Real-world incidence and cost of pneumonitis post-chemoradiotherapy for Stage III non-small-cell lung cancer.

Aim: To estimate the real-world incidence and timing of radiation pneumonitis following chemoradiotherapy for Stage III non-small-cell lung cancer and compare costs between patients with and without radiation pneumonitis. Methods: Retrospective analysis using the Symphony Health Integrated Dataverse. Results: Pneumonitis incidence was 12.4% with a 177-day mean time to onset. Patients with versus without pneumonitis were more frequently admitted to the hospital (33.8 vs 19.2%, p < 0.0001) and seen in the emergency room (51.9 vs 35.8%, p < 0.0001) and had higher mean total healthcare costs (US$4251 vs US$3969 per-patient per-month; p = 0.0163). Conclusion: Although pneumonitis significantly increased healthcare resource utilization and costs in chemoradiotherapy-treated Stage III non-small-cell lung cancer, the per-patient per-month differential was <10%. Such financial assessments are critical for cost-benefit analysis.

Observational study of clinical outcomes of eribulin mesylate in metastatic breast cancer after cyclin-dependent kinase 4/6 inhibitor therapy.

Aim: To examine the effectiveness of eribulin mesylate for metastatic breast cancer post cyclin-dependent kinase inhibitor (CDKi) 4/6 therapy. Materials & methods: US community oncologists reviewed charts of patients who had received eribulin from 3 February 2015 to 31 December 2017 after prior CDKi 4/6 therapy and detailed their clinical/treatment history, clinical outcomes (lesion measurements, progression, death) and toxicity. Results: Four patient cohorts were created according to eribulin line of therapy: second line, third line, per US label and fourth line with objective response rates/clinical benefit rates of 42.2%/58.7%, 26.1%/42.3%, 26.7%/54.1% and 17.9%/46.4%, respectively. Median progression-free survival/6-month progression-free survival (79.5% of all patients censored) by cohort was: 9.7 months/77.3%, 10.3 months/71.3%, not reached/70.4% and 4.0 months/0.0%, respectively. Overall occurrence of neutropenia = 23.5%, febrile neutropenia = 1.3%, peripheral neuropathy = 10.1% and diarrhea = 11.1%. Conclusion: Clinical outcome and adverse event rates were similar to those in clinical trials and other observational studies. Longer follow-up is required to confirm these findings.

COMPARING CLINICAL OUTCOMES AND COSTS FOR DIFFERENT TREATMENT INTENSIFICATION APPROACHES IN PATIENTS WITH TYPE 2 DIABETES UNCONTROLLED ON BASAL INSULIN: ADDING GLUCAGON-LIKE PEPTIDE 1 RECEPTOR AGONISTS VERSUS ADDING RAPID-ACTING INSULIN OR INCREASING BASAL INSULIN DOSE.

OBJECTIVE: Not all patients with type 2 diabetes achieve recommended glycated hemoglobin A1c (A1C) levels after adequate titration of basal insulin (BI). Current intensification approaches include addition of rapid-acting insulin (RAI) or a glucagon-like peptide 1 receptor agonist (GLP-1 RA), but it is not clear which strategy results in better long-term outcomes. METHODS: This retrospective analysis of health insurance claims data in the U.S. MarketScan database compared glycemic control and healthcare resource utilization and costs 12 months after adding a GLP-1 RA to BI versus adding a RAI or increasing BI doses. Propensity score matching was used in the comparative effectiveness analysis. RESULTS: A total of 8,034 patients underwent treatment intensification within 6 months of showing poor glycemic control; 4,134 patients had their BI dose adjusted, and 2,076 and 331 received RAI and GLP-1 RA, respectively. A1C changes were similar for the GLP-1 RA and RAI cohorts but higher for the GLP-1 RA versus the dose-adjustment group. The hypoglycemia rate was lower after adding GLP-1 RA versus RAI or increasing BI dose. No overall changes in utilization of healthcare resources or diabetes-related costs were observed between intensification strategies, although prescription costs were higher for the GLP-1 RA cohort. CONCLUSION: BI in combination with GLP-1 RAs appears to be an effective intensification strategy, further reducing A1C levels and hypoglycemia frequency compared to increasing BI doses. GLP-1 RA addition also decreases hypoglycemia frequency versus BI dose increases and RAI addition, without raising overall healthcare costs. ABBREVIATIONS: A1C = hemoglobin A1c; BI = basal insulin; CAD = coronary artery disease; ED = emergency department; FPG = fasting plasma glucose; GLP-1 RA = glucagon-like peptide 1 receptor agonist; ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification; NPH = neutral protamine Hagedorn; OAD = oral antidiabetes drug; PSM = propensity score matching; RAI = rapid-acting insulin; T2D = type 2 diabetes.

