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Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes.

Abstract Background Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising. Methods RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models. Results An initial cluster analysis of RNA-seq expression data showed separation by the subjects’ gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091). Conclusions Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.

Abstract Melanoma is the most serious type of skin cancer that frequently spreads to other organs of the human body. Especially melanoma metastases to the brain (intracranial metastases) are hard to treat and a major cause of death of melanoma patients. Little is known about molecular alterations and altered mechanisms that distinguish intra- from extracranial melanoma metastases. So far, almost all existing studies compared intracranial metastases from one set of patients to extracranial metastases of an another set of melanoma patients. This neglects the important facts that each melanoma is highly individual and that intra- and extracranial melanoma metastases from the same patient are more similar to each other than to melanoma metastases from other patients in the same organ. To overcome this, we compared the gene expression profiles of 16 intracranial metastases to their corresponding 21 patient-matched extracranial metastases in a personalized way using a three-state Hidden Markov Model (HMM) to identify altered genes for each individual metastasis pair. This enabled three major findings by considering the predicted gene expression alterations across all patients: (i) most frequently altered pathways include cytokine-receptor interaction, calcium signaling, ECM-receptor interaction, cAMP signaling, Jak-STAT and PI3K/Akt signaling, (ii) immune-relevant signaling pathway genes were downregulated in intracranial metastases, and (iii) intracranial metastases were associated with a brain-like phenotype gene expression program. Further, the integration of all differentially expressed genes across the patient-matched melanoma metastasis pairs led to a set of 103 genes that were consistently down- or up-regulated in at least 11 of the 16 of the patients. This set of genes contained many genes involved in the regulation of immune responses, cell growth, cellular signaling and transport processes. An analysis of these genes in the TCGA melanoma cohort showed that the expression behavior of 11 genes was significantly associated with survival. Moreover, a comparison of the 103 genes to three closely related melanoma metastasis studies revealed a core set of eight genes that were consistently down- or upregulated in intra- compared to extracranial metastases in at least two of the three related studies (down: CILP, DPT, FGF7, LAMP3, MEOX2, TMEM119; up: GLDN, PMP2) including FGF7 that was also significantly associated with survival. Our findings contribute to a better characterization of genes and pathways that distinguish intra- from extracranial melanoma metastasis and provide important hints for future experimental studies to identify potential targets for new therapeutic approaches.

Abstract Background Focal adhesion signaling involving receptor tyrosine kinases (RTK) and integrins co-controls cancer cell survival and therapy resistance. However, co-dependencies between these receptors and therapeutically exploitable vulnerabilities remain largely elusive in HPV-negative head and neck squamous cell carcinoma (HNSCC). Methods The cytotoxic and radiochemosensitizing potential of targeting 10 RTK and β1 integrin was determined in up to 20 3D matrix-grown HNSCC cell models followed by drug screening and patient-derived organoid validation. RNA sequencing and protein-based biochemical assays were performed for molecular characterization. Bioinformatically identified transcriptomic signatures were applied to patient cohorts. Results Fibroblast growth factor receptor (FGFR 1–4) targeting exhibited the strongest cytotoxic and radiosensitizing effects as monotherapy and combined with β1 integrin inhibition, exceeding the efficacy of the other RTK studied. Pharmacological pan-FGFR inhibition elicited responses ranging from cytotoxicity/radiochemosensitization to resistance/radiation protection. RNA sequence analysis revealed a mesenchymal-to-epithelial transition (MET) in sensitive cell models, whereas resistant cell models exhibited a partial epithelial-to-mesenchymal transition (EMT). Accordingly, inhibition of EMT-associated kinases such as EGFR caused reduced adaptive resistance and enhanced (radio)sensitization to FGFR inhibition cell model- and organoid-dependently. Transferring the EMT-associated transcriptomic profiles to HNSCC patient cohorts not only demonstrated their prognostic value but also provided a conclusive validation of the presence of EGFR-related vulnerabilities that can be strategically exploited for therapeutic interventions. Conclusions This study demonstrates that pan-FGFR inhibition elicits a beneficial radiochemosensitizing and a detrimental radioprotective potential in HNSCC cell models. Adaptive EMT-associated resistance appears to be of clinical importance, and we provide effective molecular approaches to exploit this therapeutically.

