Search

Background. Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ Transplant (B-HOT) panel and a customized antibody-mediated rejection (AMR)-specific NanoString nCounter Elements (Elements) panel. Additionally, we explored the potential for the classification of KTx rejection building and testing a classifier within our dataset. Methods. Ninety-six formalin-fixed paraffin-embedded KTx biopsies were retrieved from the archives of the ErasmusMC Rotterdam and the University Hospital Cologne. Biopsies with AMR, borderline or T cell-mediated rejections (BLorTCMR), and no rejection were compared using the B-HOT and Elements panels. Results. High correlation between gene expression levels was found when comparing the 2 chemistries pairwise (r = 0.76-0.88). Differential gene expression (false discovery rate; P < 0.05) was identified in biopsies diagnosed with AMR (B-HOT: 294; Elements: 76) and BLorTCMR (B-HOT: 353; Elements: 57) compared with no rejection. Using the most predictive genes from the B-HOT analysis and the Element analysis, 2 least absolute shrinkage and selection operators-based regression models to classify biopsies as AMR versus no AMR (BLorTCMR or no rejection) were developed achieving an receiver-operating-characteristic curve of 0.994 and 0.894, sensitivity of 0.821 and 0.480, and specificity of 1.00 and 0.979, respectively, during cross-validation. Conclusions. Transcriptomic analysis is feasible on KTx biopsies previously used for diagnostic purposes. The B-HOT panel has the potential to differentiate AMR from BLorTCMR or no rejection and could prove valuable in aiding kidney transplant rejection classification.

Supplementary Figure 7 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Figure 5 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Figure 10 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Figure 6 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Figure 8 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Figure 3 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Treatment decisions in patients rely mainly on histologic classification and clinical parameters. However, differences between histologic subclasses and grades are subtle, and classifying gliomas is subject to a large interobserver variability. To improve current classification standards, we have performed gene expression profiling on a large cohort of glioma samples of all histologic subtypes and grades. We identified seven distinct molecular subgroups that correlate with survival. These include two favorable prognostic subgroups (median survival, >4.7 years), two with intermediate prognosis (median survival, 1–4 years), two with poor prognosis (median survival

Supplementary Figure 2 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Figure 4 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Tables 1-6 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Figure 9 from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Supplementary Methods from Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

BACKGROUND Major obstacles that have impeded the development of effective new therapies for GBM include inter- and intratumoral heterogeneity, the blood-brain-barrier and use of sub-optimal cell line-based preclinical models. Taking these hurdles into account, we have set up a patient-derived GBM drug-screening platform. We optimized protocols to improve cell culture success rate and retrospectively assessed the predictive power of our assay for patient response to TMZ. A large panel of GBM cells was screened for sensitivity to available oncological agents. Drugs of interest were selected based on favorable physicochemical properties for BBB crossing and potent activity in (a subset of) GBM cultures. Finally, we determined the success rate of performing a small-scale screen with 20 selected agents within 4 weeks of receiving tumor tissue. RESULTS By combining both CUSA and tissue piece-derived dissociation protocols, culture success increased to 95%, ensuring representation of the near-complete spectrum of GBM subtypes. Single-cell sequencing studies confirmed heterogeneity in our low-passage cell cultures. In vitro screening of TMZ on a large cohort (n = 55) identified 3 response categories (responders/intermediates/non-responders) for which Cox regression analysis revealed significantly different overall survival curves of corresponding patients. Screening of 107 FDA-approved anticancer agents on 45 GBM cultures underscored the tremendous intertumoral heterogeneity in drug sensitivities. We identified 20 potent agents each effective at clinically-achievable concentrations in (a subset of) GBM cultures and having favorable BBB penetration properties (CNS-MPO score). Screening of these agents on a per patient basis within 4 weeks of receiving tissue was successful in 18 out of 24 (75%) tested tumors. In the remaining cases the tumor cells grew very slowly and longer culture times were required. CONCLUSION Our drug screening platform offers a tool to predict TMZ response and assess sensitivity to candidate treatments, either for GBM subsets or on a per patient basis.

