7077 results for "canc*"

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• Pharmacokinetics and Pharmacogenomics of Ribociclib in Race-Based Cohorts (LEANORA)

  Underrepresented populations' participation in clinical trials remains limited, and the potential impact of genomic variants on drug metabolism remains elusive. This study aimed to assess the pharmacokinetics (PK) and pharmacogenomics (PGx) of ribociclib in self-identified Black women with hormone receptor positive (HR+)/human epidermal growth factor receptor 2-negative (HER2) advanced breast cancer. LEANORA (NCT04657679) was a prospective, observational, multicenter cohort study involving 14 Black women. PK and PGx were evaluated using tandem mass spectrometry and PharmacoScan microarray. CYP3A5*3, CYP3A5*6, and CYP3A5*7 variants were genotyped and CYP3A5 phenotypes were constructed from these data. We observed 7 poor metabolizers (PM), 6 intermediate metabolizers (IM), and one normal metabolizer (NM). The area under the curve of plasma concentration versus time curve (AUC) of ribociclib did not differ between PMs (39,230 hr*ng/mL) and IM/NMs (43,546 hr*ng/mL; P=0.38). The incidence of adverse events (AEs) was also similar. We found no association between CYP3A5 genotype and ribociclib exposure. Continued efforts are needed to include diverse populations in clinical trials to ensure equitable treatment outcomes.

  Study phs003770

• Integrated Somatic and Germline Molecular Properties Dictating Biological and Clinical Phenotypes in Cancer

  We performed single-nuclei matched RNA- and ATAC-sequencing of frozen biopsies from normal adjacent tissue, primary and metastatic esophageal adenocarcinoma specimens. The data was then further stratified into a tumor microenvironment and malignant compartment and was computationally analyzed to reveal cancer cell subtypes and programs driving malignancy.

  Study phs003438

• Immune-Related Adverse Events after Immune Checkpoint Blockade-Based Therapy are Associated with Improved Survival in Advanced Sarcoma

  Immune activation after immune checkpoint blockade (ICB) can lead to a unique group of adverse events (AEs), which have been associated with improved outcome in many carcinomas. The association between immune-related AEs (irAEs) and outcome in patients with sarcoma is not well studied. This study has two components: (1) a retrospective clinical study of irAEs among 131 patients treated with ICB at Memorial Sloan Kettering Cancer Center and (2) an analysis of a subset of these patients who have whole transcriptome sequencing available for analysis. In the clinical study portion, we reviewed a cohort of patients with advanced sarcoma treated on prospective clinical trials utilizing ICB-based therapy between April 2017 and January 2020. The objectives were to pool the safety data from each trial, identify irAEs, and correlate them with best overall response by RECIST 1.1, progression-free survival (PFS) and overall survival (OS). Association of irAEs with response and survival was assessed using a Cox regression model. A total of 131 patients were included. Forty-two (32%) had at least one irAE of any grade and 16 (12%) had at least one Grade ≥ 3 irAE. On Cox analysis adjusting for clinical covariates that were significant in the univariate setting, the hazard ratio (HR) for an irAE (HR 0.662, 95% CI 0.421 - 1.041) approached, but did not reach statistical significance for PFS (P = 0.074), while patients had a significantly lower HR for OS (HR 0.443, 95% CI 0.246 – 0.798; P = 0.007) compared to those without or before an irAE. Tumor samples with available RNA sequencing data were stratified by presence of an irAE to identify patterns of differential gene expression. In total, 71 unique patients had RNA sequencing available for analysis. The transcriptomes of 31 of these patients have been previously uploaded to dbGaP (phs002852), leaving 36 unique transcriptomes that have not been previously publicly shared. Three patients did not agree for their sequencing to be publicly shared. Therefore, 33 unique patient samples will be uploaded to this dbGaP study. Overall, this study found that gene expression profiling on baseline tumor samples from patients who had an irAE had higher numbers of tumor-infiltrating dendritic cells, CD8+ T cells, and regulatory T cells as well as upregulation of immune and inflammatory pathways.

