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• Biopsy-Derived Organoids in Personalised Early Breast Cancer Care: Challenges of Tumour Purity and Normal Cell Overgrowth Cap Their Practical Utility

  The ability to establish organoids composed exclusively of tumour rather than healthy cells is essential for their implementation into clinical practice. Organoids have in recent years emerged as a powerful tool to expand patient material in culture and generate modifiable 3D models derived from humans or animal models. For translational research, they enable the creation of model systems for an ever-increasing number of cell types and diseases. And in personalised medicine, they potentially allow for functional drug testing with high predictive power in certain settings. We found that using biopsy material from untreated, early-stage primary breast cancer patients poses significant challenges for consistently culturing tumour cells as organoids. Specifically, we observed frequent outgrowth of genetically normal, non-cancerous epithelial cells. We analysed >100 biopsy samples from early-stage breast cancer and present our large collection of >70 organoid lines. We also show methods of assessing successful tumour cell culture in a time and cost-efficient manner, proving a high rate (>85%) of normal cell overgrowth in early-stage breast cancer organoids. Finally, we show a number of successful attempts to culture cancer organoids from mastectomy-derived tissue of advanced, metastatic breast cancer. We conclude that the usefulness of organoids from early breast cancer for translational research and personalised medicine, especially guidance of adjuvant or post-surgical maintenance therapy, is strongly limited by the low success rate of culturing cancerous cells under organoid conditions.

  Study EGAS50000000605

• Geriatric Oncology Database of genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients to establish truly effective treatment strategy

  Owing to the advent of super-aged society, cancer mortality in Japan is forecasted to become an all-time high. The management of elderly patients with cancer is a serious health issue and the need for specific care guidelines for this population is critical in Japan. The significant individual differences in comorbidity, physical and mental functioning, and social problems among aging individuals are obstacles to the progress. The response to cancer treatment varies significantly among patients, even in the same stage of the same type of cancer. Older aged patients are still less likely to be offered participation in clinical trials, thus the number of clinical evidences is limited. The molecular mechanisms regulating the physiological process of ageing and senescence, and cancer are far from understood. To establish a truly effective treatment algorithm, we attempted to develop a geriatric oncology database for genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients in this retrospective study. The genomic analysis was performed in 62, 106, and 173 cases, respectively for gastric, colon and lung cancers. The clinical data and survey results on psychosocial and physical conditions were collected from 166, 313, and 344 patients respectively for gastric, colon and lung cancers, and also collected from 357, 49, and 300 benign cases respectively for cardiovascular disorder, respiratory dysfunction, diabetes and nephropathy as the analysis control.

  Study JGAS000061

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• cfDNA methylation dataset for colon cancer

  Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

  Dataset EGAD50000000075

• PASCAL-MID Data Access Committee

  DAC for the center of Personalized Approach to Genome Editing of Stem Cells for Autotransplantation of Monogenic Immunodeficiencies (PASCAL-MID) at Aarhus University and Aarhus University Hospital

  Dac EGAC50000000680

• Pancreatic Cancer NGS WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

  Study EGAS50000001078

• V4_Colorectal_panel_test

  Targeted gene screen of cell line tumours for testing the new V4 Colorectal gene panel.

  Study EGAS00001001807

• Dataset for B-ALL scRNA-seq

  10x Genomics 5' library scRNA-seq data for 85 B-ALL patients with different subtypes

  Dataset EGAD00001011327

• WGBS data for Glioblastoma (EGAS00001003953, H016)

  Whole Genome Bisulfite data for human glioblastoma patients, EGAS00001003953. 68 human samples

  Dataset EGAD00001006546