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• Integrative Somatic and Germline Computational Biology to Redefine Clinical Actionability in Solid Tumors

  Neuroendocrine tumors (NETs) are rare cancers that arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic NETs (GEP-NETs) growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we performed single-cell RNA-sequencing (scRNA-seq) of fresh resections of GEP-NETs, including four pancreatic NETs, three small intestinal NETs, and one perigastric NET. We used single-cell sequencing to investigate the tumor and immune cellular landscapes of GEP-NET patients. Malignant GEP-NET gene and regulon expression was compared with normal, gastrointestinal endocrine cell differentiation and fate determination stages. We further characterized immune-immune and immune-tumor interaction networks within GEP-NETs, identifying novel therapeutic opportunities in the myeloid compartment of the microenvironment. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

  Study phs003141

• BarcUVa-Seq (Biology of Colorectal Cancer Risk Enhancers)

  This study was designed to generate a cohort of normal colon mucosal biopsies from the "average risk" population. Its primary aims included the development of an RNA-seq dataset of normal colon mucosal biopsies across three colon regions (ascending, transverse and descending). Further, we aimed to provide plausible prioritization to genetic components of colorectal cancer risk by employing methods such as expression quantitative trait loci analysis. In doing so, we provide a novel reference dataset for the study of colon cancer risk in the healthy colon epithelium. RNA-seq was performed in batches on an Illumina HiSeq 2500 (batch 1-7) or NovaSeq 6000 (batch 8) on a total of 463 samples. Matched genotyping data was generated on the Illumina OncoArray BeadChip. Phasing was carried out using Minimac 3 and imputation was performed using The Haplotype Reference Consortium panel on the Michigan Imputation Server.Genotype and RNA-seq data will be made available in dbGaP.

  Study phs003338

• Deterministic Evolution and Stringent Selection During Pre-Neoplasia

  The earliest events during human tumor initiation are poorly characterized but may hold clues as to how to detect and prevent malignancy. Here we model this occult process by engineering TP53 deficiency in primary human gastric organoids and performing experimental evolution in multiple clonally derived cultures over two years, thereby defining causal relationships between this common initiating genetic lesion and resulting phenotypes. TP53 loss induced progressive aneuploidy, including copy number alterations and complex structural variants that are common in established gastric cancers, and which accrued along a defined temporal order. Longitudinal single cell sequencing of TP53 deficient gastric organoids similarly indicates progression towards malignant transcriptional programs. Moreover, lineage tracing with expressed cellular barcodes revealed highly reproducible dynamics whereby initially rare subclones with shared transcriptional programs repeatedly attain clonal dominance. This powerful platform for experimental evolution reveals stringent selection and convergence at the genotypic and phenotypic levels in pre-malignant epithelial organoids, illuminating evolutionary constraints and barriers to malignant transformation.

  Study phs003249

• Unraveling the Genetic Architecture of Diabetic Retinopathy in South India

  This study aims to understand the genetic architecture of diabetic retinopathy in the South Indian population by examining participants with South Indian ancestry and type 2 diabetes (T2D) from two sources: the Sankara Nethralaya-Diabetic Retinopathy Epidemiology and Molecular Genetic Study (SN-DREAMS) and prospective recruitment at Sankara Nethralaya affiliates. A total of 2393 patients were recruited and included in the genetic analysis, with 1588 patients having no diabetic retinopathy (DR) serving as the controls and 805 patients with any level of DR serving as the cases. Enrolled individuals had genome-wide genotyping from DNA extracted from blood samples. In addition, whole genome sequencing (WGS) was performed on 31 members from 2 families. Clinical data, such as age, duration of diabetes, and hemoglobin A1C (HbA1c) were recorded for study participants. Diabetic retinopathy was assessed by clinical exam and/or fundus photography. The grading of diabetic retinopathy followed the International Clinical Diabetic Retinopathy Severity Scale.

