Erratum: PD-1 is a haploinsufficient suppressor of T cell lymphomagenesis.

This corrects the article DOI: 10.1038/nature24649.

Detecting drug resistance in pancreatic cancer organoids guides optimized chemotherapy treatment.

Drug combination therapies for cancer treatment show high efficacy but often induce severe side effects, resulting in dose or cycle number reduction. We investigated the impact of neoadjuvant chemotherapy (neoCTx) adaptions on treatment outcome in 59 patients with pancreatic ductal adenocarcinoma (PDAC). Resections with tumor-free margins were significantly more frequent when full-dose neoCTx was applied. We determined if patient-derived organoids (PDOs) can be used to personalize poly-chemotherapy regimens by pharmacotyping of treatment-naïve and post-neoCTx PDAC PDOs. Five out of ten CTx-naïve PDO lines exhibited a differential response to either the FOLFIRINOX or the Gem/Pac regimen. NeoCTx PDOs showed a poor response to the neoadjuvant regimen that had been administered to the respective patient in 30% of cases. No significant difference in PDO response was noted when comparing modified treatments in which the least effective single drug was removed from the complete regimen. Drug testing of CTx-naïve PDAC PDOs and neoCTx PDOs may be useful to guide neoadjuvant and adjuvant regimen selection, respectively. Personalizing poly-chemotherapy regimens by omitting substances with low efficacy could potentially result in less severe side effects, thereby increasing the fraction of patients receiving a full course of neoadjuvant treatment. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

PD-1 is a haploinsufficient suppressor of T cell lymphomagenesis.

T cell non-Hodgkin lymphomas are a heterogeneous group of highly aggressive malignancies with poor clinical outcomes. T cell lymphomas originate from peripheral T cells and are frequently characterized by genetic gain-of-function variants in T cell receptor (TCR) signalling molecules. Although these oncogenic alterations are thought to drive TCR pathways to induce chronic proliferation and cell survival programmes, it remains unclear whether T cells contain tumour suppressors that can counteract these events. Here we show that the acute enforcement of oncogenic TCR signalling in lymphocytes in a mouse model of human T cell lymphoma drives the strong expansion of these cells in vivo. However, this response is short-lived and robustly counteracted by cell-intrinsic mechanisms. A subsequent genome-wide in vivo screen using T cell-specific transposon mutagenesis identified PDCD1, which encodes the inhibitory receptor programmed death-1 (PD-1), as a master gene that suppresses oncogenic T cell signalling. Mono- and bi-allelic deletions of PDCD1 are also recurrently observed in human T cell lymphomas with frequencies that can exceed 30%, indicating high clinical relevance. Mechanistically, the activity of PD-1 enhances levels of the tumour suppressor PTEN and attenuates signalling by the kinases AKT and PKC in pre-malignant cells. By contrast, a homo- or heterozygous deletion of PD-1 allows unrestricted T cell growth after an oncogenic insult and leads to the rapid development of highly aggressive lymphomas in vivo that are readily transplantable to recipients. Thus, the inhibitory PD-1 receptor is a potent haploinsufficient tumour suppressor in T cell lymphomas that is frequently altered in human disease. These findings extend the known physiological functions of PD-1 beyond the prevention of immunopathology after antigen-induced T cell activation, and have implications for T cell lymphoma therapies and for current strategies that target PD-1 in the broader context of immuno-oncology.

Ethical and coordinative challenges in setting up a national cohort study during the COVID-19 pandemic in Germany.

With the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), global researchers were confronted with major challenges. The German National Pandemic Cohort Network (NAPKON) was launched in fall 2020 to effectively leverage resources and bundle research activities in the fight against the coronavirus disease 2019 (COVID-19) pandemic. We analyzed the setup phase of NAPKON as an example for multicenter studies in Germany, highlighting challenges and optimization potential in connecting 59 university and nonuniversity study sites. We examined the ethics application process of 121 ethics submissions considering durations, annotations, and outcomes. Study site activation and recruitment processes were investigated and related to the incidence of SARS-CoV-2 infections. For all initial ethics applications, the median time to a positive ethics vote was less than two weeks and 30 of these study sites (65%) joined NAPKON within less than three weeks each. Electronic instead of postal ethics submission (9.5 days (Q1: 5.75, Q3: 17) vs. 14 days (Q1: 11, Q3: 26), p value = 0.01) and adoption of the primary ethics vote significantly accelerated the ethics application process. Each study center enrolled a median of 37 patients during the 14-month observation period, with large differences depending on the health sector. We found a positive correlation between recruitment performance and COVID-19 incidence as well as hospitalization incidence. Our analysis highlighted the challenges and opportunities of the federated system in Germany. Digital ethics application tools, adoption of a primary ethics vote and standardized formal requirements lead to harmonized and thus faster study initiation processes during a pandemic.

