7201 results for "canc*"

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• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  Papillary thyroid carcinoma (PTC) is the most common malignancy amongst adolescent and young adult women. Clinical and genomic features of PTC in children differ from those in adults. Historically, a substantial proportion (~50%) of pediatric PTC (PPTC) lack any of the common driver mutations typical of adult PTC. Thus, molecular diagnostics developed for adults may not be valid in children. We applied novel bioinformatic pipelines to RNASeq analysis of pediatric thyroid tumors to identify known and novel fusion oncogenes as drivers of tumorigenesis and to define gene expression patterns among tumors. Analysis of 38 samples resulted in identification of 16 previously reported oncogenic fusions and three novel candidate fusions. In conducting these analyses, we reduced the proportion of cancers with unknown drivers from approximately 50% to 6%. Gene expression analysis identified three distinct categories of tumors. These studies represent the first unbiased genomic approach to childhood PTC. Novel bioinformatic pipeline. GEC Identified 3 distinct classes. DICER1, PTEN segregated with benign tumors. >90% of PPTC carry identifiable ongognic driver variants, however, the landscape differs from that in adults and existing tools for tumor genotyping in adults may not be applicable to pediatric tumors. BACKGROUND: Papillary thyroid carcinoma demonstrates clinically distinct behaviour in pediatric patients when compared to adults, with increased regional and distal metastases, more frequent recurrence, yet overall highly favourable prognosis. Recent tumor genotyping has demonstrated that in pediatric tumors, ***-*** do not carry the most common genomic variants found in adult PTC, leaving a substantial proportion of driver-unknown or “dark matter” tumors. METHODS: We established a cohort of 52 pediatric PTC and performed quantitative-PCR genotyping followed in a subset by whole exome and whole transcriptome (RNASeq) sequencing using a novel, robust bioinformatic pipeline to identify oncogenic fusion transcripts. Gene expression analysis was used to derive distinct clusters. RESULTS: In 52 pediatric PTC, genotyping identified BRAFV600E(21%), NRASQ61R(2%), RET/PTC1 (21%), RET/PTC3 (17%) or PAX8-PPAR in 33 (63%) of tumors. Among the remaining 19 tumors, oncogenic variants were identified in /19 (%). The variants included SNVs in DICER1, ETV6-NTRK3, PTEN and 9 additional oncogenic fusions including two previously-undescribed fusion transcripts, *** and ***. CONCLUSIONS: The genomic landscape of PTC differs between children and adults. In children, there is a substantial fraction of tumors that are unexplained by variants typical of adult PTC. This discrepancy is explained largely by uncommon oncogenic fusions which can be identified by whole-transcriptome analysis.

  Study EGAS00001005182

• Patient-derived organoids as a novel tool to study cervical cancer

  Cervical cancer is the most prevalent gynecological malignancy worldwide, often caused by infection with a high-risk human papillomavirus. Currently, there are only limited number of human-derived culture systems available that enable to study the viral infection for short-term. Here, we report on establishment of long-term human-derived organoid cultures from both healthy ecto- and endocervical epithelia that closely recapitulate the tissues of origin by maintaining the authentic histological and tissue-specific gene expression profiles. Additionally, using material from patients’ Pap-brush material, a successful panel of long-term patient-derived cancer organoids was established that maintain the causative viral infection in vitro and show differential response to common chemotherapy regimens. This study provides a promising platform for cervical cancer research and studying direct virus-host interactions.

  Study EGAS00001004439

• Methylome sequencing of cell-free DNA and RRBS of solid tissue

  Early cancer detection by cell-free DNA (cfDNA) faces multiple challenges: low fraction of tumor cfDNA, molecular heterogeneity of cancer, and sample sizes not sufficient to reflect diverse patient population. We develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of cfDNA methylome (with >12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our system to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, thereby permitting the classification models to learn new features as training cohorts grow, and expanding their scope to other cancer types.

