6048 results for "canc*"

in 34.32 milliseconds.

• Palbociclib resistance analyses on breast cancer bone metastasis PDX

  Identify mecanisms of metastatic breast cancer resistance to palbociclib by RNAseq analyses.

  Study EGAS00001006428

• Analyses of IACS-010759 treatment resistance on breast cancer bone metastases

  Identification of biological mecanisms involved in resistance of breast cancer bone metastases to IACS treatment.

  Study EGAS00001006429

• Whole-Exome Sequencing analyses in tamoxifen-associated endometrial cancer

  An increased incidence of endometrial cancer has been described for patients that have received tamoxifen to treat breast cancer. Using samples from endometrial tumors, isolated from surgivcal specimens of patients who previously received tamoxifen treatment for breast cancer, we aimed to identify whether there are specific somatic mutations enriched in this population, relative to endometrial tumors from the general population. For this, WES was performed on matched endometrial tumors and healthy tissue (n=21).

  Study EGAS00001006453

• Genomic analysis and evolutionary modeling of breast and larynx cancer, based on specimens from Polish population

  We explore the genomic characteristics of the original dataset of breast and larynx cancer specimens of several cell types from the collection of the Department of Applied Radiology of the Maria Sklodowska-Curie National Research Institute of Oncology, Krakow (Poland) Branch and Institute of Human Genetics Polish Academy of Sciences. DNA from paired tissue samples from primary tumor locations and concurrent metastasis to regional lymph nodes was sequenced and matched to controls. A range of genomic analyses was carried out, such as estimation of variant allele frequencies (VAF) and copy number variation (CNV). They show that subsets of variants from primary tumors are present in metastatic lymph nodes and that the CNV pattern is similar, but not identical to that known in the literature. In addition to that, we fit the VAF data to theoretical site frequency spectra predicted by multiple models found in the literature. Analysis suggests existence of secondary advantageous subclones arising on the clonal background as well as of a number of neutral or slightly deleterious passenger mutations.

  Study EGAS00001006456

• High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1

  Lung adenocarcinoma is one of the most common cancer types with various treatment modalities. However, better biomarkers to predict therapeutic response are still needed to improve precision medicine. We utilized a consensus hierarchical clustering approach on 509 LUAD cases from TCGA to identify five robust LUAD expression subtypes. We then integrated genomic (patient and cell line) and proteomic data to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles.

  Study EGAS00001006461

• Colorectal cancer study

  Matrix metalloproteinase-11 (MMP11) is an enzyme with proteolytic activity against matrix and non-matrix proteins. Although most MMPs are secreted as inactive proenzymes and they are later activated extracellularly, MMP11 is activated intracellularly by furin within the constitutive secretory pathway. It is a key factor in physiological tissue remodeling and its alteration may play an important role in the progression of epithelial malignancies and other diseases. TCGA colon and colorectal adenocarcinoma data showed that upregulation of MMP11 expression correlates with tumorigenesis and malignancy. Here, we provide evidence that a germline variant in the MMP11 gene (NM_005940: c.232C>T; p.(Pro78Ser)), identified by whole exome sequencing, can increase the tumorigenic properties of colorectal cancer (CRC) cells. P78S is located in the prodomain region, which is responsible for blocking MMP11’s protease activity. This variant was detected in the proband and all the cancer-affected family members analyzed, while it was not detected in healthy relatives. In silico analyses predict that P78S could have an impact on the activation of the enzyme. Furthermore, our in vitro analyses show that the expression of P78S in HCT116 cells increases tumor cell invasion and proliferation. In summary, our results show that this variant could modify the structure of the MMP11 prodomain, producing a premature or uncontrolled activation of the enzyme that may contribute to an early CRC onset in these patients. The study of this gene in other CRC cases will provide further information about its role in CRC development, which might improve patient treatment in the future.

  Study EGAS00001006489

• Persistent Mutation Burden Drives Sustained Anti-Tumor Immune Responses

  Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss and discovered that clonal mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) that is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

  Study EGAS00001006660

• Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

  Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

  Study EGAS00001006490

• Finding structural variation from the human skin fibroblast at the single-cell level

  Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their molecular consequences. We present a computational method, scNOVA, that integrates haplotype-resolved SV discovery with nucleosome occupancy analysis using Strand-seq, to functionally characterize SVs in single cells.

  Study EGAS00001006498

• Gene signature for predicting homologous recombination deficiency in triple-negative breast cancer

  We developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 94 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for high levels of a mutational signature associated with HRD in an additional MyBrCa TNBC validation cohort (this EGA study) as well as in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.

  Study EGAS00001006518