Impact of hospital-acquired Clostridium difficile.

BACKGROUND AND AIM: To investigate the impact of hospital-acquired Clostridium difficile infection (CDI) on hospital costs and patient length of stay. METHODS: Data from the 2007-2008 New York State Department of Health's Statewide Planning and Research Cooperative System (SPARCS) database was analyzed using regression analysis and descriptive statistics. RESULTS: After analysis of 4 853 800 patient discharges, the incidence rate of hospital-acquired CDI was 0.8 cases per 1000 discharges. The estimated marginal cost associated with each hospital infection was approximately $29 000. The estimated annual cost of CDI in New York State was approximately $55 million with nearly 23 000 additional hospital days. CONCLUSIONS: The development of hospital-acquired CDI is associated with a significant increase in hospital costs and patient length of stay. Extrapolation of these estimates to all US hospitals suggests this condition represents a major burden to the US healthcare system. Our findings may help hospitals understand the impact of these infections, as well as potential implications if deemed preventable by Centers for Medicare & Medicaid Services and/or private payers. Additionally, this information may benefit hospitals or health care systems transitioning to alternative payment models, such as episode-based payments or accountable care. Healthcare providers and hospitals would benefit from better understanding the impact and frequency of these infections in order to best target preventive strategies.

The financial impact of hospital-acquired conditions.

CONTEXT: This article investigates the financial impact of the Centers for Medicare & Medicaid Services' hospital-acquired conditions (HACs). METHODS: Data from 2007-2008 was analyzed using New York State Department of Health's Statewide Planning and Research Cooperative System (SPARCS), using regression analysis and descriptive statistics for each condition. RESULTS: Of 4,853,800 patient discharges, the development of decubitus ulcers was the most prevalent condition, associated with an annual cost of nearly $680 million and 376,546 hospital days. Mediastinitis after Coronary Artery Bypass Graft (CABG) had the highest marginal impact for both length of stay (LOS) and total costs, but this condition had a relatively low frequency. Extrapolation of the results suggests that HACs represent a major burden to US hospitals. CONCLUSIONS: HACs have a significant financial impact on the US health care system. Hospitals would benefit from better understanding the impact and frequency of these conditions in order to best target preventative strategies.

VirtualPlant: a software platform to support systems biology research.

Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data, its data structures, algorithms, and visualization tools are designed in a species-independent way. VirtualPlant is freely available at www.virtualplant.org.

Systems approach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1.

Understanding how nutrients affect gene expression will help us to understand the mechanisms controlling plant growth and development as a function of nutrient availability. Nitrate has been shown to serve as a signal for the control of gene expression in Arabidopsis. There is also evidence, on a gene-by-gene basis, that downstream products of nitrogen (N) assimilation such as glutamate (Glu) or glutamine (Gln) might serve as signals of organic N status that in turn regulate gene expression. To identify genome-wide responses to such organic N signals, Arabidopsis seedlings were transiently treated with ammonium nitrate in the presence or absence of MSX, an inhibitor of glutamine synthetase, resulting in a block of Glu/Gln synthesis. Genes that responded to organic N were identified as those whose response to ammonium nitrate treatment was blocked in the presence of MSX. We showed that some genes previously identified to be regulated by nitrate are under the control of an organic N-metabolite. Using an integrated network model of molecular interactions, we uncovered a subnetwork regulated by organic N that included CCA1 and target genes involved in N-assimilation. We validated some of the predicted interactions and showed that regulation of the master clock control gene CCA1 by Glu or a Glu-derived metabolite in turn regulates the expression of key N-assimilatory genes. Phase response curve analysis shows that distinct N-metabolites can advance or delay the CCA1 phase. Regulation of CCA1 by organic N signals may represent a novel input mechanism for N-nutrients to affect plant circadian clock function.