  Study phs003284

• Cancer Moonshot Biobank

  The National Cancer Institute initiated the Cancer Moonshot Biobank to accelerate research through the collection and distribution of biospecimens for key research efforts. The Biobank will engage with over one thousand cancer patients, being treated with standard-of-care therapies, for longitudinal biospecimen and data collection. Cancer patients will be enrolled into the study from a diverse participant population engaged at medical institutions throughout the U.S. The biospecimens will be distributed to qualified scientists to accelerate research progress. The Biobank program, working closely with Leidos Biomedical, Inc. (LBR), will partner with community hospitals and other medical institutions, designated as Biospecimen Source Sites (BSS), to engage and consent eligible participants and collect biospecimens and associated clinical data; work with a central Biospecimen Core Resource (BCR) to support biospecimen collection, processing and storage activities and perform pathology quality control; work with LBR's Molecular Characterization (MoCha) lab to perform clinical tumor molecular characterization assays and return results to patients and their physicians; and make the biospecimens and associated data available to researchers to accelerate cancer research progress. Return of clinical results, a dedicated Patient and Provider Engagement (PPE) website, electronic informed consent, local participant engagement projects, and an embedded ethical, legal and social issues sub-study will together support patient and provider engagement in the program. Cancer Moonshot Biobank imaging data is being made available in The Cancer Imaging Archive (TCIA) on a release schedule that is coordinated with the program releases of data to dbGaP. The imaging data can be found at the following link: Cancer Moonshot Biobank Imaging

  Study phs002192

• scRNAseq data from metastatic breast cancer samples

  Paired-end SMARTseq2 data of EpCAM+ sorted cells from liquid biopsies from 3 patients. Sequencing was performed on Illumina HiSeq 2500.

  Dataset EGAD50000000816

• WGS and WES data of metastatic breast cancer tissues and organoids

  Paired-end WGS (x25) and WES data (x2) from metastatic breast cancer organoids, tissues and germline controls. WGS was performed on Illumina NovSeq 6000 and HiSeq X, using Illumina TruSeq Nano DNA kit. WES was performed on Illumina NovSeq 6000 and HiSeq 2000, using Agilent SureSelect XT HS + Human All Exon V7 and SureSelect Human All Exon V6+UTR (hg19).

  Dataset EGAD50000000817

• RNAseq data of metastatic breast cancer samples

  Paired-end RNA sequencing data from 28 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 and HiSeq 4000 using TruSeq Stranded mRNA Kit.

  Dataset EGAD50000000818

• 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

• MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model

  DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth DNAm analysis due to the broad coverage and preservation of rare cell-type signals, compared to array-based data such as 450K/EPIC array. Here, we propose MethylBERT, a novel Transformer-based model for read-level methylation pattern classification. MethylBERT identifies tumour-derived sequence reads based on their methylation patterns and genomic sequence and the method estimates tumour cell fractions within bulk samples. In our evaluation, MethylBERT outperforms existing deconvolution methods and demonstrates high accuracy regardless of methylation pattern complexity, read length and read coverage. Moreover, we show its applicability to cell-type deconvolution as well as non-invasive early cancer diagnostics using liquid biopsy samples. MethylBERT represents a significant advancement in read-level methylome analysis and enables accurate tumour purity estimation. The broad applicability of MethylBERT will enhance studies on both tumour and non-cancerous bulk methylomes.

  Study EGAS50000000806

• WGBS dataset for lymphnode metastasis samples from prostate cancer

  This dataset contains WGBS sequencing data of lymphnode metastasis samples from prostate cancer. Sequencing was performed on Illumina HiSeq X Ten. The sequencing was always paired.

