7073 results for "canc*"

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• Single-cell atlas of penile cancer reveals TP53 mutations as driver for an aggressive phenotype, irrespective of HPV status, and provides clues for treatment personalization

  Our aim was to identify molecular differences in the microenvironment of penile squamous cell carcinoma (PSCC) stratified by TP53 loss-of-function (TP53LOF) mutations and HPV-status. Hence, we present a first single-cell transcriptomic atlas of PSCC. Stratification based on TP53 and HPV-status uncovered differences in CSS and underlying molecular pathways. Our data indicate that TP53LOF tumors are characterized by worse biological behavior regardless of HPV-status. These findings and further research are essential for trial design in PSCC, allowing us to move away from the current one-size-fits-all approach.

  Study EGAS50000000217

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 10)

  Whole genome sequencing data of 56 high-grade serous carcinoma (HGSC) patients (208 samples) sequenced with Novoseq 6000

  Dataset EGAD50000000275

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 11)

  The dataset contains whole genome sequencing data of 23 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 89 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000313

• Sensitive circulating tumor DNA based residual disease detection in epithelial ovarian cancer

  In this study we implemented a circulating tumor DNA (ctDNA) based blood test for more accurate post-operative surveillance of this disease. We analyzed 264 plasma samples collected between June 2016 and September 2021 from 63 epithelial ovarian cancer patients using tumor-guided plasma cell-free DNA analysis to detect residual disease after treatment. Assay specificity was verified using cross-patient analysis of 1195 control samples.

  Study EGAS50000000245

• Perturb-seq on CRC

  Systematic, genome-wide Investigation of enhancer regions in colorectal cancer. We used scRNA-seq with CRISPRi/dCas9 inhibition of 12,117 regions.

  Study EGAS50000000256

• Perturb-seq dataset

  We performed a systematic, genome-wide investigation of enhancer regions in colorectal cancer (CRC). We identified 12,117 putative enhancer regions using H3K27ac and H3Kme1 ChIP-seq and ATAC-seq. We performed scRNA-seq in HT29 and SW480 (MSS CRC cell lines) using the Parse Biosciences WT-mega kit with CRISPRi/dCas9 inhibition of these regions (Perturb-seq). The Parse split-pipe pipeline was used to demultiplex the raw fastq files into the processed files (mtx files for genes and gRNA) for each cell line.

  Dataset EGAD50000000375

• Cancer Genomics, ICR, cell line data

  DAC for cell line (non patient) data from the Cancer Genomics group, Division of Genetics and Epidemiology at the Institute of Cancer Research, Sutton, UK.

  Dac EGAC50000000023

• Norwegian Institute of Public Health – Cancer Registry of Norway Data Access Policy for JanusRNA transcriptomics datasets archived in Federated EGA Norway

  JanusRNA transcriptomics datasets are generated from biobank samples from the Janus Serum bank of the Cancer Registry of Norway/National Institute of Public Health. This Data Access Committee has been appointed to govern controlled access to these datasets archived in Federated EGA Norway.

  Dac EGAC50000000192

• DAC for Castleman. National Cancer Centre Singapore.

  Dac EGAC00001003328

• RNA sequencing of Non-Small Cell Lung Cancer and adjacent normal tissue

  RNA sequencing was performed on 108 NSCLC tumor samples and their paired adjacent normal tissues (n=21) to identify associations with clinical and immune characteristics.

  Study EGAS50000000246

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 12)

  The dataset contains whole genome sequencing data of 17 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 46 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000441

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 13)

  The dataset contains whole genome sequencing data of 32 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 82 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000442

• Single Cell RNAseq of PBMC from renal cancer patients

  Dac EGAC00001001605

• UCSF prostate cancer genomics data access committee

  Dac EGAC00001002685

• Targeted re-sequencing of multi-region sampled tumors in PDAC

  Multi-region tumor samples were cut from frozen sections or FFPEs and reviewed from microdissection and H&E staining in order to select ones with high cellularity. DNA extraction was done using DNeasy Blood & Tissue Kits for frozen samples following the manufacturer’s guideline. Extracted DNAs were processed on an Illumina HiSeq 2500 in a paired end mode (100x100) using a custom targeted panel based on the list of all unique somatic mutations from the original WES data by the Integrated Genomics Operation (IGO) at Memorial Sloan Kettering Cancer Center (New York, NY).