  Study EGAS00001006020

• Single-cell analysis for metastatic gastric adenocarcinoma

  Intra-tumoral heterogeneity (ITH) is the fundamental property of cancer, however, the origins of ITH remain poorly understood. Here we performed single-cell RNA sequencing of peritoneal carcinomatosis (PC) from patients with advanced gastric adenocarcinoma (GAC), constructed a transcriptome map of 45,048 PC cells, profiled the transcriptome states of diverse tumor cell lineages and types, incisively explored ITH of PC tumor cells, and identified significant correlates with patient survival.

  Study EGAS00001004443

• Somatic_mutation_profiling_of_intestinal_crypts_from_IBD_Full_STDY

  Following on from our pilot study we will investigate further the role that somatic mutations in intestinal stem cells play in IBD. We will use laser capture microdissection to ascertain epithelial cells from an individual crypts/vilus. We will extract DNA from these and use a new low-input material library prep methods to make accurate libraries for sequencing. We will perform 15X whole-genome sequencing of crypts biopsied from patients. Biopsies have been taken from inflammed and noninflammed patches to compare mutation rates and mutational signatures. We will also test if crypts from inflammed patches of a single patient are clonal (either within a given inflammed patch or across inflammed patches). We will quantify the rate of cancer driver mutations in inflammed and non-inflammed crypts. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003249

• Clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint.

  Study EGAS00001004445

• Genomic characterization of co-existing biliary tract intraepithelial neoplasia and carcinoma lesions reveals distinct evolutionary paths of gallbladder cancer

  Gallbladder carcinoma is the most common cancer of the biliary tract with dismal survival largely due to delayed diagnosis. Biliary tract intraepithelial neoplasia (BilIN) is the common benign tumor that is suspected to be precancerous lesions. However, the genetic and evolutionary relationships between BilIN and carcinoma remain unclear. Here we performed whole-exome sequencing of coexisting low-grade BilIN (adenoma), high-grade BilIN, and carcinoma lesions, and normal tissues from the same patients.

  Study EGAS00001005402

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Study EGAS00001005405

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations

  Survival of children with relapsed cancer remains unacceptably low. Cancer genomic profiling may identify new therapeutic options, enhance diagnostic accuracy, and improve understanding of tumors’ origins and continued evolution. We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. We analyzed tumor mutational signatures and burden to interrogate the relevance of germline variants in DNA repair genes and the impact of therapeutic exposures on tumor evolution. We also evaluated the frequency of changes to tumor drivers and therapeutic targets at relapse in those with serial samples. Integrative analysis yielded clinically actionable variants in a majority of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants were of unanticipated timing and type, with many of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. We show that mutation burden, which may in part be driven by prior therapeutic exposures, was significantly elevated in a minority of patients. Over one-third of patients with sequential samples analyzed showed a change in therapeutically-targetable drivers. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006034

• scRNA-seq of HGSC tumor and ascites

  Immune regulatory metabolites are key features of the tumor microenvironment (TME), yet with a few notable exceptions, their identities remain largely unknown. We uncovered the immune regulatory metabolic states and metabolomes of sorted tumor and stromal, CD4+, and CD8+ cells from the tumor and ascites of patients with high-grade serous ovarian cancer (HGSC) using high-dimensional flow cytometry and metabolomics supplemented with single cell RNA sequencing. Flow cytometry revealed that tumor cells show a consistently greater uptake of glucose than T cells, but similar mitochondrial activity. Cells within the ascites and tumor had pervasive metabolite differences, with a striking enrichment in 1-methylnicotinamide (MNA) in T cells infiltrating the tumor compared to ascites. Despite the elevated levels of MNA in T cells, the expression of nicotinamide N-methyltransferase, the gene encoding the enzyme that catalyses the transfer of a methyl group from S-adenosylmethionine to nicotinamide, was restricted to fibroblasts and tumor cells. Treatment of T cells with MNA resulted in an increase in T cell-mediated secretion of the tumor promoting cytokine tumor necrosis factor alpha. Thus, the TME-derived metabolite MNA contributes to an alternative and non-cell autonomous mechanism of immune modulation of T cells in HGSC. Collectively, uncovering the tumor-T cell metabolome may reveal metabolic vulnerabilities that can be exploited using T cell-based immunotherapies to treat human cancer.

