7825 results for "canc*"

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• Non-invasive anal (pre)cancer dataset

  Molecular analysis of DNA from human anal swabs offers a non-invasive method for anal cancer screening. Current guidelines recommend anal swab-based screening and highlight the need for objective biomarkers to improve risk stratification. We performed genome-wide methylation profiling on DNA from 86 anal swab samples, including 40 HSIL-AIN3 cases (high-grade squamous intraepithelial lesions), 39 controls (<=LSIL), and 7 anal cancer patients, using the 850K Infinium MethylationEPIC BeadChip (Illumina). From this analysis, we identified a three-gene methylation classifier that showed strong discriminatory performance in distinguishing HSIL-AIN3 and anal cancer from <=LSIL lesions and successfully identified all anal cancer cases when applied to an independent validation cohort.

  Dataset EGAD00010002832

• HSC_population_dynamics_KSP_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001002762

• Immune Biomarkers in Metastatic Castration-resistant Prostate Cancer

  Background: Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease in which molecular stratification is needed to improve clinical outcomes. The identification of predictive biomarkers can have a major impact on the care of these patients, but the availability of metastatic tissue samples for research in this setting is limited. Objective: To study the prevalence of immune biomarkers of potential clinical utility to immunotherapy in mCRPC by tumour RNA sequencing, and to determine their association with overall survival (OS).

  Study EGAS50000001269

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - WGS validation cohort

  This reposiroty contains bulk WGS data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere.

  Study EGAS50000001211

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - RNA validation cohort

  This reposiroty contains bulk RNA data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere.

  Study EGAS50000001212

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - WGS

  This reposiroty contains bulk WGS data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere. The dataset contains 11 tumor-normal sample pairs.

  Dataset EGAD50000001724

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - RNA

  This reposiroty contains bulk RNA data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere. The dataset contains RNAseq samples from bone marrows.

  Dataset EGAD50000001725

• Cancer Genomics Lab at Johns Hopkins

  Dac EGAC00001003656

• Pan Prostate Cancer Group Germany BAM files

  German early-onset prostate cancer whole-genome sequencing samples of the Pan-Prostate Cancer Genome (PPCG) project. Whole Genome Sequencing Illumina data from men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy with matched blood control.

  Dataset EGAD00001005997

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

  Ovarian cancer is a leading cause of death from gynecological malignancies worldwide. No effective screening methods exist resulting in tumor detection at advanced stages where treatment is less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women, mostly post-menopausal, from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we evaluated the detection of ovarian cancer in two clinical settings, detection of ovarian cancers among a healthy population, and classification of adnexal masses as benign or malignant. The combined approach detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach differentiated benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Dac EGAC50000000332

• Prefibrotic Bone Marrow Microenvironment is a Hallmark of Clonal Hematopoiesis

  Clonal hematopoiesis of indeterminate potential (CHIP) is linked to systemic inflammation and increased malignant risk, yet its impact on the bone marrow (BM) niche remains poorly understood. Through single-cell transcriptomic profiling of freshly isolated BM, we identify fibro-inflammatory rewiring as an early hallmark of CHIP. Beyond a myeloid-biased inflammatory state, CHIP BM exhibited coordinated TNFα activation across hematopoietic progenitor, monocyte, and stromal compartments. Stromal populations displayed early fibrotic remodeling, with mesenchymal and vascular cells upregulating collagen and extracellular matrix programs. Fibroblasts were markedly expanded independent of mutational subtype and acquired cancer-associated fibroblast (CAF)-like programs, rewiring niche interactions through IL-6, TGFβ, and collagen-integrin signaling. Together, these findings establish fibro-inflammatory BM remodeling as an early hallmark of clonal expansion, linking CHIP to prefibrotic stromal remodeling, immune dysregulation, and a niche architecture consistent with increased malignant risk.