  Study EGAS50000000239

• B Cell Receptor Study From Early Breast Cancer Tumour Samples

  B and T cells are key components of the adaptive immune system and play an important role in anti-cancer immunity. In this study, we performed an integrative analysis of the B cell and T cell repertoires across 25 serial breast tumour biopsies from 10 patients during neoadjuvant therapy.

  Study EGAS50000000241

• Non-coding mutations drive persistence of a founder pre-leukemic clone which initiates late relapse in T-ALL

  T-ALL relapse usually occurs early but can occur much later, which has been suggested to represent a de novo leukemia. However, we conclusively demonstrate late relapse can evolve from a pre-leukemic subclone harbouring a non-coding mutation that evades initial chemotherapy.

  Study EGAS50000000129

• Whole-genome sequenicng of 168 paired Gastric Cancer patients (1st part) DAC

  Dac EGAC00001001145

• Whole-genome sequenicng of 168 paired Gastric Cancer patients (2nd part) DAC

  Dac EGAC00001002854

• Whole-genome sequenicng of 168 paired Gastric Cancer patients (3rd part) DAC

  Dac EGAC00001003308

• Single cell transcriptomic profiles of advanced melanoma patients treated with checkpoint inhibitor immunotherapy

  Little is known about the resistant clones within the tumour ecosystem treated with immunotherapy. This work provides a comprehensive and integrative analysis of each individual non-responding melanoma patients, including clinical features integrated with single cell analysis, which is critical to understand features of resistance in order to improve cancer patients’ outcomes.

  Study EGAS50000000339

• Clones derived from early passage tumoroids of colorectal cancer

  We obtained different clones from early passage CRC tumoroids to study mutational signatures specific for truncal or private somatic alterations. These whole genome sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Dataset EGAD50000000152

• HiDEF-seq single-molecule sequencing of single-strand mismatches and damage

  Our study sought to resolve, with single-molecule fidelity, the mismatches and damage events that precede DNA mutations. Using a novel single-molecule, long-read sequencing method (HiDEF-seq) we detect base substitutions when present in either one or both DNA strands. We also detect cytosine deamination, a common type of DNA damage, with single-molecule fidelity. This study profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes. These samples revealed single-strand mismatch and damage signatures. Since double-strand DNA mutations are only the endpoint of the mutation process, our approach enables new studies of how mutations arise in a variety of contexts, especially in cancer and aging.

  Dataset EGAD50000000460

• Single-Cell RNA-seq of Primary High Grade Serous Carcinoma

  Single-cell RNA Sequencing of CD45- cancer cells.

  Study EGAS50000000068

• Lipomatous tumors with 12q amplification

  The project concerns whole genome sequencing (short-read and long-read) and RNA-sequencing of lipomatous tumors with 12q-amplification. A subset of lipomatous tumors is driven by amplification of genes mapping to chromosome arm 12q, including the MDM2 gene. The goals of the study were to compare expression levels of genes mapping to 12q in tumors with amplification in rod-shaped or circularized chromosomes as well as to assess and compare the structural variants in those tumors. In total, 20 samples were analyzed, and the data were correlated with genomic data on bulk and single cell DNA from the same tumors. The fastq files from the tumors were uploaded to EGA.

  Study EGAS50000000062

• RNAseq from 6 organotypic co-cultures (OC cells bulk/OCSC with or without TME)

  The dataset contains samples of 6 organotypic co-cultures, assembled with patient-derived material from ovarian cancer (OC) patients. Tumor cells, both as bulk and as cancer stem cells-enriched (OCSC) populations, are cultured or not with in vitro peritoneal TME (for details see Battistini C et al, Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness, CDDis 2024). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD50000000523

• Neoadjuvant atezolizumab plus chemotherapy in gastric and gastroesophageal junction adenocarcinoma: the phase 2 PANDA trial