  Dataset EGAD50000001183

• Yale Policy for head and neck cancer and HPV clinical trials

  Yale Policy for human controlled access data associated with head and neck cancer and HPV clinical trials

  Dac EGAC50000000403

• RNAseq of pre- and post-5AZA-treated head and neck cancer patients refractory to anti-PD-1 therapy

  RNA sequencing (RNA-seq) was performed on baseline (before low-dose 5-aza treatment) and on-treatment (low-dose 5-aza treatment for 5 or 10 days) tumor samples from eight participants with head and neck cancer who were refractory to anti-PD-1 therapy. RNA library preparations, sequencing reactions, and initial bioinformatics analyses were conducted at GENEWIZ, LLC. In total, 16 150-bp pair-end RNAseq data were generated.

  Dataset EGAD50000001010

• WES of head and neck cancer patients refractory to anti-PD-1 therapy

  Whole exome sequencing (WES) was performed on baseline (before low-dose 5-aza treatment) blood and tumor paired samples from 12 participants with head and neck cancer who were refractory to anti-PD-1 therapy. DNA extractions were performed by the Broad Institute of MIT and Harvard using Qiagen AllPrep DNA/RNA kits (Cat. 80204). In total, 24 150-bp pair-end WES data were generated by Illumina.

  Dataset EGAD50000001011

• RNA sequencing of serial samples from patients enrolled in the NA-PHER2 trial

  Improved outcomes in HER2+ breast cancer have resulted from chemotherapy and anti-HER2 therapies. However, HER2+ER+ cancers exhibit lower response rates. The NA-PHER2 trial investigated chemo-free preoperative HER2 and CDK4/6 blockade with or without endocrine therapy in HER2+ER+ breast cancer. Through RNA sequencing and tumour infiltrating lymphocytes (TIL) assessment in serial biopsies we identified predictive biomarkers of pCR, Day 14 Ki67 response, and unveiled treatment-induced molecular changes.

  Study EGAS50000000248

• Comprehensive molecular portrait reveals genetic diversity and distinct molecular subtypes of small intestinal neuroendocrine tumors

  This study aims to characterize neuroendocrine tumors of the small intestine (siNETs) from genomic, transcriptomic, epigenomic, and clinical perspectives. Involving 122 patients and 219 samples, we generated whole-genome sequencing data, RNA sequencing data, genotyping arrays, and methylation arrays to conduct an integrative analysis of this rare tumor type. Our findings identify distinct molecular subtypes that correlate with siNET clinical features.

  Study EGAS50000000642

• Enabling sensitive and precise detection of ctDNA through somatic copy number aberrations in breast cancer

  Cell-free DNA (cfDNA) extracted from peripheral blood has emerged as a crucial biomarker source in oncology research. To enhance the detection of somatic copy number alterations (SCNAs) and circulating tumor DNA (ctDNA), we developed eSENSES, a 2Mb breast cancer-targeted NGS panel. It includes 15,000 genome-wide SNPs, 500 focal SNPs in breast cancer driver regions, and exons from 81 commonly altered genes, alongside a custom computational approach. eSENSES provides a reliable, powerful and cost-effective tool for monitoring disease progression and guiding therapeutic decisions in breast cancer patients.

  Study EGAS50000000793

• Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin

  Study EGAS00001004660

• MOSAIC - Multi-Omics Spatial Atlas In Cancer

  MOSAIC is a collaborative initiative founded by Owkin, Lausanne University Hospital (CHUV), Charité Universitätsmedizin Berlin, University Hospital Erlangen (UKER), Gustave Roussy Institute in Paris, and University of Pittsburgh. The goal of MOSAIC is to build the largest collection of spatial omics data in cancer. By integrating comprehensive high quality clinical annotations with advanced deep profiling techniques, MOSAIC aims to uncover novel cancer subtypes and identify key drug targets and biomarkers within them.

  Study EGAS50000000689

• NICHE - DNA-seq of MMR proficient early stage colon cancers

  The dataset includes 152 FASTQ files from paired-end WXS sequencing on Illumina HiSeq2500 or Novaseq 6000 for 31 pMMR patients. This includes 31 tumor DNA and 31 blood germline samples.

