7792 results for "canc*"

in 15.75 milliseconds.

• Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare and lethal tumor in adolescent and young adult patients. Currently, there is no standard-of-care treatment for these patients. Reliable models that represent this disease and can be used for translational research are scarce. To model SCCOHTs, we have established eight patient-derived tumoroid lines from tumor lesions of three patients with SCCOHT. The tumoroids recapitulate genomic and transcriptomic characteristics of the corresponding patient tumors and capture intrapatient tumor heterogeneity. Organoid drug profiling using a library of 153 clinical compounds identified methotrexate as an effective and selective drug against SCCOHTs with a clinically relevant IC50 of 35 nmol/L. RNA sequencing demonstrated that methotrexate induced TP53 pathway activation and apoptosis. These data underscore that organoid technology can support the design of therapeutic strategies for rare cancers.

  Study EGAS00001007911

• Multi-Layered Molecular Profiling Informs the Diagnosis and Targeted Therapy of Desmoplastic Small Round Cell Tumor

  Desmoplastic small round cell tumor (DSRCT) is an ultra-rare soft tissue sarcoma with dismal prognosis and limited therapeutic options. Here, we identified individual therapeutic targets in a cohort of 30 DSRCT patients by use of multilayered molecular profiling (genomic, transcriptomic, and (phospho-)proteomic analyses) within the DKFZ NCT DKTK MASTER program. 28 of the 30 patients received at least one personalized treatment recommendation. In line with the observation that DSRCTs are an entity with a low mutational load, most of the treatment recommendations were based on target gene or -protein expression. 13 patients received a recommended therapy, resulting in four partial responses, four stable diseases, and five progressive diseases. Eight of 13 patients received the multi tyrosine kinase inhibitor pazopanib, with mixed response. Based on high ERBB2 expression levels, two patients received the antibody drug conjugate trastuzumab deruxtecan (T-DXd), showed exceptional, long-lasting responses and are currently (8/2024) still on treatment and progression-free. We detected high ERBB2 protein expression in all DSRCT samples with proteome data (n = 9), which suggests that ERBB2 may be a particularly useful therapeutic target for DSRCT patients. For one of the two exceptional responders we did not detect a substantial ERBB2/HER2 overexpression, which may indicate that T-DXd could also be efficacious in DSRCT patients with low levels of HER2, as also described for breast cancer patients. In conclusion, multi-omic molecular profiling revealed personalized therapeutic targets in patients with DSRCT with HER2 targeting, with T-DXd as a promising therapeutic option for this ultra-rare and difficult-to-treat tumor entity.

  Study EGAS00001007934

• Integrated genomic analysis for HCC

  Liver cancer is a common malignancy and is the third cause of cancer-related death in the world and hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for ~90% of cases. Only 20 ~ 30% of patients can benefit from combined immunotherapy and targeted therapy due to the high inter-tumor heterogeneity of HCC. This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) and/or RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the great consistence between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. And we further characterized HCC subtypes using genomic, transcriptomic and clinicopathological features. Among 9 subtypes, 5 subtypes belonged to chromosome instable tumors, while 3 subtypes belonged to chromosome stable tumors. In addition, our subtypes were associated with prognosis and we also found different distributions of subtypes across various features, such as etiology and gender. Our study provided a robust molecular classification based on a large HCC dataset from Western country, it improves our understanding of the mechanisms of carcinogenesis and will facilitate development of genome-based precision medicine in HCC.

  Study EGAS00001007957

• Beyond BRCA deficiency: Clinical and molecular predictors of survival in patients with BRCA-deficient tubo-ovarian high-grade serous carcinoma