The prevalence of diabetic metabolic derangement (DMetD) has increased dramatically over the last decades. Although there is increasing evidence that DMetD is associated with cardiac dysfunction, the early DMetD-induced myocardial alterations remain incompletely understood. Here, we studied early DMetD-related cardiac changes in a clinically relevant large animal model. DMetD was established in adult male Göttingen miniswine by streptozotocin injections and a high-fat, high-sugar diet, while control animals remained on normal pig chow. Five months later left ventricular (LV) function was assessed by echocardiography and hemodynamic measurements, followed by comprehensive biochemical, molecular and histological analyses. Robust DMetD developed, evidenced by hyperglycemia, hypercholesterolemia and hypertriglyceridemia. DMetD resulted in altered LV nitroso-redox balance, increased superoxide production—principally due to endothelial nitric oxide synthase (eNOS) uncoupling—reduced nitric oxide (NO) production, alterations in myocardial gene-expression—particularly genes related to glucose and fatty acid metabolism—and mitochondrial dysfunction. These abnormalities were accompanied by increased passive force of isolated cardiomyocytes, and impaired LV diastolic function, evidenced by reduced LV peak untwist velocity and increased E/e′. However, LV weight, volume, collagen content, and cardiomyocyte cross-sectional area were unchanged at this stage of DMetD. In conclusion, DMetD, in a clinically relevant large-animal model results in myocardial oxidative stress, eNOS uncoupling and reduced NO production, together with an altered metabolic gene expression profile and mitochondrial dysfunction. These molecular alterations are associated with stiffening of the cardiomyocytes and early diastolic dysfunction before any structural cardiac remodeling occurs. Therapies should be directed to ameliorate these early DMetD-induced myocardial changes to prevent the development of overt cardiac failure.

Background Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non–poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints. Results We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA–minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG–positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq. Conclusion By using the full potential of non–poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.

INTRODUCTION Little progress has been made in the development of effective new therapies for glioblastoma (GBM) the past decades. Fresh patient-derived GBM cell culture models have become the gold standard for GBM drug discovery and development. One of the major obstacles in identifying novel candidate drugs against GBM remains the blood-brain barrier (BBB). Therefore, it is crucial to select drugs with favourable physicochemical properties to cross BBB and reach the tumour tissue in therapeutically effective concentrations. In current drug repurposing approach, we evaluated available anti-cancer agents in our patient-derived drug screening platform against GBM. METHODS The FDA-approved Oncology Drug Set II library was tested on 45 primary GBM cell cultures. We developed a drug shortlisting pipeline combining efficacy data with pharmacodynamic and pharmacokinetic characteristics of each compound. The therapeutic efficacy of the selected agent was assessed in an orthotopic mouse PDX model, while penetration into the CNS by LC/MS/MS. RESULTS Omacetaxine mepesuccinate (OMA) was ranked as one of the most promising candidates applying our drug selection approach. In vitro, OMA revealed anti-tumour activity at IC50 values well-below reported Cmax plasma values in approximately 80% of GBM cultures. NanoString nCounter analysis, revealed DNA damage repair as the main pathway involved in OMA’s anti-tumour effect. Activation of caspase 3/7 activity and decrease of glioma cell invasiveness were also linked to its anti-tumour effect. In vivo, 1mg/kg dose of OMA was found to reach the brain tumour tissue in concentrations similar to the reported IC50 values in vitro. No adverse reactions were noted and a survival benefit was observed in a proportion of the treated mice. CONCLUSIONS At 1 mg/kg, OMA reaches the tumour brain tissue in therapeutically effective concentrations in mice while a moderate therapeutic benefit was observed. Additional in vivo experiments are ongoing investigating higher dosages of OMA and longer exposure.