  Dataset EGAD50000001247

• NICHE - RNA-seq of MMR proficient early stage colon cancers

  The dataset includes 29 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 and 66 files from 33 paired-end RNA sequencing samples on Novaseq 6000 for 31 pMMR colon cancer patients.

  Dataset EGAD50000001248

• Gene expression profiling in pregnancy-associated breast cancer

  Study EGAS00001008013

• EMBARCAM BC360 PROJECT

  This dataset is related to the EMBARCAM BC360 PROJECT. A total of 106 breast cancer samples, from Pregnancy-Associated Breast Cancer (PABC) (n=57) and non-PABC (n=49) patients, were analysed using the nCounter Breast Cancer 360 V2 panel on the NanoString platform. All samples were FFPE tumor samples from breast cancer patients, derived from GEICAM/2012-03, GEICAM/2017-07, and EpiGEICAM studies, sponsored by GEICAM.

  Dataset EGAD00010002709

• Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy

  Recurrent locally advanced head and neck cancer (HNC) patients, receiving re-radiotherapy (re-RT), are presented with short progression-free (PFS) and overall survival. Hence, biomarkers predicting therapy failure are urgently needed. We analyzed copy number variations (CNVs) in blood plasma of HNC patients collected before, during and after re-RT. Detectable CNVs after five and ten fractions of re-irradiation as well as at the end of re-RT were associated with short PFS. Furthermore, we found that CNV kinetics in longitudinally collected plasma reflected therapy response and could detect disease progression in advance of radiographic tumor assessments.

  Study EGAS50000000163

• CANCAP03 single-nuclear RNA sequencing

  CANCAP03 single-nuclear RNA sequencing. Tissue punch cores for six patients, 3 from each of olaparib and olaparib and degarelix cohorts, were processed for nuclear isolation and extraction, prior to single-nuclear RNA sequencing. 10x libraries were constructed. Sequencing on NovaSeq 6000. FASTQ files were processed using CellRanger pipeline. Outputs from the CellRanger pipeline were analysed using the Seurat package in R.

  Dataset EGAD50000001280

• CANCAP03 Data Access Committee

  Dac EGAC50000000508

• Whole genome sequencing of circulating cell-free DNA on Illumina and Ultima platforms

  The dataset includes Illumina (n=1) and Ultima (n=92) sequencing of circulating cell-free DNA. The dataset was generated through standard whole genome sequencing (Illumina n=1 & Ultima n = 15) and using a duplex unique molecular identifier whole genome sequencing workflow (Ultima, n=77). This dataset includes cancer samples and cancer-free control samples.

  Dataset EGAD50000001234

• Constrained hypermutation and absence of TERT promoter mutations in Lynch syndrome-associated urothelial cancer

  Lynch syndrome is a hereditary condition characterized by defective DNA mismatch repair and high incidence of several cancers, including urothelial cancers (UC) of the upper urinary tract and bladder. We set out to study the somatic landscape of LS-associated urothelial cancer (LS-UC) by analyzing 41 surgical tumor samples and 3 urine DNA samples from 34 LS-UC patients.

  Study EGAS50000000831

• Targeted DNA sequencing of 44 urothelial cancer samples from 34 Lynch syndrome patients

  Targeted Illumina sequencing of 41 tumor tissue samples and 3 urine tumor DNA samples from 34 patients with Lynch syndrome associated urothelial cancer. Target capture was performed using the UroScout hybridization capture panel targeting the coding regions of 25 urothelial cancer genes. Sequencing libraries were constructed using the Twist Biosciences Enzymatic Fragmentation DNA Library Prep kit. Sequencing was performed using an Illumina NovaSeq 6000 instrument with 2x150 bp paired sequencing.