Phosphoinositide 3-kinase (PI3K)-α represents a key intracellular signal transducer involved in the regulation of key cell functions such as cell survival and proliferation. Excessive activation of PI3Kα is considered one of the major determinants of cancer therapy resistance. Despite preclinical and clinical evaluation of PI3Kα inhibitors in various tumor entities, including head and neck squamous cell carcinoma (HNSCC), it remains elusive how conventional radiochemotherapy can be enhanced by concurrent PI3K inhibitors and how PI3K deactivation mechanistically exerts its effects. Here, we investigated the radiochemosensitizing potential and adaptation mechanisms of four PI3K inhibitors, Alpelisib, Copanlisib, AZD8186, and Idelalisib in eight HNSCC models grown under physiological, three-dimensional matrix conditions. We demonstrate that Alpelisib, Copanlisib and AZD8186 but not Idelalisib enhance radio- and radiochemosensitivity in the majority of HNSCC cell models (= responders) in a manner independent of PIK3CA mutation status. However, Alpelisib promotes MAPK signaling in non-responders compared to responders without profound impact on Akt, NFκB, TGFβ, JAK/STAT signaling and DNA repair. Bioinformatic analyses identified unique gene mutations associated with extracellular matrix to be more frequent in non-responder cell models than in responders. Finally, we demonstrate that targeting of the cell adhesion molecule β1 integrin on top of Alpelisib sensitizes non-responders to radiochemotherapy. Taken together, our study demonstrates the sensitizing potential of Alpelisib and other PI3K inhibitors in HNSCC models and uncovers a novel β1 integrin-dependent mechanism that may prove useful in overcoming resistance to PI3K inhibitors.

Contrary to other semiconductor alloys, incorporation of Ag into CuGaSe2 increases the bandgap, even though the lattice expands, and the Ga–Se bond length is theoretically predicted to decrease rather than increase. Herein, we experimentally confirm this peculiar bond length dependence of (Ag,Cu)GaSe2 using x-ray absorption spectroscopy. We further model the different anion displacements and estimate that their combined contribution to the bandgap bowing is close to zero. These findings differ from those for Cu(In,Ga)Se2 and demonstrate the diversity of chalcopyrite alloys and their properties.

Cancer presents as a highly heterogeneous disease with partly overlapping and partly distinct (epi)genetic characteristics. These characteristics determine inherent and acquired resistance, which need to be overcome for improving patient survival. In line with the global efforts in identifying druggable resistance factors, extensive preclinical research of the Cordes lab and others designated the cancer adhesome as a critical and general therapy resistance mechanism with multiple druggable cancer targets. In our study, we addressed pancancer cell adhesion mechanisms by connecting the preclinical datasets generated in the Cordes lab with publicly available transcriptomic and patient survival data. We identified similarly changed differentially expressed genes (scDEGs) in nine cancers and their corresponding cell models relative to normal tissues. Those scDEGs interconnected with 212 molecular targets from Cordes lab datasets generated during two decades of research on adhesome and radiobiology. Intriguingly, integrative analysis of adhesion associated scDEGs, TCGA patient survival and protein-protein network reconstruction revealed a set of overexpressed genes adversely affecting overall cancer patient survival and specifically the survival in radiotherapy-treated cohorts. This pancancer gene set includes key integrins (e.g. ITGA6, ITGB1, ITGB4) and their interconnectors (e.g. SPP1, TGFBI), affirming their critical role in the cancer adhesion resistome. In summary, this meta-analysis demonstrates the importance of the adhesome in general, and integrins together with their interconnectors in particular, as potentially conserved determinants and therapeutic targets in cancer.

