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Background. Obesity is a major health problem in both developed and emerging countries. Obesity is a complex disease whose etiology involves genetic factors in strong interplay with environmental determinants and lifestyle. The discovery of genetic factors and biological pathways underlying human obesity is hampered by the difficulty in controlling the genetic background of human cohorts. Animal models are then necessary to further dissect the genetics of obesity. Pig has emerged as one of the most attractive models, because of the similarity with humans in the mechanisms regulating the fat deposition. Results. We collected the genes related to obesity in humans and to fat deposition traits in pig. We localized them on both human and pig genomes, building a map useful to interpret comparative studies on obesity. We characterized the collected genes structurally and functionally with BAR+ and mapped them on KEGG pathways and on STRING protein interaction network. Conclusions. The collected set consists of 361 obesity related genes in human and pig genomes. All genes were mapped on the human genome, and 54 could not be localized on the pig genome (release 2012). Only for 3 human genes there is no counterpart in pig, confirming that this animal is a good model for human obesity studies. Obesity related genes are mostly involved in regulation and signaling processes/pathways and relevant connection emerges between obesity-related genes and diseases such as cancer and infectious diseases.

A human glioblastoma multiforme cell line (U87) and its derived-spheroids were irradiated either using a conventional irradiation (CIR) or a CK-like irradiation (IIR) in which the 8Gy was delivered intermittently over a period of 40 minutes. The ability of glioma cells to migrate into a matrigel matrix was evaluated on days 1-8 from irradiation. Irradiation with CK-driven IIR significantly increased the invasion potential of U87 cells in a matrigel-based assay. In contrast to CIR, IIR was associated with increased levels of TGF-B at four days (Real time PCR), β1-integrin at 4-5 days (real-time PCR and western blot) and no elevation in phosphorylated AKT at days 4 and 5 (western blot). Our data suggests that glioma cell invasion as well as elevations of TGF-B and β1-integrin are associated with IIR and not CIR.

The transition from food collection to food production (FP) modified the nature of selective pressures, and several studies illustrate that genetic adaptation to new lifestyle has occurred in humans since the agricultural revolution. Here we test the hypothesis that high levels of genetic variation at CYP2D6, a locus coding for a detoxifying enzyme of the cytochrome P450 complex, reflect this change.

Aims and background Technological advances in treatment planning and execution are providing new potential opportunities in the treatment of recurrent prostate cancer. This study was conducted to evaluate the feasibility and safety of reirradiation with image-guided radiosurgery using CyberKnife, a robotic arm-driven compact linear accelerator, for intraprostatic recurrence after external beam radiotherapy (EBRT).Methods Between September 2007 and May 2008, 6 patients diagnosed with locally recurrent prostate cancer after EBRT were treated using the CyberKnife system. The total reirradiation dose was 30 Gy in five fractions. Prior to radiosurgery four patients were treated with androgen-deprivation therapy. Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer criteria and the Houston-Phoenix definition (PSA nadir + 2 ng/mL) were used for toxicity and biochemical failure evaluation, respectively.Results After a median follow-up of 11.2 months (range, 9.6–18.6 months), all patients are alive with no evidence of severe urinary or rectal acute morbidity. Local control cannot be exactly determined due to the short follow-up and the bias of the use of androgen ablation. Four patients had biochemical failure, three of them with clinical failure evidence (lymph node, bone and lung metastasis, respectively): none of these patients had clinical evidence of tumor persistence in the prostate.Conclusions Salvage radiosurgery with CyberKnife after irradiation is feasible with low urinary and rectal morbidity. A longer follow-up and a larger number of patients are necessary to evaluate its effectiveness and optimal patient selection criteria.

