Noncanonical effector functions of the T-memory-like T-PLL cell are shaped by cooperative TCL1A and TCR signaling.

T-cell prolymphocytic leukemia (T-PLL) is a poor-prognostic neoplasm. Differentiation stage and immune-effector functions of the underlying tumor cell are insufficiently characterized. Constitutive activation of the T-cell leukemia 1A (TCL1A) oncogene distinguishes the (pre)leukemic cell from regular postthymic T cells. We assessed activation-response patterns of the T-PLL lymphocyte and interrogated the modulatory impact by TCL1A. Immunophenotypic and gene expression profiles revealed a unique spectrum of memory-type differentiation of T-PLL with predominant central-memory stages and frequent noncanonical patterns. Virtually all T-PLL expressed a T-cell receptor (TCR) and/or CD28-coreceptor without overrepresentation of specific TCR clonotypes. The highly activated leukemic cells also revealed losses of negative-regulatory TCR coreceptors (eg, CTLA4). TCR stimulation of T-PLL cells evoked higher-than-normal cell-cycle transition and profiles of cytokine release that resembled those of normal memory T cells. More activated phenotypes and higher TCL1A correlated with inferior clinical outcomes. TCL1A was linked to the marked resistance of T-PLL to activation- and FAS-induced cell death. Enforced TCL1A enhanced phospho-activation of TCR kinases, second-messenger generation, and JAK/STAT or NFAT transcriptional responses. This reduced the input thresholds for IL-2 secretion in a sensitizer-like fashion. Mice of TCL1A-initiated protracted T-PLL development resembled such features. When equipped with epitope-defined TCRs or chimeric antigen receptors, these Lckpr-hTCL1Atg T cells gained a leukemogenic growth advantage in scenarios of receptor stimulation. Overall, we propose a model of T-PLL pathogenesis in which TCL1A enhances TCR signals and drives the accumulation of death-resistant memory-type cells that use amplified low-level stimulatory input, and whose loss of negative coregulators additionally maintains their activated state. Treatment rationales are provided by combined interception in TCR and survival signaling.

Secreted frizzled-related protein 2 (SFRP2) expression promotes lesion proliferation via canonical WNT signaling and indicates lesion borders in extraovarian endometriosis.

STUDY QUESTION: What is the role of SFRP2 in endometriosis? SUMMARY ANSWER: SFRP2 acts as a canonical WNT/CTNNB1 signaling agonist in endometriosis, regulating endometriosis lesion growth and indicating endometriosis lesion borders together with CTNNB1 (also known as beta catenin). WHAT IS KNOWN ALREADY: Endometriosis is a common, chronic disease that affects women of reproductive age, causing pain and infertility, and has significant economic impact on national health systems. Despite extensive research, the pathogenesis of endometriosis is poorly understood, and targeted medical treatments are lacking. WNT signaling is dysregulated in various human diseases, but its role in extraovarian endometriosis has not been fully elucidated. STUDY DESIGN, SIZE, DURATION: We evaluated the significance of WNT signaling, and especially secreted frizzled-related protein 2 (SFRP2), in extraovarian endometriosis, including peritoneal and deep lesions. The study design was based on a cohort of clinical samples collected by laparoscopy or curettage and questionnaire data from healthy controls and endometriosis patients. PARTICIPANTS/MATERIALS, SETTING, METHODS: Global gene expression analysis in human endometrium (n = 104) and endometriosis (n = 177) specimens from 47 healthy controls and 103 endometriosis patients was followed by bioinformatics and supportive qPCR analyses. Immunohistochemistry, Western blotting, primary cell culture and siRNA knockdown approaches were used to validate the findings. MAIN RESULTS AND THE ROLE OF CHANCE: Among the 220 WNT signaling and CTNNB1 target genes analysed, 184 genes showed differential expression in extraovarian endometriosis (P < 0.05) compared with endometrium tissue, including SFRP2 and CTNNB1. Menstrual cycle-dependent regulation of WNT genes observed in the endometrium was lost in endometriosis lesions, as shown by hierarchical clustering. Immunohistochemical analysis indicated that SFRP2 and CTNNB1 are novel endometriosis lesion border markers, complementing immunostaining for the known marker CD10 (also known as MME). SFRP2 and CTNNB1 localized similarly in both the epithelium and stroma of extraovarian endometriosis tissue, and interestingly, both also indicated an additional distant lesion border, suggesting that WNT signaling is altered in the endometriosis stroma beyond the primary border indicated by the known marker CD10. SFRP2 expression was positively associated with pain symptoms experienced by patients (P < 0.05), and functional loss of SFRP2 in extraovarian endometriosis primary cell cultures resulted in decreased cell proliferation (P < 0.05) associated with reduced CTNNB1 protein expression (P = 0.05). LIMITATIONS REASONS FOR CAUTION: SFRP2 and CTNNB1 improved extraovarian endometriosis lesion border detection in a relatively small cohort (n = 20), although larger studies with different endometriosis subtypes in variable cycle phases and under hormonal medication are required. WIDER IMPLICATIONS OF THE FINDINGS: The highly expressed SFRP2 and CTNNB1 improve endometriosis lesion border detection, which can have clinical implications for better visualization of endometriosis lesions over CD10. Furthermore, SFRP2 acts as a canonical WNT/CTNNB1 signaling agonist in endometriosis and positively regulates endometriosis lesion growth, suggesting that the WNT pathway may be an important therapeutic target for endometriosis. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the Academy of Finland and by Tekes: Finnish Funding Agency for Innovation. The authors have no conflict of interest to declare.

