Search Results - EGA European Genome-Phenome Archive

Amplicon_based_sequencing_of_drug_resistant_lung_cancer_cell_lines

A EGFR mutant NSCLC cell line which is sensitive to AZD9291 inhibition was mutagenised with the chemical mutagen ENU and then drug selected using a AZD9291. Single cell derived colonies were then manually picked and expanded in drug. Resistance was confirmed in a 14 day assay and DNA was collected. These then underwent targeted amplicon-based sequencing to confirm candidate resistance effectors hypothesised from currently available literature.

Study EGAS00001001675

Cylindromas_sun_protected_and_exposed

The project aims to look at mutational signatures in a rare inherited skin tumour syndrome called CYLD cutaneous syndrome. These patients develop multiple skin tumours that are seen at sun exposed and sun protected sites. We plan to carry out WGS on carefully curated tumours from such patients. We then plan to analyse this data for mutational signatures, comparing this between sun exposed and sun protected sites.

Study EGAS00001002521

Clonal architecture and genomic features of smoking versus non-smoking oncogene-driven East-Asian non-small cell lung cancer

Unlike smoking-related non-small cell lung cancers (NSCLC), oncogene-driven tumors are characterized by low mutational burdens and complex genomic landscapes. However, the clonal architecture and genomic landscape of the oncogene-driven tumors in smokers remains unknown. Here, we investigate the impact of tobacco smoking on the genomic and transcriptomic alterations in the context of oncogene-driven NSCLC.

Study EGAS00001006942

Colorectal organoids and tumour tissue

Whole genome sequencing of single cell derived organoids from normal colon tissue and colorectal cancer.

Dataset EGAD00001001447

Epi-Tax targeted sequencing

Sequencing of 350 cancer genes in BC samples from patients treated with either Epirubicin or Paclitaxel monotherapy in the neoadjuvant setting.

Dataset EGAD00001000812

GEL WGS Comparison

These samples are to be analysed with the CGP Developed cancer panel and the results will be compared with WGS data from 4 different comercial providers.

Dataset EGAD00001000872

Melanoma-Til Study RNAseq

In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

Dataset EGAD00001000325

Cell-Free DNA Fragmentation Distinguish Immunotherapy Responders from Non- Responders in Head and Neck Cancer: A Multi-Institute Prospective Study

We performed whole-genome sequencing of 185 plasma cfDNA samples from 68 patients with head and neck squamous cell carcinoma (HNSCC) enrolled in a phase II clinical trial of neoadjuvant and adjuvant pembrolizumab. Using these data, we developed the regional motif diversity score (rMDS), a novel fragmentomic biomarker that predicts immunotherapy response and outperforms established cfDNA metrics.

Study EGAS50000001286

Whole Exome PC9 and A375 (2019-04-03)

Drug resistant population of PC9(human non-small cell lung cancer) or A375 (human melanoma) cell lines were used for this study. By exome sequencing, we will analyse mutations of cells in drug tolerent state and after drug holiday. . This dataset contains all the data available for this study on 2019-04-03.

Dataset EGAD00001004891

Whole genome sequencing informs treatment decision of end-stage metastatic cutaneous angiosarcoma in a patient with Xeroderma Pigmentosum

Whole genome sequencing (WGS) detects all mutations in a cancer. “Mutational signatures” are patterns of mutations that report the DNA damage and subsequent DNA repair processes that have occurred in cancers. We present a patient with Xeroderma Pigmentosum that developed metastatic angiosarcoma, unresponsive to all lines of sarcoma therapy. Primary tumour WGS revealed a hypermutated tumour, including clonal ultraviolet light-induced mutational patterns (Signature 7) and subclonal signatures of activating mutations of DNA Polymerase-epsilon (POLE)(Signature 10). These signatures are associated with response to immune-checkpoint blockade. Immunohistochemistry confirmed high PD-L1 expression in metastatic deposits. The patient was commenced on anti-PD-L1 therapy and has responded.