  Gastric and gastroesophageal junction (G/GEJ) cancers carry a poor prognosis, and despite recent advancements most patients die of their disease. While immune checkpoint blockade has become part of the standard of care for patients with metastatic G/GEJ cancers, its efficacy and impact on the tumor microenvironment in the early disease setting remain largely unknown. We hypothesized a higher efficacy of neoadjuvant immunotherapy plus chemotherapy in patients with non-metastatic G/GEJ cancer. In the phase 2 PANDA trial, patients with previously untreated resectable G/GEJ tumors (n=21) received neoadjuvant treatment with one cycle of atezolizumab monotherapy followed by 4 cycles of atezolizumab plus docetaxel, oxaliplatin and capecitabine. Treatment was well-tolerated, and all patients underwent resection without treatment-related delays, meeting the primary endpoint of safety and feasibility. Tissue was obtained at multiple time points, allowing analysis of the effects of single-agent PD-L1 blockade and the subsequent combination with chemotherapy on the tumor microenvironment. A total of 21 patients were included, of whom 20 patients underwent surgery and were evaluable for the secondary pathologic response and survival endpoints, while 19 were evaluable for exploratory translational analyses. A major pathologic response (MPR, ≤10% residual viable tumor) was observed in 14/20 (70%; 95% CI 46-88%) patients, including 9 (45%; 95% CI 23-68%) pathologic complete responses. At a median follow-up of 47 months, 13/14 responders were alive and disease-free, while 5/6 nonresponders had died due to disease recurrence. Notably, baseline PD-1+CD8+ T cell infiltration was significantly higher in responders than in nonresponders, and comparison of the tumor microenvironment alterations following anti-PD-L1 monotherapy versus the subsequent combination with chemotherapy revealed that increased immune activity was achieved upon single-agent PD-1/L1 axis blockade. Based on these data, anti-PD-L1 plus chemotherapy warrants further exploration in patients with non-metastatic G/GEJ cancer, and these results call for validation in a larger cohort.

  Study EGAS50000000168

• Microbiome confounders and quantitative profiling challenge established microbial targets in colorectal cancer developmental stages

  Study EGAS00001007413

• Low-coverage whole-sequencing of metastasised colorectal cancer samples treated with bevazicumab

  Low-coverage whole-genome sequencing (LC-WGS) was performed on tumor tissue, normal tissue and plasma samples collected from mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444) and the University Medical Center Mannheim (UMM).

  Study EGAS50000000131

• Analysis of Cell-Free DNA to Predict Outcome to Bevacizumab Combination Therapy in Metastatic Colorectal Cancer Patients

  This dataset includes FASTQ files of low coverage whole genome sequencing of normal tissue (n = 8), tumor tissue (n = 55) and cell free DNA from plasma samples (n=101) from patients with metastatic colorectal cancer treated with bevacizumab. A total of 164 samples are present from two different cohorts. The first batch of samples (n = 139, sample names sAPD302T until sAPD502_P0) were collected from the AC-Angiopredict Phase 2 trial (NCT01822444), the second batch of samples (n = 25m, sample names sAPD503_P0 until sAPD527_P0) were collected from the UMM cohort.

  Dataset EGAD50000000176

• Clinical and molecular features of early onset pancreatic cancer

  A retrospective cohort study on the clinical and molecular features of early onset pancreatic cancers (i. e. diagnosed at <50 years old) in comparison with later onset tumors.

  Study EGAS50000000362

• Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness

  RNAseq from patient-derived primary tumor cells, cultured or not on organotypic cultures mimicking the tumor microenvironment

  Study EGAS50000000355

• Human skin cancer (BCC, SCC, melanoma) and healthy control skin

  Smart-seq2 single cell RNA sequencing of human BCC, SCC, melanoma (ALM) and healthy control skin samples.

  Dataset EGAD50000000540

• Human Skin Cancer Atlas, Medical University of Vienna Data Access Policy

  Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. Here, we elucidate the yet unresolved intra-tumoral CAF variety in three skin cancer types at molecular and spatial single-cell resolution in a large cohort. We show that two out of three CAF subtypes contribute to tumor immune surveillance with distinct mechanisms. Matrix CAFs (mCAFs) ensheath tumor nests and synthesize extracellular-matrix to prevent T cell invasion. Immunomodulatory CAFs (iCAFs), which express proinflammatory and immunomodulatory factors, are only detected in high abundance in aggressive tumors. Strikingly, iCAFs but not tumor cells are (apart from immune cells) the exclusive cell type producing chemokines and, thus, play a key role in immune cell recruitment and activation. Mechanistically, we show that cancer cells transform adjacent healthy fibroblasts into cytokine-expressing iCAFs, which subsequently recruit immune cells and modulate the immune response. In conclusion, targeting CAF variants holds promise for improved efficacy of immunotherapy.

