Previously reported CCDC26 risk variant and novel germline variants in GALNT13, AR, and MYO10 associated with familial glioma in Finland.

Predisposing factors underlying familial aggregation of non-syndromic gliomas are still to be uncovered. Whole-exome sequencing was performed in four Finnish families with brain tumors to identify rare predisposing variants. A total of 417 detected exome variants and 102 previously reported glioma-related variants were further genotyped in 19 Finnish families with brain tumors using targeted sequencing. Rare damaging variants in GALNT13, MYO10 and AR were identified. Two families carried either c.553C>T (R185C) or c.1214T>A (L405Q) on GALNT13. Variant c.553C>T is located on the substrate-binding site of GALNT13. AR c.2180G>T (R727L), which is located on a ligand-binding domain of AR, was detected in two families, one of which also carried a GALNT13 variant. MYO10 c.4448A>G (N1483S) was detected in two families and c.1511C>T (A504V) variant was detected in one family. Both variants are located on functional domains related to MYO10 activity in filopodia formation. In addition, affected cases in six families carried a known glioma risk variant rs55705857 in CCDC26 and low-risk glioma variants. These novel findings indicate polygenic inheritance of familial glioma in Finland and increase our understanding of the genetic contribution to familial glioma susceptibility.

Aberrant DNA methylation distorts developmental trajectories in atypical teratoid/rhabdoid tumors.

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness and aberrant but still unresolved epigenetic regulation. To better understand their malignancy, we investigated how AT/RT-specific DNA hypermethylation was associated with gene expression and altered transcription factor binding and how it is linked to upstream regulation. Medulloblastomas, choroid plexus tumors, pluripotent stem cells, and fetal brain were used as references. A part of the genomic regions, which were hypermethylated in AT/RTs similarly as in pluripotent stem cells and demethylated in the fetal brain, were targeted by neural transcriptional regulators. AT/RT-unique DNA hypermethylation was associated with polycomb repressive complex 2 and linked to suppressed genes with a role in neural development and tumorigenesis. Activity of the several NEUROG/NEUROD pioneer factors, which are unable to bind to methylated DNA, was compromised via the suppressed expression or DNA hypermethylation of their target sites, which was also experimentally validated for NEUROD1 in medulloblastomas and AT/RT samples. These results highlight and characterize the role of DNA hypermethylation in AT/RT malignancy and halted neural cell differentiation.

Identification of long noncoding RNAs with aberrant expression in prostate cancer metastases.

Prostate cancer (PCa) is the second-most common cause of male cancer-related death in western industrialized countries, and the emergence of metastases is a key challenge in the treatment of PCa. Accumulating studies have shown that long noncoding RNAs (lncRNAs) play an important role in the regulation of diverse cellular and molecular processes during the development and progression of cancer. Here, we utilized a unique cohort of castration-resistant prostate cancer metastases (mCRPC) and corresponding localized tumors and RNA sequencing (RNA-seq). First, we showed that patient-to-patient variability accounted for most of the variance in lncRNA expression between the samples, suggesting that genomic alterations in the samples are the main drivers of lncRNA expression in PCa metastasis. Subsequently, we identified 27 lncRNAs with differential expression (DE-lncRNAs) between metastases and corresponding primary tumors, suggesting that they are mCRPC-specific lncRNAs. Analyses of potential regulation by transcription factors (TFs) revealed that approximately half of the DE-lncRNAs have at least one binding site for the androgen receptor in their regulatory regions. In addition, TF enrichment analysis revealed the enrichment of binding sites for PCa-associated TFs, such as FOXA1 and HOXB13, in the regulatory regions of the DE-lncRNAs. In a cohort of prostatectomy-treated prostate tumors, four of the DE-lncRNAs showed association with progression-free time and two of them (lnc-SCFD2-2 and lnc-R3HCC1L-8) were independent prognostic markers. Our study highlights several mCRPC-specific lncRNAs that might be important in the progression of the disease to the metastatic stage and may also serve as potential biomarkers for aggressive PCa.

