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• CD74-NRG1 fusions in lung adenocarcinoma

  We discovered a novel somatic gene fusion, CD74-NRG1, by transcriptome sequencing of 25 lung adenocarcinomas of never smokers. By screening 102 lung adenocarcinomas negative for known oncogenic alterations we found four additional fusion-positive tumors, all of which were of the invasive mucinous subtype. Mechanistically, CD74-NRG1 leads to extracellular expression of the EGF-like domain of NRG1 III-beta3, thereby providing the ligand for ERBB2-ERBB3 receptor complexes. Accordingly, ERBB2 and ERBB3 expression was high in the index case and expression of phospho-ERBB3 was specifically found in tumors bearing the fusion (p<0.0001). Ectopic expression of CD74-NRG1 in lung cancer cell lines expressing ERBB2 and ERBB3 activated ERBB3 and the PI3K-AKT pathway, and led to increased colony formation in soft agar. Thus, CD74-NRG1 gene fusions are activating genomic alterations in invasive mucinous adenocarcinomas and may offer a therapeutic opportunity for a lung tumor subtype with, so far, no effective treatment.

  Study EGAS00001000653

• Systematic kinase inhibitor profiling identifies CDK9 as a synthetic lethal target in NUT midline carcinoma

  Kinase inhibitors represent the backbone of targeted cancer therapy, yet only a limited number of oncogenic drivers are directly druggable. By interrogating the activity of 1,505 kinase inhibitors we found that BRD4-NUT-rearranged NUT midline carcinoma (NMC) cells are specifically killed by CDK9 inhibition (CDK9i) and exhibit a unique dependency on CDK9 and Cyclin-T1 expression. We show that CDK9i leads to robust induction of apoptosis and of markers of DNA damage response in NMC cells. While both CDK9i and bromodomain inhibition over time result in reduced Myc protein expression, only bromodomain inhibition induces cell differentiation and a p21-induced cell cycle arrest in these cells. Finally, RNA-Seq and ChIP-based analyses reveal a BRD4-NUT specific CDK9i-induced perturbation of transcriptional elongation. Thus, our data provide a mechanistic basis for the genotype-dependent vulnerability of NUT midline carcinoma cells to CDK9i that may be of relevance for the development of targeted therapies for NMC patients.

  Study EGAS00001002588

• Complete Genomics paired end sequencing; Ovarian cancer

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000158

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas

  Despite the advance in precision therapy, about 20% of stage I non-small cell lung cancer patients suffer a relapse after surgical resection. To develop molecular signatures for relapse prediction of stage I lung adenocarcinoma (LUAD), we conduct comprehensive analyses of multiplatform molecular profiling from 113 treatment-naïve stage I Taiwanese LUAD patients. We identify 16 nonsynonymous non-sporadic point mutations (NSPOPMs) harbored at EGFR, KRAS, TP53, CTNNB1 and 6 other genes, and find that the Non-EGFR NSPOPMs were associated with early relapse in a dose-dependent manner via variant allele fraction (VAF). We define a score, maxVAF, to aggregate the VAFs of these NSPOPMs by the maximum value. MicroRNA expression analysis shows a strong correlation between miR-31 and maxVAF. Combining maxVAF with miR-31 led to a powerful risk prediction for surgically resected stage I patients (hazard ratio = 8.65, P = 0.001). Our study opens up more options for precision management of stage I LUAD patients.

