Greedy parameter optimization for diabatic quantum annealing.

A shorter processing time is desirable for quantum computation to minimize the effects of noise. We propose a simple procedure to variationally determine a set of parameters in the transverse-field Ising model for quantum annealing (QA) appended with a field along the [Formula: see text]-axis. The method consists of greedy optimization of the signs of coefficients of the [Formula: see text]-field term based on the outputs of short annealing processes. We test the idea in the ferromagnetic system with all-to-all couplings and spin-glass problems, and find that the method outperforms the traditional form of QA and simulated annealing in terms of the success probability and the time to solution, in particular, in the case of shorter annealing times, achieving the goal of improved performance while avoiding noise. The non-stoquastic [Formula: see text] term can be eliminated by a rotation in the spin space, resulting in a non-trivial diabatic control of the coefficients in the stoquastic transverse-field Ising model, which may be feasible for experimental realization. This article is part of the theme issue 'Quantum annealing and computation: challenges and perspectives'.

Lossy compression of matrices by black box optimisation of mixed integer nonlinear programming.

In edge computing, suppressing data size is a challenge for machine learning models that perform complex tasks such as autonomous driving, in which computational resources (speed, memory size and power) are limited. Efficient lossy compression of matrix data has been introduced by decomposing it into the product of an integer and real matrices. However, its optimisation is difficult as it requires simultaneous optimisation of an integer and real variables. In this paper, we improve this optimisation by utilising recently developed black-box optimisation (BBO) algorithms with an Ising solver for binary variables. In addition, the algorithm can be used to solve mixed-integer programming problems that are linear and non-linear in terms of real and integer variables, respectively. The differences between the choice of Ising solvers (simulated annealing, quantum annealing and simulated quenching) and the strategies of the BBO algorithms (BOCS, FMQA and their variations) are discussed for further development of the BBO techniques.

Application of QUBO solver using black-box optimization to structural design for resonance avoidance.

Quadratic unconstrained binary optimization (QUBO) solvers can be applied to design an optimal structure to avoid resonance. QUBO algorithms that work on a classical or quantum device have succeeded in some industrial applications. However, their applications are still limited due to the difficulty of transforming from the original optimization problem to QUBO. Recently, black-box optimization (BBO) methods have been proposed to tackle this issue using a machine learning technique and a Bayesian treatment for combinatorial optimization. We propose a BBO method based on factorization machine to design a printed circuit board for resonance avoidance. This design problem is formulated to maximize natural frequency and simultaneously minimize the number of mounting points. The natural frequency, which is the bottleneck for the QUBO formulation, is approximated to a quadratic model in the BBO method. For the efficient approximation around the optimum solution, in the proposed method, we probabilistically generate the neighbors of the optimized solution of the current model and update the model. We demonstrated that the proposed method can find the optimum mounting point positions in shorter calculation time and higher success probability of finding the optimal solution than a conventional BBO method. Our results can open up QUBO solvers' potential for other applications in structural designs.

Second-line lenvatinib in patients with recurrent endometrial cancer.

OBJECTIVE: This study assessed the efficacy of lenvatinib, a multitargeted tyrosine kinase inhibitor, as second-line therapy in patients with unresectable endometrial cancer. The primary end point was the objective response rate (ORR) as assessed by independent radiologic review (IRR). Secondary end points included median progression-free survival (PFS), overall survival (OS), and clinical benefit rate. Exploratory end points examined the association of baseline levels of plasma biomarkers (50 circulating cytokine and/or angiogenic factors measured by immunoassays) with efficacy outcomes. METHODS: An international, open-label, single-arm, multicenter, phase 2 trial was conducted. Eligible patients had histologically confirmed unresectable endometrial cancer that relapsed after 1 prior systemic platinum-based chemotherapy. Patients received once-daily oral lenvatinib 24 mg in a 28-day dosing cycle. RESULTS: There were 133 patients in the study. By IRR, 19 patients had a confirmed objective response for an ORR of 14.3% (95% CI: 8.8-21.4). Durable stable disease (≥23 weeks) was observed in 31 patients (23.3%) and the clinical benefit rate was 37.6% (95% CI: 29.3-46.4). Median PFS was 5.6 months (95% CI: 3.7-6.3), and median OS was 10.6 months (95% CI: 8.9-14.9). The most common (any grade) treatment-related adverse events were fatigue/asthenia (48%), hypertension (49%), nausea/vomiting (32%), decreased appetite (32%), and diarrhea (31%). Lower baseline levels of angiopoietin-2 were associated with longer PFS, OS, and a higher ORR. CONCLUSIONS: Patients with recurrent endometrial cancer treated with second-line lenvatinib experienced modest antitumor activity and treatment was generally well tolerated, with a safety profile consistent with previous studies.

