11750 results for "cancer rna-seq"

in 27.38 milliseconds.

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010965

• Genome and transcriptome sequence data from a metastatic chondrosarcoma patient

  Genome and transcriptome sequence data from a metastatic chondrosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010966

• Genome and transcriptome sequence data from a primary unknown patient

  Genome and transcriptome sequence data from a primary unknown patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010968

• Genome and transcriptome sequence data from a rectal adenocarcinoma patient

  Genome and transcriptome sequence data from a rectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010981

• Genome and transcriptome sequence data from a cerebellar glioma patient

  Genome and transcriptome sequence data from a cerebellar glioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010982

• Genome and transcriptome sequence data from a lung adenocarcinoma patient

  Genome and transcriptome sequence data from a lung adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010987

• Genome and transcriptome sequence data from a primary unknown patient

  Genome and transcriptome sequence data from a primary unknown patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010995

• Genome and transcriptome sequence data from a hepatic cholangiocarcinoma patient

  Genome and transcriptome sequence data from a hepatic cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010997

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010998

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011000

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011004

• Genome and transcriptome sequence data from a colorectal adenocarcinoma patient

  Genome and transcriptome sequence data from a colorectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011008

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011018

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011022

• Genome and transcriptome sequence data from a follicular lymphoma patient

  Genome and transcriptome sequence data from a follicular lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011023

• Genome and transcriptome sequence data from a neuroendocrine tumor patient

  Genome and transcriptome sequence data from a neuroendocrine tumor patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011024

• Genome and transcriptome sequence data from a nasopharyngeal carcinoma patient

  Genome and transcriptome sequence data from a nasopharyngeal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011028

• Genome and transcriptome sequence data from a colorectal carcinoma patient

  Genome and transcriptome sequence data from a colorectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011029

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011030

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011032

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002623

• Genome and transcriptome sequence data from a clival chordoma patient

  Genome and transcriptome sequence data from a clival chordoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002640

• Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient

  Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002642

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004922

• Whole genome sequencing

  The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. We performed whole genome sequencing on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

  Dataset EGAD00001005240

• Predictor_ChemoNEAR_TNBC (2019-08-14)

  In this study a collection of core biopsies from breast cancer patients receiving neoadjuvant chemotherapy as part of the ChemoNEAR trial will be investigated. The study is intended to detect early acquired resistance in women with diagnosed breast carcinoma. Samples will undergo whole genome sequencing and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005255

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005882

• Genome and transcriptome sequence data from a hemangioma patient

  Genome and transcriptome sequence data from a hemangioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005900

• Whole exome sequencing of long-term, never relapse exceptional responders of trastuzumab-treated HER2+ metastatic breast cancer

  The dataset contains Whole Exome Sequencing data (BAM files) of 22 samples from HER2+ metastatic breast patients. For 9 of the 13 tumours samples there are paired controls available from normal tissue. There are 8 tumours samples that are from treatment-responder patients and 5 tumours samples from non responder patients.

  Dataset EGAD00001006217

• Genomic and transcriptomic data of glioma specimens

  Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

  Dataset EGAD00001006299

• The mutation burden of narrowband ultraviolet B phototherapy in human skin - Nanoseq

  Background: Ultraviolet radiation (UV) is used as a treatment for psoriasis, but UV can also induce mutations which may lead to development of skin cancer. Information on the mutagenicity of narrowband UVB (NBUVB) would help inform clinicians and patients who are concerned about the potential risks of this treatment.

  Dataset EGAD00001015249

• The mutation burden of narrowband ultraviolet B phototherapy in human skin - WGS

  Background: Ultraviolet radiation (UV) is used as a treatment for psoriasis, but UV can also induce mutations which may lead to development of skin cancer. Information on the mutagenicity of narrowband UVB (NBUVB) would help inform clinicians and patients who are concerned about the potential risks of this treatment.