FURIN regulates cytotoxic T-lymphocyte effector function and memory cell transition in mice.

The proprotein convertase subtilisin/kexins (PCSKs) regulate biological actions by cleaving immature substrate proteins. The archetype PCSK, FURIN, promotes the pathogenicity of viruses by proteolytically processing viral proteins. FURIN has also important regulatory functions in both innate and adaptive immune responses but its role in the CD8+ CTLs remains enigmatic. We used a T-cell-specific FURIN deletion in vivo to demonstrate that FURIN promotes host response against the CTL-dependent lymphocytic choriomeningitis virus by virtue of restricting viral burden and augmenting interferon gamma (IFNG) production. We also characterized Furin KO CD8+ T cells ex vivo, including after their activation with FURIN regulating cytokines IL12 or TGFB1. Furin KO CD8+ T cells show an inherently activated phenotype characterized by the upregulation of effector genes and increased frequencies of CD44+ , TNF+ , and IFNG+ cells. In the activated CTLs, FURIN regulates the productions of IL2, TNF, and GZMB and the genes associated with the TGFBR-signaling pathway. FURIN also controls the expression of Eomes, Foxo1, and Bcl6 and the levels of ITGAE and CD62L, which implies a role in the development of CTL memory. Collectively, our data suggest that the T-cell expressed FURIN is important for host responses in viral infections, CTL homeostasis/activation, and memory development.

Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems.

Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al. Nat Commun 10:4716, 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs' applicability in cancer research.

Adaptive and non-adaptive gene expression responses in prostate cancer during androgen deprivation.

Androgen deprivation therapy is the cornerstone treatment of advanced prostate cancer. Eventually prostate cancer cells overcome androgen deprivation therapy, giving rise to castration resistant prostate cancer (CRPC) characterized by increased androgen receptor (AR) activity. Understanding the cellular mechanisms leading to CRPC is needed for development of novel treatments. We used long-term cell cultures to model CRPC; a testosterone-dependent cell line (VCaP-T) and cell line adapted to grow in low testosterone (VCaP-CT). These were used to uncover persistent and adaptive responses to testosterone level. RNA was sequenced to study AR-regulated genes. Expression level changed due to testosterone depletion in 418 genes in VCaP-T (AR-associated genes). To evaluate significance for CRPC growth, we compared which of them were adaptive i.e., restored expression level in VCaP-CT. Adaptive genes were enriched to steroid metabolism, immune response and lipid metabolism. The Cancer Genome Atlas Prostate Adenocarcinoma data were used to assess the association with cancer aggressiveness and progression-free survival. Expressions of 47 AR-associated or association gaining genes were statistically significant markers for progression-free survival. These included genes related to immune response, adhesion and transport. Taken together, we identified and clinically validated multiple genes being linked with progression of prostate cancer and propose several novel risk genes. Possible use as biomarkers or therapeutic targets should be studied further.

Nonmalignant AR-positive prostate epithelial cells and cancer cells respond differently to androgen.

Prostate cancer research suffers from the lack of suitable models to study the role of normal cells in prostate carcinogenesis. To address this challenge, we developed a cell line model mimicking luminal prostate epithelial cells by modifying the immortalized prostate epithelial cell line RWPE-1 to constitutively express the androgen receptor (AR). RWPE-1-AR cells express known AR target genes, and exhibit coexpression of luminal and basal markers characteristic of transient amplifying cells, and an RNA signature resembling prostate luminal progenitor cells. Under unstimulated conditions, constitutive AR expression does not have a biologically significant effect on the proliferation of RWPE-1 cells, but when stimulated by androgens, growth is retarded. The transcriptional response of RWPE-1-AR cells to androgen stimulation involves suppression of the growth-related KRAS pathway and is thus markedly different from that of the prostate cancer cell line LNCaP and its derivative AR-overexpressing LNCaP-ARhi cells, in which growth- and cancer-related pathways are upregulated. Hence, the nonmalignant AR-positive RWPE-1-AR cell line model could be used to study the transformation of the prostate epithelium.

