Eva K. Lee

Systems biology of vaccination for seasonal influenza in humans

Here we have used a systems biology approach to study innate and adaptive responses to vaccination against influenza in humans during three consecutive influenza seasons. We studied healthy adults vaccinated with trivalent inactivated influenza vaccine (TIV) or live attenuated influenza vaccine (LAIV). TIV induced higher antibody titers and more plasmablasts than LAIV did. In subjects vaccinated with TIV, early molecular signatures correlated with and could be used to accurately predict later antibody titers in two independent trials. Notably, expression of the kinase CaMKIV at day 3 was inversely correlated with later antibody titers. Vaccination of CaMKIV-deficient mice with TIV induced enhanced antigen-specific antibody titers, which demonstrated an unappreciated role for CaMKIV in the regulation of antibody responses. Thus, systems approaches can be used to predict immunogenicity and provide new mechanistic insights about vaccines.We used a systems biological approach to study innate and adaptive responses to influenza vaccination in humans, during 3 consecutive influenza seasons. Healthy adults were vaccinated with inactivated (TIV) or live attenuated (LAIV) influenza vaccines. TIV induced greater antibody titers and enhanced numbers of plasmablasts than LAIV. In TIV vaccinees, early molecular signatures correlated with, and accurately predicted, later antibody titers in two independent trials. Interestingly, the expression of Calcium/calmodulin-dependent kinase IV (CamkIV) at day 3 was inversely correlated with later antibody titers. Vaccination of CamkIV −/− mice with TIV induced enhanced antigen-specific antibody titers, demonstrating an unappreciated role for CaMKIV in the regulation of antibody responses. Thus systems approaches can predict immunogenicity, and reveal new mechanistic insights about vaccines.

Predicting aberrant CpG island methylation

Epigenetic silencing associated with aberrant methylation of promoter region CpG islands is one mechanism leading to loss of tumor suppressor function in human cancer. Profiling of CpG island methylation indicates that some genes are more frequently methylated than others, and that each tumor type is associated with a unique set of methylated genes. However, little is known about why certain genes succumb to this aberrant event. To address this question, we used Restriction Landmark Genome Scanning to analyze the susceptibility of 1,749 unselected CpG islands to de novo methylation driven by overexpression of DNA cytosine-5-methyltransferase 1 (DNMT1). We found that although the overall incidence of CpG island methylation was increased in cells overexpressing DNMT1, not all loci were equally affected. The majority of CpG islands (69.9%) were resistant to de novo methylation, regardless of DNMT1 overexpression. In contrast, we identified a subset of methylation-prone CpG islands (3.8%) that were consistently hypermethylated in multiple DNMT1 overexpressing clones. Methylation-prone and methylation-resistant CpG islands were not significantly different with respect to size, C+G content, CpG frequency, chromosomal location, or promoter association. We used DNA pattern recognition and supervised learning techniques to derive a classification function based on the frequency of seven novel sequence patterns that was capable of discriminating methylation-prone from methylation-resistant CpG islands with 82% accuracy. The data indicate that CpG islands differ in their intrinsic susceptibility to de novo methylation, and suggest that the propensity for a CpG island to become aberrantly methylated can be predicted based on its sequence context.

Treatment planning for prostate implants using magnetic-resonance spectroscopy imaging