Discovery of novel drug sensitivities in T-PLL by high-throughput ex vivo drug testing and mutation profiling.

T-cell prolymphocytic leukemia (T-PLL) is a rare and aggressive neoplasm of mature T-cells with an urgent need for rationally designed therapies to address its notoriously chemo-refractory behavior. The median survival of T-PLL patients is <2 years and clinical trials are difficult to execute. Here we systematically explored the diversity of drug responses in T-PLL patient samples using an ex vivo drug sensitivity and resistance testing platform and correlated the findings with somatic mutations and gene expression profiles. Intriguingly, all T-PLL samples were sensitive to the cyclin-dependent kinase inhibitor SNS-032, which overcame stromal-cell-mediated protection and elicited robust p53-activation and apoptosis. Across all patients, the most effective classes of compounds were histone deacetylase, phosphoinositide-3 kinase/AKT/mammalian target of rapamycin, heat-shock protein 90 and BH3-family protein inhibitors as well as p53 activators, indicating previously unexplored, novel targeted approaches for treating T-PLL. Although Janus-activated kinase-signal transducer and activator of transcription factor (JAK-STAT) pathway mutations were common in T-PLL (71% of patients), JAK-STAT inhibitor responses were not directly linked to those or other T-PLL-specific lesions. Overall, we found that genetic markers do not readily translate into novel effective therapeutic vulnerabilities. In conclusion, novel classes of compounds with high efficacy in T-PLL were discovered with the comprehensive ex vivo drug screening platform warranting further studies of synergisms and clinical testing.

Enhanced sensitivity to glucocorticoids in cytarabine-resistant AML.

We sought to identify drugs that could counteract cytarabine resistance in acute myeloid leukemia (AML) by generating eight resistant variants from MOLM-13 and SHI-1 AML cell lines by long-term drug treatment. These cells were compared with 66 ex vivo chemorefractory samples from cytarabine-treated AML patients. The models and patient cells were subjected to genomic and transcriptomic profiling and high-throughput testing with 250 emerging and clinical oncology compounds. Genomic profiling uncovered deletion of the deoxycytidine kinase (DCK) gene in both MOLM-13- and SHI-1-derived cytarabine-resistant variants and in an AML patient sample. Cytarabine-resistant SHI-1 variants and a subset of chemorefractory AML patient samples showed increased sensitivity to glucocorticoids that are often used in treatment of lymphoid leukemia but not AML. Paired samples taken from AML patients before treatment and at relapse also showed acquisition of glucocorticoid sensitivity. Enhanced glucocorticoid sensitivity was only seen in AML patient samples that were negative for the FLT3 mutation (P=0.0006). Our study shows that development of cytarabine resistance is associated with increased sensitivity to glucocorticoids in a subset of AML, suggesting a new therapeutic strategy that should be explored in a clinical trial of chemorefractory AML patients carrying wild-type FLT3.