Abstract Melanomas frequently metastasize to distant organs and especially intracranial metastases still represent a major clinical challenge. Epigenetic reprogramming of intracranial metastases is thought to be involved in therapy failure, but so far only little is known about patient-specific DNA-methylation differences between intra- and extracranial melanoma metastases. Hierarchical clustering of the methylomes of 24 patient-matched intra- and extracranial melanoma metastases pairs revealed that intra- and extracranial metastases of individual patients were more similar to each other than to metastases in the same tissue from other patients. Therefore, a personalized analysis of each metastases pair was done by a Hidden Markov Model to classify methylation levels of individual CpGs as decreased, unchanged or increased in the intra- compared to the extracranial metastasis. The predicted DNA-methylation alterations were highly patient-specific differing in the number and methylation states of altered CpGs. Nevertheless, four important general observations were made: (i) intracranial metastases of most patients mainly showed a reduction of DNA-methylation, (ii) cytokine signaling was most frequently affected by differential methylation in individual metastases pairs, but also MAPK, PI3K/Akt and ECM signaling were often altered, (iii) frequently affected genes were mainly involved in signaling, growth, adhesion or apoptosis, and (iv) an enrichment of functional terms related to channel and transporter activities supports previous findings for a brain-like phenotype. In addition, the derived set of 17 signaling pathway genes that distinguished intra- from extracranial metastases in more than 50% of patients included well-known oncogenes (e.g. PRKCA, DUSP6, BMP4) and several other genes known from neuronal disorders (e.g. EIF4B, SGK1, CACNG8). Moreover, associations of gene body methylation alterations with corresponding gene expression changes revealed that especially the three signaling pathway genes JAK3, MECOM, and TNXB differ strongly in their expression between patient-matched intra- and extracranial metastases. Our analysis contributes to an in-depth characterization of DNA-methylation differences between patient-matched intra- and extracranial melanoma metastases and may provide a basis for future experimental studies to identify targets for new therapeutic approaches.

Abstract Purpose IMpassion130 led to the approval of atezolizumab plus nab-paclitaxel as first-line treatment for patients with unresectable locally advanced or metastatic triple-negative, PD-L1 immune-cell positive breast cancer (BC) by the European Medicines Agency (EMA). The objective of the present study was to investigate the implementation, safety and efficacy of this combination in the initial phase after approval. Methods A retrospective data analysis including all BC patients who received atezolizumab and nab-paclitaxel between 1.1.2019 and 31.10.2020 at the Department of Obstetrics and Gynecology and the Department of Medicine 1, respectively, at the Medical University of Vienna, Austria, was performed. Progression-free survival (PFS) and overall survival (OS) were estimated with the Kaplan-Maier product-limit method. Owing to the retrospective nature of this study, all statistics must be considered exploratory. Results In total 20 patients were included in the study. Median follow-up was 7.1 months (IQR 5.2–9.1). Median PFS was 3.0 months (SE = .24; 95% CI [2.5; 3.5]). Median OS was 8.94 months (SE = 2.34, 95%CI [4.35; 13.53]). No new safety signals were observed. Conclusion The present study showed a considerably shorter PFS (3.0 vs. 7.5 months) and OS (8.94 vs. 25.0 months) than IMpassion130 putatively owing to the use of atezolizumab in later treatment lines, more aggressive tumors and a study population with higher morbidity compared to the pivotal trial.

BackgroundFocal segmental glomerulosclerosis (FSGS) is a common cause of end-stage kidney disease requiring kidney transplantation and can recur in the allograft in 30-80% of recipients resulting in reduced graft survival. Plasmapheresis has shown efficacy in treating some cases of recurrent FSGS but isolated plasmapheresis has not demonstrated efficacy in preventing recurrent FSGS. Rituximab has had anecdotal success in preventing recurrence in a single center study but has not been studied in combination with plasmapheresis for preventing FSGS recurrence.MethodsWe are conducting a randomized, controlled, multicenter clinical trial of adult and pediatric kidney transplant recipients with primary FSGS to assess whether plasmapheresis in combination with rituximab prevents recurrent disease post-transplantation.DiscussionRituximab combined with plasmapheresis is a promising, novel therapy to prevent recurrent FSGS, a disease with limited therapeutic options and no consensus guidelines for prevention or treatment.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03763643, identifier NCT03763643.

We report on the excitonic transition energy E0 and spin–orbit split-off energy Δ0 of γ-AgxCu1–xI alloy thin films studied by using reflectivity measurements at temperatures between 20 K and 290 K. The observed bowing behavior of the E0 transition as a function of the alloy composition is explained based on first-principles band structure calculations in terms of different physical and chemical contributions within the description of ordered alloys. The spin–orbit coupling is found to increase from a value of 640 meV for CuI to approximately 790 meV for AgI. Furthermore, we show that the temperature-dependent bandgap shift between 20 K and 290 K decreases with increasing Ag-content from 25 meV for CuI to 6 meV for AgI. We attribute this behavior mostly to changes in the contribution of thermal lattice expansion to the bandgap shift.

