T-cell lymphoblastic lymphoma (T-LBL) is a heterogeneous malignancy of lymphoblasts committed to T-cell lineage. Dismal outcomes (15-30%) in case of T-LBL relapses warrants for establishing risk-based treatment in future. This is a first comprehensive, systematic, integrated genome-wide analysis including relapse cases aimed towards identifying molecular markers of prognostic relevance for T-LBL. NOTCH1 was identified as putative driver for T-LBL. Activated NOTCH/PI3K-AKT signaling axis and alterations in cell cycle regulators constitutes the core oncogenic program for T-LBL. Mutated KMT2D was identified as a prognostic marker. The cumulative incidence of relapse was 47±17% in patients with KMT2D mutations compared with 14±3% in KMT2D wildtype. Structural analysis of the mutated domains of KMT2D revealed plausible impact on the structure and functional consequences. These findings provide new insights into the pathogenesis of T-LBL including high translational potential. The ongoing trial LBL 2018 (NCT04043494) allows prospective validation and subsequent fine-tuning of the stratification criteria for T-LBL risk groups to improve survival of the pediatric patients.

Epstein–Barr virus (EBV) infection precedes multiple sclerosis (MS) pathology and cross-reactive antibodies might link EBV infection to CNS autoimmunity. As an altered anti-EBV T cell reaction was suggested in MS, we queried peripheral blood T cell receptor β chain (TCRβ) repertoires of 1,395 MS patients, 887 controls, and 35 monozygotic, MS-discordant twin pairs for multimer-confirmed, viral antigen–specific TCRβ sequences. We detected more MHC-I–restricted EBV-specific TCRβ sequences in MS patients. Differences in genetics or upbringing could be excluded by validation in monozygotic twin pairs discordant for MS. Anti–VLA-4 treatment amplified this observation, while interferon β– or anti-CD20 treatment did not modulate EBV-specific T cell occurrence. In healthy individuals, EBV-specific CD8+ T cells were of an effector-memory phenotype in peripheral blood and cerebrospinal fluid. In MS patients, cerebrospinal fluid also contained EBV-specific central-memory CD8+ T cells, suggesting recent priming. Therefore, MS is not only preceded by EBV infection, but also associated with broader EBV-specific TCR repertoires, consistent with an ongoing anti-EBV immune reaction in MS.

Peripheral central nervous system (CNS)–infiltrating lymphocytes are a hallmark of relapsing-remitting multiple sclerosis. Tissue-resident memory T cells (T RM ) not only populate the healthy CNS parenchyma but also are suspected to contribute to multiple sclerosis pathology. Because cerebrospinal fluid (CSF), unlike CNS parenchyma, is accessible for diagnostics, we evaluated whether human CSF, apart from infiltrating cells, also contains T RM cells and CNS-resident myeloid cells draining from the parenchyma or border tissues. Using deep generative models, we integrated 41 CSF and 14 CNS parenchyma single-cell RNA sequencing (scRNAseq) samples from eight independent studies, encompassing 120,629 cells. By comparing CSF immune cells collected during multiple sclerosis relapse with cells collected during therapeutic very late antigen–4 blockade, we could identify immune subsets with tissue provenance across multiple lineages, including CNS border–associated macrophages, CD8 and CD4 T RM cells, and tissue-resident natural killer cells. All lymphocytic CNS-resident cells shared expression of CXCR6 but showed differential ITGAE expression (encoding CD103). A common signature defined CD4 and CD8 T RM cells by expression of ZFP36L2 , DUSP1 , and ID2 . We further developed a user interface–driven application based on this analysis framework for atlas-level cell identity transfer onto new CSF scRNAseq data. Together, these results define CNS-resident immune cells involved in multiple sclerosis pathology that can be detected and monitored in CSF. Targeting these cell populations might be promising to modulate immunopathology in progressive multiple sclerosis and other neuroinflammatory diseases.

Low incidence and molecular heterogeneity of pediatric T‐cell lymphoblastic lymphoma (T‐LBL) require an international, large‐scale effort to identify novel clinical biomarkers. The ongoing international clinical trial LBL2018 (NCT04043494) represents an ideal opportunity to implement a common analytic approach. Targeted next‐generation sequencing is well‐suited for this purpose; however, selection of relevant target genes for T‐LBL remains subject of ongoing debates. Our group has recently designed and evaluated a first target panel of 80 candidate genes for T‐LBL. The present study aimed at developing a novel optimized gene panel for large‐scale application and to promote an international agreement on a common core panel. Small sequence variants obtained from our former study were systematically analyzed and classified with regards to pathogenic relevance, to prioritize candidate genes. Additional genes were curated from literature and online databases for a more comprehensive analysis of relevant functions and signaling pathways. The new target panel TGP‐T‐LBL entails 84 candidate genes which are key actors in NOTCH, PI3K‐AKT, JAK–STAT, RAS signaling, epigenetic regulation, transcription, DNA repair, cell cycle regulation, and ribosomal function. From our former gene panel, 35 out of 80 candidate genes were selected for the novel panel. Forty‐six out of 84 genes are currently being analyzed in the ongoing international trial LBL2018. Exploratory analysis of prognostic relevance on mutation‐level suggested a potential association of PIK3CA variants c.1624G>A(p.Glu542Lys) and c.1633G>A(p.Glu545Lys) to occurrence of relapse, emphasizing particular relevance of mutation analysis in PI3K‐AKT signaling. Our approach promotes comprehensive and clinically relevant mutational profiling of pediatric T‐LBL.

Background: Next-Generation Sequencing (NGS) enables large-scale and cost-effective sequencing of genetic samples in order to detect genetic variants. After successful use in research-oriented projects, NGS is now entering clinical practice. Consequently, variant analysis is increasingly important to facilitate a better understanding of disease entities and prognoses. Furthermore, variant calling allows to adapt and optimize specific treatments of individual patients, and thus is an integral part of personalized medicine. However, the analysis of NGS data typically requires a number of complex bioinformatics processing steps. A flexible and reliable software that combines the variant analysis process with a simple, user-friendly interface is therefore highly desirable, but still lacking. Results: With AMLVaran (AML Variant Analyzer), we present a web-based software, that covers the complete variant analysis workflow of targeted NGS samples. The software provides a generic pipeline that allows free choice of variant calling tools and a flexible language (SSDL) for filtering variant lists. AMLVaran's interactive website presents comprehensive annotation data and includes curated information on relevant hotspot regions and driver mutations. A concise clinical report with rule-based diagnostic recommendations is generated. An AMLVaran configuration with eight variant calling tools and a complex scoring scheme, based on the somatic variant calling pipeline appreci8, was used to analyze three datasets from AML and MDS studies with 402 samples in total. Maximum sensitivity and positive predictive values were 1.0 and 0.96, respectively. The tool's usability was found to be satisfactory by medical professionals. Conclusion: Coverage analysis, reproducible variant filtering and software usability are important for clinical assessment of variants. AMLVaran performs reliable NGS variant analyses and generates reports fulfilling the requirements of a clinical setting. Due to its generic design, the software can easily be adapted for use with different targeted panels for other tumor entities, or even for whole-exome data. AMLVaran has been deployed to a public web server and is distributed with Docker scripts for local use.