  Study EGAS00001004829

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Study EGAS00001004446

• Chromothripsis followed by circular recombination drives oncogene amplification in human cancer

  The mechanisms behind the evolution of complex genomic amplifications in cancer have remained largely unclear. We here identified a type of amplification, termed as “seismic amplification”, that is characterized by multiple rearrangements and discontinuous copy number levels. Seismic amplifications occurred in 9.9% (274/2,756) of cases across 38 cancer types and were associated with massively increased copy numbers and elevated oncogene expression. Reconstruction of the development of seismic amplification revealed a stepwise evolution, starting with a chromothripsis event, followed by formation of circular extrachromosomal DNA that subsequently underwent repetitive rounds of circular recombination. The resulting amplicons persisted as extrachromosomal DNA circles or had reintegrated into the genome in overt tumors. Together, our data indicate that the sequential occurrence of chromothripsis and circular recombination drives oncogene amplification and over-expression in a substantial fraction of human malignancies.

  Study EGAS00001005424

• Genotyping by OncoArray and Global Screening Array for colorectal cancer risk prediction

  The study was conducted to build a Polygenic risk scores (PRS) based on a reported set of 140 single nucleotide polymorphisms that were identified to be associated with a higher risk of colorectal cancer (CRC). Genotyping by OncoArray and Global Screening Array was performed using DNA extracted from blood samples collected at baseline of 187 participants who develop CRC and 176 randomly selected controls without diagnosis of CRC identified within 14 years of follow-up.

  Study EGAS00001005411

• Bulk RNA sequencing of Singapore colorectal cancer patients (SG-BULK)

  The study was approved by the institutional review board of Singhealth (2018-2795). Ten 5-µm tissue sections were cut using standard microtomy techniques. Each collected cell population was then extracted using the allprep kit. Extracted material was then quantified using a Qubit fluorometer.

  Study EGAS00001005978

• NSCCG CRC GWAS data

  Genotype data from 7,281 individuals with colorectal cancer. Genotyped on the Illumina OncoArray. Data has not been quality controlled. Data provided in plink format

  Study EGAS00001005412

• Custom long non-coding RNA capture enhances detection sensitivity in different human sample types.

  Long non-coding RNAs (lncRNAs) are a heterogeneous group of transcripts that lack protein coding potential and display regulatory functions in various cellular processes. As a result of their cell- and cancer-specific expression patterns, lncRNAs have emerged as potential diagnostic and therapeutic targets. The accurate characterization of lncRNAs in bulk transcriptome data remains challenging due to their low abundance compared to protein coding genes. To tackle this issue, we describe a unique short-read custom lncRNA capture sequencing approach that relies on a comprehensive set of 565,878 capture probes for 49,372 human lncRNA genes. This custom lncRNA capture approach was evaluated on various sample types ranging from artificial high-quality RNA mixtures to more challenging formalin-fixed paraffin-embedded tissue and biofluid material. The custom enrichment approach allows the detection of a more diverse repertoire of lncRNAs, with better reproducibility and higher coverage compared to classic total RNA-sequencing.

  Study EGAS00001005418

• Evolutionary analysis of pancreatic neoplastic cysts through whole-exome and targeted sequencing

  Intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs) are non-invasive neoplasms that are often observed in association with invasive pancreatic cancers, but their origins and evolutionary relationships are poorly understood. In this study, we analyzed 148 samples from IPMNs, MCNs, and small associated invasive carcinomas from 18 patients using whole exome or targeted sequencing.

  Study EGAS00001004473

• Mutational_burden_in_human_hair_follicles

  We would like to dissect human hair follicles and assess the mutations found in diffferent parts of the follicle eg bulge, root etc. We can also compare this with mutations found in the surrounding epidermis of the same patients (this is done under a different study). This may provide insights into the origin of PTCH1 mutants frequently seen in basal cell carcinoma but so far not located in our whole epidermis work as well as defining the clonality of the hair follicle

  Study EGAS00001004462

• Single cell RNA sequencing of normal endometrial derived organoids uncovers novel cell type markers for prognostication

  Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumors and found both secretory-like and ciliated-like tumor cells.

  Study EGAS00001004466

• ANGIOPREDICT - an FP7-funded project enabling personalised medicine for patients with metastatic colorectal cancer.

