9338 results for "cancer rna-seq"

in 43.77 milliseconds.

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• Discovery of Colorectal Cancer Susceptibility Genes in High-Risk Families

  Colorectal cancer remains one of the most common cancers in the US with 146,970 new diagnoses and 49,920 deaths estimated for 2009. Colon cancer is also one of the most familial of cancers. Individuals with a first-degree relative with colon cancer have a 2- to 3-fold increased risk, and those with more than one first-degree relative with colon cancer, or a single first-degree relative affected at age 50 years, have a 3- to 6-fold greater risk than those with no family history. The most prominent high-risk colorectal cancer susceptibility genes, APC, MLH1, MSH2, MSH6, and PTEN, were all discovered more than a decade ago. Currently, mutation screening of these genes, plus a short list of additional genes that are responsible for a very small fraction of colorectal cancer, plays an important role in the clinical management of individuals with a strong family history of the disease or syndromic evidence for the presence of a gene mutation. At the other end of the risk spectrum, genome-wide association studies have identified a number of common alleles with very modest effects on colorectal cancer risk; their clinical utility has yet to be established. However, taken together, the known spectrum of genetic effects only explain about one quarter of the overall familial excess of colorectal cancer. It should be emphasized that, at present, the vast majority of individuals seen at familial cancer clinics are counseled on the basis of their family history alone because they do not have mutations in the known susceptibility genes. Accordingly, the long-term objective of this project is to identify the majority of genes responsible for the unexplained component of inherited colorectal cancer risk. Nextgen DNA sequencing is well suited for application to research questions in genetic susceptibility for which linkage analysis is confounded by extensive genetic heterogeneity. Taking advantage of unparalleled familial cancer genetics resources available through the Utah Population Database, candidate genes have been identified by sequencing all of the gene exons in the human genome from a series of colorectal cancer cases with a very strong family history of colorectal cancer not explained by one of the currently known high-risk susceptibility genes.

  Study phs001787

• FGFR-driven urothelial cancer

  Study EGAS00001007335

• Elucidating the development of cervical cancer and identifying therapeutic targets based on cancer genome analysis.

  The objective of this project is to analyze genomic aberrations and gene expression changes, such as mutations, deletions, and amplifications, in human cervical cancer cells at the somatic cell level, and to contrast these with clinicopathological information to elucidate the molecular mechanisms and characteristics of lcervical cancer development and progression at the genetic level.

  Study JGAS000803

• Cancer genomics for elucidation of molecular mechanisms of carcinogenecis and progression in lung cancer

  The objective of this project is to analyze genomic aberrations and gene expression changes such as mutations, deletions, amplifications, and hypermethylation in human lung cancer cells at the somatic cell level, and to contrast these with clinicopathological information to elucidate the molecular mechanisms and characteristics of lung cancer development and progression at the genetic level.

  Study JGAS000756

• Systematic identification of long non-coding RNAs potentially involved in gastrointestinal carncer

  Recent work has suggested various important functions and molecular mechanisms for long non-coding RNAs (lncRNAs) and they are also thought to play critical roles in cancer. However the importance of lncRNAs in cancer biology is still unclear. In this study, we aim to comprehensively identify novel lncRNAs that are critically involved in tumorigenesis and progression in gastrointestinal cancer.

  Study JGAS000011

• Linking the epigenetic landscape in chronic lymphocytic leukemia to deregulated chromatin networks

  Aberrant chromatin features and epigenetic signaling emerge as an important part of the tumor disease state in chronic lymphocytic leukemia (CLL). However, an integrative analysis of the malignant chromatin landscape is currently missing. Here, we mapped DNA-methylation, nucleosome position, 7 histone modifications, ATAC-seq and the transcriptome in primary CD19+ sorted B-cells from the peripheral blood of CLL patients in comparison to non-malignant lymphocytes of healthy donor reference samples. On the > 50 kb scale we identified global differences with respect to DNA methylation, nucleosome positioning and histone modifications in CLL. Furthermore, a chromatin state annotation was developed to identify deregulated chromatin features of promoters and enhancers in CLL. By integrating these findings with an ATAC-seq based transcription factor binding analysis we identified a set of promoters and enhancers specific to CLL that were enriched in certain transcription factors binding motifs and genes of the BCR signaling pathway. Thus, our study provides an in-depth map of the CLL chromatin landscape and links chromatin state changes at promoters and enhancers to deregulated pathways.