Cancer stem cell drugs target K-ras signaling in a stemness context.

Cancer stem cells (CSCs) are considered to be responsible for treatment relapse and have therefore become a major target in cancer research. Salinomycin is the most established CSC inhibitor. However, its primary mechanistic target is still unclear, impeding the discovery of compounds with similar anti-CSC activity. Here, we show that salinomycin very specifically interferes with the activity of K-ras4B, but not H-ras, by disrupting its nanoscale membrane organization. We found that caveolae negatively regulate the sensitivity to this drug. On the basis of this novel mechanistic insight, we defined a K-ras-associated and stem cell-derived gene expression signature that predicts the drug response of cancer cells to salinomycin. Consistent with therapy resistance of CSC, 8% of tumor samples in the TCGA-database displayed our signature and were associated with a significantly higher mortality. Using our K-ras-specific screening platform, we identified several new candidate CSC drugs. Two of these, ophiobolin A and conglobatin A, possessed a similar or higher potency than salinomycin. Finally, we established that the most potent compound, ophiobolin A, exerts its K-ras4B-specific activity through inactivation of calmodulin. Our data suggest that specific interference with the K-ras4B/calmodulin interaction selectively inhibits CSC.

Anticancer compound ABT-263 accelerates apoptosis in virus-infected cells and imbalances cytokine production and lowers survival rates of infected mice.

ABT-263 and its structural analogues ABT-199 and ABT-737 inhibit B-cell lymphoma 2 (Bcl-2), BCL2L1 long isoform (Bcl-xL) and BCL2L2 (Bcl-w) proteins and promote cancer cell death. Here, we show that at non-cytotoxic concentrations, these small molecules accelerate the deaths of non-cancerous cells infected with influenza A virus (IAV) or other viruses. In particular, we demonstrate that ABT-263 altered Bcl-xL interactions with Bcl-2 antagonist of cell death (Bad), Bcl-2-associated X protein (Bax), uveal autoantigen with coiled-coil domains and ankyrin repeats protein (UACA). ABT-263 thereby activated the caspase-9-mediated mitochondria-initiated apoptosis pathway, which, together with the IAV-initiated caspase-8-mediated apoptosis pathway, triggered the deaths of IAV-infected cells. Our results also indicate that Bcl-xL, Bcl-2 and Bcl-w interact with pattern recognition receptors (PRRs) that sense virus constituents to regulate cellular apoptosis. Importantly, premature killing of IAV-infected cells by ABT-263 attenuated the production of key pro-inflammatory and antiviral cytokines. The imbalance in cytokine production was also observed in ABT-263-treated IAV-infected mice, which resulted in an inability of the immune system to clear the virus and eventually lowered the survival rates of infected animals. Thus, the results suggest that the chemical inhibition of Bcl-xL, Bcl-2 and Bcl-w could potentially be hazardous for cancer patients with viral infections.

Transcutaneous carbon dioxide profile during sleep reveals metabolic risk factors in post-menopausal females.