An interpretable machine learning model for diagnosis of Alzheimer's disease.

We present an interpretable machine learning model for medical diagnosis called sparse high-order interaction model with rejection option (SHIMR). A decision tree explains to a patient the diagnosis with a long rule (i.e., conjunction of many intervals), while SHIMR employs a weighted sum of short rules. Using proteomics data of 151 subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, SHIMR is shown to be as accurate as other non-interpretable methods (Sensitivity, SN = 0.84 ± 0.1, Specificity, SP = 0.69 ± 0.15 and Area Under the Curve, AUC = 0.86 ± 0.09). For clinical usage, SHIMR has a function to abstain from making any diagnosis when it is not confident enough, so that a medical doctor can choose more accurate but invasive and/or more costly pathologies. The incorporation of a rejection option complements SHIMR in designing a multistage cost-effective diagnosis framework. Using a baseline concentration of cerebrospinal fluid (CSF) and plasma proteins from a common cohort of 141 subjects, SHIMR is shown to be effective in designing a patient-specific cost-effective Alzheimer's disease (AD) pathology. Thus, interpretability, reliability and having the potential to design a patient-specific multistage cost-effective diagnosis framework can make SHIMR serve as an indispensable tool in the era of precision medicine that can cater to the demand of both doctors and patients, and reduce the overwhelming financial burden of medical diagnosis.

Exploratory analysis of biomarkers associated with clinical outcomes from the study of lenvatinib in differentiated cancer of the thyroid.

BACKGROUND: Lenvatinib significantly prolonged progression-free survival (PFS) versus placebo in the phase III Study of (E7080) LEnvatinib in differentiated Cancer of the Thyroid (SELECT) of patients with radioiodine-refractory differentiated thyroid cancer. This exploratory analysis investigated potential predictive biomarkers of lenvatinib efficacy and target engagement. PATIENTS AND METHODS: Circulating cytokine/angiogenic factors (CAFs) in blood samples collected at baseline and throughout treatment were analysed from patients randomised to receive lenvatinib or placebo from August 5, 2011 to October 4, 2012. For CAF biomarker analyses, patients were dichotomised by baseline levels. Tumour tissues were analysed for BRAF and NRAS/KRAS/HRAS mutations. RESULTS: Tumours and CAFs were analysed from 183/392 (47%) and 387/392 (99%) patients, respectively. Lenvatinib PFS benefit was maintained in all assessments. For lenvatinib-treated patients, interaction-term analyses revealed that low baseline Ang2 level was predictive of tumour shrinkage (Pinteraction = 0.016) and PFS (Pinteraction = 0.018). Vascular endothelial growth factor and fibroblast growth factor 23 (FGF23) were significantly upregulated with lenvatinib, and FGF23 upregulation on cycle 1/day 15 was associated with longer PFS. In mutation analyses, no significant differences in clinical outcomes were observed. BRAFWT may be a negative prognostic factor for PFS in placebo-treated patients with papillary thyroid cancer (P = 0.019). CONCLUSION: The lenvatinib PFS benefit was maintained regardless of baseline CAF or BRAF/RAS status. Baseline Ang2 was predictive of PFS in a subgroup of lenvatinib-treated patients, indicating that Ang2 may be predictive of lenvatinib sensitivity. BRAFWT may be a poor prognostic factor in patients with radioiodine-refractory papillary thyroid cancer. Improved PFS associated with upregulated FGF23 suggests that lenvatinib-induced FGF receptor inhibition contributes to lenvatinib efficacy. Trial registration ID of the main study, SELECT: ClinicalTrials.gov: NCT01321554.

Safety and Pharmacokinetics of Lenvatinib in Patients with Advanced Hepatocellular Carcinoma.

