14982 results for "cancer studies using rna-seq"

in 29.94 milliseconds.

• Evolutionary Trajectories of Small Cell Lung Cancer under Therapy

  Small cell lung cancer (SCLC) is one of the deadliest human cancers with a five-years survival rate of less than 7%. The standard of care for extensive-stage SCLC consists of systemic treatment with platinum and etoposide, recently combined with PD-L1 immune checkpoint inhibitors (ICI). SCLC patients show high sensitivity to platinum-based chemotherapy, followed by rapid recurrence, which distinguishes SCLC from most human cancers. Unfortunately, second-line treatment with other chemotherapeutics or immunotherapy is only marginally effective, and patients ultimately succumb to their disease. We performed whole exome sequencing, whole genome sequencing and transcriptome sequencing of multiple tumor regions from 65 patients with SCLC. We determined tumor phylogenies at diagnosis and throughout chemotherapy and immunotherapy by multi-region sequencing of 160 tumors from 65 patients, to thus decipher the evolutionary processes underlying the remarkable sensitivity of small cell lung cancer (SCLC) to chemotherapy.

  Study EGAS50000000169

• Characterization and clinical relevance of the genomic alterations defining invasive lobular breast cancer

  Background: Invasive lobular breast cancer (ILBC) is the second most common histological subtype after ductal breast cancer (IDBC). In spite of significant clinical and pathological differences, ILBC is still treated as IDBC. Here, we aimed at identifying recurrent genomic alterations in ILBC with potential clinical implications.Methods: Starting from 630 ILBC primary tumors with a median follow up of 10 years, we interrogated oncogenic substitutions and indels of 360 cancer genes and genome-wide copy number alterations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinical, pathological, and outcome features. The Cancer Genome Atlas database was used for comparison of frequency estimates.Results: Besides the high mutation frequency of CDH1 in 65% of the tumors, alterations in one of the three key genes of the PI3K pathway, PIK3CA, PTEN and AKT1, were present in more than half of the cases. ERBB2 and ERBB3 were mutated in 5.1 and 3.6% of the tumors. FOXA1 mutations and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than IDBC. The histological diversity of ILBC was associated with specific genomic alterations, such as enrichment for ERBB2 mutations in the mixed, non-classic subtype, and for ARID1A mutations and ESR1 gains in the solid subtype. Finally, ERBB2 and AKT1 mutations were associated with short-term risk of relapse, and chromosome 1q and 11p gain with increased and decreased breast cancer free survival, respectively.Conclusion: ERBB2, ERBB3 and AKT1 mutations represent high prevalence therapeutic targets in ILBC. FOXA1 mutations and ESR1 gains urgently deserve dedicated clinical investigation, especially in the context of endocrine treatment.

  Dataset EGAD00001001395

• Whole-genome sequencing in 14 cases and whole-exome sequencing in 90 cases of Chinese ESCC

  Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases.

  Study EGAS00001001487

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - WGS

  Whole genome sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015469

• Brain Arteriovenous Malformation Genetics Study

  The Predictors of Spontaneous Cerebral AVM Hemorrhage study was designed to identify genetic markers that predict adverse outcomes in brain arteriovenous malformation (BAVM) patients, examine race-ethnicity influences on BAVM hemorrhage risk, and use genome-wide association analysis to identify novel genetic predictors of AVM and hemorrhage using the Affymetrix GeneChip. We performed the first genome-wide association study (GWAS) (PMID: 26818729) of sporadic BAVM to investigate association of common single nucleotide polymorphisms (SNPs) with risk of sporadic BAVM in the international, multicenter Genetics of Arteriovenous Malformation (GEN-AVM) consortium. The study included a Caucasian discovery cohort of 515 BAVM cases and 1,191 controls genotyped using Affymetrix genome-wide SNP arrays. The Phase 1 discovery cohort comprised of 338 BAVM cases (154 male) and 504 controls genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0. The molecular data (individual genetic data) for the Phase 1 discovery cohort 338 BAVM cases (self-reported Caucasian) recruited at University of California, San Francisco, or Kaiser Permanente of Northern California (KPNC) are included in the dbGaP Study Report: Brain Arteriovenous Malformation Genetics Study, with the additional BAVM case phenotypic and sample attribute characteristics: sex, race, age at BAVM diagnosis, hemorrhagic presentation, BAVM size. Written informed consent was obtained from all participants and the study was approved by the respective Institutional Review Boards. The molecular dataset for this study in dbGaP is based on the genotypes obtained for the initial set of 906,600 SNPs for cases and controls called together using Birdseed v2 algorithm in Affymetrix Genotyping Console Software. The final QC'd dataset includes 717,335 markers as SNPs with MAF<0.01 or deviating from Hardy-Weinberg equilibrium (P<0.00001) in controls were excluded. After QC, the average genotyping call rate was 99%. The discovery phase GWAS identified 57 top BAVM-associated SNPs which were tested in a replication cohort including 608 BAVM cases and 744 controls. The molecular dataset for these 338 BAVM cases was also included in a report investigating common and rare genome-wide copy number variation for association with BAVM (PMID: 24098321), which included a total sample size of 371 sporadic Caucasian BAVM cases and 563 Caucasian controls. This study identified a CNV region on 1p36.13 (NBPF1 locus) that was significantly enriched with duplications in BAVM cases compared to controls, although this association did not replicate in an independent cohort of 184 sporadic BAVM cases and 182 controls. This resource will help researchers to better understand the genetic risk factors for BAVM and/or hemorrhage. These data may be applied to examine the genetic contributions to arteriovenous malformation, stroke, and related vascular disorders and may help generate hypotheses regarding the genetics of cerebrovascular disease.