PURPOSE Recent studies have demonstrated that magnetic-resonance spectroscopic imaging (MRSI) of the prostate may effectively distinguish between regions of cancer and normal prostatic epithelium. This diagnostic imaging tool takes advantage of the increased choline plus creatine versus citrate ratio found in malignant compared to normal prostate tissue. The purpose of this study is to describe a novel brachytherapy treatment-planning optimization module using an integer programming technique that will utilize biologic-based optimization. A method is described that registers MRSI to intraoperative-obtained ultrasound images and incorporates this information into a treatment-planning system to achieve dose escalation to intraprostatic tumor deposits. METHODS MRSI was obtained for a patient with Gleason 7 clinically localized prostate cancer. The ratios of choline plus creatine to citrate for the prostate were analyzed, and regions of high risk for malignant cells were identified. The ratios representing peaks on the MR spectrum were calculated on a spatial grid covering the prostate tissue. A procedure for mapping points of interest from the MRSI to the ultrasound images is described. An integer-programming technique is described as an optimization module to determine optimal seed distribution for permanent interstitial implantation. MRSI data are incorporated into the treatment-planning system to test the feasibility of dose escalation to positive voxels with relative sparing of surrounding normal tissues. The resultant tumor control probability (TCP) is estimated and compared to TCP for standard brachytherapy-planned implantation. RESULTS The proposed brachytherapy treatment-planning system is able to achieve a minimum dose of 120% of the 144 Gy prescription to the MRS positive voxels using (125)I seeds. The preset dose bounds of 100-150% to the prostate and 100-120% to the urethra were maintained. When compared to a standard plan without MRS-guided optimization, the estimated TCP for the MRS-optimized plan is superior. The enhanced TCP was more pronounced for smaller volumes of intraprostatic tumor deposits compared to estimated TCP values for larger lesions. CONCLUSIONS Using this brachytherapy-optimization system, we could demonstrate the feasibility of MRS-optimized dose distributions for (125)I permanent prostate implants. Based on probability estimates of anticipated improved TCP, this approach may have an impact on the ability to safely escalate dose and potentially improve outcome for patients with organ-confined but aggressive prostatic cancers. The magnitude of the TCP enhancement, and therefore the risks of ignoring the MR data, appear to be more substantial when the tumor is well localized; however, the gain achievable in TCP may depend quite considerably on the MRS tumor-detection efficiency.

Integer Programming Applied to Intensity-Modulated Radiation Therapy Treatment Planning

In intensity-modulated radiation therapy (IMRT) not only is the shape of the beam controlled, but combinations of open and closed multileaf collimators modulate the intensity as well. In this paper, we offer a mixed integer programming approach which allows optimization over beamlet fluence weights as well as beam and couch angles. Computational strategies, including a constraint and column generator, a specialized set-based branching scheme, a geometric heuristic procedure, and the use of disjunctive cuts, are described. Our algorithmic design thus far has been motivated by clinical cases. Numerical tests on real patient cases reveal that good treatment plans are returned within 30 minutes. The MIP plans consistently provide superior tumor coverage and conformity, as well as dose homogeneity within the tumor region while maintaining a low irradiation to important critical and normal tissues.

Large-Scale Dispensing for Emergency Response to Bioterrorism and Infectious-Disease Outbreak

We describe RealOpt©, a simulation and decision-support system for planning large-scale emergency dispensing clinics to respond to biological threats and infectious-disease outbreaks. The system allows public-health administrators to investigate clinic-design and staffing scenarios quickly. The system incorporates efficient optimization technology seamlessly interfaced with a simulation module. The simulation studies we present explore facility-layout and staffing scenarios for an actual anthrax-emergency drill, and we discuss post-event analysis. Using our staff allocation and assignments for the exercise, DeKalb County achieved the highest throughput among all counties that simultaneously conducted the same scale of anthrax drill at various locations. Its labor usage was at or below that of the other counties. The external evaluators commented that DeKalb produced the most efficient floor plan (with no path crossing), the most cost-effective dispensing (lowest labor and throughput value), and the smoothest operations (shortest average wait time, average queue length, and equalized utilization rate). The study proves that even without historical data, the use of our system enables emergency personnel to plan ahead and be able to estimate required labor resources accurately. The exercise also revealed many areas that need attention during the operations planning and design of dispensing centers. A real-time decision-support system is, therefore, viable through careful design of a stand-alone simulator, coupled with powerful and tailored optimization solvers. The system facilitates analysis of “what-if” scenarios, and serves as an invaluable tool for operational planning and dynamic, on-the-fly reconfigurations of large-scale emergency dispensing clinics. It also allows performing “virtual field exercises” on the decision-support system, offering insight into operations flow and bottlenecks when mass dispensing is required for a region with a large population. Working with emergency-response departments, we will perform additional tuning and development of the system to address different biological attacks and infectious-disease outbreaks, and to ensure its practicality and usability.