Dataset EGAD00001004786

Single Cell Genome Sequence for DLP+ library A96212B

Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96212B

Dataset EGAD00001009476

Single Cell Genome Sequence for DLP+ library A98240A

Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA530 passage 3 on DLP+ library A98240A

Dataset EGAD00001009480

Single Cell Genome Sequence for DLP+ library A96141A

Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

Dataset EGAD00001009513

A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

Dataset EGAD00001015535

Discovering the Genetic Basis of Human Neuroblastoma: A Gabriella Miller Kids First Pediatric Research Program (Kids First) Project

The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Children with disseminated neuroblastoma have a very high risk of treatment failure and death despite receiving intensified chemotherapy, radiation therapy and immunotherapy. The long-term goal of our research program is to ultimately improve neuroblastoma cure rates by first comprehensively defining the genetic basis of the disease. The central hypothesis to be tested here is that neuroblastoma arises largely due to the epistatic interaction of common and rare heritable DNA variation. Here we will perform a comprehensive whole genome sequencing of 563 quartets of neuroblastoma patient germline and diagnostic tumor DNAs and germline DNAs from both parents. The case series was recently collected through a Children's Oncology Group epidemiology clinical trial and is robustly annotated with complete demographic (age, sex, race, ethnicity), clinical (e.g. age at diagnosis, stage, risk group), epidemiologic (parental dietary and exposure questionnaire) and biological (e.g. tumor MYCN status and multiple other tumor genomic measures) co-variates. Subjects were consented for genetic research and DNA is immediately available for shipment for sequencing. We propose Illumina-based whole genome sequencing in the 593 "trio" germline samples (Aim 1; due to missing parent: 487 full neuroblastoma triads, 106 child-single parent dyads = 1673 whole genome sequences) and matched diagnostic tumor DNA (Aim 2; N=366) at 30x sequencing depth (N=2039 whole genome sequences). Also in Aim 2 we will perform whole exome (100x) and RNA sequencing on the 366 tumor DNA and 228 tumor RNA samples from this cohort. Finally, we propose a pilot study of structural variation using long-range sequencing in 10 non-overlapping tumor samples chosen based on potentially relevant chromosomal alterations discovered with conventional NGS. Thus, a total of 2277 individual samples and 2655 sequences will be generated. We will use our established analytic pipeline that is currently being used to study the germline genomes of all cases sequenced through the NCI supported Therapeutically Applicable Research to Generate Effective Treatments program. We plan a three-stage analytic approach, first focusing on classic de novo and inherited Mendelian damaging alterations. We will next integrate our extensive epigenomic data from human neuroblastoma cell lines and genome-wide association study data (N=5,703 neuroblastoma cases to date) to guide a comprehensive assessment of noncoding variants that influence tumor initiation with a recently established analytic pipeline. Finally, we will utilize the tumor DNA analyses to inform relevance via somatic gain or loss of function effects at the sequence and/or copy number levels. All data generated in this project will be immediately placed into the Genomic Data Commons (GDC) and we will compute within this environment by importing our analytic pipelines into the GDC. These data will be fully integrated into the Kids First Data Resource and freely shared with all academically qualified petitioners. This comprehensive data set derived from a large and richly phenotyped series of neuroblastoma DNA quartets will be integrated with existing germline and/or tumor genomic data from over 6,000 neuroblastoma subjects (but none with matched patient-parent germline sequencing data) to provide an unparalleled opportunity to comprehensively discover the genetic basis of neuroblastoma.

Study phs001436

Structure and Diversity of Urinary Cell-Free DNA Informative of Host-Pathogen Interactions in Human Urinary Tract Infection

The risk of acquiring urinary tract infection (UTI) is very high for patients who have received kidney transplants; nearly half will develop bacteriuria and an eighth viruria via BK polyomavirus in the first three years following transplantation. Current methodology for diagnosing viral and bacterial infections, while well practiced, is often limited in scope. The advent of next generation sequencing of cell-free DNA has shown promise in its ability to capture multiple perspectives of human health from discovering the origin of cell-free DNA in plasma; such a diagnostic has not been readily applied to urinary cell-free DNA. In this study, we selected 141 urine samples from a cohort of kidney transplant patients, which were collected and stored at Weill Cornell Medical College - New York Presbyterian Hospital. Of these samples, 43 samples were determined to be culture positive (> 10,000 CFU) for one or more bacterial species, including E. coli, Enterococcus, Klebsiella, Haemophilus, and Raoultella. A separate 23 samples were confirmed for BK virus nephropathy, with presence of BK polyomavirus confirmed via qPCR. We also included 29 samples from 14 patients who did not develop UTIs in the first three months following transplantation, and 11 samples that were negative for BK virus nephropathy. For a full description of samples, please see the Supplementary Data 1 in https://pubmed.ncbi.nlm.nih.gov/29925834/. From these urine samples, we aimed to capture and sequence urinary cell-free DNA using a single-stranded library preparation. In addition, we performed whole-genome bisulfite sequencing to 170 plasma samples collected from 27 hematopoietic cell transplant patients who developed graft-versus host disease and BK polyomavirus infection. We also performed Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) on 196 cell-free DNA (cfDNA) samples (154 plasma and 42 urine) collected from five groups of subjects. For a full description of samples, please see publications in PMID: 35864089 and PMID: 35058359.

