Lumbar discectomy outcomes vary by herniation level in the Spine Patient Outcomes Research Trial.

BACKGROUND: The Spine Patient Outcomes Research Trial showed an overall advantage for operative compared with nonoperative treatment of lumbar disc herniations. Because a recent randomized trial showed no benefit for operative treatment of a disc at the lumbosacral junction (L5-S1), we reviewed subgroups within the Spine Patient Outcomes Research Trial to assess the effect of herniation level on outcomes of operative and nonoperative care. METHODS: The combined randomized and observation cohorts of the Spine Patient Outcomes Research Trial were analyzed by actual treatment received stratified by level of disc herniation. Overall, 646 L5-S1 herniations, 456 L4-L5 herniations, and eighty-eight upper lumbar (L2-L3 or L3-L4) herniations were evaluated. Primary outcome measures were the Short Form-36 bodily pain and physical functioning scales and the modified Oswestry Disability Index assessed at six weeks, three months, six months, one year, and two years. Treatment effects (the improvement in the operative group minus the improvement in the nonoperative group) were estimated with use of longitudinal regression models, adjusting for important covariates. RESULTS: At two years, patients with upper lumbar herniations (L2-L3 or L3-L4) showed a significantly greater treatment effect from surgery than did patients with L5-S1 herniations for all outcome measures: 24.6 and 7.1, respectively, for bodily pain (p = 0.002); 23.4 and 9.9 for Short Form-36 physical functioning (p = 0.014); and -19 and -10.3 for Oswestry Disability Index (p = 0.033). There was a trend toward greater treatment effect for surgery at L4-L5 compared with L5-S1, but this was significant only for the Short Form-36 physical functioning subscale (p = 0.006). Differences in treatment effects between the upper lumbar levels and L4-L5 were significant for Short Form-36 bodily pain only (p = 0.018). CONCLUSIONS: The advantage of operative compared with nonoperative treatment varied by herniation level, with the smallest treatment effects at L5-S1, intermediate effects at L4-L5, and the largest effects at L2-L3 and L3-L4. This difference in effect was mainly a result of less improvement in patients with upper lumbar herniations after nonoperative treatment.

Signal pathway profiling of epithelial and stromal compartments of colonic carcinoma reveals epithelial-mesenchymal transition.

Molecular crosstalk, including reciprocal stimulation, is theorized to take place between epithelial cancer cells and surrounding non-neoplastic stromal cells. This is the rationale for stromal therapy, which could eliminate support of a cancer by its genetically stable stroma. Epithelial-stromal crosstalk is so far poorly documented in vivo, and cell cultures and animal experiments may not provide accurate models. The current study details stromal-epithelial signalling pathways in 35 human colon cancers, and compares them with matched normal tissues using quantitative proteomic microarrays. Lysates prepared from separately microdissected epithelium and stroma were analysed using antibodies against 61 cell signalling proteins, most of which recognize activated phospho-isoforms. Analyses using unsupervised and supervised statistical methods suggest that cell signalling pathway profiles in stroma and epithelium appear more similar to each other in tumours than in normal colon. This supports the concept that coordinated crosstalk occurs between epithelium and stroma in cancer and suggests epithelial-mesenchymal transition. Furthermore, the data herein suggest that it is driven by cell proliferation pathways and that, specifically, several key molecules within the mitogen-activated protein kinase pathway may play an important role. Given recent findings of epithelial-mesenchymal transition in therapy-resistant tumour epithelium, these findings could have therapeutic implications for colon cancer.

Pharmacogenomic analysis: correlating molecular substructure classes with microarray gene expression data.