  Study EGAS50000001774

• NICHE - Pre-treatment single cell RNA-seq of MMR proficient early stage colon cancers

  This dataset includes raw single cell RNA sequencing data from 13 pMMR colon cancer patients treated with neoadjuvant immune checkpoint blockade in the NICHE trial. This dataset comprises pre-treatment colon cancer biopsy samples, which digested to obtain single cell suspensions, sorted for CD45+, labelled with hashtag antibodies, split in 3 cell pools, and distributed in 5 sequencing samples (7654_1-5). 30 FASTQ files were generated, 10 files for scRNAseq gene expression (10X Genomics Chromium Next GEM Single Cell 5' v2), 10 files for single cell TCRseq (10X Genomics Chromium Next GEM Single Cell V(D)J Reagent Kits 5' v2) and 10 files for feature barcodes and hashtag antibodies, with feature reference barcodes provided. Samples were sequenced on Illumina Novaseq 6000 and raw FASTQ files were later processed with Cellranger workflows from 10X Genomics, investigating features of pre-treatment immune tumour cells and associations with neoadjuvant response.

  Dataset EGAD50000002853

• Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin

  Study EGAS00001004660

• Pre-existing immunity and hrHPV status as determinants of immunotherapy response in advanced penile cancer: biomarkers and overall survival in the PERICLES trial

  The phase II PERICLES trial (NCT03686332) investigated atezolizumab with or without radiotherapy in advanced penile cancer. Here, we report mature overall survival (OS) and updated progression-free survival (PFS) outcomes and an in-depth biomarker analysis. The goal was to perform an in-depth assessment of the tumor microenvironment to identify potential predictive biomarkers and cellular mechanisms underlying successful PD-L1 blockade response.

  Study EGAS50000001571

• DAC Study assessing the efficacy and safety of durvalumab plus olaparib plus fulvestrant in selected metastatic or locally advanced ER-positive, HER2-negative breast cancer patients.

  DAC for Study assessing the efficacy and safety of durvalumab plus olaparib plus fulvestrant in selected metastatic or locally advanced ER-positive, HER2-negative breast cancer patients.

  Dac EGAC50000000694

• NeoLetExe clinical trial single-cell RNA-seq, scTCR-seq, scBCR-seq and cis-regulatory elements mapping

  We performed single cell RNA sequencing, single cell T cell receptor and B cell receptor sequencing on breast tumor biopsies collected from patient of the NeoLetExe clinical trial at 3 time points of neoadjuvant therapy with aromatase inhibitors. The NeoLetExe study is a randomized open-label clinical trial aimed at evaluating the effects of sequential aromatase inhibition in postmenopausal women with ER-positive, HER-2 negative locally advanced breast cancer (stages T3-T4 and/or N2-3, including larger T2 tumors). Fresh tumor biopsies were dissociated at the single cell level which when then processed using the 10x Genomics Chromium platform, using the Single-Cell 5′ RNA-seq method along with single cell BCR and TCR-seq. The target was 7,500 to 10,000 cells per well, with libraries prepared using Gel Bead, Multiplex, and Chip Kits, following the manufacturer’s guidelines. Sequencing was performed on NovaSeq6000. We used SCAFE v1.0.065 to identify TSSs and map transcriptionally active regulatory elements.

  Study EGAS50000001362

• Cell-Free DNA Fragmentation Distinguish Immunotherapy Responders from Non- Responders in Head and Neck Cancer: A Multi-Institute Prospective Study

  We performed whole-genome sequencing of 185 plasma cfDNA samples from 68 patients with head and neck squamous cell carcinoma (HNSCC) enrolled in a phase II clinical trial of neoadjuvant and adjuvant pembrolizumab. Using these data, we developed the regional motif diversity score (rMDS), a novel fragmentomic biomarker that predicts immunotherapy response and outperforms established cfDNA metrics.

  Study EGAS50000001286

• Xenium in situ spatial transcriptomics analysis of cervical cancer sample Cx71

  This submission adds Xenium in situ spatial transcriptomics analysis data generated from an FFPE tissue section of a human cervical cancer sample (case ID: Cx71) to the hum0358 research. The files include a morphology OME-TIFF image, decoded transcript coordinates, a cell feature matrix, cell metadata, and cell/nucleus segmentation boundaries.

  Study JGAS000918

• Molecular Characterization of Large Cell Neuroendocrine Carcinoma of the Lung by Multilayered Omics Analysis

  Large cell neuroendocrine carcinoma (LCNEC) is a rare lung cancer type with a very poor prognosis. The underlying molecular features remain unclear. Here, we conducted a multi-omics analysis of 27 LCNEC cases along with 7 small cell lung carcinoma and aimed to propose new classification by extracting genomic and transcriptomic features in LCNEC, leading to the elucidation of the therapeutic approaches.

