6140 results for "canc*"

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• Genomic analysis of Smoothened inhibitor resistance in basal cell carcinoma

  Smoothened inhibitors are currently being investigated for the treatment of several cancers. Vismodegib is approved for the treatment of locally advanced and metastatic basal cell carcinoma (BCC). The majority of BCC patients treated with vismodegib experience significant clinical benefit, however, a small number of patients develop resistance. Knowledge of resistance mechanisms can generate predictive biomarkers and is critical for the design of additional therapeutic strategies aimed at circumventing resistance. To investigate mechanisms of resistance to vismodegib in BCC we sequenced and profiled biopsies from patients who initially responded to treatment and subsequently progressed on drug.We find that resistance is associated with re-activation of the Hedgehog (Hh) pathway through diverse mechanisms, including concurrent copy number alterations in the downstream Hh pathway components SUFU and GLI2, as well as novel SMO mutations that reduce sensitivity to vismodegib. The latter fall into two classes: those that activate SMO and those that directly affect the vismodegib-binding pocket. Additionally, we observe evidence of clonal selection of SMO mutations and intra-tumor heterogeneity of resistance mechanisms, which implies diverse and combinatorial strategies are required to overcome resistance.

  Study EGAS00001000845

• Systems biology of Colorectal Cancer

  Colorectal cancer (CRC) is one of the most common cancers in both males and females, and it is perhaps the best understood of all epithelial tumors in terms of its molecular origin. Yet, despite large amount of work that has concentrated on understanding of colon tumorigenesis, we still do not know the full complement of molecular lesions that are individually necessary – and together sufficient – to cause colorectal cancer. Neither do we understand why some specific mutations that are relatively rare in other tumors (e.g. loss of the APC tumor suppressor) are extremely common in colorectal cancer. We propose here to use the tools of systems biology to develop a quantitative and comprehensive model of colorectal tumorigenesis. The model will include identification of cell-type specific and oncogenic pathways that contribute to colon tumorigenesis, and explain in molecular detail how a genotype of an individual CRC leads to activation of downstream genes that drive uncontrolled cell growth. This model will subsequently be used to find novel therapeutic targets, to guide genetic screening to identify individuals with elevated risk for developing CRC, and to classify patients into molecular subgroups to select the treatment combination that is optimal for each patient (personalized medicine). The specific objectives of the SYSCOL project are: 1. Identify genetic markers for individual risk using genotyping and sequencing of constitutional DNA from sporadic and familial CRC cases and controls 2. Identify genes and regulatory elements that contribute to colorectal cancer cell growth 3. Use data from Aims 1-2 to develop a quantitative model for colorectal tumorigenesis 4. Apply the model for identification of high-risk individuals, for molecular classification of the disease, and for identification of novel molecular treatment targets

  Study EGAS00001000854

• Molecular Subtype-specific Biomarkers Improves Colorectal Cancer Prognostication

  Colorectal cancer (CRC) is characterized by major inter-tumor diversity that complicates the prediction of disease and treatment outcomes. Recent efforts help resolve this by sub-classification of CRC according to natural molecular subtypes, however, this strategy is not yet able to provide clinicians with improved tools for decision-making. We here present an extended framework for CRC stratification that specifically aims to improve patient prognostication. Using transcriptional profiles from 1,100 CRCs, including a novel set of >300 samples, we identify novel cancer cell and tumor archetypes and suggest the tumor microenvironment as a major prognostic determinant that can be influenced by the microbiome. Notably, our subtyping strategy allowed identification of novel archetype-specific prognostic biomarkers that provided information beyond and independent of UICC-TNM staging, MSI-status and consensus molecular subtyping. The results illustrate that our extended subtyping framework, combining subtyping and subtype-specific biomarkers, could contribute to improved patient prognostication and may form a strong basis for future studies.

  Study EGAS00001002376

• Whole exome sequencing for gallbladder cancer in Xinhua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine

  Patients with gallbladder carcinoma (GBC), the most aggressive malignancy of the biliary tract, have a poor prognosis. Here, we report our identification of somatic mutations of GBCs in 57 tumor-normal pairs by use of a combination of exome sequencing and ultra-deep sequencing of cancer-related genes. The mutation pattern is defined by a dominative prevalence of C>T mutations at TCN sites. Genes with a significant frequency of non-silent mutations include TP53 (47.1%), KRAS (7.8%), and ERBB3 (11.8%). Moreover, ErbB signaling (including EGFR, ERBB2, ERBB3, ERBB4 and their downstream genes) is the most extensively mutated pathway, affecting 36.8% (21 of 57) of the GBC samples. Multivariate analyses further reveal that patients with ErbB pathway mutations have a worse outcome (P = 0.001). These findings provide insight into the somatic mutational landscape in GBC and highlight the key role of the ErbB signaling pathway in the pathogenesis of GBCs.