BackgroundLow anterior resection for rectal cancer is commonly associated with a diverting stoma. In general, the stoma is closed 3 months after the initial operation. The diverting stoma reduces the rate of anastomotic leakage as well as the severeness of a potential leakage itself. Nevertheless, anastomotic leakage is still a life-threatening complication and might reduce the quality of life in the short and long term. In case of leakage, the construction can be converted into a Hartmann situation or it could be treated by endoscopic vacuum therapy or by leaving the drains. In recent years, endoscopic vacuum therapy has become the treatment of choice in many institutions. In this study, the hypothesis is to be evaluated, if a prophylactic endoscopic vacuum therapy reduces the rate of anastomotic leakage after rectal resections.MethodsA multicenter parallel group randomized controlled trial is planned in as many as possible centers in Europe. The study aims to recruit 362 analyzable patients with a resection of the rectum combined with a diverting ileostoma. The anastomosis has to be between 2 and 8 cm off the anal verge. Half of these patients receive a sponge for 5 days, and the control group is treated as usual in the participating hospitals. There will be a check for anastomotic leakage after 30 days. Primary end point is the rate of anastomotic leakages. The study will have 60% power to detect a difference of 10%, at a one-sided alpha significance level of 5%, assuming an anastomosis leakage rate of 10%–15%.DiscussionIf the hypothesis proves to be true, anastomosis leakage could be reduced significantly by placing a vacuum sponge over the anastomosis for 5 days.Trial registrationThe trial is registered at DRKS: DRKS00023436. It has been accredited by Onkocert of the German Society of Cancer: ST-D483. The leading Ethics Committee is the Ethics Committee of Rostock University with the registration ID A 2019–0203.

T-cell prolymphocytic leukemia (T-PLL) is a rare blood cancer with poor prognosis. Overexpression of the proto-oncogene TCL1A and missense mutations of the tumor suppressor ATM are putative main drivers of T-PLL development, but so far only little is known about the existence of T-PLL gene expression subtypes. We performed an in-depth computational reanalysis of 68 gene expression profiles of one of the largest currently existing T-PLL patient cohorts. Hierarchical clustering combined with bootstrapping revealed three robust T-PLL gene expression subgroups. Additional comparative analyses revealed similarities and differences of these subgroups at the level of individual genes, signaling and metabolic pathways, and associated gene regulatory networks. Differences were mainly reflected at the transcriptomic level, whereas gene copy number profiles of the three subgroups were much more similar to each other, except for few characteristic differences like duplications of parts of the chromosomes 7, 8, 14, and 22. At the network level, most of the 41 predicted potential major regulators showed subgroup-specific expression levels that differed at least in comparison to one other subgroup. Functional annotations suggest that these regulators contribute to differences between the subgroups by altering processes like immune responses, angiogenesis, cellular respiration, cell proliferation, apoptosis, or migration. Most of these regulators are known from other cancers and several of them have been reported in relation to leukemia (e.g. AHSP, CXCL8, CXCR2, ELANE, FFAR2, G0S2, GIMAP2, IL1RN, LCN2, MBTD1, PPP1R15A). The existence of the three revealed T-PLL subgroups was further validated by a classification of T-PLL patients from two other smaller cohorts. Overall, our study contributes to an improved stratification of T-PLL and the observed subgroup-specific molecular characteristics could help to develop urgently needed targeted treatment strategies.

T-cell prolymphocytic leukemia (T-PLL) is the most common mature T-cell leukemia. It is a typically aggressively growing and chemotherapy-resistant malignancy with a poor prognosis. T-PLL cells resemble activated, post-thymic T-lymphocytes with memory-type effector functions. Constitutive transcriptional activation of genes of the T-cell leukemia 1 (TCL1) family based on genomic inversions/translocations is recognized as a key event in T-PLL’s pathogenesis. TCL1’s multiple effector pathways include the enhancement of T-cell receptor (TCR) signals. New molecular dependencies around responses to DNA damage, including repair and apoptosis regulation, as well as alterations of cytokine and non-TCR activation signaling were identified as perturbed hallmark pathways within the past years. We currently witness these vulnerabilities to be interrogated in first pre-clinical concepts and initial clinical testing in relapsed/refractory T-PLL patients. We summarize here the current knowledge on the molecular understanding of T-PLL’s pathobiology and critically assess the true translational progress around this to help appraisal by caregivers and patients. Overall, the contemporary concepts on T-PLL’s pathobiology are condensed in a comprehensive mechanistic disease model and promising interventional strategies derived from it are highlighted.

