126 research outputs found

    Enriching for correct prediction of biological processes using a combination of diverse classifiers

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    <p>Abstract</p> <p>Background</p> <p>Machine learning models (classifiers) for classifying genes to biological processes each have their own unique characteristics in what genes can be classified and to what biological processes. No single learning model is qualitatively superior to any other model and overall precision for each model tends to be low. The classification results for each classifier can be complementary and synergistic suggesting the benefit of a combination of algorithms, but often the prediction probability outputs of various learning models are neither comparable nor compatible for combining. A means to compare outputs regardless of the model and data used and combine the results into an improved comprehensive model is needed.</p> <p>Results</p> <p>Gene expression patterns from NCI's panel of 60 cell lines were used to train a Random Forest, a Support Vector Machine and a Neural Network model, plus two over-sampled models for classifying genes to biological processes. Each model produced unique characteristics in the classification results. We introduce the Precision Index measure (PIN) from the maximum posterior probability that allows assessing, comparing and combining multiple classifiers. The class specific precision measure (PIC) is introduced and used to select a subset of predictions across all classes and all classifiers with high precision. We developed a single classifier that combines the PINs from these five models in prediction and found that the PIN Combined Classifier (PINCom) significantly increased the number of correctly predicted genes over any single classifier. The PINCom applied to test genes that were not used in training also showed substantial improvement over any single model.</p> <p>Conclusions</p> <p>This paper introduces novel and effective ways of assessing predictions by their precision and recall plus a method that combines several machine learning models and capitalizes on synergy and complementation in class selection, resulting in higher precision and recall. Different machine learning models yielded incongruent results each of which were successfully combined into one superior model using the PIN measure we developed. Validation of the boosted predictions for gene functions showed the genes to be accurately predicted.</p

    Impact of the frequency of online verifications on the patient set-up accuracy and set-up margins

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    <p>Abstract</p> <p>Purpose</p> <p>The purpose of the study was to evaluate the patient set-up error of different anatomical sites, to estimate the effect of different frequencies of online verifications on the patient set-up accuracy, and to calculate margins to accommodate for the patient set-up error (ICRU set-up margin, SM).</p> <p>Methods and materials</p> <p>Alignment data of 148 patients treated with inversed planned intensity modulated radiotherapy (IMRT) or three-dimensional conformal radiotherapy (3D-CRT) of the head and neck (n = 31), chest (n = 72), abdomen (n = 15), and pelvis (n = 30) were evaluated. The patient set-up accuracy was assessed using orthogonal megavoltage electronic portal images of 2328 fractions of 173 planning target volumes (PTV). In 25 patients, two PTVs were analyzed where the PTVs were located in different anatomical sites and treated in two different radiotherapy courses. The patient set-up error and the corresponding SM were retrospectively determined assuming no online verification, online verification once a week and online verification every other day.</p> <p>Results</p> <p>The SM could be effectively reduced with increasing frequency of online verifications. However, a significant frequency of relevant set-up errors remained even after online verification every other day. For example, residual set-up errors larger than 5 mm were observed on average in 18% to 27% of all fractions of patients treated in the chest, abdomen and pelvis, and in 10% of fractions of patients treated in the head and neck after online verification every other day.</p> <p>Conclusion</p> <p>In patients where high set-up accuracy is desired, daily online verification is highly recommended.</p

    Alternative splicing and the progesterone receptor in breast cancer

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    Progesterone receptor status is a marker for hormone responsiveness and disease prognosis in breast cancer. Progesterone receptor negative tumours have generally been shown to have a poorer prognosis than progesterone receptor positive tumours. The observed loss of progesterone receptor could be through a range of mechanisms, including the generation of alternatively spliced progesterone receptor variants that are not detectable by current screening methods. Many progesterone receptor mRNA variants have been described with deletions of various whole, multiple or partial exons that encode differing protein functional domains. These variants may alter the progestin responsiveness of a tissue and contribute to the abnormal growth associated with breast cancer. Absence of specific functional domains from these spliced variants may also make them undetectable or indistinguishable from full length progesterone receptor by conventional antibodies. A comprehensive investigation into the expression profile and activity of progesterone receptor spliced variants in breast cancer is required to advance our understanding of tumour hormone receptor status. This, in turn, may aid the development of new biomarkers of disease prognosis and improve adjuvant treatment decisions

    Hypoxia inducible factor 1α gene (HIF-1α) splice variants: potential prognostic biomarkers in breast cancer