BACKGROUND The dismal prognosis of glioblastoma (GBM) patients, with a median survival of less than 15 months despite maximal therapy urgently warrants new therapeutic approaches. Clinical trials employing oncolytic viruses (OVs) have shown encouraging results, however, in each OV clinical trial only a small subset of patients responded to treatment. As inter-tumoral heterogeneity has been the key challenge in treating GBM, we hypothesized that development of an in vitro co-culture model for assessment of viral replication and subsequent immune response might ultimately predict in vivo OV efficacy for individual GBM patients. METHODS 20 patient-derived GBM cell cultures were tested with dose-ranges of two clinically relevant OVs (DNX2401 and rQnestin34.5 V1) to determine the EC50 values (half-maximal effective concentration). To discriminate between responders and non-responders six of these cultures were infected using MOI 10 for DNX2401 and 0.25 for rQnestin34.5V1, and co-cultured with autologous PBMCs. OV-induced changes in gene and protein expression of immune associated genes were assessed using targeted gene expression (NanoString Technology) and ELISA. RESULTS DNX2401 EC50 values ranged from 0.35 to > 600 and from 0.04 to 1.77 for rQnestin34.5V1. Induction of pro-inflammatory cytokines and chemokines differed per virus and per patient. Enhanced OV infection or oncolysis efficiency did not lead to increased levels of IFNγ production. Importantly, longer exposure to dexamethasone prior to PBMC isolation correlated with suppressed IFNγ production. CONCLUSION We established an autologous GBM cells/PBMCs co-culture model which reflects inter-tumoral heterogeneity in terms of cytokine induction and virus-specific changes in gene and protein expression upon OV infection. Immune activation is not directly related to degree of infection or oncolysis and can be hampered by prolonged prior dexamethasone use. These first results support our hypothesis that improved prediction of response rates in oncolytic virotherapy for GBM may require a personalized approach with an in vitro test system.

Background: Patients with locally advanced pancreatic cancer (LAPC) are treated with chemotherapy. In selected cases, stereotactic body radiotherapy (SBRT) can be added to the regimen. We hypothesized that adding an adjuvant containing a heat-killed mycobacterium (IMM-101) to SBRT may lead to beneficial immuno-modulatory effects, thereby improving survival. This study aims to investigate the safety of adding IMM-101 to SBRT and to investigate the immuno-modulatory effects of the combination treatment in the peripheral blood of LAPC patients. Methods: LAPC patients were treated with SBRT (40 Gy) and six intradermal vaccinations of one milligram IMM-101. The primary endpoint was an observed toxicity rate of grade 4 or higher. Targeted gene-expression profiling and multicolor flow cytometry were performed for longitudinal immune-monitoring of the peripheral blood. Results: Twenty patients received study treatment. No treatment-related adverse events of grade 4 or higher occurred. SBRT/IMM-101 treatment induced a transient decrease in different lymphocyte subsets and an increase in CD14+CD16−CD11b+HLA−DRlow myeloid-derived suppressor cells. Importantly, treatment significantly increased activated ICOS+, HLA-DR+ and Ki67+PD1+ T and NK cell frequencies. This was not accompanied by increased levels of most inhibitory markers, such as TIM-3 and LAG-3. Conclusions: Combination therapy with SBRT and a heat-killed mycobacterium vaccine was safe and had an immune-stimulatory effect.

Lower respiratory tract infections (LRTIs) in children are common and, although often mild, a major cause of mortality and hospitalization. Recently, the respiratory microbiome has been associated with both susceptibility and severity of LRTI. In this current study, we combined respiratory microbiome, viral, and clinical data to find associations with the severity of LRTI. Nasopharyngeal aspirates of children aged one month to five years included in the STRAP study (Study to Reduce Antibiotic prescription in childhood Pneumonia), who presented at the emergency department (ED) with fever and cough or dyspnea, were sequenced with nanopore 16S-rRNA gene sequencing and subsequently analyzed with hierarchical clustering to identify respiratory microbiome profiles. Samples were also tested using a panel of 15 respiratory viruses and Mycoplasma pneumoniae, which were analyzed in two groups, according to their reported virulence. The primary outcome was hospitalization, as measure of disease severity. Nasopharyngeal samples were isolated from a total of 167 children. After quality filtering, microbiome results were available for 54 children and virology panels for 158 children. Six distinct genus-dominant microbiome profiles were identified, with Haemophilus-, Moraxella-, and Streptococcus-dominant profiles being the most prevalent. However, these profiles were not found to be significantly associated with hospitalization. At least one virus was detected in 139 (88%) children, of whom 32.4% had co-infections with multiple viruses. Viral co-infections were common for adenovirus, bocavirus, and enterovirus, and uncommon for human metapneumovirus (hMPV) and influenza A virus. The detection of enteroviruses was negatively associated with hospitalization. Virulence groups were not significantly associated with hospitalization. Our data underlines high detection rates and co-infection of viruses in children with respiratory symptoms and confirms the predominant presence of Haemophilus-, Streptococcus-, and Moraxella-dominant profiles in a symptomatic pediatric population at the ED. However, we could not assess significant associations between microbiome profiles and disease severity measures.