Abstract Background With the introduction of Olaparib treatment for BRCA-deficient recurrent ovarian cancer, testing for somatic and/or germline mutations in BRCA1/2 genes in tumor tissues became essential for treatment decisions. In most cases only formalin-fixed paraffin-embedded (FFPE) samples, containing fragmented and chemically modified DNA of minor quality, are available. Thus, multiplex PCR-based sequencing is most commonly applied in routine molecular testing, which is predominantly focused on the identification of known hot spot mutations in oncogenes. Methods We compared the overall performance of an adjusted targeted capture-based enrichment protocol and a multiplex PCR-based approach for calling of pathogenic SNVs and InDels using DNA extracted from 13 FFPE tissue samples. We further applied both strategies to seven blood samples and five matched FFPE tumor tissues of patients with known germline exon-spanning deletions and gene-wide duplications in BRCA1/2 to evaluate CNV detection based solely on panel NGS data. Finally, we analyzed DNA from FFPE tissues of 11 index patients from families suspected of having hereditary breast and ovarian cancer, of whom no blood samples were available for testing, in order to identify underlying pathogenic germline BRCA1/2 mutations. Results The multiplex PCR-based protocol produced inhomogeneous coverage among targets of each sample and between samples as well as sporadic amplicon drop out, leading to insufficiently or non-covered nucleotides, which subsequently hindered variant detection. This protocol further led to detection of PCR-artifacts that could easily have been misinterpreted as pathogenic mutations. No such limitations were observed by application of an adjusted targeted capture-based protocol, which allowed for CNV calling with 86% sensitivity and 100% specificity. All pathogenic CNVs were confirmed in the five matched FFPE tumor samples from patients carrying known pathogenic germline mutations and we additionally identified somatic loss of the second allele in BRCA1/2. Furthermore we detected pathogenic BRCA1/2 variants in four the eleven FFPE samples from patients of whom no blood was available for analysis. Conclusions We demonstrate that an adjusted targeted capture-based enrichment protocol is superior to commonly applied multiplex PCR-based protocols for reliable BRCA1/2 variant detection, including CNV-detection, using FFPE tumor samples.

DNA-methyltransferase 3A (DNMT3A) mutations belong to the most frequent genetic aberrations found in adult acute myeloid leukemia (AML). Recent evidence suggests that these mutations arise early in leukemogenesis, marking leukemic progenitors and stem cells, and persist through consolidation chemotherapy, providing a pool for AML relapse. Currently, there are no therapeutic approaches directed specifically against this cell population. To unravel therapeutically actionable targets in mutant DNMT3A-driven AML cells, we have performed a focused RNAi screen in a panel of 30 primary AML samples, all carrying a DNMT3A R882 mutation. As one of the strongest hits, we identified MDM4 as a gene essential for proliferation of primary DNMT3AWT/R882X AML cells. We analyzed a publicly available RNA-Seq dataset of primary normal karyotype (NK) AML samples and found a trend towards MDM4 transcript overexpression particularly in DNMT3A-mutant samples. Moreover, we found that the MDM2/4 inhibitor ALRN-6924 impairs growth of DNMT3AWT/R882X primary cells in vitro by inducing cell cycle arrest through upregulation of p53 target genes. Our results suggest that MDM4 inhibition is a potential target in NK-AML patients bearing DNMT3A R882X mutations.