In silico evaluation of predicted regulatory interactions in Arabidopsis thaliana.

BACKGROUND: Prediction of transcriptional regulatory mechanisms in Arabidopsis has become increasingly critical with the explosion of genomic data now available for both gene expression and gene sequence composition. We have shown in previous work 1, that a combination of correlation measurements and cis-regulatory element (CRE) detection methods are effective in predicting targets for candidate transcription factors for specific case studies which were validated. However, to date there has been no quantitative assessment as to which correlation measures or CRE detection methods used alone or in combination are most effective in predicting TF-->target relationships on a genome-wide scale. RESULTS: We tested several widely used methods, based on correlation (Pearson and Spearman Rank correlation) and cis-regulatory element (CRE) detection (>or=1 CRE or CRE over-representation), to determine which of these methods individually or in combination is the most effective by various measures for making regulatory predictions. To predict the regulatory targets of a transcription factor (TF) of interest, we applied these methods to microarray expression data for genes that were regulated over treatment and control conditions in wild type (WT) plants. Because the chosen data sets included identical experimental conditions used on TF over-expressor or T-DNA knockout plants, we were able to test the TF-->target predictions made using microarray data from WT plants, with microarray data from mutant/transgenic plants. For each method, or combination of methods, we computed sensitivity, specificity, positive and negative predictive value and the F-measure of balance between sensitivity and positive predictive value (precision). This analysis revealed that the >or=1 CRE and Spearman correlation (used alone or in combination) were the most balanced CRE detection and correlation methods, respectively with regard to their power to accurately predict regulatory-target interactions. CONCLUSION: These findings provide an approach and guidance for researchers interested in predicting transcriptional regulatory mechanisms using microarray data that they generate (or microarray data that is publically available) combined with CRE detection in promoter sequence data.

Health Care Resource Utilization and Costs in First-Line Treatments for Patients with Metastatic Melanoma in the United States.

BACKGROUND: The treatment landscape for patients with metastatic melanoma has changed dramatically with the introduction of novel therapies, such as targeted therapies and immunotherapies, in recent years. Health care resource utilization (HCRU) and cost data are needed to further evaluate these treatments in a value-based health care system. OBJECTIVE: To examine HCRU and total cost of care among U.S. metastatic melanoma patients treated with first-line systemic therapies, including immunotherapies, targeted therapies, and chemotherapy. METHODS: A retrospective observational study was conducted using a U.S. claims database. Adults with ≥ 2 claims for melanoma and ≥ 1 claim for metastasis between January 1, 2012, and June 30, 2017, were identified. Patients had pharmacy and medical enrollment ≥ 6 months before and ≥ 3 months following first-line treatment start. Per patient per month (PPPM) HCRU and costs were calculated by first-line treatment drug class: PD-1 inhibitors, CTLA-4 inhibitors, CTLA-4 + PD-1 combination, BRAF monotherapy, BRAF + MEK combination, and chemotherapy. Adjusted odds ratios (ORs) for HCRU were estimated by logistic regressions and adjusted costs were estimated by generalized linear models using log-link with gamma distribution to control for differences in patient characteristics across groups. RESULTS: Among 1,599 metastatic melanoma patients (PD-1, n = 255; CTLA-4, n = 555; CTLA-4 + PD-1, n = 88; BRAF, n = 210; BRAF + MEK, n=102; chemotherapy=389), mean age ranged from 59-68 years, and the majority were male (62%). Any hospitalization during first-line treatment was less frequent among PD-1-treated patients (25.9%) compared with 34.7%-45.5% of all other groups (all P < 0.05). PPPM hospitalizations were lowest in PD-1 (0.06) compared with 0.09-0.16 across all other groups (all P < 0.05), and PPPM emergency department (ED) visits were lowest in PD-1 (0.09) compared with 0.13-0.18 across all other groups (all P < 0.05), except for BRAF + MEK (0.14, P = 0.08). CTLA-4, CTLA-4 + PD-1, and BRAF + MEK had increased odds of hospitalization compared to PD-1 (adjusted ORs = 2.10, 2.35, 2.15, respectively; all P < 0.05). Total adjusted PPPM costs were significantly lower for PD-1 ($13,059) compared with CTLA-4 ($25,583), CTLA-4 + PD-1 ($31,310), and BRAF + MEK ($21,517) and higher compared to BRAF ($8,158) and chemotherapy ($6,361). CONCLUSIONS: Hospitalizations and ED visits represent important HCRU for metastatic melanoma patients and were lowest among PD-1-treated patients compared with any other systemic therapies (except for ED visits when compared with BRAF + MEK). Total monthly costs varied substantially across first-line regimens and were significantly lower in PD-1-treated patients compared with patients treated with CTLA-4, CTLA-4 + PD-1, and BRAF + MEK. DISCLOSURES: This study was funded by Merck Sharp & Dohme, a subsidiary of Merck & Co. Klink, Feinberg, and Nero are employees of Cardinal Health Specialty Solutions, which received funding from Merck to conduct this study. Chmielsowki is a consultant to Merck but received no funding for the development of this manuscript. Ahsan and Liu are employees of Merck. Chmielowski reports advisory board/speaker fees from Bristol-Myers Squibb, Merck, Genentech/Roche, Iovance Biotherapeutics, HUYA Bioscience International, Compugen, Array BioPharma, Regeneron, Biothera, Janssen, and Novartis. Ahsan has a patent (US20160008380A1) pending.