  Study phs002069

• Health and Retirement Study (HRS)

  Introduction to V2: This data release comprises data from the V1 release combined with approximately 3,000 additional samples, collected during the HRS 2010 field period. The 2010 data include samples from a random half of the new cohort enrolled in 2010 along with a significant expansion of the minority sample. Description: The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of approximately 20,000 people in America over the age of 50 every two years. Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study collects information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Because of its innovation and importance, the HRS has become the model and hub for a growing network of harmonized longitudinal aging studies around the world. Origins of the HRS. As the population ages it is increasingly important to obtain reliable data about aging and topics that are relevant to a range of policy issues in aging. To address this need, the National Institutes on Aging (NIA) established a cooperative agreement with the University of Michigan Institute for Social Research to collect such data. The HRS launched data collection in 1992 and has re-interviewed the original sample of respondents every two years since then. By adding new cohorts and refreshing the sample, the HRS has grown to become the largest, most representative longitudinal panel study of Americans 50 years and older. HRS Study Design. The target population for the original HRS cohort includes all adults in the contiguous United States born during the years 1931-1941 who reside in households, with a 2:1 oversample of African-American and Hispanic populations. The original sample is refreshed with new birth cohorts (51-56 years of age) every six years. The sample has been expanded over the years to include a broader range of birth cohorts as well. The target population for the AHEAD survey consists of United States household residents who were born in 1923 or earlier. Children of the Depression (CODA) recruits households born 1924-1930, War Babies 1942-47, Early Boomers 1948-53, and Mid-Boomers 1954-59. Data collection includes a mixed mode design combining in-person, telephone, mail, and Internet. For consenting respondents, HRS data are linked at the individual level to administrative records from Social Security and Medicare claims. Genetic Research in the HRS. The HRS has genotyped 2.5 million single nucleotide polymorphisms (SNPs) on respondents using Illumina's Human Omni2.5-Quad (Omni2.5) BeadChip. The genotyping was performed by the NIH Center for Inherited Disease Research (CIDR). Saliva was collected on half of the HRS sample each wave starting in 2006. In 2006, saliva was collected using a mouthwash collection method. From 2008 onward, the data collection method switched to the Oragene kit. Saliva completion rates were 83% in 2006, 84% in 2008, and 80% in 2010 among new cohort enrollees. HRS Phenotypic data. Phenotypic data are available on a variety of dimensions. Health measures include physical/psychological self-report, various health conditions, disabilities, cognitive performance, health behaviors (smoking, drinking, exercise), physical performance and anthropomorphic measures, and biomarkers (HbA1c, Total Cholesterol, HDL, CRP, Cystatin-C). Data are also available on health services including utilization, insurance and out-of-pocket spending with linkage to Medicare records. Economic measures include employment status/history, earnings, disability, retirement, type of work, income by source, wealth by asset type, capital gains/debt, consumption, linkage to pensions, Social Security earnings/benefit histories. There is also extensive information on family structure, proximity, transfers to/from of money, time, social and psychological characteristics, as well as a wide range of demographics. Performance on a cognitive test combining immediate and delayed word recall was selected as an example trait for the dbGaP data release. In the immediate word recall task the interviewer reads a list of 10 nouns to the respondent and asks the respondent to recall as many words as possible from the list in any order. After approximately five minutes of asking other survey questions, the respondent is asked to recall the nouns previously presented as part of the immediate recall task. The total recall score is the sum of the correct answers to these two tasks, with a range of 0 to 20. Researchers who wish to link to other HRS measures not in dbGaP will be able to apply for access from HRS. A separate Data Use Agreement (DUA) will be required for linkage to the HRS data. See the HRS website (http://hrsonline.isr.umich.edu/gwas) for details.

  Study phs000428

• Molecular Biomarkers Predicting Lung Cancer Response Phenotypes

  We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.

