Follow-up of potential germline variants revealed by diagnostic targeted sequencing (TS) for myelodysplastic syndromes (MDS) has been proposed by clinical guidelines. However, their feasibility and clinical yield in routine MDS practice remain uncertain. We evaluated real-world applicability of systematic germline follow-up in an unselected cohort of 716 patients (median age 74 years) evaluated for MDS. Their diagnostic TS data was analyzed to identify variants in CEBPA, DDX41, ETV6, GATA2, and RUNX1 with a variant allele frequency ≥35%. In total, 98 variants were identified in 87 (12.2%) patients. Germline investigation was possible for 62 patients; for the remaining 25 without biobanked material, medical charts were reviewed. We identified pathogenic/likely pathogenic (P/LP) germline variants in 19 patients (2.7%). Most P/LP variants were found in DDX41 (73.7%), followed by 10.5%, 10.5%, and 5.3% in RUNX1, GATA2, and ETV6, for germline conversion rates between 5.4% and 93.3%. Patients with P/LP variants had a median age at diagnosis of 73 years, with marked male predominance (3.75:1). Most patients were diagnosed with MDS-EB1 or MDS-EB2 (68.4%) and had normal cytogenetics (95%). A review of medical charts in younger patients (<50 years) revealed germline predisposition in other genes in additional five patients, revisiting the prevalence of predisposition to 3.4% overall and to 16.7% in those under 50. Our results show that systematic germline follow-up after diagnostic TS succeeds in identifying predisposition in nearly 3% of patients at a typical adult MDS clinic. Germline testing for genes not routinely assessed by diagnostic TS is required in younger patients.

BACKGROUND:An increased risk of breast cancer has been reported in women with neurofibromatosis type 1 (NF1), especially at younger ages, and NF1-related breast cancer has been associated with poor survival. We performed a large population-based cohort study to estimate the age-related breast cancer risk and survival in Danish and Swedish women with NF1. PATIENTS AND METHODS:We used national registers to identify all women with a diagnosis of NF1 in Denmark and Sweden born between 1930 and 1990 (Denmark) or 1987 (Sweden). Age- and sex-matched comparisons were randomly selected from population registers. Cox proportional hazards models were used to study the association between NF1, breast cancer risk, and overall 5-year mortality after a breast cancer diagnosis. RESULTS:We included 2164 women with NF1 and 71 586 comparisons. A two-fold increased risk of breast cancer was observed in women with NF1 (hazard ratio (HR) 1.94, 95% confidence interval (CI) 1.59-2.36). The strongest association was observed in women between 30 and 39 years of age (HR = 3.98, 95% CI 2.16-7.32). Five-year mortality after a breast cancer diagnosis was higher in women with NF1 (HR = 1.98, 95% CI 1.31-2.99). CONCLUSIONS:Our results suggest that although increased, the risk of breast cancer in women with NF1 is not as high as previously reported, particularly among young women. These findings add to previous data and will contribute to the gathered knowledge needed to accurately address the risk of breast cancer in women with NF1.

We present a spatial transcriptomic atlas of 19 pediatric brain tumor patients spanning nine major and rare diagnoses, including seven relapses, revealing their spatial cellular and molecular organization. Each tumor section resolves into 2 - 4 recurrent spatial archetypes across 11 biological themes, with some mirroring developmental lineage patterns - for example, oligodendrocyte-lineage programs in pilocytic astrocytomas. Spatially inferred copy-number analysis identifies relapse-associated putative clones. In one rare embryonal tumor, spatial niches in the primary tumor harboring putative clones colocalized with an archetype enriched for nervous system development and glioblast-lineage programs. In one ependymoma and one pilocytic astrocytoma, relapse-associated putative clones preferentially localized to the vasculature, suggesting regrowth during relapse may be seeded by clonal selection of residual tumor cells within specialized microenvironmental niches. This resource provides an open-access spatially resolved map via an interactive viewer to inform research on pediatric brain tumor ecosystems, relapse biology, and therapeutic strategies.