  Study JGAS000832

• IRCCS Istituto Romagnolo per lo Studio dei Tumori Dino Amadori Italian Cancer Center Data Access Committee

  Dac EGAC00001003631

• Genetic, epigenetic and fragmentomic profiling of plasma cell-free DNA in cancer patients

  The primary goal of the study is to explore the temporal changes in cfDNA profiles in liver cancer patients undergoing therapeutic treatment. Serial blood collection and plasma cfDNA analysis were performed in patients with liver cancer, including patients with primary hepatocellular carcinoma, or those with secondary liver metastasis. Various molecular features of cfDNA were studied, including tumor fraction, epigenetic and fragmentomic analysis.

  Study EGAS50000002022

• Ex vivo therapy-driven selection of glioblastoma stem-like cells models resistance evolution

  Glioblastoma (GBM) remains lethal, creating an urgent need for experimental models of therapy- specific resistance evolution. Within-patient GSC models were developed by parallel ex-vivo selection under temozolomide (TMZ-GSC) or ionizing radiation (IR-GSC), alongside untreated controls (CTRL- GSC). • O6-methylguanine-DNA methyltransferase (MGMT) expression was confirmed as a determinant of primary TMZ resistance and was maintained during GSC evolution. • In MGMT-negative GSCs, primary TMZ sensitivity evolved into stable secondary resistance through mismatch-repair gene inactivation, recapitulating patient findings, or was retained along with a newly identified drug-tolerant phenotype. • Primary radioresistance was commonly observed, while its further evolution was associated with more efficient DNA double-strand-break repair and enrichment of homologous- recombination and checkpoint-control transcriptional programs. • In GSCs emerging after either TMZ or IR, broad transcriptional patient-specific programs and classification-relevant subtypes were largely preserved. • Across treatments, GSC evolution was accompanied by shared genome-maintenance and mitotic chromosome-segregation transcriptional programs and increased RTK expression and activity, collectively promoting recovery after genotoxic stress.

  Study EGAS50000002011

• Genetic, epigenetic and fragmentomic profiling of plasma cell-free DNA in cancer patients

  The uploaded data includes sequencing of plasma cfDNA from a total of 33 cancer patients. Plasma cfDNA samples were sequenced for whole-genome sequencing analysis using double-stranded DNA libraries, and paired bisulfite sequencing using single-stranded DNA libraries. All sequencing data are of extracted plasma cfDNA from human patients, and sequenced using the Illumina NovaSeq6000 platform. Alignment was performed to the human genome (hg19). Lambda DNA was added to samples subjected to bisulfite sequencing for quality control.

  Dataset EGAD50000002912

• Nicotinamide phosphoribosyltransferase is an integrator of circadian clock regulation and NAD+ metabolism in liver cancer

  NAMPT is a liver-specific integrator of circadian and metabolic regulation, and its dysregulation creates a therapeutic window for a more precise treatment of liver cancer.

  Study EGAS50000000868

• The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET) – HCC recurrence cohort

  Hepatocellular carcinoma (HCC) is a highly fatal cancer marked by significant intra-tumor heterogeneity (ITH). Given 50% to 70% of HCC patients experience recurrence, understanding the origins and progression of recurrence is crucial. To address this, we assembled a multi-sector, paired HCC recurrence cohort of 24 patients, including comprehensive whole genome sequencing and transcriptome samples. Through this longitudinal cohort, we aimed to trace the origins of recurrence and identify molecular features associated with early recurrence. These insights may improve predictions of early HCC recurrence and inform potential therapeutic strategies.

  Study EGAS50000000869

• The dataset for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  The dataset for “Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types” includes 288 bam files from whole genome, whole exome and targeted next-generation sequencing on the Illumina HiSeq2500 and MiSeq. The samples analyzed include tumor and normal tissue samples from patients with cancer.