PURPOSE: To determine the maximum tolerable dose (MTD), safety, pharmacokinetics, pharmacodynamics, and preliminary efficacy of lenvatinib in patients with advanced hepatocellular carcinoma (HCC). EXPERIMENTAL DESIGN: This multicenter, open-label, phase I, dose-escalation study included patients aged 20 to 80 years, refractory to standard therapy, and stratified by hepatic function measured using Child-Pugh (CP) scores: CP-A (score, 5-6) and CP-B (score, 7-8). Lenvatinib was administered continually once daily for 4-week cycles. MTD was defined as the maximum dose associated with ≤ 1 dose-limiting toxicity (DLT) occurring in cycle 1 among 6 patients. RESULTS: In total, 20 patients (9 in CP-A and 11 in CP-B) were enrolled. The MTD was 12 and 8 mg once daily in CP-A and CP-B, respectively; DLTs included proteinuria, hepatic encephalopathy, and hyperbilirubinemia. The most common grade 3 toxicities included hypertension in CP-A and hyperbilirubinemia in CP-B. Lenvatinib plasma concentration at 24 hours after administration (C24 h) for 12 mg once daily was higher in patients with HCC than in patients with other solid tumors shown in a previous phase I study, but C24 h for 25 mg once daily lenvatinib was comparable. After lenvatinib treatment, the number of circulating endothelial and c-Kit(+) cells decreased and the levels of interleukin (IL)-6, IL10, granulocyte-colony stimulating factor, and vascular endothelial growth factor increased (P < 0.05). Partial responses were observed in 3 patients and tumor shrinkage occurred in 14 patients. CONCLUSIONS: Lenvatinib (12 mg once daily) demonstrated preliminary efficacy with manageable toxicity and is the recommended dose for phase II studies in patients with HCC and CP-A.

Selective inhibition of EZH2 by EPZ-6438 leads to potent antitumor activity in EZH2-mutant non-Hodgkin lymphoma.

Mutations within the catalytic domain of the histone methyltransferase EZH2 have been identified in subsets of patients with non-Hodgkin lymphoma (NHL). These genetic alterations are hypothesized to confer an oncogenic dependency on EZH2 enzymatic activity in these cancers. We have previously reported the discovery of EPZ005678 and EPZ-6438, potent and selective S-adenosyl-methionine-competitive small molecule inhibitors of EZH2. Although both compounds are similar with respect to their mechanism of action and selectivity, EPZ-6438 possesses superior potency and drug-like properties, including good oral bioavailability in animals. Here, we characterize the activity of EPZ-6438 in preclinical models of NHL. EPZ-6438 selectively inhibits intracellular lysine 27 of histone H3 (H3K27) methylation in a concentration- and time-dependent manner in both EZH2 wild-type and mutant lymphoma cells. Inhibition of H3K27 trimethylation (H3K27Me3) leads to selective cell killing of human lymphoma cell lines bearing EZH2 catalytic domain point mutations. Treatment of EZH2-mutant NHL xenograft-bearing mice with EPZ-6438 causes dose-dependent tumor growth inhibition, including complete and sustained tumor regressions with correlative diminution of H3K27Me3 levels in tumors and selected normal tissues. Mice dosed orally with EPZ-6438 for 28 days remained tumor free for up to 63 days after stopping compound treatment in two EZH2-mutant xenograft models. These data confirm the dependency of EZH2-mutant NHL on EZH2 activity and portend the utility of EPZ-6438 as a potential treatment for these genetically defined cancers.

Biological validation that SF3b is a target of the antitumor macrolide pladienolide.

Pladienolide is a naturally occurring macrolide that binds to the SF3b complex to inhibit mRNA splicing. It has not been fully validated whether the splicing impairment is a relevant mechanism for the potent antitumor activity of pladienolide. We established pladienolide-resistant clones from WiDr and DLD1 colorectal cancer cells that were insensitive to the inhibitory action of pladienolide on cell proliferation and splicing. An mRNA-Seq differential analysis revealed that these two cell lines have an identical mutation at Arg1074 in the gene for SF3B1, which encodes a subunit of the SF3b complex. Reverse expression of the mutant protein transferred pladienolide resistance to WiDr cells. Furthermore, immunoprecipitation analysis using a radiolabeled probe showed that the mutation impaired the binding affinity of paldienolide to its target. These results clearly demonstrate that pladienolide exerts its potent activity by targeting SF3b and also suggest that inhibition of SF3b is a promising drug target for anticancer therapy.

Expressions of cytochrome P450, UDP-glucuronosyltranferase, and transporter genes in monolayer carcinoma cells change in subcutaneous tumors grown as xenografts in immunodeficient nude mice.