  Study EGAS00001002518

• A Single-cell Atlas of Progressive TKI Resistance in Chronic Myeloid Leukemia

  High-dimensional scRNA seq and CyTOF were used to identify features predictive of treatment outcome at diagnosis. An optimal TKI response was characterised by erythroid lineage skewing of the CD34+ HSPC compartment. While TKI-resistant CP was reminiscent of a BC-like state, where HSPCs were enriched for inflammation, stemness and quiescence. We designed a machine-learning approach which assessed the prognostic potential of all 32 sub-populations of our scRNA seq dataset. LSCs and NK populations harboured the highest prognostic power at diagnosis. Within the LSCs, erythroid lineage priming and MYC activation were features of an optimal and poor TKI responses, respectively. With the NK cell compartment, apart from a higher abundance of NK cells in TKI optimal responders, a memory-like HLA-DR+ adaptive NK and KLRC1+ NK populations were hallmarks of an optimal and poor TKI responses, respectively. Mechanistically, both cell intrinsic and extrinsic mechanisms contributed towards the higher sensitivity of EPs to TKI therapy. In summary, our high-dimensional single-cell atlas of TKI resistance highlights pivotal transcriptional features associated with TKI-resistance disease, some of which have the potential to be exploited as biomarkers.

  Study EGAS00001005509

• Colon Cancer Family Registry (Colon CFR)

  The Colon Cancer Family Registry Cohort (CCFRC www.coloncfr.org) is a cohort of families recruited through six study sites located in the USA, Canada, Australia, and New Zealand. The CCFRC was formed as a resource to support studies on the etiology, prevention, and clinical management of colorectal cancer. Recruitment protocols fall broadly into two main categories: population-based and clinic-based ascertainment. Between 1998 and 2013, the CCFR recruited and interviewed probands who were either recently diagnosed with colorectal cancer that was reported to state or regional population cancer registries in the United States (Washington, California, Arizona, Minnesota, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria), and Canada (Ontario) or were from multiple-case families referred to family-cancer clinics in the United States (Mayo Clinic in Rochester, Minnesota, and Cleveland Clinic in Cleveland, Ohio), Australia (Melbourne, Adelaide, Perth, Brisbane, and Sydney), New Zealand (Auckland), and Canada. Cases with known familial adenomatous polyposis were excluded. Once recruited, probands were asked for permission to contact their relatives for recruitment. Collectively, we have enrolled 42,49874 participants in 15,048 families who participated in standardized protocols used to collect information regarding family cancer history and colorectal cancer risk factors and biospecimens. All participants of population-based case families (excluding control-families) and clinic-based families are asked to provide updates on their personal and family history of cancer as well as their history of surgery, cancer screening, and some risk factors every 4-5 years either by telephone interview or by self-completed questionnaire via mail or online (PMID: 17982118).

  Study phs002733

• Breast Cancer Family Registry

  The Breast Cancer Family Registry (BCFR) is a multi-center prospective cohort, comprised of over 30,000 women and men from nearly 12,000 families from the United States, Canada, and Australia. Our BCFR resource has been used, and continues to be used, by breast cancer researchers around the world in order to find new ways to prevent, diagnose, and treat cancer. The BCFR provides an extensive and diverse range of resources, expertise, and specialized skills, and has several unique strengths: 1) the collection of a large number of individuals and families across a wide spectrum of breast cancer risk, including both affected and unaffected individuals; 2) the large collection of families with early-onset breast cancer; 3) the large collection of racial/ethnic minority families not replicated elsewhere; 4) the extensive molecular characterization performed to date; and 5) active follow-up of both probands and family members. Thus, the BCFR comprises a unique cohort of probands and family members at familial/genetic risk of breast cancer that will continue to facilitate a wide range of research studies, such as gene discovery, examination of cancer-related outcomes and risk factors in high-risk subjects, investigation of novel behavioral interventions, and cancer prevention trials among at-risk family members. Consequently, the BCFR Cohort, as one of the few cohorts available worldwide with biospecimens and extensive molecular and genetic characterization, combined with epidemiologic data and long-term follow up, will be an invaluable resource for translational research in the genetic epidemiology of breast cancer.

  Study phs002835

• LifeLines-DEEP 16s seq

  16S sequencing of stool samples of LifeLines-DEEP, domain V4

  Dataset EGAD00001003453

• ChIP-sequencing

  Raw reads from ChIP- [Anti-Histone H3 (acetyl K27) (Abcam, ab4729)] and input sequencing of EBV transformed lymphoblastoid cells from three carriers of TET2 mutation (Ly9, Ly11 and Ly14) and two wild-type (Ly8 and Ly10) family members using Illumina HiSeq Rapid paired-end 60 bp sequencing.

  Dataset EGAD00001004781

• Chromatin accessibility in human monocyte differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 26 samples.

  Dataset EGAD00001006601

• SMRT-seq

  In this study, we enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model.

  Dataset EGAD00001006875

• 17 skin and oral epithelial bulk samples from 2 donors

  Aligned BAM files with removed duplicate reads of targeted sequencing data (exomes of a panel of 153 genes) from 12 skin and 5 oral epithelial bulk samples from 2 donors. Sequences generated by the BGI DNB-SEQ platform.