  Dataset EGAD50000000744

• The dataset of Detection and characterization of lung cancer using cell-free DNA fragmentomes on NovaSeq 6000 at 1-2x coverage

  The dataset contains 364 CRAM files from whole-genome next-generation sequencing on the Illumina NovaSeq 6000 at 1- 2x coverage. These are plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000001961

• Analysis of Somatic Mutations from Liquid Biopsy-Derived cfDNA in Advanced Cancers

  This study aims to identify somatic mutations and characterize potential neoantigens for immunotherapeutic targeting using paired whole-exome sequencing (WES) of germline DNA and plasma-derived circulating cell-free DNA (cfDNA) from patients with advanced-stage cancers.

  Study EGAS50000001169

• Analysis of Somatic Mutations and Neoantigen Landscape from Liquid Biopsy-Derived cfDNA in Advanced Cancers

  This study involves paired whole-exome sequencing (WES) of germline DNA and plasma-derived circulating cell-free DNA (cfDNA) from patients with advanced-stage cancers, aiming to identify somatic mutations and characterize potential neoantigens for immunotherapeutic targeting.

  Dac EGAC50000000717

• Validation of cfDNA fragmentome analyses for early detection of liver cancer

  Study EGAS00001008111

• Methylation data for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  Study EGAS00001008175

• A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

  Abstract: Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cancer cell trajectory regionalizes tumours into distinct tissue niches and manifests in a conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to jointly map cancer cell states and clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

  Dataset EGAD00001015516

• Analysis of Somatic Mutations and Neoantigen Landscape from Liquid Biopsy-Derived cfDNA in Advanced Cancers

  This study involves paired whole-exome sequencing (WES) of germline DNA and plasma-derived circulating cell-free DNA (cfDNA) from patients with advanced-stage cancers, aiming to identify somatic mutations and characterize potential neoantigens for immunotherapeutic targeting.

  Dataset EGAD50000001671

• Exome (FrTu, cfDNA and normal), transcriptome (FrTu) and single-cell (PBLs) sequencing of metastatic cancer patients

  Whole Exome Sequencing of tumor biopsy DNA (FrTu), cfDNA and matching normal PBMC DNA; total RNA-Seq of FrTu samples; and scRNA- and scTCR-seq of PBLs from metastatic cancer patients included in Garcia-Garijo et al., 2026.

  Dataset EGAD50000001672

• PBMCs Bellini TNBC anti-PD1 monotherapy

  Immune checkpoint blockade (ICB) combined with chemotherapy (CT) has improved outcome in high-risk early-stage triple-negative breast cancer (TNBC); yet it is unclear which patients benefit from the addition of ICB beyond chemotherapy alone. We profiled 67 serial tumor and 175 blood samples obtained before and during anti-PD1 treatment across 3 breast cancer trials using single-cell transcriptomic and T cell receptor (TCR) sequencing. Early intratumoral T cell expansion emerged as a consistent hallmark of clinical benefit. This expansion was reflected in increased TCR sharing between tumor and blood after treatment initiation, with shared blood T cells displaying immune-activated programs and their tumor counterparts enriched for expanding clonotypes, suggesting blood-to-tumor trafficking of activated T cells. In TNBC treated with anti-PD1+CT, T cell expansion distinguished an immune-driven response from a chemotherapy-dominant route to pathological complete response (pCR). To enable baseline patient stratification, we derived a 15-gene tumor signature predictive of T cell expansion, which associated with response in independent breast cancer cohorts and with improved survival across ICB-treated cancer types. Our data establish T cell expansion as an early marker of sustained ICB response and could allow stratification of patients likely to benefit from the addition of ICB to chemotherapy.

  Study EGAS50000002067

• PARADIGM: Combined ctDNA and serum PSA for dynamic monitoring of metastatic prostate cancer starting first-line treatment

  The prognosis of newly-diagnosed metastatic prostate cancer is highly variable. The PARADIGM prospective cohort study evaluated predictors of survival in blood collected at the start of each of the first six treatment cycles from 114 high-volume metastatic patients starting androgen deprivation therapy combined with docetaxel or an androgen receptor pathway inhibitor.

