11799 results for "cancer rna-seq"

in 15.70 milliseconds.

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002696

• Cholangiocarcinoma

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting two datasets that contain NGS files from gastrointestinal rare cancers (n=119): - Dataset 2 (87 patients): Intra-hepatic cholangiocarcinoma (n=47), Extra-hepatic, cholangiocarcinoma (n=16), Not specified Cholangiocarcinoma (n=9), Small bowel adenocarcinoma (n=6) and other rare GI cancer (n=9)

  Dataset EGAD00001008968

• The Natural History of Human Prostate Cancer

  Whole genome DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of 3 men. For each of three different prostates, multiple tumour samples (4, 5, and 3 depending on the case) and one normal tissue sample were whole genome sequenced with a matched blood sample using the Illumiuna HiSeq platform. Tumour samples were sequenced to a target depth of 50X and normals and blood to a target depth of 30X. As of September 2020, some of the studies using these data include: Cooper et al, Nature Genetics 2015 (PMID: 25730763) Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000689

• IMMUcan Lung NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

  Study EGAS50000001558

• PCR-free shallow whole genome sequencing for chromosomal copy number detection from plasma of cancer patients is an efficient alternative to the conventional PCR-based approach

  Somatic copy number alterations (SCNAs) can be detected in tumor cell-free DNA (cfDNA) by shallow whole genome sequencing (sWGS). Polymerase chain reaction (PCR) is typically included in library preparations, but a PCR-free method could be an effective alternative for research and diagnostics. Peripheral blood samples (n=22) were collected in EDTA-containing tubes from non-small cell lung cancer patients (n=10) and healthy donors (n=12). PCR and PCR-free library preparations underwent sWGS and the following metrics were compared: mapping quality, proportion of duplicate reads, genome coverage, sequencing read length and copy number profiles. The PCR-free method was further evaluated on archived plasma samples (n=33) of varying pre-analytical quality collected in EDTA or lithium heparin tubes. Archived samples were from acute myeloid leukaemia (n=15) and B-cell lymphoma (n=18) patients. The percentage of unique reads was significantly higher for the 22 samples analysed by PCR-free (95.7%) compared to PCR (84%). PCR-free libraries from 33 archived samples produced data of a comparable quality, with 95.4% unique reads. All other evaluated metrics were highly comparable for PCR and PCR-free library preparations. We conclude that SCNA detection can be performed by PCR-free sWGS on cfDNA from cancer patients and is feasible for diagnostic and archival plasma collected in EDTA- or lithium heparin-containing tubes. Our results pave the way for an automated cfDNA workflow for cancer plasma samples.

  Study EGAS00001004692

• Transcriptional profiling of ovarian tumours and cell lines

  Purpose: Endogenous retroviruses (ERVs) play a role in a variety of biological processes, including embryogenesis and cancer. DNA methyltransferase inhibitors (DNMTi)-induced ERV expression triggers interferon responses in ovarian cancer cells via the viral sensing machinery. Baseline expression of ERVs also occurs in cancer cells, though this process is poorly understood and previously unexplored in epithelial ovarian cancer (EOC). Here, the prognostic and immunomodulatory consequences of baseline ERV expression was assessed in EOC. Experimental Design: ERV expression was assessed using EOC transcriptional data from TCGA and from an independent cohort (HH), as well as from untreated or DNMTi-treated EOC cell lines. LASSO logistic regression defined an ERV expression score to predict patient prognosis. Immunohistochemistry (IHC) was conducted on the HH cohort. Combination of DNMTi treatment with γδ T cells was tested in vitro, using EOC cell lines and patient-derived tumor cells. Results: ERV expression was found to define clinically relevant subsets of EOC patients. An ERV prognostic score was successfully generated in TCGA and validated in the independent cohort. In EOC patients from this cohort, a high ERV score was associated with better survival (log-rank p=0.0009) and correlated with infiltration of CD8+PD1+ T cells (r=0.46, p=0.0001). In vitro, baseline ERV expression dictates the level of ERV induction in response to DNMTi. Manipulation of ERV expression by DNMTi resulted in improved EOC cell killing by cytotoxic immune cells. Conclusions: These findings uncover the potential for baseline ERV expression to robustly inform EOC patient prognosis, influence tumor immune infiltration and affect anti-tumor immunity.

  Study EGAS00001004814

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• Whole Exome Sequencing data of six chRCC tumors corresponding to three patients

  Mammalian target of rapamycin (mTOR) is a central regulator of mammalian metabolism and physiology. Aberrant hyperactivation of the mTOR pathway promotes tumor growth and metastasis, and can also promote tumor resistance to chemotherapy and cancer drugs; this makes mTOR an attractive cancer therapeutic target. mTOR inhibitors have been approved to treat cancer; however, the mechanisms underlying drug sensitivity remain poorly understood. Here, whole exome sequencing of three chromophobe renal cell carcinoma (chRCC) patients with exceptional mTOR inhibitor sensitivity revealed that all three patients shared somatic mutations in the deubiquitinase USP9X. The clonal characteristics of the mutations, which were amassed by studying multiple patients’ primary and metastatic samples from various years, together with the low USP9X mutation rate in unselected chRCC series, reinforced a causal link between USP9X and mTOR inhibitor sensitivity. Rapamycin treatment of USP9X-depleted HeLa and renal cancer 786-O cells, along with the pharmacological inhibition of USP9X, confirmed that this protein plays a role in patients’ sensitivity to mTOR inhibition. USP9X was not found to exert a direct effect on mTORC1, but subsequent ubiquitylome analyses identified p62 as a direct USP9X target. Increased p62 ubiquitination and the augmented rapamycin effect upon bortezomib treatment, together with the results of p62 and LC3 immunofluorescence assays, suggested that dysregulated autophagy in USP9X-depleted cells can have a synergistic effect with mTOR inhibitors. In summary, we show that USP9X constitutes a potential novel marker of sensitivity to mTOR inhibitors in chRCC patients, and represents a clinical strategy for increasing the sensitivity to these drugs.

  Study EGAS00001007104

• The University of Hong Kong Intestinal Metaplasia Organoids Study

  Background: Gastric intestinal metaplasia (IM) is a pre-cancerous stage spanning a morphological spectrum that is poorly represented by human cell line models. Objective: We aim to establish and characterize human IM cell models to better understand IM progression along the cancer spectrum. Design: A large human gastric IM organoid (IMO) cohort (n=28), their clonal derivatives and normal gastric organoids (n=42) for comparison were established. Comprehensive multi-omics profiling and functional characterization were performed. Results: Single-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation. Their lineage trajectories connected different cycling and quiescent stem and progenitors, highlighting differences in gastric to IM transition and the potential origin of IM from STMN1 cycling isthmus stem cells. Hybrid IMOs showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates, and reactivation of a fetal gene program. Cell populations in gastric IM and cancer tissues were highly similar to those derived from IMOs and exhibited a fetal signature. Genomically, IMOs showed elevated mutation burden, frequent chromosome 20 gain, and epigenetic de-regulation of many intestinal and gastric genes. Functionally, IMOs were FGF10 independent and showed downregulated FGFR2. Several IMOs exhibited a cell-matrix adhesion independent (CMi) subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, potentially representing the earliest neoplastic precursor of IM-induced gastric cancer. Conclusions: Overall, our IM organoid biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.

  Study EGAS00001007899

• Recurrent Somatic Mutations in CLL

  Study EGAS00001000070