Summary: The Hedgehog (Hh) and Wnt/β-Catenin (Wnt) cascades are morphogen pathways whose pronounced influence on adult liver metabolism has been identified in recent years. How both pathways communicate and control liver metabolic functions are largely unknown. Detecting core components of Wnt and Hh signaling and mathematical modeling showed that both pathways in healthy liver act largely complementary to each other in the pericentral (Wnt) and the periportal zone (Hh) and communicate mainly by mutual repression. The Wnt/Hh module inversely controls the spatiotemporal operation of various liver metabolic pathways, as revealed by transcriptome, proteome, and metabolome analyses. Shifting the balance to Wnt (activation) or Hh (inhibition) causes pericentralization and periportalization of liver functions, respectively. Thus, homeostasis of the Wnt/Hh module is essential for maintaining proper liver metabolism and to avoid the development of certain metabolic diseases. With caution due to minor species-specific differences, these conclusions may hold for human liver as well. : Wnt/β-catenin and Hh signaling contribute to embryogenesis as well as to the maintenance of organ homeostasis through intensive crosstalk. Here, Kolbe et al. describe that both pathways act largely complementary to each other in the healthy liver and that this crosstalk is responsible for the maintenance of metabolic zonation.

Abstract Oligodendrogliomas are primary human brain tumors with a characteristic 1p/19q co-deletion of important prognostic relevance, but little is known about the pathology of this chromosomal mutation. We developed a network-based approach to identify novel cancer gene candidates in the region of the 1p/19q co-deletion. Gene regulatory networks were learned from gene expression and copy number data of 178 oligodendrogliomas and further used to quantify putative impacts of differentially expressed genes of the 1p/19q region on cancer-relevant pathways. We predicted 8 genes with strong impact on signaling pathways and 14 genes with strong impact on metabolic pathways widespread across the region of the 1p/19 co-deletion. Many of these candidates (e.g. ELTD1, SDHB, SEPW1, SLC17A7, SZRD1, THAP3, ZBTB17) are likely to push, whereas others (e.g. CAP1, HBXIP, KLK6, PARK7, PTAFR) might counteract oligodendroglioma development. For example, ELTD1, a functionally validated glioblastoma oncogene located on 1p, was overexpressed. Further, the known glioblastoma tumor suppressor SLC17A7 located on 19q was underexpressed. Moreover, known epigenetic alterations triggered by mutated SDHB in paragangliomas suggest that underexpressed SDHB in oligodendrogliomas may support and possibly enhance the epigenetic reprogramming induced by the IDH-mutation. We further analyzed rarely observed deletions and duplications of chromosomal arms within oligodendroglioma subcohorts identifying putative oncogenes and tumor suppressors that possibly influence the development of oligodendroglioma subgroups. Our in-depth computational study contributes to a better understanding of the pathology of the 1p/19q co-deletion and other chromosomal arm mutations. This might open opportunities for functional validations and new therapeutic strategies.

Abstract Background In the course of neurological early rehabilitation, decannulation is attempted in tracheotomized patients after weaning due to its considerable prognostic significance. We aimed to identify predictors of a successful tracheostomy decannulation. Methods From 09/2014 to 03/2016, 831 tracheotomized and weaned patients (65.4 ± 12.9 years, 68% male) were included consecutively in a prospective multicentric observation study. At admission, sociodemographic and clinical data (e.g. relevant neurological and internistic diseases, duration of mechanical ventilation, tracheotomy technique, and nutrition) as well as functional assessments (Coma Recovery Scale-Revised (CRS-R), Early Rehabilitation Barthel Index, Bogenhausener Dysphagia Score) were collected. Complications and the success of the decannulation procedure were documented at discharge. Results Four hundred seventy patients (57%) were decannulated. The probability of decannulation was significantly negatively associated with increasing age (OR 0.68 per SD = 12.9 years, p

