Search Results - EGA European Genome-Phenome Archive

ICGC PedBrain DNA methylation sequencing

DNA methylation profiling of 107 medulloblastoma and 8 control samples by high-coverage whole-genome bisulfite (WBGS) sequencing and Illumina Infinium HumanMethylation450k array.

Study EGAS00001000561

Whole genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes

Glioblastoma (GBM) has one of the worst five-year survival rates of all cancers. While genomic studies of the disease have been performed, alterations in the non-coding regulatory regions of GBM have largely remained unexplored. We apply whole-genome sequencing (WGS) to identify non-coding mutations, with regulatory potential in GBM, under the hypothesis that regions of evolutionary constraint are likely to be functional, and somatic mutations are likely more damaging than in unconstrained regions.

Study EGAS00001004379

Leeds_Melanoma_Cohort

Leeds Melanoma Cohort

Study EGAS00001001158

MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

Despite the established role of the transcription factor MYC in cancer, little is known about the involvement of lncRNAs in mediating MYC’s function. Here we have intersected RNA-sequencing data from MYC-inducible cell lines, from a cohort of 91 mature B-cell lymphomas and from sorted germinal-center B-cells. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, showing a strong correlation with MYC expression in MYC-positive lymphomas and in pancreatic ductal adenocarcinomas. RNAi experiments showed that MINCR controls cellular viability by influencing the expression of MYC-regulated cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR acts as a modulator of MYC transcriptional control of cell cycle genes.

Study EGAS00001001199

Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

Genomic analyses promise to improve tumor characterization in order to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors revealed mutational signatures associated with specific risk factors, mainly combined alcohol/tobacco consumption, aflatoxin B1 and HBV infection. We identified 161 putative driver genes associated with 11 recurrent pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (HBV) and AXIN1. Analyses according to tumor stage progression revealed TERT promoter mutation as an early event whereas FGF/CCND1 amplification, TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 24% of the tumors, we identified genetic alterations potentially targetable by FDA-approved drugs. In conclusion, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.

Study EGAS00001001002

Spatial heterogeneity in medulloblastoma

Spatial heterogeneity of transcriptional and genetic markers between physically isolated biopsies of a single tumor poses major barriers to the identification of biomarkers and the development of targeted therapies that will be effective against the entire tumor. We analyzed the spatial heterogeneity of multiregional biopsies from 35 patients, using a combination of transcriptomic and genomic profiles. Medulloblastomas (MBs), but not high-grade gliomas (HGGs), demonstrated spatially homogeneous transcriptomes, which allowed for accurate subgrouping of tumors from a single biopsy. Conversely, somatic mutations that affect genes suitable for targeted therapeutics demonstrated high levels of spatial heterogeneity in MB, malignant glioma, and renal cell carcinoma (RCC). Actionable targets found in a single MB biopsy were seldom clonal across the entire tumor,which brings the efficacy of monotherapies against a single target into question. Clinical trials of targeted therapies for MB should first ensure the spatially ubiquitous nature of the target mutation.

Study EGAS00001001014

Bulk RNAseq gene expression of baseline tumors from metastatic urothelial bladder cancer patients (IMvigor210) and metastatic renal cell carcinoma (IMmotion150)

We examined tumors from a large cohort of patients with metastatic urothelial bladder cancer (mUC) and metastatic renal cell carcinoma (mRCC) treated with an anti-PD-L1 agent (atezolizumab) and found that high tumor IL8 gene expression was associated with worse overall survival (OS). We further identified the tumoral immune presence based on Teff signature. We found that high tumor IL8 expression continued to be associated with worse OS even in inflamed tumors in mUC and mRCC.

Study EGAS00001004386

Exome and transcriptome sequencing of Desmoplastic Small Round Cell Sarcoma

To conduct exome and transcriptome profiling to identify secondary recurrent mutations, multi-site phylogenetic analyse and immune characterization of Desmoplastic Small Round Cell Sarcoma.

Study EGAS00001004575

Exploration of CNV’s and SNV’s in cancers with well-known genetic rearrangements: Identification of additional genetic changes in rearrangements-driven cancer

Specific cancers are well known to have specific gene rearrangements. Representative cancer is chronic myeloid leukemia (CML) which is famous for BCR/ABL gene rearrangements. By the way, also genetic rearrangements are not infrequently found in acute leukemia, and those include CBFB/MYH11 rearrangements, PML/RARA rearrangements, AML/ETO rearrangements, and BCR/ABL rearrangements. The situation is same is for lung adenocarcinoma of non-smokers and prostate cancers, and ALK and RET gene rearrangements are recently found. However, not all these rearrangements are sufficient to develop cancer, and it is suggested that some genetic aberrations are required for the development and progression of cancer in addition to these genetic rearrangements. In this study, we have a plan to explore the existence of additional genetic changes including single nucleotide variants (SNV’s) and copy number variations (CNV’s) in cancers with specific genetic rearrangements so as to define additional genetic changes that confer full oncogenic potential to cancer cells. So as to look at SNV’s and small indels, we are going to use whole exome sequencing (WES) data. And as for CNV’s, we are going to use array-CGH data. Also, to check the functionality of these genetic changes, we are going to use whole transcriptome data (WTS). In addition, in samples with whole genome sequencing (WGS ) data, we are going to explore genetic changes in intronic regions also. In fact, we sequenced 10 AML samples which are known to have specific genetic rearrangements. Analysis of these WGS, WES and WTS data are under the way. If we have a chance to access WES, array-CGH and WTS data of other cancer samples with specific genetic rearrangements, we would be able to compare additional genetic changes required for oncogenesis in cancer cells with various genetic rearrangements. We hope this result will enlighten our understanding of cancer genetics further.

