CTTN Overexpression Confers Cancer Stem Cell-like Properties and Trastuzumab Resistance via DKK-1/WNT Signaling in HER2 Positive Breast Cancer.

BACKGROUND: Despite the therapeutic success of trastuzumab, HER2 positive (HER2+) breast cancer patients continue to face significant difficulties due to innate or acquired drug resistance. In this study we explored the potential role of CTTN in inducing trastuzumab resistance of HER2+ breast cancers. METHODS: Genetic changes of CTTN and survival of HER2+ breast cancer patients were analyzed in multiple breast cancer patient cohorts (METABRIC, TCGA, Kaplan-Meier (KM) plotter, and Hanyang University cohort). The effect of CTTN on cancer stem cell activity was assessed using the tumorsphere formation, ALDEFLUOR assay, and by in vivo xenograft experiments. CTTN-induced trastuzumab resistance was assessed by the sulforhodamine B (SRB) assay, colony formation assays, and in vivo xenograft model. RNA-seq analysis was used to clarify the mechanism of trastuzumab resistance conferred by CTTN. RESULTS: Survival analysis indicated that CTTN overexpression is related to a poor prognosis in HER2+ breast cancers (OS, p = 0.05 in the Hanyang University cohort; OS, p = 0.0014 in KM plotter; OS, p = 0.008 and DFS, p = 0.010 in METABRIC). CTTN overexpression-induced cancer stem cell-like characteristics in experiments of tumorsphere formation, ALDEFLUOR assays, and in vivo limiting dilution assays. CTTN overexpression resulted in trastuzumab resistance in SRB, colony formation assays, and in vivo xenograft models. Mechanistically, the mRNA and protein levels of DKK-1, a Wnt antagonist, were downregulated by CTTN. Treatment of the ß-catenin/TCF inhibitor reversed CTTN-induced cancer stem cell-like properties in vitro. Combination treatment with trastuzumab and ß-catenin/TCF inhibitor overcame trastuzumab resistance conferred by CTTN overexpression in in vitro colony formation assays. CONCLUSIONS: CTTN activates DKK-1/Wnt/ß-catenin signaling to induce trastuzumab resistance. We propose that CTTN is a novel biomarker indicating a poor prognosis and a possible therapeutic target for overcoming trastuzumab resistance.

Osteoporosis Pre-Screening Using Ensemble Machine Learning in Postmenopausal Korean Women.

As osteoporosis is a degenerative disease related to postmenopausal aging, early diagnosis is vital. This study used data from the Korea National Health and Nutrition Examination Surveys to predict a patient's risk of osteoporosis using machine learning algorithms. Data from 1431 postmenopausal women aged 40-69 years were used, including 20 features affecting osteoporosis, chosen by feature importance and recursive feature elimination. Random Forest (RF), AdaBoost, and Gradient Boosting (GBM) machine learning algorithms were each used to train three models: A, checkup features; B, survey features; and C, both checkup and survey features, respectively. Of the three models, Model C generated the best outcomes with an accuracy of 0.832 for RF, 0.849 for AdaBoost, and 0.829 for GBM. Its area under the receiver operating characteristic curve (AUROC) was 0.919 for RF, 0.921 for AdaBoost, and 0.908 for GBM. By utilizing multiple feature selection methods, the ensemble models of this study achieved excellent results with an AUROC score of 0.921 with AdaBoost, which is 0.1-0.2 higher than those of the best performing models from recent studies. Our model can be further improved as a practical medical tool for the early diagnosis of osteoporosis after menopause.

Epigenetic mechanisms involved in the neuroprotective effect of scorpion extract in a Parkinson's disease murine model based on multi-omics approach.