Motivation:The prediction of protein stability change upon mutations is key to understanding protein folding and misfolding. At present, methods are available to predict stability changes only when the atomic structure of the protein is available. Methods addressing the same task starting from the protein sequence are, however, necessary in order to complete genome annotation, especially in relation to single nucleotide polymorphisms (SNPs) and related diseases.Results:We develop a method based on support vector machines that, starting from the protein sequence, predicts the sign and the value of free energy stability change upon single point mutation. We show that the accuracy of our predictor is as high as 77% in the specific task of predicting the ΔΔGsign related to the corresponding protein stability. When predicting the ΔΔGvalues, a satisfactory correlation agreement with the experimental data is also found. As a final blind benchmark, the predictor is applied to proteins with a set of disease-related SNPs, for which thermodynamic data are also known. We found that our predictions corroborate the view that disease-related mutations correspond to a decrease in protein stability.Availability:http://gpcr2.biocomp.unibo.it/cgi/predictors/I-Mutant2.0/I-Mutant2.0.cgiContact:casadio@alma.unibo.it

New methods, essentially based on hidden Markov models (HMM) and neural networks (NN), can predict the topography of both β-barrel and all-α membrane proteins with high accuracy and a low rate of false positives and false negatives. These methods have been integrated in a suite of programs to filter proteomes of Gram-negative bacteria, searching for new membrane proteins. Copyright © 2003 John Wiley & Sons, Ltd.

Motivation: All-alpha membrane proteins constitute a functionally relevant subset of the whole proteome. Their content ranges from about 10 to 30% of the cell proteins, based on sequence comparison and specific predictive methods. Due to the paucity of membrane proteins solved with atomic resolution, the training/testing sets of predictive methods for protein topography and topology routinely include very few well-solved structures mixed with a hundred proteins known with low resolution. Moreover, available predictors fail in predicting recently crystallised membrane proteins (Chen et al., 2002). Presently the number of well-solved membrane proteins comprises some 59 chains of low sequence homology. It is therefore possible to train/test predictors only with the set of proteins known with atomic resolution and evaluate more thoroughly the performance of different methods.Results: We implement a cascade-neural network (NN), two different hidden Markov models (HMM), and their ensemble (ENSEMBLE) as a new method. We train and test in cross validation the three methods and ENSEMBLE on the 59 well resolved membrane proteins. ENSEMBLE scores with a per-protein accuracy of 90% for topography and 71% for topology, outperforming the best single method of 7 and 5 percentage points, respectively. When tested on a low resolution set of 151 proteins, with no homology with the 59 proteins, the per-protein accuracy of ENSEMBLE is 76% for topography and 68% for topology. Our results also indicate that the performance of ENSEMBLE is higher than that of the best predictors presently available on the Web.Contact: gigi@biocomp.unibo.it; http://www.biocomp.unibo.it

Motivation: Membrane proteins are an abundant and functionally relevant subset of proteins that putatively include from about 15 up to 30% of the proteome of organisms fully sequenced. These estimates are mainly computed on the basis of sequence comparison and membrane protein prediction. It is therefore urgent to develop methods capable of selecting membrane proteins especially in the case of outer membrane proteins, barely taken into consideration when proteome wide analysis is performed. This will also help protein annotation when no homologous sequence is found in the database. Outer membrane proteins solved so far at atomic resolution interact with the external membrane of bacteria with a characteristic β barrel structure comprising different even numbers of β strands (β barrel membrane proteins). In this they differ from the membrane proteins of the cytoplasmic membrane endowed with alpha helix bundles (all alpha membrane proteins) and need specialised predictors.
Results: We develop a HMM model, which can predict the topology of β barrel membrane proteins using, as input, evolutionary information. The model is cyclic with 6 types of states: two for the β strand transmembrane core, one for the β strand cap on either side of the membrane, one for the inner loop, one for the outer loop and one for the globular domain state in the middle of each loop. The development of a specific input for HMM based on multiple sequence alignment is novel. The accuracy per residue of the model is 83% when a jack knife procedure is adopted. With a model optimisation method using a dynamic programming algorithm seven topological models out of the twelve proteins included in the testing set are also correctly predicted. When used as a discriminator, the model is rather selective. At a fixed probability value, it retains 84% of a non-redundant set comprising 145 sequences of well-annotated outer membrane proteins. Concomitantly, it correctly rejects 90% of a set of globular proteins including about 1200 chains with low sequence identity (<30%) and 90% of a set of all alpha membrane proteins, including 188 chains.
Availability:The program will be available on request from the authors.
Contact: gigi@lipid.biocomp.unibo.it http://www.biocomp.unibo.it
Keywords: β barrel membrane proteins; HMM; genome analysis; protein structure prediction; outer membrane protein topology.