Study EGAS00001000673

Blueprint RNAseq profile of purified plasma cells from multiple myeloma patients and tonsils of healthy donors

In the context of an epigenomic study of multiple myeloma, a have generated RNAseq profiles of purified plasma cells from 11 multiple myeloma patients and tonsils of 4 healthy donors

Study EGAS00001001110

Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

We discovered a conserved neural tri- lineage cancer hierarchy centered around glial progenitor-like cells. We also found that this progenitor population contains the majority of the cancer’s cycling cells, and, using RNA velocity, is often the originator of the other cell types. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, suggests a possible origin for glioblastoma hierarchy, and helps to identify cancer stem cell-specific targets.

Study EGAS00001004422

The genomic landscape of primary cutaneous anaplastic large cell lymphoma (pcALCL)

Primary cutaneous anaplastic large cell lymphoma (pcALCL) is the second most common variant of cutaneous T-cell lymphoma. We subjected tumor biopsies from patients with pcALCL to whole-genome sequencing, whole-exome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

Study EGAS00001004429

Neuroblastoma relapse trio series from the AMC

The majority of neuroblastoma patients have tumors that initially respond to chemotherapy, but a large proportion of patients will experience therapy-resistant relapses. The molecular basis of this aggressive phenotype is unknown. Whole genome sequencing of 23 paired diagnostic and relapsed neuroblastomas showed clonal evolution from the diagnostic tumor with a median of 29 somatic mutations unique to the relapse sample. Eighteen of the 23 relapse tumors (78%) showed RAS-MAPK pathway mutations. Seven events were detected only in the relapse tumor while the others showed clonal enrichment. In neuroblastoma cell lines we also detected a high frequency of activating mutations in the RAS-MAPK pathway (11/18, 61%) and these lesions predicted for sensitivity to MEK inhibition in vitro and in vivo. Our findings provide a rationale for genetic characterization of relapse neuroblastoma and show that RAS-MAPK pathway mutations may function as a biomarker for new therapeutic approaches to refractory disease.

Study EGAS00001001183

Recurrent mTORC1-activating RRAGC mutations in follicular lymphoma

Follicular lymphoma (FL) is an incurable B-cell malignancy characterized by the t(14;18) and mutations in one or more components of the epigenome. Whilst frequent gene mutations in signaling pathways, including JAK-STAT, NOTCH and NF-κB, have also been defined, the spectrum of these mutations typically overlap with the closely-related diffuse large B cell lymphoma (DLBCL). A combination of discovery exome and extended targeted sequencing revealed recurrent somatic mutations in RRAGC uniquely enriched in FL patients (17%). More than half of the mutations preferentially co-occurred with ATP6V1B2 and ATP6AP1 mutations, components of the vacuolar H+-adenosine triphosphate ATPase (v-ATPase) known to be necessary for amino acid-dependent mTORC1 activation. RagC mutants increased raptor binding whilst rendering mTORC1 signaling resistant to amino acid deprivation through nucleotide-independent mechanisms. Collectively, the activating nature of the RRAGC mutations, their existence within the dominant clone and stability during disease progression supports their potential as an excellent candidate to be therapeutically exploited.

Study EGAS00001001190

Study of non-clear cell renal cell carcinoma

Study EGAS00001000926

ctDNA monitoring using patient-specific sequencing and integration of variant reads - Lung cohort

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

Study EGAS00001004447

Clinical outcomes in ctDNA-positive urothelial carcinoma patients treated with adjuvant immunotherapy