Abstract Background As clinical genetics evolves towards the broader field of clinical genomics, the diagnostic approach to rare diseases is undergoing a paradigm shift. This transformation has significantly impacted rare disease diagnostics, increasingly done through gene panels, whole exome and whole genome sequencing. To advance beyond genomics into precision medicine and encompass the breadth of relevant clinical scenarios, a true systems shift is required that challenges conventional barriers and enables the formation of cross-disciplinary, integrated environments. Methods The Genomic Medicine Center Karolinska Rare Diseases (GMCK-RD) has, for the past 10 years, brought together healthcare and academia to enable large-scale genome sequencing in a clinical diagnostics context. Within GMCK-RD, experts from various medical disciplines collaborate closely with clinical geneticists, bioinformaticians, and researchers to integrate genome sequencing into healthcare. Results In total, 15 644 individuals with suspected rare diseases were analyzed using clinical genome sequencing, including pediatric (48%), adult (48%) and fetal (4%) samples. The overall diagnostic yield was 22.6%, providing a diagnosis for 3 538 individuals with variants in 1 570 genes. Moreover, a rare disease analysis tool suite developed and validated in house includes a bioinformatic pipeline allowing for comprehensive data analysis covering a wide range of genetic variants including SNVs, INDELs, repeat expansions, uniparental disomies, balanced and unbalanced structural variants as well as insertions of mobile elements. Results are visualized and interpreted in custom-developed decision support systems functioning as an interpretation portal as well as a knowledge-base to capture the interpretation efforts made in a structured format allowing future secondary use. Conclusions Altogether, GMCK-RD has shifted healthcare in our region towards precision diagnostics. We emphasize the need to transition from traditional clinical genetic diagnostics to a broader clinical genomics approach. Beyond this shift, we advocate integrating genomics with specialized clinical and laboratory medicine, a concept pioneered for inborn errors of metabolism (IEM) with stepwise spread to additional disease groups. In this model, a multidisciplinary unit combines screening, targeted diagnostics, individualized treatment, and long-term patient follow-up. Here we provide a road map and guide for inspiration for centers aiming to implement genome sequencing in rare disease diagnostics.

Introduction:A trio analysis refers to the strategy of exome or genome sequencing of DNA from a patient, as well as parents, in order to identify the genetic cause of a disorder or syndrome. Methods:During the last 10 years, we have successfully applied exome or genome sequencing and performed trio analysis for 1,000 patients. Results:Overall, 39% of the patients were diagnosed, with the detection of causative variant(s). The variants were located in 308 different genes. Autosomal dominant de novo variants were detected in 46% of the solved cases. Detection rates were highest in patients with a syndromic neurodevelopmental disorder (46%) and in patients with known consanguinity (59%). Even for patients previously analyzed as singletons, using a pre-defined gene panel, a consecutive trio analysis resulted in the detection of a causative variant in 30%. Discussion:A major advantage of trio analysis is the immediate identification of de novo variants as well as confirmation of compound heterozygosity. Additionally, inherited variants from a healthy parent can be dismissed as non-disease causing. The trio strategy enables analysis of a high number of genes-or even the whole genome-simultaneously. The strengths of a trio analysis, in combination with analysis of genome sequence data, allows for the detection of a wide range of genetic aberrations. This enables a high diagnostic yield, even in previously analyzed patients. Our current protocol for trio analysis is based on genome sequencing data, which allows for simultaneous detection of single nucleotide variants, insertion/deletions, structural variants, expanded short tandem repeats, as well as a copy number analysis corresponding to an array-CGH, and analysis regarding SMN1 gene copies.

Variables significant for survival analysis in univariate analysis

Polygenic risk scores (PRS) are not yet standard in clinical risk assessments for familial breast cancer in Sweden. This study evaluated the distribution and impact of an established PRS (PRS313) in women undergoing clinical sequencing for hereditary breast cancer. We integrated PRS313 into a hereditary breast cancer gene panel used in clinical practice and calculated scores for 262 women. Comparisons were made between women with unilateral and contralateral breast cancer, as well as those with and without pathogenic variants in breast cancer susceptibility genes. PRS313 was significantly higher in women with contralateral breast cancer (median + 1.3 SD, n = 33, P = 8e-9) compared to those with unilateral disease (median + 0.66 SD, n = 197, P = 5e-10). Elevated PRS313 was also observed in women with pathogenic variants, including those in high-penetrance genes (+ 0.65 SD) and moderate-penetrance genes (+ 0.93 SD), compared to population controls. Incorporating PRS313 into a clinical risk model (BOADICEA), shifted 20

MDSRS+ event free survival (EFS) stratified by estimated MEP percentage in the four genetic subgroups (A-D).

UMAP plot of MDSRS+ bone marrow CD34 mononuclear cells transcriptomes. Each point is one patient, overlaid with results from unsupervised clustering.

Due to their intrinsic heterogeneity and plasticity, pediatric brain tumors present highly complex clinical challenges. To provide insight into the molecular scene of these tumors, we generated spatial transcriptomics data from 19 distinct patients, 7 of which suffered a relapse of the disease. In this cohort, spanning 59 tissue sections across 8 diagnoses and 4 tumor grades, we recovered diagnosis-specific gene expression patterns that could be linked to processes characteristic of developmental stages. We also identified between 2 to 4 spatial archetypal niches per section, which could then be related to 11 main biological themes, and to distinct celltype-like transcriptomic signatures. For example, we noted strong spatial correlations between developmental archetypes and oligodendrocyte lineage signal in pilocytic astrocytoma. Lastly, we utilised spatially inferred copy-number variants for the profiling of relapse-associated tentative tumor clones. These clones were then related via spatial geographical analysis to regions with strong blood vessel signatures. Overall, these results provide vital details into the progression and maintenance of pediatric brain tumors, offering novel edges to be exploited in personalized medicine.