Functional human cell-based vascularised cardiac tissue model for biomedical research and testing.

Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC) are widely used in in vitro biomedical research and testing. However, fully matured, adult cardiomyocyte characteristics have not been achieved. To improve the maturity and physiological relevance of hiPSC-derived cardiomyocytes, we co-cultured them with preconstructed vascular-like networks to form a functional, human cell-based cardiac tissue model. The morphology and gene expression profiles indicated advanced maturation in the cardiac tissue model compared to those of a cardiomyocyte monoculture. The cardiac tissue model's functionality was confirmed by measuring the effects of 32 compounds with multielectrode array and comparing results to human data. Our model predicted the cardiac effects with a predictive accuracy of 91%, sensitivity of 90% and specificity of 100%. The correlation between the effective concentration (EC50) and the reported clinical plasma concentrations was 0.952 (R2 = 0.905). The developed advanced human cell-based cardiac tissue model showed characteristics and functionality of human cardiac tissue enabling accurate transferability of gained in vitro data to human settings. The model is standardized and thus, it would be highly useful in biomedical research and cardiotoxicity testing.

The transcription factor network of E. coli steers global responses to shifts in RNAP concentration.

The robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the gene's numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.

Combined Longitudinal Clinical and Autopsy Phenomic Assessment in Lethal Metastatic Prostate Cancer: Recommendations for Advancing Precision Medicine.

BACKGROUND: Systematic identification of data essential for outcome prediction in metastatic prostate cancer (mPC) would accelerate development of precision oncology. OBJECTIVE: To identify novel phenotypes and features associated with mPC outcome, and to identify biomarker and data requirements to be tested in future precision oncology trials. DESIGN SETTING AND PARTICIPANTS: We analyzed deep longitudinal clinical, neuroendocrine expression, and autopsy data of 33 men who died from mPC between 1995 and 2004 (PELICAN33), and related findings to mPC biomarkers reported in the literature. INTERVENTION: Thirty-three men prospectively consented to participate in an integrated clinical-molecular rapid autopsy study of mPC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Data exploration with correction for multiple testing and survival analysis from the time of diagnosis to time to death and time to first occurrence of severe pain as outcomes were carried out. The effect of seven complications on the modeled probability of dying within 2 yr after presenting with the complication was evaluated using logistic regression. RESULTS AND LIMITATIONS: Feature exploration revealed novel phenotypes related to mPC outcome. Four complications (pleural effusion, severe anemia, severe or controlled pain, and bone fracture) predict the likelihood of death within 2 yr. Men with Gleason grade group 5 cancers developed severe pain sooner than those with lower-grade tumors. Surprisingly, neuroendocrine (NE) differentiation was frequently observed in the setting of high serum prostate-specific antigen (PSA) levels (≥30 ng/ml). In 4/33 patients, no controlled (requiring analgesics) or severe pain was detected, and strikingly, 14/15 metastatic sites studied in these men did not express NE markers, suggesting an inverse relationship between NE differentiation and pain in mPC. Intracranial subdural metastasis is common (36%) and is usually clinically undetected. Categorization of "skeletal-related events" complications used in recent studies likely obscures the understanding of spinal cord compression and fracture. Early death from prostate cancer was identified in a subgroup of men with a low longitudinal PSA bandwidth. Cachexia is common (body mass index <0.89 in 24/31 patients) but limited to the last year of life. Biomarker review identified 30 categories of mPC biomarkers in need of winnowing in future trials. All findings require validation in larger cohorts, preferably alongside data from this study. CONCLUSIONS: The study identified novel outcome subgroups for future validation and provides "vision for mPC precision oncology 2020-2050" draft recommendations for future data collection and biomarker studies. PATIENT SUMMARY: To better understand variation in metastatic prostate cancer behavior, we assembled and analyzed longitudinal clinical and autopsy records in 33 men. We identified novel outcomes, phenotypes, and aspects of disease burden to be tested and refined in future trials.

