11768 results for "cancer rna-seq"

in 22.18 milliseconds.

• Whole genome sequencing of cfDNA

  random whole-genome shotgun sequencing of cfDNA in control samples (NPH*) and late-stage cancer samples. First letter denotes primary cancer tissue (C: Colon, B: Breast, P: Prostate)

  Dataset EGAD00001005343

• Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Dataset EGAD00001011123

• The tissue origin of highly elevated cell-free DNA in patients with and without cancer

  Forty years ago, the first measurements of cell free DNA (cfDNA) from cancer patients revealed that its total concentration was often elevated compared to healthy controls. The basis for this increase, and in particular the source of the extra cfDNA in such patients, has never been determined. To address this issue, we assessed methylation patterns of cfDNA from 57 individuals, 34 of whom had unequivocally elevated cfDNA concentrations (i.e., >15 ng/mL of plasma). We found that the excess cfDNA in cancer patients did not come from either neoplastic cells or surrounding cells from the tumor's tissue of origin. Instead, 80% of the cfDNA was derived from neutrophils, B cells or T cells, with neutrophils accounting for ~2/3. B cells contributed more than T cells despite the great excess of T cells over B cells in the blood. To see if this result was generalizable to other clinical situations in which elevated cfDNA concentrations have been described, we evaluated nine patients before and one day following surgery. After surgical resection, cfDNA concentration increased by an average of 16.1-fold, as expected. The majority of this increase (55%) was contributed by leukocytes, though damaged hepatocytes contributed a substantial minority (31% of increase). These data suggest that the elevated concentrations of cfDNA in cancer patients, as with patients after surgery, arises largely from dying leukocytes—not from the neoplastic cells or the tissue of origin of the cancer.

  Study EGAS00001005400

• Extent and Significance of Bacterial DNA Integrations in the Human Cancer Genome

  The integration of exogenous DNA into the human genome can cause somatic mutations associated with oncogenesis. For example, the insertion of HPV DNA into human chromosomes is the single most important event leading to tumorigenesis in cervical cancer. It is also now preventable with vaccines against HPV. In contrast to viral DNA integrations, the instances and repercussions of bacterial DNA integration into the somatic human genome are less clear. Yet bacterial DNA integrations (BDI) found to be associated with tumorigenesis could also be prevented using therapeutics like vaccines that limit exposure to the bacteria. Previous analysis of publicly available sequencing data from the Cancer Genome Atlas (TCGA) showed BDIs from Pseudomonas spp. rRNA into the 5'-UTR of four proto-oncogenes as well as in Ig (the immunoglobulin gene) of gastric cancer samples. The original samples from TCGA were not available to validate these findings. Therefore, a different cohort of gastric cancer patients was identified in order to establish the presence BDIs. Whole exome sequencing was completed on seven tumor samples and six adjacent gastric samples, as well as one intestinal metaplasia sample and one non-atrophic gastritis sample. Four of those samples were also investigated with transcriptomics and whole genome sequencing. Given that 15-20% of cancers worldwide are linked to infections, more work is needed to understand the role of infectious agents in oncogenesis and the mechanisms underlying that role.

  Study phs001936

• The spatio-temporal evolution of lymph node spread in early breast cancer

  Purpose: The most significant prognostic factor in early breast cancer is lymph node involvement. This stage between localised and systemic disease is key to understanding breast cancer progression, however our knowledge of the evolution of lymph node malignant invasion remains limited, as most currently available data derive from primary tumours. Experimental design: In 11 treatment-naïve node positive early breast cancer patients without clinical evidence of distant metastasis, we investigated lymph node evolution using spatial multi-region sequencing (n=78 samples) of primary and lymph node deposits and genomic profiling of matched longitudinal circulating tumour DNA (ctDNA). Results: Linear evolution from primary to lymph node was rare (1/11) whereas the majority of cases displayed either early divergence between primary and nodes (4/11), or no detectable divergence (6/11) where both primary and nodal cells belonged to a single recent expansion of a metastatic clone. Divergence of metastatic subclones was driven in part by APOBEC. Longitudinal ctDNA samples from 2 subjects taken peri-operatively reflected the two major evolutionary patterns and demonstrate that private mutations can be detected even from early metastatic nodal deposits. Moreover, node removal resulted in disappearance of private lymph node mutations in ctDNA.Conclusions: This study sheds new light on a crucial evolutionary step in the natural history of breast cancer, demonstrating early establishment of axillary lymph node metastasis in a substantial proportion of patients.

