3291 results for "ovarian cancer"

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• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Immune checkpoint inhibitors (ICI), which target immune regulatory pathways to unleash antitumor responses, have revolutionized cancer immunotherapy. Despite the remarkable success of ICI immunotherapy, a significant proportion of patients whose tumors respond to these treatments develop immune-related adverse events (irAEs) resembling autoimmune diseases. Although the clinical spectrum of irAEs is well characterized, their successful management remains empiric. This is in part because the pathogenic mechanisms involved in the break-down of peripheral tolerance and induction of irAEs remain elusive. Herein, we focused on regulatory T cells (Tregs) in individuals with irAEs because these cells are vital for maintenance of peripheral tolerance, appear expanded in the peripheral blood of individuals with cancer and abundantly express checkpoint molecules, hence representing direct targets of ICI immunotherapy. Our data demonstrate an intense transcriptomic reprogramming of CD4+CD25+CD127– Tregs in the blood of individuals with advanced metastatic melanoma who develop irAEs following ICI immunotherapy, with a characteristic inflammatory, apoptotic and metabolic signature. This inflammatory signature was shared by Tregs from individuals with different types of cancer developing irAEs and individuals with autoimmune diseases. Our findings propose an inflammatory Treg reprogramming as a feature of immunotherapy-induced irAEs, that may facilitate translational approaches aiming to induce robust antitumor immunity without disturbing peripheral tolerance.

  Study EGAS00001004694

• Proteogenomics of chronic lymphocytic leukemia

  Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. This is the transcriptomics data of the discovery cohort.

  Study EGAS00001005746

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• Identification of biomarkers of response to preoperative talazoparib monotherapy in treatment naïve gBRCA+ breast cancers

  Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.

  Study EGAS00001005676

• Integration of intra-sample contextual error modeling for improved detection of somatic mutations

  Study EGAS00001003806

• 5' Single cell RNA sequencing of pre-treatment tissues from lung cancer patients receiving immunotherapy

  Study EGAS00001006188

• The landscape of somatic mutations in epigenetic regulators across 1000 pediatric cancer genomes

  Study EGAS00001000449

• Identification of mutations and structural rearrangements in plasma DNA form metastatic prostate cancer patients

  Study EGAS00001000453

• Fresh vs. frozen cell preparations of colorectal cancer single-cell RNA sequencing

  Study EGAS00001003769

• Single cell sequencing: Capturing the origin and dynamics of chromosomal copy-number heterogeneity

  Study EGAS00001003812

• STM4 - Mouliere et al, 2018. Enhanced detection of circulating tumor DNA by fragment size analysis

  Study EGAS00001004418

• BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression

  Study EGAS00001004800

• IG-MYC rearrangement defines a high-risk subgroup of B-cell precursor acute lymphoblastic leukaemia

  Study EGAS00001005111

• Genomic Analysis of Focal Nodular Hyperplasia with Associated Hepatocellular Carcinoma Unveils its Malignant Potential

  Study EGAS00001005313

• Evaluating CRISPR-based Prime Editing for cancer modeling and CFTR repair in organoids

  Study EGAS00001005358

• Genomic profiling of metastatic basal cell carcinoma reveals candidate drivers of disease and therapeutic targets

  Study EGAS00001006148

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer

  Study EGAS00001007372

• CUPiD, a cfDNA methylation-based tissue-of-origin classifier for Cancers of Unknown Primary

  Study EGAS00001007445

• The WID-EC test for the detection and risk prediction of endometrial cancer

  Study EGAS00001005033

• Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  Study EGAS00001008128

• Multi-modal analysis of pediatric pilocytic astrocytomas reveals tumor location-associated cellular and transcriptional heterogeneity

  Study EGAS00001008187

• An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

  Study EGAS00001004655

• Angiosarcoma_targeted_pulldown_cancer_gene_panel

  Extension of angiosarcoma whole genome sequencing study

  Study EGAS00001000589

• FFPE_whole_genome_pilot

  To assess feasibility of whole genome sequencing

  Study EGAS00001001967

• Angiosarcoma_whole_exome

  Extension of angiosarcoma whole genome sequencing study

  Study EGAS00001000588