Proprotein convertase subtilisin/kexin type 9 regulates the production of acute-phase reactants from the liver.

BACKGROUND & AIMS: Proprotein convertase subtilisin/kexin type 9 (PCSK9) controls blood cholesterol levels by fostering the LDL receptor (LDLR) degradation in hepatocytes. Additionally, PCSK9 has been suggested to participate in immunoregulation by modulating cytokine production. We studied the immunological role of PCSK9 in Streptococcus pneumoniae bacteraemia in vivo and in a human hepatocyte cell line. METHODS: CRISPR/Cas9 mutagenesis was utilized to create pcsk9 knock-out (KO) zebrafish, which were infected with S pneumoniae to assess the role of PCSK9 for the survival of the fish and in the transcriptomic response of the liver. The direct effects of PCSK9 on the expression of acute-phase reaction (APR) genes were studied in HepG2 cells. RESULTS: The pcsk9 KO zebrafish lines (pcsk9tpu-13 and pcsk9tpu-2,+15 ) did not show developmental defects or gross phenotypical differences. In the S pneumoniae infected zebrafish, the mortality of pcsk9 KOs was similar to the controls. A liver-specific gene expression analysis revealed that a pneumococcal challenge upregulated pcsk9, and that the pcsk9 deletion reduced the expression of APR genes, including hepcidin antimicrobial peptide (hamp) and complement component 7b (c7b). Accordingly, silencing PCSK9 in vitro in HepG2 cells using small interfering RNAs (siRNAs) decreased HAMP expression. CONCLUSIONS: We demonstrate that PCSK9 is not critical for zebrafish survival in a systemic pneumococcal infection. However, PCSK9 deficiency was associated with the lower expression of APR genes in zebrafish and altered the expression of innate immunity genes in a human hepatocyte cell line. Overall, our data suggest an evolutionarily conserved function for PCSK9 in APR in the liver.

AR and ERG drive the expression of prostate cancer specific long noncoding RNAs.

Long noncoding RNAs (lncRNAs) play pivotal roles in cancer development and progression, and some function in a highly cancer-specific manner. However, whether the cause of their expression is an outcome of a specific regulatory mechanism or nonspecific transcription induced by genome reorganization in cancer remains largely unknown. Here, we investigated a group of lncRNAs that we previously identified to be aberrantly expressed in prostate cancer (PC), called TPCATs. Our high-throughput real-time PCR experiments were integrated with publicly available RNA-seq and ChIP-seq data and revealed that the expression of a subset of TPCATs is driven by PC-specific transcription factors (TFs), especially androgen receptor (AR) and ETS-related gene (ERG). Our in vitro validations confirmed that AR and ERG regulated a subset of TPCATs, most notably for EPCART. Knockout of EPCART was found to reduce migration and proliferation of the PC cells in vitro. The high expression of EPCART and two other TPCATs (TPCAT-3-174133 and TPCAT-18-31849) were also associated with the biochemical recurrence of PC in prostatectomy patients and were independent prognostic markers. Our findings suggest that the expression of numerous PC-associated lncRNAs is driven by PC-specific mechanisms and not by random cellular events that occur during cancer development. Furthermore, we report three prospective prognostic markers for the early detection of advanced PC and show EPCART to be a functionally relevant lncRNA in PC.

Moderate-to-strong expression of FGFR3 and TP53 alterations in a subpopulation of choroid plexus tumors.

