Search Results - EGA European Genome-Phenome Archive

Single_cell_resolution_of_human_CNV_body_map

12 tissues from the warm autopsy are selected for this project. Using 10X Chromium technology we will generate ~1000 single cell/nulei genomic libraries per tissue. Each tissue will be whole genome sequenced (~2 lanes per 1000 cells) on hiseq X10. per single cell we will generate CNV profile and we investigate the level of genomic heterogenity with in tissue and across different tissues.

Study EGAS00001003162

Persistence of circulating tumor DNA in breast cancer patients during neoadjuvant treatment is a significant predictor of poor tumor response

Purpose:Accurate assessment of response during neoadjuvant systemic treatment (NST) poses a major clinical challenge. Therefore, a minimally-invasive assessment of tumor response based on cell-free circulating tumor DNA (ctDNA) may be beneficial to guide treatment decisions.Experimental Design: We profiled 93 genes in tissue from 193 early breast cancer patients. Patient-specific assays were designed to track ctDNA during NST from 145 patients with available plasma. ctDNA presence and levels were correlated with complete pathological response (pCR) and residual cancer burden (RCB) as well as with clinicopathologic characteristics of the tumor to identify potential proxies for ctDNA release. Moreover, we tested the predictive value of driver events identified in the tumor.Results:At baseline, ctDNA could be detected in 63/145 (43.4%) patients and persisted in 25/63 (39.7%) patients at mid-therapy (MT) and 15/63 (23.8%) patients at the end of treatment. ctDNA detection at MT was significantly associated with higher RCB (OR 0.062, 95% CI 0.01-0.48, P=0.0077). Out of 31 patients with detectable ctDNA at MT, 30 patients (96.8%) were non-responders (RCB II, n=8; RCB III, n=22) and only one patient responded to the treatment (RCB I). Considering all 145 patients with baseline (BL) plasma, none of the patients with RCB 0 and only 6.7% of patients with RCB I had ctDNA detectable at MT, while 30.6% and 29.6% of patients with RCB II/III, respectively, had a positive ctDNA result. Conclusion:Overall, our results demonstrate that the detection and persistence of ctDNA at mid-therapy may have the potential to negatively predict response to neoadjuvant treatment and identify patients who will not achieve pCR or be classified with RCB II/III.

Study EGAS00001005798

Sequencing of cancer autopsies and ctDNA

Tumor heterogeneity is a major obstacle for precision oncology strategies. To characterize inter-lesion heterogeneity in pre-treated cancers, we performed genetic and transcriptomic profiling of synchronous lesions from ten rapid autopsies comprising six cases of breast cancer, three of cholangiocarcinoma and one lung cancer case. For nine patients, we studied mutation representation in circulating cell-free DNA (cfDNA).

Study EGAS00001005109

Whole genome sequencing of a breast cancer cohort with known functional homologous recombination status

Optimal patient selection for PARP inhibitors and double strand break (DSB) inducing chemotherapy is of great clinical importance. In principle, the use of these therapies can be extended beyond germline BRCA1/2 mutated cancers. Although several methods for detection of BRCA-like tumors have been developed, a golden standard is lacking. We have developed the RECAP test, a functional HR assay exploiting the formation of RAD51 foci in proliferating cells after ex vivo irradiation of fresh primary breast cancer (BrC) tissue. The RECAP test seems robust and has an advantage over genetic tests, due to its functional character for exploring the HR phenotype. Another type of HRD test is the BRCAness classifier, which is based on specific genomic patterns derived from copy number data of BRCA1/2 mutated BrCs that also occur in sporadic cancers. The BRCAness classifier is a robust test that is easily applicable in the clinic and has also been validated to predict in vivo response to high dose chemotherapy in clinical trials. More recently, a new HRD test based on genomic signatures which can be extracted from whole genome sequencing has been published, HRDetect. Studies comparing these different HRD tests within the same cohort of patients do not yet exist. Here, we have the unique opportunity to compare three HRD tests within the same cohort. We aim to compare three different HRD tests (RECAP, BRCAness classifier and HRDetect) within the same cohort of primary BrCs (n=41). As a secondary aim, we will analyze additional genetic alterations in HRD tumors (both BRCA-deficient and BRCA-proficient HRD tumors).

