5270 results for "*oma"

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• Tumoral immune microenvironment profiling in B-cell non-Hodgkin lymphoma stratifies patients in different prognostic groups

  Dac EGAC50000001065

• Tumoral immune microenvironment profiling in B-cell non-Hodgkin lymphoma stratifies patients in different prognostic groups

  Non-Hodgkin lymphomas (NHL) are heterogeneous B-cell malignancies in which the tumor immune microenvironment (TIM) influences disease progression and has emerging potential for prognostic patient stratification. This project investigates the TIM of NHL by combining multiparameter flow cytometry with targeted DNA sequencing of NHL biopsies. The study aimed to characterize the immune cell composition, immune checkpoint expression, and mutational landscape, and to evaluate their association with clinical and prognostic features across NHL subtypes. The classification of TIM profiles by flow cytometry predicts clinical outcomes in patients with follicular lymphoma (FL), highlighting its potential value for risk stratification and the identification of novel immunotherapeutic targets in NHL.

  Study EGAS50000001964

• RNAseq and WES of CHC patients years before HCC development

  We conducted a nested case–control study within a prospective liver biopsy biobank at the University Hospital Basel. Patients with chronic hepatitis C (CHC) who developed hepatocellular carcinoma (HCC) during follow-up (index cases, CHC-HCC) were identified and 1:2 propensity score-matched to CHC controls without HCC (controls, CHC-nonHCC). Matching included clinical, demographic, and virological risk factors for HCC. Liver biopsies were analyzed using RNA and whole-exome sequencing.

  Dataset EGAD50000001591

• Targeted DNA sequencing of 60 non-Hodgkin lymphoma biopsies using a custom gene panel for hematological malignancies: raw (FASTQ) data

  Targeted DNA sequencing was performed on 60 non-Hodgkin lymphoma (NHL) samples using a custom next-generation sequencing panel targeting the coding regions of 190 genes recurrently mutated in hematological malignancies. Libraries were sequenced on an Illumina NovaSeq 6000 platform using 2 × 150 bp paired-end reads. The dataset includes the raw sequencing data (FASTQ files) for all 60 samples.

  Dataset EGAD50000002845

• scRNAseq and spatial transcriptomics data of melanoma samples

  Paired-end 10x single-cell RNA sequencing and Visium spatial transcriptomics data from samples derived from 11 melanoma patients. Sequencing was performed on the Illumina NovaSeq 6000 using 10xGenomics Chromium Next GEM Single-Cell 5 Reagent Kits v2 or 10xGenomics Visium Gene Expression kit.

  Dataset EGAD50000002902

• RNA-seq of adult T-cell leukemia-lymphoma patient-derived xenograft (PDX) models treated with the MALT1 protease inhibitor CRD-1441551

  To elucidate the therapeutic effect of MALT1 protease inhibition in adult T-cell leukemia/lymphoma (ATL), we performed RNA-seq on tumor tissues from five ATL patient-derived xenograft (PDX) models. NOG mice engrafted with each PDX model were treated with the MALT1 protease inhibitor CRD-1441551 or vehicle for 21 days, in biological triplicate (n = 3 per condition; 30 samples in total). Mouse-derived reads were removed and the remaining human reads were aligned to the human reference genome (hg19). These data underlie the gene-expression analyses reported in the associated publication.

  Study JGAS000921

• Impact of Mutated CTCF DNA binding sites of Topologically associating domains on nearby Cancer Gene Regulation: A Multi-Omics Analysis

  Cutaneous squamous cell carcinoma (cSCC) is the most common lethal malignancy world-wide. Due in most part to the extremely high mutational burden (TMB) in cSCC, making sense of it’s non-coding and regulatory regional genomic variation has lagged that of other far less common cancers. This study presents the first investigation of mutations at CCCTC-binding factor binding sites (CTCFbs) of Topologically associating domains (TAD) across defined cSCC progression stages—primary non-metastatic (PNM), primary metastat-ic (PM), and lymph node metastasis (LNM).