Knowing the coordination number and relative solvent accessibility of all the residues in a protein is crucial for deriving constraints useful in modeling protein folding and protein structure and in scoring remote homology searches. We develop ensembles of bidirectional recurrent neural network architectures to improve the state of the art in both contact and accessibility prediction, leveraging a large corpus of curated data together with evolutionary information. The ensembles are used to discriminate between two different states of residue contacts or relative solvent accessibility, higher or lower than a threshold determined by the average value of the residue distribution or the accessibility cutoff. For coordination numbers, the ensemble achieves performances ranging within 70.6–73.9% depending on the radius adopted to discriminate contacts (6Å–12Å). These performances represent gains of 16–20% over the baseline statistical predictor, always assigning an amino acid to the largest class, and are 4–7% better than any previous method. A combination of different radius predictors further improves performance. For accessibility thresholds in the relevant 15–30% range, the ensemble consistently achieves a performance above 77%, which is 10–16% above the baseline prediction and better than other existing predictors, by up to several percentage points. For both problems, we quantify the improvement due to evolutionary information in the form of PSI‐BLAST‐generated profiles over BLAST profiles. The prediction programs are implemented in the form of two web servers, CONpro and ACCpro, available at . Proteins 2002;47:142–153. © 2002 Wiley‐Liss, Inc.

Membrane proteins are an abundant and functionally relevant subset of proteins that putatively include from about 15 up to 30% of the proteome of organisms fully sequenced. These estimates are mainly computed on the basis of sequence comparison and membrane protein prediction. It is therefore urgent to develop methods capable of selecting membrane proteins especially in the case of outer membrane proteins, barely taken into consideration when proteome wide analysis is performed. This will also help protein annotation when no homologous sequence is found in the database. Outer membrane proteins solved so far at atomic resolution interact with the external membrane of bacteria with a characteristic beta barrel structure comprising different even numbers of beta strands (beta barrel membrane proteins). In this they differ from the membrane proteins of the cytoplasmic membrane endowed with alpha helix bundles (all alpha membrane proteins) and need specialised predictors.

Contact maps of proteins are predicted with neural network-based methods, using as input codings of increasing complexity including evolutionary information, sequence conservation, correlated mutations and predicted secondary structures. Neural networks are trained on a data set comprising the contact maps of 173 non-homologous proteins as computed from their well resolved three-dimensional structures. Proteins are selected from the Protein Data Bank database provided that they align with at least 15 similar sequences in the corresponding families. The predictors are trained to learn the association rules between the covalent structure of each protein and its contact map with a standard back propagation algorithm and tested on the same protein set with a cross-validation procedure. Our results indicate that the method can assign protein contacts with an average accuracy of 0.21 and with an improvement over a random predictor of a factor >6, which is higher than that previously obtained with methods only based either on neural networks or on correlated mutations. Furthermore, filtering the network outputs with a procedure based on the residue coordination numbers, the accuracy of predictions increases up to 0.25 for all the proteins, with an 8-fold deviation from a random predictor. These scores are the highest reported so far for predicting protein contact maps.

A major problem in protein structure prediction is the correct location of disulfide bridges in cysteine-rich proteins. In protein-folding prediction, the location of disulfide bridges can strongly reduce the search in the conformational space. Therefore the correct prediction of the disulfide connectivity starting from the protein residue sequence may also help in predicting its 3D structure.

Knowing the number of residue contacts in a protein is crucial for deriving constraints useful in modeling protein folding, protein structure, and/or scoring remote homology searches. Here we use an ensemble of bi-directional recurrent neural network architectures and evolutionary information to improve the state-of-the-art in contact prediction using a large corpus of curated data. The ensemble is used to discriminate between two different states of residue contacts, characterized by a contact number higher or lower than the average value of the residue distribution. The ensemble achieves performances ranging from 70.1% to 73.1% depending on the radius adopted to discriminate contacts (6Ato 12A). These performances represent gains of 15% to 20% over the base line statistical predictors always assigning an aminoacid to the most numerous state, 3% to 7% better than any previous method. Combination of different radius predictors further improves the performance.
Server: http://promoter.ics.uci.edu/BRNN-PRED/
Contact: pfbaldi@ics.uci.edu

