D Zheng

EPSVR and EPMeta: Prediction of Antigenic Epitopes Using Support Vector Regression and Multiple Server Results

BackgroundAccurate prediction of antigenic epitopes is important for immunologic research and medical applications, but it is still an open problem in bioinformatics. The case for discontinuous epitopes is even worse - currently there are only a few discontinuous epitope prediction servers available, though discontinuous peptides constitute the majority of all B-cell antigenic epitopes. The small number of structures for antigen-antibody complexes limits the development of reliable discontinuous epitope prediction methods and an unbiased benchmark to evaluate developed methods.ResultsIn this work, we present two novel server applications for discontinuous epitope prediction: EPSVR and EPMeta, where EPMeta is a meta server. EPSVR, EPMeta, and datasets are available at http://sysbio.unl.edu/services.ConclusionThe server application for discontinuous epitope prediction, EPSVR, uses a Support Vector Regression (SVR) method to integrate six scoring terms. Furthermore, we combined EPSVR with five existing epitope prediction servers to construct EPMeta. All methods were benchmarked by our curated independent test set, in which all antigens had no complex structures with the antibody, and their epitopes were identified by various biochemical experiments. The area under the receiver operating characteristic curve (AUC) of EPSVR was 0.597, higher than that of any other existing single server, and EPMeta had a better performance than any single server - with an AUC of 0.638, significantly higher than PEPITO and Disctope (p-value < 0.05).

Prediction of antigenic epitopes on protein surfaces by consensus scoring

BackgroundPrediction of antigenic epitopes on protein surfaces is important for vaccine design. Most existing epitope prediction methods focus on protein sequences to predict continuous epitopes linear in sequence. Only a few structure-based epitope prediction algorithms are available and they have not yet shown satisfying performance.ResultsWe present a new antigen Epitope Prediction method, which uses ConsEnsus Scoring (EPCES) from six different scoring functions - residue epitope propensity, conservation score, side-chain energy score, contact number, surface planarity score, and secondary structure composition. Applied to unbounded antigen structures from an independent test set, EPCES was able to predict antigenic eptitopes with 47.8% sensitivity, 69.5% specificity and an AUC value of 0.632. The performance of the method is statistically similar to other published methods. The AUC value of EPCES is slightly higher compared to the best results of existing algorithms by about 0.034.ConclusionOur work shows consensus scoring of multiple features has a better performance than any single term. The successful prediction is also due to the new score of residue epitope propensity based on atomic solvent accessibility.

Conformational B-Cell Epitope Prediction on Antigen Protein Structures: A Review of Current Algorithms and Comparison with Common Binding Site Prediction Methods

Accurate prediction of B-cell antigenic epitopes is important for immunologic research and medical applications, but compared with other bioinformatic problems, antigenic epitope prediction is more challenging because of the extreme variability of antigenic epitopes, where the paratope on the antibody binds specifically to a given epitope with high precision. In spite of the continuing efforts in the past decade, the problem remains unsolved and therefore still attracts a lot of attention from bioinformaticists. Recently, several discontinuous epitope prediction servers became available, and it is intriguing to review all existing methods and evaluate their performances on the same benchmark. In addition, these methods are also compared against common binding site prediction algorithms, since they have been frequently used as substitutes in the absence of good epitope prediction methods.

Fast and accurate prediction of protein side-chain conformations

Summary: We developed a fast and accurate side-chain modeling program [Optimized Side Chain Atomic eneRgy (OSCAR)-star] based on orientation-dependent energy functions and a rigid rotamer model. The average computing time was 18 s per protein for 218 test proteins with higher prediction accuracy (1.1% increase for χ1 and 0.8% increase for χ1+2) than the best performing program developed by other groups. We show that the energy functions, which were calibrated to tolerate the discrete errors of rigid rotamers, are appropriate for protein loop selection, especially for decoys without extensive structural refinement. Availability: OSCAR-star and the 218 test proteins are available for download at http://sysimm.ifrec.osaka-u.ac.jp/OSCAR Contact: standley@ifrec.osaka-u.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

