast cancer primary tumors obtained from 45 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (15 patients, 25 samples) received nivolumab for 4 weeks, patients in cohort B (15 patients, 28 samples) received nivolumab + ipilimumab for 4 weeks, and patients in cohort C (15 patients, 25 samples) received nivolumab + ipilimumab for 6 weeks. The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000.

  Dataset EGAD50000000808

• BELLINI clinical trial bulk WES data: cohorts A & B

  WES data of 30 breast cancer primary tumors obtained from 30 unique patients from BELLINI clinical trial (cohorts A & B) and 30 matched blood samples. The data includes pretreatment samples. The included raw WES sequencing data in fastq format was generated using Illumina NovaSeq 6000.

  Dataset EGAD50000000809

• Amsterdam UMC Head and Neck Cancer Biology and Immunology

  This data access committee oversees data and assesses requests for the Head and Neck Cancer Biology and Immunology lab of Amsterdam UMC, location VUmc.

  Dac EGAC50000000350

• Spatially resolved niche and tumor microenvironmental alterations in gastric cancer peritoneal metastases

  Peritoneal metastases (PM) in gastric cancer (GC) portend a poor prognosis, yet our understanding of tumor microenvironmental (TME) characteristics associated with GCPM remain limited. Here, we analyzed intrinsic genomic alterations and transcriptomic programs predictive of GCPM in a prospective cohort of 248 patients, identifying CDH1, PIGR, and ELF3 mutations as predictors. By inspecting the spatial dynamics of the TME, we find that tumor compartment infiltration of pro-tumorigenic cell types such as inflammatory cancer-associated fibroblasts (CAFs) predict peritoneal recurrence. Next, in a cross-sectional study of 205 samples from 55 patients, distinct pathways and immune compositions in GCPM relative to liver metastases highlight the TME's significance in transcoelomic metastases. Notably, several putative therapeutic targets exhibited distinct expression patterns between PTs and PMs. Our findings highlight transcriptomic variations and niche reprogramming in the GCPM peritoneal environment, revealing roles of myeloid dendritic cells, effector memory CD8+ T cells, and CAFs in metastatic progression.

  Study EGAS50000000501

• Singapore Gastric Cancer Consortium Data Access Committee

  Dac EGAC00001002251

• NanoString Cancer

  RCC files of 17 Cartridges from metastatic melanoma

  Dataset EGAD00010002432

• Low-coverage whole genome sequencing of plasma from BRCA-mutant breast cancer patients

  Plasma samples from patients with breast cancer (stage IV) who had confirmed BRCA mutations were subjected to low-coverage whole-genome sequencing This dataset contains raw fastq files from 6 breast cancer plasma samples.

  Dataset EGAD50000000810

• Whole-genome sequencing of tumour, germline and plasma samples from a BRCA1-mutant breast cancer patient

  This data set contains the fastq files from whole-genome sequencing of temporally matched tumour (fresh frozen biopsies), blood germline and plasma samples collected from a BRCA1-mutant breast cancer patient to directly compare mutation signature analysis using gold-standard tumour-germline paired variant calling with a novel ctDNA-based method (MisMatchFinder).

  Dataset EGAD50000000811

• Duplex sequencing of selected breast cancer patients

  This study assessed the variant profiles of 22 samples from 11 breast cancer patients with adverse survival outcomes, including paired uninvolved mammary gland samples collected at various distances from primary lesions. Ultra-deep sequencing was performed to identify the presence of low-frequency pathogenic post-zygotic variants in PIK3CA and TP53 genes.

  Study EGAS50000000538

• WES of breast cancer patients and controls

  This study assessed the variant profiles of 408 samples from 126 breast cancer patients with various survival outcomes, including paired uninvolved mammary gland samples collected at proximal distances from primary lesions. As a reference, control samples from 15 mammoplasty individuals without cancer history were studied. Whole exome sequencing was performed to identify post-zygotic and germline variants present in the studied samples. Variant annotation in known databases, interpretation, and statistical analyses followed to discern the clinical relevance of called variants.

  Study EGAS50000000539

• Duplex sequencing of selected breast cancer patients

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primaty tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000769

• WES of breast cancer patients and controls

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primary tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000770

• Cancer cell and tumor microenvironment biomarkers associated with disease-free survival with adjuvant nivolumab in the phase 3 CheckMate 274 trial

  In the CheckMate 274 trial, adjuvant nivolumab versus placebo demonstrated an improvement in the primary endpoint of disease-free survival (DFS) in patients with high-risk muscle-invasive urothelial carcinoma after radical resection. An extensive analysis of tumor biomarkers, including their associations with DFS, was performed. Analysis of genome-wide differential gene expression and known gene signatures found that immune-related genes and pathways, in particular an IFNγ signature, were predictive of DFS in nivolumab-treated patients. Predictive and prognostic associations, respectively, were found for tumor-infiltrating CD4 and CD8 T cells. Analysis of a composite predictive model suggested that CD4 gene expression and tumor cell PD-L1 expression had the greatest contributions to predicting outcomes in nivolumab-treated patients. These results reinforce recent studies establishing the importance of biomarkers of adaptive immunity, and in particular CD4 T cells, in influencing response to PD-1/PD-L1 blockade and establish the potential predictive rather than solely prognostic nature of such findings.

