5731 results for "canc*"

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• MED12L Gene Alterations Define Aggressive BRCA2-Mutant Prostate Cancers

  Germline mutation of BRCA2 increases the lifetime risk of developing prostate cancer (PCa) by over 700%. BRCA2-mutant PCa have poorer prognosis than sporadic PCa, with rapid development of metastatic, castrate-resistant prostate cancer (mCRPC) and 5-year cancer-specific survival rates of ~50-60%1-4. Despite this, unique genomic driver events that explain the aggressiveness of localized BRCA2-mutant PCa are lacking. We used whole-genome sequencing to fully characterize 14 BRCA2-mutant PCa and demonstrate that BRCA2-mutant PCa is associated with increased genetic instability and a mutually exclusive mutational burden when compared to sporadic PCa. Importantly, BRCA2-mutated cancers are defined by unique copy number gains and hypomethylation events, including alterations in the MED12L/MED12 axis, which are found solely in mCRPC and are enriched in PCa tumours harbouring aggressive intraductal carcinoma (IDC-P) pathologic sub-types. Our findings begin to explain the clinical entity of BRCA2-mutated PCa as these tumours have a unique and aggressive genotype de novo, associated with IDC-P and mCRPC, even in the hormone-naive setting.

  Study EGAS00001001615

• Whole genome bisulfite sequencing of hepatitis B virus-associated hepatocellular carcinoma tumor and non-cancerous samples

  To understand comprehensive epigenetic alterations in hepatitis B virus-associated HCC, we have conducted a whole genome bisulfite sequencing of 5 tumor samples and 3 non-cancerous samples (3 pairs and 2 tumors).

  Study EGAS00001002230

• 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

• Osteosarcoma_X10

  This is a continuation of the osteosarcoma work we have undertaken.

  Study EGAS00001002167

• Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration.

  The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines revealed a unique form of structural variation, termed heterocateny here, characterized by heterogeneous, interrelated, and repetative patterns of concatemerized virus and host DNA segments. Evidence of heterocateny was detected in extrachromosomal and/or intrachromosomal DNA in all cases. Unique breakpoint sequences shared across structurally heterogeneous virus-host concatemers within each cancer facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that unstable virus and virus-host concatemers in ecDNA or integrated form mediate insertion into and excision from chromosomes, capture, rearrangement, and rolling-circle amplification of host DNA, and chromosomal rearrangements. The data indicate that heterocatena is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intra-tumoral heterogeneity and clonal evolution.

  Study EGAS00001006652

• 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

• ICGC PanCancer Analysis of Whole Genomes

  Study EGAS00001001692

• The Landscape of Genetic Alterations in Hepatocellular Carcinoma, 88 matched HCC tumour/normal pairs WGS belongs to ICGC LICA-CN project

  Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy. Whole genome shotgun sequencing (WGS) and the landscaple of somatic mutations in 88 paired samples from HCC patients including tumors and matched adjacent normal tissues using Illumina HiSeq 2000 platform were performed.

  Study EGAS00001002218

• Organoid_Derivation_Project__TGS

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Study EGAS00001002221

• Sequencing of an organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity.

  Kidney tumors are among the most common solid tumors in children, comprising several distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first pediatric cancer organoid biobank. It contains tumor and matching normal organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumors, malignant rhabdoid tumors, renal cell carcinomas, and congenital mesoblastic nephromas. The malignant rhabdoid tumor organoids represent the first organoid model for tumors of non-epithelial origin. The tumor organoids retain key properties of native tumors, useful for revealing patient specific drug vulnerabilities. We further demonstrate that organoid cultures derived from Wilms tumors consist of multiple different cell types, including epithelial, stromal and blastemal-like. Our organoid biobank captures the cellular heterogeneity of pediatric kidney tumors, providing a representative collection of well-characterized models for basic cancer research, drug-screening, and personalized medicine.

  Study EGAS00001003853