  Study EGAS50000001686

• CTCF Binding Site Mutations: Linking Topologically Associated Domains Dysregulation to Cutaneous Squamous Cell Carcinoma Progression

  Fresh tumor tissue from nodal metastases (n = 41) was harvested during surgery and immediately snap-frozen. A total of 72/75 cSCC, WGS samples were included in the analysis (refer to QC section), comprising primary tumors (both metastatic (PM (n = 16)) and non-metastatic (PNM (n = 15)), as well as lymph node metastases (LNM (n = 41)). The metastatic cohort included matched PM and LNM samples for 13 patients. The PNM group had to meet the following criteria: absence of metastases at > 24 months follow-up after resection of the primary or negative sentinel lymph node biopsy at time of resection or histologically negative neck dissection. Somatic variant analysis was performed using DRAGEN pipeline version 4.3.6 on the Illumina Connected Analytics (ICA) v2 environment using in house shell scripting. Tumor-normal paired analyses were carried out in three stages: alignment, variant calling, and integrative somatic analysis. Further information on the somatic calling is available at https://help.dragen.illumina.com/product-guides/dragen-v4.3/dragen-dna-pipeline/small-variant-calling/somatic-mode.

  Dataset EGAD50000002416

• IMC-F106C-101 dose escalation

  Brenetafusp is an ImmTAC bispecific (PRAME×CD3) targeting the cancer testis antigen PRAME. In this phase 1 study (NCT04262466), 126 HLA-A*02:01+ patients with advanced solid tumors received weekly IV doses from 0.3-320 mcg. The primary objective was to identify the maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D); additional objectives included pharmacokinetics, pharmacodynamics, and preliminary anti-tumor activity. Brenetafusp demonstrated manageable safety and preliminary efficacy in PRAME+ tumors. A phase 3 trial in metastatic cutaneous melanoma is ongoing

  Study EGAS50000001976

• RNA-seq for "A preinvasive regulatory T cell axis for lung cancer interception" paper

  Bulk RNA sequencing data generated from primary resected non-small cell lung cancer (NSCLC) tumour tissue collected through the ASCENT study (Analysis of Screen-Detected Lung Cancers’ Genomic Traits; NCT04204499). The dataset comprises tumour RNA-seq from 89 patients with CT screen-detected NSCLC, predominantly early-stage disease, including lung adenocarcinoma and lung squamous cell carcinoma. The RNA-seq data were used to characterise tumour-immune transcriptional programmes and were analysed alongside matched peripheral blood immune profiling and clinical follow-up data.

  Dataset EGAD50000002852

• LUAD RNAseq – LORD

  RNA-seq data from paired normal and adenocarcinoma lung samples obtained from 515 patients that underwent lung cancer surgery.

  Study EGAS50000001705

• LUAD RNAseq - LORD

  The Lung Oncology Research and Discovery (LORD) program is a multi-omics translational initiative aimed at advancing precision medicine in lung cancer. It builds on a lung tissue biobank and leverages biological samples collected from patients who underwent lung cancer surgery at the IUCPQ-UL (Quebec City, Canada). LORD is therefore a single-site, retrospective, case-only study. Genomic profiling of biobanked samples is ongoing, with samples being analyzed sequentially in phases defined by sample type and omic modality. For this dataset, we provide RNA-seq data from paired normal and adenocarcinoma lung samples obtained from 515 patients.

  Dataset EGAD50000002450

• Projet LORD- LUAD RNAseq data

  RNAseq data from paired samples of non affected lung parenchyma and Lung adenocarcinoma (LUAD) from 515 patients surgically intervened at the Institut universitaire de cardiologie et de pneumologie de Québec- Université Laval

  Dac EGAC50000000846

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - pilot normal and pre/post-chemo

  Dataset EGAD00001000704

• Single-cell RNA sequencing of large B cell lymphoma relapsed after CAR T-cell therapy and in vitro serial killing models

  Relapsed/refractory large B-cell lymphoma (rrLBCL) following CAR T-cell therapy remains associated with a poor prognosis. Using single-cell RNA sequencing (scRNA-seq), we characterized the T-cell profiles in 7 post-CAR T rrLBCL and 5 CAR T-naïve rrLBCL, revealing dysfunctional transcriptional features in T cells after CAR T-cell therapy. In addition, the dataset includes T cell profiling of CAR T-cell products and samples obtained after serial killing assays in vitro, performed with or without supplementation with non-IL2Rα agonist pegenzileukin. These analyses demonstrated that IL-2 was the most depleted cytokine following the coculture assay.

