The interplay between neoantigens and immune cells in sarcomas treated with checkpoint inhibition.

Introduction: Sarcomas are comprised of diverse bone and connective tissue tumors with few effective therapeutic options for locally advanced unresectable and/or metastatic disease. Recent advances in immunotherapy, in particular immune checkpoint inhibition (ICI), have shown promising outcomes in several cancer indications. Unfortunately, ICI therapy has provided only modest clinical responses and seems moderately effective in a subset of the diverse subtypes. Methods: To explore the immune parameters governing ICI therapy resistance or immune escape, we performed whole exome sequencing (WES) on tumors and their matched normal blood, in addition to RNA-seq from tumors of 31 sarcoma patients treated with pembrolizumab. We used advanced computational methods to investigate key immune properties, such as neoantigens and immune cell composition in the tumor microenvironment (TME). Results: A multifactorial analysis suggested that expression of high quality neoantigens in the context of specific immune cells in the TME are key prognostic markers of progression-free survival (PFS). The presence of several types of immune cells, including T cells, B cells and macrophages, in the TME were associated with improved PFS. Importantly, we also found the presence of both CD8+ T cells and neoantigens together was associated with improved survival compared to the presence of CD8+ T cells or neoantigens alone. Interestingly, this trend was not identified with the combined presence of CD8+ T cells and TMB; suggesting that a combined CD8+ T cell and neoantigen effect on PFS was important. Discussion: The outcome of this study may inform future trials that may lead to improved outcomes for sarcoma patients treated with ICI.

Personalized HLA typing leads to the discovery of novel HLA alleles and tumor-specific HLA variants.

Accurate and full-length typing of the HLA region is important in many clinical and research settings. With the advent of next generation sequencing (NGS), several HLA typing algorithms have been developed, including many that are applicable to whole exome sequencing (WES). However, most of these solutions operate by providing the closest-matched HLA allele among the known alleles in IPD-IMGT/HLA Database. These database-matching approaches have demonstrated very high performance when typing well characterized HLA alleles. However, as they rely on the completeness of the HLA database, they are not optimal for detecting novel or less well characterized alleles. Furthermore, the database-matching approaches are also not adequate in the context of cancer, where a comprehensive characterization of somatic HLA variation and expression patterns of a tumor's HLA locus may guide therapy and clinical outcome, because of the pivotal role HLA alleles play in tumor antigen recognition and immune escape. Here, we describe a personalized HLA typing approach applied to WES data that leverages the strengths of database-matching approaches while simultaneously allowing for the discovery of novel HLA alleles and tumor-specific HLA variants, through the systematic integration of germline and somatic variant calling. We applied this approach on WES from 10 metastatic melanoma patients and validated the HLA typing results using HLA targeted NGS sequencing from patients where at least one HLA germline candidate was detected on Class I HLA. Targeted NGS sequencing confirmed 100% performance for the 1st and 2nd fields. In total, five out of the six detected HLA germline variants were because of Class I ambiguities at the third or fourth fields, and their detection recovered the correct HLA allele genotype. The sixth germline variant let to the formal discovery of a novel Class I allele. Finally, we demonstrated a substantially improved somatic variant detection accuracy in HLA alleles with a 91% of success rate in simulated experiments. The approach described here may allow the field to genotype more accurately using WES data, leading to the discovery of novel HLA alleles and help characterize the relationship between somatic variation in the HLA region and immunosurveillance.

The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research.

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While "High-Throughput" sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR's recently established human CNV Community, with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

Whole exome sequencing of sporadic patients with Currarino Syndrome: A report of three trios.

Currarino Syndrome is a rare congenital malformation syndrome described as a triad of anorectal, sacral and presacral anomalies. Currarino Syndrome is reported to be both familial and sporadic. Familial CS is today known as an autosomal dominant disorder caused by mutations in the transcription factor MNX1. The aim of this study was to look for genetic causes of Currarino Syndrome in sporadic patients after ruling out other causes, like chromosome aberrations, disease-causing variants in possible MNX1 cooperating transcription factors and aberrant methylation in the promoter of the MNX1 gene. The hypothesis was that MNX1 was affected through interactions with other transcription factors or through other regulatory elements and thereby possibly leading to abnormal function of the gene. We performed whole exome sequencing with an additional 6Mb custom made region on chromosome 7 (GRCh37/hg19, chr7:153.138.664-159.138.663) to detect regulatory elements in non-coding regions around the MNX1 gene. We did not find any variants in genes of interest shared between the patients. However, after analyzing the whole exome sequencing data with Filtus, the in-house SNV filtration program, we did find some interesting variants in possibly relevant genes that could be explaining these patients` phenotypes. The most promising genes were ETV3L, ARID5A and NCAPD3. To our knowledge this is the first report of whole exome sequencing in sporadic CS patients.

Primary immunodeficiency diseases: Genomic approaches delineate heterogeneous Mendelian disorders.