  Dataset EGAD00001015250

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010940

• Genome and transcriptome sequence data from a myoepithelioma patient

  Genome and transcriptome sequence data from a myoepithelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010938

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010939

• Genome sequence data from a metastatic rectal carcinoma patient

  Genome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010972

• Genome and transcriptome sequence data from a thymoma patient

  Genome and transcriptome sequence data from a thymoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011039

• Genome and transcriptome sequence data from a rectal adenocarcinoma patient

  Genome and transcriptome sequence data from a rectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011040

• Prediction of Trastuzumab Benefit in Adjuvant Breast Cancer: Gene Expression Profiling in NSABP B31

  Background National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31. Methods Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided. Results Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P < .001; n = 442; P interaction between the model and trastuzumab < .001). Conclusions We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demostrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47). ** Reprinted from J Natl Cancer Inst;2013;105:1782-1788 with permission from Oxford University Press.

  Study phs000826

• The University of Hong Kong Colon Cancer GCV Study

  Background: Ganciclovir (GCV) is widely used in solid organ and hematopoietic stem cell transplant patients for prophylaxis and treatment of cytomegalovirus. It has long been considered a mutagen and carcinogen. However, the contribution of GCV to cancer incidence and other factors that influence its mutagenicity remains unknown. Methods: This retrospective cohort study analysed genomics data for 121,771 patients who had undergone targeted sequencing compiled by the Genomics Evidence Neoplasia Information Exchange (GENIE) or Foundation Medicine (FM). A statistical approach was developed to identify patients with GCV-associated mutational signature (GCVsig) from targeted sequenced data of tumour samples. Cell line exposure models were further used to quantify mutation burden and DNA damage caused by GCV and other antiviral and immunosuppressive drugs. Results: Mutational profiles from 22 of 121,771 patient samples in the GENIE and FM cohorts showed evidence of GCVsig. A diverse range of cancers was represented. All patients with detailed clinical history available had previously undergone solid organ transplantation and received GCV and mycophenolate treatment. RAS hotspot mutations associated with GCVsig¬¬ were present in 9 of the 22 samples, with all samples harbouring multiple GCV-associated protein-altering mutations in cancer driver genes. In vitro testing in cell lines showed that elevated DNA damage response and GCV¬sig are uniquely associated with GCV but not acyclovir, a structurally similar antiviral. Combination treatment of GCV with the immunosuppressant, mycophenolate mofetil (MMF), increased the misincorporation of GCV in genomic DNA and mutations attributed to GCVsig in cell lines and organoids. Conclusions: In summary, GCV can cause a diverse range of cancers. Its mutagenicity may be potentiated by other therapies, such as mycophenolate, commonly co-prescribed with GCV for post-transplant patients. Further investigation of the optimal use of these drugs could help reduce GCV-associated mutagenesis in post-transplant patients.

  Study EGAS00001006707

• Immune induction strategies to enhance the sensitivity to PD-1 blockade in metastatic triple negative breast cancer: the TONIC-trial

  The response rate in metastatic triple negative breast cancer (TNBC) to PD-1 blockade is low, highlighting an urgent clinical need for strategies that render the TNBC tumor microenvironment (TME) more sensitive to PD-1 blockade. Immunomodulatory mechanisms have been proposed for both chemotherapy and irradiation, but it has not been established whether these therapies may improve efficacy of PD-1 blockade by favorably changing the TME. In the first stage of this adaptive, non-comparative phase II trial (TONIC-trial; NCT02499367), 67 patients with metastatic TNBC were randomized to nivolumab without induction or to one of four induction treatments, consisting of irradiation of one metastatic lesion (3x8 Gy) or a two- week low-dose regimen of cyclophosphamide, cisplatin or doxorubicin, all followed by nivolumab. In the overall cohort of 66 evaluable patients, the objective response rate (ORR; iRECIST16) was 20% (95% CI: 11%-31%), with two complete responses and 11 partial responses. The majority of clinical responses were observed on nivolumab in the cisplatin (ORR 23%; 3/13) and doxorubicin (ORR 35%; 6/17) cohorts. After doxorubicin and cisplatin induction, we detected an upregulation of immune-related genes, involved in PD-1/PD-L1, and T-cell cytotoxicity pathways. This was further supported by enrichment among upregulated genes related to inflammation, JAK-STAT and TNFα-signaling after doxorubicin. In addition, we observed a trend towards increased T-cell infiltration, measured using T-cell receptor (TCR) sequencing, after doxorubicin. Together, the clinical and translational data of this study testing different immune induction strategies prior to nivolumab suggest that short-term doxorubicin and cisplatin may induce a more favorable TME and increase the likelihood of response to PD-1 blockade in TNBC. These data warrant further confirmation in TNBC and exploration of induction treatments prior to PD-1 blockade in other cancer types.