  Study EGAS50000001357

• Clinical Outcomes of 344 Diffuse Large B-Cell Lymphoma patients

  This study examines clinical outcomes of patients with diffuse large B-cell lymphoma (DLBCL). We analyzed a cohort of 344 patients from the German High-Grade Non-Hodgkin Lymphoma Study Group (DSHNHL). To protect patient confidentiality, all samples were pseudonymized. The dataset includes clinical key characteristics, such as patient age at diagnosis, sex, ECOG performance status, disease stage, serum lactate dehydrogenase levels, bulky disease, bone marrow involvement, extranodal involvement, and B-symptoms. We used these data alongside proteomic and transcriptomic profiles to explore relationships between clinical features and molecular signatures, reconstructing regulatory networks. Insights from this integrative analysis aim to identify key pathological drivers and biomarkers of DLBCL progression, ultimately informing improved risk stratification and targeted therapeutic approaches.

  Study EGAS50000001054

• IMMUcan Upstream SCCHN3 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients from the UPSTREAM trial, with squamous cell carcinoma of the head and neck (SCCHN) cancer which has spread (metastatic) or the tumour has come back after previous treatment (recurrent). Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

  Study EGAS50000001505

• IMMUcan SCCHN1 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with confirmed locally recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) who receive first-line treatment with immune checkpoint inhibitors (ICI) or ICI combined with chemotherapy. Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

  Study EGAS50000001533

• Whole-genome sequencing study of uveal melanoma

  Uveal melanoma is the most common primary intraocular cancer, characterized by metastasis-related mortality. Here, we explored whole-genome sequences from 40 primary uveal melanomas to illustrate the landscape of genomic mutations and investigate their association with prognosis.

  Study EGAS50000001603

• Evaluation Of The Role Of Tumor Mutational Burden As A Prognostic Biomarker In Follicular Lymphoma

  In this study, we have evaluated TMB through a 409-gene panel in 135 patients with FL or transformed FL (tFL) at presentation. We analyzed the association of TMB with prognosis and specific genetic alterations recurrent in FL, with the goal of identifying molecular markers that could improve prognostic assessment.

  Study EGAS50000001448

• MIBC NAC2020 cohort RNA sequencing

  The dataset contains RNA sequencing data from N=48 transurethral resections of bladder tumours (TURBTs) from N=48 patients with muscle-invasive bladder cancer. All TURBTs originate from formalin-fixed paraffin embedded tissue. We used the Illumina TruSeq RNA exome kit, previously known as the TruSeq RNA Access Library Prep Kit. This kit converts total RNA into template molecules of known strand origin, followed by sequence-specific capture of coding RNA. All samples were run in an Illumina NovaSeq6000 instrument. Paired FASTQ files from all 48 patients are provided.

  Study EGAS50000000741

• A New CA19-9 Cut-Off Value Identifies Lewis Antigen Status and Refines Prognostic Stratification in PDAC

  This study investigates the clinical utility of serum CA19-9 levels in pancreatic ductal adenocarcinoma (PDAC), with a focus on identifying patients with Lewis antigen–negative status due to germline FUT3 variants. Using data from multicenter prospective cohorts in Taiwan, we analyzed CA19-9 classification, FUT2/FUT3 genotypes, and clinicopathological annotations. The goal of this study is to refine prognostic stratification and reduce false-negative interpretation of CA19-9 in PDAC patients. All participants provided informed consent, and the study was approved by the relevant institutional review boards.

  Study EGAS50000001575

• Single-cell profiling reveals mechanisms of response to anti-PD-L1 versus anti-PD-L1 combined with anti-CTLA4 in head and neck squamous cell carcinoma

  Cancer patients often receive a combination of PD-(L)1 and CTLA4 inhibitors, but the mechanisms underlying their concerted actions remain unclear. We conducted a neoadjuvant study in head and neck squamous cell carcinoma (HNSCC) involving anti-PD-L1 monotherapy versus anti-PD-L1/anti-CTLA4 combination. Single-cell profiling of on- versus pre-treatment biopsies confirmed T-cell expansion as response biomarker. We identified a type 1 immune response accompanying T-cell expansion on-treatment across treatment arms, and herein characterized co-localized IgG plasma cell expansion as important contributor. In pre-treatment biopsies, similar features correlated with expansion upon anti-PD-L1, but not anti-PD-L1/anti-CTLA4. By profiling tumor-draining lymph nodes, we found the addition of anti-CTLA4 to trigger activation and subsequent trafficking of CD4+ T-cells via the blood, to become T-helper 1 cells in the tumor. anti-PD-L1/anti-CTLA4 indeed facilitated co-localized expansion of CD4+ and CD8+ T-cells in tumors versus mostly CD8+ T-cells with anti-PD-L1 alone. Hence, we identify complimentary mechanisms underlying anti-PD-L1/anti-CTLA4 therapy in HNSCC.

