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• Genomic features of Helicobacter pylori-na��ve diffuse-type gastric cancer.

  Helicobacter pylori (HP) is a major etiologic driver of diffuse-type gastric cancer (DGC). However, improvements in hygiene have led to an increase in the prevalence of HP-na��ve DGC; that is, DGC that occurs independent of HP. Although multiple genomic cohort studies for gastric cancer have been conducted, including studies for DGC, distinctive genomic differences between HP-exposed and HP-na��ve DGC remain largely unknown. Here, we employed exome and RNA sequencing with immunohistochemical analyses to perform binary comparisons between 36 HP-exposed and 27 HP-na��ve DGCs from sporadic, early-stage, and intramucosal or submucosal tumor samples. Among the samples, 33 HP-exposed and 17 HP-na��ve samples had been preserved as fresh-frozen samples. HP infection status was determined using stringent criteria. HP-exposed DGCs exhibited an increased single nucleotide variant burden (HP- exposed DGCs; 1.97 [0.48���7.19] and HP-na��ve DGCs; 1.09 [0.38���3.68] per megabase; p=0.0003) and a higher prevalence of chromosome arm-level aneuploidies (p<0.0001). CDH1 was mutated at similar frequencies in both groups, whereas RHOA���ARHGAP pathway misregulation was exclusive to HP-exposed DGCs (p=0.0167). HP-exposed DGCs showed gains in chromosome arms 8p/8q (p<0.0001), 7p (p=0.0035) and 7q (p=0.0354), and losses in 16q (p=0.0167). Immunohistochemical analyses revealed a higher expression of intestinal markers such as CD10 (p<0.0001) and CDX2 (p=0.0002) and a lower expression of the gastric marker, MUC5AC (p=0.0305) among HP-exposed DGCs. HP-na��ve DGCs, on the other hand, had a purely gastric marker phenotype. This work reveals that HP-na��ve and HP-exposed DGCs develop along different molecular pathways, which provide a basis for early detection strategies in high incidence settings.

  Study JGAS000575

• Local In Time Statistics for processual research

  Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

  Study EGAS00001002520

• RNA sequencing of pretreatment, on-treatment and posttreatment gastric and gastroesophageal junction tumors treated with neoadjuvant anti-PD-L1 plus chemotherapy

  This set contains a total of 78 files cram files with RNA sequencing data from 20 patients included in the PANDA study treated with 1 cycle of monotherapy atezolizumab and 4 cycles atezolizumab plus chemotherapy (docetaxel, oxaliplatin and capecitabine). RNA was isolated from fresh frozen material and sequenced at 4 timepoints baseline, after monotherapy atezolizumab, after combination atezolizumab plus chemotherapy and at resection (due to 2 missing samples, there is a total of 78 samples).

  Dataset EGAD50000000241

• Proteogenomic Landscape of Squamous Cell Lung Cancer

  To provide a detailed analysis on how genomic and transcriptomic alterations related to proteome level changes in squamous cell lung cancer (SCC), we performed an integrated analysis incorporating DNA copy number, somatic mutations, expression RNA-sequencing, and expression proteomics in 108 SCC nested within clinical outcome, tumor pathology, and other clinically relevant data.

  Study phs001781

• BRCA Mutation Status Shapes the Microenvironment of Pancreatic Adenocarcinoma

  This study was established in order to address how the stromal landscape is influenced by BRCA-mutated and BRCA Wild-type (WT) pancreatic ductal adenocarcinoma (PDAC). A primary cohort of 12 PDAC patients (7 BRCA-WT and 5 germline BRCA-mut) was analyzed by laser-capture microdissection, RNA-sequencing and multiplexed immunofluorescence.

  Study phs002994

• Transcriptomic Profiles of Neoantigen-Reactive T Cells in Human Gastrointestinal Cancers

  This study explores the transcriptomic profiles of neoantigen-reactive tumor-infiltrating lymphocytes (TILs) from human bile duct and pancreatic cancer. The submitted data are bulk tumor RNA-Seq, tumor and germline whole-exome sequencing from 10 patients, and single cell RNA-Seq data from TIL of 5 of these patients.

  Study phs002765

• Characterization of Immune-Related Gene Expression in Lung Cancer

  We performed a comprehensive analysis of inter- and intratumor heterogeneity of immune gene expression in 160 lung cancer patients from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. The transcriptome was profiled with RNA sequencing in 269 tumor samples and 110 normal tissue samples from 160 subjects.

  Study phs002346

• Autopsy-Confirmed Parkinson Disease GWAS Consortium (APDGC)

  The APDGC was formed to conduct a genome-wide association study in individuals with neuropathologically confirmed Parkinson Disease (PD) and neuropathologically normal controls. The rationale for the study is that including only cases and controls with neuropathologically confirmed disease status will reduce diagnostic misclassification and increase power to detect novel genetic associations.

  Study phs000394

• B Cell Receptor Study From Early Breast Cancer Tumour Samples

  B and T cells are key components of the adaptive immune system and play an important role in anti-cancer immunity. In this study, we performed an integrative analysis of the B cell and T cell repertoires across 25 serial breast tumour biopsies from 10 patients during neoadjuvant therapy.

  Study EGAS50000000241

• WGS of CTCs enriched using high-throughout microfluidic device from entire cancer patient leukopak

  Single-cell low-pass WGS analysis (illumina platform, PE150, 1-2x coverage) was performed on CTCs enriched using high-throughout microfluidic device from entire leukopak from patients with metastatic prostate cancer (GU-1 and GU-2) and metastatic hepatocellular carcinoma (HCC-1 and HCC-2).

  Study EGAS50000000723