3773 results for "*oma"

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• Genome-wide cell-free DNA biological patterns in patients with cancer

  The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

  Study EGAS00001007400

• Spatial tumor microenvironment characterization and outcome of relapsed/refractory classic Hodgkin lymphoma

  About half of relapsed or refractory classic Hodgkin lymphoma (r/r CHL) patients succumb to their disease after high dose chemotherapy followed by autologous stem cell transplantation (HDT/ASCT). Here, we aimed at describing spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL.

  Study EGAS00001007261

• Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types (RNAseq)

  Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

  Study EGAS00001007428

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005738

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005747

• Analysis of enhancer-promoter connectivity alterations

  The study uncovers epigenomic changes associated with dexamethasone response heterogeneity in myeloma cells, revealing rewired promoter-enhancer interactions and DNA loop stabilization

  Study EGAS00001007411

• Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types

  Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

  Study EGAS00001007412

• WGS and WES of pediatric osteosarcoma

  Despite being the most common childhood bone tumor, the genomic characterization of osteosarcoma remains incomplete. Very few metastatic cases have been sequenced to date, a required step to better understand the progression and evolution of this tumor. Here, we present an integrative analysis of whole genome and whole exome sequencing (WGS and WES) of a cohort of primary and metastatic pediatric osteosarcoma, in order to identify recurrent genomic alterations between and within patients.

  Study EGAS00001003342

• Revealing active mutational processes in tumours using DigiPico/MutLX at unprecedented accuracy

  Active mutational processes in a tumor result in genetic micro-heterogeneity that can determine the tumor’s evolutionary trajectory. Identification of these processes by studying micro-heterogeneity can unveil novel aspects of tumor evolution with potential therapeutic implications. Such studies, however, are inherently problematic because of the discovery of excessive false positive mutations. Here we report the optimization and validation of a robust whole genome sequencing and analysis pipeline (DigiPico/MutLX) that virtually eliminates false positive results. Using our method, we identified, for the first time, a sub-clonal local hyper-mutation (kataegis) event in a recurrent ovarian carcinoma, which was unidentifiable from the bulk WGS data of the same tumor. Overall, we propose DigiPico/MutLX method as a powerful framework for the reliable study of genetic micro-heterogeneity in tumor and normal tissues.

  Study EGAS00001003555

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432