Human tumors grown as xenografts in immunodeficient nude mice are widely used to investigate the pharmacological activities of anticancer drugs. Drug-metabolizing enzymes and transporters are expressed in tumor cell lines and changes in drug metabolism and pharmacokinetics (DMPK)-related gene expression after inoculation of the tumor cell may affect the pharmacological activity of the drug under consideration. The aims of the current study were to characterize DMPK-related gene expression profiles and responses to typical cytochrome P450 inducers in monolayer carcinoma cells grown in tissue culture versus those inoculated into a xenograft model. We used the human hepatocellular carcinoma cell line PLC/PRF/5 for this study and comprehensively assessed changes in DMPK-related gene expression by reverse transcription-polymerase chain reaction quantitation. CYP3A4 and UDP-glucuronosyltransferase 1A protein amounts were also analyzed by immunoprecipitation followed by immunoblotting. We found that the expression of many DMPK-related genes was elevated in the inoculated tumor compared with the monolayer carcinoma cells, indicating changes in their gene regulation pathways, presumably due to modulation of the nuclear receptor family of transcription factors. In addition, monolayer carcinoma versus inoculated tumor cells showed different responses to rifampicin, but similar responses to dexamethasone or 3-methylcholanthrene. These results suggest that inoculation of tumor cells results in the activation of drug metabolism and transport function, leading to changes in the responses to pregnane X receptor ligands and consequent discrepancies in the pharmacological activities between in vitro monolayer carcinoma cells and in vivo xenograft models.

Inoculation of human tumor cells alters the basal expression but not the inducibility of cytochrome P450 enzymes in tumor-bearing mouse liver.

The athymic nude mouse is often used to grow tumors for in vivo oncology research, including the identification of anticancer drugs, whereas wild-type mice are usually used to assess the pharmacokinetics (PK) of new chemical entities. The relationship between PK and pharmacodynamics (PD) provides useful mechanistic information and helps guide of the clinical regimen. The aim of this study was to assess whether the inoculation of human hepatocellular carcinoma cells (PLC/PRF/5) into athymic nude mice alters the expression of genes encoding the drug-metabolizing enzymes and transporters in host liver. The livers from nontumor- and tumor-bearing mice were initially subjected to drug metabolism gene microarray analysis. Microarray analysis indicated that tumor inoculation had little effect on drug metabolism-related genes, including several cytochrome P450s: Cyp1a, Cyp2b, and Cyp3a. This result was further confirmed by reverse transcription-polymerase chain reaction (RT-PCR). However, immunoreactive proteins of Cyp1a, Cyp2b, and Cyp3a were suppressed by tumor inoculation. RT-PCR and Western immunoblotting analysis showed that the inducibility of Cyp1a, Cyp2b, and Cyp3a by 3-methylcholanthrene, phenobarbital, and dexamethasone, respectively, was similar between nontumor- and tumor-bearing mice. These results suggest that inoculation of human tumor cells into athymic nude mice suppresses the expression of certain drug-metabolizing enzymes, which may alter the PK and PD of antitumor drugs.

Quantitative phosphorus metabolomics using nanoflow liquid chromatography-tandem mass spectrometry and culture-derived comprehensive global internal standards.

Highly sensitive and quantitative analytical methods are essential for metabolomics. In this report, we introduce an analytical method focused on endogenous phosphorus metabolites, using nanoflow liquid chromatography-electrospray ionization tandem mass spectrometry (nanoLC-ESI-MS/MS) and culture-derived isotope-tagged metabolites as global internal standards for quantitative metabolomics. The nanoLC-ESI-MS/MS method employing a stone-arch microcolumn with amino propyl silica gel achieved good separation of phosphorus metabolites with forty- to hundred-fold increase of sensitivity compared with semimicro flow LC-ESI-MS. The quantitative reproducibility of the nanoLC-ESI-MS has been improved to the point where it is useful for studies of cellular metabolism. Focused metabolomics using culture-derived internal standards was employed to monitor 184 phosphorus-related metabolic changes in cancer cells treated with metabolic enzyme inhibitors, methotrexate, fluorouracil, and gemcitabine. We found marked perturbations of cellular metabolism, of which many, though not all, were in line with the known biological activities of these drugs.

Microarray-based identification of CUB-domain containing protein 1 as a potential prognostic marker in conventional renal cell carcinoma.