A Multifactorial Signature of DNA Sequence and Polycomb Binding Predicts Aberrant CpG Island Methylation

Aberrant CpG island methylation is associated with transcriptional silencing of regulatory genes in human cancer. Although most CpG islands remain unmethylated, a subset accrues aberrant methylation in cancer via unknown mechanisms. Previously, we showed that CpG islands differ in their intrinsic propensity towards hypermethylation. We developed a classifier (PatMAn) based on the frequencies of seven DNA sequence patterns that discriminated methylation-prone (MP) and methylation-resistant (MR) CpG islands. Here, we report on the genome-wide application and direct testing of PatMAn in cancer. Although trained on data from a cell culture model of de novo methylation involving the overexpression of DNMT1, PatMAn accurately predicted CpG islands at increased risk of hypermethylation in cancer cell lines and primary tumors. Analysis of CpG islands predicted to be MP revealed a strong association with embryonic targets of polycomb-repressive complex 2 (PRC2), indicating that PatMAn predicts not only aberrant methylation, but also PRC2 binding. A second classifier (SUPER-PatMAn) that integrates the seven PatMAn DNA patterns with SUZ12 enriched regions as a marker of PRC2 occupancy showed improved performance (prediction accuracy, 81-88%). In addition to many non-PRC2 targets, SUPER-PatMAn identified a subset of PRC2 targets that were more likely to be hypermethylated in cancer. Genome-wide, CpG islands predicted to be MP were enriched in genes known to undergo hypermethylation in cancer, genes functioning in transcriptional regulation, and components of developmental pathways. These findings show that hypermethylation of certain gene loci is controlled in part by an underlying susceptibility influenced by both local sequence context and trans-acting factors.

Modeling and Optimizing the Public-Health Infrastructure for Emergency Response

Public-health emergencies, such as bioterrorist attacks or pandemics, demand fast, efficient, large-scale dispensing of critical medical countermeasures. By combining mathematical modeling, large-scale simulation, and powerful optimization engines, and coupling them with automatic graph-drawing tools and a user-friendly interface, we designed and implemented RealOpt©, a fast and practical emergency-response decision-support tool. RealOpt allows public-health emergency coordinators to (1) determine locations for point-of-dispensing (POD) facility setup; (2) design customized and efficient floor plans for PODs via an automatic graph-drawing tool; (3) determine required labor resources and provide efficient placement of staff at individual stations within a POD; (4) perform disease-propagation analysis, understand and monitor the intra-POD disease dilemma, and help to derive dynamic response strategies to mitigate casualties; (5) assess resources and determine minimum needs to prepare for treating their regional populations in emergency situations; (6) carry out large-scale virtual drills and performance analyses, and investigate alternative strategies; and (7) design a variety of dispensing scenarios that include emergency-event exercises to train personnel. These advanced and powerful computational strategies allow emergency coordinators to quickly analyze design decisions, generate feasible regional dispensing plans based on best estimates and analyses available, and reconfigure PODs as an event unfolds. The ability to analyze planning strategies, compare the various options, and determine the most cost-effective combination of dispensing strategies is critical to the ultimate success of any mass dispensing effort.

Systems Analysis of Immunity to Influenza Vaccination across Multiple Years and in Diverse Populations Reveals Shared Molecular Signatures.

