8432 results for "canc*"

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• (h)MeDIP-Seq of high-risk prostate cancer

  Immunoprecipitation of methylated and hydroxymethylated DNA was performed on DNA isolated from tumoral and non-tumoral prostate tissue of patients with high-risk disease. Samples were sequenced on the Illumina HiSeq as 50 bp single end.

  Study EGAS00001001019

• FinHer_Breast_Cancer_Study

  The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.

  Study EGAS00001000648

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma

  A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames. To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a step-wise approach to employ multiple CRISPR-Cas9 screens to elucidate functional non-canonical ORFs implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream open reading frames (uORFs) exhibited selective functionality independent of the main coding sequence. One of these, ASNSD1-uORF or ASDURF, was upregulated, associated with the MYC family oncogenes, and was required for medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future cancer genomics studies seeking to define new cancer targets.

  Study EGAS00001007426

• 54 metastatic colorectal cancer patients from Schleswig-Holstein in North Germany

  Personalized treatment vs standard of care is much debated, especially in clinical practice. Here we investigated whether overall survival differences in metastatic colorectal cancer patients are explained by their tumor mutation profiles or by their treatment differences in real clinical practice.

  Study EGAS00001004108

• CRC Promoter capture Hi-C

  Genome organisation determines chromosome interactions between regulatory elements, such as promoters and enhancers, influencing gene expression. Despite the fact that it is possible to assess whether a gene is actively transcribed, it has been challenging to point out the genomic regions that are involved in the regulation of a particular gene. We are interested in better understanding the interactions between promoters and their regulatory elements in colorectal cancer in order to unveil novel non-coding regions which might have a role in tumour development. To do so, we utilise the HiC method complemented with promoter capture in combination with NGS to map promoter interactions in two CRC cell lines, representing two distinct CRC subtypes.

  Study EGAS00001001946

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Metastatic_breast_cancer_targeted_gene_screen

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations.

  Study EGAS00001000704

• Precursor_lesions__clonal_architecture_and_relapse_in_Wilms_nephroblastoma

  Targeted resequencing at high depth (21 genes, 9 chromosomal regions): at least 4 FFPE samples per case and matched germline DNA: •100 cases with detailed outcome data, including 15 cases with tumour relapse (515 samples)•40 cases with matched pre-chemotherapy biopsies (240 samples)•50 nephrogenic rests matched to above cases (50 samples)We expect a proportion (possibly 10%) of cases to be mutationally silent on the above studies, and propose to subsequently carry out integrated whole-genome, methylome and transcriptome studies on matched frozen tissue from these cases

  Study EGAS00001001422

• Spatiotemporal evolution and inter-patient heterogeneity in primary and recurrent/metastatic head and neck squamous cell carcinoma

  Head and neck cancer squamous cell carcinomas (HNSCCs) are heterogeneous in terms of origin and aetiology. In addition, there is uncertainty about the spatiotemporal genetic evolution from initial diagnosis to recurrence/metastasis (R/M) after primary treatments and further disease progression following systemic treatment. Changes in the genetic profile have implications on the selection of appropriate treatments for patients, especially in the era of targeted therapies and immunotherapies. Here, we analysed a cohort of 11 HNSCC patients with metachronous R/M, among whom nine had paired primary and R/M samples suitable for next-generation sequencing (multiple R/M samples collected at different time points were available for some of the patients). At the genomic level, the R/M samples shared a fraction of the somatic single nucleotide variants (SNVs) with the index primary tumours, but they also acquired many additional mutations, while losing only a few others. A similar behaviour was also observed when examining the changes of mutational signatures between primary and R/M samples. Overall, R/M appeared thus more genetically diverse than the respective primary tumours. The transcriptomic analysis showed that R/M samples had lower immune cell infiltration and several genes related to immune response were significantly downregulated compared to the primary samples. Our results underline the importance of analysing multiple samples per patient to obtain a more complete picture of the patient’s tumour and advocates a re-biopsy in the event of R/M and treatment failure, in order to select the most appropriate therapeutic strategy.

  Study EGAS00001007464

• Heterogeneous Genomic Evolution and Immune Microenvironments in Metastatic Lung Cancer

  The mechanism underlying the occurrence of lung cancer metastasis to different tissues/organs remains elusive. We investigated the genomic evolution and immune microenvironments of paired primary-metastatic tumors by employing multi-region whole-exome sequencing in 179 samples of 106 tumors from 51 lung cancer patients and subsequent immunohistochemistry assays in 70 of them. Our data revealed differences in genomic landscapes, molecular determinants, evolutionary dynamics, and lymphocyte infiltration among different metastatic sites. We demonstrated commonly late arising of metastatic seeding of lung cancer with quantitative evidence. Most distant metastases originated from independent origins of earlier lymph node spreads. Immune-heterogeneity and -homogeneity were primarily driven by arm-level and focal copy number events in primary tumors, respectively. These findings implied the combinatorial role of multiple factors in shaping patterns of dissemination and advanced the clinical evaluation and intervention of lung cancer metastasis.

  Study EGAS00001004228