PURPOSE: Renal cell carcinoma (RCC) is characterized by a variable and unpredictable clinical course. Thus, accurate prediction of the prognosis is important in clinical settings. We conducted microarray-based study to identify a novel prognostic marker in conventional RCC. PATIENTS AND METHODS: The present study included the patients surgically treated at Kyoto University Hospital. Gene expression profiling of 39 samples was carried out to select candidate prognostic markers. Quantitative real-time PCR of 65 samples confirmed the microarray experiment results. Finally, we evaluated the significance of potential markers at their protein expression level by immunohistochemically analyzing 230 conventional RCC patients. RESULTS: Using expression profiling analysis, we identified 14 candidate genes whose expression levels predicted unfavorable disease-specific survival. Next, we examined the expression levels of nine candidate genes by quantitative real-time PCR and selected CUB-domain containing protein 1 (CDCP1) for further immunohistochemical analysis. Positive staining for CDCP1 inversely correlated with disease-specific and recurrence-free survivals. In multivariate analysis including clinical/pathological factors, CDCP1 staining was a significant predictor of disease-specific and recurrence-free survivals. CONCLUSIONS: We identified CDCP1 as a potential prognostic marker for conventional RCC. Further studies might be required to confirm the prognostic value of CDCP1 and to understand its function in RCC progression.

In silico approach to identify the expression of the undiscovered molecules from microarray public database: identification of odorant receptors expressed in non-olfactory tissues.

Although both genomic sequencing and expression analysis are becoming indispensable for biological research, methods that can effectively survey large public gene expression repositories remain to be established. In this study, we developed an approach for the retrieval of tissue-specific expression information for certain genes from public databases; our approach was based on performance of a basic local alignment search tool search against probes on DNA microarray chips. To test the effectiveness of this approach, we examined the expression of human odorant receptors in non-olfactory tissues, as recent studies showed that such non-olfactory odorant receptors have physiological and pathophysiological significance. When we screened a large expression data set using this approach, we were able to effectively identify candidate odorant receptors in non-olfactory tissues and confirmed their expression by reverse transcription-polymerase chain reaction. Using receiver-operating characteristic curve analysis, the sensitivity and the specificity of this approach were 60 and 68%, respectively, indicating that the use of this technique would efficiently identify the previously unidentified expression of odorant receptors in non-olfactory tissues. Taken together, the in silico approach, as shown in the present study, would facilitate to elucidate the function of genes of interest.

Identification of endocrine disruptor biodegradation by integration of structure-activity relationship with pathway analysis.

We present a SAR method that can predict estrogen-like endocrine disrupting chemical (EDC) activity as well as key biodegradation steps for detoxification. This method is based on a recent graph-mining algorithm developed by Kudo et al., which generates a set of descriptors from all potent chemical fragments (including rings). This method is novel in that it achieves chemical diversity in the training data set by sampling another data set of larger diversity. The model achieved an 83% accuracy prediction rate, and identified 1291 EDC candidates from the KEGG database. From this set of candidate compounds, bisphenol A was chosen for assay validation and biodegradation pathway analysis. Results showed that bisphenol A exhibited estrogen-like activity and was degraded in three distinct reactions. The prediction model provided information on the mechanism of the ligand-target binding, such as key functional groups involved. We focused on the enzyme commission number, which is useful for analyses of biodegradation pathways. Results identified oxygenases, ether hydrolases, and carbon-halide lyases as being important in the biodegradation pathway. This combined approach provided new information regarding the biodegradation of EDCs, and can potentially be extended to applications with transcriptomic, proteomic, and metabolomic data to provide a quick screen of biological activity and biodegradation pathway(s).

An ultrasensitive new DNA microarray chip provides gene expression profiles for preoperative esophageal cancer biopsies without RNA amplification.

OBJECTIVES: Gene expression profiling using pretreatment biopsies has been limited due to their small sample sizes. This study evaluated the usefulness of an ultrasensitive new DNA microarray chip, which has a unique array structure, for the clinical diagnosis of esophageal cancer using preoperative biopsies. METHODS: Paired cancer and normal esophageal epithelial tissues from 56 patients who underwent esophagectomy and from 48 patients who underwent preoperative endoscopy were studied. Among 2 feature gene sets selected by a reference DNA chip discriminating malignant status of samples, 20 feature genes were selected for the development of the new DNA chip. The new DNA chip was hybridized with 0.1 mug of total RNA per slide without RNA amplification. RESULTS: Twenty feature genes, including RRM-2 and XRCC-3, for the new DNA chip could discriminate cancer from noncancer at a 95.2% rate of accuracy in 42 biopsies (sensitivity 95.7%, specificity 94.7%). A receiver operating characteristic (ROC) curve analysis showed that the area under ROC curve for the prediction was 0.966. CONCLUSIONS: The gene expression profiles from the preoperative biopsies could diagnose esophageal cancer accurately, using the ultrasensitive DNA chip without RNA amplification. This new DNA chip technology might contribute further to the development of customized therapeutic strategies for various cancer patients.

