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• SUM-seq data for Macrophage polarisation to M1 and M2 phenotypes experiment

  We stimulated iPSC-derived M0 macrophages with LPS and IFN-γ to induce M1 polarization or IL-4 to induce M2 polarization. To discern early and sustained responses at chromatin accessibility and gene expression levels, we collected samples at five time points along the two polarization trajectories; prior to stimulation (M0) and at 1-hour, 6-hour, 10-hour, and 24-hour intervals, each sampled in duplicates totaling 18 samples, and subjected them to SUM-seq library preparation. Sequenced files for both data modalities are provided as demultiplexed fastq files.

  Dataset EGAD50000001206

• High-resolution testing of ctDNA dynamics predicts survival in metastatic NSCLC

  One of the great challenges of therapeutic oncology is determining who might achieve survival benefit from a particular therapy. Circulating tumor DNA (ctDNA) provides real-time assessments of patient prognosis and response to treatment using a simple blood draw. While ctDNA positivity is established as a poor prognostic factor, studies on longitudinal ctDNA dynamics have been small and non-randomized, with ctDNA assessments done at disparate time points. To address this, we performed high-sensitivity longitudinal ctDNA testing in 466 patients across 5 time points (1,954 samples total) in a randomized phase III study comparing different chemotherapy-immunotherapy combinations. We leverage machine learning to jointly model multiple ctDNA metrics to predict overall survival in a training/testing framework. _ . Treatment initiation correlated with reductions in ctDNA levels, and training of our machine learning model suggests that assessment of ctDNA dynamics at C3D1 (cycle 3 day 1) of chemo-IO treatment may be optimal to predict OS. The model performs well in the hold-back test data, enabling stratification of patients with Stable Disease (SD) into high-risk vs low-intermediate-risk (HR = 3.2 [2.0-5.3], p <0.001; median 7.1 versus 22.3 months respectively); similarly, the model stratifies patients with a Partial Response (PR) (HR =3.3 [1.7-6.4], p <0.001; median 8.8 versus 28.6 months). Importantly, the model validates well in an external cohort of patients in a different treatment setting and assayed with a different ctDNA technology, in which model predictions similarly identified high-risk patients (OS HR=3.73 [1.83-7.60], logrank p=0.00012). Simulations of clinical trial scenarios employing our ctDNA model further suggest that early ctDNA testing outperforms early radiographic imaging for predicting trial outcomes (increasing the rate of ‘True Go’ decisions by 5.2 - 22.8% depending on the drug combination). Overall, we show that measuring ctDNA dynamics during the course of therapy dramatically improves patient risk stratification, and may provide a means to differentiate between competing therapies at an early time point during clinical trials.

  Study EGAS00001006703

• SCANDARE HNSCC DNA targeted panel sequencing

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 232 FFPE samples at baseline from 83 HNSCC patients using DNA targeted panel sequencing, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001654

• 16S-based fecal microbiota composition

  The dataset reports the 16S rRNA gene sequencing of the fecal microbiota of donors from the Milieu Intérieur Cohort. The Milieu Intérieur cohort includes a total of 1,000 healthy individuals of western European ancestry, recruited in France as part of the Milieu Intérieur project. To assess their fecal microbiota composition, 16S rRNA profiles were generated from stool samples of 863 of the 1,000 donors. Human stool samples were produced at home no more than 24 hours before the scheduled medical visit and collected in a double-lined sealable bag maintaining strict anaerobic conditions. Upon reception at the clinical site, the fresh stool samples were aliquoted and stored immediately at -80°C. DNA was extracted from stool and barcoding PCR was carried out using indexed primers targeting the V3-V5 region of the 16S rRNA gene. Equal volumes of normalized PCR reaction were pooled and thoroughly mixed. The amplicon libraries were sequenced on Illumina MiSeq.