Minimally invasive approaches to detect residual disease after surgery are urgently needed to select patients at highest risk for metastatic relapse for additional therapies. Circulating tumour DNA (ctDNA) holds promise as a biomarker for molecular residual disease (MRD) and relapse,1-3 but its clinical value has yet to be demonstrated in a randomised clinical trial. We evaluated outcomes in post-surgical ctDNA-positive (+) patients in a randomised phase III trial of adjuvant atezolizumab versus observation. IMvigor010 enrolled 809 patients with muscle-invasive urothelial carcinoma and did not meet its primary endpoint of disease-free survival (DFS) in the intent-to-treat population. Within the study, an exploratory planned analysis of prospectively collected plasma was performed, which tested the utility of ctDNA to identify patients who may benefit from adjuvant atezolizumab treatment. ctDNA was measured at the start of therapy (cycle 1 day 1; C1D1) and at week 6 (cycle 3 day 1; C3D1), and 581 patients were evaluable for ctDNA. The prevalence of ctDNA positivity at C1D1 was 37% (n=214), and ctDNA positivity identified patients with poor prognosis (observation arm DFS HR= 6.19 (4.29, 8.91), p&lt;0.0001). Here we show that ctDNA(+) patients had improved DFS and overall survival (OS) with atezolizumab versus observation (DFS HR= 0.56 (0.41-0.77); p=0.0003 and OS HR= 0.58 (0.4-0.86); p=0.0063). No difference in DFS or OS between arms was noted for ctDNA-negative patients. The rate of ctDNA clearance was higher with atezolizumab (18%) versus observation (4%) (p=0.0041). Transcriptomic analysis revealed that tumours from ctDNA(+) patients had higher expression of cell cycle and keratin genes. Within the ctDNA(+) patient population in the atezolizumab arm, non-relapsing patients were further enriched in prominent immune response signatures including PD-L1, IFNG, CXCL9, and high tumour mutational burden, whereas relapse was associated with angiogenesis and fibroblast-transforming growth factor-beta signatures (F-TBRS). TCGA molecular subset analysis revealed increased efficacy of atezolizumab in patients with basal-squamous tumours, consistent with underlying tumour-immune contexture. Together these findings suggest that adjuvant atezolizumab may be associated with improved outcomes compared with observation in this high-risk ctDNA(+) population. These findings, if validated in other settings, would shift approaches to post-operative cancer care.

Study EGAS00001004997

Comprehensive Transcriptional Analysis of Early Stage Urothelial Carcinoma using whole transcriptome sequencing

The expression profile and sequence variants of 476 early stage urothelial carcinoma were studied using whole transcriptome sequencing. RNA-Seq libraries were prepared by Ribo-Zero treatment of total-RNA followed by library preparation using ScriptSeq (both Epicentre/Illumina). RNA-Seq libraries were paired-end sequenced (2x 101 bp) on Illumina HiSeq 2000 and the resulting fastq files were processed using tools from the Genome Analysis Toolkit (GATK and from the Tuxedo suite. Access to the sequence data (mapped and un-mapped bam and vcf files), containing person identifying information, needs signature on a controlled access form, and can be accessed at The European Genome-phenome Archive (EGA) following request. An expression matrice of FPKM values are available without restriction at ArrayExpress (E-MTAB-4321).

Study EGAS00001001236

Initial whole genome sequencing of plasma cell neoplasms in First Responders exposed to the World Trade Center attack of September 11, 2001

The World Trade Center (WTC) attack of September 11, 2001 created an unprecedented environmental exposure to known and suspected carcinogens. High incidence of multiple myeloma (MM) and precursor conditions has been reported among first responders to the WTC disaster. To expand on our prior screening studies, and to characterize the genomic impact of the exposure to known and potential carcinogens in the WTC debris, we were motivated to perform whole genome sequencing (WGS) of WTC first responders and recovery workers who developed a plasma cell disorder after the attack. PATIENTS AND METHODS: We performed WGS of 9 CD138-positive bone marrow mononuclear samples from patients who were diagnosed with plasma cell disorders after the WTC disaster. RESULTS: No significant differences were observed in comparing the post-WTC driver and mutational signatures landscape with 110 previously published WGS from 56 patients with MM and the CoMMpass WGS cohort (n=752). Leveraging constant activity of the single base substitution mutational signatures 1 and 5 over time, we estimated that tumor-initiating chromosomal gains were windowed to both pre- and post-WTC exposure. CONCLUSIONS: Although limitations in sample size preclude any definitive conclusions, our findings suggest that the observed increased incidence of plasma cell neoplasms in this population is due to complex and heterogeneous effects of the WTC exposure that may have initiated or contributed to progression of malignancy.

Study EGAS00001004467

Uterine leiomyoma: DNA methylation, chromatin activity and gene expression

In this study, we observed the effects of different uterine leiomyoma driver mutations to tumor DNA methylation, chromatin activity and gene expression, to form a comprehensive view on the epigenetic consequences of the mutations.

Study EGAS00001004499

DNA methylation and somatic mutations converge on cell cycle and define similar evolutionary histories in brain tumors

The evolutionary history of tumor cell populations can be reconstructed from patterns of genetic alterations. In contrast to the stability of genetic events, epigenetic states are reversible and sensitive to the microenvironment, prompting the question whether epigenetics can be similarly used to discover tumor phylogeny. We examined the spatial and temporal dynamics of DNA methylation in a cohort of low-grade gliomas and their patient-matched recurrences. Genes upregulated through promoter hypomethylation during malignant progression to high-grade glioblastoma were enriched in cell cycle function, evolving in parallel with genetic alterations that deregulate the G1/S cell cycle checkpoint. Moreover, phyloepigenetic relationships robustly recapitulated phylogenetic patterns inferred from somatic mutations. These findings highlight widespread co-dependency of genetic and epigenetic events throughout brain tumor evolution.

Study EGAS00001001255

Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

Study EGAS00001001184

Super enhancers define regulatory subtypes and cell identity in neuroblastoma - RNA-seq

Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

Study EGAS00001004552

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

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.

Study EGAS00001004564

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.

Study EGAS00001004567

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