Deregulation of fibroblast growth factor receptor (FGFR) signaling is tightly associated with numerous human malignancies, including cancer. Indeed, FGFR inhibitors are being tested as anti-tumor drugs in clinical trials. Among gliomas, FGFR3 fusions occur in IDH wild-type diffuse gliomas leading to high FGFR3 protein expression and both, FGFR3 and FGFR1, show elevated expression in aggressive ependymomas. The aim of this study was to uncover the expression of FGFR1 and FGFR3 proteins in choroid plexus tumors and to further characterize FGFR-related as well as other genetic alterations in FGFR3 expressing tumors. Expression levels of FGFR1 and FGFR3 were detected in 15 choroid plexus tumor tissues using immunohistochemistry of tissue microarrays and 6 samples were subjected to whole mount FGFR3 staining. Targeted sequencing was used for deeper molecular analysis of two FGFR3 positive cases. Moderate expression of FGFR1 or FGFR3 was evidenced in one third of the studied choroid plexus tumors. Targeted sequencing of a choroid plexus carcinoma and an atypical choroid plexus papilloma, both with moderate-to-strong FGFR3 expression, revealed lack of protein-altering mutations or fusions in FGFR1 or FGFR3, but TP53 was altered in both tumors. FGFR3 and FGFR1 proteins are expressed in a subpopulation of choroid plexus tumors. Further studies using larger cohorts of patients will allow identification of the clinicopathological implications of FGFR1 and FGFR3 expression in choroid plexus tumors.

Computational Characterization of Suppressive Immune Microenvironments in Glioblastoma.

The immunosuppressive microenvironment in glioblastoma (GBM) prevents an efficient antitumoral immune response and enables tumor formation and growth. Although an understanding of the nature of immunosuppression is still largely lacking, it is important for successful cancer treatment through immune system modulation. To gain insight into immunosuppression in GBM, we performed a computational analysis to model relative immune cell content and type of immune response in each GBM tumor sample from The Cancer Genome Atlas RNA-seq data set. We uncovered high variability in immune system-related responses and in the composition of the microenvironment across the cohort, suggesting immunologic diversity. Immune cell compositions were associated with typical alterations such as IDH mutation or inactivating NF1 mutation/deletion. Furthermore, our analysis identified three GBM subgroups presenting different adaptive immune responses: negative, humoral, and cellular-like. These subgroups were linked to transcriptional GBM subtypes and typical genetic alterations. All G-CIMP and IDH-mutated samples were in the negative group, which was also enriched by cases with focal amplification of CDK4 and MARCH9. IDH1-mutated samples showed lower expression and higher DNA methylation of MHC-I-type HLA genes. Overall, our analysis reveals heterogeneity in the immune microenvironment of GBM and identifies new markers for immunosuppression. Characterization of diverse immune responses will facilitate patient stratification and improve personalized immunotherapy in the future.Significance: This study utilizes a computational approach to characterize the immune environments in glioblastoma and shows that glioblastoma immune microenvironments can be classified into three major subgroups, which are linked to typical glioblastoma alterations such as IDH mutation, NF1 inactivation, and CDK4-MARCH9 locus amplification.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/19/5574/F1.large.jpg Cancer Res; 78(19); 5574-85. ©2018 AACR.

Feasibility of Prostate PAXgene Fixation for Molecular Research and Diagnostic Surgical Pathology: Comparison of Matched Fresh Frozen, FFPE, and PFPE Tissues.

Advances in prostate cancer biology and diagnostics are dependent upon high-fidelity integration of clinical, histomorphologic, and molecular phenotypic findings. In this study, we compared fresh frozen, formalin-fixed paraffin-embedded (FFPE), and PAXgene-fixed paraffin-embedded (PFPE) tissue preparation methods in radical prostatectomy prostate tissue from 36 patients and performed a preliminary test of feasibility of using PFPE tissue in routine prostate surgical pathology diagnostic assessment. In addition to comparing histology, immunohistochemistry, and general measures of DNA and RNA integrity in each fixation method, we performed functional tests of DNA and RNA quality, including targeted Miseq RNA and DNA sequencing, and implemented methods to relate DNA and RNA yield and quality to quantified DNA and RNA picogram nuclear content in each tissue volume studied. Our results suggest that it is feasible to use PFPE tissue for routine robot-assisted laparoscopic prostatectomy surgical pathology diagnostics and immunohistochemistry, with the benefit of significantly improvedDNA and RNA quality and RNA picogram yield per nucleus as compared with FFPE tissue. For fresh frozen, FFPE, and PFPE tissues, respectively, the average Genomic Quality Numbers were 7.9, 3.2, and 6.2, average RNA Quality Numbers were 8.7, 2.6, and 6.3, average DNA picogram yields per nucleus were 0.41, 0.69, and 0.78, and average RNA picogram yields per nucleus were 1.40, 0.94, and 2.24. These findings suggest that where DNA and/or RNA analysis of tissue is required, and when tissue size is small, PFPE may provide important advantages over FFPE. The results also suggest several interesting nuances including potential avenues to improve RNA quality in FFPE tissues and confirm recent suggestions that some DNA sequence artifacts associated with FFPE can be avoided.