  Study EGAS00001003535

• Molecular features of adenomas predicting metachronous colorectal cancer: a nested-case control study

  "Background & Aims: Current morphological features defining advanced adenomas (size ≥10 mm, high grade dysplasia or >25% villous component) cannot optimally distinguish individuals at high-risk or low-risk of metachronous colorectal cancer (me-CRC), which may result in suboptimal surveillance. Certain DNA copy number alterations are associated with adenoma-to-carcinoma progression (cancer-associated events; CAEs). We aimed to evaluate whether CAEs can better predict an individual’s risk of me-CRC than the morphological advanced adenoma features. Methods: In this nested case-control study, 529 individuals with a single adenoma at their first colonoscopy were selected from a Norwegian adenoma cohort. DNA copy number profiles were determined, by means of low-coverage whole genome sequencing. We assessed the prevalence of CAEs in advanced and non-advanced adenomas and its association with me-CRC. For the latter, cases (with CRC) were matched to controls (without CRC), with the same follow-up period as cases, as well as age and sex. Subsequently, odds ratios (OR) for the association of the presence of an advanced adenoma or a molecularly-defined high-risk adenoma with me-CRC were calculated. Results: Molecular high-risk features were observed in 85/267 (32%) of advanced adenomas and in 27/262 (10%) of non-advanced adenomas. Me-CRC was more strongly associated with advanced adenomas (OR 3.58; 95% CI 2.27-5.72) than with molecular high-risk adenomas (OR 1.90; 95% CI 1.14–3.16). After adjusting for other variables, only advanced adenoma remained significantly associated with me-CRC (OR 3.39; 95% CI 2.10–5.55). Conclusion: Molecularly-defined high-risk adenomas were associated with me-CRC, but the association of advanced adenoma with me-CRC was stronger. " Project goal: Evaluate the value of DNA copy numbers alterations detected in a baseline adenoma, in the prediction of risk of metachronous CRC

  Study EGAS00001007039

• CTSP: Clinical Trial Sequencing Project

  For the Clinical Trials Sequencing Project (CTSP), National Cancer Institute (NCI) will utilize whole genome sequencing and/or whole exome sequencing in conjunction with transcriptome sequencing to try to identify recurrent genetic alterations (mutations, deletions, amplifications, rearrangements) and/or gene expression signatures that would be important to the hypothesis(es) submitted by the investigators. The samples will be processed and submitted for genomic characterization using pipelines and procedures established within The Cancer Genome Analysis (TCGA) project. Data analysis will be performed as a collaboration between the National Clinical Trials Network (NCTN) Group and its investigators submitting the proposal. The investigators at the NCI-sponsored Genomic Data Analysis Center (GDAC) will characterize the samples. The NCTN Group will be responsible for providing the clinical data needed for the proposal to the open clinical system maintained by NCI CCG's Biospecimen Core Resource (BCR) at Nationwide Children's Hospital in Columbus, Ohio. The project team (Network Group/investigators and GDAC) will analyze the data together. Additionally, clinical and genomic data related to the analyses will also need to be registered by NCI and will be made available to qualified researchers via a controlled-access database (e.g., dbGaP) upon publication of the primary analysis described in the study proposal. A substudy description and its molecular data information are provided under its own page: phs001184 CTSP Diffuse Large B-Cell Lymphoma (DLBCL) CALGB 50303

  Study phs001175

• Neoadjuvant immune checkpoint blockade in women with mismatch repair deficient endometrial cancer