  Dac EGAC50000000154

• Origin of second malignancies in children

  Pediatric cancers are rare diseases, and children without known germline predisposing conditions who develop a second malignancy during developmental ages are extremely rare. We present four such clinical cases and through whole-genome and error-correcting ultra-deep duplex sequencing of tumor and normal samples, we explored the origin of the second malignancy in four children, uncovering different routes of development. The exposure to cytotoxic therapies was linked to the emergence of a secondary AML. A common somatic mutation acquired early during embryonic development was the driver of two solid malignancies in another child. In two cases, the two tumors developed from completely independent clones diverging during embryogenesis. Importantly, we demonstrate that platinum-based therapies contributed at least in one order of magnitude more mutations per day of exposure than aging to normal tissues in these children.

  Study EGAS50000000167

• Peripheral blood RNA sequencing of samples for a healthy cohort and a cohort with cancer patients

  RNA sequencing (fastq files) of white blood cells (WBCs) from healthy donors (n=376) and cancer patients (n=421) with different diagnoses, stages of disease and previously administered treatments, was performed. Samples from cancer patients were collected from the BostonGene clinical program; all patients provided written consent per IRB-approved protocols. Blood samples from healthy donors were purchased from multiple collection centers throughout the United States. Whole blood samples (3 ml) in K2-EDTA tubes received within 24 hours of collection at RT underwent red blood cell (RBC) lysis to isolate WBCs. Isolated WBCs for RNA sequencing were centrifuged at 300 x g for 5 minutes with a maximum of 10^6 cells per vial. The supernatant was removed, and the cells were resuspended in cold Homogenization Buffer (2% 1-Thioglycerol, Promega). Samples were then frozen at -80°C until extraction. RNA extraction was performed from frozen samples with Maxwell RSC simplyRNA Cells Kit (Promega) using the benchtop automated Maxwell RSC Instrument (Promega). Libraries were prepared with Illumina TruSeq® Stranded mRNA Library Prep (Poly-A mRNA; stranded). Libraries were sequenced on NovaSeq 6000 as Paired-End Reads (2x150) with targeted coverage of 50 mln reads.

  Dataset EGAD50000000414

• Panel sequencing of endocrine-resistant breast cancer

  Patients with endocrine-resistant breast cancer in Stockholm Sweden. DNA obtained from patients primary and relapse tumors, and tumor-free lymph nodes used as germline control. DNA was extracted from formalin-fixed paraffin-embedded tissue and sequenced by 370-gene panel-based sequencing with Kapa HyperPlus library preparation and Twist Bioscience hybrid capture. Custom bait sets (panels) from Twist Bioscience. Paired end 2x150 bp using NovaSeq X. The data is presented as fastq-files.

  Study EGAS50000000236

• MAF dataset of Colorectal Cancer Synthetic genomes

  This dataset contains genomic variants data in MAF format from four patients synthetically generated

  Dataset EGAD50000000315

• EOSC4Cancer Synthetic Colorectal Cancer Genomic data

  In this study there are stored the synthetic datasets produced by partners involved in EOSC4Cancer. The study contains independent datasets available for the research community. The synthetic genomes have been created trying to mimic real cancer data.

  Study EGAS50000000190

• EOSC4Cancer Longitudinal Synthetic Colorectal Cancer Genomic data developed at BSC

  The synthetic genomes have been created trying to mimic real cancer data of 4 patients (Named 185,186,187 and 188). Mutations are based on real CRC patients from the PCAWG dataset. For each patient, two tumor samples at different time points and one healthy sample have been simulated. The cancer intra-tumor heterogeneity and evolution in the patients is depicted by simulating reads from tumor subclones separately and then mixing them according to their clonal proportions in each sample. For rapid use and transfer only selected chromosomes have been generated for each patient. Chromosomes per patient: -185: chr4, chr5, chr7, chr17 -186: chr1, chr7, chr12, chr17 -187: chr1, chr2, chr5, chr12, chr17 -188: chr2, chr5, chr12, chr13, chr17 Worflows used to create BAM/BAI, VCF and MAF files from FASTQ (Alignment with GRCh38): - https://usegalaxy.eu/published/workflow?id=2c3d05023c02113e - https://usegalaxy.eu/published/workflow?id=1da86d74f8535f4e

  Dataset EGAD50000000276

• VCF dataset of Colorectal Cancer Synthetic genomes

  This dataset contains genomic variants data from VCF files of four patients synthetically generated in the EOSC4Cancer project

  Dataset EGAD50000000314

• BAM/BAI dataset of Colorectal Cancer Synthetic genomes

  This dataset contains binary alignment map (BAM) data with their respective index (BAI) from four patients synthetically generated.

