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• Multi-organ landscape of therapy-resistant melanoma

  Metastasis and failure of present-day therapies represent the most common causes of mortality in patients with cutaneous melanoma. To identify the underlying genetic and transcriptomic landscapes, here we analyzed multi-organ metastases and tumor-adjacent tissues from eleven rapid autopsies after treatment with MAPK inhibitor (MAPKi) and/or immune checkpoint blockade (ICB) and death due to acquired resistance. Either treatment elicits shared genetic alterations that suggest immune-evasive, cross-therapy resistance mechanisms. Large, non-clustered deletions, inversions, and inter-chromosomal translocations dominate rearrangements. Using 345 therapy-naïve TCGA melanoma and 131 patient-matched melanoma pre-and-post acquired resistance to only either treatment, we performed cross-cohort analyses to identify MAPKi and ICB as respective contributors to gene amplifications and deletions enriched in autopsy versus therapy-naïve tumors. Private/late mutations and structural variants display shifted mutational and rearrangement signatures, with MAPKi specifically selecting for signatures of defective homologous-recombination, mismatch, and base-excision repair. Transcriptomic signatures and cross-talks with tumor-adjacent macroenvironments nominate organ-specific adaptive pathways. An immune-desert, CD8+-macrophage-biased archetype, T-cell exhaustion, and type-2 immunity characterize the immune contexture. This multi-organ analysis of lethal, therapy-resistant melanoma presents preliminary insights with potential to improve therapeutic strategies.

  Study EGAS00001006644

• Integrated Genomic Analyses of Cutaneous T Cell Lymphomas Reveal the Molecular Bases for Disease Heterogeneity

  Cutaneous T cell lymphomas (CTCLs) are a clinically diverse collection of lymphomas of the skin-homing T cell. In the present study, we performed DNA and RNA sequencing on a cohort of CTCLs with representative samples from varying disease subtypes and stages. We characterized the landscape of putative driver genes, identified genetic relationships between CTCLs across disease stages, and inferred molecular subtypes in patients with stage-matched leukemic disease. Collectively, our findings clarify CTCL genetics and provide novel insights into pathways that drive diverse disease phenotypes. DNA and RNA sequencing was performed on 114 and 96 samples respectively. Tumor samples were obtained from University of Chicago (Chicago, IL), Northwestern University (Chicago, IL) and Yale University (New Haven, CT). 

  Study phs002456

• Development of a fully human glioblastoma-in-brain-spheroid model for accelerated translational research

  In glioblastoma (GBM) the intricate interplay between tumor cells and the surrounding microenvironment plays a crucial role in tumor progression, invasion, and therapeutic resistance. So far, studying these interactions in a controlled and representative model system has been challenging. Here, we report the development of hGliCS, a human glioma-cortical spheroid model that allows the elucidation of the biology of GBM cells and their interactions with a human-specific brain-like microenvironment and neurons. GBM cells efficiently invade the cortical spheroids, forming a well-connected network of communicating cells. The heterogeneous cellular states of the GBM cells within this model closely resembled findings previously observed in glioblastoma patients and in mouse xenografts. We observed a transition from predominantly mesenchymal-like cells to heterotopic states with a high diversity. In contrast to the substantial changes observed in the tumor cell population, the impact of the GBM cells on the neurons was minimal. We further demonstrate the suitability of hGliCS to test compounds targeting tumor-specific neurobiological features.

  Study EGAS50000000757

• SG10K_Pilot - Large-scale whole-genome sequencing of three diverse Asian populations in Singapore

  Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions/deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore, and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ~24,800 years ago, and experienced significant admixture with East Asians ~1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, among which 14 harbored robust associations with complex traits and diseases. Finally, we showed that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions.