Clinical association analysis of ependymomas and pilocytic astrocytomas reveals elevated FGFR3 and FGFR1 expression in aggressive ependymomas.

BACKGROUND: Fibroblast growth factor receptors (FGFRs) are well-known proto-oncogenes in several human malignancies and are currently therapeutically targeted in clinical trials. Among glioma subtypes, activating FGFR1 alterations have been observed in a subpopulation of pilocytic astrocytomas while FGFR3 fusions occur in IDH wild-type diffuse gliomas, resulting in high FGFR3 protein expression. The purpose of this study was to associate FGFR1 and FGFR3 protein levels with clinical features and genetic alterations in ependymoma and pilocytic astrocytoma. METHODS: FGFR1 and FGFR3 expression levels were detected in ependymoma and pilocytic astrocytoma tissues using immunohistochemistry. Selected cases were further analyzed using targeted sequencing. RESULTS: Expression of both FGFR1 and FGFR3 varied within all tumor types. In ependymomas, increased FGFR3 or FGFR1 expression was associated with high tumor grade, cerebral location, young patient age, and poor prognosis. Moderate-to-strong expression of FGFR1 and/or FGFR3 was observed in 76% of cerebral ependymomas. Cases with moderate-to-strong expression of both proteins had poor clinical prognosis. In pilocytic astrocytomas, moderate-to-strong FGFR3 expression was detected predominantly in non-pediatric patients. Targeted sequencing of 12 tumors found no protein-altering mutations or fusions in FGFR1 or FGFR3. CONCLUSIONS: Elevated FGFR3 and FGFR1 protein expression is common in aggressive ependymomas but likely not driven by genetic alterations. Further studies are warranted to evaluate whether ependymoma patients with high FGFR3 and/or FGFR1 expression could benefit from treatment with FGFR inhibitor based therapeutic approaches currently under evaluation in clinical trials.

Strong FGFR3 staining is a marker for FGFR3 fusions in diffuse gliomas.

BACKGROUND: Inhibitors of fibroblast growth factor receptors (FGFRs) have recently arisen as a promising treatment option for patients with FGFR alterations. Gene fusions involving FGFR3 and transforming acidic coiled-coil protein 3 (TACC3) have been detected in diffuse gliomas and other malignancies, and fusion-positive cases have responded well to FGFR inhibition. As high FGFR3 expression has been detected in fusion-positive tumors, we sought to determine the clinical significance of FGFR3 protein expression level as well as its potential for indicating FGFR3 fusions. METHODS: We performed FGFR3 immunohistochemistry on tissue microarrays containing 676 grades II-IV astrocytomas and 116 grades II-III oligodendroglial tumor specimens. Fifty-one cases were further analyzed using targeted sequencing. RESULTS: Moderate to strong FGFR3 staining was detected in gliomas of all grades, was more common in females, and was associated with poor survival in diffuse astrocytomas. Targeted sequencing identified FGFR3-TACC3 fusions and an FGFR3-CAMK2A fusion in 10 of 15 strongly stained cases, whereas no fusions were found in 36 negatively to moderately stained cases. Fusion-positive cases were predominantly female and negative for IDH and EGFR/PDGFRA/MET alterations. These and moderately stained cases show lower MIB-1 proliferation index than negatively to weakly stained cases. Furthermore, stronger FGFR3 expression was commonly observed in malignant tissue regions of lower cellularity in fusion-negative cases. Importantly, subregional negative FGFR3 staining was also observed in a few fusion-positive cases. CONCLUSIONS: Strong FGFR3 protein expression is indicative of FGFR3 fusions and may serve as a clinically applicable predictive marker for treatment regimens based on FGFR inhibitors.