  Study EGAS00001004461

• Whole Genome Sequencing on OCIAML-22

  Donor_OCIAML22_bulk: The donor (unsorted) that was used to generate OCI-AML22. OCI-AML22_bulk_1month_inVitro: The donor (unsorted) that was used to generate OCI-AML22 was expanded for 1 month in vitro, then sequenced. OCI-AML22_graft_CD34minus_WGS: The donor (unsorted) that was used to generate OCI-AML22 was expanded for 1 month in vitro, then injected in NSG-SGM3 mice. 21 weeks after injection, cells from 5 mice injected with 5 mice injected with 1475 cells per mice and 4 mice injected with 469 cells per mice were sorted. The human CD34- fraction was sequenced (CD45h+CD45m-7aad-annexinV-CD34-) OCI-AML22_graft_CD34positive_WGS: The donor (unsorted) that was used to generate OCI-AML22 was expanded for 1 month in vitro, then injected in NSG-SGM3 mice. 21 weeks after injection, cells from 5 mice injected with 5 mice injected with 1475 cells per mice and 4 mice injected with 469 cells per mice were sorted. The human CD34+ fraction was sequenced (CD45h+CD45m-7aad-annexinV-CD34+)

  Study EGAS00001006513

• Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

  These data relate to Abbosh et al 2023 'Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA'. Some patients were included in this work that were excluded from the other TRACERx 421 papers (Frankell et al and Al-bakir et al) often due to exclusion criteria in the TRACERx clinical trial. Reasons include partial contamination with C>A artefact mutational signature (CRUK0480 ,0490) which were included for ctDNA detection analyses using high confidence clonal mutations but not clonality analyses, incomplete resection at primary surgery (CRUK0291, 0234, 0230, 0387, 0622) and a concurrent oesophageal second primary cancer (CRUK0498). The primary tissue exome sequencing for these patients that were used in this study are included in this repository. Deep targeted sequencing of (median 200) tumour specific mutations in plasma for 1069 samples from 198 TRACERx patients are also included. Additional details related to these patients and samples can be found in the supplementary or data repositories from Frankell et al and Abbosh et al.

  Study EGAS00001006923

• WGS of MAPKi acquired resistant samples from patients and PDX models

  Blocking cancer genomic instability, which generates diverse variants that enable rapid adaptations, may prevent tumor escape from therapies. We show that, after MAPK inhibitor (MAPKi) therapy in patients and patient-derived xenografts, acquired-resistant genomes of metastatic cutaneous melanoma accumulate amplicons of resistance-driver, non-homologous end-joining (NHEJ), and homologous recombination repair (HRR) genes within complex genomic rearrangements (CGRs) and extrachromosomal circular DNAs (ecDNAs). Also, chromothriptic genomic regions enrich for mutations and may engender ecDNAs and CGRs. Overall, somatic mutations within ecDNA- and CGR-amplicons enrich for HRR signatures, and, in acquired resistance, ecDNA (versus CGR) mutations enrich for APOBEC3 signatures. Breakpoint-sequence analysis suggests NHEJ as critical to double-stranded DNA break repair underlying CGR and ecDNA formation. In vivo, NHEJ-targeting by a DNA-PKCS inhibitor prevented acquired MAPKi-resistance by reducing the size of ecDNAs and CGRs early on combination treatment. Thus, targeting the cause(s), as opposed to the consequences, of genomic instability prevents acquired resistance.

  Study EGAS00001006874

• RNAseq of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007300

• WES of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007301

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma_CM67-RNASeq

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006306

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006309

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Study EGAS00001007327

• Causative Mutations for TAR DAC

  Dac EGAC00001000008

• Data Access Committee for TraIT

  Dac EGAC00001000212

• Data Committee for EMSEQ project

  Dac EGAC00001000265

• DAC for HTS MRD study

  Dac EGAC00001000359

• DAC for Korean BC data

  Dac EGAC00001000740

• DAC for A Karadimitris Lab

  Dac EGAC00001001003

• Data Access Commitee for EGAS00001003258

  Dac EGAC00001001038

• Data access comittee for Institut Curie

  Dac EGAC00001001042

• DAC for the study EGAS00001003572

  Dac EGAC00001001174

• DAC for hepatitis B analysis

  Dac EGAC00001001228

• DAC for Wigler Group

  Dac EGAC00001001256

• DAC for panc_met data set

  Dac EGAC00001001480

• Center for Medical Genetics Ghent

  Dac EGAC00001001507