The risks of metabolic syndrome and sleep-disordered breathing increase around the time of the menopause. We have previously shown that features of the nocturnal transcutaneous carbon dioxide (TcCO2) profile are associated with metabolic variables such as cholesterol, glycosylated haemoglobin A1C (GHbA1C) and blood pressure in patients with sleep apnoea. In the present study, we investigated whether these metabolic variables can be predicted using noninvasive TcCO2 measurements during sleep in generally healthy post-menopausal females. 22 post-menopausal females underwent an overnight polygraphic sleep study that involved the continuous monitoring of arterial oxygen saturation (S(a,O2)) and TcCO2. Body composition, GHbA1C, plasma cholesterol and blood pressure were measured prior to the sleep study. Nocturnal TcCO2 features were the most important predictors of lipoprotein cholesterols, triglycerides and blood pressure levels. A longer sleep period and higher TcCO2 levels were linked with lower GHbA1C, and fragmented sleep with lower high-density lipoprotein cholesterol. Neither nocturnal S(a,O2) indices nor the apnoea/hypopnoea index had a predictive power. The results suggest that nocturnal TcCO2 events revealed metabolic risk factors already present in healthy post-menopausal females.

Parameter estimation of a respiratory control model from noninvasive carbon dioxide measurements during sleep.

A new method for estimating the parameters of a human gas exchange model is presented. Sensitivity analysis is used both to inspect the relative importance of the model parameters and to speed up the par-ameter estimation process. Multistart optimization is used to compensate for the effects of partial and noisy measurements. The validity of the method is first investigated with a test problem for which par-ameter identifiability is shown. The method is then applied to the estimation of sleep-related changes in the respiratory control system from the end-tidal and transcutaneous carbon dioxide measurements on human subjects. The results show that it is possible to gain insight into the behaviour of the rather complex physiological system using only a few noninvasive measurements and tractable computations.

Model-based analysis of mechanisms responsible for sleep-induced carbon dioxide differences.

This work describes a comprehensive mathematical model of the human respiratory control system which incorporates the central mechanisms for predicting sleep-induced changes in chemical regulation of ventilation. The model integrates four individual compartments for gas storage and exchange, namely alveolar air, pulmonary blood, tissue capillary blood, body tissues, and gas transport between them. An essential mechanism in the carbon dioxide transport is its dissociation into bicarbonate and acid, where a buffering mechanism through hemoglobin is used to prevent harmfully low pH levels. In the current model, we assume high oxygen levels and consider intracellular hydrogen ion concentration as the principal respiratory control variable. The resulting system of delayed differential equations is solved numerically. With an appropriate choice of key parameters, such as velocity of blood flow and gain of a non-linear controller function, the model provides steady-state results consistent with our experimental observations measured in subjects across sleep onset. Dynamic predictions from the model give new insights into the behaviour of the system in subjects with different buffering capacities and suggest novel hypotheses for future experimental and clinical studies.

A human ImmunoChip cDNA microarray provides a comprehensive tool to study immune responses.

DNA microarray technology has developed rapidly in recent years and has become an essential tool, providing novel approaches to biomedical research. In this paper, we describe a self-designed ImmunoChip cDNA array for immunological research. With a comprehensive selection of genes of interest, we can focus on key signalling pathways and molecular mechanisms at relatively low cost compared to commercial platforms which are usually targeted at global screening of gene expression. To validate the efficiency of the ImmunoChip, we studied T helper cell polarization to functionally distinct subsets (Th1 and Th2). We also developed a tool for quality control of cDNA microarrays that assesses the technical quality of an ImmunoChip. The information produced with the quality control tool is shown to be valuable for extracting correct information from cDNA microarrays. Gene expression measurements with ImmunoChip are in agreement with the results obtained using oligonucleotide microarrays and with published quantitative RT-PCR data. The ImmunoChip provides reliable measurements and gives new insights into various aspects of human immune responses.

Geometrical distortions in two-dimensional gels: applicable correction methods.

