5706 results for "canc*"

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• Immunological hallmarks for clinical response to BCG in bladder cancer

  Intravesical Bacillus Calmette-Guerin (BCG) is an effective immunotherapy for non-muscle invasive bladder cancer (NMIBC). However, recurrence and progression remain frequent warranting deeper insights into its mechanism. We herein comprehensively profiled blood and tissues obtained from NMIBC patients before, during and after BCG treatment using cytometry by time-of-flight (CyTOF) and RNA sequencing to identify the key immune subsets crucial for anti-tumour activity.

  Study EGAS00001004764

• 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

• Integrated Genomic and Transcriptomic Analysis Reveals Unique Characteristics of Hepatic Metastases and Pro-metastatic Role of Complement C1q in Pancreatic Ductal Adenocarcinoma

  Study EGAS00001004821

• AGECAN - Interespecies conservation of brain specific DNA methylation in aging and cancer

  Study EGAS00001004851

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• UROMOL 2020 - SNP data

  The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters.

  Study EGAS00001004862

• Genetic makeup of agnospheres

  Agnospheres are cultures of cancer stem cells isolated from tissue biopsies from patients with Cancer of Unknown Primary (CUPs). The latter is a lethal malignancy (median survival <1 year), representing approximately the 3% of all cancers, and characterized by metastatic dissemination in the absence of a primary tumor recognizable by a standardized protocol including thorough body imaging and histopathological analysis. Agnospheres are long-term propagated in culture and, after subcutaneous injection into immunocompromised mice, they display high tumorigenicity and quickly reproduce the clinical presentation of the original tumor, featuring a multi-organ metastatic pattern and poorly differentiated histology. The goal of the project is to analyse the mutational profile of agnospheres in detail, as to verify its correspondance with that of the original tumors. Genetic information will be exploited to investigate the genetic drivers of the CUP phenotype, in particular the hypermetastatic ability and the differentiative block.

  Study EGAS00001004868

• Multiregional sequencing of IDH-WT glioblastoma reveals high genetic heterogeneity and a dynamic evolutionary history

  Glioblastoma is the most common and aggressive primary brain malignancy in adults. In addi-tion to extensive inter-patient heterogeneity, glioblastoma shows intra-tumor extensive cellular and molecular heterogeneity, both spatially and temporally. This heterogeneity is one of the main reasons for the poor prognosis and overall survival. Moreover, it raises the important question of whether the molecular characterization of a single bioptic sample, as performed in standard di-agnostics, actually represents the entire lesion. In this study, we sequenced the whole-exome of nine spatially different cancer regions of three primary glioblastomas. We characterized their mutational profiles and copy number alterations, with implications for our understanding of tu-mor biology in relation to clonal architecture and evolutionary dynamics, as well as therapeuti-cally relevant alterations.

  Study EGAS00001005128

• Molecular evolution and clinical trajectories of prostate cancer identifies novel markers for risk stratification - additional data

  Study EGAS00001004884

• Targeted sequencing DDR genes in cancer stem cells

  Colorectal cancer stem cells (CSCs) show heterogeneous levels of constitutive replication stress leading distinct dependence on the replication stress response. The aim of the projects was to find genetic, epigenetic, phenotypic factors associated with the resistance of colorectal CSCs to inhibitors of the ATR/CHK1 pathway, which regulates of the replication stress response. Different pairs of colorectal CSCs sensitive and resistant to ATR or CHK1 inhibitors were analyzed

  Study EGAS00001004892

• Selective Elimination of Immunosuppressive T cells in Patients with Multiple Myeloma

  Study EGAS00001004915

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Study EGAS00001005355

• Phase Ib of olaparib and capivasertib

  Background: Combining poly(ADP-ribose) polymerase (PARP) with phosphatidylinositol-3-kinase (PI3K) pathway inhibitors is supported by strong preclinical rationale. We sought to assess safety and a recommended phase 2 dose (RP2D) for the PARPi olaparib combined with the AKT inhibitor, capivasertib, and evaluate molecular markers of response and resistance. Methods: As part of a larger phase 1b trial, we performed a safety lead in of olaparib and capivasertib followed by expansion (n=24) in endometrial, triple negative breast, ovarian, fallopian tube, or peritoneal cancer. Olaparib 300mg orally twice daily and capivasertib orally twice daily on a 4 day on/3 day off schedule were evaluated. Two dose levels (DL) were planned: capivasertib 400mg (DL1); capivasertib 320mg (DL-1). Patients underwent biopsies at baseline and after 28 days.

  Study EGAS00001004930

• Tissue and plasma RNA from esophageal cancer and precursor lesions

  In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. This unique resource allows for discovery of novel biomarkers and disease mechanisms, comparison of tissue and liquid biopsy profiles, integration of coding and non-coding RNA patterns, and can serve as a validation dataset in other RNA landscaping studies. Moreover, structural RNA differences can be identified in this dataset, including protein coding mutations fusion genes, and circular RNAs.

  Study EGAS00001004939

• Sensitive and robust liquid biopsy-based detection of PIK3CA mutations

  Over the last years, the treatment of hormone receptor-positive metastatic breast cancer patients has dramatically changed. Combination strategies attempting to overcome resistance to endocrine therapy such as targeting the PI3 kinase pathway are gaining importance. The phase III SOLAR-1 trial demonstrated the benefit of the addition of alpelisib to fulvestrant, thereby providing further clinical evidence of the increasing importance of PIK3CA testing. Here, we performed a comparison of liquid biopsy and tissue-based detection of PIK3CA mutations in HR-positive metastatic breast cancer patients. Plasma samples and the latest available tumor tissue from 69 patients with metastatic hormone-receptor positive breast cancer were analyzed for PIK3CA hotspot mutations. A high-resolution NGS assay (SiMSen-Seq) was used for plasma samples covering 11 recurrent PIK3CA mutations, used for stratification in SOLAR-1. Additionally, mFAST-SeqS was used to estimate the tumor fractions in the plasma samples. For tumor tissue samples, targeted Ion Torrent NGS was employed. Matched tissue and plasma samples were available from 63 patients. PIK3CA mutations were detected in 46.1% of the tissue samples and in 50.7% of the plasma samples. The variant allele frequency (VAF) ranged from 4.36% to 72.93% with a median of 28.60% in tissue samples, and from 0.28% to 49.85% with a median of 1.17% in plasma samples. The most frequent variants in tissue and plasma were H1047R, E545K, and E542K. We detected at least one of 11 PIK3CA mutations from the SOLAR-1 trial in 51/63 patients, both in tissue and plasma. In 7 patients, such mutations were found only in plasma. In 5 patients, PIK3CA mutations found in tissue were not detectable in ctDNA, 2 of which had a low tumor fraction.Together, in 33/67 plasma samples without detectable PIK3CA mutations, 18 samples had elevated tumor fraction, implicating true negative results. In the remaining 15 patients with low tumor fraction, additional tissue analysis was needed. SiMSen-Seq-based detection of PIK3CA mutations in plasma shows advantageous concordance with the tissue analyses. A combination with an untargeted, mutation-independent approach for detecting ctDNA fractions may confirm a negative PIK3CA result and thereby enhance the performance of the SiMSen-Seq test. This combinatory approach for selecting suitable patients for alpelisib treatment should be validated in larger patient cohorts.

  Study EGAS00001004940

• Genetic insights into the biological mechanisms governing human ovarian ageing

  Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ~200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

  Study EGAS00001004947