  Study EGAS00001002947

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  As 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. Paired DNA samples – isolated from the tumor tissue and from the blood of fifty patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumor DNA samples using two orthogonal platforms – exome capture by Roche-Nimblegen SeqCap Ez kit followed by sequencing on Roche-454 GS FLX, and exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 30x. In addition, we have used Illumina Omni Quad SNP-chips to generate genotype data at 1.14 million genomic markers. The average concordance between SNP-chip and sequence data is 99.8%.

  Study EGAS00001000249

• Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary with Neuroendocrine Differentiation

  PURPOSE: Cancer of unknown primary (CUP) is a group of metastatic tumors in which the standard diagnostic work-up fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large since their tumors might have actionable driver mutations that can provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomics analyses could inform on the origin of the tumor. PATIENT AND METHODS: Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a PDX mouse model and bioinformatics was used to identify an actionable mutation, predict resistance development to the targeted therapy, and to correctly diagnose the origin of the tumor. The Cancer Genome Atlas was used to benchmark the bioinformatics workflow. RESULTS: Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatics workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from The Cancer Genome Atlas. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION: Comprehensive genomics analyses could inform on the origin of tumors in patients suffering from CUP.

  Study EGAS00001003026

• Prostate cancer ancestral genomic disparity

  Prostate cancer is characterised by significant global disparity; mortality rates in SubSaharan Africa are double to quadruple those in Eurasia. Hypothesising unknown interplay between genetic and non-genetic factors, tumour genome profiling envisages contributing mutational processes. Through whole-genome sequencing of treatment-naïve prostate cancer from 183 ethnically/globally distinct patients (African versus European), we generate the largest cancer genomics resource for Sub-Saharan Africa. Identifying ~2 million somatic variants, Africans carried the greatest burden. We describe a new molecular taxonomy using all mutational types and ethno39 geographic identifiers, including Asian. Defined as Global Mutational Subtypes (GMS) A–D, although Africans presented within all subtypes, we found GMS-B to be ‘African-specific’ and GMS-D ‘African-predominant’, including Admixed and European Africans. Conversely, Europeans from Australia, Africa and Brazil predominated within ‘mutationally-quiet’ and ethnically/globally ‘universal’ GMS-A, while European Australians shared a higher mutational burden with Africans in GMS45 C. GMS predicts clinical outcomes; reconstructing cancer timelines suggests four evolutionary trajectories with different mutation rates (GMS-A, low 0.968/year versus D, highest 1.315/year). Our data suggest both common genetic factors across extant populations and regional environmental factors contributing to carcinogenesis, analogous to gene-environment interaction defined here as a different effect of an environmental surrounding in persons with different ancestries or vice versa. We anticipate GMS acting as a proxy to intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

  Study EGAS00001006425

• EPICC: Evolutionary Predictions in Colorectal Cancer

  ATAC-seq profiling bam files from colorectal carcinoma and adenoma.

  Dataset EGAD00001008140

• Raw bulk TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008118

• Single cell TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008161

• Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Dataset EGAD00001000175

• Dataset SNP tumours

  This dataset contains 30 idat files each from 15 SNP array runs on patient colitis-associated colorectal cancer tumours. All phenotypes are cancer. See Baker et al. 2018 Supplementary Table 2 for patient details of 12 tumours used in the analyses in the publication.

  Dataset EGAD00010001587

• ICGC breast cancer sequencing project SNP6 data

  Affymetrix SNP6.0 breast cancer genome sequencing data

  Dataset EGAD00010000915

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  These are 28 targeted exome sequencing fastq files (tumour and germline) generated from ovarian cancer samples which had been exposed to PARP inhibitors, for the described project.

  Dataset EGAD50000000206

• NTNU Data Access Committee for “ProstOmics: spatial and bulk multi-omics of prostate cancer” datasets archived in Federated EGA Norway

  The ProstOmics project of NTNU contains spatial and bulk multi-omics datasets of prostate cancer, and access request to these datasets are handled by this Data Access Committee on behalf of NTNU.

  Dac EGAC50000000277

• CRC Patient-derived-organoids Whole Genome Sequencing

  Whole Genome Sequencing raw paired-ends reads for 20 matched colorectal patient-derived-organoids (normal and tumor). Tumor samples were obtained from patients treated at Niguarda Cancer Center, (Milano, Italy) and Candiolo Cancer Institute (Candiolo, Turin, Italy).

  Dataset EGAD50000000617

• DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

  This is the DAC for the study "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients." of Andreas Trumpp (a.trumpp@dkfz.de), Roberto Würth (r.wuerth@dkfz.de) and Martin Sprick (Martin.Sprick@hi-stem.de).