  Homologous recombination DNA repair deficient (HRD) tumors account for about 50% of tubo-ovarian high-grade serous carcinomas (HGSC) and are associated with a high response to platinum-based chemotherapy. However, a subset of patients with HRD tumors have unexpected resistance to chemotherapy and experience short survival. Our study compared BRCA-deficient and proficient HGSC among patients with short (<3 years, the lowest quartile of overall survival (OS)) versus longer-term (>3 year OS) to identify prognostic markers and potential therapeutic opportunities. Primary tumors from a cohort of patients with advanced-stage HGSC (n=154) enriched for those with HRD tumors and short survival (n=42) were analyzed using whole-genome sequencing, bulk RNA-sequencing, and DNA methylation profiling. A subset of HRD tumors (n=143) were characterized for immune cell densities by multiplex immunofluorescence. Clinicopathological features were assessed in 1,389 patients with HGSC, including 282 with pathogenic germline BRCA variants (gBRCApv). Findings were validated in two international HGSC cohorts: the Ovarian Tumor Tissue Analysis consortium (n=5,875) and Multisciplinary Ovarian Cancer Outcome Group (n=895). In gBRCApv-carriers, residual disease following surgical cytoreduction was not associated with shorter OS unlike in non-carriers where it was strongly associated. While most patients with gBRCApv had a more favorable OS compared to non-carriers, a survival advantage was not apparent in those with variants located outside of BRCA1 exon 10/23 and BRCA2 exon 11/27. Patient survival correlated with HRD score, such that those with a score ≥63 had significantly longer OS compared to those with HRD scores of 42-63 and <42. While higher HRD scores were associated with better survival outcomes, most gBRCApv carriers with a short survival had tumor HRD scores that exceeded the threshold typically considered predictive of a good response to carboplatin or PARP inhibitors. BRCA2-deficient HGSC with loss of the tumor suppressor NF1 was associated with exceptionally favorable outcome (median OS 17 years), whereas amplification of both PIK3CA and RAD21, was associated with poor outcome in BRCA2-deficient HGSC (median OS 2.9 years). The density of tumor-infiltrating CD8+ PD-1+ T cells was prognostic for OS in gBRCApv-carriers. In summary, rather than simply the presence or absence of a germline BRCA pathological variant influencing patient survival, the co-occurrence of specific somatic gene alterations, the extent of immune cell infiltration, the level of homologous recombination deficiency, and BRCA-variant location may modify clinical outcomes in patients with BRCA-deficient HGSC. Analysis of exceptional outcome patients, in this case gBRCApv-carriers with an atypically short survival, may identify determinants of outcome applicable to the wider HGSC patient population.

  Study EGAS00001008059

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• This study generated Oxford Nanopore long read sequencing data of cancer cell line mixtures for validating long-read variant calls in cancer genomics

  Long-read sequencing (LRS) improves genome alignment and facilitates resolving variants in complex genomic regions, making it a promising approach for cancer variant detection and biomarker discovery. Here, we evaluate the performance of LRS to detect somatic variants across different tumour purities and sequencing depths by comparing to somatic variants from short-read sequencing. We generated experimental mixtures of cancer cell lines and matched normal cell lines to simulate 10 tumour purities (ranging from 0 to 100% tumour content). This resulted in 22 samples which were sequenced using whole genome LRS to a targeted depth of 60x and somatic variants were identified. We downsampled sequencing data to explore the optimal read depth for somatic variant detection. Our results show that long-read variant calling tools achieve recall rates comparable to short-read gold standards. While a tumour sequencing depth of 30x to 60× is generally sufficient for detecting common variants, particularly structural variants (SVs), sequencing the matched normal sample at adequate depth is crucial for accuracy. Notably, we found variants unique to LRS that may represent real and previously undetected events. This study highlights key factors for optimising cancer genome sequencing with LRS and provides a comprehensive dataset of cell line mixtures for future research and tool development.

  Study EGAS00001008107

• Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma

  The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT’s regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation. Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as druggability for future translational studies and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.

  Study EGAS00001008140

• Single cell TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008161

• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Cold Ischemia Study

  This study aimed to evaluate the impact of cold ischemia time on the expression of cancer-related genes, particularly those involved in hypoxia, apoptosis, and epithelial-to-mesenchymal transition (EMT). We performed RNA sequencing on 54 normal colon mucosa samples from nine patients undergoing colorectal cancer surgeries, freezing samples at predefined intervals ranging from 0 to 60 minutes. A total of 44 differentially expressed genes (DEGs) (p < 0.05) were identified when comparing samples frozen immediately (T0) with those frozen after 60 minutes (T5).

  Study EGAS00001008233

• Colorectal Microenvironment Spatial Mapping

  In colorectal cancer (CRC), interactions between tumor and immune cells within the tumor microenvironment are critical drivers of tumorigenesis, immune evasion, prognosis, and therapeutic response. Therefore, a deeper understanding of the spatial organization of cancer and immune cells within the CRC microenvironment is urgently needed. In this study, we aimed to characterize distinct cell populations and patterns of spatial gene expression associated with CRC tumorigenesis and immune infiltration. Spatial transcriptomics (ST) was performed on CRC and adjacent normal tissues to investigate the patterns of gene expression. Integrative ST data and publicly available single-cell RNA sequencing (scRNA-seq) data analysis tools were used for data integration, dimension reduction, clustering, and differential expression analysis. This study identified novel immunosuppressive cell populations and immune regulatory factors in CRC. Further functional validation of these findings will be essential to assess their potential as therapeutic targets.