  Study EGAS50000001982

• Single-cell RNA sequencing of large B cell lymphoma relapsed after CAR T-cell therapy and in vitro serial killing models

  Relapsed/refractory large B-cell lymphoma (rrLBCL) following CAR T-cell therapy remains associated with a poor prognosis. Using single-cell RNA sequencing (scRNA-seq), we characterized the T-cell profiles in 7 post-CAR T rrLBCL and 5 CAR T-naïve rrLBCL, revealing dysfunctional transcriptional features in T cells after CAR T-cell therapy. In addition, the dataset includes T cell profiling of CAR T-cell products and samples obtained after serial killing assays in vitro, performed with or without supplementation with non-IL2Rα agonist pegenzileukin. These analyses demonstrated that IL-2 was the most depleted cytokine following the coculture assay.

  Dataset EGAD50000002866

• MOSAIC Window Mesothelioma Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 Mesothelioma patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001706

• MOSAIC Window Glioblastoma Data

  This dataset will include Spatial Transcriptomics, Single-Cell RNA-Seq, Bulk RNA-Seq, Clinical data, WES, and H&E data from 10 Glioblastoma (GBM) Cancer patients. Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001352

• Genome-wide genotype data of 125 Agotes individuals presented in Portela-Estevez et al. 2026

  Genome-wide genotype data of 125 Agotes individuals presented in Portela-Estevez et al. 2026

  Dataset EGAD00010002839

• Mechanisms of resistance to pembrolizumab treatment in classical Hodgkin Lymphoma

  In this project we are applying whole exome sequencing (WES) on plasma-derived ctDNA samples to identify mutations that drive resistance to pembrolizumab treatment in classical Hodgkin Lymphoma

  Study EGAS50000001985

• Whole-exome sequencing (WES) data from a classical Hodgkin lymphoma patient obtained before pembrolizumab treatment and at relapse

  This dataset contains raw paired-end whole-exome sequencing (WES) FASTQ files generated from plasma-derived cell-free DNA (cfDNA) collected from a patient with classical Hodgkin lymphoma before pembrolizumab treatment and at the time of relapse, together with a matched normal sample. Libraries were prepared using a whole-exome capture kit and sequenced on the Element AVITI platform to generate 2 × 150 bp paired-end reads. The submitted data comprise the primary sequencing output in gzipped FASTQ format.

  Dataset EGAD50000002869

• Familial Melanoma Sequencing

  In this experiment we have sequenced the exome of 15 individuals from eight families who have familial melanoma. By sequencing the exome we hope to be able to identify new genes that are associated with this disease.

  Study EGAS00001000017

• 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

• Bulk RNA sequencing of 36 multi-region IPMN–PDAC tumours comprising 160 sequencing runs

  This dataset contains bulk RNA sequencing data generated from 36 multi-region tumour samples obtained from patients with intraductal papillary mucinous neoplasms (IPMN) and associated pancreatic ductal adenocarcinoma (PDAC). A total of 160 sequencing runs are included. Libraries were prepared from poly(A)-selected RNA and sequenced on an Illumina platform. The data are provided as raw sequencing files for downstream transcriptomic analyses.

  Dataset EGAD50000002215

• Single-cell profiling of peripheral blood from treatment-naïve GBM patients and healthy donors.

  Glioblastoma (GBM) induces systemic immune reprogramming characterized by altered circulating myeloid and lymphoid populations. Single-cell profiling of peripheral blood from treatment-naïve GBM patients identified heterogeneous monocyte states, expansion of suppressive myeloid cells, reduced MHC class II expression and distinct GBM-associated immune signatures. These findings support peripheral blood immune profiling as a potential source of biomarkers in GBM.

  Study EGAS00001008497

• single-cell RNA-Seq data of Circulating immune profiling reveals impaired monocyte states and trajectories driving immunosuppression in glioblastoma

  This dataset contains single-cell RNA sequencing data generated from human PBMC obtained from 10 GBM patients and 5 healthy donors. The main objective of this study was to map the differentiation continuum and transcriptional landscape of peripheral blood mononuclear cells in primary glioblastoma patients at the single-cell level to identify specific systemic immune signatures. Libraries were prepared using the Chromium Next GEM Single Cell 3’ GEM (10x Genomics, Pleasanton, CA, USA) and sequenced on an Illumina NextSeq 500/550 or an Illumina NovaSeq 6000 system. This dataset comprises raw FASTQ files and gene expression count matrices. Access to these data is controlled and managed by the Luxembourg Institute of Health (LIH) Data Access Committee (DAC).