  Study EGAS50000000560

• ROBUST (NCT02285062)

  The ROBUST clinical trial is a Phase III, randomized, double-blind, placebo-controlled study designed to compare the efficacy and safety of lenalidomide plus R-CHOP chemotherapy (R2-CHOP) versus placebo plus R-CHOP in newly diagnosed Diffuse Large B-cell Lymphoma (DLBCL). Molecular data was collected for all patients at screening, but the only patients of the Activated B-cell (ABC) cell-of-origin subtype were eligible for study inclusion and clinical follow-up. We have performed unsupervised clustering on this cohort and identified 7 novel transcriptional subtypes of DLBCL, one of which represents a high-risk subset of patients with high MYC expression, ABC-associated biology, and low immune infiltration.

  Study EGAS50000000333

• HiDEF-seq single-molecule sequencing of single-strand mismatches and damage

  Our study sought to resolve, with single-molecule fidelity, the mismatches and damage events that precede DNA mutations. Using a novel single-molecule, long-read sequencing method (HiDEF-seq) we detect base substitutions when present in either one or both DNA strands. We also detect cytosine deamination, a common type of DNA damage, with single-molecule fidelity. This study profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes. These samples revealed single-strand mismatch and damage signatures. Since double-strand DNA mutations are only the endpoint of the mutation process, our approach enables new studies of how mutations arise in a variety of contexts, especially in cancer and aging.

  Study EGAS50000000318

• WES data from 438 tumor/germline samples with non muscle invasive bladder cancer

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 876 BAM files corresponding to the full WES dataset. Tumor and matched germline DNA were sequenced to a mean coverage of 132x (35x-338x) and 128x (31x-302x), respectively.

  Dataset EGAD50000000730

• Long Read sequencing data from 4 tumor/germline samples with non muscle invasive bladder cancer

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). Additionally, tumor/germline samples from 4 patients were sequenced using Oxford Nanopore technology. This dataset contains 8 BAM files corresponding to the Long read sequencing data.

  Dataset EGAD50000000731

• sWGS data from 362 tumor with non muscle invasive bladder cancer and 30 blood samples (15 males and 15 females)

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 876 BAM files corresponding to the full WES dataset. This dataset contains 392 BAM files corresponding to the full sWGS dataset. Tumor samples were sequenced to median coverage of 2.14x (1.24-9.01).

  Dataset EGAD50000000732

• RnaSeq data from 414 tumor samples with non muscle invasive bladder cancer

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 414 BAM files corresponding to the full total RNA-sequencing dataset.

  Dataset EGAD50000000733

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  Dac EGAC00001003503

• Cancer Biomarkers team at The ICR DAC

  DAC for Cancer Biomarkers

  Dac EGAC50000000200

• Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Dataset EGAD00001000002

• CLL Cancer Whole Genome Sequencing

  CLL Cancer Whole Genome Sequencing

  Dataset EGAD00001000013

• Whole Genome Sequencing of Multiple Myeloma patients treated with T-cell redirecting immunotherapies

  Samples was collected at the Arnie Charbonneau Cancer Institute (University of Calgary). Whole Genome Sequencing was performed at the New York Genome Center, and libraries were prepared using the Truseq DNA Nano Library Preparation Kit. Libraries were sequenced on an Illumina Novaseq 6000 sequencer using 2 x 150-bp cycles. The dataset consists in 85 BAM files from patients with Multiple Myeloma treated with bi-specific and CAR-T therapies. Reference Genome: GRCh38.

  Dataset EGAD50000000776

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 16)

  The dataset contains whole genome sequencing data of 58 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 144 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000777

• ICARUS-BREAST01-RNAseq

  Efficacy, safety and biomarker analysis of ICARUS-BREAST01: a phase 2 Study of Patritumab Deruxtecan in patients with HR+/HER2- advanced breast cancer. RNA-squencing is available for 44 samples comprising 22 samples collected at entry into the trial and 22 samples collected during treatment (cycle 1 day 3, cycle 1 day 19, or cycle 2 day 3) from 22 patients.

  Study EGAS50000000543

• Genomic profiling of Rare Tumors Release 2

  Utilizing the rare and unique patient samples provided by Pattern Medicine, LLC, MD Anderson will molecularly characterize rare cancer samples, and potentially generate a collection of preclinical models to enable identification of novel therapeutic targets and concepts, as well as evaluation of innovative treatment strategies.

  Study EGAS50000000615

• Comparison of good PDX responders and bad PDX responders

  RNA-Seq raw data of untreated breast cancer xenografts known as good or bad acetalax responders.

  Dataset EGAD50000000876

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1,070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8,887 TCGA, and 1,261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n=1,261) including our lung cancer cohort (n=497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

  Study EGAS50000000324

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  Raw bam file for bulk RNA-seq of checkpoint-blockade treated lung cancer cohorts

  Dataset EGAD50000000469

• DAC for a single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Dac EGAC50000000226

• Genomic Alterations and Transcriptional Phenotypes in Circulating Tumor DNA and Matched Metastatic Tumor

  We analyzed a prospective cohort of 49 plasma samples obtained before, during, and after treatment from 20 patients with recurrent small cell lung cancer. We conducted cfDNA low-pass whole genome sequencing (0.1X coverage) and exome sequencing (130X coverage) in comparison with time-point matched tumor characterized using whole-exome (130X) and transcriptome sequencing. A direct comparison of cfDNA and tumor biopsy revealed that cfDNA not only mirrors the mutation and copy number landscape of the corresponding tumor, but also identifies clinically relevant resistance mechanisms and cancer driver alterations not detected in matched tumor biopsies. Longitudinal cfDNA analysis reliably tracks tumor response, progression, and clonal evolution. Sequencing coverage of plasma DNA fragments around transcription start sites showed distinct treatment-related changes and captured the expression of key transcription factors n the corresponding SCLC tumors.

  Study phs003689