Background Bacterial plasmids often carry antibiotic resistance genes and are a significant factor in the spread of antibiotic resistance. The ability to completely assemble plasmid sequences would facilitate the localization of antibiotic resistance genes, the identification of genes that promote plasmid transmission and the accurate tracking of plasmid mobility. However, the complete assembly of plasmid sequences using the currently most widely used sequencing platform (Illumina-based sequencing) is restricted due to the generation of short sequence lengths. The long-read Oxford Nanopore Technologies (ONT) sequencing platform overcomes this limitation. Still, the assembly of plasmid sequence data remains challenging due to software incompatibility with long-reads and the error rate generated using ONT sequencing. Bioinformatics pipelines have been developed for ONT-generated sequencing but require computational skills that frequently are beyond the abilities of scientific researchers. To overcome this challenge, the authors developed ‘WeFaceNano’, a user-friendly Web interFace for rapid assembly and analysis of plasmid DNA sequences generated using the ONT platform. WeFaceNano includes: a read statistics report; two assemblers (Miniasm and Flye); BLAST searching; the detection of antibiotic resistance- and replicon genes and several plasmid visualizations. A user-friendly interface displays the main features of WeFaceNano and gives access to the analysis tools. Results Publicly available ONT sequence data of 21 plasmids were used to validate WeFaceNano, with plasmid assemblages and anti-microbial resistance gene detection being concordant with the published results. Interestingly, the “Flye” assembler with “meta” settings generated the most complete plasmids. Conclusions WeFaceNano is a user-friendly open-source software pipeline suitable for accurate plasmid assembly and the detection of anti-microbial resistance genes in (clinical) samples where multiple plasmids can be present.

Epigenetic programming is essential for lineage differentiation, embryogenesis and placentation in early pregnancy. In epigenetic association studies, DNA methylation is often examined in DNA derived from white blood cells, although its validity to other tissues of interest remains questionable. Therefore, we investigated the tissue specificity of epigenome-wide DNA methylation in newborn and placental tissues. Umbilical cord white blood cells (UC-WBC, n = 25), umbilical cord blood mononuclear cells (UC-MNC, n = 10), human umbilical vein endothelial cells (HUVEC, n = 25) and placental tissue (n = 25) were obtained from 36 uncomplicated pregnancies. Genome-wide DNA methylation was measured by the Illumina HumanMethylation450K BeadChip. Using UC-WBC as a reference tissue, we identified 3595 HUVEC tissue-specific differentially methylated regions (tDMRs) and 11,938 placental tDMRs. Functional enrichment analysis showed that HUVEC and placental tDMRs were involved in embryogenesis, vascular development and regulation of gene expression. No tDMRs were identified in UC-MNC. In conclusion, the extensive amount of genome-wide HUVEC and placental tDMRs underlines the relevance of tissue-specific approaches in future epigenetic association studies, or the use of validated representative tissues for a certain disease of interest, if available. To this purpose, we herewith provide a relevant dataset of paired, tissue-specific, genome-wide methylation measurements in newborn tissues.