Abstract Background Molecular data of histologically classified oligodendrogliomas are available offering the possibility to stratify these human brain tumors into clinically relevant molecular subtypes. Methods Gene copy number, mutation, and expression data of 193 histologically classified oligodendrogliomas from The Cancer Genome Atlas (TCGA) were analyzed by well-established computational approaches (unsupervised clustering, statistical testing, network inference). Results We applied hierarchical clustering to tumor gene copy number profiles and revealed three molecular subgroups within histologically classified oligodendrogliomas. We further screened these subgroups for molecular glioma markers (1p/19q co-deletion, IDH mutation, gain of chromosome 7 and loss of chromosome 10) and found that our subgroups largely resemble known molecular glioma subtypes. We excluded glioblastoma-like tumors (7a10d subgroup) and derived a gene expression signature distinguishing histologically classified oligodendrogliomas with concurrent 1p/19q co-deletion and IDH mutation (1p/19q subgroup) from those with predominant IDH mutation alone (IDHme subgroup). Interestingly, many signature genes were part of signaling pathways involved in the regulation of cell proliferation, differentiation, migration, and cell-cell contacts. We further learned a gene regulatory network associated with the gene expression signature revealing novel putative major regulators with functions in cytoskeleton remodeling (e.g. APBB1IP, VAV1, ARPC1B), apoptosis (CCNL2, CREB3L1), and neural development (e.g. MYTIL, SCRT1, MEF2C) potentially contributing to the manifestation of differences between both subgroups. Moreover, we revealed characteristic expression differences of several HOX and SOX transcription factors suggesting the activity of different glioma stemness programs in both subgroups. Conclusions We show that gene copy number profiles alone are sufficient to derive molecular subgroups of histologically classified oligodendrogliomas that are well-embedded into general glioma classification schemes. Moreover, our revealed novel putative major regulators and characteristic stemness signatures indicate that different developmental programs might be active in these subgroups, providing a basis for future studies.

Radiation therapy is an important and effective treatment option for prostate cancer, but high-risk patients are prone to relapse due to radioresistance of cancer cells. Molecular mechanisms that contribute to radioresistance are not fully understood. Novel computational strategies are needed to identify radioresistance driver genes from hundreds of gene copy number alterations. We developed a network-based approach based on lasso regression in combination with network propagation for the analysis of prostate cancer cell lines with acquired radioresistance to identify clinically relevant marker genes associated with radioresistance in prostate cancer patients. We analyzed established radioresistant cell lines of the prostate cancer cell lines DU145 and LNCaP and compared their gene copy number and expression profiles to their radiosensitive parental cells. We found that radioresistant DU145 showed much more gene copy number alterations than LNCaP and their gene expression profiles were highly cell line specific. We learned a genome-wide prostate cancer-specific gene regulatory network and quantified impacts of differentially expressed genes with directly underlying copy number alterations on known radioresistance marker genes. This revealed several potential driver candidates involved in the regulation of cancer-relevant processes. Importantly, we found that ten driver candidates from DU145 (ADAMTS9, AKR1B10, CXXC5, FST, FOXL1, GRPR, ITGA2, SOX17, STARD4, VGF) and four from LNCaP (FHL5, LYPLAL1, PAK7, TDRD6) were able to distinguish irradiated prostate cancer patients into early and late relapse groups. Moreover, in-depth in vitro validations for VGF (Neurosecretory protein VGF) showed that siRNA-mediated gene silencing increased the radiosensitivity of DU145 and LNCaP cells. Our computational approach enabled to predict novel radioresistance driver gene candidates. Additional preclinical and clinical studies are required to further validate the role of VGF and other candidate genes as potential biomarkers for the prediction of radiotherapy responses and as potential targets for radiosensitization of prostate cancer.

Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub ( https://github.com/tbuder/CellTrans ).

Many models in which Lorentz symmetry is spontaneously broken in a curved spacetime do so via a “Lorentz-violating” (LV) vector or tensor field, which dynamically takes on a vacuum expectation value and provides additional local geometric structure beyond the metric. The kinetic terms of such a field will not necessarily be decoupled from the kinetic terms of the metric, and will generically lead to a set of coupled equations for the perturbations of the metric and the LV field. In some models, however, the imposition of certain additional conditions can decouple these equations, yielding an “effective equation” for the metric perturbations alone. The resulting effective equation may depend on the metric in a gauge-invariant way, or it may be gauge-dependent. The only two known models yielding gauge-invariant effective equations involve differential forms; I show in this work that the obvious generalizations of these models do not yield gauge-invariant effective equations. Meanwhile, I show that a gauge-dependent effective equation may be obtained from any “tensor Klein–Gordon” model under similar assumptions. Finally, I discuss the implications of this work in the search for Lorentz-violating gravitational effects.