  Study EGAS50000000037

• Patient-specific CAR T cell barriers in colorectal cancer identified by phenotypic screening of tumor organoids

  This study used CAR-T cells in coculture with patient-derived organoids to model patient-specific responses to CAR-T cell therapy. Heterogeneous killing efficiencies together with downstream analysis revealed tumor-intrinsic drivers of CAR-T resistance. In addition, drug library screens for synthetic lethality identified possible targets for combinatorial treatment strategies.

  Study EGAS50000002034

• DKTK Organoid Platform: A multicentric living biobank for functionalizing patient-derived organoids and model clinical outcomes

  To enable the generation of harmonized and well annotated PDTO cohorts across national institutions, the German Cancer Consortium (DKTK) has established the Strategic Initiative Organoid Platform. For the MetPredict cohort, individual PDTOs were generated from spatially distinct liver metastases of colorectal cancer. To study the molecular inter-metastatic heterogeneity, samples were submitted to whole exome sequencing.

  Study EGAS50000002045

• Bladder Cancer Genomics Data Access Committee – Erlangen–Bonn Collaboration

  The Bladder Cancer Genomics Data Access Committee (DAC) represents the collaborative bladder cancer research program between the Institute of Pathology, Universitätsklinikum Erlangen; the Department of Urology and the Institute of Experimental Oncology, Universitätsklinikum Bonn. The DAC comprises representatives from each participating institution, including Prof. Dr. med. Dr. rer. biol. hum. Markus Eckstein (Universitätsklinikum Erlangen) and PD Dr. med. Niklas Klümper (Universitätsklinikum Bonn). The committee is responsible for reviewing and approving requests for access to controlled-access bladder cancer genomic and associated clinical datasets generated through this collaboration deposited in the European Genome-phenome Archive (EGA). The committee reviews requests from qualified researchers to determine whether the proposed use of the data is consistent with the participants' informed consent, applicable ethical approvals, institutional data access policies, and relevant data protection regulations before granting access.

  Dac EGAC50000001118

• Bulk RNA Sequencing of 112 Bladder Cancer Tumor Samples Using Lexogen QuantSeq 3′ mRNA-Seq

  Bulk RNA sequencing dataset comprising tumor samples from 112 bladder cancer patients. Gene expression profiling was performed using the Lexogen QuantSeq 3′ mRNA-Seq library preparation protocol, which generates strand-specific 3′ end transcript libraries for digital gene expression quantification. The dataset provides transcriptomic profiles for molecular characterization of bladder cancer and supports studies of tumor biology, biomarker discovery, and clinical outcome associations.

  Study EGAS50000002032

• Raw Bulk QuantSeq 3′ mRNA Sequencing Data from 137 Bladder Cancer Tumor Samples

  This controlled-access dataset comprises raw single-end FASTQ files generated from 137 bladder cancer tumor samples collected from 112 patients using the Lexogen QuantSeq 3′ mRNA-Seq protocol on the Illumina NovaSeq 6000 platform. Access is governed by the Bladder Cancer Genomics Data Access Committee (DAC) and the associated controlled-access policy.

  Dataset EGAD50000002920

• Processed Gene-Level Expression Counts from 137 Bladder Cancer QuantSeq 3′ RNA-seq Samples

  This controlled-access dataset contains processed gene-level expression counts generated from 137 bladder cancer tumor samples collected from 112 patients. Gene expression quantification was performed using the nf-core/rnaseq workflow with Salmon, and transcript-level abundance estimates were aggregated to gene-level counts. Access is governed by the Bladder Cancer Genomics Data Access Committee (DAC) and the associated controlled-access policy.

  Dataset EGAD50000002921