This article presents recent progress in predicting inter‐residue contacts of proteins with a neural network‐based method. Improvement over the results obtained at the previous CASP3 competition is attained by using as input to the network a complex code, which includes evolutionary information, sequence conservation, correlated mutations, and predicted secondary structures. The predictor was trained and cross‐validated on a data set comprising the contact maps of 173 non‐homologous proteins as computed from their well‐resolved three‐dimensional structures. The method could assign protein contacts with an average accuracy of 0.21 and with an improvement over a random predictor of a factor greater than 6, which is higher than that previously obtained with methods only based either on neural networks or on correlated mutations. Although far from being ideal, these scores are the highest reported so far for predicting protein contact maps. On 29 targets automatically predicted by the server (CORNET) the average accuracy is 0.14. The predictor is poorly performing on all‐α proteins, not represented in the training set. On all‐β and mixed proteins (22 targets) the average accuracy is 0.16. This set comprises proteins of different complexity and different chain length, suggesting that the predictor is capable of generalization over a broad number of features. Proteins 2001;Suppl 5:157–162. © 2002 Wiley‐Liss, Inc.

The most stringent test for predictive methods of protein secondary structure is whether identical short sequences that are known to be present with different conformations in different proteins known at atomic resolution can be correctly discriminated. In this study, we show that the prediction efficiency of this type of segments in unrelated proteins reaches an average accuracy per residue ranging from about 72 to 75% (depending on the alignment method used to generate the input sequence profile) only when methods of the third generation are used. A comparison of different methods based on segment statistics (2nd generation methods) and/or including also evolutionary information (3rd generation methods) indicate that the discrimination of the different conformations of identical segments is dependent on the method used for the prediction. Accuracy is similar when methods similarly performing on the secondary structure prediction are tested. When evolutionary information is taken into account as compared to single sequence input, the number of correctly discriminated pairs is increased twofold. The results also highlight the predictive capability of neural networks for identical segments whose conformation differs in different proteins. Proteins 2000;41:535–544. © 2000 Wiley‐Liss, Inc.

A neural network‐based predictor is trained to distinguish the bonding states of cysteine in proteins starting from the residue chain. Training is performed by using 2,452 cysteine‐containing segments extracted from 641 nonhomologous proteins of well‐resolved three‐dimensional structure. After a cross‐validation procedure, efficiency of the prediction scores were as high as 72% when the predictor is trained by using protein single sequences. The addition of evolutionary information in the form of multiple sequence alignment and a jury of neural networks increases the prediction efficiency up to 81%. Assessment of the goodness of the prediction with a reliability index indicates that more than 60% of the predictions have an accuracy level greater than 90%. A comparison with a statistical method previously described and tested on the same database shows that the neural network‐based predictor is performing with the highest efficiency. Proteins 1999;36:340–346. © 1999 Wiley‐Liss, Inc.

The clinical-radiologic-cytologic triplet was used for diagnostic evaluation in 1708 women over 30 years old with a breast lump. All the lumps were subjected to surgery except for 258 cases in which clinical resolution took place within 1-2 months. Seven-hundred and ninety-three out of 1450 nodules removed were cancers. Sensitivity of the clinical, mammographic and cytologic examinations was 82%, 73% and 68%, respectively. It increased to 95% when they were as sociated. Specificity was 63%, 80% and 97%, respectively. The predictive value of positive results of the triple test was 100%. No patient with malignant cytology was subsequently shown to have benign disease. The systematic use of the triple test in solid breast lumps for the early detection of cancer is recommended as a routine procedure. However, participation of experienced radiologists and pathologists as well as physicians skilled in fine needle puncture is required.

Circulating levels and cyst fluid concentrations of human chorionic gonadotropin, progesterone and testosterone were measured in 30 premenopausal women with gross cystic breast disease. Specific radioimmunoassay procedures were used. Amounts of human chorionic gonadotropin exceeding 5.0 mIU/ml were found in cyst fluid of many patients, but not in serum. Progesterone and testosterone concentrations in breast cyst fluid were significantly higher than in serum (p < 0.01 and p < 0.001, respectively).