Genomic studies are producing large databases of molecular information on cancers and other cell and tissue types. Hence, we have the opportunity to link these accumulating data to the drug discovery processes. Our previous efforts at 'information-intensive' molecular pharmacology have focused on the relationship between patterns of gene expression and patterns of drug activity. In the present study, we take the process a step further-relating gene expression patterns, not just to the drugs as entities, but to approximately 27,000 substructures and other chemical features within the drugs. This coupling of genomic information with structure-based data mining can be used to identify classes of compounds for which detailed experimental structure-activity studies may be fruitful. Using a systematic substructure analysis coupled with statistical correlations of compound activity with differential gene expression, we have identified two subclasses of quinones whose patterns of activity in the National Cancer Institute's 60-cell line screening panel (NCI-60) correlate strongly with the expression patterns of particular genes: (i) The growth inhibitory patterns of an electron-withdrawing subclass of benzodithiophenedione-containing compounds over the NCI-60 are highly correlated with the expression patterns of Rab7 and other melanoma-specific genes; (ii) the inhibitory patterns of indolonaphthoquinone-containing compounds are highly correlated with the expression patterns of the hematopoietic lineage-specific gene HS1 and other leukemia genes. As illustrated by these proof-of-principle examples, we introduce here a set of conceptual tools and fluent computational methods for projecting directly from gene expression patterns to drug substructures and vice versa. The analysis is presented in terms of the NCI-60 cell lines and microarray-based gene expression patterns, but the concept and methods are broadly applicable to other large-scale pharmacogenomic database sets as well. The approach (SAT for Structure-Activity-Target) provides a systematic way to mine databases for the design of further structure-activity studies, particularly to aid in target and lead identification.

Repeated injury to the lumbar nerve roots produces enhanced mechanical allodynia and persistent spinal neuroinflammation.

STUDY DESIGN: A lumbar radiculopathy model investigated pain behavioral responses after nerve root reinjury. OBJECTIVES: To gain a further understanding of central sensitization and neuroinflammation associated with chronic lumbar radiculopathy after repeated nerve root injury. SUMMARY OF BACKGROUND DATA: The pathophysiologic mechanisms associated with chronic radicular pain remain obscure. It has been hypothesized that lumbar root injury produces neuroimmunologic and neurochemical changes, sensitizing the spinal cord and causing pain responses to manifest with greater intensity and longer duration after reinjury. However, this remains untested experimentally. METHODS: Male Holtzman rats were divided into two groups: a sham group having only nerve root exposure, and a chromic group in which the nerve root was ligated loosely with chromic gut suture. Animals underwent a second procedure at 42 days. The chromic group was further divided into a reinjury group and a chromic-sham group, in which the lumbar roots were only re-exposed. Bilateral mechanical allodynia was continuously assessed throughout the study. Qualitative assessment of spinal cord glial activation and IL-beta expression was performed. RESULTS: Mechanical allodynia was significantly greater on both the ipsilateral and contralateral sides after reinjury (P < 0.001), and the response did not return to baseline after reinjury, as it did with the initial injury. There were also persistent spinal astrocytic and microglial activation and interleukin-1beta expression. CONCLUSIONS: The bilateral responses support central modulation of radicular pain after nerve root injury. An exaggerated and more prolonged response bilaterally after reinjury suggests central sensitization after initial injury. Neuroinflammatory activation in the spinal cord further supports the hypothesis that central neuroinflammation plays an important role in chronic radicular pain.

Searching for pharmacogenomic markers: the synergy between omic and hypothesis-driven research.

With 35,000 genes and hundreds of thousands of protein states to identify, correlate, and understand, it no longer suffices to rely on studies of one gene, gene product, or process at a time. We have entered the "omic" era in biology. But large-scale omic studies of cellular molecules in aggregate rarely can answer interesting questions without the assistance of information from traditional hypothesis-driven research. The two types of science are synergistic. A case in point is the set of pharmacogenomic studies that we and our collaborators have done with the 60 human cancer cell lines of the National Cancer Institute's drug discovery program. Those cells (the NCI-60) have been characterized pharmacologically with respect to their sensitivity to >70,000 chemical compounds. We are further characterizing them at the DNA, RNA, protein, and functional levels. Our major aim is to identify pharmacogenomic markers that can aid in drug discovery and design, as well as in individualization of cancer therapy. The bioinformatic and chemoinformatic challenges of this study have demanded novel methods for analysis and visualization of high-dimensional data. Included are the color-coded "clustered image map" and also the MedMiner program package, which captures and organizes the biomedical literature on gene-gene and gene-drug relationships. Microarray transcript expression studies of the 60 cell lines reveal, for example, a gene-drug correlation with potential clinical implications--that between the asparagine synthetase gene and the enzyme-drug L-asparaginase in ovarian cancer cells.

Chemosensitivity prediction by transcriptional profiling.

In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6,817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with P < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds genomic approaches to chemosensitivity prediction are feasible.

Quantitative structure-antitumor activity relationships of camptothecin analogues: cluster analysis and genetic algorithm-based studies.