Study phs001564

National Cancer Institute (NCI) Non-Hodgkin Lymphoma Genome-wide Association Study (GWAS)

Within the framework of the International Lymphoma Epidemiology Consortium (InterLymph) Consortium and NCI-sponsored Cohort Consortium, investigators from 22 studies came together to conduct a genome-wide association study (GWAS) of non-Hodgkin lymphoma (NHL). The goal of the study was to identify common genetic variants associated with the risk of NHL. As described previously (Berndt SI et al., Nature Genetics, 2013, PMID: 23770605 ), cases and controls from 22 studies, including nine prospective cohort studies, eight population-based case-control studies, and five clinic or hospital-based case-control studies were included in this effort. Cases of NHL were ascertained from cancer registries, clinics or hospitals, or through self-report verified by medical and pathology reports. The phenotype information for all NHL cases was reviewed centrally at the InterLymph Data Coordinating Center and harmonized according to the hierarchical classification proposed by the InterLymph Pathology Working Group based on the World Health Organization (WHO) classification (2008). Controls were frequency matched to cases on age and gender by study, and the study was limited to subjects of European ancestry. Participants were genotyped using the Illumina Omni Express. The NCI Non-Hodgkin Lymphoma GWAS is utilized in the following dbGaP sub-studies. To view genotypes and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000801 NCI Non-Hodgkin Lymphoma GWAS. phs000802 NCI Non-Hodgkin Lymphoma GWAS: CLL phs000818 NCI Non-Hodgkin Lymphoma GWAS: Controls phs000889 NCI Non-Hodgkin Lymphoma GWAS: DLBCL phs000890 NCI Non-Hodgkin Lymphoma GWAS: FL phs000891 NCI Non-Hodgkin Lymphoma GWAS: MZL

Study phs000801

Genome and gene analysis of gastrointestinal cancer and elucidation of its clinicopathological significance

Cancer develops through the accumulation of genetic and epigenetic aberrations. To identify sequential molecular alterations that occur during the development of hepatocellular carcinoma (HCC), we molecularly compared 52 early and 108 overt HCC samples by genome sequencing. Gene mutations in the p53/RB1 pathway, WNT pathway, MLLs, SWI/SNF complexes, and AKT/PI3K pathway were common in HCC. In the early phase of all entities, TERT was the most frequently upregulated gene owing to diverse mechanisms. Despite frequent somatic mutations in driver genes, including CTNNB1 and TP53, early HCC was a separate molecular entity from overt HCC as each had a distinct expression profile. Notably, WNT target genes were not activated in early HCC, regardless of CTNNB1 mutation status, because ?-catenin did not translocate into the nucleus due to the E-Cadherin/?-catenin complex at the membrane. Conversely, WNT targets were definitively upregulated in overt HCC with CTNNB1 mutation associated with downregulation of CDH1 and hypomethylation of CpG islands in the target genes. Similarly, cell cycle genes downstream of the p53/RB pathway were upregulated only in overt HCC with TP53 and/or RB1 gene mutations associated with chromosomal deletion of 4q and/or 16q. Differing from the expression profile, HCC was epigenetically distinguished into four subclasses: normal-like methylation, global-hypomethylation (favorable prognosis), stem-like methylation (poor prognosis), and CpG island methylation. These methylation statuses were globally maintained through HCC progression. Taken together, additional molecular events besides driver gene mutations cooperatively contribute to transcriptional activation of downstream targets as HCC progresses, according to the methylation status of the associated genes.