Two-dimensional electrophoresis (2-DE) provides a rapid means for separating thousands of proteins from cell and tissue samples in one run. Although this powerful research tool has been enthusiastically applied in many fields of biomedical research, accurate analysis and interpretation of the data have provided many challenges. Several analysis steps are needed to convert the large amount of noisy data obtained with 2-DE into reliable and interpretable biological information. The goals of such analysis steps include accurate protein detection and quantification, as well as the identification of differentially expressed proteins between samples run on different gels. To achieve these goals, systematic errors such as geometric distortions between the gels must be corrected by using computer-assisted methods. A wide range of computer software has been developed, but no general consensus exists as standard for 2-DE data analysis protocol. The choice of analysis approach is an important element depending both on the data and on the goals of the experiment. Therefore, basic understanding of the algorithms behind the software is required for optimal results. This review highlights some of the common themes in 2-DE data analysis, including protein spot detection and geometric image warping using both spot- and pixel-based approaches. Several computational strategies are overviewed and their relative merits and potential pitfalls discussed. Finally, we offer our own personal view of future trends and developments in large-scale proteome research.

Electrophoretic signal comparison applied to mRNA differential display analysis.

Gene expression analysis by electrophoretic methods is currently limited by the labor-intensive visual evaluation of the electrophoretic signal profiles. For this purpose, we present a flexible approach to computer-assisted comparison of quantitative electrophoretic patterns between multiple expression signals. Gaussian curves are first fitted to the complex peak mixtures, and the resulting approximate signals are then aligned and compared on a peak-by-peak basis with respect to specific patterns defined by the investigator. The rationale of the method is to produce a compressed list of exceptional expression patterns quantified by a set of associated numeric features. A score value is attached to each pattern in such a way that large values identify the most potential findings to be focused on in visual analysis instead of the vast amount of original electrophoretic results. The validity of the method is demonstrated by analyzing a large set of electrophoretic data from mRNA differential display experiments monitoring changes in gene expression patterns in human colonic carcinoma. The automated identification of variously defined gene expression patterns agrees well with the visual evaluation of the same electropherograms. The general comparison approach may also be found useful with other gene expression profiling instruments.

Adjustment of the human respiratory system to increased upper airway resistance during sleep.

A cardiorespiratory model incorporating control of the human upper airway during sleep is described. Most previous models have not considered the possibility that the upper airway could be a limiting factor for gas exchange. Our model was developed to also predict certain pathophysiological phenomena in the cardiorespiratory system that characterize heavy snoring or sleep apnea. We started by adapting our collapsible upper airway model to include the impact of nasal passage and larynx, and extended the model with equations for gas exchange in the lungs. A feedback loop both to the respiratory pump and the upper airway dilator muscles was included. The model enabled successful breath-by-breath simulations of obstructive events of the upper airway. Although the model incorporates several physiologically relevant components of the system, the simulation results suggest that only few parameters suffice to predict the key adjustments that the cardiorespiratory system is known to make in patients with heavy snoring.

Automated detection of differently expressed fragments in mRNA differential display.

We present a novel method for the automated detection of fragments showing dissimilar expression in mRNA differential display. The analysis is based on aligning the numerical electrophoretic lane data in respect of a given distance function defined on a set of fragments, or signal peaks in general. We presume that significant dissimilarities between peaks result in extreme score values computed for aligned peak pairs. Whereas in sequence comparison, an overall sequence similarity score is conventionally used, the current method defines a special dissimilarity score for searching the peak pairs showing the largest relative differences between the lanes. The output of the analysis is a highly reduced list of peak pairs, along with a set of associated features extracted from the lanes. Only the peaks of this list need to be visually confirmed instead of the vast amount of peaks in the original electrophoretic results. The results obtained by the algorithm correlate well with results of visual evaluation of the same electropherograms. The current algorithm may be applied to the study of complex expression patterns in multiple lanes and, in general, to automated recognition of variously defined patterns of quantitative electrophoretic data.

Climacteric vasomotor symptoms do not predict nocturnal breathing abnormalities in postmenopausal women.