Topoisomerase 1 (top1) inhibitors are proving useful against a range of refractory tumors, and there is considerable interest in the development of additional top1 agents. Despite crystallographic studies, the binding site and ligand properties that lead to activity are poorly understood. Here we report a unique approach to quantitative structure-activity relationship (QSAR) analysis based on the National Cancer Institute's (NCI) drug databases. In 1990, the NCI established a drug discovery program in which compounds are tested for their ability to inhibit the growth of 60 different human cancer cell lines in culture. More than 70 000 compounds have been screened, and patterns of activity against the 60 cell lines have been found to encode rich information on mechanisms of drug action and drug resistance. Here, we use hierarchical clustering to define antitumor activity patterns in a data set of 167 tested camptothecins (CPTs) in the NCI drug database. The average pairwise Pearson correlation coefficient between activity patterns for the CPT set was 0.70. Coherence between chemical structures and their activity patterns was observed. QSAR studies were carried out using the mean 50% growth inhibitory concentrations (GI(50)) for 60 cell lines as the dependent variables. Different statistical methods, including stepwise linear regression, principal component regression (PCR), partial least-squares regression (PLS), and fully cross-validated genetic function approximation (GFA) were applied to construct quantitative structure-antitumor relationship models. For our data set, the GFA method performed better in terms of correlation coefficients and cross-validation analysis. A number of molecular descriptors were identified as being correlated with antitumor activity. Included were partial atomic charges and three interatomic distances that define the relative spatial dispositions of three significant atoms (the hydroxyl hydrogen of the E-ring, the lactone carbonyl oxygen of the E-ring, and the carbonyl oxygen of the D-ring). The cross-validated r(2) for the final GFA model was 0.783, indicating a predictive QSAR model.

Comparison of a neural net-based QSAR algorithm (PCANN) with Hologram- and multiple linear regression-based QSAR approaches: application to 1,4-dihydropyridine-based calcium channel antagonists.

A QSAR algorithm (PCANN) has been developed and applied to a set of calcium channel blockers which are of special interest because of their role in cardiac disease and also because many of them interact with P-glycoprotein, a membrane protein associated with multidrug resistance to anticancer agents. A database of 46 1,4-dihydropyridines with known Ca2+ channel binding affinities was employed for the present analysis. The QSAR algorithm can be summarized as follows: (1) a set of 90 graph theoretic and information theoretic descriptors representing various structural and topological characteristics was calculated for each of the 1,4-dihydropyridines and (2) principal component analysis (PCA) was used to compress these 90 into the eight best orthogonal composite descriptors for the database. These eight sufficed to explain 96% of the variance in the original descriptor set. (3) Two important empirical descriptors, the Leo-Hansch lipophilic constant and the Hammet electronic parameter, were added to the list of eight. (4) The 10 resulting descriptors were used as inputs to a back-propagation neural network whose output was the predicted binding affinity. (5) The predictive ability of the network was assessed by cross-validation. A comparison of the present approach with two other QSAR approaches (multiple linear regression using the same variables and a Hologram QSAR model) is made and shows that the PCANN approach can yield better predictions, once the right network configuration is identified. The present approach (PCANN) may prove useful for rapid assessment of the potential for biological activity when dealing with large chemical libraries.

Shared decision-making and the orthopaedic workforce.

Studies of physician workforce need a standard of an appropriately sized workforce to compare projections. Although many studies use average rates of healthcare use as a standard, regional benchmarks provide a pragmatic alternative approach to estimating a reasonably sized physician workforce and avoid many of the problems of needs- and demand-based planning. Wide geographic variations in the rates of many procedures, unexplained by differences in population characteristics, suggest that supply-induced demand or physician practice style or both may be the major determinates of the rates for these procedures. In the current study, the authors explore some of these differences in orthopaedic procedure rates and their implications for workforce planning. For example, the rates of hip fracture are fairly uniform across geographic regions, whereas the rates of spine surgery vary sixfold and the rates of spinal fusion vary 10-fold. Shared decision-making is the process of giving patients informed choices about their treatment options based on current best evidence. Careful studies of treatment effectiveness and shared decision-making hold the promise of allowing patients' preferences and values to determine the right rate of healthcare use. These rates could allow workforce projections to be compared with optimal benchmarks for future planning.