Real-world outcomes among patients with early rapidly progressive rheumatoid arthritis.

OBJECTIVES: To characterize treatment patterns, healthcare resource utilization (HRU), and disease activity among patients with early rapidly progressive rheumatoid arthritis (eRPRA) in the United States when treated with a first-line biologic disease-modifying antirheumatic drug (bDMARD) tumor necrosis factor-α (TNF) inhibitor or first-line abatacept. STUDY DESIGN: Observational, multicenter, retrospective, longitudinal, medical records-based, cohort study. METHODS: Patients with eRPRA were identified by anti-citrullinated protein antibody positivity, 28-joint Disease Activity Score-C-reactive protein of 3.2 or greater, symptomatic synovitis in 2 or more joints for at least 8 weeks prior to the index date, and onset of symptoms within 2 years or less of the index date. Patients received abatacept or a TNF inhibitor as first-line treatment. Patient characteristics, treatment patterns, HRU, and disease activity following bDMARD initiation were compared across the 2 groups. Odds ratios (ORs) of HRU in the first 6 months of bDMARD treatment were estimated using multivariable logistic regression to adjust for patient mix. RESULTS: There were 60 patients treated with abatacept and 192 treated with a TNF inhibitor in the first line. Those treated with first-line abatacept had lower adjusted odds of hospitalization (OR, 0.42; 95% CI, 0.18-0.95), emergency department (ED) visits (OR, 0.39; 95% CI, 0.16-0.93), and magnetic resonance imaging (MRI) (OR, 0.45; 95% CI, 0.21-0.97) than those treated with a first-line TNF inhibitor (all P <.05). Adjusted odds of achieving low disease activity as measured by clinical disease activity index within 100 days of bDMARD initiation favored first-line abatacept versus a first-line TNF inhibitor (OR, 4.37; 95% CI, 1.34-13.94; P = .01). CONCLUSIONS: Adjusting for disease severity, patients with eRPRA who were treated with first-line abatacept were less likely to have hospitalizations, ED visits, and MRI use during the first 6 months of bDMARD treatment and more likely to achieve low disease activity within 100 days of bDMARD start compared with those who received a first-line TNF inhibitor.

Societal burden of cluster headache in the United States: a descriptive economic analysis.