  Dataset EGAD50000002932

• Spatial atlas of diffuse large B-cell lymphoma

  We leveraged highly multiplexed, single-cell–resolution spatial transcriptomics, bulk RNA sequencing, and tumor–germline paired whole-exome sequencing to profile 465 diffuse large B-cell lymphoma (DLBCL) tumors and define the assembly of 60 lymphoma microenvironment (LME) cell subsets and 5 tumor B cell states into conserved spatial niches and communities that resemble non-malignant lymphoid architecture. Three distinct LME-enriched communities were assembled from combinations of niches and reflected recently described LME archetypes with conserved spatial biology. Tumor B cells were enriched in three B communities harboring distinct, developmentally linked, transcriptional states associated with divergent cell-cell communication (CCC) pathways. Intratumoral heterogeneity in B communities was pervasive across patients and largely unlinked with molecular subtype. Combinations of B communities, rather than single states, were associated with patient outcome, implicating microenvironment-associated tumor B cell transcriptional plasticity in the biology and clinical behavior of DLBCL.

  Study EGAS50000002037

• Spatial atlas of diffuse large B-cell lymphoma

  We leveraged highly multiplexed, single-cell–resolution spatial transcriptomics, bulk RNA sequencing, and tumor–germline paired whole-exome sequencing to profile 465 diffuse large B-cell lymphoma (DLBCL) tumors and define the assembly of 60 lymphoma microenvironment (LME) cell subsets and 5 tumor B cell states into conserved spatial niches and communities that resemble non-malignant lymphoid architecture. Three distinct LME-enriched communities were assembled from combinations of niches and reflected recently described LME archetypes with conserved spatial biology. Tumor B cells were enriched in three B communities harboring distinct, developmentally linked, transcriptional states associated with divergent cell-cell communication (CCC) pathways. Intratumoral heterogeneity in B communities was pervasive across patients and largely unlinked with molecular subtype. Combinations of B communities, rather than single states, were associated with patient outcome, implicating microenvironment-associated tumor B cell transcriptional plasticity in the biology and clinical behavior of DLBCL.

  Study EGAS50000002036

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  DAC for RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  Dac EGAC50000000627

• DAC_RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Data access committee for RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Dac EGAC50000000352

• Spatial atlas of diffuse large B-cell lymphoma

  Bulk RNA sequencing libraries were prepared from diffuse large B-cell lymphoma tumor samples and sequenced using paired-end Illumina sequencing for transcriptome profiling.

  Dataset EGAD50000002927

• Spatial atlas of diffuse large B-cell lymphoma

  Whole-exome sequencing libraries were prepared from genomic DNA isolated from diffuse large B-cell lymphoma tumor biopsies and matched normal samples using exome capture followed by paired-end Illumina sequencing.

  Dataset EGAD50000002928

• 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

• 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

• 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

• Dataset related to ""Ex vivo therapy-driven selection of glioblastoma stem-like cells models resistance evolution"

  RNA-seq and NGS target panel dataset related to "Ex vivo therapy-driven selection of glioblastoma stem-like cells models resistance evolution"

  Dataset EGAD50000002898

• 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

• Single-nuclei RNAseq of normal human choroid and uveal melanoma

  Single-nuclei RNAseq of normal human choroid and uveal melanoma

  Study EGAS00001004955

• Single-nuclei RNAseq of normal human choroid and uveal melanoma

  Single-nuclei RNAseq of normal human choroid and uveal melanoma. Libraries were prepared using the Chromium Single Cell 3' Reagent Kits v3,. Paired-end libraries were sequenced on a NovaSeq X instrument (Illumina).

  Dataset EGAD50000002941

• 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

• Transcriptional alterations induced by BET inhibitor and Omaveloxolone combination in acute myeloid leukemia cells

  Kasumi-1 and OCI-AML3 cells treated for 24h with BETi and Oma in hypoxia (1% O2) or normoxia (20% O2) were used for RNA extraction and hybridization on microarrays.

  Dataset EGAD00010002852

• Distinct molecular profiles characterize the spontaneous growth rate of IDHmt low-grade astrocytomas and oligodendrogliomas

  The life expectancy of patients with diffuse IDH-mutant low-grade gliomas (IDHmt LGG) ranges from 5 to over 20 years. Tumor behavior, including spontaneous growth rate, varies even within homogeneously classified subtypes of oligodendroglioma and astrocytoma. Risk-adjusted treatment strategies are needed to avoid therapy-related toxicities without compromising outcome. The spontaneous tumor volume growth rate (TVGR) serves as a prognostic marker and predicts response to therapy. Accurate prediction of TVGR through biomarkers would enable improved evidence-based risk management.

  Study EGAS50000002072

• 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