Helping patients decide about back surgery: a randomized trial of an interactive video program.

STUDY DESIGN: A randomized trial of 100 patients with low back pain who were potential surgical candidates. OBJECTIVES: To determine whether an interactive videodisc with a booklet is superior to a booklet alone for informing patients about back surgery. SUMMARY OF BACKGROUND DATA: Substantial geographic variation has been observed in lumbar spine surgery. Informed patient preferences should play an important role in decisions about surgery. However, little is known about optimal strategies for informing patients. METHODS: Subjects were randomized to receive an interactive videodisc (with a booklet) or a booklet alone. A knowledge test administered at baseline and follow-up was used to measure improvement in knowledge about treatment options for lumbar spine problems. Patients' reactions to the videodisc and booklet and preferences for treatment were also assessed. RESULTS: The patients' knowledge improved after exposure to either intervention. Multivariate analyses adjusted for baseline score, age, education, gender, and diagnosis showed a significant advantage for the videodisc with booklet over the booklet alone. The videodisc-booklet group showed significantly greater gains in knowledge among subjects with the worst baseline knowledge scores. A larger proportion of subjects in the videodisc-booklet group rated the materials easy to understand (93% vs.- 72%,P = 0.04), containing the right amount of information (93% vs.- 80%,P = 0.3), and adequate to assist in choice of treatment (75% vs.- 51%,P = 0.2). Those who viewed the videodisc expressed a somewhat lower preference for surgery than those who received the booklet alone (23% vs.- 42%,P = 0.4). CONCLUSIONS: Both the booklet alone and the combination of videodisc and booklet improved knowledge. The combination produced greater knowledge gains than the booklet alone for the subgroup with the least knowledge at baseline. Patients preferred the combination and had a slightly lower preference for surgery if they had viewed the video presentation. For some patients, the video may enhance involvement in clinical decisions.

EDGAR: extraction of drugs, genes and relations from the biomedical literature.

EDGAR (Extraction of Drugs, Genes and Relations) is a natural language processing system that extracts information about drugs and genes relevant to cancer from the biomedical literature. This automatically extracted information has remarkable potential to facilitate computational analysis in the molecular biology of cancer, and the technology is straightforwardly generalizable to many areas of biomedicine. This paper reports on the mechanisms for automatically generating such assertions and on a simple application, conceptual clustering of documents. The system uses a stochastic part of speech tagger, generates an underspecified syntactic parse and then uses semantic and pragmatic information to construct its assertions. The system builds on two important existing resources: the MEDLINE database of biomedical citations and abstracts and the Unified Medical Language System, which provides syntactic and semantic information about the terms found in biomedical abstracts.

The impact of spinal problems on the health status of patients: have we underestimated the effect?

STUDY DESIGN: A prospective study of 17,774 patients who consulted spine centers in which the impact of spinal disorders and comorbidities on physical functional status were evaluated. OBJECTIVES: To quantify the effect spinal diagnoses have on patients' physical functional status (SF-36 Physical Component Summary [PCS] score) compared with other common conditions and to quantify the effects of comorbidities on physical functional status in spine patients. SUMMARY OF BACKGROUND DATA: The burden of spinal conditions on a patient's function and the role that comorbidities play in this affliction are poorly quantified in the literature. METHODS: Data from the Health Survey Questionnaire were prospectively gathered through the National Spine Network, a nonprofit consortium of spine-focused practices. Each patient's SF-36 score was summarized into a single PCS score. The correlation between diagnosis and comorbidity and PCS score was assessed using multivariate linear regression. RESULTS: The study patients were a mean of 47.5 years of age, 54.7% were female, 52.3% had lumbosacral diagnoses, and 82.0% had had 3 or more months of pain. The population had a mean PCS score of 30.4 +/- 9.95 (SD) compared with 50.0 +/- 10.00 for the general United States population. The more comorbidities in a patient, the lower the PCS score (Spearman rank correlation = -0.27). The five comorbid conditions that lowered the PCS the most included congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), renal failure, rheumatoid arthritis, and lupus (all P <0.001). In multiple linear regression analysis, age, gender, diagnosis, and comorbidity explained 12.1% of the variance in PCS score. CONCLUSIONS: The PCS score is greatly affected in patients with spinal problems. The study population's PCS (30.4) was lower or similar to the PCS for patients with other illnesses reported in the literature: CHF (31.0), COPD (33.9), SLE (37.1), cancer (38.4), primary total hip arthroplasty (29.0), primary total knee arthroplasty (32.6), and glenohumeral degenerative joint disease (35.2). Further, the presence of comorbidity in spine patients adds to the burden of spinal conditions on functional status.