  Dataset EGAD00001004979

• Complete Genomics Deep Whole-Genome Sequencing of Circulating Tumor Cells from a Patient with Metastatic Breast Cancer

  Circulating tumor cells (CTCs) are considered to be informative non-invasive biopsy for the early detection, diagnosis or therapy guidance of cancer. CTCs also contain most of the heterogeneity found across multiple metastatic sites. In this study, we combine recently improved CTC isolation methods, resulting in almost pure CTCs, with advanced whole genome sequencing (WGS) based on Long Fragment Read (LFR) technology to demonstrate, for the first time, the research and clinical utility of an accurate, comprehensive, phased, and quantitative genomic analysis of CTCs. In particular, genomes of 34 CTCs, collected at two different time points from a patient whose metastatic breast cancer ultimately became resistant to standard treatments, were analyzed as 3072 barcoded sub-genomic compartments of long DNA. An average read coverage of 23X per cell enabled the high-resolution detection of somatic variants, cancer copy number variations (CNVs) and structural variants, including 133 CNVs shorter than 1Mb and an early chromothripsis-like event.

  Study phs001028

• Novel Strategies to Eliminate Resistance to B-cell Receptor Inhibitor Therapy in Lymphoid Malignancies

  Ibrutinib and acalabrutinib are BTK inhibitors (BTKi) used as frontline therapies for chronic lymphocytic leukemia (CLL). Clonal evolution during ibrutinib treatment has previously been studied, but limited study of clonal evolution in patients receiving acalabrutinib has been done. Our group analyzed 216 blood samples from 38 CLL patients at multiple time points during their BTKi treatment. Samples were prepared by standard protocols and sequenced using 200x Illumina sequencing. Using the longitudinal data, we reconstructed the clonal evolution of each patient using somatic mutations found within the B-cell populations. Three patterns of clonal evolution were identified: 1) new clone emergence, 2) clonal selection, and 3) clonal replacement. As previously seen in ibrutinib treatment, the evolution of subclones containing CLL-driver mutations was associated with worse clinical outcomes for patients treated with acalabrutinib (Log-rank p=0.04). Understanding clonal evolution during treatment with acalabrutinib can help determine and modify the clinical course of patients with CLL.

  Study phs003042

• Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

  The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

  Study phs003322

• A Comprehensive Platform for Analyzing Longitudinal Multi-Omics Data

  PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for analyzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type or user defined groups. It allows to infer stable and variable features in a given donor and each cell type or a user defined group. The outlier analysis can be performed to identify technical/biological perturbed samples in a donor or a participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type. The data that is available in the dbGaP is the demo longitudinal samples used in the study, which includes hashed raw fastq files for single-cell RNA-sequencing (scRNA-seq) and non-hashed fastq files for single-cell ATAC-sequencing (scATAC) experiment.

  Study phs003203

• Starting Treatment with Agonist Replacement Therapies (START): A Randomized Trial of Methadone vs Buprenorphine/Naloxone for the Treatment of Opioid Dependence

  The Starting Treatment with Agonist Replacement Therapy (START) study was a 24-week, open-label, randomized trial of methadone versus Suboxone (buprenorphine/naloxone) for the treatment of opioid dependence. Patients were over the age of 18 and met DSM-IV qualifications for opioid dependence. The primary goal of the study was to determine if either medicine was associated with liver toxicity issues in this vulnerable patient population. Liver enzymes were measured at four time points. Urinalysis for opioids, cocaine, cannabis, benzodiazepines, and methamphetamine were performed on a weekly basis. A flexible dosing scheme was used during which physicians could alter medication dose based on withdrawal symptoms and urinalysis results. Neither medication was found to be associated with liver enzyme levels. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001135

• Genomics and Methylation of Neuroendocrine Prostate Cancer from cfDNA (Cornell/Trento 2019)

  A subset of castration resistant prostate cancers develop small cell neuroendocrine prostate cancer (NEPC) as a mechanism of treatment resistance. Metastatic tissue biopsies to evaluate for NEPC transformation are invasive and challenging to perform serially. We performed whole exome and whole genome bisulfite sequencing of plasma cfDNA and matched tumor biopsy samples from 62 patients with metastatic prostate cancer along the disease spectrum to evaluate for NEPC associated genomic and epigenomic features. Multiple tissue biopsies and/or plasma time points were included for a subset of patients to characterize disease heterogeneity and dynamic changes. Computational analysis of clonality and allele specific quantification allowed for detailed comparison of matched tumor tissue and cfDNA data (CLONET v2). Methylation profiles detected from tissue and plasma data were compared and NEPC specific alterations were evaluated in cfDNA. The study supports the feasibility of a plasma based assay for the detection of NEPC.

  Study phs001752