Unbiased analysis of pancreatic cancer radiation resistance reveals cholesterol biosynthesis as a novel target for radiosensitisation

Background:Despite its promise as a highly useful therapy for pancreatic cancer (PC), the addition of external beam radiation therapy to PC treatment has shown varying success in clinical trials. Understanding PC radioresistance and discovery of methods to sensitise PC to radiation will increase patient survival and improve quality of life. In this study, we identified PC radioresistance-associated pathways using global, unbiased techniques.Methods:Radioresistant cells were generated by sequential irradiation and recovery, and global genome cDNA microarray analysis was performed to identify differentially expressed genes in radiosensitive and radioresistant cells. Ingenuity pathway analysis was performed to discover cellular pathways and functions associated with differential radioresponse and identify potential small-molecule inhibitors for radiosensitisation. The expression of FDPS, one of the most differentially expressed genes, was determined in human PC tissues by IHC and the impact of its pharmacological inhibition with zoledronic acid (ZOL, Zometa) on radiosensitivity was determined by colony-forming assays. The radiosensitising effect of Zol in vivo was determined using allograft transplantation mouse model.Results:Microarray analysis indicated that 11 genes (FDPS, ACAT2, AG2, CLDN7, DHCR7, ELFN2, FASN, SC4MOL, SIX6, SLC12A2, and SQLE) were consistently associated with radioresistance in the cell lines, a majority of which are involved in cholesterol biosynthesis. We demonstrated that knockdown of farnesyl diphosphate synthase (FDPS), a branchpoint enzyme of the cholesterol synthesis pathway, radiosensitised PC cells. FDPS was significantly overexpressed in human PC tumour tissues compared with healthy pancreas samples. Also, pharmacologic inhibition of FDPS by ZOL radiosensitised PC cell lines, with a radiation enhancement ratio between 1.26 and 1.5. Further, ZOL treatment resulted in radiosensitisation of PC tumours in an allograft mouse model.Conclusions:Unbiased pathway analysis of radioresistance allowed for the discovery of novel pathways associated with resistance to ionising radiation in PC. Specifically, our analysis indicates the importance of the cholesterol synthesis pathway in PC radioresistance. Further, a novel radiosensitiser, ZOL, showed promising results and warrants further study into the universality of these findings in PC, as well as the true potential of this drug as a clinical radiosensitiser.

Estimation of CT cone-beam geometry using a novel method insensitive to phantom fabrication inaccuracy: Implications for isocenter localization accuracy

PURPOSE Mechanical instabilities that occur during gantry rotation of on-board cone-beam computed tomography (CBCT) imaging systems limit the efficacy of image-guided radiotherapy. Various methods for calibrating the CBCT geometry and correcting errors have been proposed, including some that utilize dedicated fiducial phantoms. The purpose of this work was to investigate the role of phantom fabrication imprecision on the accuracy of a particular CT cone-beam geometry estimate and to test a new method to mitigate errors in beam geometry arising from imperfectly fabricated phantoms. METHODS The authors implemented a fiducial phantom-based beam geometry estimation following the one described by Cho et al. [Med Phys 32(4), 968-983 (2005)]. The algorithm utilizes as input projection images of the phantom at various gantry angles and provides a full nine parameter beam geometry characterization of the source and detector position and detector orientation versus gantry angle. A method was developed for recalculating the beam geometry in a coordinate system with origin at the source trajectory center and aligned with the axis of gantry rotation, thus making the beam geometry estimation independent of the placement of the phantom. A second CBCT scan with the phantom rotated 180 degrees about its long axis was averaged with the first scan to mitigate errors from phantom imprecision. Computer simulations were performed to assess the effect of 2D fiducial marker positional error on the projections due to image discretization, as well as 3D fiducial marker position error due to phantom fabrication imprecision. Experimental CBCT images of a fiducial phantom were obtained and the algorithm used to measure beam geometry for a Varian Trilogy with an on-board CBCT. RESULTS Both simulations and experimental results reveal large sinusoidal oscillations in the calculated beam geometry parameters with gantry angle due to displacement of the phantom from CBCT isocenter and misalignment with the gantry axis, which are eliminated by recalculating the beam geometry in the source coordinate system. Simulations and experiments also reveal an additional source of oscillations arising from fiducial marker position error due to phantom fabrication imprecision that are mitigated by averaging the results with those of a second CBCT scan with phantom rotated. With a typical fiducial marker position error of 0.020 mm (0.001 in.), source and detector position are found in simulations to be within 250 microm of the true values, and detector and gantry angles less than 0.2 degrees. Detector offsets are within 100 microm of the known value. Experimental results verify the efficacy of the second scan in mitigating beam geometry errors, as well as large apparent source/detector isocenter offsets arising from phantom fabrication imprecision. CONCLUSIONS The authors have developed and validated a novel fiducial phantom-based CBCT beam geometry estimation algorithm that does not require precise positioning of the phantom at machine isocenter and is insensitive to positional imprecision of fiducial markers within the phantom due to fabrication errors. The method can accurately locate source and detector isocenters even when using an imprecise phantom, which is very important for measurement of isocenter coincidence of the therapy and on-board imaging systems.

