9295 results for "cancer rna-seq"

in 51.55 milliseconds.

• A Genome-Wide Association Study of CALGB 90401: Randomized, Double-Blind, Placebo-Controlled Phase III Trial Comparing Docetaxel and Prednisone with or without Bevacizumab in Men with Metastatic Castration-Resistant Prostate Cancer

  The Cancer and Leukemia Group B (CALGB) 90401 trial compared docetaxel and prednisone with or without bevacizumab in men with metastatic castration-resistant prostate cancer. A genome-wide association study using clinical outcomes and toxicities was conducted on the basis of data from CALGB patients who provided consent for pharmacogenomic studies and usable DNA

  Study phs001002

• WGS

  Whole-genome sequencing of pancreatic cancer organoids and matched germline controls.

  Study EGAS00001007211

• Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

  Study EGAS00001007291

• National Cancer Institute (NCI) Prostate Cancer Genome-Wide Association Study for Uncommon Susceptibility Loci (PEGASUS)

  This genome-wide association study was funded by the National Cancer Institute (NCI) to identify uncommon susceptibility loci for prostate cancer. A total of 4,600 prostate cancer cases and 2,840 controls of European ancestry from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were genotyped using the Illumina HumanOmni2.5 and passed rigorous quality control filters. Additional genotype data (available in dbGap under other accession numbers) from 101 independent controls of European ancestry scanned with the HumanOmni2.5 were also included, resulting in a total of 4,600 cases and 2,941 controls for the published analysis. SNPs from the most promising regions, as determined by rank p-value, under multiple different models as well as select candidate genes were taken forward for replication using a custom Iselect chip in 6,575 cases and 6,392 controls of European ancestry. Results from the primary scan after imputation were then meta-analyzed with the Iselect results as well as results from previous GWAS. In a combined meta-analysis of the primary scan together with the custom Iselect replication and a previous GWAS, thirteen loci reached genome-wide significance (P < 5 x 10-8) for prostate cancer overall; however, each of them confirmed a previously reported locus. Although they did not reach genome-wide significance, we found evidence for two new suggestive loci at chromosome 16q22.2 (PKD1L3, rs12597458, P = 9.67 x 10-8) and 6p22.3 (CDKAL1, rs12198220, P = 2.13 x 10-7). In a combined case-only analysis of 12,518 prostate cancer cases, we identified two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49x10-9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18x10-8). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85x10-5) with no association for non-aggressive prostate cancer compared to controls (P=0.57). Only the cases and controls genotyped on the HumanOmni2.5 specifically for this study are included under this accession number. Controls (n=101) genotyped with the HumanOmni2.5 for another study are posted under a different accession number. Please note that the majority of prostate cancer cases and controls genotyped in CGEMS (and posted under a different accession number) are included in this study.

  Study phs000882

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• Genomics_of_acral_lentiginous_melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003740

• Genomic analysis of HPV positive versus HPV negative esophageal adenocarcinoma

  High-risk human papillomavirus (hr-HPV) has been implicated in a subset of patients with esophageal adenocarcinoma (EAC). We therefore hypothesized that HPV associated EAC may have distinct genomic aberrations compared with viral negative esophageal cancer as shown in Head and Neck cancer and cervical cancer. Whole exome sequencing (WES) was performed to explore the mutational landscape and potential molecular signature of HPV positive versus HPV negative EAC, which includes four hr-HPV-positive and 8 HPV-negative treatment naive fresh-frozen EAC tissue specimens and matched normal tissues.

  Study EGAS00001001340

• Targeted sequencing of breast cancers with germline BRCA1/2 mutations

  Breast cancer is the most prevalent cancer in women, where a germline predisposition plays a substantial role. However, the effects of pathogenic germline variants on accompanying breast cancers have not been fully characterized in terms of somatic alterations. We obtained tumor samples from 30 patients with pathogenic germline variants in BRCA2 (n = 25) and BRCA1 (n = 5), as well as an additional 30 patients without pathogenic germline mutations, in which somatic mutations in common breast cancer drivers and CNAs were analyzed using targeted panel sequencing.