  Dataset EGAD50000001220

• Randomized Phase II 2 x 2 Factorial Trial of the Addition of Carboplatin +/- Bevacizumab to Neoadjuvant Weekly Paclitaxel Followed by Dose-Dense AC in Hormone Receptor-Poor/HER2-Negative Resectable Breast Cancer: DNA Sequencing

  This randomized phase II trial studies how well paclitaxel with or without carboplatin and/or bevacizumab followed by doxorubicin and cyclophosphamide works in treating patients with breast cancer that can be removed by surgery. Drugs used in chemotherapy, such as paclitaxel, carboplatin, doxorubicin, and cyclophosphamide, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing. Bevacizumab may stop the growth of tumor cells by blocking blood flow to the tumor. Giving chemotherapy together with bevacizumab before surgery may make the tumor smaller and reduce the amount of normal tissue that needs to be removed. All participants in this study were female. RNA sequencing data from the same patients were published under phs001863. Subject aliases are the same in the two datasets.

  Study phs003801

• SAPCS Blood RNA-seq of prostate cancer patients

  The study aims to quantify the gene expression in blood samples in 20 prostate cancer patients under the Southern African Prostate Cancer Study (SAPCS). The objective is to identify a list of differentially expressed genes.

  Study EGAS50000000702

• Clonal Evolution of PPM1D Mutations in the Spectrum of Myeloid Disorders

  PPM1D, a central regulator of the DNA damage response, is commonly mutated in therapy-related clonal hematopoiesis (CH), acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS). PPM1D mutations have been shown to expand under selective pressure of DNA-damaging chemotherapy. However, whether PPM1D mutations promote the development of hematologic malignancies remains unclear.

  Study EGAS50000000840

• Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy

  Anti-PD-(L)1 therapy is routinely used in metastatic NSCLC. However, response rates vary and biomarkers predicting treatment efficacy are lacking. Liquid biopsies allow monitoring of residual disease during therapy. Residual circulating tumor DNA (ctDNA) after therapy represents a predictive marker for adverse outcome. Here, we assessed copy number variations (CNVs) in serial plasma samples of NSCLC patients receiving PD-(L)1 blockade. We profiled CNV and fragmentation features in 118 plasma samples of advanced NSCLC patients by low-coverage whole genome sequencing taken at baseline, after four therapy cycles and at disease progression. CNVs and fragment features (i.e., fragment length, end motifs, position) were significantly altered in patients compared to healthy donors. Furthermore, fragment length changes at baseline and residual CNVs after four therapy cycles correlated with short progression-free survival. Our results highlight the suitability of plasma-based CNV and fragment analysis for disease monitoring and as a predictive marker for response duration in NSCLC patients under anti-PD-(L)1 therapy.

  Study EGAS50000000441

• WGS data of non-small cell lung cancer samples

  Paired-end WGS data from 118 non-small cell lung cancer samples from 49 patients. WGS was performed on Illumina NovaSeq 6000.

  Dataset EGAD50000000639

• DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy"

  DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy" with Florian Janke (f.janke@dkfz-heidelberg.de) and Holger Sültmann (h.sueltmann@dkfz-heidelberg.de)

  Dac EGAC50000000308

• Discovery and validation of an ancillary genomic test of malignancy for primary melanocytic tumors