AIM: To estimate direct and indirect costs in patients with a diagnosis of cluster headache in the US. METHODS: Adult patients (18-64 years of age) enrolled in the Marketscan Commercial and Medicare Databases with ≥2 non-diagnostic outpatient (≥30 days apart between the two outpatient claims) or ≥1 inpatient diagnoses of cluster headache (ICD-9-CM code 339.00, 339.01, or 339.02) between January 1, 2009 and June 30, 2014, were included in the analyses. Patients had ≥6 months of continuous enrollment with medical and pharmacy coverage before and after the index date (first cluster headache diagnosis). Three outcomes were evaluated: (1) healthcare resource utilization, (2) direct healthcare costs, and (3) indirect costs associated with work days lost due to absenteeism and short-term disability. Direct costs included costs of all-cause and cluster headache-related outpatient, inpatient hospitalization, surgery, and pharmacy claims. Indirect costs were based on an average daily wage, which was estimated from the 2014 US Bureau of Labor Statistics and inflated to 2015 dollars. RESULTS: There were 9,328 patients with cluster headache claims included in the analysis. Cluster headache-related total direct costs (mean [standard deviation]) were $3,132 [$13,396] per patient per year (PPPY), accounting for 17.8% of the all-cause total direct cost. Cluster headache-related inpatient hospitalizations ($1,604) and pharmacy ($809) together ($2,413) contributed over 75% of the cluster headache-related direct healthcare cost. There were three sub-groups of patients with claims associated with indirect costs that included absenteeism, short-term disability, and absenteeism + short-term disability. Indirect costs PPPY were $4,928 [$4,860] for absenteeism, $803 [$2,621] for short-term disability, and $3,374 [$3,198] for absenteeism + disability. CONCLUSION: Patients with cluster headache have high healthcare costs that are associated with inpatient admissions and pharmacy fulfillments, and high indirect costs associated with absenteeism and short-term disability.

Racial/ethnic and gender differences in severity of diabetes-related complications, health care resource use, and costs in a Medicare population.

This retrospective cohort study evaluated associations of race/ethnicity and gender with outcomes of diabetes complications severity, health care resource utilization (HRU), and costs among Medicare Advantage health plan members with type 2 diabetes (T2DM). Medical and pharmacy claims were evaluated for 333,576 members continuously enrolled from January 1, 2010, to December 31, 2011, aged 18-89 years, with ≥1 primary diagnosis medical claim, or ≥2 claims with a secondary diagnosis of T2DM (International Classification of Diseases, Ninth Revision, Clinical Modification code 250.x0 or 250.x2). Complications severity assessment by Diabetes Complications Severity Index ranged from 0 (no complications) to 5+. Mean (SD) all-cause medical, pharmacy, and total costs were reported alongside all-cause HRU by place of service (outpatient, inpatient, emergency room [ER]) and number of visits. Multivariate regression showed being Hispanic, black, or male was associated with higher prevalence of more severe complications. This racial/ethnic disparity was more pronounced among females, among whom odds of having more severe complications were higher for Hispanic and black as compared to white females [(Hispanic vs. white odds ratio [OR], 1.40; 95% confidence interval [CI], 1.32-1.48), and (black vs. white OR, 1.22; 95% CI, 1.19-1.25)]. Regardless of gender, blacks had more ER visits than whites. White females incurred the highest total health care costs (mean annual costs: $13,086; 95% CI, $12,935-$13,240, vs. Hispanic females: $10,732; 95% CI, $10,406-$11,067). These effects held regardless of other demographic and clinical attributes. These findings suggest racial/ethnic and gender differences exist in certain T2DM clinical and economic outcomes.

Relationship of diabetes complications severity to healthcare utilization and costs among Medicare Advantage beneficiaries.

OBJECTIVES: This study evaluated the usefulness of the Diabetes Complications Severity Index (DCSI) in assessing healthcare resource utilization (HRU) and costs among Medicare Advantage plan members diagnosed with type 2 diabetes mellitus (T2DM). STUDY DESIGN: A retrospective cohort study of medical and pharmacy claims of 333,576 Medicare members aged 18 to 89 years with ≥1 medical claim with primary diagnosis or ≥2 medical claims with secondary diagnosis, of T2DM (International Classification of Diseases, Ninth Revision, Clinical Modification code 250.x0 or 250.x2) during the period of January 1, 2010, to December 31, 2011. METHODS: DCSI was assessed concurrently with HRU and healthcare costs (total, medical, and pharmacy). The cohort was subdivided into 6 DCSI groups: DCSI = 0 (no complications) through DCSI = 5+ (≥5). Associations of complication severity with HRU and costs of care were summarized using regression models. RESULTS: A 1-point increase in DCSI was associated with a $2744 increase in total costs (a $2480 increase in medical costs plus a $264 increase in pharmacy costs). Increasing DCSI was associated with greater use of inpatient and emergency department (ED) services. Among the higher complications subgroups, there were greater representations of older patients, men, and cases of depressive disorders and hypoglycemia. CONCLUSIONS: DCSI is useful for identifying Medicare plan members with T2DM who should be targeted for clinical programs. HRU and costs increased with DCSI severity. Increases in high-cost HRU, driven by inpatient and ED visits, suggest that preventing or delaying utilization of these services are essential to driving down costs in the T2DM population. Furthermore, high rates of depression and hypoglycemia warrant early screening and necessary treatment to improve patient outcomes.

