11810 results for "cancer rna-seq"

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• RESOLVE_trial_targeted_sequencing_data

  RESOLVE: Abemaciclib + Letrozole +/_- Metformin, Zotatifin, or Gedatolisib in Endometrial or Low-Grade Serous Ovarian Cancer

  Study EGAS50000001202

• Dataset for hepatopancreaticobiliary_malignancy-RNA

  Rare cancer sequencing data of 119 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008863

• OncoArray: Oral and Pharynx Cancer

  Genetic factors play an important role in susceptibility to head and neck cancer and could also explain differences in response to treatment and outcome. The goal of this project is to investigate genetic variation involved in oral and oropharyngeal cancer susceptibility by performing the largest GWAS on these diseases, using a novel genotyping tool specifically designed for cancer studies by the OncoArray Network. This project encompasses data from approximately 6000 oral and pharynx cancer cases and 4000 controls derived from 12 epidemiological studies most of case-control design. The genotyping was centralized at the Center for Inherited Disease Research (CIDR), and the epidemiological data harmonization and analysis were completed at the International Agency for Research on Cancer (IARC). This study was supported by National Institute of Dental and Craniofacial Research (NIDCR) with direct funding to CIDR.

  Study phs001202

• End motifs analysis of circulating DNA from the plasma of patients with stage II-III breast cancer (n=50), stage I-III non-small cell lung cancer (n=56), metastatic colorectal cancer (mCRC) (n=15) and healthy individuals (n=37)..

  We have developed an algorithm designed to discriminate cancer patients and healthy individuals based on cirDNA fragment end motif analysis assisted by machine learning, using data obtained from shallow whole genome sequencing (a method we call EMA). We applied EMA to cirDNA from the plasma of patients with stage II-III breast cancer, stage I-III non-small cell lung cancer, and metastatic colorectal cancer (mCRC). CirDNA from 158 individuals was prepared following the conventional double-stranded DNA library preparation (DSP). We also performed a single-stranded DNA library preparation (SSP) using mCRC patients and healthy control cirDNA, which allowed us to make the first ever end motif analysis in the literature which compares the use of DSP and SSP.

  Study EGAS50000001319

• Molecular Signature of Saudi Thyroid Cancer Using whole exome sequencing

  In Saudi Arabia, thyroid cancer ranked second only to breast cancer among females, eleventh among males and this increased incidence is prevalent in other Gulf Council Countries also. Differentiated thyroid cancer, which includes papillary thyroid cancer (PTC) and follicular subtypes, accounts for 90% of all thyroid malignancies. Currently, there are no clinical or molecular diagnostic tools to predict recurrence and aggressiveness of a subset of PTC. With the goal of better understanding the pathobiology of thyroid carcinogenesis we will use Whole Exome Sequencing to decipher the molecular and genetic signature of Saudi PTC based on International Cancer Genome Consortium (ICGC) Guidelines. The study will provide a better understanding of PTC and should have important clinical implications in the development of new and better strategies for targeted therapeutic intervention for the treatment of Saudi Arabian PTC

  Study EGAS00001000680

• Genome-wide cell-free DNA biological patterns in patients with cancer

  The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

  Study EGAS00001007400

• Genome-Wide Association Study of Endometrial Cancer in the Epidemiology of Endometrial Cancer Consortium (E2C2)

  Endometrial cancer, the most common gynecological malignancy in the United States, has both an environmental and genetic component. To this end, we conducted a genome-wide association study to identify genes involved in endometrial cancer using studies from the NCI-supported Epidemiology of Endometrial Cancer Consortium (E2C2). For the discovery stage we included samples from 6 cohort and 7 case control studies through 2007. The total number of cases genotyped were 2,307, white women of European descent, and 2,307 matched controls using the Illumina HumanOmniExpress platform. We conducted the replication using the Infinium HumanExome BeadChip, which successfully genotyped 177,139 variants in 1055 cases and 1778 controls from four ethnically diverse studies that are part of the Epidemiology of Endometrial Cancer Consortium (E2C2). The overall goal is to determine whether certain genotypes are predictive of future endometrial cancer risk, and whether the genotypes interact with established endometrial risk factors.

  Study phs000893

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• FIGHT-207: Anonymized Genomic Alterations and Clinical Responses

  Background: FIGHT-207 was a phase 2 study of the FGFR1-FGFR3 inhibitor pemigatinib in patients with previously treated, locally advanced/metastatic or unresectable solid tumor malignancies harboring activating fibroblast growth factor receptor (FGFR) gene alterations. Population information: 107 patients were divided into 3 cohorts: FGFR1–FGFR3 fusions/rearrangements; n=49 Activating FGFR1–FGFR3 non-kinase domain single nucleotide variants (SNVs); n=32 FGFR1–FGFR3 kinase domain mutations or variants of unknown significance (VUS) with potential pathogenicity; n=26 Participants on study had tumors that were grouped into the following histologies based on ≥ 5 patients: Cholangiocarcinoma, gynecologic cancers (cervical, endometrial, uterine), central nervous system (glioblastoma, low-grade pediatric glioma, astrocytoma), pancreatic cancer, breast cancer, urothelial tract/bladder cancer, non-small cell lung cancer, and other (adrenal cancer, anal cancer, cancer of unknown primary origin, colorectal cancer, gastric/gastroesophageal cancer, gallbladder cancer, giant cell bone tumor, head and neck cancer, lung neuroendocrine cancer, nasopharyngeal cancer, ovarian cancer, prostate cancer, renal cell cancer, sarcoma, solitary fibrous tumor). Among the efficacy-evaluable participants, 99 had both independent review committee (IRC) central best overall response (BOR) and tissue NGS- data; 2 additional patients had Not Evaluable (NE) as central BOR Baseline tissue targeted NGS data (F1CDx, Foundation Medicine Inc.) of genomic alterations are reported for N=101 participants Baseline plasma targeted NGS analysis (PredicineCare, Predicine Inc.) of genomic data are reported for N=83 participants; data at disease-progression are reported for N=78 participants. Principal Findings: The FIGHT-207 study provided evidence of clinical benefit of pemigatinib in multiple histologies, explored the clinical actionability of various FGFR1-FGFR3 gene alterations, and leveraged the depth of translational data from targeted NGS analysis of baseline samples and plasma samples obtained at baseline and end of treatment to provide key insights into the biology of FGFR inhibition and the clinical utility of FGFR inhibitors. The FIGHT-207 article (pending in Nat.Med. NMED-A128973B) reports evidence suggesting clinical acquired resistance to FGFR inhibition via secondary FGFR mutations as well as emerging co-mutations in other oncogenic and tumor suppressor pathways. This study also provides evidence of acquired resistance to FGFR inhibition in multiple histologies beyond cholangiocarcinoma and urothelial cancers in a systemic correlative analysis of post-progression ctDNA in a trial. Data available through dbGaP: Anonymized information for 101 participants with both IRC central BOR evaluation (including 2 patients with NE as BOR) and tissue NGS data, including tumor histology, enrollable FGFR alteration, and outcome. Genomic alterations determined by baseline tissue NGS (F1CDx, Foundation Medicine Inc.) Genomic alterations determined by plasma NGS analysis (PredicineCare, Predicine Inc.) of ctDNA analysis at baseline (n=83) and at end of treatment/ disease progression (n=78) including genomic alterations that were not assessed to be Germline SNPs.

  Study phs003590