  Study phs002116

• Structure of the Mucosal and Stool Microbiome in Lynch Syndrome

  The gut microbiota has been associated with colorectal cancer (CRC), but causal alterations preceding CRC have not been elucidated. To prospectively assess microbiome changes prior to colorectal neoplasia, we investigated samples from 100 Lynch syndrome patients using 16S rRNA gene sequencing of colon biopsies, coupled with metagenomic and metatranscriptomic sequencing of feces. Colectomy and CRC history represented the largest effects on microbiome profiles. A subset of Clostridiaceae were depleted in stool corresponding with baseline adenomas, while Desulfovibrio was enriched in both stool and mucosal biopsies. A classifier leveraging stool metatranscriptomes resulted in modest power to predict interval development of preneoplastic colonic adenoma. Predictive transcripts corresponded with a shift in flagellin contributors and oxidative metabolic microenvironment, potentially factors in local CRC pathogenesis. This suggests that the effectiveness of prospective microbiome monitoring for adenomas may be limited but supports the potential causality of these consistent, early microbial changes in colonic neoplasia.

  Study phs002343

• Identification of High-Risk PHF19 Expressing Cells in Myeloma Single-Cell Multiomics

  The aim of this study is to identify novel subsets of cells that are associated with progression and response to treatment. In this project, we study the tumor fraction from 49 myeloma patients across stages of progression. Samples were collected from 10 smoldering multiple myeloma (SMM), 22 newly diagnosed multiple myeloma (NDMM), and 17 relapsed refractory multiple myeloma (RRMM) patients. These samples were then sorted using magnetic-activated cell sorting (MACS) for CD138+ cells that represent the tumor fraction of each sample. The CD138+ fraction then underwent whole genome sequencing (WGS), where possible, and single-cell multiomics. Single-cell multiomics can now measure scRNA-seq and scATAC-seq simultaneously, which we use in this project. Using single-cell multiomics, we will study subclonal changes in gene expression, chromatin accessibility, and identify novel regulatory relationships within myeloma tumors. Furthermore, we will apply state of the art single-cell and single-cell multiomic techniques to better identify the more high-risk components of myeloma.

  Study phs003220

• Ipilimumab and Decitabine in Treating Patients With Relapsed or Refractory Myelodysplastic Syndrome or Acute Myeloid Leukemia

  The NCI Experimental Therapeutics Clinical Trials Network (ETCTN)/Cancer Therapy Evaluation Program (CTEP) 10026 study (NCT02890329) tested combined ipilimumab and decitabine treatment in two cohorts: Arm A consisted of patients with relapsed acute myeloid leukemia (AML) after allogeneic hematopoietic stem cell transplantation. Arm B consisted of patients with advanced myelodysplastic syndrome (MDS) or AML that did not previously undergo stem cell transplantation. During the study, peripheral blood and bone marrow samples were obtained from study participants at study entry (screening), following the first lead-in cycle of decitabine monotherapy, during combined treatment with decitabine and ipilimumab, and at the end of treatment.This study tested the combination of the CTLA-4 blocking antibody ipilimumab and the DNA methyltransferase inhibitor decitabine in advanced myeloid disease in the transplant-naive and post-transplant context. The samples were used for bulk and single cell RNA sequencing (scRNA-seq) as well as whole exome sequencing (WES).

  Study phs003015

• Single cell chromatin accessibility allows analysis of the transposable element landscape, revealing shared features of immune tissue-residency

  Tissue adaptation is required for regulatory T (Treg) cells to function within organs. Whether this program shares similarities between different tissue-localized immune populations is poorly understood. Here, we addressed this by analyzing single-cell chromatin accessibility data, including the transposable element (TE) landscape, of CD45+ immune cells from different tissues. We identified features of organ-specific tissue adaptation across different immune cells. Focusing on tissue-Treg cells, we found that the Treg tissue adaptation program was conserved in other tissue-localized immune cells, such as amphiregulin-producing Th17 cells. Accessible TEs can act as regulatory elements but their contribution to tissue adaptation is unclear. TE landscape analysis revealed an enrichment of specific transcription factor binding motifs in TE regions within accessible chromatin peaks. TEs, specifically from the LTR family, were located in enhancer regions and associated with tissue adaptation. These findings broaden our understanding of immune tissue-residency, an important step towards organ-specific immune interventions.

  Study EGAS50000000350

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__alkylating_agents

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003637

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__oncology_agents

  he Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001004125