  Study EGAS00001000853

• Study on the proliferation history of colorectal adenomas

  Mismatch repair (MMR) deficient colorectal adenomas are composed of transformed cells that descend from a common founder and progressively accumulate genomic alterations but their proliferation history is still largely unknown. Here we rebuilt the proliferation history of four MMR deficient colorectal adenomas from male individuals by deep sequencing the X chromosome and mapping the somatic mutations that were progressively acquired during tumor growth. We developed a novel method to call high and low frequency mutations, to cluster them according to their frequencies and rebuild the proliferation trees directly from these mutation clusters using a recursive algorithm. The trees of all four lesions were formed of a dominant subclone that coexisted with other genetically heterogeneous subpopulations of cells. Despite this similar hierarchical organization, however, the growth dynamics varied among and within tumors, likely depending on a combination of tumor-specific genetic and environmental factors. Our study provides insights into the biological properties of individual MMR deficient colorectal adenomas that may influence their growth and also the response to therapy. Extended to other solid tumors, our approach could inform on the mechanisms of cancer progression, thus providing insight into the best choice of cancer treatment methods.

  Study EGAS00001000883

• Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies

  Massively parallel sequencing has revolutionized research in cancer genetics and genomics and enhanced our understanding of natural human genetic variation. Recently, Lam et al. have performed a detailed comparison of two next-generation sequencing technologies with respect to their sensitivity to call single nucleotide variants (SNV) and indels. Here, we sequenced two tumor/normal pairs obtained from two paedriatic medulloblastoma patients with Life Technologies’ SOLiD 4 and 5500xl SOLiD, Illumina’s HiSeq2000, and Complete Genomics’ technology. We then compared their ability to call SNVs with high confidence. As gold standard for SNV calling, we used genotypes determined by an Affymetrix SNP array. Additionally, we performed a detailed analysis of how evenly each technology covers the genome and how the reads are distributed across functional genomic regions. Finally, we studied how a combination of data from different technologies might help to overcome the limitations in SNV calling by any of the four technologies alone.

  Study EGAS00001000274

• Tumor-derived exosomes modulate PD-L1 expression in monocytes

  In chronic lymphocytic leukemia (CLL), monocytes and macrophages are skewed toward protumorigenic phenotypes, including the release of tumor-supportive cytokines and the expression of immunosuppressive molecules such as programmed cell death 1 ligand 1 (PD-L1). To understand the mechanism driving protumorigenic skewing in CLL, we evaluated the role of tumor cell–derived exosomes in the cross-talk with monocytes. We carried out RNA sequencing and proteome analyses of CLL-derived exosomes and identified noncoding Y RNA hY4 as a highly abundant RNA species that is enriched in exosomes from plasma of CLL patients compared with healthy donor samples. Transfer of CLL-derived exosomes or hY4 alone to monocytes resulted in key CLL-associated phenotypes, including the release of cytokines, such as C-C motif chemokine ligand 2 (CCL2), CCL4, and interleukin-6, and the expression of PD-L1. These responses were abolished in Toll-like receptor 7 (TLR7)–deficient monocytes, suggesting exosomal hY4 as a driver of TLR7 signaling. Pharmacologic inhibition of endosomal TLR signaling resulted in a substantially reduced activation of monocytes in vitro and attenuated CLL development in vivo. Our results indicate that exosome-mediated transfer of noncoding RNAs to monocytes contributes to cancer-related inflammation and concurrent immune escape via PD-L1 expression.

  Study EGAS00001002377

• GENOMIC INSTABILITY IN MISMATCH REPAIR DEFICIENT COLORECTAL CANCER

  Here we performed whole exome sequencing on a series of 47 mismatch repair (MMR) deficient colorectal cancers (CRC) in order to identified key events in tumoral initiation and progression

  Study EGAS00001002477

• A biobank of patient-derived pediatric brain tumor models

  Brain tumors are the leading cause of cancer-related death in children. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of pediatric brain tumors that may lead to novel therapeutic strategies. To evaluate new treatments, better preclinical models adequately reflecting the biological heterogeneity are needed. Through the Children’s Oncology Group ACNS02B3 study, we have generated and comprehensively characterized 30 patient-derived orthotopic xenograft models and 7 cell lines representing 14 molecular subgroups of pediatric brain tumors. Patient-derived orthotopic xenograft models were found to be representative of the human tumors they were derived from in terms of histology, immunohistochemistry, gene expression, DNA methylation, copy number, and mutational profiles. In vivo drug sensitivity of targeted therapeutics was associated with distinct molecular tumor subgroups and specific genetic alterations. These models and their molecular characterization provide an unprecedented resource for the cancer community to study key oncogenic drivers and to evaluate novel treatment strategies.

  Study EGAS00001002536

• Therapeutic Targeting of Ependymoma as Informed by Oncogenic Enhancer Profiling

  Genomic sequencing has driven precision-based oncology therapy; however, genetic drivers remain unknown or non-targetable for many malignancies, demanding alternative approaches to identify therapeutic leads. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Here, we mapped active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts. Enhancer regions revealed novel oncogenes, molecular targets, and pathways, which when subjected to small molecule inhibitor or shRNA treatment, increased survival and slowed proliferation in mouse and neurosphere patient-derived models of ependymomas. This study represents one of the largest enhancer mapping study of any cancer type to date, and provides a framework for target and drug discovery for other cancers recalcitrant to therapeutic development because of their lack of known genetic drivers.

  Study EGAS00001002696