  Study phs001823

• Somatic Genome Dynamics of Barrett's Esophagus Patients with Non-Cancer and Cancer Outcomes

  A case-control study was designed with 80 participants diagnosed with Barrett's Esophagus (BE) selected from a larger case-cohort study (Li et al., 2014, PMID: 24253313) within the Seattle Barrett's Esophagus Program (SBEP) at the Fred Hutchinson Cancer Research Center. The study included 40 cases with BE with non-cancer outcomes, "NCO", who did not progress to esophageal adenocarcinoma (EA), and 40 controls who progressed to an endoscopically detected, incident EA (cancer outcome, "CO"). For each patient, two timepoints were evaluated (T1 and T2). NCO were matched to CO based on age at T1 (T1=first endoscopy with sufficient sample availability), and time between T1 and T2 (T2 in CO=time of diagnosis of incident EA). In 10 NCO, a third time point (T3), a mean of 13.2 years after T1, was also sequenced. Mapped endoscopic biopsies, at 1/3 and 2/3 annotated distances from the gastroesophageal junction within the Barrett's segment, were sampled per patient at each timepoint. Each biopsy was purified to separate BE epithelium from stroma, and DNA was extracted from purified epithelium for 60X WGS and 2.5M SNP array; normal control blood (N=62) or normal gastric sample (N=18) were analyzed by 30X WGS and 2.5M SNP array. An additional seven normal gastric biopsy samples in seven patients with normal control blood were also sequenced at 60X as controls. All research participants contributing clinical data and esophageal samples to this study provided written informed consent, subject to oversight by the Fred Hutchinson Cancer Research Center IRB Committee D (Reg ID 5619).

  Study phs001912

• Oncogenome of Kaposi Sarcoma

  Kaposi Sarcoma (KS) is an aggressive cancer caused by the Kaposi Sarcoma Herpesvirus (KSHV/HHV-8). Individuals with immunodeficiencies, exemplified by HIV, have an elevated risk of developing KS. However, understanding of the genetic factors contributing to KS progression is still limited. To explore potential genetic alterations in KS that could offer biological or therapeutic insights, whole exome sequencing was performed on 78 KS tumors and matching normal skin samples from 59 adults with KS (46 with HIV-associated KS and 13 with HIV-negative KS) receiving treatment at the Uganda Cancer Institute in Kampala, Uganda. Results showed a very low mutational burden in all samples except one (median = 11 mutations), which is the smallest number of mutations found across all 33 cancer types in The Cancer Genome Atlas (TCGA). No recurrent mutations were identified. Mutational signatures included impaired DNA mismatch repair and smoking. There was no evidence suggesting that multiple tumors from the same patient originated from a single clone. The number of genome copy alterations per genome was higher in tumors from individuals without HIV and those with advanced-stage disease. This suggests that lesions that take longer to develop may accumulate more alterations, although the overall number of alterations remains low compared to other cancers. These findings suggest that KS pathogenesis differs from other cancers, with KSHV viral infection and the expression of viral oncogenes being the primary drivers of carcinogenesis, rather than clonal oncogenic transformation arising from genetic alterations of cancer-related cellular genes.

  Study phs003897

• A novel breast cancer cell line derived from a metastatic bone lesion of a breast cancer patient

  Purpose: We sought to generate and characterize a novel cell line from a breast cancer bone metastasis in order to better study the progression of the disease.Methods: The cell line, P7731, was derived from a metastatic bone lesion of a breast cancer patient and assessed for marker expression. P7731 was analyzed for DNA copy number variation, somatic mutations and gene expression and compared to the primary tumor. Results: P7731 cells are negative for estrogen receptor alpha (ERα), progesterone receptor (PR) and HER2 (triple-negative), strongly express vimentin (100% of cells positive) and also express cytokeratins 8/18 and 19 but at lower frequencies. Flow cytometry indicates P7731 cells are predominantly CD44+/CD49f+/EpCAM-, consistent with a primitive, mesenchymal-like phenotype. The cell line is tumorigenic in immunocompromised mice. Exome sequencing identified a total of 45 and 76 somatic mutations in the primary tumor and cell line respectively, of which 32 were identified in both samples and included mutations in known driver genes PIK3CA, TP53 and ARID1A. P7731 retains the DNA copy number alterations present in the matching primary tumor. Homozygous deletions detected in the cell line and in the primary tumor were found in regions containing three known (CDKN2A, CDKN2B and CDKN1B) and 23 putative tumor suppressor genes. Cell line specific gene amplification coupled with mRNA expression analysis revealed genes and pathways with potential pro-metastatic functions.Conclusion: This novel human breast cancer-bone metastasis cell line will be a useful model to study aspects of breast cancer biology, particularly metastasis-related changes from breast to bone.

  Study EGAS00001002840

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Genotyping_data_total

  Genotyping data for ACE2 (rs2285666), MX1 (rs469390) and TMPRSS2 (rs2070788) variants. Patients are classified as mild (n=34) and severe (n=32). DNA genotyping was performed using the TaqMan® Genotyping Master Mix (Applied Biosystems). Allelic discrimination assays were performed on a 7900HT Fast Real-Time PCR System (Applied Biosystems).

  Dataset EGAD00010002445

• Whole genome sequencing of Sinonasal hemangiopericytoma and patient derived cell line model

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. In this study, a novel SFT/HPC was characterized using whole genome sequencing.

  Dataset EGAD50000000038

• Raw ONT R10 data: Rapid brain tumor classification from sparse epigenomic data

  This dataset contains 207 samples sequenced using rapid-multiplexed barcoded library preparation on Nanopore PromethION R10 flow cells on P2 Solo and P24 systems. One unaligned BAM file per sample is provided.

  Dataset EGAD50000000791