  Study EGAS00001004182

• Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

  While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

  Study EGAS00001002499

• Breast cancer women lack normal lifelong immune response after full-term pregnancies

  Immunological tolerance during pregnancy is necessary for women’s bodies to accept the semi-allogenic fetus. Interestingly, “immune evasion”, which consists of some similar immunological changes, was recently proposed as a hallmark of cancer. Looking at these results, it seems paradoxical that increasing number of full-term pregnancies (FTP) reduces the risk of breast cancer in women. Our aim was to use a systems epidemiology approach to investigate this paradox by modelling breast cancer incidence as a function of parity in the Norwegian Women and Cancer (NOWAC) cohort, then testing the mathematical model using gene expression from blood in a subcohort of these women: the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis for immunological gene sets. A linear trend nicely fitted the dataset showing an 8% decrease in risk for each FTP, independent of stratification on other risk factors and lasting for decades after a woman’s last FTP. However, when we looked at gene expression we found that hundreds of genes showed linear trends in cancer-free controls, but this was not the case in /any/ of the samples from breast cancer cases. In the gene set enrichment analysis, samples consisted of human blood or cord blood and mouse bone marrow or spleen. We found more adaptive gene sets than expected in humans and more innate gene sets than expected in mice. None of the gene sets provided information about the long-term effects of immunological tolerance during pregnancy, but the lack of relevant reductionist experiments hampers our interpretation. We suggest that, after resolution at birth, the immunological tolerance induced by pregnancy augments immune response to cancer development.

  Study EGAS00001002616

• Genome and transcriptome sequence data from a primary unknown cancer patient

  Genome and transcriptome sequence data from a primary unknown cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001308

• Genome and transcriptome sequence data from a non small cell lung cancer patient

  Genome and transcriptome sequence data from a non small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001963

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001964

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001969

• Genome and transcriptome sequence data from a GI primary (prev breast cancer) patient

  Genome and transcriptome sequence data from a GI primary (prev breast cancer) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002979

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002990

• Genome and transcriptome sequence data from a metastatic medullary thyroid cancer patient

  Genome and transcriptome sequence data from a metastatic medullary thyroid cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003006

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003014

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003041

• Genome and transcriptome sequence data from a low grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003020

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003022

• Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003054

• Genome and transcriptome sequence data from a presumed metastatic lung cancer patient

  Genome and transcriptome sequence data from a presumed metastatic lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003079

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003639

• Genome and transcriptome sequence data from a metastatic serous ovarian cancer patient

  Genome and transcriptome sequence data from a metastatic serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003609

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003617

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003624

• Genome and transcriptome sequence data from a metastatic clear cell ovarian cancer patient

  Genome and transcriptome sequence data from a metastatic clear cell ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003672

• Genome and transcriptome sequence data from a low grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003680

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003682

• Genome and transcriptome sequence data from a bilateral breast lobular cancer patient

  Genome and transcriptome sequence data from a bilateral breast lobular cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003711

• Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003713

• Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low-grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004697

• Genome and transcriptome sequence data from a metastatic transverse colon cancer patient

  Genome and transcriptome sequence data from a metastatic transverse colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004691

• Genome and transcriptome sequence data from a high grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a high grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004638

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004646

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004672

• Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002577

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002606

• Genome and transcriptome sequence data from a pancreatic cancer (likely PNET) patient

  Genome and transcriptome sequence data from a pancreatic cancer (likely PNET) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002607

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002611

• Genome and transcriptome sequence data from a locally advanced breast cancer patient

  Genome and transcriptome sequence data from a locally advanced breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004897

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004923

• Genome and transcriptome sequence data from a metastatic serous ovarian cancer patient

  Genome and transcriptome sequence data from a metastatic serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004909

• The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer

  The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer includes 538 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001005339

• Genome and transcriptome sequence data from a metastatic unknown primary cancer patient

  Genome and transcriptome sequence data from a metastatic unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005845

• Genome and transcriptome sequence data from a large intestine-colon cancer patient

  Genome and transcriptome sequence data from a large intestine-colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005885

• WES_localized non-small cell lung cancer (540 samples)_MDACC

  Whole exome sequencing of tumors and paired adjacent uninvolved tissues from 222 early stage NSCLC patients, in order to identify genomic drivers present in early-stage non-small cell lung cancer and determine the overall tumor mutational burden in early-stage non-small cell lung cancer.

  Dataset EGAD00001005956

• ChIP_sequencing_in_Cancer_Cell_Lines

  The project is to evaluate the genomic binding sites of the histone demethylase JARID1C. This gene was recently identified in CGP as a novel recessive cancer gene in human renal cell carcinoma.

  Study EGAS00001000203

• BIG_MS_Pilot

  Testing logistics and infrastructure of molecular screening program. Core biopsies taken from invasive recurrent or metastatic breast cancer to evaluate and identify molecular traits rendering them suitable for clinical trials

  Study EGAS00001000616