  Dac EGAC50000000371

• Methylation Array of pre- and post-5ZA-treated head and neck cancer patients refractory to anto-PD-1 therapy

  Illumina MethylationEpic Beachip data generated from tissue samples collected from head and neck cancer patients refractory to anti-PD-1 therapy, collected before and after the 5AZA treatment

  Dataset EGAD00010002718

• DAC Study assessing the efficacy and safety of durvalumab plus olaparib plus fulvestrant in selected metastatic or locally advanced ER-positive, HER2-negative breast cancer patients.

  DAC for Study assessing the efficacy and safety of durvalumab plus olaparib plus fulvestrant in selected metastatic or locally advanced ER-positive, HER2-negative breast cancer patients.

  Dac EGAC50000000694

• Spatial transcriptomics prostate cancer

  Spatial transcriptomic characterization of human fresh frozen prostate cancer and non-malignant regions from the same patient. 100 micron thick sections were made from the biopsies, adjacent to snRNA sequencing, and subjected to 10x Genomics Visium ST analysis.

  Dataset EGAD50000001634

• Project for Development of Innovative Research on Cancer Therapeutics; Identifiying the predictive factors for response to chemoherapy in ovarian cancer

  To identify novel predictive biomarkers of response to chemotherapy for clear cell carcinoma of the ovary

  Study JGAS000076

• Elucidation of molecular mechanism of NAFLD-HCC

  We aimed to elucidate the interaction between cancer cells and immune cells in the tumor immune microenvironment of non-viral hepatocellular carcinoma.

  Study JGAS000311

• WES sequencing of metastatic colorectal cancer patient-derived xenografts with known response to irinotecan

  Whole exome sequencing of patient-derived xenograft (PDX) models from NOD/SCID mice without treatment. These PDX are obtained from tumors from patients with metastatic colorectal cancer after serial passaging in mice.

  Dataset EGAD50000002137

• SCLC ctDNA sequencing

  In this study we have sequenced the ctDNA of 28 Small Cell Lung Cancer patients in the TP53 gene, each sample has been sequenced twice.

  Study EGAS00001003984

• Landscape and significance of multiple mutations in oncogenes.

  This study is a comprehensive pan-cancer study of oncogenic multiple mutations (MMs) which includes long-read whole-genome sequencing data (n = 3).

  Study EGAS00001003763

• 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

• Feasibility of targeted capture sequencing in routinely collected FFPE cancer specimens

  Testing the feasibility of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing.

  Dataset EGAD00001000354

• Bam files for a metastatic bladder cancer patient with BAP1 variants

  This dataset consists of three bam files (two cell-free DNA and one germline DNA) from a metastatic bladder cancer patient with BAP1 variants. Bam files were generated from targeted Illumina sequencing data.

  Dataset EGAD00001005520

• WGS on patients 1-4, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of fifteen samples, tumour and whole blood, from the four initial patients.

  Dataset EGAD00001001343

• 16 Year Life History and Genomic Evolution of an ER+ HER2- Breast Cancer

  Case report of an ER+ Her2- breast cancer patient. Whole exome and transcriptome sequencing at time of diagnosis and relapse, targeted DNA sequencing of a liver met

  Dataset EGAD00001006365

• Whole exome and whole genome sequencing of pancreatic cancer

  These are seven sequencing files form whole exome and whole genome of five tissue samples collected from one pancreatic cancer patient

  Dataset EGAD00001003261

• Clinical cancer panel sequencing (UCSF500) analysis of TERT promoter duplication in GBM.

  Dataset contains paired-end clinical cancer panel sequencing (UCSF500) data from 2 samples of an initial tumor and one sample of a recurrence from one GBM patient and one sample from a second GBM patient.

  Dataset EGAD00001009286

• Cancer Cell Line Exome Sequencing

  Genomic characterisation of a large series of cancer cell lines.

  Dataset EGAD00001001039

• 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.

  Dataset EGAD00001001453

• Exome sequencing files for "Minimal functional driver gene heterogeneity among untreated metastases"

  Files from whole exome sequencing of 14 tumors from two cancer patients (endometrial and lung cancer) along with a matched normal tissue per patient.

  Dataset EGAD00001004212

• low-pass WGS and 48 cancer gene exon sequencing of COCOS growth

  55 single read fastq files of low-pass WGS sequencing used to determine copy number aberrations and 34 paired read fastq files of 48 cancer gene exon sequencing

  Dataset EGAD00001004427

• Exome and Transcriptome for pan-cancer gene-drug analysis

  Total of 584 tumor specimens and/or patient-derived cells across 14 cancer types were subjected for whole-exome/targeted-exome and/or whole-transcriptome sequencing.

