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• Integrated Genomic Analysis of Periampullary Tumors at The Human Genome Sequencing Center, Baylor College of Medicine (HGSC-BCM)

  Adenocarcinomas arising in the complex environment of the ampulla of Vater constitute a histopathological heterogenous group, presumably originating from the different epithelial cellular constituents present at the site: pancreas, bile duct, and intestinal duodenum. These tumors have been described in many different ways: intra-ampullary, periampullary, intra-ampullary papillary-tubular neoplasm, ampullary-ductal, periampullary-duodenal, and ampullary-not otherwise specified. These varied classifications reflect the difficulty in classifying these tumors into specific groups. Only the tumors clearly localized in the bile duct or duodenum are identified as distal cholangiocarcinomas (CAC) or duodenal adenocarcinomas (DUOAC). The current classification is based on macroscopic features that may distinguish the epithelium of origin, microscopic features, clinicopathological criteria, histopathology and expression of differential markers. This classification is subjective and prone to inter-observer variability and significantly impacts on treatment selection and therapeutic development. In order to define subtypes of periampullary cancer with clinical relevance, we performed whole exome sequencing and copy number analysis of 160 cancers arising in the periampullary region, 62 of these clearly arising from either the bile duct (n = 44), or the duodenum (n = 18) and 98 periampullary cancers (AMPAC) where the epithelium of origin could not be clearly defined.

  Study phs000895

• WNT-dependent interaction between inflammatory fibroblasts and FOLR2+ macrophages promotes fibrosis in chronic kidney disease

  Chronic kidney disease (CKD) is a public health problem driven by myofibroblast accumulation, leading to interstitial fibrosis. Heterogeneity is a recently recognised characteristics in kidney fibroblasts in CKD, but the role of different populations is still unclear. Here, we characterize a proinflammatory fibroblast population (named CXCL-iFibro), which corresponds to an early state of myofibroblast differentiation in CKD. By performing immunofluorescence studies and spatial transcriptomics analysis on 2 patients, we demonstrate that CXCL-iFibro co-localize with macrophages in the kidney and participate in their attraction, accumulation, and switch into FOLR2+ macrophages from early CKD stages on. In vitro, we cultured primary inflammatory fibroblasts that we characterized by using bulk RNAseq. We show that macrophages promote the switch of CXCL-iFibro into ECM-secreting myofibroblasts through a WNT/-catenin-dependent pathway, thereby suggesting a reciprocal crosstalk between these populations of fibroblasts and macrophages. Finally, the detection of CXCL-iFibro at early stages of CKD is predictive of poor patient prognosis, which shows that the CXCL-iFibro population is an early player in CKD progression and demonstrates the clinical relevance of our findings.

  Study EGAS50000000101

• A Single-Cell Atlas of the Multicellular Ecosystem of Primary and Metastatic Hepatocellular Carcinoma

  Hepatocellular carcinoma (HCC) represents a paradigm of the relation between tumor microenvironment (TME) and tumor development. Here, we generated a single-cell atlas of the multicellular ecosystem of HCCs from four relevant sites. Antitumor central memory T (TCM) cells were found in tertiary lymphoid structures (TLSs). Chronic HBV/HCV infection increases infiltration of CD8+ T cells in tumors but aggravates T cell exhaustion. We identified CD11b+ macrophages to be terminally differentiated tumor-associated macrophages (TAMs) and two distinct differentiation trajectories contribute to their accumulation. We further demonstrated CD11b+ TAMs promote HCC cells invasion and migration, and angiogenesis. We characterized the heterogeneous subpopulations of malignant hepatocytes and their multifaceted roles in shaping the immune microenvironment. Finally, we identified seven TME subtypes that can predict patient prognosis. Collectively, this large-scale atlas deepens our understanding of the ecosystem in primary and metastatic HCCs, might facilitating the development of new immune therapy strategies for this malignancy.