Systems approaches have been used to describe molecular signatures driving immunity to influenza vaccination in humans. Whether such signatures are similar across multiple seasons and in diverse populations is unknown. We applied systems approaches to study immune responses in young, elderly, and diabetic subjects vaccinated with the seasonal influenza vaccine across five consecutive seasons. Signatures of innate immunity and plasmablasts correlated with and predicted influenza antibody titers at 1 month after vaccination with >80% accuracy across multiple seasons but were not associated with the longevity of the response. Baseline signatures of lymphocyte and monocyte inflammation were positively and negatively correlated, respectively, with antibody responses at 1 month. Finally, integrative analysis of microRNAs and transcriptomic profiling revealed potential regulators of vaccine immunity. These results identify shared vaccine-induced signatures across multiple seasons and in diverse populations and might help guide the development of next-generation vaccines that provide persistent immunity against influenza.

Optimization of radiosurgery treatment planning via mixed integer programming.

An automated optimization algorithm based on mixed integer programming techniques is presented for generating high-quality treatment plans for LINAC radiosurgery treatment. The physical planning in radiosurgery treatment involves selecting among a large collection of beams with different physical parameters an optimal beam configuration (geometries and intensities) to deliver the clinically prescribed radiation dose to the tumor volume while sparing the nearby critical structure and normal tissue. The proposed mixed integer programming models incorporate strict dose restrictions on tumor volume, and constraints on the desired number of beams, isocenters, couch angles, and gantry angles. The model seeks to deliver full prescription dose coverage and uniform radiation dose to the tumor volume while minimizing the excess radiation to the periphery normal tissue. In particular, it ensures that proximal normal tissues receive minimal dose via rapid dose fall-off. Preliminary numerical tests on a single patient case indicate that this approach can produce exceptionally high-quality plans in a fraction of the time required using the procedure currently employed by clinicians. The resulting plans provide highly uniform prescription dose to the tumor volume while drastically reducing the irradiation received by the proximal critical normal tissue.

Systems analysis of protective immune responses to RTS,S malaria vaccination in humans

Significance The RTS,S malaria vaccine is the most advanced malaria vaccine candidate to be tested in humans. Despite its promise, there is little understanding of its mechanism of action. In this work, we describe the use of a systems biological approach to identify “molecular signatures” that are induced rapidly after the standard RTS,S vaccination regimen, consisting of three RTS,S immunizations, or with a different regimen consisting of a primary immunization with recombinant adenovirus 35 (Ad35) expressing the circumsporozoite malaria antigen followed by two immunizations with RTS,S. These results reveal important insights about the innate and adaptive responses to vaccination and identify signatures of protective immunity against malaria. RTS,S is an advanced malaria vaccine candidate and confers significant protection against Plasmodium falciparum infection in humans. Little is known about the molecular mechanisms driving vaccine immunity. Here, we applied a systems biology approach to study immune responses in subjects receiving three consecutive immunizations with RTS,S (RRR), or in those receiving two immunizations of RTS,S/AS01 following a primary immunization with adenovirus 35 (Ad35) (ARR) vector expressing circumsporozoite protein. Subsequent controlled human malaria challenge (CHMI) of the vaccinees with Plasmodium-infected mosquitoes, 3 wk after the final immunization, resulted in ∼50% protection in both groups of vaccinees. Circumsporozoite protein (CSP)-specific antibody titers, prechallenge, were associated with protection in the RRR group. In contrast, ARR-induced lower antibody responses, and protection was associated with polyfunctional CD4+ T-cell responses 2 wk after priming with Ad35. Molecular signatures of B and plasma cells detected in PBMCs were highly correlated with antibody titers prechallenge and protection in the RRR cohort. In contrast, early signatures of innate immunity and dendritic cell activation were highly associated with protection in the ARR cohort. For both vaccine regimens, natural killer (NK) cell signatures negatively correlated with and predicted protection. These results suggest that protective immunity against P. falciparum can be achieved via multiple mechanisms and highlight the utility of systems approaches in defining molecular correlates of protection to vaccination.