  Dataset EGAD00001003441

• 2 paired WGS samples of peritumour regions of colorectal cancer

  2 paired WGS samples of peritumour regions of colorectal cancer (2 patients). The library was prepared using the Illumina TruSeq Nano FFPE kit and the sequencing was done on NovaSeq6000.

  Dataset EGAD00001009714

• RNAseq of breast cancer bone metastases PDX treated to IACS

  Fastq files from RNAseq of breast cancer bone metastases PDX of tumor HBC-124 treated by IACS-010759 (4 samples) or not (4 samples).

  Dataset EGAD00001009857

• Feasibility of targeted capture sequencing in FFPE cancer specimens 2

  Testing the feasibility of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing.

  Dataset EGAD00001001448

• DNA WGS Long Read Sequence (PromethION) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  DNA WGS Long Read Sequence (PromethION) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  Dataset EGAD00001015400

• Transdisciplinary Research Into Cancer of the Lung (TRICL) - Exome Plus Targeted Sequencing

  The study was conducted under the auspices of the Transdisciplinary Research In Cancer of the Lung (TRICL) Research Team, which is a part of the Genetic Associations and MEchanisms in ONcology (GAME-ON) consortium, and associated with the International Lung Cancer Consortium (ILCCO). Ethics All participants provided written informed consent. All studies were reviewed and approved by institutional ethics review committees at the involved institutions. Sequencing data are derived from four sub-studies. The sub-studies that contributed include Harvard, Liverpool, Toronto, and IARC. The IARC and Toronto studies are described above. A description of the Harvard and Liverpool studies is provided below. Liverpool Lung Project: The Liverpool Lung Project (LLP)1 is a case control and cohort study, which has over 11,500 individuals, with detailed epidemiological, clinical and outcome data with associated specimens (i.e. tumour tissue, blood, plasma, sputum, bronchial lavage, EBUS and oral brushings). The participants have completed a detailed lifestyle questionnaire and updated data on clinical outcome and hospital events are collected through the Office of National Statistics, Cancer Registry and from Health Episode Statistics. The project is registered on the UK National Institute for Health Research (NIHR) lung cancer portfolio and has all the required ethical approvals and sponsorship arrangements in place. The LLP has detailed standard operating procedures (SOP) for all aspects of the recruitment, data, specimen collection as well as the data storage. The LLP Cohort study has 8,224 participants with blood and 7,761 with plasma samples. The LLP case-control samples have been incorporated into in a large number of international GWAS and molecular studies 2,3, methylation 4-7, microRNA 8and next generation studies 9-11, resulting in high ranking publications, as well as forming the basis for the LLP risk prediction model 12-14 which has been utilised in the UK lung cancer screening trial (UKLS) 15-17 Patient and control DNAs were derived from EDTA-venous blood samples. Harvard Samples. David Christiani at the Harvard University School of Public Health has been directing research studies to investigate etiological factors influencing lung cancer development since 1983 and has amassed a collection of 2000 controls and 5055 lung cancer cases. He has been actively collecting and storing snap frozen tumor samples since 1992. Around 1500 tumor samples have been collected and the average wet tumor yield is about 30 grams of tumor, of which 631 cases have completely annotated clinical and survival information. Pathology confirmation is provided by two pathologists. At the time of surgery, a minimum of 30 grams of wet lung tumor tissue and 30 grams of non-involved tissue from the same lobe is sectioned, flash frozen and sent to Dr. Christiani's lab for logging and storage. A blood sample for DNA and serum is collected. A structured interview by trained research staff is conducted on each case, and clinical outcomes and treatments is extracted and entered into the molecular epidemiology data base at Harvard. Fresh frozen samples have been collected from 1451 lung cancer and are available for study. Samples from this collaborative study have played key roles in major studies, including the initial finding describing EGFR mutations in lung cancer 22. Participants in this study are patients, > 18 years of age, with newly diagnosed histologically confirmed lung cancer. Samples that are included in the analysis have the following histologies: Adenocarcinoma: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3 8560/3; LCC: 8012/3, 8031/3; squamous carcinoma: 8070/3, 8071/3, 8072/3, 8074/3; and other NSCLC: 8010/3, 8020/3, 8021/3, 8032/3, 8230/3. The Toronto Study: The Toronto study was conducted in the Great Toronto Area between 1997 and 2014. Cases were recruited at the hospitals in the network of University of Toronto and Lunenfeld- Tanenbaum Research Institute. At the time of recruitment in the clinical setting, provisional diagnoses of lung carcinoma were first assigned based on clinical criteria. Diagnoses for all cases included were histologically confirmed by the reference pathologist who is a specialist in pulmonary pathology, based on review of pathology reports from surgery, biopsy or cytology samples in 100% of cases. Diagnostic classification was done initially according to ICD-9, ICD-10, and ICD for oncology-2, and subsequently converted to ICD-O-3. Tumors were grouped into the major categories included in this analysis according to primary cancer type based on the ICD-3 definitions. Controls were randomly selected from individual visiting family medicine clinics and Ministry of Finance Municipal Tax Tapes. All subjects were interviewed using a standard questionnaire and information on lifestyle risk factors, occupational history, medical and family history was collected. Blood samples were collected from more than 85% of the subjects. IARC: The IARC data are derived from case-control studies conducted in Russia and include samples that have available tissue samples. Patient and control DNAs were derived from EDTA-venous blood samples. The lung cancer patients were classified according to ICD-O-3; SQ: 8070/3, 8071/3, 8072/3, 8074/3; AD: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3, 8560/3, 8251/3, 8490/3, 8570/3, 8574/3; with tumous with overlapping histologies classified as mixed. The Lung Cancer Transdisciplinary Research Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000876 Lung Cancer Transdisciplinary Research Cohort. phs000877 Meta Analysis phs000878 CIDR Lung Cancer phs001681 Affy Axiom Array