  Study EGAS00001008254

• Organoid_Derivation_Project___GRCh38___TGS

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001007349

• Endocrine therapy reprogramming of breast cancer facilitates metastatic escape via upregulation of P-Rex1/Rac1 signalling

  The estrogen receptor (ER) drives growth in ~70% of breast cancers, and endocrine therapies prevent recurrence. However, 30% of patients recur, with many fatal cases occurring late (after >5 years), presenting a challenge due to their often non-proliferative nature and limited options. To study this, we generated slow-growing resistant cells that form small primary tumours but readily metastasize. Single-cell RNA sequencing (scRNAseq) revealed that endocrine therapy reprograms these cells, notably upregulating the Rac1 signalling component P-Rex1. We found in clinical cohorts that P-Rex1 in high in ER+ breast cancer. Intravital imaging demonstrated that Rac1 signalling is active in ER+ cells following endocrine therapy. Targeting the Rac1 pathway with small molecule inhibitors (NSC23766, R-ketorolac) reduced survival and motility in resistant cells, inhibited in vivo Rac1 activity, and reduced tumour burden when combined with tamoxifen in a drug-refractory patient-derived xenograft. This work identifies the P-Rex1/Rac1 axis, as a potential therapeutic target for late recurring ER+ breast cancer.

  Study EGAS00001008353

• Plasma CTCF ChIP-seq Reveals Cancer-Associated cfDNA Binding Profiles

  Cell-free DNA (cfDNA) in plasma predominantly exists as nucleoprotein complexes. Although circulating CTCF-bound cfDNA (cfCTCF-DNA) has previously been reported, the occupancy of individual CTCF binding sites in plasma has not been systematically characterised. This study describes the isolation of endogenous plasma cfCTCF-DNA by chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) in samples obtained from cancer patients and healthy individuals. A two-step enrichment strategy was employed, combining physical removal of background cfDNA by immunoprecipitation with bioinformatic filtering to remove residual non-CTCF-derived sequences. Sequencing reads were aligned to the UCSC hg38 reference genome using BWA-MEM v0.7.17 and processed to generate CRAM files containing alignments restricted to the primary chromosomes (chr1–chr22, chrX, chrY and chrM). CTCF-associated cfDNA fragments were classified according to their similarity to a consensus CTCF binding motif, enabling discrimination between low-affinity and high-affinity CTCF binding sites. Comparative analyses identified quantitative and qualitative differences in plasma cfCTCF-DNA profiles between healthy individuals and patients with cancer. The deposited dataset comprises plasma cfCTCF-DNA ChIP-seq data from four clinical cohorts and includes both CTCF-enriched and total cfDNA samples where applicable. These data support the investigation of CTCF occupancy patterns as a novel class of liquid biopsy biomarkers for cancer detection and monitoring.

  Study EGAS50000001937

• Measurement of altered CTCF binding in cancer using ChIP-seq

  Sequencing data for the paper: Direct analysis of transcription factor protected cfDNA in plasma by ChIP-seq: Measurement of altered CTCF binding in cancer is a novel biomarker for liquid biopsy. This dataset contains 160 CRAM files containing Illumina NovaSeq reads aligned using BWA to the UCSC hg38 reference. These 160 samples belong to four experiments - a 70 sample development cohort, a 24 sample validation cohort, a second 58 sample validation cohort and eight samples from an enrichment recovery experiment, consisting of a CTCF and a Total sample from each of four cancer patients.

  Dataset EGAD50000002809

• Multi-omic signatures in multiple myeloma

  Multiple myeloma (MM) is a genetically and clinically heterogeneous plasma-cell malignancy. Quadruplet therapy, combining anti-CD38 antibodies, immunomodulatory drugs, proteasome inhibitors, and dexamethasone, is now the standard induction treatment for newly diagnosed multiple myeloma (NDMM). To gain a comprehensive view of molecular changes in MM and their association with treatment response in this new standard care, we performed a multi-omic study of 423 NDMM from the MIDAS trial.

  Study EGAS50000001573

• Dataset of scRNAseq from 56 CRC, treatment-naive and post-chemotherapy

  The dataset includes FASTQ source files of scRNA-seq for 56 CRC patients, sequenced with Illumina 10x platform. All patients were diagnosed with colorectal cancer between 2014 and 2022 at the Gustave Roussy Institute. Cohort includes 32 samples from untreated patients and 24 samples from patients who received chemotherapy. Chemotherapy included FOLFOX or FOLFIRI as first line, in some cases in combination with anti-VEGF or anti-EGRF drugs (avastin, bevacizumab or cetuximab) as the second and third lines. The post-treatment cohort included 18 responders (partial response, stable disease and complete response) and 6 progressors (progressive disease).