Study JGAS000233

Genomic platform specific polygenic risk scores impact breast cancer risk stratification

Background: At present, there is no consensus on which genotyping platform should serve as the standard for clinical polygenic risk score (PRS) implementation. Previous studies have compared the overall performance and concordance of different genotyping and sequencing technologies; however, these analyses have generally averaged the results over the whole genome. We evaluated differences in a 313-variant breast cancer PRS (PRS313) across genomic platforms and their impact on risk stratification. Methods: We compare PRS313 derived from genotyping arrays (Global Screening Array [GSA], OncoArray-500K [OncoArray], Global Diversity Array [GDA], custom Axiom_PrecipV1 array [ThermoFisher]) and low-coverage genome sequencing (lc-WGS) in 2 cell lines and 92 individuals. Probes are designed for all variants on ThermoFisher (success rate: 259/313). Sanger sequencing profiles indels. Concordance of high-risk classification (PRS313scoresum > 0.6) across platforms is assessed using Kappa statistics. Results: In saliva samples, indel concordance with Sanger sequencing varies widely (Kappa: 0.007-1.000). PRS313-ThermoFisher is predictable from other platforms using linear models, despite systematic differences. Greater agreement is observed between arrays with high imputation overlap (e.g., GDA ~ GSA slope=0.986). Agreement in high-risk classification before mean correction is moderate (Fleiss's Kappa=0.552) and improves after mean correction (Kappa=0.650). Arrays with similar designs show higher agreement before mean correction (Kappa=0.745). Mean correction narrows high-risk proportions from 4-45% to 15-21%. Overall, 26 of 92 samples are classified as high risk on at least one platform, but only 7 are high risk across all. When restricting to identical variants across all platforms for PRS313 calculation, the corresponding number of high-risk individuals are 24 and 11. Conclusion: Our findings demonstrate that platform-specific variability can influence PRS313 estimates to potentially reclassify individuals around clinically relevant thresholds.

Study EGAS00001008439

Development and validation of multivariate predictors of primary endocrine resistance to tamoxifen and aromatase inhibitors in luminal breast cancer reveal drug-specific differences

Background: Endocrine therapy is highly effective in blocking the estrogen receptor pathway in HR+/HER2- early breast cancer (EBC). However, up to 40% of patients experience relapse during or after adjuvant endocrine therapy. Here, we investigate molecular mechanisms associated with primary resistance to endocrine therapy and develop predictive models. Results: TP53 mutations were prominently associated with primary resistance to both tamoxifen (TAM) and aromatase inhibitors (AI), with AI non-responders exhibiting resistance in up to 32% of cases. Additionally, we identified distinct DNA methylation patterns in TAM and AI non-responders, with TAM non-responders showing global DNA methylation loss, associated with KRAS signaling, apical junctions and epithelial-mesenchymal transition (EMT). Conversely, we observed methylation gain in AI non-responders affecting developmental transcription factors, hypoxia and estrogen signaling. TAM or AI resistance was associated with increased methylation-inferred proportions of immune cells and decreased proportions of endothelial cells. Based on these findings and patient age, we developed the Predictive Endocrine ResistanCe Index (PERCI). PERCI stratified NR and R cases in both treatment groups and cohorts with high accuracy (ROC AUC TAM discovery 93.9%, validation 83%; AI discovery 98.6%, validation 76.9%). A simplified PERCI efficiently predicted progression-free survival in the TCGA-BRCA sub-cohort (Kaplan-Meier log-rank p-value = 0.03 between low and high PERCI groups). Conclusions: We identified genomic and epigenomic features associated with primary resistance to TMA and AI. By combining information on genomic alterations, patient age, differential methylation and tumor microenvironment (TME) composition, we developed PERCI TAM and PERCI AI as novel predictors of primary resistance, with potential additional prognostic value. Applying PERCI in a clinical setting may allow patient-specific drug selection to overcome resistance.