  Study phs000876

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination. Biological Materials were provided by the Ontario Tumour Bank, which is funded by the Ontario Institute for Cancer Research Reference for citation: Ling Liu, Jinghua Feng, Julian Polimeni, Manli Zhang, Hai Nguyen, Urmi Das, Xu Zhang, Harminder Singh, Xiao-Jian Yao, Etienne Leygue, Sam K.P. Kung, and Xie J. Characterization of cell free plasma methyl-DNA from xenografted tumours to guide the selection of diagnostic markers for early-stage cancers. Frontiers in Oncology, 2021 Feb. 5. DOI: 10.3389/fonc.2021.615821.

  Study EGAS00001006175

• RNAseq of preneoplasia lung adenocarcinoma

  RNA sequencing of 168 pulmonary samples including lung preneoplasia atypical adenomatous hyperplasia (AAH, N=38), adenocarcinoma in situ (AIS, N=22), minimally invasive adenocarcinoma (MIA, N=19) and invasive lung adenocarcinoma (ADC, N=38) and adjacent lung tissues (Normal, N=62).

  Dataset EGAD50000000395

• Single-cell RNA sequencing data of patients with T follicular helper cell lymphomas

  This dataset contains single-cell count data generated by the Cellranger pipeline (v3.1.0, 10X Genomics) from 9 LN and 16 PB samples of 14 patients with T follicular helper cell lymphomas (TFHLs) as well as 7 homeostatic LN (HLN) samples.

  Dataset EGAD50000000402

• Pregnancy-associated melanoma

  The aim of this project is to assess differences in intratumoral immune composition in pregnant melanoma patients versus non pregnant melanoma controls. Samples (N=25) were obtained from a local patient database. From archived FFPE we isolated RNA and performed NGS and bio-informatica data-analysis.

  Dataset EGAD50000000706

• RNAseq of samples from CLL patients treated with ibrutinib in vivo

  The dataset contains RNA sequencing data from 22 paired samples of 11 patients before and during ibrutinib therapy (median time on therapy 2 weeks; range 1-12 weeks). The sequencing was performed in two batches.

  Dataset EGAD50000000879

• Altered Blood and Keratinocyte microRNA/transfer RNA Fragment Profiles Related to Fibromyalgia Syndrome and its Severity

  We show dysregulated microRNA and tRNA fragment profiles related to FMS pathopyhsiology and opening new perspectives for FMS diagnostics and symptom monitoring. This dataset includes all sequencing raw files from whole blood (tempus tube) and keratinocyte sequencing.

  Dataset EGAD50000000900

• Melanoma transcriptomic data from patients undergoing immunotherapy

  This dataset contains raw RNA sequencing data from melanoma patient tumor samples collected before and during immunotherapy. The data support investigation of treatment-related changes in tumor cell populations. Samples were analyzed as part of a study exploring cellular responses to immune-based therapies.

  Dataset EGAD50000001569