OBJECTIVE: To study the association of climacteric vasomotor symptoms and nocturnal breathing abnormalities in a sample of healthy postmenopausal women. METHODS: Out of 71 postmenopausal women who took part in a large sleep study, 65 women were included into the present study. Sleep was monitored with polysomnography and nocturnal breathing with a static-charge sensitive bed and a pulse oximeter. Climacteric vasomotor symptoms were scored daily for 14 days and levels of oestradiol and FSH were measured in the serum. RESULTS: Altogether 21 (32.3%) women had some degree of breathing abnormalities during the study night. The occurrence of clinically significant sleep apnoea was low (1.5%) and of moderate type (OP-2). In contrast, increased respiratory resistance pattern, typical for partial upper airway obstruction, was frequent (16.9%). Seventy-eight per cent of the women had arterial oxyhaemoglobin desaturation events, but only in 4.6% of the women these events occurred more than 5 times/h of time in bed. Older women had more simple periodic breathing (P-1) and lower mean arterial oxyhaemoglobin saturation (SaO(2)). Body mass index (BMI) correlated with the apnoea frequency (OP-2) and inversely with the mean SaO(2). The severity of climacteric vasomotor symptoms or serum oestradiol concentration did not correlate with nocturnal breathing abnormalities. CONCLUSIONS: Nocturnal breathing abnormalities, especially partial upper airway obstruction, are common in postmenopausal women, but climacteric vasomotor symptoms do not predict their occurrence or severity. Increasing age and high BMI are important determinants of nocturnal breathing abnormalities.

A model of a snorer's upper airway.

In snorers, the physiologic decrease of postural muscle tone during sleep results in increased collapsibility of the upper airway. Measurement of nasal pressure changes with prongs is increasingly used to monitor flow kinetics through a collapsing upper airway. This report presents a mathematical model to predict nasal flow profile from three critical components that control upper airway patency during sleep. The model includes the respiratory pump drive, the stiffness of the pharyngeal soft tissues, and the dynamic support of the muscles surrounding the upper airway. Depending on these three components, the proposed model is able to reproduce the characteristic changes in flow profile that are clinically observed in snorers and non-snorers during sleep.

Analysis of inspiratory flow shapes in patients with partial upper-airway obstruction during sleep.

STUDY OBJECTIVE: To study the spectrum of inspiratory flow signal shapes in patients with partial upper airway obstruction during sleep. DESIGN: We identified seven different inspiratory flow shapes and determined their frequencies in two groups of patients (10 postmenopausal women and 19 men after surgical treatment for sleep apnea) and in 9 control subjects. SETTING: Sleep research unit, Department of Physiology, University of Turku, Finland. MEASUREMENTS AND RESULTS: Nasal flow was recorded with nasal prongs. The shape analyses were performed with an automated attribute grammar recognizer. The inspiratory flow-shape distributions differed significantly between patients and control subjects. The flow shapes were also different between postmenopausal women and men after uvulopalatopharyngoplasty. CONCLUSIONS: The differences in the inspiratory flow-shape distributions between the control subjects and the two patient groups suggest that the upper airways behave differently in the three study groups. Automated inspiratory flow-shape analysis seems to be a promising tool to distinguish patient groups with different upper airway function to be treated with different treatment alternatives. The physiologic correlates of each flow-shape class remain to be elucidated.

Analysis of similarity of electrophoretic patterns in mRNA differential display.

We present a novel method of statistical analysis for the comparison of electrophoretic data. The method is based on the squared Euclidian distance of normalized signal data vectors of electrophoretic lanes. The differences in the electrophoretic patterns are evaluated by a statistical test based on Hubert's statistics which measures the significance of the signal grouping. We demonstrate the validity and applicability of the method in a large data set derived from automated fluorescent mRNA differential display analysis of the expression of acute-phase proteins during experimental Escherichia coli infection in mice. The current testing method is capable of finding theoretically similar natural groupings to be similar in a statistically significant way whereas theoretically dissimilar or random groupings can be recognized to be artifactual. We also show how the calculated pairwise signal distances can be utilized in methodological problem solving. These analytical methods can be applied to the study of other related problems of similarity analysis of electrophoretic patterns, and also provide useful tools for the development of automated recognition of differentially expressed mRNAs.