  Background:Pathological diagnosis of melanocytic tumors can be difficult and prone to error. More accurate and reliable ancillary investigations than those currently available are required to improve diagnostic accuracy. Goals: (1) to generate a genomic model for distinguishing benign (nevi) from malignant (melanoma) melanocytic skin tumors, developed from a customized gene panel evaluated on a cohort of 250 nevi and melanomas. (2) To evaluate the performance of the genomic model in melanocytic tumors of uncertain diagnosis/behavior. Details: The cohort of 250 melanomas and naevi was split into a discovery set and a validation set. Our genomic model obtained an area under the curve of 95% in the discovery cohort and 96% for the validation cohort. Based on a Youden index threshold, the resulting classifier shows high specificity (>95% in the discovery and validation cohorts), with sensitivities >80% in the discovery and validation cohorts. Evaluation of the genomic model on a cohort of 110 melanocytic tumors identifies key driver mutations in agreement with the likely pathway of origin of the tumors. The probability of melanoma (p=0.02) from the genomic model was significantly associated with pathology-based estimates of malignancy for melanocytic tumors lacking pathway-defining genomic aberrations (conventional tumors). The genomic model identified 8/36 (22%) conventional tumors with unresolved malignancy to have a high probability of melanoma, with 7/8 of these cases showing negative/non-aberrant results with either fluorescent in-situ hybridization, PRAME and/or p16 immunostains. Furthermore, no evidence of malignant behavior based on the genomic model was seen in 4 conventional borderline tumors with more than 1 year follow-up. Conclusion: This genomic model can become a clinically useful ancillary tool that is highly specific for differentiating melanomas from nevi.

  Study EGAS50000000887

• Tumor Profiler Project - OV scRNA data

  The dataset contains 10x Chromium single-cell transcriptomics data from 43 samples from 38 different patients with ovarian cancer. 36 samples were collected from the tumor, 7 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000001290

• Tumor Profiler Project - OV scDNA data

  The dataset contains 10x Chromium single-cell DNA sequencing data from 42 samples from 38 different patients with ovarian cancer. 35 samples were collected from the tumor, and 7 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000001291

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• Tumor Profiler Project - OV scRNA data additional samples

  The dataset contains 10x Chromium single-cell transcriptomics data from 6 samples from 4 different patients with ovarian cancer. 3 samples were collected from the tumor, 3 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format. This dataset contains additional samples from patients not classified as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001293

• Tumor Profiler Project - OV scDNA data additional samples

  The dataset contains 10x Chromium single-cell DNA sequencing data from 6 samples from 5 different patients with ovarian cancer. 4 samples were collected from the tumor, and 2 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format. This dataset contains additional samples from patients not classified as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001294

• Proteogenomic Analysis of CALGB40601 (ALLIANCE) a Neoadjuvant Phase III HER2-Positive Breast Cancer Trial

  80 frozen core needle biopsies from 54 HER2+ breast cancer patients from the CALGB 40601 trial (NCT00770809) were processed for proteogenomic analysis to identify genes, proteins, and phosphosites associated with pathological complete response to neodjuvant anti-HER2 therapies. The final set included 22 patients treated with trastuzumab plus lapatinib in combination with pacletaxel (THL arm), 24 patients treated with trastuzumab in combination with pacletaxel (TH arm), and 8 patients treated lapatinib in combination with pacletaxel (TL arm). Principal findings of this study included identifying negative cases misdiagnosed as HER2+ that did not respond to targeted therapy and observing higher levels of two biomarker candidates in non-pCR tumors. Mass spec-based proteomics and phosphoproteomics data generated from 75 biopsies (all 54 patients) will be made available via the Proteomic Data Commons. Whole exome- (67 biopsies from 49 patients) and RNA-sequencing (52 biopsies from 39 patients) data for the subset profiled with proteogenomics will be made available through dbGaP, but genomic and transcriptomic profiling data for the whole cohort has previously been deposited (phs001570).

  Study phs003576

• DNA Methylation in Prostate Tumor and Paired Benign Tissue for African and European Ancestry Men