Comparison of PD-L1 expression in squamous cell cancer of unknown primary and oropharyngeal squamous cell carcinoma.

PURPOSE: The tumorigenesis of squamous cell cancer of unknown primary (SCCUP) in the head and neck area has not been decoded so far, while poor survival rates and limited therapeutic options pose a serious challenge. The aim of this project was to investigate immunological characteristics of SCCUPs and compare them to oropharyngeal squamous cell carcinoma (OPSCC). METHODS: PD-L1 expression (TC) was examined by immunohistochemistry in 50 lymph node metastases of SCCUP and 47 primaries of OPSCC. CD3 + and CD8 + lymphocytic infiltration was measured in 5 high power fields. Expression of p16 and HPV ISH were assessed. RESULTS: SCCUP demonstrated a significantly higher expression of PD-L1 than OPSCC. In p16-negative SCCUPs PD-L1 proved to be an independent prognostic factor to prioritize high-risk patients. CONCLUSIONS: Immunologic differences between SCCUP and OPSCC were detected. A higher PD-L1 expression in SCCUP could potentially facilitate further evaluation of checkpoint inhibitor therapy.

Genetic Architecture of Ischaemic Strokes after COVID-19 Shows Similarities with Large Vessel Strokes.

We aimed to analyse whether patients with ischaemic stroke (IS) occurring within eight days after the onset of COVID-19 (IS-COV) are associated with a specific aetiology of IS. We used SUPERGNOVA to identify genome regions that correlate between the IS-COV cohort (73 IS-COV cases vs. 701 population controls) and different aetiological subtypes. Polygenic risk scores (PRSs) for each subtype were generated and tested in the IS-COV cohort using PRSice-2 and PLINK to find genetic associations. Both analyses used the IS-COV cohort and GWAS from MEGASTROKE (67,162 stroke patients vs. 454,450 population controls), GIGASTROKE (110,182 vs. 1,503,898), and the NINDS Stroke Genetics Network (16,851 vs. 32,473). Three genomic regions were associated (p-value < 0.05) with large artery atherosclerosis (LAA) and cardioembolic stroke (CES). We found four loci targeting the genes PITX2 (rs10033464, IS-COV beta = 0.04, p-value = 2.3 × 10-2, se = 0.02), previously associated with CES, HS6ST1 (rs4662630, IS-COV beta = -0.04, p-value = 1.3 × 10-3, se = 0.01), TMEM132E (rs12941838 IS-COV beta = 0.05, p-value = 3.6 × 10-4, se = 0.01), and RFFL (rs797989 IS-COV beta = 0.03, p-value = 1.0 × 10-2, se = 0.01). A statistically significant PRS was observed for LAA. Our results suggest that IS-COV cases are genetically similar to LAA and CES subtypes. Larger cohorts are needed to assess if the genetic factors in IS-COV cases are shared with the general population or specific to viral infection.

Cyclophosphamide plus etoposide is a safe and effective mobilization regimen in patients with multiple myeloma.

High-dose chemotherapy followed by autologous stem cell transplantation is a major component in the treatment of patients with multiple myeloma. As a prerequisite, the successful collection of a sufficient number of viable peripheral blood hematopoietic CD34+ cells is critical. A common standard protocol for mobilization is currently not defined and critically discussed especially in German-speaking Europe. In times of the Covid-19 pandemic, safe and effective strategies have to be chosen to minimize hospitalization times and severe courses. In this single-center retrospective analysis, safety and efficacy of cyclophosphamide plus etoposide (CE) and growth-factor support (n = 33) was compared to cyclophosphamide mono treatment and growth-factor support (n = 49) in 82 patients with multiple myeloma at first diagnosis. CE was superior to cyclophosphamide mono with a significantly higher number of collected CD34+ cells (15.46 × 106 CD34+ cells/kg vs. 9.92 × 106 CD34+ cells/kg), significantly faster engraftment of granulocytes after stem cell transplantation (day 10.5 vs. day 11.6), shorter duration of the inpatient stay (17.47 days vs. 19.16 days) and significantly less transfusions (8.82 % vs. 30.61 % patients receiving transfusions). The safety profile was comparable in both groups and in line with published data. We conclude that CE is a safe and highly effective mobilization protocol in patients with multiple myeloma at first diagnosis and appears to be superior to the commonly used cyclophosphamide mono regimen.