Balance between noise and information flow maximizes set complexity of network dynamics.

Boolean networks have been used as a discrete model for several biological systems, including metabolic and genetic regulatory networks. Due to their simplicity they offer a firm foundation for generic studies of physical systems. In this work we show, using a measure of context-dependent information, set complexity, that prior to reaching an attractor, random Boolean networks pass through a transient state characterized by high complexity. We justify this finding with a use of another measure of complexity, namely, the statistical complexity. We show that the networks can be tuned to the regime of maximal complexity by adding a suitable amount of noise to the deterministic Boolean dynamics. In fact, we show that for networks with Poisson degree distributions, all networks ranging from subcritical to slightly supercritical can be tuned with noise to reach maximal set complexity in their dynamics. For networks with a fixed number of inputs this is true for near-to-critical networks. This increase in complexity is obtained at the expense of disruption in information flow. For a large ensemble of networks showing maximal complexity, there exists a balance between noise and contracting dynamics in the state space. In networks that are close to critical the intrinsic noise required for the tuning is smaller and thus also has the smallest effect in terms of the information processing in the system. Our results suggest that the maximization of complexity near to the state transition might be a more general phenomenon in physical systems, and that noise present in a system may in fact be useful in retaining the system in a state with high information content.

Information-theoretic analysis of the dynamics of an executable biological model.

To facilitate analysis and understanding of biological systems, large-scale data are often integrated into models using a variety of mathematical and computational approaches. Such models describe the dynamics of the biological system and can be used to study the changes in the state of the system over time. For many model classes, such as discrete or continuous dynamical systems, there exist appropriate frameworks and tools for analyzing system dynamics. However, the heterogeneous information that encodes and bridges molecular and cellular dynamics, inherent to fine-grained molecular simulation models, presents significant challenges to the study of system dynamics. In this paper, we present an algorithmic information theory based approach for the analysis and interpretation of the dynamics of such executable models of biological systems. We apply a normalized compression distance (NCD) analysis to the state representations of a model that simulates the immune decision making and immune cell behavior. We show that this analysis successfully captures the essential information in the dynamics of the system, which results from a variety of events including proliferation, differentiation, or perturbations such as gene knock-outs. We demonstrate that this approach can be used for the analysis of executable models, regardless of the modeling framework, and for making experimentally quantifiable predictions.

Information diversity in structure and dynamics of simulated neuronal networks.

Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neuronal network is studied using the normalized compression distance. To describe the structure, a scheme for generating distance-dependent networks with identical in-degree distribution but variable strength of dependence on distance is presented. The resulting network structure classes possess differing path length and clustering coefficient distributions. In parallel, comparable realistic neuronal networks are generated with NETMORPH simulator and similar analysis is done on them. To describe the dynamics, network spike trains are simulated using different network structures and their bursting behaviors are analyzed. For the simulation of the network activity the Izhikevich model of spiking neurons is used together with the Tsodyks model of dynamical synapses. We show that the structure of the simulated neuronal networks affects the spontaneous bursting activity when measured with bursting frequency and a set of intraburst measures: the more locally connected networks produce more and longer bursts than the more random networks. The information diversity of the structure of a network is greatest in the most locally connected networks, smallest in random networks, and somewhere in between in the networks between order and disorder. As for the dynamics, the most locally connected networks and some of the in-between networks produce the most complex intraburst spike trains. The same result also holds for sparser of the two considered network densities in the case of full spike trains.