A novel method for accurate needle-tip identification in trans-rectal ultrasound-based high-dose-rate prostate brachytherapy

PURPOSE In real-time trans-rectal ultrasound (TRUS)-based high-dose-rate prostate brachytherapy, the accurate identification of needle-tip position is critical for treatment planning and delivery. Currently, needle-tip identification on ultrasound images can be subject to large uncertainty and errors because of ultrasound image quality and imaging artifacts. To address this problem, we developed a method based on physical measurements with simple and practical implementation to improve the accuracy and robustness of needle-tip identification. METHODS AND MATERIALS Our method uses measurements of the residual needle length and an off-line pre-established coordinate transformation factor, to calculate the needle-tip position on the TRUS images. The transformation factor was established through a one-time systematic set of measurements of the probe and template holder positions, applicable to all patients. To compare the accuracy and robustness of the proposed method and the conventional method (ultrasound detection), based on the gold-standard X-ray fluoroscopy, extensive measurements were conducted in water and gel phantoms. RESULTS In water phantom, our method showed an average tip-detection accuracy of 0.7 mm compared with 1.6 mm of the conventional method. In gel phantom (more realistic and tissue-like), our method maintained its level of accuracy while the uncertainty of the conventional method was 3.4mm on average with maximum values of over 10mm because of imaging artifacts. CONCLUSIONS A novel method based on simple physical measurements was developed to accurately detect the needle-tip position for TRUS-based high-dose-rate prostate brachytherapy. The method demonstrated much improved accuracy and robustness over the conventional method.

Automatic planning on hippocampal avoidance whole-brain radiotherapy

Mounting evidence suggests that radiation-induced damage to the hippocampus plays a role in neurocognitive decline for patients receiving whole-brain radiotherapy (WBRT). Hippocampal avoidance whole-brain radiotherapy (HA-WBRT) has been proposed to reduce the putative neurocognitive deficits by limiting the dose to the hippocampus. However, urgency of palliation for patients as well as the complexities of the treatment planning may be barriers to protocol enrollment to accumulate further clinical evidence. This warrants expedited quality planning of HA-WBRT. Pinnacle3 Automatic treatment planning was designed to increase planning efficiency while maintaining or improving plan quality and consistency. The aim of the present study is to evaluate the performance of the Pinnacle3 Auto-Planning on HA-WBRT treatment planning. Ten patients previously treated for brain metastases were selected. Hippocampal volumes were contoured on T1 magnetic resonance (MR) images, and planning target volumes (PTVs) were generated based on RTOG0933. The following 2 types of plans were generated by Pinnacle3 Auto-Planning: the one with 2 coplanar volumetric modulated arc therapy (VMAT) arcs and the other with 9-field noncoplanar intensity-modulated radiation therapy (IMRT). D2% and D98% of PTV were used to calculate homogeneity index (HI). HI and Paddick Conformity index (CI) of PTV as well as D100% and Dmax of the hippocampus were used to evaluate the plan quality. All the auto-plans met the dose coverage and constraint objectives based on RTOG0933. The auto-plans eliminated the necessity of generating pseudostructures by the planners, and it required little manual intervention which expedited the planning process. IMRT quality assurance (QA) results also suggest that all the auto-plans are practically acceptable on delivery. Pinnacle3 Auto-Planning generates acceptable plans by RTOG0933 criteria without time-consuming planning process. The expedited quality planning achieved by Auto-Planning (AP) may facilitate protocol enrollment of patients to further investigate the hippocampal-sparing effect and be used to ensure timely start of palliative treatment in future clinical practice.

