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• ATAC-seq of metastatic prostate tumors

  This dataset includes Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data, in FASTQ format, from 70 metastatic castration-resistant prostate cancer tumor samples from the SU2C/PCF West Coast Dream Team (WCDT) project. The sequencing data is paired-end, 150 bp sequencing data from an Illumina NovaSeq 6000 machine. ATAC-seq libraries were prepared following the protocol described in Buenrostro et al. Nature Methods. 2013 (PMID: 24097267) and Corces et al. Nature Methods. 2017 (PMID: 28846090).

  Dataset EGAD00001009654

• Whole genome sequencing of chondrosarcoma

  Massive parallel sequencing of 10 chondrosarcoma genomes was conducted to identify somatic mutations, structural alterations including fusion genes and mutation signatures that may help to comprehensively characterize the molecular features.

  Study EGAS00001000505

• Sequencing_melanoma_germlines

  In this project we performed targeted sequencing of around 50 candidate melanoma genes in the germline of melanoma patients and matched controls. Our aim was to identify variants that contribute to melanoma susceptibility.

  Study EGAS00001002081

• Whole Exome Sequencing of 5 FFPE prostate samples (normal and tumour pairs) to identify mutations

  Whole Exome Sequencing was performed on radical prostatectomy formalin-fixed paraffin-embedded sample pairs (n = 6). Library prep was done by exon capture using the Illumina Truseq Exome kit and sequenced as 75bp paired end on Illumina NextSeq 500. Sequences were aligned to the human genome (hg38) using BWA.

  Dataset EGAD00001006107

• Partner independent fusion gene detection by multiplexed CRISPR Cas9 enrichment and long read Nanopore sequencing (FUDGE)

  Targeted long-read nanopore sequencing. Abstract: Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment. Fusion gene partner choice and breakpoint-position promiscuity restricts diagnostic detection, even for known and recurrent configurations. To accurately and impartially identify fusions, we developed FUDGE: FUsion Detection from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for fusion gene driver enrichment - without prior knowledge of fusion partner or breakpoint-location – to long-read Nanopore sequencing with the bioinformatics pipeline NanoFG. FUDGE has flexible target-loci choices and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in one sequencing run. We observe on-average 665 fold breakpoint-site enrichment and identify nucleotide resolution fusion breakpoints - within two days. The assay identifies cancer cell line and tumor sample fusions irrespective of partner gene or breakpoint-position. FUDGE is a rapid and versatile fusion detection assay, providing unparalleled opportunity for diagnostic pan-cancer fusion detection.

  Dataset EGAD00001006111

• Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma

  We examined pre-treatment tumors from participants of the IMmotion150 trial. Biomarker analyses indicate that high angiogenesis gene expression was associated with improved PFS within the sunitinib arm, and high T-effector/IFNγ response (Teff) gene expression with longer PFS in atezolizumab + bevacizumab vs sunitinib patients. In high Teff tumors, concomitant high myeloid inflammation was associated with worse PFS in the atezolizumab monotherapy arm; adding bevacizumab to atezolizumab in this subgroup improved PFS vs atezolizumab. Molecular profiles suggest that prediction of outcomes with VEGF inhibitors and immunotherapy may be possible in mRCC, and bevacizumab may overcome myeloid inflammation-associated atezolizumab resistance.

  Study EGAS00001002928

• Precise reconstruction of the tumor microenvironment using bulk RNA-seq and a unique machine learning-based algorithm trained on artificial transcriptomes

  Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. Here, we present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of > 9,400 tissue and blood sorted cell RNA profiles to accurately reconstruct the tumor microenvironment (TME). Bioinformatic correction for technical and biological variability, aberrant cancer cell expression inclusion, and the accurate quantification and normalization of transcript expression increased the stability and robustness of Kassandra. Performance was validated on over 4,000 H&E tissue slides and more than 1,000 normal and tumor tissues by comparison with cytometric, immunohistochemical or single-cell RNA-seq measurements. Kassandra accurately deconvolved stromal and immune elements of blood and tumors, revealing the role of the TME in tumor pathogenesis. Digital TME reconstruction revealed that the presence of PD1-positive CD8+ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

  Dataset EGAD00001008776

• Viral integration analysis of hepatocellular carcinoma using virus capture sequence.

  Hepatitis B viral (HBV) DNA is frequently integrated into the genome of hepatocellular carcinoma (HCC) in patients with chronic HBV infection (chronic HBV, hereafter), whereas it is yet to be clarified in patients after HBV disappearance (prior HBV, hereafter). This study aimed to identify viral integration such as HBV and adeno-associated virus type 2 (AAV2) into the HCC genome as oncogenic event.

  Study JGAS000194

• Bulk RNA-seq (FASTQ) – melanoma samples

  This dataset comprises raw FASTQ files from bulk RNA sequencing of metastatic melanoma lymph node samples collected from patients with differential responses to immune checkpoint inhibitor therapy. RNA was extracted from tumour tissue, enriched for polyadenylated transcripts, and libraries were prepared using standard Illumina protocols. Sequencing was performed on an Illumina platform to generate high-quality paired-end reads. The dataset includes multiple patient samples with associated clinical annotations, enabling analysis of tumour-intrinsic transcriptional programs linked to immunotherapy response and resistance.

  Dataset EGAD50000002475

• Genomic profiling of BRCA- mutant breast cancer tumors

  This data set contains whole exome sequencing (WXS) and RNA-Seq on germline BRCA- mutant tumors from 18 patients. BAM files are provided for WXS on tumor and germline samples. FASTQ files are provided for the RNA-Seq samples. Sequencing was done on an Illumina Hi-Seq 2500.

  Dataset EGAD00001008276