There are limited data in the literature concerning chemotherapy trials for the treatment of anaplastic astrocytomas. Forty-one anaplastic astrocytoma patients, operated on during the period 1988 to 1993 at the Neurological Institute of Milan, received 4-5 cycles of chemotherapy (BCNU + cisplatin), subsequently radiotherapy (median dose 56.5 Gy), and finally a second-line chemotherapy protocol at recurrence (procarbazine, vincristine, lomustine). The aim of the study was to evaluate the effectiveness of the planned protocol, considering the time to tumor progression and the survival time. The group of anaplastic astrocytoma patients was compared with a homogeneous group of 39 anaplastic astrocytoma patients treated only with radiotherapy after surgery. The median time to tumor progression of patients on the protocol was 24.5 months. The median survival time for anaplastic astrocytoma patients treated with our scheduled protocol or only with radiotherapy was 38.8 and 21 months, respectively. However, our data need to be confirmed by large randomized clinical studies.

Malignant brain tumors (primary and metastatic) are apparently resistant to most therapeutic efforts. Several randomized trials have provided evidence supporting the efficacy of radiation therapy. Attempts at improving the results of external beam radiotherapy include altered fractionation, radiation sensitizers and concomitant chemotherapy. In low-grade gliomas, all clinical studies with radiotherapy have employed conventional dose fractionation regimens. In high-grade gliomas, hypofractionation schedules represent effective palliative regimens in poor prognosis subsets of patients; short-term survival in these patients has not allowed to evaluate late toxicity. In tumors arising within the central nervous system, hyperfractionated irradiation exploits the differences in repair capacity between tumour and late responding normal tissues. It may allow for higher total dose and may result in increased tumor cell kill. Accelerated radiotherapy may reduce the repopulation of tumor cells between fractions. It may potentially improve tumor control for a given dose level, provided that there is no increase in late normal tissue injury. In supratentorial malignant gliomas, superiority of accelerated hyperfractionated over conventionally fractionated schedules was observed in a randomized trial; however, the gain in survival was less than 6 months. At present no other randomized trial supports the preferential choice for altered fractionation irradiation. Also in pediatric brainstem tumors there are no data to confirm the routine use of hyperfractionated irradiation, and significant late sequelae have been reported in the few long-term survivors. Shorter treatment courses with accelerated hyperfractionated radiotherapy may represent a useful alternative to conventional irradiation for the palliation of brain metastases. Different considerations have been proposed to explain this gap between theory and clinical data. Patients included in dose/effect studies are not stratified by prognostic factors and other treatment-related parameters. This observation precludes any definite conclusion about the relative role of conventional and of altered fractionation. New approaches are currently in progress. More prolonged radiation treatments, up to higher total doses, could delay time to tumor progression and improve survival in good prognosis subsets of patients; altered fractionation may be an effective therapeutic tool to achieve this goal.

Sixty-five postmenopausal patients with metastatic or surgically unresectable primary breast cancer, all estrogen receptor (ER) positive, were treated with tamoxifen 20–40 mg a day. Overall objective response rate was 58%, with a median duration time of 13 months. The correlation between response rate and ER levels appears positive, although not statistically significant. The analysis of the data was also performed in the subgroups « locally advanced tumors » and « recurrences and metastases ».

We measured the lateral diffusion of different coenzyme Q homologues and analogues in model lipid vesicles using the fluorescence collisional quenching technique with pyrene derivatives and found diffusion coefficients in the range of 10−6cm2/s. Theoretical diffusion coefficients for these highly hydrophobic components were calculated according to the free volume theory. An important parameter in the free volume theory is the relative dimension between diffusant and solvent: a molecular dynamics computer simulation of the coenzymes yielded their most probable geometries and volumes and revealed surprisingly similar sizes of the short and long homologues, due to a folded structure of the isoprenoid chain in the latter, with a length for coenzyme Q10of 21 Å. Using this information we were able to calculate diffusion coefficients in the range of 10−6cm2/s, in good agreement with those found experimentally.