Study EGAS50000001102

Histone chaperone CHAF1A promotes proliferation and tumorigenicity in gastric cancer and impacts prognosis via context-depedent regulation of gene expression

The histone chaperone CHAF1A is associated with some tumors, but its mechanisms in tumor biology remain elusive. Gastric cancer (GC) has significant heterogeneity among patients, and novel prognostic markers and therapeutic targets may improve its outcomes. The role of CHAF1A in GC is unknown. In this study, we demonstrated that CHAF1A was overexpressed in GC tissues accompanied by low expression of wild-type P53 and high expression of the proliferation marker MKI67. In vitro, CHAF1A knockdown inhibited cell proliferation, induced cell cycle arrest and promoted apoptosis, while CHAF1A overexpression had contrary effects. In vivo, CHAF1A knockdown inhibited tumorigenicity of GC cells. A microarray assay with CHAF1A inhibition and a PathScan signaling antibody array with CHAF1A overexpression showed that CHAF1A inhibited the P53 pathway, activated stress response and induced glycolytic metabolism. In 665 patients, the expression level of CHAF1A protein was an independent predictor for overall survival and disease-free survival in non-cardia GC and also had survival associations in patients with small or perineural invasion-negative tumors. Tumor mRNA analyses based on next-generation sequencing in patients indicated that CHAF1A promoted the Warburg effect by depressing oxidative phosphorylation and increasing glycolysis. Furthermore, the heterogeneous clinical significance of CHAF1A among patient subgroups was associated with its differential regulation of gene expression involved with glycolysis and cell proliferation and survival, indicating that the role of CHAF1A is depended on patient characteristics. These results reveal critical roles and clinical values for CHAF1A in GC. CHAF1A may have context-dependent effects in GC, which increases understandings for GC heterogeneity.

Study EGAS00001003064

Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

Most patients with late stage high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy but inevitably relapse and develop resistance, highlighting the need for novel therapies to improve patient outcomes. The MEK/ERK pathway is activated in a large subset of HGSOC, thus making it an attractive therapeutic target. Here, we systematically evaluated the extent of MEK/ERK pathway activation and efficacy of pathway inhibition in a large panel of well-annotated HGSOC patient-derived xenograft (PDX) models. The vast majority of models were nonresponsive to the MEK inhibitor cobimetinib (GDC-0973) despite effective pathway inhibition. Proteomic analyses of adaptive responses to GDC-0973 revealed that GDC-0973 upregulated the pro-apoptotic protein BIM, thus priming the cells for apoptosis regulated by BCL2-family proteins. Indeed, combination of both MEK inhibitor and dual BCL-2/XL inhibitor (ABT-263) significantly reduced cell number, increased cell death and displayed synergy in vitro in most models. In vivo, the GDC-0973 and ABT-263 combination was well tolerated and resulted in greater tumor growth inhibition than single agents. Detailed proteomic and correlation analyses identified two subsets of responsive models – those with high BIM at baseline that was increased with MEK inhibition and those with low basal Bim and high pERK levels. Models with low BIM and low pERK were non-responsive. Our findings demonstrate that combined MEK and BCL-2/XL inhibition has therapeutic activity in HGSOC models and provide a mechanistic rationale for clinical evaluation of this drug combination as well as the assessment of the extent to which BIM and/or pERK levels predict drug combination effectiveness in chemoresistant HGSOC.

Study EGAS00001003427

Circulating Tumor DNA in Checkpoint Inhibitor treated Lung Cancer

BackgroundImmune checkpoint inhibitors (ICI) are increasingly used to treat non-small cell lung cancer (NSCLC) and there is a critical need for novel predictive/prognostic biomarkers. We evaluated whether dynamics of circulating tumor (ctDNA) can identify NSCLC patients who benefit from single agent ICI.MethodsCirculating cell-free DNA (cfDNA) from 177 patients was analyzed prior ICI and at first treatment evaluation using a Commercial 77-gene panel. We performed de novo mutation calling and corrected for variants related clonal hematopoiesis. ctDNA changes were evaluated as predictors of tumor response estimated with PET/diagnostic CT and survival.ResultsMutations were detected in 159 of 174 (91.4%) analyzable patients. Most responders presented decreasing ctDNA levels, while non-responders had mixed molecular responses. Patients with a >50% molecular ctDNA decrease or no detectable ctDNA demonstrated improved PFS (5.9 versus 1.8 months; HR 0.49, 95%CI, 0.35-0.67, P < .001), and OS (18.9 versus 9.9 months; HR 0.41, 95%CI, 0.30-0.57, P < .001) compared to patients not achieving these endpoints. Clearance of mutations (and no detected ctDNA) had a similar effect (PFS HR 0.45, 95%CI, 0.32-0.61, P < .001; OS 0.37,95%CI, 0.27-0.52, P < .001) compared to patients having stable or additional mutations. After adjusting for clinical factors both >50% ctDNA decrease (HR 0.4, 95% CI, 0.3-0.6, P < .001) and clearance of mutations (HR 0.42, 95% CI, 0.3-0.6, P < .001) remained independent predictors for PFS and OS.ConclusionsctDNA testing reveals significant prognostic albeit not predictive information in ICI treated advanced NSCLC. This relevant information can be obtained with a commercial easy-to-implement ctDNA test that will facilitate extensive testing.

