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Immune checkpoint blockade (ICB)-based or natural cancer immune responses largely eliminate tumours. Yet, they require additional mechanisms to arrest those cancer cells that are not rejected. Cytokine-induced senescence (CIS) can stably arrest cancer cells, suggesting that interferon-dependent induction of senescence-inducing cell cycle regulators is needed to control those cancer cells that escape from killing. Here we report in two different cancers sensitive to T cell-mediated rejection, that deletion of the senescence-inducing cell cycle regulators p16 Ink4a /p19 Arf ( Cdkn2a ) or p21 Cip1 ( Cdkn1a ) in the tumour cells abrogates both the natural and the ICB-induced cancer immune control. Also in humans, melanoma metastases that progressed rapidly during ICB have losses of senescence-inducing genes and amplifications of senescence inhibitors. Metastatic cells also resist CIS. Such genetic and functional alterations are infrequent in metastatic melanomas regressing during ICB. Thus, activation of tumour-intrinsic, senescence-inducing cell cycle regulators is required to stably arrest cancer cells that escape from eradication. The growth of cancer cells can be stably arrested by cytokine-induced senescence. Here, the authors show that cancers with defects in senescence-inducing cell cycle regulator pathways are resistant to immune checkpoint blockade.

The detection of somatic driver mutations by next-generation sequencing (NGS) is becoming increasingly important in the care of advanced melanoma patients. In our study, we evaluated the NGS results of 82 melanoma patients from clinical routine in 2017. Besides determining the tumor mutational burden (TMB) and annotation of all genetic driver alterations, we investigated their potential as a predictor for resistance to immune checkpoint inhibitors (ICI) and as a distinguishing feature between melanoma subtypes. Melanomas of unknown primary had a similar mutation pattern and TMB to cutaneous melanoma, which hints at its cutaneous origin. Besides the typical hotspot mutation in BRAF and NRAS, we frequently observed CDKN2A deletions. Acral and mucosal melanomas were dominated by CNV alterations affecting PDGFRA, KIT, CDK4, RICTOR, CCND2 and CHEK2. Uveal melanoma often had somatic SNVs in GNA11/Q and amplification of MYC in all cases. A significantly higher incidence of BRAF V600 mutations and EGFR amplifications, PTEN and TP53 deletions was found in patients with disease progression while on ICI. Thus, NGS might help to characterize melanoma subtypes more precisely and to identify possible resistance mechanisms to ICI therapy. Nevertheless, NGS based studies, including larger cohorts, are needed to support potential genetic ICI resistance mechanisms.

In the era of precision medicine, genome sequencing (GS) has become more affordable and the importance of genomics and multi-omics in clinical care is increasingly being recognized. However, how to scale and effectively implement GS on an institutional level remains a challenge for many. Here, we present Genome First and Ge-Med, two clinical implementation studies focused on identifying the key pillars and processes that are required to make routine GS and predictive genomics a reality in the clinical setting. We describe our experience and lessons learned for a variety of topics including test logistics, patient care processes, data reporting, and infrastructure. Our model of providing clinical care and comprehensive genomic analysis from a single source may be used by other centers with a similar structure to facilitate the implementation of omics-based personalized health concepts in medicine.

Background Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. Results We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm’s sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. Conclusion We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants in coding or regulatory regions with complex diseases in large cohorts at genome-wide scale. However, rare variant association studies (RVAS) still lack power when cohorts are small to medium-sized and if genetic variation explains a small fraction of phenotypic variance. Here we present a novel Bayesian rare variant Association Test using Integrated Nested Laplace Approximation (BATI). Unlike existing RVAS tests, BATI allows integration of individual or variant-specific features as covariates, while efficiently performing inference based on full model estimation. We demonstrate that BATI outperforms established RVAS methods on realistic, semi-synthetic whole-exome sequencing cohorts, especially when using meaningful biological context, such as functional annotation. We show that BATI achieves power above 70% in scenarios in which competing tests fail to identify risk genes, e.g. when risk variants in sum explain less than 0.5% of phenotypic variance. We have integrated BATI, together with five existing RVAS tests in the ‘Rare Variant Genome Wide Association Study’ (rvGWAS) framework for data analyzed by whole-exome or whole genome sequencing. rvGWAS supports rare variant association for genes or any other biological unit such as promoters, while allowing the analysis of essential functionalities like quality control or filtering. Applying rvGWAS to a Chronic Lymphocytic Leukemia study we identified eight candidate predisposition genes, including EHMT2 and COPS7A.

