BackgroundAutoantibodies against self-antigens have been associated not only with autoimmune diseases, but also with cancer and are even found in healthy individuals. The mechanism causing the autoantibody response remains elusive for the majority of the immunogenic antigens. To deepen the understanding of autoantibody responses, we ask whether natural-occurring, autoimmunity-associated and tumor-associated antigens have structural or biological features related to the immune response. To this end, we have carried out the most comprehensive in-silicio study of different groups of autoantigens including large antigen sets identified by our groups combined with publicly available antigen sets.ResultsWe found evidence for an enrichment of genes with a larger exon length increasing the probability of the occurrence of potential immunogenic features such as mutations, SNPs, immunogenic sequence patterns and structural epitopes, or alternative splicing events. While SNPs seem to play a more central role in autoimmunity, somatic mutations seem to be stronger enriched in tumor-associated antigens. In addition, antigens of autoimmune diseases are different from other antigen sets in that they appear preferentially secreted, have frequently an extracellular location, and they are enriched in pathways associated with the immune system. Furthermore, for autoantibodies in general, we found enrichment of sequence-based properties including coiled-coils motifs, ELR motifs, and Zinc finger DNA-binding motifs. Moreover, we found enrichment of proteins binding to proteins or nucleic acids including RNA and enrichment of proteins that are part of ribosome or spliceosome. Both, homologies to proteins of other species and an enrichment of ancient protein domains indicate that immunogenic proteins are evolutionary conserved and that mimicry might play a central role.ConclusionsOur results provide evidence that proteins which i) are evolutionary conserved, ii) show specific sequence motifs, and iii) are part of cellular structures show an increased likelihood to become autoimmunogenic.

BackgroundAmyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder. About 90% of ALS cases are without a known genetic cause. The human endogenous retrovirus multi-copy HERV-K(HML-2) group was recently reported to potentially contribute to neurodegeneration and disease pathogenesis in ALS because of transcriptional upregulation and toxic effects of HML-2 Envelope (Env) protein. Env and other proteins are encoded by some transcriptionally active HML-2 loci. However, more detailed information is required regarding which HML-2 loci are transcribed in ALS, which of their proteins are expressed, and differences between the disease and non-disease states.MethodsFor brain and spinal cord tissue samples from ALS patients and controls, we identified transcribed HML-2 loci by generating and mapping HML-2-specific cDNA sequences. We predicted expression of HML-2 env gene-derived proteins based on the observed cDNA sequences. Furthermore, we determined overall HML-2 transcript levels by RT-qPCR and investigated presence of HML-2 Env protein in ALS and control tissue samples by Western blotting.ResultsWe identified 24 different transcribed HML-2 loci. Some of those loci are transcribed at relatively high levels. However, significant differences in HML-2 loci transcriptional activities were not seen when comparing ALS and controls. Likewise, overall HML-2 transcript levels, as determined by RT-qPCR, were not significantly different between ALS and controls. Indeed, we were unable to detect full-length HML-2 Env protein in ALS and control tissue samples despite reasonable sensitivity. Rather our analyses suggest that a number of HML-2 protein variants other than full-length Env may potentially be expressed in ALS patients.ConclusionsOur results expand and refine recent publications on HERV-K(HML-2) and ALS. Some of our results are in conflict with recent findings and call for further specific analyses. Our profiling of HML-2 transcription in ALS opens up the possibility that HML-2 proteins other than canonical full-length Env may have to be considered when studying the role of HML-2 in ALS disease.Electronic supplementary materialThe online version of this article (10.1186/s13024-018-0275-3) contains supplementary material, which is available to authorized users.

Glioblastoma multiforme (GBM) is the most aggressive and malignant subtype of human brain tumors. While a family clustering of GBM has long been acknowledged, relevant hereditary factors still remained elusive. Exome sequencing of families offers the option to discover respective genetic factors.We sequenced blood samples of one of the rare affected families: while both parents were healthy, both children were diagnosed with GBM. We report 85 homozygous non-synonymous single nucleotide variations (SNVs) in both siblings that were heterozygous in the parents. Beyond known key players for GBM such as ERBB2, PMS2, or CHI3L1, we identified over 50 genes that have not been associated to GBM so far. We also discovered three accumulative effects potentially adding to the tumorigenesis in the siblings: a clustering of multiple variants in single genes (e.g. PTPRB, CROCC), the aggregation of affected genes on specific molecular pathways (e.g. Focal adhesion or ECM receptor interaction) and genomic proximity (e.g. chr22.q12.2, chr1.p36.33). We found a striking accumulation of SNVs in specific genes for the daughter, who developed not only a GBM at the age of 12 years but was subsequently diagnosed with a pilocytic astrocytoma, a common acute lymphatic leukemia and a diffuse pontine glioma.The reported variants underline the relevance of genetic predisposition and cancer development in this family and demonstrate that GBM has a complex and heterogeneous genetic background. Sequencing of other affected families will help to further narrow down the driving genetic causes for this disease.

High-throughput sequencing opens avenues to find genetic variations that may be indicative of an increased risk for certain diseases. Linking these genomic data to other “omics” approaches bears the potential to deepen our understanding of pathogenic processes at the molecular level. To detect novel single nucleotide polymorphisms (SNPs) for glioblastoma multiforme (GBM), we used a combination of specific target selection and next generation sequencing (NGS). We generated a microarray covering the exonic regions of 132 GBM associated genes to enrich target sequences in two GBM tissues and corresponding leukocytes of the patients. Enriched target genes were sequenced with Illumina and the resulting reads were mapped to the human genome. With this approach we identified over 6000 SNPs, including over 1300 SNPs located in the targeted genes. Integrating the genome-wide association study (GWAS) catalog and known disease associated SNPs, we found that several of the detected SNPs were previously associated with smoking behavior, body mass index, breast cancer and high-grade glioma. Particularly, the breast cancer associated allele of rs660118 SNP in the gene SART1 showed a near doubled frequency in glioblastoma patients, as verified in an independent control cohort by Sanger sequencing. In addition, we identified SNPs in 20 of 21 GBM associated antigens providing further evidence that genetic variations are significantly associated with the immunogenicity of antigens.

Although an increased level of the prostate-specific antigen can be an indication for prostate cancer, other reasons often lead to a high rate of false positive results. Therefore, an additional serological screening of autoantibodies in patients’ sera could improve the detection of prostate cancer. We performed protein macroarray screening with sera from 49 prostate cancer patients, 70 patients with benign prostatic hyperplasia and 28 healthy controls and compared the autoimmune response in those groups. We were able to distinguish prostate cancer patients from normal controls with an accuracy of 83.2%, patients with benign prostatic hyperplasia from normal controls with an accuracy of 86.0% and prostate cancer patients from patients with benign prostatic hyperplasia with an accuracy of 70.3%. Combining seroreactivity pattern with a PSA level of higher than 4.0 ng/ml this classification could be improved to an accuracy of 84.1%. For selected proteins we were able to confirm the differential expression by using luminex on 84 samples. We provide a minimally invasive serological method to reduce false positive results in detection of prostate cancer and according to PSA screening to distinguish men with prostate cancer from men with benign prostatic hyperplasia.