Study EGAS00001005572

Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

Study EGAS00001005584

A living biobank of breast cancer organoids captures disease heterogeneity

Breast Cancer (BC) comprises multiple distinct subtypes that differ genetically, pathologically, and clinically. Xeno-transplantation and direct culturing of tumor tissue are increasingly used in drug development and personalized medicine strategies. Here, we describe a robust protocol for long-term culturing of human mammary epithelial organoids. Using this protocol, 101 BC organoid lines were generated, broadly recapitulating the diversity of the disease. BC organoid morphologies typically matched the histopathology, hormone receptor-, and HER2 status of the original tumor. DNA copy number variations as well as sequence changes were consistent within tumor-organoid pairs and largely retained even after extended passaging. BC organoids furthermore populated all major gene expression-based classification groups and allowed drug screens in vitro and upon xenotransplantation. This study describes a representative collection of well-characterized BC organoids available for cancer research and drug development, as well as a strategy to assess in vitro drug response in a personalized fashion.

Study EGAS00001002158

Somatic_mutation_in_skin_epidermis__SMS_

We aim to assess the range and depth of mutations in genes linked with cancer in skin epidermis surrounding lesions which are undergoing surgical removal. Patient history will be collected to provide a detailed outline of tumour type (including histology), skin type, and sunlight exposure. We will perform ultra-deep targeted sequencing using genes implicated in cancer to try and understand the background of mutations surrounding these lesions

Study EGAS00001002165

Genetics and therapeutic responses to TIL therapy of pancreatic cancer PDX models

Pancreatic cancer is the 7th leading cause of cancer-related deaths worldwide. Checkpoint immunotherapy has not yet showed encouraging results in pancreatic cancer possibly owing to a poor immunogenicity and/or an immune suppressive microenvironment. The aim of this study was to develop patient-derived xenografts (PDX) models and to assess if autologous tumor-infiltrating lymphocytes (TILs) would have anti-tumoral activity in pancreatic cancer. Tumor biopsies from 29 patients were subcutaneously transplanted into NOG mice. Tumor growths were confirmed in 11 out of 29 transplantations. The PDX tumors histologically resembled their original biopsies, but since stromal cells in the PDX model tumors were from mouse, their gene expression differed from the original biopsies. Immune checkpoint ligands other than PD-L1 were expressed in pancreatic cancers but PD-L1 was rarely expressed. One of the three tumors that did express PD-L1 was an adenosquamous cancer and another had a mismatch repair deficiency. TILs were expanded from six tumors and were injected into NOG or human interleukin-2 transgenic-NOG (hIL2-NOG) mice carrying PDX tumors. Regression of tumors could be verified in hIL2-NOG mice in 3 of the 6 PDX models treated with autologous TILs, including the adenosquamous PDX model. In conclusion, PDX models of pancreatic cancer can be used to learn more about tumor characteristics and biomarkers, and to evaluate responses to ACT and combination therapies. The major benefit of the model is that modifications of T cells can be tested in an autologous humanized mouse model to gain preclinical data to support the initiation of a clinical trial.

Study EGAS00001005596

COIN CRC GWAS data

Genotype data from the COIN and COIN-B trials of advanced/metastatic colorectal cancer. Data provided in plink format, and has been quality controlled. Control data used was from the WTCCC2 project National Blood Donors (NBS) Cohort (EGAD00000000024).

Study EGAS00001005421

Gene expression-based prediction of pazopanib efficacy in sarcoma (HIPO, H021)

The multi-receptor tyrosine kinase (RTK) inhibitor pazopanib is approved for the treatment of advanced non-adipocytic soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to date to select patients who are most likely to benefit from this drug. We analyzed the molecular profiles and clinical outcomes of pazopanib-treated sarcoma patients enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing (WGS/WES) and transcriptome sequencing to inform the care of adults with advanced cancer across histologies who are younger than 51 and patients with rare tumors, including rare subtypes of more common entities, regardless of age. Among a total of 109 patients with available WGS/WES data, there was no correlation between clinical parameters, specific genetic alterations, or mutational signatures and clinical outcome. In contrast, analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR]=0.53, p=0.021), IGF1R (HR=1.82, p=0.027), and KDR (HR=0.50, p=0.011) were independently associated with progression-free survival (PFS). Based on the expression of these RTK genes, i.e., the features NTRK3-high, IGF1R-low, and KDR-high, we developed a pazopanib efficacy predictor (PEP) that stratified patients into three groups with significantly different PFS (p<0.0001). Application of the PEP to an independent cohort of pazopanib-treated sarcoma patients from DKTK MASTER (n=43) confirmed its potential to separate patient groups with significantly different PFS (p=0.02), whereas no such association was observed in sarcoma patients from DKTK MASTER (n=77) or The Cancer Genome Atlas sarcoma cohort (n=256) who were not treated with pazopanib. A score based on the combined expression of NTRK3, IGF1R, and KDR allows identification of sarcoma patients with good, intermediate, and poor outcome following pazopanib therapy and warrants investigation as a predictive tool in prospective studies to optimize the use of this drug in the clinic.

Study EGAS00001005836

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