External quality assessment schemes for glucose measurements in Germany: factors for successful participation, analytical performance and medical impact.

BACKGROUND: Determination of blood glucose concentration is one of the most important measurements in clinical chemistry worldwide. Analyzers in central laboratories (CL) and point-of-care tests (POCT) are both frequently used. In Germany, regular participation in external quality assessment (EQA) schemes is mandatory for laboratories performing glucose testing. METHODS: Glucose testing data from the two German EQAs "Reference Institute for Bioanalytics" (RfB) and "INSTAND - Gesellschaft zur Förderung der Qualitätssicherung in medizinischen Laboratorien" (Instand) were analyzed from 2012 to 2016. Multivariable odds ratios (OR) for the probability to reach a "good" result were calculated. Imprecision and bias were determined and clinical risk of measurement errors estimated. RESULTS: The device employed was the most important variable required for a "good" performance in all EQAs. Additional participation in an EQA for CL automated analyzers improved performance in POCT EQAs. The reciprocal effect was less pronounced. New participants performed worse than experienced participants especially in CL EQAs. Imprecision was generally smaller for CL, but some POCT devices reached a comparable performance. Large lot-to-lot differences occurred in over 10% of analyzed cases. We propose the "bias budget" as a new metric to express the maximum allowable bias that still carries acceptable medical risk. Bias budgets were smallest and clinical risks of errors greatest in the low range of measurement 60-115 mg/dL (3.3-6.4 mmol/L) for most devices. CONCLUSIONS: EQAs help to maintain high analytical performances. They generate important data that serve as the foundation for learning and improvement in the laboratory healthcare system.

Network information improves cancer outcome prediction.

Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression.

Contralateral breast cancer can represent a metastatic spread of the first primary tumor: determination of clonal relationship between contralateral breast cancers using next-generation whole genome sequencing.

INTRODUCTION: By convention, a contralateral breast cancer (CBC) is treated as a new primary tumor, independent of the first cancer (BC1). Although there have been indications that the second tumor (BC2) sometimes may represent a metastatic spread of BC1, this has never been conclusively shown. We sought to apply next-generation sequencing to determine a "genetic barcode" for each tumor and reveal the clonal relationship of CBCs. METHODS: Ten CBC patients with detailed clinical information and available fresh frozen tumor tissue were studied. Using low-coverage whole genome DNA-sequencing data for each tumor, chromosomal rearrangements were enumerated and copy number profiles were generated. Comparisons between tumors provided an estimate of clonal relatedness for tumor pairs within individual patients. RESULTS: Between 15-256 rearrangements were detected in each tumor (median 87). For one patient, 76 % (68 out of 90) of the rearrangements were shared between BC1 and BC2, highly consistent with what has been seen for true primary-metastasis pairs (>50 %) and thus confirming a common clonal origin of the two tumors. For most of the remaining cases, BC1 and BC2 had similarly low overlap as unmatched randomized pairs of tumors from different individuals, suggesting the CBC to represent a new independent primary tumor. CONCLUSION: Using rearrangement fingerprinting, we show for the first time with certainty that a contralateral BC2 can represent a metastatic spread of BC1. Given the poor prognosis of a generalized disease compared to a new primary tumor, these women need to be identified at diagnosis of CBC for appropriate determination of treatment. Our approach generates a promising new method to assess clonal relationship between tumors. Additional studies are required to confirm the frequency of CBCs representing metastatic events.

Molecular and genetic diversity in the metastatic process of melanoma.