Summary A major challenge for treating patients with pancreatic ductal adenocarcinoma (PDAC) is the unpredictability of their prognoses due to high heterogeneity. We present Multi-Omics DEep Learning for Prognosis-correlated subtyping (MODEL-P) to identify PDAC subtypes and to predict prognoses of new patients. MODEL-P was trained on autoencoder integrated multi-omics of 146 patients with PDAC together with their survival outcome. Using MODEL-P, we identified two PDAC subtypes with distinct survival outcomes (median survival 10.1 and 22.7 months, respectively, log rank p = 1 × 10−6), which correspond to DNA damage repair and immune response. We rigorously validated MODEL-P by stratifying patients in five independent datasets into these two survival groups and achieved significant survival difference, which is superior to current practice and other subtyping schemas. We believe the subtype-specific signatures would facilitate PDAC pathogenesis discovery, and MODEL-P can provide clinicians the prognoses information in the treatment decision-making to better gauge the benefits versus the risks., Graphical abstract, Highlights • We developed DL-based MODEL-P to identify prognosis-correlated PDAC subtypes • The identified subtypes related to DNA damage repair and immune response processes • MODEL-P stratified patients from independent datasets into distinct survival groups • MODEL-P could be used in clinics to aid treatment decision-making, Biocomputational method; Cancer systems biology; Cancer

Background Long-read sequencing can be applied to generate very long contigs and even completely assembled genomes at relatively low cost and with minimal sample preparation. As a result, long-read sequencing platforms are becoming more popular. In this respect, the Oxford Nanopore Technologies–based long-read sequencing “nanopore" platform is becoming a widely used tool with a broad range of applications and end-users. However, the need to explore and manipulate the complex data generated by long-read sequencing platforms necessitates accompanying specialized bioinformatics platforms and tools to process the long-read data correctly. Importantly, such tools should additionally help democratize bioinformatics analysis by enabling easy access and ease-of-use solutions for researchers. Results The Galaxy platform provides a user-friendly interface to computational command line–based tools, handles the software dependencies, and provides refined workflows. The users do not have to possess programming experience or extended computer skills. The interface enables researchers to perform powerful bioinformatics analysis, including the assembly and analysis of short- or long-read sequence data. The newly developed “NanoGalaxy" is a Galaxy-based toolkit for analysing long-read sequencing data, which is suitable for diverse applications, including de novo genome assembly from genomic, metagenomic, and plasmid sequence reads. Conclusions A range of best-practice tools and workflows for long-read sequence genome assembly has been integrated into a NanoGalaxy platform to facilitate easy access and use of bioinformatics tools for researchers. NanoGalaxy is freely available at the European Galaxy server https://nanopore.usegalaxy.eu with supporting self-learning training material available at https://training.galaxyproject.org.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is notoriously resistant to treatment including checkpoint-blockade immunotherapy. We hypothesized that a bimodal treatment approach consisting of dendritic cell (DC) vaccination to prime tumor-specific T cells, and a strategy to reprogram the desmoplastic tumor microenvironment (TME) would be needed to break tolerance to these pancreatic cancers. As a proof-of-concept, we investigated the efficacy of combined DC vaccination with CD40-agonistic antibodies in a poorly immunogenic murine model of PDAC. Based on the rationale that mesothelioma and pancreatic cancer share a number of tumor associated antigens, the DCs were loaded with either pancreatic or mesothelioma tumor lysates.MethodsImmune-competent mice with subcutaneously or orthotopically growing KrasG12D/+;Trp53R172H/+;Pdx-1-Cre (KPC) PDAC tumors were vaccinated with syngeneic bone marrow-derived DCs loaded with either pancreatic cancer (KPC) or mesothelioma (AE17) lysate and consequently treated with FGK45 (CD40 agonist). Tumor progression was monitored and immune responses in TME and lymphoid organs were analyzed using multicolor flow cytometry and NanoString analyzes.ResultsMesothelioma-lysate loaded DCs generated cross-reactive tumor-antigen-specific T-cell responses to pancreatic cancer and induced delayed tumor outgrowth when provided as prophylactic vaccine. In established disease, combination with stimulating CD40 antibody was necessary to improve survival, while anti-CD40 alone was ineffective. Extensive analysis of the TME showed that anti-CD40 monotherapy did improve CD8 +T cell infiltration, but these essential effector cells displayed hallmarks of exhaustion, including PD-1, TIM-3 and NKG2A. Combination therapy induced a strong change in tumor transcriptome and mitigated the expression of inhibitory markers on CD8 +T cells.ConclusionThese results demonstrate the potency of DC therapy in combination with CD40-stimulation for the treatment of pancreatic cancer and provide directions for near future clinical trials.