Of about 8500 women with a minimum age of 30 years who had a breast examination at our Ouptatient Clinic from April 1982 to March 1983, we found in 286 cases a clinically evident carcinoma, and in 534 cases an apparently benign or suspect solid lump. All 534 of these cases were subjected to the triplet clinical, mammographic and cytologic diagnostic investigation by needle aspiration within 1 to 4 days. The clinical judgment was based on a method of scoring of the characters of 9 physical features (Clinical Diagnostic Index) in use at our Institute. The results of the examinations were grouped into 5 categories: 1) certain benignancy or negativity of the examination; 2) probable benignancy (excluding the cytologic examination); 3) probable malignancy; 4) certain malignancy; 5) nonevaluability of the examination (excluding the clinical examination). Except for 80 cases with collectively negative examinations which were clearly or completely regressed at the control within 2 months, all the others were subjected to surgery. On the basis of the histologic examination (or if regression occurred), 284 of the 534 lumps examined were found to be benign or nontumoral, whereas the other 250 (47%) were carcinomas. Of the latter, 57% were not more than 20 mm in size, whereas in 67.6% there was no microscopic evidence of axillary metastases. Sensitivity of the clinical, mammographic and cytologic examinations was 0.79, 0.76 and 0.72, respectively; specificity 0.71, 0.75 and 0.94, respectively, and the predictive value for malignancy of the positive response of the three examinations 0.71, 0.75 and 0.93, respectively. The use of the diagnostic triplet demonstrated an overall sensitivity of 0.95, specificity of 0.59, and a predictive value for malignancy of 0.98 and 0.93 for benignancy. These results confirm the usefulness of the systematic use of the diagnostic triplet in solid breast lumps of over thirty aged women for the early detection of cancer.

We measured the lateral diffusion of different coenzyme Q homologues and analogues in model lipid vesicles using the fluorescence collisional quenching technique with pyrene derivatives and found diffusion coefficients in the range of 10 −6cm 2/s. Theoretical diffusion coefficients for these highly hydrophobic components were calculated according to the free volume theory. An important parameter in the free volume theory is the relative dimension between diffusant and solvent: a molecular dynamics computer simulation of the coenzymes yielded their most probable geometries and volumes and revealed surprisingly similar sizes of the short and long homologues, due to a folded structure of the isoprenoid chain in the latter, with a length for coenzyme Q 10of 21 Å. Using this information we were able to calculate diffusion coefficients in the range of 10 −6cm 2/s, in good agreement with those found experimentally.

Of 100 cases of Paget's disease of the breast admitted to the National Cancer Institute of Milan from 1940 to 1974, 91 were statistically evaluated. They were divided in two groups according to presence or absence of a palpable nodule. The results of surgical treatment in terms of 5 and 10 year survival rates were 59 and 44 %, respectively, with a median survival of 9 years. For the two separate subgroups, those with a palpable nodule were 38 and 22 % for 5 and 10 years, respectively, while those without a palpable nodule were 92 and 82 % for 5 and 10 years, respectively. For the two groups the median survival was 3.6 and 16.4 years, respectively. The extent of surgery should be dependent on the presence or absence of palpable nodules under the nipple. For the two groups (with and without) extended radical mastectomy and the Patey-Dawson mastectomy are recommended.

A hybrid system (hidden neural network) based on a hidden Markov model (HMM) and neural networks (NN) was trained to predict the bonding states of cysteines in proteins starting from the residue chains. Training was performed using 4136 cysteine-containing segments extracted from 969 non-homologous proteins of well-resolved 3D structure and without chain-breaks. After a 20-fold cross-validation procedure, the efficiency of the prediction scores as high as 80% using neural networks based on evolutionary information. When the whole protein is taken into account by means of an HMM, a hybrid system is generated, whose emission probabilities are computed using the NN output (hidden neural networks). In this case, the predictor accuracy increases up to 88%. Further, when tested on a protein basis, the hybrid system can correctly predict 84% of the chains in the data set, with a gain of at least 27% over the NN predictor.

The RCNPRED server implements a neural network-based method to predict the co-ordination numbers of residues starting from the protein sequence. Using evolutionary information as input, RCNPRED predicts the residue states of the proteins in the database with 69% accuracy and scores 12 percentage points higher than a simple statistical method. Moreover the server implements a neural network to predict the relative solvent accessibility of each residue. A protein sequence can be directly submitted to RCNPRED: residue co-ordination numbers and solvent accessibility for each chain are returned via e-mail.