Diversity between metastatic melanoma tumours in individual patients is known; however, the molecular and genetic differences remain unclear. To examine the molecular and genetic differences between metastatic tumours, we performed gene-expression profiling of 63 melanoma tumours obtained from 28 patients (two or three tumours/patient), followed by analysis of their mutational landscape, using targeted deep sequencing of 1697 cancer genes and DNA copy number analysis. Gene-expression signatures revealed discordant phenotypes between tumour lesions within a patient in 50% of the cases. In 18 of 22 patients (where matched normal tissue was available), we found that the multiple lesions within a patient were genetically divergent, with one or more melanoma tumours harbouring 'private' somatic mutations. In one case, the distant subcutaneous metastasis of one patient occurring 3 months after an earlier regional lymph node metastasis had acquired 37 new coding sequence mutations, including mutations in PTEN and CDH1. However, BRAF and NRAS mutations, when present in the first metastasis, were always preserved in subsequent metastases. The patterns of nucleotide substitutions found in this study indicate an influence of UV radiation but possibly also DNA alkylating agents. Our results clearly demonstrate that metastatic melanoma is a molecularly highly heterogeneous disease that continues to progress throughout its clinical course. The private aberrations observed on a background of shared aberrations within a patient provide evidence of continued evolution of individual tumours following divergence from a common parental clone, and might have implications for personalized medicine strategies in melanoma treatment.

Head and neck cancer of unknown primary: unveiling primary tumor sites through machine learning on DNA methylation profiles.

BACKGROUND: The unknown tissue of origin in head and neck cancer of unknown primary (hnCUP) leads to invasive diagnostic procedures and unspecific and potentially inefficient treatment options for patients. The most common histologic subtype, squamous cell carcinoma, can stem from various tumor primary sites, including the oral cavity, oropharynx, larynx, head and neck skin, lungs, and esophagus. DNA methylation profiles are highly tissue-specific and have been successfully used to classify tissue origin. We therefore developed a support vector machine (SVM) classifier trained with publicly available DNA methylation profiles of commonly cervically metastasizing squamous cell carcinomas (n = 1103) in order to identify the primary tissue of origin of our own cohort of squamous cell hnCUP patient's samples (n = 28). Methylation analysis was performed with Infinium MethylationEPIC v1.0 BeadChip by Illumina. RESULTS: The SVM algorithm achieved the highest overall accuracy of tested classifiers, with 87%. Squamous cell hnCUP samples on DNA methylation level resembled squamous cell carcinomas commonly metastasizing into cervical lymph nodes. The most frequently predicted cancer localization was the oral cavity in 11 cases (39%), followed by the oropharynx and larynx (both 7, 25%), skin (2, 7%), and esophagus (1, 4%). These frequencies concord with the expected distribution of lymph node metastases in epidemiological studies. CONCLUSIONS: On DNA methylation level, hnCUP is comparable to primary tumor tissue cancer types that commonly metastasize to cervical lymph nodes. Our SVM-based classifier can accurately predict these cancers' tissues of origin and could significantly reduce the invasiveness of hnCUP diagnostics and enable a more precise therapy after clinical validation.

Expert-Guided Large Language Models for Clinical Decision Support in Precision Oncology.

PURPOSE: Rapidly expanding medical literature challenges oncologists seeking targeted cancer therapies. General-purpose large language models (LLMs) lack domain-specific knowledge, limiting their clinical utility. This study introduces the LLM system Medical Evidence Retrieval and Data Integration for Tailored Healthcare (MEREDITH), designed to support treatment recommendations in precision oncology. Built on Google's Gemini Pro LLM, MEREDITH uses retrieval-augmented generation and chain of thought. METHODS: We evaluated MEREDITH on 10 publicly available fictional oncology cases with iterative feedback from a molecular tumor board (MTB) at a major German cancer center. Initially limited to PubMed-indexed literature (draft system), MEREDITH was enhanced to incorporate clinical studies on drug response within the specific tumor type, trial databases, drug approval status, and oncologic guidelines. The MTB provided a benchmark with manually curated treatment recommendations and assessed the clinical relevance of LLM-generated options (qualitative assessment). We measured semantic cosine similarity between LLM suggestions and clinician responses (quantitative assessment). RESULTS: MEREDITH identified a broader range of treatment options (median 4) compared with MTB experts (median 2). These options included therapies on the basis of preclinical data and combination treatments, expanding the treatment possibilities for consideration by the MTB. This broader approach was achieved by incorporating a curated medical data set that contextualized molecular targetability. Mirroring the approach MTB experts use to evaluate MTB cases improved the LLM's ability to generate relevant suggestions. This is supported by high concordance between LLM suggestions and expert recommendations (94.7% for the enhanced system) and a significant increase in semantic similarity from the draft to the enhanced system (from 0.71 to 0.76, P = .01). CONCLUSION: Expert feedback and domain-specific data augment LLM performance. Future research should investigate responsible LLM integration into real-world clinical workflows.