  Neoadjuvant immune checkpoint blockade (ICB) has shown unprecedented activity in mismatch repair deficient (MMRd) colorectal cancers, but its effectiveness in MMRd endometrial cancer (EC) remains unknown. In this investigator-driven, phase I, feasibility study (NCT04262089), 10 women with MMRd EC of any grade, planned for primary surgery, received two cycles of neoadjuvant pembrolizumab (200 mg IV) every three weeks. A pathologic response (primary objective) was observed in 5/10 patients, with 2 patients showing a major pathologic response. No patient achieved a complete pathologic response. A partial radiologic response (secondary objective) was observed in 3/10 patients, 5/10 patients had stable disease and 2/10 patients were non-evaluable on Magnetic Resonance Imaging (MRI). All patients completed treatment without severe toxicity (exploratory objective). At median duration of follow-up of 22.5 months, two non-responders experienced disease recurrence. In-depth analysis of the loco-regional and systemic immune response (predefined exploratory objective) showed that monoclonal T cell expansion significantly correlated with treatment response. Tumour-draining lymph nodes displayed clonal overlap with intra-tumoural T cell expansion. All pre-specified endpoints, efficacy in terms of pathologic response as primary endpoint, radiologic response as secondary outcome and safety and tolerability as exploratory endpoint, were reached. Neoadjuvant ICB with pembrolizumab proved safe and induced pathologic, radiologic, and immunologic responses in MMRd EC, warranting further exploration of extended neoadjuvant treatment.

  Study EGAS50000000483

• UCSF Database for the Advancement of JMML - Integration of Metadata with Omic Data

  Juvenile myelomonocytic leukemia (JMML) is a rare and frequently fatal myeloproliferative/myelodysplastic disorder of early childhood with an estimated incidence of 1.2 cases per million. It is associated with a spectrum of diverse outcomes ranging from spontaneous resolution in rare patients to transformation to acute myeloid leukemia in others. The overwhelming majority of JMML patients (~95%) will harbor mutations in canonical Ras pathway genes, including NF1, NRAS, KRAS, PTPN11, and CBL. As Ras proteins are mutated in more than 30% of human cancers, the information gleaned from the study of JMML has provided insights into Ras signaling in cancer as well as a group of congenital diseases with tumor predispositions known as the “Rasopathies”. While oncogenic Ras is one of the most common mutations in human cancer, it remains one of the most vexing targets for efficacious therapy. To better understand this disease, a JMML tissue bank was established at UCSF that allows for consenting of subjects, biobanking of tissue and collection of follow up data from patients both locally and at other institutions. Through the collection and analysis of specimens, knowledge about the genetic, epigenetic, and biochemical basis of JMML has been gained. This integrated database will enable future JMML research, and importantly, additional Ras/MAPK pathway research by depositing linked, processed data to well annotated anonymized patients in an easily accessible online database

  Study phs002504

• The Dynamic Immune Behavior of Primary and Metastatic Ovarian Carcinoma

  Patients with high-grade serous ovarian carcinoma are usually diagnosed at an advanced stage and often develop resistance to conventional therapy. Epithelial ovarian tumors have been shown to be rich in CD8+ lymphocytes, which infiltrate both primary and omental sites. In recent years, several prominent studies have highlighted a positive association between the presence of these immune cells and a good prognosis; however, clinical trials of immune checkpoint inhibitors have so far shown unsatisfactory results in ovarian cancer. In this study, we used an innovative combination of single-cell sequencing and spatial transcriptomics to identify the molecular mechanisms that lead to immunosuppression in primary and metastatic HGSC. Primary tumors consistently showed a more active immune microenvironment than did omental tumors. In addition, while several immune cell subtypes were present in all samples, their relative abundance differed between primary and omental tumors. Finally, we found that primary tumors were mostly populated by dysfunctional CD4 and CD8 T cells in later stages of differentiation, while omental tumors were mostly populated by naïve immune cells; this, in turn, was correlated with expression changes in the interferon α and γ pathways in epithelial cells, showing that cross-communication between the epithelial and immune compartments is important for immune suppression in ovarian cancer. These findings can impact the timing and choice of immune-modulating drugs and should be considered when planning treatment for patients with high-grade serous ovarian carcinoma.