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    <p>Abstract</p> <p>Background</p> <p>Hypoxia-inducible factor 1 (HIF-1) is a master transcriptional regulator of genes regulating oxygen homeostasis. The HIF-1 protein is composed of two HIF-1α and HIF-1β/aryl hydrocarbon receptor nuclear translocator (ARNT) subunits. The prognostic relevance of HIF-1α protein overexpression has been shown in breast cancer. The impact of HIF-1α alternative splice variant expression on breast cancer prognosis in terms of metastasis risk is not well known.</p> <p>Methods</p> <p>Using real-time quantitative reverse transcription PCR assays, we measured mRNA concentrations of total <it>HIF-1α </it>and 4 variants in breast tissue specimens in a series of 29 normal tissues or benign lesions (normal/benign) and 53 primary carcinomas. In breast cancers <it>HIF-1α </it>splice variant levels were compared to clinicopathological parameters including tumour microvessel density and metastasis-free survival.</p> <p>Results</p> <p><it>HIF-1α </it>isoforms containing a three base pairs TAG insertion between exon 1 and exon 2 (designated <it>HIF-1α</it><sup><it>TAG</it></sup>) and <it>HIF-1α</it><sup><it>736 </it></sup>mRNAs were found expressed at higher levels in oestrogen receptor (OR)-negative carcinomas compared to normal/benign tissues (<it>P </it>= 0.009 and <it>P </it>= 0.004 respectively). In breast carcinoma specimens, lymph node status was significantly associated with <it>HIF-1α</it><sup><it>TAG </it></sup>mRNA levels (<it>P </it>= 0.037). Significant statistical association was found between tumour grade and <it>HIF-1α</it><sup><it>TAG </it></sup>(<it>P </it>= 0.048), and total <it>HIF-1α </it>(<it>P </it>= 0.048) mRNA levels. <it>HIF-1α</it><sup><it>TAG </it></sup>mRNA levels were also inversely correlated with both oestrogen and progesterone receptor status (<it>P </it>= 0.005 and <it>P </it>= 0.033 respectively). Univariate analysis showed that high <it>HIF-1α</it><sup><it>TAG </it></sup>mRNA levels correlated with shortened metastasis free survival (<it>P </it>= 0.01).</p> <p>Conclusions</p> <p>Our results show for the first time that mRNA expression of a <it>HIF-1α</it><sup><it>TAG </it></sup>splice variant reflects a stage of breast cancer progression and is associated with a worse prognosis.</p> <p>See commentary: <url>http://www.biomedcentral.com/1741-7015/8/45</url></p

    Detecting and correcting partial errors: Evidence for efficient control without conscious access

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    Appropriate reactions to erroneous actions are essential to keeping behavior adaptive. Erring, however, is not an all-or-none process: electromyographic (EMG) recordings of the responding muscles have revealed that covert incorrect response activations (termed "partial errors") occur on a proportion of overtly correct trials. The occurrence of such "partial errors" shows that incorrect response activations could be corrected online, before turning into overt errors. In the present study, we showed that, unlike overt errors, such "partial errors" are poorly consciously detected by participants, who could report only one third of their partial errors. Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected). These two parameters provided independent information. The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection. The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed

    Differential gene expression between wild-type and Gulo-deficient mice supplied with vitamin C

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    The aim of this study was to test the hypothesis that hepatic vitamin C (VC) levels in VC deficient mice rescued with high doses of VC supplements still do not reach the optimal levels present in wild-type mice. For this, we used a mouse scurvy model (sfx) in which the L-gulonolactone oxidase gene (Gulo) is deleted. Six age- (6 weeks old) and gender- (female) matched wild-type (WT) and sfx mice (rescued by administering 500 mg of VC/L) were used as the control (WT) and treatment (MT) groups (n = 3 for each group), respectively. Total hepatic RNA was used in triplicate microarray assays for each group. EDGE software was used to identify differentially expressed genes and transcriptomic analysis was used to assess the potential genetic regulation of Gulo gene expression. Hepatic VC concentrations in MT mice were significantly lower than in WT mice, even though there were no morphological differences between the two groups. In MT mice, 269 differentially expressed transcripts were detected (≥ twice the difference between MT and WT mice), including 107 up-regulated and 162 down-regulated genes. These differentially expressed genes included stress-related and exclusively/predominantly hepatocyte genes. Transcriptomic analysis identified a major locus on chromosome 18 that regulates Gulo expression. Since three relevant oxidative genes are located within the critical region of this locus we suspect that they are involved in the down-regulation of oxidative activity in sfx mice

    Cranial Growth and Variation in Edmontosaurs (Dinosauria: Hadrosauridae): Implications for Latest Cretaceous Megaherbivore Diversity in North America

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    The well-sampled Late Cretaceous fossil record of North America remains the only high-resolution dataset for evaluating patterns of dinosaur diversity leading up to the terminal Cretaceous extinction event. Hadrosaurine hadrosaurids (Dinosauria: Ornithopoda) closely related to Edmontosaurus are among the most common megaherbivores in latest Campanian and Maastrichtian deposits of western North America. However, interpretations of edmontosaur species richness and biostratigraphy have been in constant flux for almost three decades, although the clade is generally thought to have undergone a radiation in the late Maastrichtian. We address the issue of edmontosaur diversity for the first time using rigorous morphometric analyses of virtually all known complete edmontosaur skulls. Results suggest only two valid species, Edmontosaurus regalis from the late Campanian, and E. annectens from the late Maastrichtian, with previously named taxa, including the controversial Anatotitan copei, erected on hypothesized transitional morphologies associated with ontogenetic size increase and allometric growth. A revision of North American hadrosaurid taxa suggests a decrease in both hadrosaurid diversity and disparity from the early to late Maastrichtian, a pattern likely also present in ceratopsid dinosaurs. A decline in the disparity of dominant megaherbivores in the latest Maastrichtian interval supports the hypothesis that dinosaur diversity decreased immediately preceding the end Cretaceous extinction event