CRISPR-Cas9 systems are enriched in human pathogenic bacteria and have been linked to cytotoxicity by an unknown mechanism. Here, we show that upon infection of human cells, Campylobacter jejuni secretes its Cas9 (CjeCas9) nuclease into their cytoplasm. Next, a native nuclear localization signal enables CjeCas9 nuclear entry, where it catalyzes metal-dependent nonspecific DNA cleavage leading to cell death. Compared to CjeCas9, native Cas9 of Streptococcus pyogenes (SpyCas9) is more suitable for guide-dependent editing. However, in human cells, native SpyCas9 may still cause some DNA damage, most likely because of its ssDNA cleavage activity. This side effect can be completely prevented by saturation of SpyCas9 with an appropriate guide RNA, which is only partially effective for CjeCas9. We conclude that CjeCas9 plays an active role in attacking human cells rather than in viral defense. Moreover, these unique catalytic features may therefore make CjeCas9 less suitable for genome editing applications.

Consensus molecular subtyping is an RNA expression-based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI). We aimed to investigate whether colorectal adenomas can already be stratified into consensus molecular subtype (CMS) classes, and whether specific CMS classes are related to the presence of specific DNA copy number aberrations associated with progression to malignancy. RNA sequencing was performed on 62 adenomas and 59 CRCs. MSI status was determined with polymerase chain reaction-based methodology. DNA copy number was assessed by low-coverage DNA sequencing (n = 30) or array-comparative genomic hybridisation (n = 32). Adenomas were classified into CMS classes together with CRCs from the study cohort and from The Cancer Genome Atlas (n = 556), by use of the established CMS classifier. As a result, 54 of 62 (87%) adenomas were classified according to the CMS. The CMS3 ‘metabolic subtype’, which was least common among CRCs, was most prevalent among adenomas (n = 45; 73%). One of the two adenomas showing MSI was classified as CMS1 (2%), the ‘MSI immune’ subtype. Eight adenomas (13%) were classified as the ‘canonical’ CMS2. No adenomas were classified as the ‘mesenchymal’ CMS4, consistent with the fact that adenomas lack invasion-associated stroma. The distribution of the CMS classes among adenomas was confirmed in an independent series. CMS3 was enriched with adenomas at low risk of progressing to CRC, whereas relatively more high-risk adenomas were observed in CMS2. We conclude that adenomas can be stratified into the CMS classes. Considering that CMS1 and CMS2 expression signatures may mark adenomas at increased risk of progression, the distribution of the CMS classes among adenomas is consistent with the proportion of adenomas expected to progress to CRC.