  We recruited prostate cancer (PCa) patients undergoing robotic-assisted laparoscopic radical prostatectomy at the University of Chicago Medical Center Urology Clinic between 2011 and 2017. Our study includes 76 African American (AA) and 75 European American (EA) men with PCa of Gleason Score (GS) ≥7, recruited by the Epidemiology Research Recruitment Core at the University of Chicago. All patients consented to the collection of questionnaire data, prostate tissue, and medical records. The study was approved by the Institutional Review Board of the University of Chicago. Following prostatectomy, prostate tissue was sent to the Human Tissue Research Center (HTRC) at the University of Chicago. Each sample underwent histological examination and Gleason scoring by University of Chicago genitourinary pathologists. The presence of adenocarcinoma was confirmed by overexpression of alpha-methylacyl-coenzyme-A racemase (AMACR) and areas for DNA extraction were marked. Tissue samples used for DNA extraction were obtained using with either a 1mm biopunch or laser microdissection of a 100 µm2 area of tissue. Genome-wide DNA methylation profiles were generated using Illumina's Infinium MethylationEPIC BeadChip array kit. Genome-wide SNP data was generated (from benign tissue DNA) using the Illumina Infinium Multi-Ethnic Global-8 v1.0 array at the University of Chicago Genomics Core Facility. We performed imputation using the Haplotype Reference Consortium (HRC, Version r1.1 2016) panel, which includes all samples from the 1,000 Genomes Project (Phase 3), using the Michigan Imputation Server. The imputed SNP data for mQTL analysis was imputed based on genotype SNP data which was all from benign tissue DNA and the methylation data was identified in both tumor and benign tissue, both AA and EA men, and identified QTLs co-occuring with prostate cancer susceptibility loci.Data including SNP genotypes, DNA methylation, tissue type, and participant characteristics will be available in dbGaP.

  Study phs003516

• Atezolizumab Plus Personalized Neoantigen Vaccination in Patients with Urothelial Cancer: a Phase 1 Trial

  This is a phase 1 single center clinical trial evaluating a multi-peptide personalized neoantigen vaccine, PGV001, in combination with atezolizumab for patients with urothelial cancer. Patients were enrolled in either the adjuvant or metastatic setting. Those in the adjuvant setting included patients considered high risk of recurrence (pathological stage ypT2-T4 or ypN+ for those treated with prior neoadjuvant chemotherapy or pT3-T4 or pN+ for those not treated with prior neoadjuvant chemotherapy). Those in the metastatic setting included patients progressing after prior chemotherapy or those with at least stable disease after chemotherapy treated as “switch maintenance” therapy. The primary endpoint was feasibility (including the number of neoantigens identified per patient, vaccine production time, the proportion of patients consenting to the vaccine development phase for whom a vaccine product was prepared, and the proportion of patients eligible for the treatment phase who completed the priming cycle 1 of PGV001 plus atezolizumab) and safety. Secondary endpoints included the objective response rate, progression-free survival or disease-free survival, overall survival, and immunomodulatory effects of treatment. Urothelial tumor tissue and normal tissue or peripheral blood specimens were utilized for DNA sequencing. HLA typing was performed utilizing genomic DNA isolated from whole blood, and RNA sequencing was performed utilizing tumor tissue specimens. Neoantigen prediction and final selection for incorporation into the vaccine was determined by the OpenVax computational pipeline. 12 patients were initially enrolled into the vaccine development phase and 10 patients initiated the treatment phase. PGV001 was administered with poly-ICLC and tetanus peptide on subsequent days for up to 10 doses, including an initial priming cycle 1. Atezolizumab was administered every 3 weeks for up to 1 year in the adjuvant setting or 2 years in the metastatic setting. The vaccine was feasible and safe, the median vaccine production time was 20.3 weeks, and 100% of patients that initiated the treatment phase completed the priming cycle. The most common treatment-related adverse events were local grade 1 injection site reactions, fever, and fatigue. Three of the 4 patients in the adjuvant setting remained disease-free at median follow-up of 39.5 months. There was a 40% objective response rate among patients with measurable disease in the metastatic setting. The single patient treated as “switch maintenance” therapy remained with no evidence of disease at 39.4 month follow-up. All patients demonstrated on-treatment neoantigen-specific T cell reactivity, as measured by ELISPOT and flow cytometry assays. Overall, PGV001 plus atezolizumab was feasible, safe, and warrants further investigation. Whole exome sequencing from tumor tissue and normal tissue or whole blood specimens and RNA sequencing from tumor tissue specimens will be available through dbGaP.