  Dataset EGAD50000000316

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 14)

  The dataset contains whole genome sequencing data of 42 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 100 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000507

• Whole Genome Sequencing of HER2-Positive Metastatic Extramammary Paget’s Disease: A Case Report

  Extramammary Paget’s disease (EMPD) is a rare cancer that occurs within the epithelium of the skin. Whole genome sequencing of the tumor and matched blood was performed. Whole genome sequencing revealed the underlying copy number variation landscape in HER2-positive metastatic EMPD. The presence of alternative signalling pathways and genetic variants suggests potential interactions with HER2 signalling, which possibly contributed to the HER2 overexpression and observed response to HER2-directed therapy combined with other agents in a comprehensive treatment regimen.

  Study EGAS50000000243

• Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

  This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

  Dataset EGAD50000000559

• TOTHER3

  Patritumab deruxtecan in HER2-negative breast cancer: part B results of the window-of-opportunity SOLTI TOT-HER3 trial and biological determinants of early-response

  Dac EGAC50000000255

• Orthogonal proteogenomic analysis identifies the druggable PA2G4-MYC axis in 3q26 AML

  Our aim was to identify regulators of the EVI1/MECOM gene, which is the most lethal oncogenic TF and is highly expressed in AML with chromosome 3q26 abnormalities.

  Study EGAS50000000347

• Mechanisms of duodenal adenoma development in familial polyposis syndromes

  Study EGAS00001006561

• Buccal sample methylation from breast cancer cases

  Buccal sample methylation from breast cancer cases

  Dataset EGAD00010002635

• Dataset developed for use with EOSC4Cancer of synthetic colorectal cancer tumor/normal pairs.

  This dataset contains 10 tumor and normal pairs synthetic WGS data of colorectal cancer that were simulated in a standard format of Illumina paired-end reads. The NEAT read simulator (version 3.0, https://github.com/zstephens/neat-genreads) was utilized to synthetize these 10 pairs of tumor and normal WGS data. In the procedure of data generation, simulated parameters (i.e., sequencing error statistics, read fragment length distribution and GC% coverage bias) were learned from data models provided by NEAT. The average sequencing depth for tumor and normal samples aimed to reach around 110X and 60X, respectively. For generation of synthetic normal WGS data per each sample, a germline variant profile from a real patient was down-sampled randomly, representing 50% germline variants of a given patient. These were mixed with the other 50% in silico germline variants that were modelled randomly using an average mutation rate (0.001), finally constituting a full germline profile for normal synthetic WGS data. For generation of synthetic tumor WGS data per each sample, a pre-defined somatic short variant profile (SNVs+Indels) learnt from a real CRC patient was added to the germline variant profile used for creating the normal synthetic WGS data of the same patient, consisting of the variants for tumor sample. Neither copy number profile nor structural variation profile was introduced into the tumor synthetic WGS data. Tumor content and ploidy were assumed to be 100% and 2, respectively. For mapping/variant detection, the Sarek pipeline v3.1.2 (https://nf-co.re/sarek/3.1.2) was used, specifically: 1. BWA v0.7.17-r1188 for read mapping 2. GATK v4.3.0.0 for pre-processing BAM file (including markduplicates and recalibration). 2. Mutect2 (GATK v4.3.0.0) for somatic variant calling 3. Strelka2 v2.9.10 for germline and somatic variant calling Metadata information of 10 CRC patients used for the generation of synthetic normal and tumor WGS data: Patient_id Tumor_barcode Normal_barcode Age Sex Tissue Cancer SIM007 SIM007_T SIM007_N 71 F Rectal Primary CRC SIM008 SIM008_T SIM008_N 45 F Colon Neuroendocrine Metastasis CRC SIM010 SIM010_T SIM010_N 62 M Colon Metastasis CRC SIM011 SIM011_T SIM011_N 55 M Colon Neuroendocrine Metastasis CRC SIM012 SIM012_T SIM012_N 57 M Rectal Metastasis CRC SIM013 SIM013_T SIM013_N 69 M Colon Metastasis CRC SIM014 SIM014_T SIM014_N 68 M Colon Neuroendocrine primary CRC SIM015 SIM015_T SIM015_N 58 F Colon Primary CRC SIM016 SIM016_T SIM016_N 49 M Colon/Rectal Primary CRC SIM017 SIM017_T SIM017_N 78 M Colon Neuroendocrine primary CRC

  Dataset EGAD50000000564