B-cell intrinsic RANK signaling cooperates with TCL1 to induce lineage-dependent B-cell transformation.

B-cell malignancies, such as chronic lymphocytic leukemia (CLL) and multiple myeloma (MM), remain incurable, with MM particularly prone to relapse. Our study introduces a novel mouse model with active RANK signaling and the TCL1 oncogene, displaying both CLL and MM phenotypes. In younger mice, TCL1 and RANK expression expands CLL-like B1-lymphocytes, while MM originates from B2-cells, becoming predominant in later stages and leading to severe disease progression and mortality. The induced MM mimics human disease, exhibiting features like clonal plasma cell expansion, paraproteinemia, anemia, and kidney and bone failure, as well as critical immunosurveillance strategies that promote a tumor-supportive microenvironment. This research elucidates the differential impacts of RANK activation in B1- and B2-cells and underscores the distinct roles of single versus combined oncogenes in B-cell malignancies. We also demonstrate that human MM cells express RANK and that inhibiting RANK signaling can reduce MM progression in a xenotransplantation model. Our study provides a rationale for further investigating the effects of RANK signaling in B-cell transformation and the shaping of a tumor-promoting microenvironment.

Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

The role of extended coagulation screening in adult cranial neurosurgery.

Introduction: Postoperative hemorrhage after adult cranial neurosurgery is a serious complication with substantial morbidity and mortality. Research question: We investigated if an extended preoperative screening and an early treatment of previously undetected coagulopathies may decrease the risk of postoperative hemorrhage. Methods: A prospective study cohort of patients undergoing elective cranial surgery and receiving the extended coagulatory work-up were compared to a propensity matched historical control cohort. The extended work-up included a standardized questionnaire on the patient's bleeding history as well as coagulatory tests of Factor XIII, von-Willebrand-Factor and PFA-100®. Deficiencies were substituted perioperatively. The primary outcome was determined as the surgical revision rate due to postoperative hemorrhage. Results: The study cohort and the control cohort included 197 cases each, without any significant difference in the preoperative intake of anticoagulant medication (p â€‹= â€‹.546). Most common interventions were resections of malignant tumors (41%), benign tumors (27%) and neurovascular surgeries (9%) in both cohorts. Imaging revealed postoperative hemorrhage in 7 cases (3.6%) in the study cohort and 18 cases (9.1%) in the control cohort (p â€‹= â€‹.023). Of these, revision surgeries were significantly more common in the control cohort with 14 cases (9.1%) compared to 5 cases (2.5%) in the study cohort (p â€‹= â€‹.034). Differences in mean intraoperative blood loss were not significant with 528 â€‹ml in the study cohort and 486 â€‹ml in the control cohort (p â€‹= â€‹.376). Conclusion: Preoperative extended coagulatory screening may allow for revealing previously undiagnosed coagulopathies with subsequent preoperative substitution and thereby reduction of risk for postoperative hemorrhage in adult cranial neurosurgery.

Synthetic enforcement of STING signaling in cancer cells appropriates the immune microenvironment for checkpoint inhibitor therapy.

Immune checkpoint inhibitors (ICIs) enhance anticancer immunity by releasing repressive signals into tumor microenvironments (TMEs). To be effective, ICIs require preexisting immunologically "hot" niches for tumor antigen presentation and lymphocyte recruitment. How the mutational landscape of cancer cells shapes these immunological niches remains poorly defined. We found in human and murine colorectal cancer (CRC) models that the superior antitumor immune response of mismatch repair (MMR)-deficient CRC required tumor cell-intrinsic activation of cGAS-STING signaling triggered by genomic instability. Subsequently, we synthetically enforced STING signaling in CRC cells with intact MMR signaling using constitutively active STING variants. Even in MMR-proficient CRC, genetically encoded gain-of-function STING was sufficient to induce cancer cell-intrinsic interferon signaling, local activation of antigen-presenting cells, recruitment of effector lymphocytes, and sensitization of previously "cold" TMEs to ICI therapy in vivo. Thus, our results introduce a rational strategy for modulating cancer cell-intrinsic programs via engineered STING enforcement to sensitize resistant tumors to ICI responsiveness.