Cost-effectiveness of fusion with and without instrumentation for patients with degenerative spondylolisthesis and spinal stenosis.

STUDY DESIGN: A cost-effectiveness study was performed from the societal perspective. OBJECTIVE: To evaluate the costs and benefits of laminectomy alone and laminectomy with concomitant lumbar fusion for patients with degenerative lumbar spondylolisthesis and spinal stenosis. SUMMARY OF BACKGROUND DATA: Costs, probabilities, and utilities were estimated from the literature. Short-term risks considered were perioperative complications, the probability of the fusion healing, and the probability that surgery will relieve symptoms. Long-term risks considered were recurrence of symptoms and reoperation. METHODS: The 10-year costs, quality-adjusted life years, and incremental cost-effectiveness ratios (reported as dollars per quality-adjusted year of life gained) were calculated using a Markov model. Sensitivity analysis was performed on all variables using clinically plausible ranges. RESULTS: Laminectomy with noninstrumented fusion costs $56,500 per quality-adjusted year of life versuslaminectomy without fusion. The cost-effectiveness of laminectomy with noninstrumented fusion was most sensitive to the increase in quality-of-life associated with relief of severe stenosis symptoms. The cost-effectiveness ratio of instrumented fusion compared with noninstrumented fusion was $3,112,800 per quality-adjusted year of life. However, if the proportion of patients experiencing symptom relief after instrumented fusion was 90% as compared with 80% for patients with noninstrumented fusion, then the cost-effectiveness ratio of instrumented fusion compared with noninstrumented fusion would be $82,400 per quality-adjusted year of life. CONCLUSIONS: The cost-effectiveness of laminectomy with noninstrumented fusion compares favorably with other surgical interventions, although it depends greatly on the true effectiveness of these surgeries to alleviatesymptoms and on how patients value the quality-of-life effect of relieving severe stenosis symptoms. Instrumented fusion was very expensive compared with the incremental gain in health outcome. Better data on the effectiveness of these alternative procedures are needed.

Spinal glial activation and cytokine expression after lumbar root injury in the rat.

STUDY DESIGN: This study was designed to examine the behaviorial immunohistochemical changes of spinal glial cells and spinal Interleukin (IL)-1beta expression after various nerve root injuries used as models of lumbar radiculopathy. OBJECTIVES: In order to better understand the role of central inflammation in the pathophysiologic mechanisms that give rise to pain associated with lumbar radiculopathy, this research studied the relationship between pain-related behavior associated with spinal glial activation and IL-1beta expression generated by three types of nerve root injury: loose ligation with chromic gut, loose ligation with silk, and tight ligation with silk. SUMMARY OF BACKGROUND DATA: An animal model of lumbar radiculopathy originally described by Kawakami and Weinstein involved loose ligation of unilateral L4-L6 nerve roots with chromic gut. Characterization and establishment of such an animal model of low back pain enables further investigation of the nature of the pathophysiologic mechanisms associated with lumbar radiculopathy in humans. METHODS: Seventy-three rats were divided into four treatment groups. Chromic group (n = 25): The L5 nerve roots (dorsal and ventral) were exposed by hemilaminectomy and loosely ligated with chromic gut. Tight silk group (n = 18): The exposed L5 nerve roots were tightly ligated extradurally with 5-0 silk suture. Loose silk group (n = 15): two loose ligatures of 5-0 silk were placed around the exposed L5 nerve roots. Sham group (n = 15): the rats were subjected to laminectomy alone for exposing nerve roots. Following surgery, thermal hyperalgesia and mechanical allodynia was assessed time-dependently up to 42 days post operatively. At 1, 3, 7, 14, and 42 days postoperatively, the rats in each group were perfused with fixative. The L5 spinal cord segments was harvested and cryosectioned for glial and cytokine immunohistochemistry. RESULTS: In the chromic and the tight silk group, an immediate and sustained mechanical allodynia was observed in the ipsilateral hind paw up to 35 days postoperatively. The loose silk group also showed an immediate mechanical allodynia that subsided by 14 days postoperatively. Sham-treated animals exhibited mild mechanicalallodynia for the initial 7 days after the surgery. Thermalhyperalgesia was evident in the three primary treatment groups, but not in the sham-treated rats. OX-42 expression was elevated in the gray matter of the L5 spinal section by 3 days in the chromic, the tight silk, and the loose silk groups as compared to the sham group. Astrocytic activation increased over time in all groups except the sham group. There was no direct correlation between degree of microglial response and severity of pain behaviors. In contrast, astrocytic activation demonstrated a direct relationship with the elevation of mechanical allodynia for the first 7 days. In addition, spinal IL-1beta protein expression was increased bilaterally in the superficial layer of the dorsal horn and cell nuclei of the ventral horns in the ligature treated groups as compared with the sham group. CONCLUSION: Direct mechanical and/or chemical injury to lumbar roots in the rat gives rise to pain behavior suggestive of lumbar radiculopathy. The finding that glial activation and enhanced IL-1beta expression are observed in the spinal cord after root injury supports a central, neuroimmune component in the generation of lumbar radiculopathy. A further understanding of the immunologic consequences of root injury may lead to further development and the novel use of selective cytokine-inflammatory inhibitors for the treatment of low back pain associated with radiculopathy.