A system biology approach highlights a hormonal enhancer effect on regulation of genes in a nitrate responsive "biomodule".

BACKGROUND: Nitrate-induced reprogramming of the transcriptome has recently been shown to be highly context dependent. Herein, a systems biology approach was developed to identify the components and role of cross-talk between nitrate and hormone signals, likely to be involved in the conditional response of NO3- signaling. RESULTS: Biclustering was used to identify a set of genes that are N-responsive across a range of Nitrogen (N)-treatment backgrounds (i.e. nitrogen treatments under different growth conditions) using a meta-dataset of 76 Affymetrix ATH1 chips from 5 different laboratories. Twenty-one biclusters were found to be N-responsive across subsets of this meta-dataset. N-bicluster 9 (126 genes) was selected for further analysis, as it was shown to be reproducibly responsive to NO3- as a signal, across a wide-variety of background conditions and datasets. N-bicluster 9 genes were then used as "seed" to identify putative cross-talk mechanisms between nitrate and hormone signaling. For this, the 126 nitrate-regulated genes in N-bicluster 9 were biclustered over a meta-dataset of 278 ATH1 chips spanning a variety of hormone treatments. This analysis divided the bicluster 9 genes into two classes: i) genes controlled by NO3- only vs. ii) genes controlled by both NO3- and hormones. The genes in the latter group showed a NO3- response that is significantly enhanced, compared to the former. In silico analysis identified two Cis-Regulatory Elements candidates (CRE) (E2F, HSE) potentially involved the interplay between NO3- and hormonal signals. CONCLUSION: This systems analysis enabled us to derive a hypothesis in which hormone signals are proposed to enhance the nitrate response, providing a potential mechanistic explanation for the link between nitrate signaling and the control of plant development.

An integrated genetic, genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis.

BACKGROUND: Light and carbon are two important interacting signals affecting plant growth and development. The mechanism(s) and/or genes involved in sensing and/or mediating the signaling pathways involving these interactions are unknown. This study integrates genetic, genomic and systems approaches to identify a genetically perturbed gene network that is regulated by the interaction of carbon and light signaling in Arabidopsis. RESULTS: Carbon and light insensitive (cli) mutants were isolated. Microarray data from cli186 is analyzed to identify the genes, biological processes and gene networks affected by the integration of light and carbon pathways. Analysis of this data reveals 966 genes regulated by light and/or carbon signaling in wild-type. In cli186, 216 of these light/carbon regulated genes are misregulated in response to light and/or carbon treatments where 78% are misregulated in response to light and carbon interactions. Analysis of the gene lists show that genes in the biological processes "energy" and "metabolism" are over-represented among the 966 genes regulated by carbon and/or light in wild-type, and the 216 misregulated genes in cli186. To understand connections among carbon and/or light regulated genes in wild-type and the misregulated genes in cli186, the microarray data is interpreted in the context of metabolic and regulatory networks. The network created from the 966 light/carbon regulated genes in wild-type, reveals that cli186 is affected in the light and/or carbon regulation of a network of 60 connected genes, including six transcription factors. One transcription factor, HAT22 appears to be a regulatory "hub" in the cli186 network as it shows regulatory connections linking a metabolic network of genes involved in "amino acid metabolism", "C-compound/carbohydrate metabolism" and "glycolysis/gluconeogenesis". CONCLUSION: The global misregulation of gene networks controlled by light and carbon signaling in cli186 indicates that it represents one of the first Arabidopsis mutants isolated that is specifically disrupted in the integration of both carbon and light signals to control the regulation of metabolic, developmental and regulatory genes. The network analysis of misregulated genes suggests that CLI186 acts to integrate light and carbon signaling interactions and is a master regulator connecting the regulation of a host of downstream metabolic and regulatory processes.