High throughput comparative genomic hybridization array analysis of multifocal urothelial cancers.

The purpose of this study was to examine genetic alterations occur during synchronous or metachronous multifocal development of urothelial cancers on the whole genome using a comparative genomic hybridization (CGH) array. We used 10 tumor pairs (2 tumors for each patient), in which we had previously defined a clonal relationship by microsatellite analysis. For CGH array analysis, Vysis GenoSensor Array 300 kit was used. An unsupervised hierarchical cluster analysis revealed that the tumors from one patient were clustered together independent of the tumors of all other patients. On the other hand, many genetic divergences among multifocal urothelial cancers were newly found by a CGH array analysis. The concordant genetic alteration patterns of the chromosomal arm in tumor pairs were most frequently observed in 9p, 9q, 8p, 7p, 7q and 11q, while discordant patterns were most frequently found in 15q, 20q, 2q, 10p and 11q. Investigation using a CGH array showed that genetically stable multifocal tumors were less frequent, and that a large percentage of urothelial cancers accumulate genetic alterations during multifocal development by clonal evolution. We might have to consider these genetic accumulations during multifocal development when designing strategies for prevention and detection of recurrent multifocal urothelial cancers. CGH array can be a powerful tool for genetic analysis of multifocal urothelial cancer.

Developmental aberrations of liver gene expression in bovine fetuses derived from somatic cell nuclear transplantation.

Cloning by somatic cell nuclear transfer (NT) has been accomplished. However, the process itself is inefficient since most clones die before birth and survivors often display various anomalies. In an effort to determine global expression profiles of developmentally regulated liver genes in NT bovine fetuses, we employed a custom-made bovine liver complementary DNA (cDNA) microarray. The NT fetuses in early pregnancy were derived from cumulus cells as the nuclear donor cells. Normal fetuses were derived from in vitro fertilization (IVF) and artificial insemination (AI). Gene expression levels in NT, IVF, and AI fetal livers were obtained by comparing individual fetal liver samples with that of adult liver of nonpregnant cycling cows. Statistical analyses of the expression data showed widespread dysregulation of developmentally important genes in the three NT fetuses examined. It was found that the number of dysregulated genes was within a range of 3.5-7.7% of the tested genes in the NT fetal livers. The analyses revealed that one NT fetus was markedly different in liver gene expression profile from the other two NT fetal livers in which the expression profiles were highly correlated. Thus, our findings demonstrate that widespread dysregulation of liver genes occurs in the developing liver of NT bovine fetuses. It is possible that inappropriate genomic reprogramming after NT is a key factor associated with abnormal gene expressions in the livers of NT fetuses, whereas distinct expression patterns between the fellow cloned fetuses likely have resulted from variable epigenetic status of the donor nuclei.

Inhibition of protein kinase CK2 prevents the progression of glomerulonephritis.

Glomerulonephritis (GN) is a progressive inflammation that may be caused by a variety of underlying disorders. It is the primary cause of chronic renal failure and end-stage renal disease, which require dialysis and transplantation worldwide. Immunosuppressive therapy has been used to treat GN clinically, but this treatment has had insufficient therapeutic effects. Here, we show that protein kinase CK2 is a key molecule in the progression of GN. cDNA microarray analysis identified CK2alpha, the catalytic subunit of CK2, as a GN-related, differentially expressed gene. Overexpression of CK2alpha was noted in the proliferative glomerular lesions in rat GN models and in renal biopsy specimens from lupus nephritis or IgA nephropathy patients. Administration of either antisense oligodeoxynucleotide against CK2alpha or low molecular weight CK2-specific inhibitors effectively prevented the progression of renal pathology in the rat GN models. The resolution of GN by CK2 inhibition may result from its suppression of extracellular signal-regulated kinase-mediated cell proliferation, and its suppression of inflammatory and fibrotic processes that are enhanced in GN. Our results show that CK2 plays a critical role in the progression of immunogenic renal injury, and therefore, CK2 is a potential target for GN therapy.