  Dataset EGAD50000001218

• Asan Medical Center Data Access Committee

  This Data Access Committee is responsible for reviewing and approving data access requests for human genomic and clinical datasets deposited at the EGA by Asan Medical Center, in order to protect the sensitive information of patients. The committee oversees a range of data types, including sequencing, variant profiling, and transcriptomic data across multiple cancer types and research projects. Data access requests require an approved ethical research plan and are limited to legitimate biomedical research use in accordance with the terms of the associated Data Access Agreement.

  Dac EGAC50000000439

• The evolving genomic landscape of circulating tumor DNA represents an early predictor of immunotherapy response in lung cancer

  Circulating tumor DNA (ctDNA) analyses are informative as an early indicator of immunotherapy response in advanced non-small cell lung cancer (NSCLC), however the clinical role of ctDNA molecular response requires further validation. As part of a prospective clinical protocol (NCT05995821), we performed ctDNA (n=328) and matched white blood cell DNA (WBC; n=109) targeted error-correction sequencing from 109 patients with advanced/metastatic NSCLC who received anti-PD-(L)1 as monotherapy or in combination. Following variant cellular origin resolution, landmark molecular response (mR) was defined as undetectable ctDNA within 3-9 weeks of treatment initiation. Among 2,818 plasma variants, 23% were clonal haematopoiesis-related, which confounded driver gene associations with clinical outcomes and molecular responses. Implementing a tumor-naïve WBC DNA-informed approach increased the number of evaluable cases while maintaining the overall accuracy of landmark ctDNA molecular responses. Pre-treatment ctDNA burden but not blood tumor mutation burden predicted survival. A significant enrichment in landmark ctDNA mR was noted among patients with progression-free survival (PFS) ≥6 months with immunotherapy (p=2.5e-05) and chemo-immunotherapy (p=0.02). Patients in the landmark mR group attained longer progression-free (p=1.6e-06) and overall survival (p=2.5e-05) compared to those with molecular progression. Our findings indicate that landmark ctDNA molecular response provides a real-time and accurate approach for monitoring immunotherapy clinical outcomes. Although not currently validated for regulatory use, these findings demonstrate the potential utility of ctDNA as an early endpoint in clinical trials.

  Study EGAS50000001957

• Dataset for "The evolving genomic landscape of circulating tumor DNA represents an early predictor of immunotherapy response in lung cancer"

  Dataset for the study "The evolving genomic landscape of circulating tumor DNA represents an early predictor of immunotherapy response in lung cancer". This study has 437 samples and the corresponding bam from TEC-seq

  Dataset EGAD50000002837

• Data access committee for study: "Landmark ctDNA molecular response represents an early predictor of immunotherapy outcomes in lung cancer"

  This is the Data Access committee that regulates access to the sequence data for the study: "Landmark ctDNA molecular response represents an early predictor of immunotherapy outcomes in lung cancer".

  Dac EGAC50000000787

• Wellcome LEAP TNBC cohort raw sequencing data

  This study contains controlled-access raw sequencing data from the retrospective Wellcome LEAP triple-negative breast cancer cohort. The data include human patient-derived single-nucleus RNA-seq and 10x Visium spatial transcriptomics generated from pre- and post-treatment tumour samples. The first dataset linked to this study supports the Victori et al. Cell Reports Medicine manuscript and includes raw FASTQ files from the relevant sequencing runs. Because some snRNA-seq libraries were generated from multiplexed pools, some raw FASTQ files may include additional co-multiplexed LEAP samples beyond those directly analysed in that manuscript. Access is controlled through the appropriate LEAP Data Access Committee and policy.

  Study EGAS50000001956

• Wellcome LEAP TNBC Data Access Committee

  Data Access Committee for controlled-access human patient-derived sequencing data from the Wellcome LEAP triple-negative breast cancer study

  Dac EGAC50000001072

• Synthetic longitudinal breast cancer whole-genome sequencing dataset

  This study contains fully simulated longitudinal whole-genome sequencing data for one synthetic female breast cancer patient. It includes one matched-normal paired-end sample generated at a nominal depth of 30x and three longitudinal tumour samples generated at a nominal depth of 60x.

  Study EGAS50000001932

• Non-invasive anal (pre)cancer dataset DAC

  Dac EGAC00001003635