    A prognostic index for operable, node-negative breast cancer

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    Clinical data and samples from patients diagnosed, more than 10 years previously, with operable node-negative breast cancer (participants in the Scottish Adjuvant Tamoxifen trial), were revisited, Cases with two distinct categories of outcome were selected; more than 10 years disease-free survival ('good outcome') or distant relapse within 6 years of diagnosis ('poor outcome'). An initial set of cases was analysed for a range of putative prognostic markers and a prognostic index, distinguishing the two outcome categories, was calculated. This index was then validated by testing its predictive power on a second, independent set of cases. A combination of histological grade plus immunochemical staining for BCL-2, p27 and Cyclin D 1, generated a useful prognostic index for tamoxifen-treated patients but not for those treated by surgery alone, The value of the index was confirmed in a second set of tamoxifen-treated, early stage breast cancers. Over-all, it correctly predicted good and poor outcome in 79 and 74% of cases, respectively (odds ratio 11.0). Other markers assessed added little to prediction of outcome. In the case of molecular assays, sensitivity and reliability were compromised by the age of the tissue specimens and the variability of fixation protocols. In selecting patients for adjuvant systemic chemotherapy, the proposed index improves considerably on current international guidelines and matches the performance reported for 'gene-expression signature' analysis. (C) 2004 Cancer Research UK.</p

    Fox-1 family of RNA-binding proteins

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    The Fox-1 family of RNA-binding proteins are evolutionarily conserved regulators of tissue-specific alternative splicing in metazoans. The Fox-1 family specifically recognizes the (U)GCAUG stretch in regulated exons or in flanking introns, and either promotes or represses target exons. Recent unbiased bioinformatics analyses of alternatively spliced exons and comparison of various vertebrate genomes identified the (U)GCAUG stretch as a highly conserved and widely distributed element enriched in intronic regions surrounding exons with altered inclusion in muscle, heart, and brain, consistent with specific expression of Fox-1 and Fox-2 in these tissues. Global identification of Fox-2 target RNAs in living cells revealed that many of the Fox-2 target genes themselves encode splicing regulators. Further systematic elucidation of target genes of the Fox-1 family and other splicing regulators in various tissues will lead to a comprehensive understanding of splicing regulatory networks

    Identifying Alternative Hyper-Splicing Signatures in MG-Thymoma by Exon Arrays

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    BACKGROUND: The vast majority of human genes (>70%) are alternatively spliced. Although alternative pre-mRNA processing is modified in multiple tumors, alternative hyper-splicing signatures specific to particular tumor types are still lacking. Here, we report the use of Affymetrix Human Exon Arrays to spot hyper-splicing events characteristic of myasthenia gravis (MG)-thymoma, thymic tumors which develop in patients with MG and discriminate them from colon cancer changes. METHODOLOGY/PRINCIPAL FINDINGS: We combined GO term to parent threshold-based and threshold-independent ad-hoc functional statistics with in-depth analysis of key modified transcripts to highlight various exon-specific changes. These denote alternative splicing in MG-thymoma tumors compared to healthy human thymus and to in-house and Affymetrix datasets from colon cancer and healthy tissues. By using both global and specific, term-to-parent Gene Ontology (GO) statistical comparisons, our functional integrative ad-hoc method allowed the detection of disease-relevant splicing events. CONCLUSIONS/SIGNIFICANCE: Hyper-spliced transcripts spanned several categories, including the tumorogenic ERBB4 tyrosine kinase receptor and the connective tissue growth factor CTGF, as well as the immune function-related histocompatibility gene HLA-DRB1 and interleukin (IL)19, two muscle-specific collagens and one myosin heavy chain gene; intriguingly, a putative new exon was discovered in the MG-involved acetylcholinesterase ACHE gene. Corresponding changes in spliceosome composition were indicated by co-decreases in the splicing factors ASF/SF(2) and SC35. Parallel tumor-associated changes occurred in colon cancer as well, but the majority of the apparent hyper-splicing events were particular to MG-thymoma and could be validated by Fluorescent In-Situ Hybridization (FISH), Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and mass spectrometry (MS) followed by peptide sequencing. Our findings demonstrate a particular alternative hyper-splicing signature for transcripts over-expressed in MG-thymoma, supporting the hypothesis that alternative hyper-splicing contributes to shaping the biological functions of these and other specialized tumors and opening new venues for the development of diagnosis and treatment approaches
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