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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

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Dataset EGAD00001002738

• Transcriptome Sequencing PPGL

  RNA library preparation of samples with RNA Integrity Number (RIN) > 5.5 (median 7.1; range 5.6-8.9) was performed as described in the TruSeq Stranded mRNA Library Prep Kit (Illumina, RS-122-2101). Briefly, 0.7-1 µg total RNA PolyA+ fraction was purified and randomly fragmented, converted to double stranded cDNA and processed through subsequent enzymatic treatments of end-repair, dA-tailing, and ligation to adapters. Adapter-ligated library was completed by PCR with Illumina PE primers. The resulting purified cDNA library was applied to an Illumina flow cell for cluster generation and sequenced on an Illumina HiSeq2500 on a 51bp single-read format following manufacturer's protocols. cDNA libraries from FFPE tumors and low integrity RNA’s (RIN<5.5) from FF tumors (median 2.4; range 1-5.5) but % of fragments > 200 nucleotides higher than 20% (median 57.5; range 20-96) were prepared using QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015) with a UMI Second Strand Synthesis Module for QuantSeq FWD (Lexogen, 081), vendor’s protocol for low input/ low quality/ FFPE RNA using 200-500 ng of total RNA, according to availability, was used as starting material. PCR Add-on Kit for Illumina (Lexogen, 020) was used to adjust the library amplification number of cycles. Libraries were applied to an Illumina flow cell for cluster generation and sequenced on NovaSeq6000. Image analysis, per-cycle basecalling and quality score assignment was performed with Illumina Real Time Analysis software. Demultiplexing of BCL files to FASTQ format was performed with the bcl2fastq Software (Illumina).

  Study EGAS00001006044

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

  Study EGAS50000001554

• Understanding_Society_GWAS

  The UK Household Longitudinal Study (Understanding Society https://www.understandingsociety.ac.uk/) aims to create and enhance a resource for a wide range of scientists, both social and biological, by combining the collection of biomarkers and psychosocial information with high quality longitudinal social and economic data about individuals and families. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001232

• Immuno-genomic landscape of osteosarcoma

  Osteosarcoma is an orphan disease affecting children and young adults that has seen little to no progress in survival outcomes for >30 years. Despite having heavily rearranged genomes, to date, clinical trials with immunotherapy have shown no benefit for patients with osteosarcoma. In this study, we conducted the first multi-platform immune profiling (whole genome, transcriptome, T-cell receptor sequencing, immunohistochemistry and reverse phase protein array) on every available pediatric and adult osteosarcoma patients from our institution (N = 48) with the goal of describing immune features that may contribute to immunotherapy resistance.

  Study EGAS00001004197

• Analysis of copy number variation landscape of glioma by shallow coverage whole genome sequencing

  We reported shallow coverage whole genome sequencing (WGS) is an economic method for identification of whole genome somatic copy number variation (SCNV). Combining with a Taqman low density array (TLDA) designed for molecular subtyping of glioma, it enabled classification of glioma into biological entities with different cellular origin and genomic alterations. Further, we also showed shallow-coverage WGS enabled systematic identification of clonal and subclonal SCNV in glioma genomes and the burden and pattern of SCNV can serve as an objective marker of tumor progression and predict risk and relapse.

  Study EGAS00001003690

• Transcriptional_analysis_of_cells_from_lungs

  To capture the full heterogeneity of the cellular types and states during HSPCs differentiation, haematopoietic progenitors will be obtained through column-enrichment of cells expressing CD34, a pan-progenitor marker for HSPCs. The samples from tumour and non-tumour lung tissue from different patients will be processed using the 10x Genomics platform. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002649

• Immuno-genomic landscape of osteosarcoma

  Osteosarcoma is an orphan disease affecting children and young adults that has seen little to no progress in survival outcomes for >30 years. Despite having heavily rearranged genomes, to date, clinical trials with immunotherapy have shown no benefit for patients with osteosarcoma. In this study, we conducted the first multi-platform immune profiling (whole genome, transcriptome, T-cell receptor sequencing, immunohistochemistry and reverse phase protein array) on every available pediatric and adult osteosarcoma patients from our institution (N = 48) with the goal of describing immune features that may contribute to immunotherapy resistance.

  Study EGAS00001003887

• Stratton__WGS___Identification_of_Early_Life_Exposures_in_Paediatric_Colonic_Crypts_of_Healthy_Individuals

  The Stratton team uses DNA sequencing for somatic mutations to advance understanding of the causes of cancer. In particular, the investigation of “mutational signatures”, which report the mutational processes operative over the lifetime of each individual, to understand whether they are generated by endogenous or exogenous exposures and the extent to which these vary between human populations. Our work brings together global cancer epidemiology and genomics and is particularly characterised by large-scale multinational studies. Whole genome sequencing of colon crypts from healthy paediatric individuals for identification of early life exposure to carcinogens.

  Study EGAS00001007921