Consensus molecular subtyping is an RNA expression‐based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI). We aimed to investigate whether colorectal adenomas can already be stratified into consensus molecular subtype (CMS) classes, and whether specific CMS classes are related to the presence of specific DNA copy number aberrations associated with progression to malignancy. RNA sequencing was performed on 62 adenomas and 59 CRCs. MSI status was determined with polymerase chain reaction‐based methodology. DNA copy number was assessed by low‐coverage DNA sequencing (n = 30) or array‐comparative genomic hybridisation (n = 32). Adenomas were classified into CMS classes together with CRCs from the study cohort and from The Cancer Genome Atlas (n = 556), by use of the established CMS classifier. As a result, 54 of 62 (87%) adenomas were classified according to the CMS. The CMS3 ‘metabolic subtype’, which was least common among CRCs, was most prevalent among adenomas (n = 45; 73%). One of the two adenomas showing MSI was classified as CMS1 (2%), the ‘MSI immune’ subtype. Eight adenomas (13%) were classified as the ‘canonical’ CMS2. No adenomas were classified as the ‘mesenchymal’ CMS4, consistent with the fact that adenomas lack invasion‐associated stroma. The distribution of the CMS classes among adenomas was confirmed in an independent series. CMS3 was enriched with adenomas at low risk of progressing to CRC, whereas relatively more high‐risk adenomas were observed in CMS2. We conclude that adenomas can be stratified into the CMS classes. Considering that CMS1 and CMS2 expression signatures may mark adenomas at increased risk of progression, the distribution of the CMS classes among adenomas is consistent with the proportion of adenomas expected to progress to CRC. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy associated with a poor prognosis. Only 10% of the patients survive longer than five years. So far, factors underlining long-term survivorship in PDAC are not well understood. Therefore, we aimed to identify the key players in the tumor immune microenvironment (TIME) associated with long-term survivorship in PDAC patients. Methods: The immune-related gene expression profiles of surgically resected PDAC tumors of patients who survived and remained recurrence-free of disease for > 3 years (long-term survivors, n=10) were compared to PDAC tumors of patients who had survived ≤ 6 months (short-term survivors, n=10) due to tumor recurrence. Samples were profiled using the nCounter® PanCancer Immune Profiling Panel of NanoString Technology. Validation was performed by spatial analysis of immune cells using the GeoMx™ Digital Spatial Profiler. Results: Tumor-infiltrating B cells were found to be significantly increased in the TIME of long-term survivors by gene expression profiling (p=0.018). The high tumor infiltration of B cells was confirmed by spatial protein profiling (p=0.049). This increase was accompanied by more T cells and antigen-presenting cell infiltration. Moreover, the activated immune cells were found to infiltrate in between tumor cells as well as in stromal areas in long-term survivors. In contrast, the TIME of short-term survivors was characterized by a high density of immunosuppressive cells like CD25 and regulatory T cells infiltrating in a highly fibrotic vicinity. Conclusion: This is the first comprehensive study that connects the immune landscape of gene expression profiles and protein spatial infiltration with the survivorship of PDAC patients. We found higher infiltration of B cells in TIME of long-term survivors which highlights the importance of targeting B cells and B cell-based therapy for future personalized immunotherapy in PDAC patients. Citation Format: Hosein M. Aziz, Lawlaw Saida, Willem de Koning, Andrew Stubbs, Yunlei Li, Casper H. J. van Eijck, Dana A. M. Mustafa. The tumor immune microenvironment is decisive in the survival of pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-118.

In B-cell precursor acute lymphoblastic leukemia, the initial leukemic cells share the same antigen receptor gene rearrangements. However, due to ongoing rearrangement processes, leukemic cells with different gene rearrangement patterns can develop, resulting in subclone formation. We studied leukemic subclones and their distribution in the bone marrow and peripheral blood at diagnosis. Antigen receptor gene rearrangements (IGH, IGK, TRG, TRD, TRB) were analyzed by next-generation sequencing in seven paired bone marrow samples and five paired bone marrow-peripheral blood samples. Background-thresholds were defined, which enabled identification of leukemic gene rearrangements down to very low levels. Paired bone marrow analysis showed oligoclonality in all 7 patients and up to 34 leukemic clones per patient. Additional analysis of evolutionary-related IGH gene rearrangements revealed up to 171 leukemic clones per patient. Interestingly, overall 86% of all leukemic gene rearrangements, including small subclones, were present in both bone marrow samples (range per patient: 72–100%). Paired bone marrow-peripheral blood analysis showed that 83% of all leukemic gene rearrangements in bone marrow were also found in peripheral blood (range per patient: 81–100%). Remarkably, in the paired bone marrow samples and paired bone marrow-peripheral blood samples the vast majority of leukemic gene rearrangements had a similar frequency (

Antigen Receptor Galaxy (ARGalaxy) is a Web-based tool for analyses and visualization of TCR and BCR sequencing data of 13 species. ARGalaxy consists of four parts: the demultiplex tool, the international ImMunoGeneTics information system (IMGT) concatenate tool, the immune repertoire pipeline, and the somatic hypermutation (SHM) and class switch recombination (CSR) pipeline. Together they allow the analysis of all different aspects of the immune repertoire. All pipelines can be run independently or combined, depending on the available data and the question of interest. The demultiplex tool allows data trimming and demultiplexing, whereas with the concatenate tool multiple IMGT/HighV-QUEST output files can be merged into a single file. The immune repertoire pipeline is an extended version of our previously published ImmunoGlobulin Galaxy (IGGalaxy) virtual machine that was developed to visualize V(D)J gene usage. It allows analysis of both BCR and TCR rearrangements, visualizes CDR3 characteristics (length and amino acid usage) and junction characteristics, and calculates the diversity of the immune repertoire. Finally, ARGalaxy includes the newly developed SHM and CSR pipeline to analyze SHM and/or CSR in BCR rearrangements. It analyzes the frequency and patterns of SHM, Ag selection (including BASELINe), clonality (Change-O), and CSR. The functionality of the ARGalaxy tool is illustrated in several clinical examples of patients with primary immunodeficiencies. In conclusion, ARGalaxy is a novel tool for the analysis of the complete immune repertoire, which is applicable to many patient groups with disturbances in the immune repertoire such as autoimmune diseases, allergy, and leukemia, but it can also be used to address basic research questions in repertoire formation and selection.