Changes in gene expression programs play a central role in cancer. Chromosomal aberrations such as deletions, duplications and translocations of DNA segments can lead to highly significant positive correlations of gene expression levels of neighboring genes. This should be utilized to improve the analysis of tumor expression profiles. Here, we develop a novel model class of autoregressive higher-order Hidden Markov Models (HMMs) that carefully exploit local data-dependent chromosomal dependencies to improve the identification of differentially expressed genes in tumor. Autoregressive higher-order HMMs overcome generally existing limitations of standard first-order HMMs in the modeling of dependencies between genes in close chromosomal proximity by the simultaneous usage of higher-order state-transitions and autoregressive emissions as novel model features. We apply autoregressive higher-order HMMs to the analysis of breast cancer and glioma gene expression data and perform in-depth model evaluation studies. We find that autoregressive higher-order HMMs clearly improve the identification of overexpressed genes with underlying gene copy number duplications in breast cancer in comparison to mixture models, standard first- and higher-order HMMs, and other related methods. The performance benefit is attributed to the simultaneous usage of higher-order state-transitions in combination with autoregressive emissions. This benefit could not be reached by using each of these two features independently. We also find that autoregressive higher-order HMMs are better able to identify differentially expressed genes in tumors independent of the underlying gene copy number status in comparison to the majority of related methods. This is further supported by the identification of well-known and of previously unreported hotspots of differential expression in glioblastomas demonstrating the efficacy of autoregressive higher-order HMMs for the analysis of individual tumor expression profiles. Moreover, we reveal interesting novel details of systematic alterations of gene expression levels in known cancer signaling pathways distinguishing oligodendrogliomas, astrocytomas and glioblastomas. An implementation is available under www.jstacs.de/index.php/ARHMM.

Cohesin subunit SMC1β is specific and essential for meiosis. Previous studies showed functions of SMC1β in determining the axis-loop structure of synaptonemal complexes (SCs), in providing sister chromatid cohesion (SCC) in metaphase I and thereafter, in protecting telomere structure, and in synapsis. However, several central questions remained unanswered and concern roles of SMC1β in SCC and synapsis and processes related to these two processes. Here we show that SMC1β substantially supports prophase I SCC at centromeres but not along chromosome arms. Arm cohesion and some of centromeric cohesion in prophase I are provided by non-phosphorylated SMC1α. Besides supporting synapsis of autosomes, SMC1β is also required for synapsis and silencing of sex chromosomes. In absence of SMC1β, the silencing factor γH2AX remains associated with asynapsed autosomes and fails to localize to sex chromosomes. Microarray expression studies revealed up-regulated sex chromosome genes and many down-regulated autosomal genes. SMC1β is further required for non-homologous chromosome associations observed in absence of SPO11 and thus of programmed double-strand breaks. These breaks are properly generated in Smc1β⁻/⁻ spermatocytes, but their repair is delayed on asynapsed chromosomes. SMC1α alone cannot support non-homologous associations. Together with previous knowledge, three main functions of SMC1β have emerged, which have multiple consequences for spermatocyte biology: generation of the loop-axis architecture of SCs, homologous and non-homologous synapsis, and SCC starting in early prophase I.

Array-based comparative genomic hybridization (Array-CGH) is an important technology in molecular biology for the detection of DNA copy number polymorphisms between closely related genomes. Hidden Markov Models (HMMs) are popular tools for the analysis of Array-CGH data, but current methods are only based on first-order HMMs having constrained abilities to model spatial dependencies between measurements of closely adjacent chromosomal regions. Here, we develop parsimonious higher-order HMMs enabling the interpolation between a mixture model ignoring spatial dependencies and a higher-order HMM exhaustively modeling spatial dependencies. We apply parsimonious higher-order HMMs to the analysis of Array-CGH data of the accessions C24 and Col-0 of the model plant Arabidopsis thaliana. We compare these models against first-order HMMs and other existing methods using a reference of known deletions and sequence deviations. We find that parsimonious higher-order HMMs clearly improve the identification of these polymorphisms. Moreover, we perform a functional analysis of identified polymorphisms revealing novel details of genomic differences between C24 and Col-0. Additional model evaluations are done on widely considered Array-CGH data of human cell lines indicating that parsimonious HMMs are also well-suited for the analysis of non-plant specific data. All these results indicate that parsimonious higher-order HMMs are useful for Array-CGH analyses. An implementation of parsimonious higher-order HMMs is available as part of the open source Java library Jstacs (www.jstacs.de/index.php/PHHMM).