  Study EGAS00001004468

• Endocrine therapy reprogramming of breast cancer facilitates metastatic escape via upregulation of P-Rex1/Rac1 signalling

  The estrogen receptor (ER) drives growth in ~70% of breast cancers, and endocrine therapies prevent recurrence. However, 30% of patients recur, with many fatal cases occurring late (after >5 years), presenting a challenge due to their often non-proliferative nature and limited options. To study this, we generated slow-growing resistant cells that form small primary tumours but readily metastasize. Single-cell RNA sequencing (scRNAseq) revealed that endocrine therapy reprograms these cells, notably upregulating the Rac1 signalling component P-Rex1. We found in clinical cohorts that P-Rex1 in high in ER+ breast cancer. Intravital imaging demonstrated that Rac1 signalling is active in ER+ cells following endocrine therapy. Targeting the Rac1 pathway with small molecule inhibitors (NSC23766, R-ketorolac) reduced survival and motility in resistant cells, inhibited in vivo Rac1 activity, and reduced tumour burden when combined with tamoxifen in a drug-refractory patient-derived xenograft. This work identifies the P-Rex1/Rac1 axis, as a potential therapeutic target for late recurring ER+ breast cancer.

  Study EGAS00001008353

• Evolutionary analysis of primary tumors and metastatic lesions from 20 breast cancer patients (99 samples in total) using exome sequencing data.

  Metastatic breast cancers are still incurable. Characterizing their evolutionary landscape including the role of metastatic axillary lymph nodes to seed distant organ metastasis can provide rational basis for effective treatments. Here, we describe the genomic analyses of the primary tumors and metastatic lesions from 20 breast cancer patients (99 samples). Our evolutionary analyses revealed diverse spreading and seeding patterns governing tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, where multiple metastatic subclones originated from primary tumor and/or other distant metastases. Synchronous axillary lymph node metastasis, a well-established prognosticator of breast cancer, was not involved in seeding distant metastasis, suggesting haematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably a significant increase in apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) associated mutagenesis. Our data provide the first genomic evidence regarding the role of axillary lymph node metastasis in seeding distant organ metastasis and elucidates the evolving mutational landscape during cancer progression.

  Study EGAS00001002737

• Alzheimer's Disease Sequencing Project (ADSP)

  NOTICE OF CHANGE IN LOCATION FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) GENETIC AND PHENOTYPIC DATA: ADSP whole exome and whole genome sequence data that are shared through dbGaP were mapped to the Genome Reference Consortium human genome GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. Please see the ADSP Design page for the complete study description. All data that are mapped to GRCh38 (hg38) are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). For instructions on how access the ADSP Build 38 data that are shared through NIAGADS DSS, visit the Application Instructions page. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases The first ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals. The second ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals. The third ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals. The fourth ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data. The fifth ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs. The sixth ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs. This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members. Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.

  Study phs000572

• WGS data for ctDNA monitoring for NSCLC in TRACERx

  Ultrasensitive circulating tumour DNA (ctDNA) detection can stratify clinical risk in early-stage non-small cell lung cancer (NSCLC). Here, we applied a whole-genome, tumour-informed approach to study ctDNA in more than 400 NSCLC of the TRACERx project

  Study EGAS50000001187

• intratumor heterogeneity in colorectal adenoma and carcinoma

  To investigate intratumor heterogeneity in precancerous lesions of colorectal cancers (PCRCs), we performed whole-exome sequencing of 53 tumor and 10 matched-normal samples from 10 laterally spreading tumors in the colon and rectum, which were histologically diagnosed as adenoma with/without adenocarcinoma.

  Study JGAS000092

• A living biobank of patient-derived ductal carcinoma in situ Mouse-INtraDuctal xenografts identifies factors associated with risk of invasive progression

  Create a living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts to find factors explaining invasive growth. Samples exist of both primary and pdx samples. Invasive growth was scored in the pdx.

  Study EGAS00001006554

• Identification of point mutations, expression perturbations, and gene fusions in T-cell acute lymphoblastic leukemia by RNA-seq

  RNA-seq is a promising technology to re-sequence protein-coding genes for the identification of single nucleotide variants, while simultaneously obtaining information on structural variations and gene expression perturbations. T-cell acute lymphoblastic leukemia (T-ALL) is caused by a combination of gene fusions leading to the over-expression of transcription factors reinforced by point mutations in oncogenes and tumor suppressor genes. We asked whether RNA-seq is suitable for the detection of driver mutations in these leukemias. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq.

  Study EGAS00001000536