Ventricular noncompaction cardiomyopathy is a rare form of congenital cardiomyopathy with increasing evidence of genetic etiology, especially when presenting in childhood. Fetal presentation is rare. We describe a case of fetal hydrops, presenting at 24 weeks gestation and leading to intrapartum death at 26 weeks gestation. Autopsy examination revealed characteristic features of left ventricular noncompaction. A genetic analysis identified a constellation of variants of unknown significance in MYH6, TNNC1, and MYBPC3, genes known to be important in sarcomeric function. Additionally, the variant in MYBPC3 was homozygous. While this case did not demonstrate a conventional single-gene mutation as the cause of the ventricular noncompaction, a broader genomic investigation revealed several variants in sarcomeric genes which may act synergistically to impact cardiac function.

Common variable immune deficiency disorder (CVID) is the most clinically relevant cause of antibody failure. It is a highly heterogeneous disease with different underlying etiologies. CVID has been associated with a quantitative B cell defect, however, little is known about the quality of B cells present. Here, we studied the naive and antigen selected B-cell receptor (BCR) repertoire in 33 CVID patients using next generation sequencing, to investigate B cells quality. Analysis for each individual patient revealed whether they have a defect in immune repertoire formation [V(D)J recombination] or specification (somatic hypermutation, subclass distribution, or selection). The naive BCR repertoire was normal in most of the patients, although alterations in repertoire diversity and the junctions were found in a limited number of patients indicating possible defects in early B-cell development or V(D)J recombination in these patients. In contrast, major differences were found in the antigen selected BCR repertoire. Here, most patients (15/17) showed a reduced frequency of somatic hypermutation (SHM), changes in subclass distribution and/or minor alterations in antigen selection. Together these data show that in our CVID cohort only a small number of patients have a defect in formation of the naive BCR repertoire, whereas the clear majority of patients have disturbances in their antigen selected repertoire, suggesting a defect in repertoire specification in the germinal centers of these patients. This highlights that CVID patients not only have a quantitative B cell defect, but that also the quality of, especially post germinal center B cells, is impaired.

Background Mutations in the γ‐secretase enzyme subunits have been described in multiple kindreds with familial hidradenitis suppurativa (HS). Objective In this study, we report a novel nicastrin (NCSTN) mutation causing HS in a Dutch family. We sought to explore the immunobiological function of NCSTN mutations using data of the Immunological Genome Project. Methods Blood samples of three affected and two unaffected family members were collected. Whole‐genome sequencing was performed using genomic DNA isolated from peripheral blood leucocytes. Sanger sequencing was done to confirm the causative NCSTN variant and the familial segregation. The microarray data set of the Immunological Genome Project was used for thorough dissection of the expression and function of wildtype NCSTN in the immune system. Results In a family consisting of 23 members, we found an autosomal dominant inheritance pattern of HS and detected a novel splice site mutation (c.1912_1915delCAGT) in the NCSTN gene resulting in a frameshift and subsequent premature stop. All affected individuals had HS lesions on non‐flexural and atypical locations. Wildtype NCSTN appears to be upregulated in myeloid cells like monocytes and macrophages, and in mesenchymal cells such as fibroblastic reticular cells and fibroblasts. In addition, within the 25 highest co‐expressed genes with NCSTN we identified CAPNS1,ARNT and PPARD. Conclusion This study reports the identification a novel NCSTN gene splice site mutation which causes familial HS. The associated immunobiological functions of NCSTN and its co‐expressed genes ARNT and PPARD link genetics to the most common environmental and metabolic HS risk factors which are smoking and obesity.