  Dataset EGAD00001008956

• BLUEPRINT Methylome saturation and COMET analysis of monocyte samples

  Bisulfite-Seq of CD14-positive, CD16-negative classical monocyte samples for methylome saturation and COMET analysis

  Dataset EGAD00001001261

• scATAC-seq of first and second trimester human gonads - HUGODECA dataset

  Comprehensive map of first- and second-trimester gonadal development in humans using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays, and imaging. ArrayExpress Accession: E-MTAB-10570

  Dataset EGAD00001009387

• Whole Exome Sequencing of Colorectal Cancer Patients from the Nurses' Health Study (NHS) and Health Professionals Follow-up Study (HPFS)

  Colorectal cancer is a molecularly heterogeneous disease. Whole Exome Sequencing from patients diagnosed with colorectal cancer in the NHS and HPFS cohorts will extend our understanding of the genetic changes occurring in specific clinical contexts in the disease. This effort has the potential to discover novel recurrently mutated genes and pathways in colorectal cancer that can be functionally validated and give further insights to colorectal cancer pathogenesis. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000.

  Study phs000722

• Breast Cancer Risk Pathways

  We sought to identify genomic variants that differed between individuals who developed familial breast cancer and individuals who had a family history of breast cancer but who had not developed breast cancer. We aggregated these data at the pathway level to identify pathways that play a role in familial breast cancer development. We profiled peripheral blood cells, extracted DNA, and sequenced the DNA using exome-capture sequencing to identify genomic variants in these samples. For 34 of the 35 samples, we also profiled peripheral blood using Affymetrix Human Exon 1.0 ST Array microarrays. Those data can be found in Gene Expression Omnibus under accession identifier GSE47862.

  Study phs001044

• Development of molecular targeted therapy for small cell lung cancer by comprehensive genome analysis

  Aims: Identifying new therapeutic targets of small cell lung cancer (SCLC), genome-wide mutation analysis has been performed. Methods: Genomic DNA was extracted from formalin-fixed or methanol-fixed tissue samples. 71 Mb of DNA fragments containing whole coding exons were concentrated using SureSelect Human All Exon V4+UTRs Kit (Agilent Technologies) followed by 100-bp paired end sequencing by HiSeq 2000 (Illumina). Participants/Materials: 51 of 1042 cases of pathologically diagnosed small seen lung cancer that were registered to National Cancer Hospital East Lung Cancer Database in 1992-2012, and which surgically resected or biopsy samples were suitable for DNA extraction for further analyses.

  Study JGAS000037

• Whole-exome Sequencing Combined with Functional Genomics Reveals Novel Candidate Driver Cancer Genes in Endometrial Cancer

  Endometrial cancer is the most common gynecological malignancy, with more than 280,000 cases occurring annually worldwide. Although previous studies have identified important common somatic mutations in endometrial cancer, they have primarily focused on a small set of known cancer genes and have thus provided a limited view of the molecular basis underlying this disease. Here we developed an integrated systems biology approach to identifying novel cancer genes contributing to endometrial tumorigenesis. We first performed whole-exome sequencing on 13 endometrial cancers and matched normal samples, systematically identifying somatic alterations with high precision and sensitivity. We then combined bioinformatics prioritization with high-throughput screening (including both shRNA-mediated knockdown and expression of wild type and mutant constructs) in a highly sensitive cell viability assay. Our results revealed 12 potential driver cancer genes including 10 tumor suppressor candidates (ARID1A, INHBA, KMO, TTLL5, GRM8, IGFBP3, AKTIP, PHKA2, TRPS1 and WNT11) and two oncogene candidates (ERBB3 and RPS6KC1). The results in the “sensor” cell line were recapitulated by siRNA-mediated knockdown in endometrial cancer cell lines. Focusing on ARID1A, we integrated mutation profiles with functional proteomics in 222 endometrial cancer samples, demonstrating that ARID1A mutations frequently co-occur with mutations in the phosphatidylinositol 3-kinase (PI3K) pathway and are associated with PI3K pathway activation. siRNA knockdown in endometrial cancer cell lines increased AKT phosphorylation supporting ARID1A as a novel regulator of PI3K pathway activity. Our study presents the first unbiased view of somatic coding mutations in endometrial cancer and provides functional evidence for diverse driver genes and mutations in this disease.

  Study EGAS00001000318

• Molecular Profiling of Gallbladder Cancer (MPOG)

  The purpose of this study is to investigate the underlying genetic factors involved in gallbladder cancer.

  Study phs001404

• Genomics_of_Colorectal_Cancer_Metastases___Massively_Parallel_Sequencing_of_Matched_Primary_and_Metastatic_tumours_to_Identify_a_Metastatic_Signature_of_Somatic_Mutations__MOSAIC_

  Exome pulldown and SNP6 Affymetrix array of matched primary and metastatic colorectal cancer samples from 20 patients

  Study EGAS00001000103

• Pulldown_cytosine_deaminases

  We are looking at the causal factors behind hyper-mutator phenotypes found in previous Breast Cancer sequencing studies.

  Study EGAS00001000233

• Non-small cell lung cancer sequencing

  Study EGAS00001005499