VPS dependency after aneurysmal subarachnoid haemorrhage and influence of admission hyperglycaemia.

Introduction: Hydrocephalus after aneurysmal subarachnoid haemorrhage (aSAH) is a common complication which may lead to insertion of a ventriculoperitoneal shunt (VPS). Our aim is to evaluate a possible influence of specific clinical and biochemical factors on VPS dependency with special emphasis on hyperglycaemia on admission. Patients and methods: Retrospective analysis of a monocentric database of aSAH patients. Using univariable and multivariable logistic regression analysis we evaluated factors influencing VPS dependency, with a special focus on hyperglycaemia on blood sample within 24 h of admission, dichotomised at 126 mg/dl. Factors evaluated in the univariable analysis were age, sex, known diabetes, Hunt and Hess grade, Barrow Neurological Institute scale, treatment modality, extra-ventricular drain (EVD) insertion, complications (rebleeding, vasospasm, infarction, decompressive craniectomy, ventriculitis), outcome variables and laboratory parameters (glucose, C-reactive protein, procalcitonin). Results: We included 510 consecutive patients treated with acute aSAH requiring a VPS (mean age 58.2 years, 66% were female). An EVD was inserted in 387 (75.9%) patients. In the univariable analysis, VPS dependency was associated with hyperglycaemia on admission (OR 2.56, 95%CI 1.58-4.14, p < 0.001). In the multivariable regression analysis after stepwise backward regression, factors associated with VPS dependency were hyperglycaemia >126 mg/dl on admission (OR 1.93, 95%CI 1.13-3.30, p = 0.02), ventriculitis (OR 2.33, 95%CI 1.33-4.04, p = 0.003), Hunt and Hess grade (overall p-value 0.02) and decompressive craniectomy (OR 2.68, 95%CI 1.55-4.64, p < 0.001). Conclusion: Hyperglycaemia on admission was associated with an increased probability of VPS placement. If confirmed, this finding might facilitate treatment of these patients by accelerating insertion of a permanent draining system.

Targeting nucleic acid sensors in tumor cells to reprogram biogenesis and RNA cargo of extracellular vesicles for T cell-mediated cancer immunotherapy.

Tumor-derived extracellular vesicles (EVs) have been associated with immune evasion and tumor progression. We show that the RNA-sensing receptor RIG-I within tumor cells governs biogenesis and immunomodulatory function of EVs. Cancer-intrinsic RIG-I activation releases EVs, which mediate dendritic cell maturation and T cell antitumor immunity, synergizing with immune checkpoint blockade. Intact RIG-I, autocrine interferon signaling, and the GTPase Rab27a in tumor cells are required for biogenesis of immunostimulatory EVs. Active intrinsic RIG-I signaling governs composition of the tumor EV RNA cargo including small non-coding stimulatory RNAs. High transcriptional activity of EV pathway genes and RIG-I in melanoma samples associate with prolonged patient survival and beneficial response to immunotherapy. EVs generated from human melanoma after RIG-I stimulation induce potent antigen-specific T cell responses. We thus define a molecular pathway that can be targeted in tumors to favorably alter EV immunomodulatory function. We propose "reprogramming" of tumor EVs as a personalized strategy for T cell-mediated cancer immunotherapy.

Protein interactions in 3D: from interface evolution to drug discovery.

Over the past 10years, much research has been dedicated to the understanding of protein interactions. Large-scale experiments to elucidate the global structure of protein interaction networks have been complemented by detailed studies of protein interaction interfaces. Understanding the evolution of interfaces allows one to identify convergently evolved interfaces which are evolutionary unrelated but share a few key residues and hence have common binding partners. Understanding interaction interfaces and their evolution is an important basis for pharmaceutical applications in drug discovery. Here, we review the algorithms and databases on 3D protein interactions and discuss in detail applications in interface evolution, drug discovery, and interface prediction.