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• A Risk Score Incorporating Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Study EGAS00001006308

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• RNA-Seq Data From Early Stage Triple Negative Breast Cancer Tumors Treated With TVEC and Chemotherapy (MCC18621)

  This study is a phase 1/phase 2 trial testing the combination of talimogene laherparepvec (TVEC) and neoadjuvant chemotherapy for the treatment of stage II-III triple negative breast cancer. The trial demonstrated that the addition of TVEC to neoadjuvant chemotherapy was feasible, and resulted in a pathological complete response (pCR) rate of 45.9%, residual cancer burden (RCB) 0-1 rate of 65%, and event free survival of 89%. The macrodissected formalin-fixed paraffin-embedded (FFPE) samples were from 50 patients treated across two phases at different timepoints (pre-treatment, 6th week of treatment, and surgical resection). RNA-Seq data is provided along with clinical classifiers.

  Study phs003199

• Division of Cancer Epidemiology and Genetics (DCEG) Imputation Reference Dataset

  We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.

  Study phs000396

• Tumor Fraction Guided Cell-Free DNA Profiling in Metastatic Cancer Patients

  Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. The results show that cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.

  Study phs002290

• cfDNA dataset for cfDNA cohort

  Cell free DNA sequencing data for 233 samples across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000104

• TOPARP-B patient cell-free DNA WGS

  Sequencing files for TOPARP-B patients as described in manuscript

  Study EGAS50000000280

• Influence of age on molecular changes and treatment stratification in multimodal glioblastoma therapy

  Background: The increasing life expectancy has led to a rise in high-grade gliomas, particularly in patients of older age. The impact of chronological age, associated molecular changes and contributing factors on therapy response, progression-free survival (PFS) and overall survival (OS) remain uncertain. Methods: Between January 1st, 2016, and December 31th, 2021, patients with glioblastoma IDH-wt (CNS WHO grade 4) were included. RNA- and T-cell receptor sequencing was performed in a subset of patients. Primary outcome parameters were extent of resection (EOR), progression free- and overall survival. Multivariate analysis was performed to identify independent predictors of survival. Results: A total of 286 patients were included. The mean age was 66.4 years. Chronological age did not correlate with overall survival (r=0.12). With age, tumor immune composition changed towards macrophages with M2 phenotype and decreased numbers of CD8+ and neutrophiles. Aging related genes were not enriched. Beyond 69.5 years of age, despite similar PFS (p=0.0783), OS (p<0.0001) was significantly shorter, compared to younger patients. Extent of resection and adjuvant radiochemotherapy were significant predictors of OS (p<0.0001). No difference in PFS and OS was found between younger and older patients treated with maximal safe resection, followed by concomitant RT and chemotherapy and adjuvant chemotherapy. Conclusions: This study suggests that age alone should not be the sole determinant in therapeutic decision-making for glioblastoma patients. Gross total resection and adjuvant therapy, tailored to individual clinical status, significantly impact survival outcomes. Patient-specific treatment strategies are important to minimize undertreatment and optimize therapeutic outcomes in older patients.

  Study EGAS00001008246

• STAMPEED: Cardiovascular Health Study (CHS) GWAS to identify genetic variants associated with aging and CVD risk factors and events

  The primary aim of the study is to conduct a genome-wide association study to identify genetic variants associated with the incidence of myocardial infarction (MI), stroke, and heart failure (HF) among participants enrolled in the Cardiovascular Health Study (CHS) who were free of clinical cardiovascular disease at baseline. The secondary aim is to conduct genome-wide association study of other phenotypes in CHS. The study is an ancillary study to CHS. CHS is a population-based cohort study of risk factors for heart disease and stroke among older adults recruited at 4 US sites in 1989-1990. Subjects underwent an extensive baseline examination, and annual follow-up examinations through 1988-1999.

  Study phs000226

• Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors

  Cell-free tumour-derived DNA (ctDNA) allows non-invasive monitoring of various cancers but its utility in renal cell cancer (RCC) has not been well established. A combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n=90) with various renal tumour subtypes, were used to determine ctDNA content in plasma and urine. Our data revealed lower plasma ctDNA levels in RCC relative to other cancers, with untargeted detection of ~33% for both cohorts. A highly sensitive personalised approach, applied to plasma and urine from select patients (n=22), improved detection to ~50%, including in patients with early stage and even benign lesions. A machine-learning based model, applied to untargeted data, predicted this detection, potentially offering a means of triaging patient samples for personalised analysis. We observed that plasma, and for the first time, urine ctDNA may better represent tumour heterogeneity than a single tissue biopsy. Longitudinal sampling of >200 plasma samples revealed that ctDNA can track disease course. These data highlight low ctDNA levels in RCC but indicate potential clinical utility provided improvement in isolation and detection approaches.

  Study EGAS00001003530