Effect of the normalized prescription isodose line on the magnitude of Monte Carlo vs. pencil beam target dose differences for lung stereotactic body radiotherapy

In lung stereotactic body radiotherapy (SBRT) cases, the pencil beam (PB) dose calculation algorithm is known to overestimate target dose as compared to the more accurate Monte Carlo (MC) algorithm. We investigated whether changing the normalized prescription isodose line affected the magnitude of MC vs. PB target dose differences. Forty-eight patient plans and twenty virtual-tumor phantom plans were studied. For patient plans, four alternative plans prescribed to 60%, 70%, 80%, and 90% isodose lines were each created for 12 patients who previously received lung SBRT treatments. Using 6 MV dynamic conformal arcs, the plans were individually optimized to achieve similar dose coverage and conformity for all plans of the same patient, albeit at the different prescription levels. These plans, having used a PB algorithm, were all recalculated with MC to compare the target dose differences. The relative MC vs. PB target dose variations were investigated by comparing PTV D95, Dmean, and D5 loss at the four prescription levels. The MC-to-PB ratio of the plan heterogeneity index (HI) was also evaluated and compared among different isodose levels. To definitively demonstrate the cause of the isodose line dependence, a simulated phantom study was conducted using simple, spherical virtual tumors planned with uniform block margins. The tumor size and beam energy were also altered in the phantom study to investigate the interplay between these confounding factors and the isodose line effect. The magnitude of the target dose overestimation by PB was greater for higher prescription isodose levels. The MC vs. PB reduction in the target dose coverage indices, D95 and V100 of PTV, were found to monotonically increase with increasing isodose lines from 60% to 90%, resulting in more pronounced target dose coverage deficiency at higher isodose prescription levels. No isodose level-dependent trend was observed for the dose errors in the target mean or high dose indices, Dmean or D5. The phantom study demonstrated that the observed isodose level dependence was caused by different beam margins used for the different isodose levels: a higher prescription line required a larger beam margin, leading to more low-density lung tissues in the field and, therefore, larger dose errors at the target periphery (when calculated with PB). The phantom study also found that the observed isodose level dependence was greater for smaller targets and for higher beam energies. We hereby characterized the effect of normalized prescription isodose line on magnitude of PTV dose coverage as calculated by MC vs. PB. When comparing reported MC dose deficiency values for different patients, the selection of prescription isodose line should be considered in addition to other factors known to affect differences in calculated doses between various algorithms. PACS number(s): 87.55.kh, 87.55.dk, 87.55.de.In lung stereotactic body radiotherapy (SBRT) cases, the pencil beam (PB) dose calculation algorithm is known to overestimate target dose as compared to the more accurate Monte Carlo (MC) algorithm. We investigated whether changing the normalized prescription isodose line affected the magnitude of MC vs. PB target dose differences. Forty‐eight patient plans and twenty virtual‐tumor phantom plans were studied. For patient plans, four alternative plans prescribed to 60%, 70%, 80%, and 90% isodose lines were each created for 12 patients who previously received lung SBRT treatments. Using 6 MV dynamic conformal arcs, the plans were individually optimized to achieve similar dose coverage and conformity for all plans of the same patient, albeit at the different prescription levels. These plans, having used a PB algorithm, were all recalculated with MC to compare the target dose differences. The relative MC vs. PB target dose variations were investigated by comparing PTV D95, Dmean, and D5 loss at the four prescription levels. The MC‐to‐PB ratio of the plan heterogeneity index (HI) was also evaluated and compared among different isodose levels. To definitively demonstrate the cause of the isodose line dependence, a simulated phantom study was conducted using simple, spherical virtual tumors planned with uniform block margins. The tumor size and beam energy were also altered in the phantom study to investigate the interplay between these confounding factors and the isodose line effect. The magnitude of the target dose overestimation by PB was greater for higher prescription isodose levels. The MC vs. PB reduction in the target dose coverage indices, D95 and V100 of PTV, were found to monotonically increase with increasing isodose lines from 60% to 90%, resulting in more pronounced target dose coverage deficiency at higher isodose prescription levels. No isodose level‐dependent trend was observed for the dose errors in the target mean or high dose indices, Dmean or D5. The phantom study demonstrated that the observed isodose level dependence was caused by different beam margins used for the different isodose levels: a higher prescription line required a larger beam margin, leading to more low‐density lung tissues in the field and, therefore, larger dose errors at the target periphery (when calculated with PB). The phantom study also found that the observed isodose level dependence was greater for smaller targets and for higher beam energies. We hereby characterized the effect of normalized prescription isodose line on magnitude of PTV dose coverage as calculated by MC vs. PB. When comparing reported MC dose deficiency values for different patients, the selection of prescription isodose line should be considered in addition to other factors known to affect differences in calculated doses between various algorithms. PACS number(s): 87.55.kh, 87.55.dk, 87.55.de