BACKGROUND: Primary immunodeficiency diseases (PIDDs) are clinically and genetically heterogeneous disorders thus far associated with mutations in more than 300 genes. The clinical phenotypes derived from distinct genotypes can overlap. Genetic etiology can be a prognostic indicator of disease severity and can influence treatment decisions. OBJECTIVE: We sought to investigate the ability of whole-exome screening methods to detect disease-causing variants in patients with PIDDs. METHODS: Patients with PIDDs from 278 families from 22 countries were investigated by using whole-exome sequencing. Computational copy number variant (CNV) prediction pipelines and an exome-tiling chromosomal microarray were also applied to identify intragenic CNVs. Analytic approaches initially focused on 475 known or candidate PIDD genes but were nonexclusive and further tailored based on clinical data, family history, and immunophenotyping. RESULTS: A likely molecular diagnosis was achieved in 110 (40%) unrelated probands. Clinical diagnosis was revised in about half (60/110) and management was directly altered in nearly a quarter (26/110) of families based on molecular findings. Twelve PIDD-causing CNVs were detected, including 7 smaller than 30 Kb that would not have been detected with conventional diagnostic CNV arrays. CONCLUSION: This high-throughput genomic approach enabled detection of disease-related variants in unexpected genes; permitted detection of low-grade constitutional, somatic, and revertant mosaicism; and provided evidence of a mutational burden in mixed PIDD immunophenotypes.

A potential founder variant in CARMIL2/RLTPR in three Norwegian families with warts, molluscum contagiosum, and T-cell dysfunction.

BACKGROUND: Four patients from three Norwegian families presented with a common skin phenotype of warts, molluscum contagiosum, and dermatitis since early childhood, and various other immunological features. Warts are a common manifestation of human papilloma virus (HPV), but when they are overwhelming, disseminated and/or persistent, and presenting together with other immunological features, a primary immunodeficiency disease (PIDD) may be suspected. METHODS AND RESULTS: The four patients were exome sequenced as part of a larger study for detecting genetic causes of primary immunodeficiencies. No disease-causing variants were identified in known primary immunodeficiency genes or in other disease-related OMIM genes. However, the same homozygous missense variant in CARMIL2 (also known as RLTPR) was identified in all four patients. In each family, the variant was located within a narrow region of homozygosity, representing a potential region of autozygosity. CARMIL2 is a protein of undetermined function. A role in T-cell activation has been suggested and the mouse protein homolog (Rltpr) is essential for costimulation of T-cell activation via CD28, and for the development of regulatory T cells. Immunophenotyping demonstrated reduced regulatory, CD4+ memory, and CD4+ follicular T cells in all four patients. In addition, they all seem to have a deficiency in IFN γ -synthesis in CD4+ T cells and NK cells. CONCLUSIONS: We report a novel primary immunodeficiency, and a differential molecular diagnosis to CXCR4-,DOCK8-,GATA2-,MAGT1-,MCM4-,STK4-,RHOH-,TMC6-, and TMC8-related diseases. The specific variant may represent a Norwegian founder variant segregating on a population-specific haplotype.

cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data.

BACKGROUND: With advances in next generation sequencing technology and analysis methods, single nucleotide variants (SNVs) and indels can be detected with high sensitivity and specificity in exome sequencing data. Recent studies have demonstrated the ability to detect disease-causing copy number variants (CNVs) in exome sequencing data. However, exonic CNV prediction programs have shown high false positive CNV counts, which is the major limiting factor for the applicability of these programs in clinical studies. RESULTS: We have developed a tool (cnvScan) to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets. We assessed the performance of cnvScan on CNV predictions from five different prediction programs using 64 exomes from Primary Immunodeficiency (PIDD) patients, and identified PIDD-causing CNVs in three individuals from two different families. CONCLUSIONS: In summary, cnvScan reduces the time and effort required to detect disease-causing CNVs by reducing the false positive count and providing annotation. This improves the clinical utility of CNV detection in exome data.

Identification of copy number variants from exome sequence data.

BACKGROUND: With advances in next generation sequencing technologies and genomic capture techniques, exome sequencing has become a cost-effective approach for mutation detection in genetic diseases. However, computational prediction of copy number variants (CNVs) from exome sequence data is a challenging task. Whilst numerous programs are available, they have different sensitivities, and have low sensitivity to detect smaller CNVs (1-4 exons). Additionally, exonic CNV discovery using standard aCGH has limitations due to the low probe density over exonic regions. The goal of our study was to develop a protocol to detect exonic CNVs (including shorter CNVs that cover 1-4 exons), combining computational prediction algorithms and a high-resolution custom CGH array. RESULTS: We used six published CNV prediction programs (ExomeCNV, CONTRA, ExomeCopy, ExomeDepth, CoNIFER, XHMM) and an in-house modification to ExomeCopy and ExomeDepth (ExCopyDepth) for computational CNV prediction on 30 exomes from the 1000 genomes project and 9 exomes from primary immunodeficiency patients. CNV predictions were tested using a custom CGH array designed to capture all exons (exaCGH). After this validation, we next evaluated the computational prediction of shorter CNVs. ExomeCopy and the in-house modified algorithm, ExCopyDepth, showed the highest capability in detecting shorter CNVs. Finally, the performance of each computational program was assessed by calculating the sensitivity and false positive rate. CONCLUSIONS: In this paper, we assessed the ability of 6 computational programs to predict CNVs, focussing on short (1-4 exon) CNVs. We also tested these predictions using a custom array targeting exons. Based on these results, we propose a protocol to identify and confirm shorter exonic CNVs combining computational prediction algorithms and custom aCGH experiments.