  Study EGAS50000000038

• Tissue-specific mutation accumulation in human adult stem cells during life

  Gradual accumulation of mutations in human adult stem cells during life is associated with various age-related diseases, including cancer. The number of stem cell divisions throughout life is believed to be a major determinant for mutation accumulation and could explain the extreme variation of cancer incidence across different organs. Yet, mutation patterns and rates of healthy adult stem cells remain unknown. Here, we determined genome-wide mutation patterns in primary adult stem cells of the small intestine, colon and liver of human donors with ages ranging from 3 to 87 years. We find that the number of mutations increases linearly with age up to several thousand mutations per cell at 87 years of age, while mutation spectra remain constant throughout life. Small intestine and colon stem cells have a 2-fold higher mutation rate per year compared with liver stem cells. These differences could be exclusively attributed to the mutagenic action of spontaneous deamination of cytosine residues and may reflect the high stem cell division rate in these tissues. The genomic distribution of somatic mutations is non-random and predominantly associated with DNA replication dynamics in the small intestine and colon, and with transcription in the liver. These results indicate that a stable balance between various mutagenic and DNA repair processes is maintained throughout life and that the activity of these processes in adult stem cells varies between tissues.

  Study EGAS00001001682

• RB1 Gene Inactivation by Chromothripsis in Human Retinoblastoma

  Retinoblastoma is a rare childhood cancer of the developing retina. Most retinoblastomas initiate with biallelic inactivation of the RB1 gene through diverse mechanisms including point mutations, nucleotide insertions, deletions, loss of heterozygosity and promoter hypermethylation. Recently, a novel mechanism of retinoblastoma initiation was proposed. Gallie and colleagues discovered that a small proportion of retinoblastomas lack RB1 mutations and had MYCN amplification [1]. In this study, we identified recurrent chromosomal, regional and focal genomic lesions in 94 primary retinoblastomas with their matched normal DNA using SNP 6.0 chips. We also analyzed the RB1 gene mutations and compared the mechanism of RB1 inactivation to the recurrent copy number variations in the retinoblastoma genome. In addition to the previously described focal amplification of MYCN and deletions in RB1 and BCOR, we also identified recurrent focal amplification of OTX2, a transcription factor required for retinal photoreceptor development. We identified 10 retinoblastomas in our cohort that lacked RB1 point mutations or indels. We performed whole genome sequencing on those 10 tumors and their corresponding germline DNA. In one of the tumors, the RB1 gene was unaltered, the MYCN gene was amplified and RB1 protein was expressed in the nuclei of the tumor cells. In addition, several tumors had complex patterns of structural variations and we identified 3 tumors with chromothripsis at the RB1 locus. This is the first report of chromothripsis as a mechanism for RB1 gene inactivation in cancer.

  Study EGAS00001000598

• RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.

  Background: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called `epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. Results: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder. Conclusions: Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity.

  Study EGAS00001002484

• Genomic stratification and liquid biopsy in a rare adrenocortical carcinoma (ACC) case, with dual lung metastases

  Adrenocortical carcinoma is a rare malignancy with a poor prognosis and few treatment options. Molecular characterization of this cancer remains limited. We present a case of an adrenocortical carcinoma (ACC) in a 37-yr-old female, with dual lung metastases identified 1 yr following commencement of adjuvant mitotane therapy. As standard therapeutic regimens are often unsuccessful in ACC, we undertook a comprehensive genomic study into this case to identify treatment options and monitor disease progress. We performed targeted and whole-genome sequencing of germline, primary tumor, and both metastatic tumors from this patient and monitored recurrence over 2 yr using liquid biopsy for ctDNA and steroid hormone measurements. Sequencing revealed the primary and metastatic tumors were hyperhaploid, with extensive loss of heterozygosity but few structural rearrangements. Loss-of-function mutations were identified in MSH2, TP53, RB1, and PTEN, resulting in tumors with mismatch repair signatures and microsatellite instability. At the cellular level, tumors were populated by mitochondria-rich oncocytes. Longitudinal ctDNA mutation and hormone profiles were unable to detect micrometastatic disease, consistent with clinical indicators of disease remission. The molecular signatures in our ACC case suggested immunotherapy in the event of disease progression; however, the patient remains free of cancer. The extensive molecular analysis presented here could be applied to other rare and/or poorly stratified cancers, to identify novel or repurpose existing therapeutic options, thereby broadly improving diagnoses, treatments, and prognoses.

  Study EGAS00001003497