PURPOSE:In a multicenter prospective cohort study, we assessed the diagnostic yield of the Nordic guidelines for germline investigation in myeloid neoplasms and mapped the spectrum of inherited and somatic variants. EXPERIMENTAL DESIGN:Eighty-five patients (acute myeloid leukemia, n = 38; myelodysplastic syndromes, n = 26; thrombocytopenia, n = 14; and other, n = 7) fulfilling the Nordic criteria for germline investigation, based on (i) medical history or family history suggestive of a germline condition and (ii) relevant findings from the somatic diagnostic work-up (CytoMol), were recruited. The genetic analysis included enhanced whole-exome sequencing (n = 69) or sequencing of specific variants of interest (n = 16). RESULTS:Pathogenic or likely pathogenic (P/LP) germline variants were identified in 35% of patients (30/85). The diagnostic yield varied from 6% (1/16) in the family history group to 52% (17/33) in the CytoMol group. Germline DDX41 P/LP variants were the most frequent finding (13/30, 43% of all positive cases) almost exclusively found within the CytoMol group (12/13). Seven variants of unknown significance were also detected (TERT n = 2 and DDX41, RTEL1, ETV6, PARN, and SAMD9 n = 1). Five patients carried a P/LP variant in genes associated with another hereditary cancer syndrome (BRCA1 n = 3; PALB2 n = 1; and CHEK2; n = 1). Survival analysis showed a trend for longer survival among patients with acute myeloid leukemia and confirmed or suspected germline predisposition that underwent allogeneic stem cell transplantation. CONCLUSIONS:The implementation of the Nordic guidelines in a prospective Swedish cohort results in a high overall diagnostic yield (35%), proving the feasibility and utility of these or similar guidelines in a clinical setting.

Cumulative proportion of principal components derived from principal component analysis. The first 14 explain 2/3 of the total variability.

To explore the relation between disease characteristics, comorbidities, mutations and overall survival (OS) in chronic myelomonocytic leukaemia (CMML), we collected data from a population-based cohort of 149 consecutive patients. TET2 mutation (TET2(MT)) was associated with higher haemoglobin, less leucocytosis and longer OS compared to no TET2(MT) (TET2(WT)), despite patients being significantly older. Patients with multihit TET2(MT) had the most favourable outcome (HR 0.55, CI 0.35-0.88, p < 0.05). Multihit TET2(MT) was associated with lower lactate dehydrogenase and less monocytosis, indicating multihit TET2(MT) as a separate disease entity. Autoimmune disease (AID) was present in 33.6% of patients, with no association to any mutations. In multivariable analysis, the number of TET2(MT) was demonstrated to be an independent factor associated with improved OS, and RUNX1(MT), myeloproliferative CMML (CMML-MP), ECOG >0 and transfusion dependence remained significant adverse factors. Internal validation including cross-validation and correction for optimism consistently demonstrated that a prognostic model containing the number of TET2(MT), RUNX1, CMML-MP, ECOG >0 and transfusion dependence showed better calibration, discrimination and overall performance than CPSS-Mol in predicting OS. Importantly, the addition of TET2 mutation status to CPSS-Mol also improved the CPSS-Mol score performance. Taken together, TET2(MT) status, especially multihit TET2(MT), defines a specific CMML phenotype and should be considered in future prognostic scores.

– Results from Gene Ontology enrichment analysis (molecular function dataset) for the top 250 contributors of principal component 1 (PC1)

Clonal hierarchy analysis of SF3B1-SRSF2 co-mutated cases. A. Results from the hierarchical rank analysis of mutations detected by DNAseq in the 4 cases harboring both SF3B1 and SRSF2 mutation using Pyclone. The analysis was also performed using DPClust, which provided converging results (data not shown). Tumor cell fraction (axes) for each detected clone and its 95% confidence interval (dot size) is represented in a scatter-plot, using different color according to the cluster driving mutation (SF3B1, red; SRSF2, blue; other drivers, gray). SF3B1 dominancy in MDS392 and MDS 640, together with the SRSF2 large clone size are suggestive of both splicing factor mutations in the same clone. On the contrary, MDS694 and MDS965 had a dominant SF3B1 clone associated with a very little and probably independent SRSF2 secondary clone. B. Results from single-cell derived colony-forming unit (CFU) genotyping confirming the concurrent double splicing factor mutations within the same clone in patient MDS382 and MDS640. CFU experiment was not carried out for the other two cases because of the very low probability of SF3B1/SRSF2 double positive clone identification, as already suggested by current data in the literature related to the presence of SF3B1K700E mutation (ref. 1).

Treatment. Number of cases that underwent to each treatment category and the associated hazard-ratio for death is reported for each genetic subgroup and for the whole cohort.

Prognostic effect of genomic and transcriptomic analyses on MDSRS+ outcome. Overall survival (OS) stratified by genomic (A), transcriptomic classification (B) and estimated MEP percentage (C) in all MDSRS+ (A-C) and MDS-RS-SLD/MLD only (D-F). Multivariable Cox proportional hazard model for OS in all MDSRS+ including age, IPSS-mol score and estimated MEP percentage as continuous variables (G). OS stratified by estimated MEP percentage and IPSS-mol risk category (full representation of the 6 IPSS-mol categories shown in Supplemental Figure 21B).