  Study EGAS00001003875

• single nuclei RNASeq of 5 regions of the human prenatal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Study EGAS00001006537

• Multi-region RNA-Seq data of 10 neuroblastoma cases

  To investigate intratumour heterogeneity and to better understand tumour evolution in neuroblastoma, we have performed a multi-region RNA sequencing on a total of 51 spatially separated tumor samples from 9 primary neuroblastomas (2 low-risk, 1 intermediate-risk and 6 high-risk) and 1 relapsed neuroblastoma. We also assessed the impact of chemotherapy on the clonal expansion by sequencing tumour regions from one medium risk and one high-risk tumour for which we had matched samples obtained at diagnosis and after chemotherapy.

  Dataset EGAD00001008133

• Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  While endometrioid and mucinous ovarian cancers represent nearly a quarter of ovarian cancers, their molecular characteristics and pathologic origins are poorly understood. To characterize the genomic and epigenomic alterations of these ovarian cancer subtypes and evaluate links to morphologically similar tumors from other sites, we performed sequence, copy number, mutation signature, rearrangement, and methylation analyses from tumor samples and matched normal tissues of 133 patients. These analyses included patients with ovarian endometrioid (n=44), ovarian mucinous (n=43), uterine endometrial (n=15), and gastrointestinal mucinous cancers (n=31). In addition to identifying genes previously known to be involved in these tumors, we identified alterations in RAD51C, NOTCH4, SMARCA1/4 and JAK1 in ovarian endometrioid, ESR1 in uterine endometrioid, and SMARCA4 in ovarian mucinous cancers. Whole genome sequencing revealed rearrangements involving PTEN, NF1, and NF2 in ovarian endometrioid tumors, and NF1 and MED1 in ovarian mucinous cancers. The number of alterations and affected genes in ovarian and uterine endometrioid cancers were similar as were genome-wide methylation profiles, suggesting that these tumors may have a similar tissue of origin. By contrast, methylation patterns in ovarian mucinous cancers were more similar to other gastrointestinal mucinous cancers, including mucinous cancers of the stomach, colon, and pancreas. These analyses provide insights into the genomic landscapes and origins of mucinous and endometrioid ovarian carcinomas, providing new avenues for early clinical intervention and management of patients with these cancers.

  Study EGAS50000000523

• Whole-genome sequencing analysis for understanding of the stepwise progression of lung adenocarcinoma

  In this study, we performed long and short read whole-genome sequencing analysis of lung adenocarcinoma from early to advanced stages to identify molecular events associated with the stepwise progression of lung adenocarcinoma. We particularly focused on very early stage of lung adenocarcinoma, such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA). In addition to the whole-genome sequencing analysis, we conducted transcriptome and epigenome analysis, multiplex fluorescence immunostaining. This study would enable us to understand important molecular events of pathogenesis in detail during lung adenocarcinoma progression.

  Study JGAS000570

• Homologous recombination repair status in metastatic prostate cancer by next-generation sequencing and functional tissue-based immunofluorescence assays

  - WES files from primary or metastatic prostate cancer biopsies, from patients with metastatic prostate cancer. - This dataset includes those cases profiled by WES and included in the manuscript Homologous recombination repair status in metastatic prostate cancer by next-generation sequencing and functional tissue-based immunofluorescence assays, Arce-Gallego et al, Cell Rep Med 2024 - The dataset includes WES for 80 tumor biopsies from 65 different patients, including paired tumor/normal samples.

  Dataset EGAD50000001018

• Deep WGS of matched tumor-normal pairs for HGSOC copy-number signatures study

  This dataset includes 111 bam files from WGS sequence data aligned to human genome assembly GRCh37 (hg19) from 56 tumour and matched normal samples. Libraries were constructed with ~350-bp insert length using the TruSeq Nano DNA Library prep kit (Illumina) and sequenced on an Illumina HiSeq X Ten System in paired-end 150-bp reads mode. The average depth was 60× (range 40-101×) in tumours and 40× (range 24-73×) in matched blood samples.

  Dataset EGAD00001004189