3429 results for "ovarian cancer"

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• Ghana Prostate Study

  Participants were recruited through the Ghana Prostate Study-a population-based component, and a clinical component. The population-based component was a probability sample designed using the 2000 Ghana Population and Housing Census data in an attempt to recruit approximately 1,000 men aged 50-74 years in the Greater Accra region (~3 million people), which successfully recruited 1,037 healthy men between 2004 and 2006 with a response percentage of 98.8 %. Consented individuals underwent an in-person interview, and within 7 days had a digital rectal examination (DRE) and provided an overnight fasting blood sample for prostate-specific antigen (PSA) testing, biomarker assays, and genetic analysis. Subjects who had a positive screen by PSA (>2.5 ng/ml) or DRE underwent a transrectal ultrasound-guided biopsy. A total of 73 histologically confirmed prostate cancer cases were identified through the population-based screening component of the Ghana Prostate Study and were included in the case population in the published GWAS (Cook et al., Human genetics, 2013). From the remaining 964 screen-negative individuals, 836 had at least 20 μg DNA extracted and available for analysis, and 500 of these were matched to cases for analysis by age (in 5-year categories). In the Ghana Prostate Study, we recruited 676 prostate cancer cases at Korle Bu Teaching Hospital in Accra, Ghana, between 2008 and 2012. All consented cases were interviewed and provided an overnight fasting blood sample. At the time of selection for this analysis we had recruited 582 prostate cancer cases, from which we selected 427 for analysis. Combined with the 73 cases diagnosed through the population-based component of the study, this yielded 500 available prostate cancer cases for analysis.

  Study phs000838

• Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive NSCLC patients

  Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but efficacy varies between patients and is believed to depend in part on the amount and properties of tumor infiltrating lymphocytes (TILs). To comprehensively depict and dissect the baseline landscape of the composition, lineage and functional states of TILs in lung cancer, here we generated deep single-cell RNA sequencing data for 12,346 T cells from the primary tumour, adjacent normal tissues and peripheral blood of 14 treatment-naive NSCLC patients. Combined expression and TCR-based lineage tracking revealed a significant proportion of effector T cells with common origins and similar functional states across peripheral blood and tumours pointing towards a highly migratory nature of these T cells. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of pre-exhausted to exhausted T cells is associated with better prognosis of lung adenocarcinoma (LUAD). In addition, we observed further heterogeneity within the tumour regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of this group of activated tumour Tregs, which included IL1R2, correlated with poor prognosis in LUAD. The T cell clusters revealed by our single cell analyses provide a new approach for patient stratification, and the accompanying compendium of data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer.

  Study EGAS00001002430

• METABRIC

  Solid tumors are complex tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Normal cell contamination can dilute cancer cell information and tissue architecture is generally not reflected in molecular assays. To address these challenges, we developed a computational approach based on standard Haematoxylin and Eosin-stained sections and demonstrated its power in a discovery cohort of 323 breast tumors and an independent validation cohort of 241 tumors. First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.

  Study EGAS00000000098

• Enhanced detection of circulating tumor DNA by fragment size analysis

  Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on sensitivity for detecting genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for non-invasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 cancer patients using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90–150 bp, and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90–150 bp improved detection of tumor DNA, with more than 2-fold median enrichment in >95% of cases, and more than 4-fold enrichment in > 10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with AUC> 0.99 compared to AUC < 0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC > 0.91, compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection. This could reduce the required depth of cfDNA sequencing for clinical applications, earlier diagnosis and study of tumor biology.

  Study EGAS00001003258

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Lung cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Study EGAS00001004447

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Study EGAS00001004446

• Germline variants in patients with rare cancers and their implications for precision cancer medicine: experiences from the Multicenter MASTER Trial by the German Cancer Consortium (HIPO_021)

  The era of precision oncology entails an increasing amount of molecular data from tumor sequencing in research and diagnostics. In this setting, germline variant analysis may add clinical benefits for patients and family members. In this study, we evaluated germline variants from genome/exome matched tumor-blood sequencing in 1.485 advanced cancer patients within a prospective observational study carried out by the German Cancer Consortium. Included patients had cancers of rare entities (79.2%) or were under the age of 51 at first diagnosis (76.6%). Ten percent of the patients harbored pathogenic germline variants in 35 tumor predisposition genes with autosomal-dominant inheritance such as BRCA1, BRCA2, TP53, RB1, CHEK2, ATM, PALB2, SDHB etc., while 4.6% of the patients were carriers of pathogenic germline variants in 18 genes with autosomal-recessive inheritance of tumor predisposition. Based on pathogenic germline variants, 14% of the patients received genetic counselling recommendations in the molecular tumor board report. Forty five percent of pathogenic germline variants supported a molecular treatment recommendation, which was implemented for 28 patients. Furthermore, we compared our approach and results to previous studies, broadening the insight into pan cancer germline findings but also revealing differences between studies on various levels, such as cohort demographics, tumor entities, gene nominations, variant detection and variant interpretation. Our data support the importance of germline variant interpretation in precision oncology studies for patients and their families, if applicable. However, guidelines for evaluation and reporting of germline variants in the context of genetic tumor profiling need to be established and further research on the relevance of germline mutations as biomarkers for treatment recommendations is needed.

  Study EGAS00001005537

• Characterization_of_individual_foci_of_multicentric_multifocal_breast_cancer_using_targeted_next_generation_sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the “quadrants” of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients’ survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Study EGAS00001000407

• The genomic imprint of cancer therapies helps timing the formation of metastases

  Study EGAS00001003416

• Organoid Models of Human Liver Cancers Derived from Tumor Needle Biopsies

  Study EGAS00001003115