Background The role of copy number variants (CNVs) in susceptibility to asthma is not well understood. This is, in part, due to the difficulty of accurately measuring CNVs in large enough sample sizes to detect associations. The recent availability of whole-exome sequencing (WES) in large biobank studies provides an unprecedented opportunity to study the role of CNVs in asthma. Methods We called common CNVs in 49,953 individuals in the first release of UK Biobank WES using ClinCNV software. CNVs were tested for association with asthma in a stage 1 analysis comprising 7098 asthma cases and 36,578 controls from the first release of sequencing data. Nominally-associated CNVs were then meta-analysed in stage 2 with an additional 17,280 asthma cases and 115,562 controls from the second release of UK Biobank exome sequencing, followed by validation and fine-mapping. Results Five of 189 CNVs were associated with asthma in stage 2, including a deletion overlapping the HLA-DQA1 and HLA-DQB1 genes, a duplication of CHROMR/PRKRA , deletions within MUC22 and TAP2 , and a duplication in FBRSL1 . The HLA-DQA1 , HLA-DQB1 , MUC22 and TAP2 genes all reside within the human leukocyte antigen (HLA) region on chromosome 6. In silico analyses demonstrated that the deletion overlapping HLA-DQA1 and HLA-DQB1 is likely to be an artefact arising from under-mapping of reads from non-reference HLA haplotypes, and that the CHROMR/PRKRA and FBRSL1 duplications represent presence/absence of pseudogenes within the HLA region. Bayesian fine-mapping of the HLA region suggested that there are two independent asthma association signals. The variants with the largest posterior inclusion probability in the two credible sets were an amino acid change in HLA-DQB1 (glutamine to histidine at residue 253) and a multi-allelic amino acid change in HLA-DRB1 (presence/absence of serine, glycine or leucine at residue 11). Conclusions At least two independent loci characterised by amino acid changes in the HLA-DQA1 , HLA-DQB1 and HLA-DRB1 genes are likely to account for association of SNPs and CNVs in this region with asthma. The high divergence of haplotypes in the HLA can give rise to spurious CNVs, providing an important, cautionary tale for future large-scale analyses of sequencing data.

The impact of healthy aging on molecular programming of immune cells is poorly understood. Here we report comprehensive characterization of healthy aging in human classical monocytes, with a focus on epigenomic, transcriptomic and proteomic alterations, as well as the corresponding proteomic and metabolomic data for plasma, using healthy cohorts of 20 young and 20 older males (~27 and ~64 years old on average). For each individual, we performed enhanced reduced representation bisulfite sequencing-based DNA methylation profiling, which allowed us to identify a set of age-associated differentially methylated regions (DMRs)—a novel, cell-type-specific signature of aging in the DNA methylome. Hypermethylation events were associated with H3K27me3 in the CpG islands near promoters of lowly expressed genes, while hypomethylated DMRs were enriched in H3K4me1-marked regions and associated with age-related increase of expression of the corresponding genes, providing a link between DNA methylation and age-associated transcriptional changes in primary human cells. Multiomics profiling of circulating monocytes from young and older healthy males reveals key determinants of healthy aging, including regions of age-associated DNA hypo- and hypermethylation, cellular chromatin landscape and effect on gene expression.