Molecular targets in cancer drug discovery: cell-based profiling.

The phrase "molecular target-based drug discovery" usually implies an in vitro biochemical assay or battery of assays. One portion of the U.S. National Cancer Institute's drug discovery program, to the contrary, examines molecular targets for cancer therapy in a cell-based format. That approach has a number of significant limitations, but it has produced databases of significant utility on the activities and structures of tested compounds, as well as on molecular characteristics of the cell types used for testing.

Mining and visualizing large anticancer drug discovery databases.

In order to find more effective anticancer drugs, the U.S. National Cancer Institute (NCI) screens a large number of compounds in vitro against 60 human cancer cell lines from different organs of origin. About 70,000 compounds have been tested in the program since 1990, and each tested compound can be characterized by a vector (i.e., "fingerprint") of 60 anticancer activity, or -[log(GI50)], values. GI50 is the concentration required to inhibit cell growth by 50% compared with untreated controls. Although cell growth inhibitory activity for a single cell line is not very informative, activity patterns across the 60 cell lines can provide incisive information on the mechanisms of action of screened compounds and also on molecular targets and modulators of activity within the cancer cells. Various statistical and artificial intelligence methods, including principal component analysis, hierarchical cluster analysis, stepwise linear regression, multidimensional scaling, neural network modeling, and genetic function approximation, among others, can be used to analyze this large activity database. Mining the database can provide useful information: (a) for the development of anticancer drugs; (b) for a better understanding of the molecular pharmacology of cancer; and (c) for improvement of the drug discovery process.

Combination gene therapy: synergistic inhibition of human immunodeficiency virus Tat and Rev functions by a single RNA molecule.

Current drug combinations can achieve long-term suppression of HIV replication in infected individuals. Unfortunately, complicated dosing schedules and high toxicity make long-term compliance with drug regimens difficult for most patients. Gene therapy may provide a permanent solution for HIV disease by generating cells genetically resistant to virus replication. As with the highly active antiretroviral therapies, genetic drugs must have strong antiviral potency and the ability to prevent the emergence of escape mutants. We have constructed antiviral genes containing unique combinations of Tat- and Rev-binding decoys. The new antiviral molecules are chimeric TAR-RRE RNAs that are expressed only in HIV infected cells in a Tat-regulated manner. One RNA molecule competes for both Tat and Rev binding, and thus blocks the activation and the expression of all viral genes. The two functional Tat- and Rev-binding domains exhibit the highest synergy at the lowest concentration. Conservative quantitative estimates of this synergistic effect were I = 0.24 at 50% inhibition, in terms of the Berenbaum "interaction index," indicating that the combined construct was approximately fourfold more potent than would be predicted on the basis of additive effects. The possibility of HIV escape from this inhibition is unlikely, because it requires simultaneous mutation of TAR and RRE in a manner in which both Tat and Rev preserve their respective functions. TAR-RRE combination decoys represent the first example of mathematically proven synergistic antiviral activity between two domains of the same molecule.