Still equivalent for dose calculation in the Monte Carlo era? A comparison of free breathing and average intensity projection CT datasets for lung SBRT using three generations of dose calculation algorithms

Purpose Inhomogeneity dose modeling and respiratory motion description are two critical technical challenges for lung stereotactic body radiotherapy, an important treatment modality for small size primary and secondary lung tumors. Recent studies revealed lung density‐dependent target dose differences between Monte Carlo (Type‐C) algorithm and earlier algorithms. Therefore, this study aimed to investigate the equivalence of the two most popular CT datasets for treatment planning, free breathing (FB) and average intensity projection (AIP) CTs, using Type‐C algorithms, and comparing with two older generation algorithms (Type‐A and Type‐B). Methods Twenty patients (twenty‐one lesions) were planned using a Type‐A algorithm on the FB CT. Lung was contoured separately on FB and AIP CTs and compared. Dose comparison was obtained between the two CTs using four commercial dose algorithms including one Type‐A (Pencil Beam Convolution – PBC), one Type‐B (Analytical Anisotropic Algorithm – AAA), and two Type‐C algorithms (Voxel Monte Carlo – VMC and Acuros External Beam – AXB). For each algorithm, the dosimetric parameters of the target (PTV, Dmin, Dmax, Dmean, D95, and D90) and lung (V5, V10, V20, V30, V35, and V40) were compared between the two CTs using the Wilcoxon signed rank test. Correlation between dosimetric differences and density differences for each algorithm were studied using linear regression and Spearman correlation, in which both global and local density differences were evaluated. Results Although the lung density differences on FB and AIP CTs were statistically significant (P = 0.003), the magnitude was small at 1.21 ± 1.45%. Correspondingly, for the two Type‐C algorithms, target and lung dosimetric differences were small in magnitude and statistically insignificant (P > 0.05) for all but one instance, similar to the findings for the older generation algorithms. Nevertheless, a significant correlation was shown between the dosimetric and density differences for Type‐C and Type‐B algorithms, but not for the Type‐A algorithm. Conclusions With the capability to more accurately model inhomogeneity, Monte Carlo (Type‐C) algorithms are sensitive to respiration‐induced local and global tissue density changes and exhibit a strong correlation between dosimetric and density differences. However, FB and AIP CTs may still be considered equivalent for dose calculation in the Monte Carlo era, due to the small magnitude of lung density differences between these two datasets.