Study EGAS00001004847

Spiradenocarcinoma

• Spiradenocarcinoma is a rare cutaneous sweat gland adnexal cancer with potential for aggressive behaviour. They are classified histologically into low- and high-grade tumours, with morphologically low-grade tumours thought to behave more favourably. However, limited information is available, with only 18 published cases. • We have collected morphologically low-grade spiroadenocarcinomas (one with a lung metastasis) and high-grade spiroadenocarcinomas, as well as some spiradenomas (benign lesions), cylindromas (another type of malignant cutaneous sweat gland adnexal tumour) and hybrid spiradenoma-cylindromas. • H&E-stained sections were reviewed, follow-up was obtained, and immunohistochemistry for Ki-67, p53 and, MYB has been performed. The tumours were solitary, measuring 0.8-7?cm (median: 2.7?cm), with a predilection for the head and neck of elderly patients (median age: 72 years; range 53-92) without gender bias. Histologically, the tumours were multinodular and located in deep dermis and subcutis. A pre-existing spiradenoma was present in all cases. The malignant component was characterized by expansile growth with loss of the dual cell population, up to moderate cytological atypia and increased mitotic activity (median: 10/10 HPF; range 1-28). Additional findings included squamoid differentiation (n=9), necrosis (n=7), and ulceration (n=5). P53 expression was variable and no significant differences were noted in the benign compared with the malignant parts of the tumours. In contrast, in the malignant components the Ki-67 proliferative index was slightly increased, and MYB expression was lost. Follow-up (median: 67 months; range: 13-132) available for 16 patients (84%) revealed a local recurrence rate of 19% but no metastases or disease-related mortality. • Here we wish to exome sequence these cases to define the first genomic landscape for this malignancy.

Study EGAS00001001799

Tumor-specific expression of let-7i and miR-192 is associated with resistance to cisplatin-based chemoradiotherapy in patients with larynx and hypopharynx cancer

Background: The majority of patients with locally advanced larynx or hypopharynx squamous cell carcinoma are treated with organ preserving chemoradiotherapy (CRT). Clinical outcome following CRT varies greatly. We hypothesized tumor microRNA (miRNA) expression is predictive for outcome following CRT. Methods: Next-generation sequencing (NGS) miRNA profiling was performed on 37 formalin fixed paraffin embedded (FFPE) tumor samples. Patients with a recurrence free survival (RFS) of less than 2 years (“poor outcome”) and patients without recurrence within 2 years (“good outcome”) were compared by differential expression analysis. Tumor-specific miRNAs were selected based on normal mucosa miRNA expression data from The Cancer Genome Atlas database. A model was constructed to predict outcome using group-regularized penalized logistic ridge regression. Candidate miRNAs were validated in the initial sample set by RT-qPCR as well as in 46 additional tumor samples.Results: 1,938 known mature miRNAs were detected. Thirteen miRNAs were differentially expressed (p<0.05, FDR<0.1) according to outcome group. Initial class prediction in the NGS cohort (n=37) resulted in a model combining five miRNAs and disease stage, able to predict CRT outcome with an area under the curve (AUC) of 0.82. In the RT-qPCR cohort (n=83), 25 patients (30%) experienced early recurrence (median RFS 8 months; median follow-up 42 months). Class prediction resulted in a model combining let-7i-5p and miR-192-5p and disease stage, able to discriminate with an AUC of 0.80 patients with good versus poor clinical outcome.Conclusion: The combined miRNA expression and disease stage prediction model is superior to using either factor alone. ¬¬¬This study indicates NGS miRNA profiling using FFPE specimens is feasible, resulting in clinically relevant biomarkers.

Study EGAS00001004001

12304 results for "cancer rna-seq"

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