4836 results for "*oma"

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• Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma

  Atezolizumab (anti–programmed death-ligand 1 [anti-PD-L1]) and bevacizumab (anti-vascular endothelial growth factor [anti-VEGF]) combination therapy has become the new standard of care in patients with unresectable hepatocellular carcinoma. However, potential predictive biomarkers and mechanisms of response and resistance remain less understood. We report integrated molecular analyses of tumor samples from 358 patients enrolled in the GO30140 phase 1b or IMbrave150 phase 3 trials who were treated with atezolizumab combined with bevacizumab, atezolizumab alone, or sorafenib. Pre-existing immunity assessed by high expression of CD274 (PD-L1 mRNA), T-effector signature, and intratumoral CD8+ T cell density were associated with response and better clinical outcomes with the combination treatment. Less clinical benefit was associated with high regulatory T cell (Treg) to effector T-cell ratio and high expression of oncofetal genes such as GPC3 and AFP. Improved outcomes from the combination vs atezolizumab alone appeared to be associated with high expression of KDR (VEGFR2), Treg, and myeloid inflammation signatures, indicating anti-VEGF may contribute by targeting these axes. These findings were further validated by transcriptome analysis of paired pre- and post-treatment biopsies, in situ analysis by multiplex IHC and digital pathology, and in vivo study of an immunogenic hepatocellular carcinoma mouse model. Our findings highlight that anti-VEGF therapy might augment antitumor immunity and enhance anti–PD-L1 immunotherapy by targeting VEGF-mediated angiogenesis, Treg proliferation, and myeloid cell inflammation. Furthermore, our study identified candidate biomarkers for predicting response and resistance to anti–PD-L1 and anti-VEGF combination therapy.

  Study EGAS00001005503

• Genome-wide expression profiles to compare array-based, RNAseq and NanoString technologies in patients with resected pancreatic ductal carcinoma.

  Using formalin-fixed paraffin embedded (FFPE) tissues collected prospectively in patients with resected pancreatic ductal carcinoma (PDC) we generated genome-wide expression profiles to compare array-based, RNAseq and NanoString technologies. Samples included in the study were collected 17 patients. After careful selection by the pathologist of 17 malignant cells-enriched, 7 stroma-enriched, and 6 normal (normal pancreas in 4 cases and normal duodenum in 2 cases) regions, sections were macrodissected, and total RNA extracted. Two additional FFPE-frozen matched-paired PDAC from our local Biobank were included. Our study represents the most extensive work comparing three technologies to generate gene expression profiles from FFPE samples, and provides technical guidance for future biomarker studies in samples collected prospectively in the context of clinical trials.

  Study EGAS00001002501

• 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

• Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens

  Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor “purity.” Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling. (Companion proteomic data is available in the ProteomeXchange Consortium, PRIDE: PXD026570).

  Study EGAS00001005786

• Whole Exome Sequencing in Multiple Myeloma

  By whole exome sequencing (WES) our group observed the accumulation of mutations in receptor tyrosine kinases (RTKs), adhesion molecules and their effectors and developed a signaling network that was affected by at least one mutation in almost 100% of MM patients and by more than one mutation in around 50% of MM patients which we decided to call inter- and intra-individual pathway redundancy. Interestingly, the extension of our WES dataset to 67 primary MM samples with correspond normal tissue which were collected at the Medizinische Klinik and Poliklinik II in Würzburg within the frame of the CRU216 has tentatively led to the designation of three molecular subgroups based on their mutation profile: "adhesion only", "adhesion & downstream" and "RTK & adhesion & downstream

  Study EGAS00001003227

• Molecular programs of melanoma brain metastases (MBM)

  We performed paired-end whole transcriptome sequencing of fresh frozen or intraoperative brain metastases of therapeutically treated stage IV melanoma patients. In addition, we analysed the epigenetic landscape of tumors usind Illumina 850k bead chip technology.

  Study EGAS00001005976

• Identification of gene mutations and fusion genes in patients with Sézary Syndrome

  Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

  Study EGAS00001001706

• Whole-genome and transcriptome sequencing of primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma

  Primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma (pcAECyTCL) is a rare variant of cutaneous T-cell lymphoma with an aggressive clinical course and a very poor prognosis. We subjected tumor biopsies from patients with pcAECyTCL to whole-genome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001004332

• Salivary Gland Cancer TSO500 dataset

  Salivary gland cancer (SGC) is a rare cancer for which systemic treatment options are limited. Therefore, it is important to characterize its genetic landscape in search for actionable aberrations. This research aimed to identify these actionable aberrations by NGS-based analysis of DNA (single and multiple nucleotide variants, copy number variants, microsatellite instability and tumor mutational burden) in a large cohort of SGC patients. DNA was extracted from archival tissue of 119 patients with various SGC subtypes and sequenced using a targeted NGS panel encompassing 523 cancer related genes (TruSight Oncology 500, TSO500). The 119 patients included 46 AdCC patients, 43 SDC patients, 15 MEC patients, 9 AciCC patients and 6 patients with other subtypes (1 secretory carcinoma, 1 polymorphic adenocarcinoma (PAC), 1 adenocarcinoma NOS, 1 myoepithelial carcinoma, 1 epithelial/myoepithelial carcinoma and 1 mixed PAC/myoepithelial carcinoma). Median exon coverage ranged from 80-904 (median 308) unique reads and the median percentage of exon coverage with at least 100 unique reads was median 96.6% in these 119 samples.

  Study EGAS00001006232

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

  The structure, fragmentation patterns and terminal sequences of cell-free DNA (cfDNA) are altered by nucleases and biological mechanisms in the blood of cancer patients. The cfDNA fragment-end composition recovered from low coverage WGS (<1 fold coverage) using a bespoke software (FrEIA) is aberrant in the plasma from cancer patient (n = 418, 655 samples) compared to controls (n = 117). As a standalone test FrEIA allows detection down to ~0.2% tumor fraction in vitro and in silico at 95% specificity, leading to a sensitivity of ~71% for detecting lung cancer (14/22 stage I-II, 27/38 stage III, 92/127 stage IV) and ~68% for detecting esophageal adenocarcinoma (26/44 stage II, 46/62 stage III). Additional cfDNA biological patterns can be combined with FrEIA increasing the diagnostic potential of low coverage WGS at minimal cost (mean AUROC = 0.96). Integrating multiple cfDNA biological signal augments the diagnostic performance of liquid biopsy.

  Study EGAS00001006142