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• GoNL aligned sequence data in BAM format.

  We mapped the data to the UCSC human reference genome build 37 using BWA 0.5.9-r16. We first mapped each read pair separately using bwa aln. Then we used bwa sampe to map the paired reads together to a BAM9 file. The BAM file was then sorted by genomic position and indexed using PicardTools-1.32 SortSam. To prevent PCR artifacts from influencing the downstream analysis of our data, we used Picard to mark the duplicate reads, which were ignored in downstream analysis. We used GATK IndelRealigner on our data around known indels (from 1KG Pilot). The IndelRealigner creates all possible read alignments using the source and computes the likelihood of the data containing the indel based on the read pileup. Whenever the maximum likelihood contains an indel, the reads are realigned accordingly. Each base is associated with a phred-scaled base quality score. Calibration of Phred scores is crucial as they are used in some of the downstream analysis models. We used GATK to recalibrate the base qualities with respect to (i) the base cycle, (ii) original quality score, and (iii) dinucleotide context. To minimize issues stemming from mapping problems around indels, we decided to undergo a second round of indel realignment using the GATK IndelRealigner by family rather than by individual. For this second round, we considered two sources of possible indels: 1KG Phase 1 indels and indels aligned by BWA in the GoNL data.

  Dataset EGAD00001001038

• Bulk RNAseq FASTQ files of three PDAC organoid lines treated with LGK974 or DMSO for 24h

  This dataset contains raw FASTQ files from bulk RNA sequencing of three patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid lines (P28, P40, P47). Each organoid line was treated with either the WNT secretion inhibitor LGK974 or DMSO for 24 hours, with three biological replicates per treatment condition. RNA was extracted using the Qiagen QiaSymphony SP system, and libraries were prepared with the Illumina Truseq stranded polyA kit. Sequencing was performed on an Illumina NextSeq2000 platform using single-end 50bp reads. Quality control was conducted with FastQC, and reads were trimmed with TrimGalore as appropriate. Data are controlled-access and intended for transcriptomic analysis of WNT pathway perturbation in PDAC organoid models.

  Dataset EGAD50000002219

• CAGEKID: Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001000083

• CAGEKID: Cancer Genomics of the Kidney - Targeted Sequencing

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001007004

• Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

  We performed scRNA-seq of patient-derived glioblastoma cells alone or after co-culture with human iPSC-derived cerebral organoid cells. Transcriptional changes implicated in the invasion process that are coherent across patient samples indicate that GBM cells reactively upregulate genes required for their dispersion. Potential interactions between GBM and organoid cells identified by an in silico receptor-ligand pairing screen suggest functional therapeutic targets.

  Study EGAS00001003852

• SGCC TMA cohort

  This Tissue Microarray (TMA) GeoMx Digital Spatial Profiler (DSP) dataset was a part of the validation cohort in the study. Tumor tissue blocks were first annotated as tumor core or tumor edge by pathologists, then Regions of Interest (ROIs) were selected on various blocks. The data is in FASTQ format. GeoMx DSP data from 840 ROIs (after QC) from 86 GCs were included in the datasets.

  Dataset EGAD50000000903

• Extreme phenotypes define epigenetic and metabolic signatures in cardiovascular diseases

  Improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis are ongoing healthcare challenges. Using plasma biomarkers analysis coupled with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (obese and lipodystrophy) and comparing these to lean individuals and blood donors, the present study identifies the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells and shows that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, six months after bariatric surgery shows the loss of the patterns of abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurs via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Taken together, by integrating across data layers, the observed molecular and metabolic differences form a disease signature that is able to discriminate, amongst the blood donors, those individuals with a higher likelihood of having cardiometabolic syndrome, even when not presenting with the classic features.

  Dataset EGAD00001005197

• Whole-exome and targeted sequencing of pediatric hyperdiploid B-cell precursor acute lymphoblastic leukemia

  High hyperdiploidy defines the largest genetic entity of childhood acute lymphoblastic leukemia (ALL). Despite its relatively low recurrence risk, this subgroup generates a high proportion of relapses. The cause and origin of these relapses remains obscure. We therefore explored the mutational landscape in high hyperdiploid (HD) ALL with whole-exome (n=19) and subsequent targeted deep sequencing of 60 genes in 100 relapsing and 51 non-relapsing cases. We identified multiple clones at diagnosis that were primarily defined by a variety of mutations in receptor tyrosine kinase (RTK)/Ras pathway and chromatin-modifying genes. The relapse clones consisted of reappearing as well as new mutations, and overall contained more mutations. Although RTK/Ras pathway mutations were similarly frequent between diagnosis and relapse, both intergenic and intragenic heterogeneity was essentially lost at relapse. CREBBP mutations, however, increased from initially 18-30% at relapse, then commonly co-occurred with KRAS mutations (P<0.001) and these relapses appeared primarily early (P=0.012). Our results confirm the exceptional susceptibility of HD ALL to RTK/Ras pathway and CREBBP mutations, but, more importantly, suggest that mutant KRAS and CREBBP might cooperate and equip cells with the necessary capacity to evolve into a relapse-generating clone.

  Study EGAS00001001113

• Molecular Correlatives from SU2C-SARC032

  SU2C-SARC032 was a phase II international, randomized trial for patients with localized, high-risk undifferentiated pleomorphic sarcoma or dedifferentiated or pleomorphic liposarcoma of the extremity and limb girdle. On the trial, the addition of perioperative pembrolizumab to preoperative radiotherapy and surgery improved disease-free survival compared to preoperative radiotherapy and surgery alone. Bulk RNA-sequencing was performed on pre-treatment and surgically resected tumor specimens.

  Study phs003921

• Ancestry and somatic profile predict acral melanoma origin and prognosis – RNA

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015756