ABSTRACTIn a two-stage phase II study, 24 patients with first diagnosis of glioblastoma (GBM) were treated with dendritic cell (DC) immunotherapy associated to standard radiochemotherapy with temozolomide (TMZ) followed by adjuvant TMZ.Three intradermal injections of mature DC loaded with autologous GBM lysate were administered before adjuvant TMZ, while 4 injections were performed during adjuvant TMZ. According to a two-stage Simon design, to proceed to the second stage progression-free survival (PFS) 12 months after surgery was expected in at least 8 cases enrolled in the first stage. Evidence of immune response and interaction with chemotherapy were investigated. After a median follow up of 17.4 months, 9 patients reached PFS12. In these patients (responders, 37.5%), DC vaccination induced a significant, persistent activation of NK cells, whose increased response was significantly associated with prolonged survival. CD8+T cells underwent rapid expansion and priming but, after the first administration of adjuvant TMZ, failed to generate a memory status. Resistance to TMZ was associated with robust expression of the multidrug resistance protein ABCC3 in NK but not CD8+T cells. The negative effect of TMZ on the formation of T cell-associated antitumor memory deserves consideration in future clinical trials including immunotherapy.

Motivation. The knowledge of the subcellular localization of a protein is fundamental for elucidating its function. It is difficult to determine the subcellular location for eukaryotic cells with experimental high-throughput procedures. Computational procedures are then needed for annotating the subcellular location of proteins in large scale genomic projects. Results. BaCelLo is a predictor for five classes of subcellular localization (secretory pathway, cytoplasm, nucleus, mitochondrion and chloroplast) and it is based on different SVMs organized in a decision tree. The system exploits the information derived from the residue sequence and from the evolutionary information contained in alignment profiles. It analyzes the whole sequence composition and the compositions of both the N- and C-termini. The training set is curated in order to avoid redundancy. For the first time a balancing procedure is introduced in order to mitigate the effect of biased training sets. Three kingdom-specific predictors are implemented: for animals, plants and fungi, respectively. When distributing the proteins from animals and fungi into four classes, accuracy of BaCelLo reach 74% and 76%, respectively; a score of 67% is obtained when proteins from plants are distributed into five classes. BaCelLo outperforms the other presently available methods for the same task and gives more balanced accuracy and coverage values for each class. We also predict the subcellular localization of five whole proteomes, Homo sapiens, Mus musculus, Caenorhabditis elegans, Saccharomyces cerevisiae and Arabidopsis thaliana, comparing the protein content in each different compartment. Availability. BaCelLo can be accessed at http://www.biocomp.unibo.it/bacello/ Contact. casadio@alma.unibo.it, andrea@biocomp.unibo.it, gigi@biocomp.unibo.it, piero@biocomp.unibo.it

Motivation: One important requirement for protein design is to be able to predict changes of protein stability upon mutation. Different methods addressing this task have been described and their performance tested considering global linear correlation between predicted and experimental data. Neither is direct statistical evaluation of their prediction performance available, nor is a direct comparison among different approaches possible. Recently, a significant database of thermodynamic data on protein stability changes upon single point mutation has been generated (ProTherm). This allows the application of machine learning techniques to predicting free energy stability changes upon mutation starting from the protein sequence. Results: In this paper, we present a neural-network-based method to predict if a given mutation increases or decreases the protein thermodynamic stability with respect to the native structure. Using a dataset consisting of 1615 mutations, our predictor correctly classifies >80% of the mutations in the database. On the same task and using the same data, our predictor performs better than other methods available on the Web. Moreover, when our system is coupled with energy-based methods, the joint prediction accuracy increases up to 90%, suggesting that it can be used to increase also the performance of pre-existing methods, and generally to improve protein design strategies. Availability: The server is under construction and will be available at http://www.biocomp.unibo.it

Motivation: ConSeq is a web server for the identification of biologically important residues in protein sequences. Functionally important residues that take part, e.g. in ligand binding and protein–protein interactions, are often evolutionarily conserved and are most likely to be solvent-accessible, whereas conserved residues within the protein core most probably have an important structural role in maintaining the protein's fold. Thus, estimated evolutionary rates, as well as relative solvent accessibility predictions, are assigned to each amino acid in the sequence; both are subsequently used to indicate residues that have potential structural or functional importance. Availability: The ConSeq web server is available at http://conseq.bioinfo.tau.ac.il/ Supplementary information: The ConSeq methodology, a description of its performance in a set of five well-documented proteins, a comparison to other methods, and the outcome of its application to a set of 111 proteins of unknown function, are presented at http://conseq.bioinfo.tau.ac.il/ under ‘OVERVIEW’, ‘VALIDATION’, ‘COMPARISON’ and ‘PREDICTIONS’, respectively.