Background Targeted sequencing approaches such as gene panel or exome sequencing have become standard of care for the diagnosis of rare and common genetic disease. The detection and interpretation of point mutations, small insertions and deletions, and even exon‐level copy number variants are well established in clinical genetic testing. Other types of genetic variation such as mobile elements insertions (MEIs) are technically difficult to detect. In addition, their downstream clinical interpretation is more complex compared to point mutations due to a larger genomic footprint that can not only predict a clear loss of protein function but might disturb gene regulation and splicing even when located within the non‐coding regions. As a consequence, the contribution of MEIs to disease and tumor development remains largely unexplored in routine diagnostics. Methods In this study, we investigated the occurrence of MEIs in 7,693 exome datasets from individuals with rare diseases and healthy relatives as well as 788 cancer patients analyzed by panel sequencing. Results We present several exemplary cases highlighting the diagnostic value of MEIs and propose a strategy for the detection, prioritization, and clinical interpretation of MEIs in routine clinical diagnostics. Conclusion In this paper, we state that detection and interpretation of MEIs in clinical practice in targeted NGS data can be performed relatively easy despite the fact that MEIs very rarely occur in coding parts of the human genome. Large scale reanalysis of MEIs in existing cohorts may solve otherwise unsolvable cases. Mobile elements insertions (MEIs) are technically difficult to detect in targeted NGS data. In this study, we investigated the occurrence of MEIs in 7,693 exome datasets from individuals with rare diseases and healthy relatives as well as 788 cancer patients analyzed by panel sequencing. We present several exemplary cases highlighting the diagnostic value of MEIs and propose a strategy for the detection, prioritization, and clinical interpretation of MEIs in routine clinical diagnostics.

PurposeGenome sequencing (GS) is expected to reduce the diagnostic gap in rare disease genetics. We aimed to evaluate a scalable framework for genome-based analyses ‘beyond the exome’ in regular care of patients with inherited retinal degeneration (IRD) or inherited optic neuropathy (ION).MethodsPCR-free short-read GS was performed on 1000 consecutive probands with IRD/ION in routine diagnostics. Complementary whole-blood RNA-sequencing (RNA-seq) was done in a subset of 74 patients. An open-source bioinformatics analysis pipeline was optimised for structural variant (SV) calling and combined RNA/DNA variation interpretation.ResultsA definite genetic diagnosis was established in 57.4% of cases. For another 16.7%, variants of uncertain significance were identified in known IRD/ION genes, while the underlying genetic cause remained unresolved in 25.9%. SVs or alterations in non-coding genomic regions made up for 12.7% of the observed variants. The RNA-seq studies supported the classification of two unclear variants.ConclusionGS is feasible in clinical practice and reliably identifies causal variants in a substantial proportion of individuals. GS extends the diagnostic yield to rare non-coding variants and enables precise determination of SVs. The added diagnostic value of RNA-seq is limited by low expression levels of the major IRD disease genes in blood.

Background: Mucosal and acral melanoma respond worse to immune checkpoint inhibitors (ICI) than cutaneous melanoma. MDM2/4 as well as EGFR amplifications are supposed to be associated with hyperprogression on ICI in diverse cancers. We therefore investigated the response of metastatic acral and mucosal melanoma to ICI in regard to MDM2/4 or EGFR amplifications and melanoma type. Methods: We conducted a query of our melanoma registry, looking for patients with metastatic acral or mucosal melanoma treated by ICI. Whole exome sequencing, FISH and immunohistochemistry on melanoma tissue could be performed on 45 of the total cohort of 51 patients. Data were correlated with patients’ responses to ICI and survival. Results: 22 out of 51 patients had hyperprogressive disease (an increase in tumor load of >50% at the first staging). Hyperprogression occurred more often in case of MDM2/4 or EGFR amplification or <1% PD-L1 positive tumor cells. Nevertheless, this association was not significant. Interestingly, the anorectal melanoma type and the presence of liver metastases were significantly associated with worse survival. Conclusions: So far, we found no reliable predictive marker for patients who develop hyperprogression on ICI, specifically with regard to MDM2/4 or EGFR amplifications. Nevertheless, patients with anorectal melanoma, liver metastases or melanoma with amplified MYC seem to have an increased risk of not benefitting from ICI.