  Study phs003922

• Array-based methylation analysis of SDHB-deficient pheochromocytoma and paraganglioma

  Study EGAS00001007844

• Multi-omic analysis of SDHB-related PCPG

  Hereditary SDHB-mutant pheochromocytomas (PC) and paragangliomas (PG) are rare tumours with a high propensity to metastasize although their clinical behaviour is unpredictable. To characterize the genomic landscape of these tumours and identify metastasis biomarkers, we performed multi-omic analysis on 94 tumours from 79 patients using six molecular methods including: whole-genome sequencing (WGS) of tumour and matched blood (n=94), whole transcriptome sequencing (RNA-seq) (n=91), small-RNA seq (n=90), DNA methylation profiling (n=93). Droplet-based (10x) single nuclei (sn)RNA-seq and snATAC-seq was applied to 9 and 7 cases, respectively. Additionally snATAC-seq was applied to one sample of normal adrenal medulla.

  Study EGAS50000000346

• Rapid brain tumor classification from sparse epigenomic data

  Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.

  Study EGAS50000000559

• Study of biomarkers implicated in radio-immunotherapy response in metastatic cancer

  Immuno-radiotherapy may improve outcomes for patients with advanced solid tumors, although optimized combination modalities remain unclear. Here, we report the analysis from the SABR-PDL1 (NCT02992912) trial that evaluated the PD-L1 inhibitor atezolizumab in combination with stereotactic body radiation therapy (SBRT) in patients with advanced cancer.

  Study EGAS50000000681

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• Timing and trajectory of BCR-ABL1 driven chronic myeloid leukaemia

  Mutation of some genes provide fitness advantages that drive uncontrolled cell proliferation, leading to clinical manifestations of cancer. The discovery of the Philadelphia chromosome in chronic myeloid leukaemia (CML) provided the very first such genetic link to cancer and the hypothesis that this lesion provided an abnormal growth advantage to cells. However, little is known about the trajectory to CML, the rate of BCR::ABL1 driven clonal expansion, and how this impacts on disease presentation. Here, using whole-genome sequencing of 1013 single-cell-derived colonies from patients with CML, we reconstruct phylogenetic trees of haematopoiesis in 9 patients aged 22 to 81 years at diagnosis. The expected intronic breaks in BCR and ABL1 were not always observed, and out-of-frame exonic breakpoints in BCR, requiring exon skipping to derive BCR::ABL1 fusion transcripts, were noted in several patients. Apart from ASXL1 and RUNX1 mutations, additional somatic mutations in myeloid genes were generally present only in wild-type cells and did not contribute to the CML clone. Using phylogenetic analysis, we infer sustained explosive growth attributed to BCR::ABL1 fusion, with clonal expansions beginning 3-14 years (Cl 2-16 years) before diagnosis and annual growth rates exceeding 70,000% per year in some young patients with the most recent and rapid clonal expansions. Mutation rate was higher in BCR::ABL1-positive cells than in wild-type counterparts, together with markedly shorter telomere lengths, reflecting their excessive cell division history. Clonal expansion rates inferred from phylogenetic trees were in line with mutational signature patterns and telomere attrition, and inversely correlated with the time to diagnosis. Whole genome sequencing of advanced phase CML was characterised by genomic evolution within BCR::ABL1-positive cells. Our findings highlight the oncogenic potency of a single BCR::ABL1 fusion and its capacity to drive fast clonal outgrowth to cancer. These data contrast with the early-in-life, slow, and sequential clonal trajectories typical of most cancers, such as Philadelphia-negative myeloproliferative neoplasms, solid organ malignancies, and patterns of clonal expansion in healthy tissue ageing.

  Dataset EGAD00001015473

• MOSAIC Window Glioblastoma Data

  This dataset will include Spatial Transcriptomics, Single-Cell RNA-Seq, Bulk RNA-Seq, Clinical data, WES, and H&E data from 10 Glioblastoma (GBM) Cancer patients. Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001352