  In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers will work together with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to Avastin® combination therapy. Diagnostic tests using these biomarkers will also be developed to provide clinicians with the means to predict patient treatment responses in the future.

  Study EGAS00001005423

• Whole Genome sequencing of colorectal cancer patients (SG-BULK-3)

  The study was approved by the institutional review board of Singhealth (2018-2795). Ten 5-µm tissue sections were cut using standard microtomy techniques. Each collected cell population was then extracted using the allprep kit. Extracted material was then quantified using a Qubit fluorometer.

  Study EGAS00001006056

• A higher ctDNA fraction decreases survival in regorafenib-treated metastatic colorectal cancer patients

  The predictive effect of circulating tumor DNA (ctDNA) in colorectal cancer (CRC) treatment is still highly discussed. The primary objective of this study was to investigate a possible prognostic/predictive value of ctDNA under regorafenib treatment. This prospective multicenter translational biomarker phase II pilot study enrolled 30 metastatic CRC patients (67% men, 33% women) treated with regorafenib. ctDNA was assessed in plasma before treatment start and at defined time points during administration. Measurement of tumor fraction as well as mutation and copy number analysis of CRC driver genes were performed by next generation sequencing approaches. Multivariate analyses for survival and treatment efficacy were adjusted to age, gender and ECOG. Disease control rate was 30%. Median tumor fraction at baseline was 18.5% (0-49.9). Mutations in CRC driver genes or genes involved in angiogenesis were identified in 25 patients (83.3%). KRAS mutations were detected in 13 out of 14 KRAS positive tumors, in three patients without KRAS mutation in the respective tumor acquired mutations as a consequence of prior anti-EGFR treatment were detected. In a subset of patients, novel occurring mutations or focal amplifications were detected. A tumor fraction of 5% and higher at baseline was significantly associated with a decreased OS (p=0.022; HHR 3.110 (95%CI: 1.2-8.2). ctDNA is detectable in a high proportion of mCRC patients. Higher ctDNA levels are associated with survival among regorafenib treatment. Moreover, our data highlight the benefit of a combined evaluation of mutations and somatic copy number alterations (SCNA) in advanced cancer patients.

  Study EGAS00001004491

• Genome analysis of early onset sporadic rectal cancer

  Study EGAS00001005970

• Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized controlled trial AGITG-MAX

  Patients and methods: We analyzed tumor samples of 256 patients enrolled in the AGITG-MAX 3-arm randomized controlled trial (RCT) who were randomly assigned to receive either capecitabine, or capecitabine and bevacizumab with- or without mitomycin. Chromosome 18q11.2-q12.1 copy number status was measured and correlated with PFS according to a predefined analysis plan with marker-treatment interaction as the primary end-point.Results: Chromosome 18q11.2-q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the non-randomized study, significant PFS benefit of bevacizumab was observed in chromosome 18q11.2-q12.1 loss patients (P=0.009), and not in 18q no-loss patients (P=0.67). Although significance for marker-treatment interaction was not reached (Pinteraction = 0.28), hazard ratio and 95% confidence interval (HRinteraction 0.72, CI 0.39 - 1.32) show striking overlap with the non-randomized study cohorts (HRinteraction 0.41, CI 0.32 - 0.8) supported by a non-significant Cochrane chi-squared (P=0.11) for heterogeneity. Conclusions: PFS characteristics for marker positive- and negative patients randomized for treatment with- or without bevacizumab were consistent with those of the non-randomized discovery study, though the number of AGITG-MAX samples fell short to reach significance for marker-treatment interaction. Post-hoc analysis of the AGITG-MAX RCT provides supportive evidence for chromosome 18q11.2-q12.1 as a clinically relevant predictive marker for mCRC patients.

  Study EGAS00001005453

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_Batch05

  Transcriptome Sequencing of Gingivo-buccal Cancer: ICGC-India ProjectAs a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Transcriptome sequencing of paired RNA samples – isolated from the tumor and adjacent normal tissues of 28 patients – have been performed. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from adjacent normal and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Sequencing is being performed at the National Institute of Biomedical Genomics, Kalyani.

  Study EGAS00001003285