OBJECTIVE: To investigate whether scorpion extract elicits a neuroprotective effect in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice models, and the genes associated with the therapeutic effects using RNA sequencing (seq) analysis. METHODS: This study investigated the changes in interaction between messenger ribonucleic acid (mRNA) expression and deoxyribonucleic acid (DNA) methylation related to the protective effects of scorpion extracts, in the substantia nigra (SN) region of a MPTP-induced Parkinson's disease (PD) model. RESULTS: In this model, scorpion extracts attenuated the motor impairment as demonstrated by the rotarod and open field tests. Scorpion extracts consistently attenuated the decrease of tyrosine hydroxylase (TH) positive neural cells in the SN and striatum of mice. We profiled genome- wide DNA methylation using Methyl-Seq and measured the transcriptome using RNA-Seq in murine SN in the following groups: vehicle-treated MPTP-induced PD mice and scorpion extract- treated MPTP-induced PD mice. In total, 13 479 differentially expressed genes were identified in association with the anti-PD effect of the scorpion extract, mainly in the promoter and coding regions. Among them, 47 were negatively correlated down- regulated genes. Nineteen genes out of 47 down- regulated genes were negatively correlated with the expression of the other 28 genes. Among these genes, SGSM1 was related to dopaminergic neu- rons including dopamine transporters, TH, dihy- droxyphenylalanine decarboxylase, and dopamine D2 receptor. CONCLUSION: This study provides insights into the anti-parkinsonian effects of scorpion extract and reveals the epigenetic targets in its therapeutic mechanism.

Identification of Target Chicken Populations by Machine Learning Models Using the Minimum Number of SNPs.

A marker combination capable of classifying a specific chicken population could improve commercial value by increasing consumer confidence with respect to the origin of the population. This would facilitate the protection of native genetic resources in the market of each country. In this study, a total of 283 samples from 20 lines, which consisted of Korean native chickens, commercial native chickens, and commercial broilers with a layer population, were analyzed to determine the optimal marker combination comprising the minimum number of markers, using a 600 k high-density single nucleotide polymorphism (SNP) array. Machine learning algorithms, a genome-wide association study (GWAS), linkage disequilibrium (LD) analysis, and principal component analysis (PCA) were used to distinguish a target (case) group for comparison with control chicken groups. In the processing of marker selection, a total of 47,303 SNPs were used for classifying chicken populations; 96 LD-pruned SNPs (50 SNPs per LD block) served as the best marker combination for target chicken classification. Moreover, 36, 44, and 8 SNPs were selected as the minimum numbers of markers by the AdaBoost (AB), Random Forest (RF), and Decision Tree (DT) machine learning classification models, which had accuracy rates of 99.6%, 98.0%, and 97.9%, respectively. The selected marker combinations increased the genetic distance and fixation index (Fst) values between the case and control groups, and they reduced the number of genetic components required, confirming that efficient classification of the groups was possible by using a small number of marker sets. In a verification study including additional chicken breeds and samples (12 lines and 182 samples), the accuracy did not significantly change, and the target chicken group could be clearly distinguished from the other populations. The GWAS, PCA, and machine learning algorithms used in this study can be applied efficiently, to determine the optimal marker combination with the minimum number of markers that can distinguish the target population among a large number of SNP markers.

NSD3-Induced Methylation of H3K36 Activates NOTCH Signaling to Drive Breast Tumor Initiation and Metastatic Progression.

Histone methyltransferase NSD3 is frequently dysregulated in human cancers, yet the epigenetic role of NSD3 during cancer development remains elusive. Here we report that NSD3-induced methylation of H3K36 is crucial for breast tumor initiation and metastasis. In patients with breast cancer, elevated expression of NSD3 was associated with recurrence, distant metastasis, and poor survival. In vivo, NSD3 promoted malignant transformation of mammary epithelial cells, a function comparable to that of HRAS. Furthermore, NSD3 expanded breast cancer-initiating cells and promoted epithelial-mesenchymal transition to trigger tumor invasion and metastasis. Mechanistically, the long isoform (full-length transcript) of NSD3, but not its shorter isoform lacking a catalytic domain, cooperated with EZH2 and RNA polymerase II to stimulate H3K36me2/3-dependent transactivation of genes associated with NOTCH receptor cleavage, leading to nuclear accumulation of NICD and NICD-mediated transcriptional repression of E-cadherin. Furthermore, mice harboring primary and metastatic breast tumors with overexpressed NSD3 showed sensitivity to NOTCH inhibition. Together, our findings uncover the critical epigenetic role of NSD3 in the modulation of NOTCH-dependent breast tumor progression, providing a rationale for targeting the NSD3-NOTCH signaling regulatory axis in aggressive breast cancer. SIGNIFICANCE: This study demonstrates the functional significance of histone methyltransferase NSD3 in epigenetic regulation of breast cancer stemness, EMT, and metastasis, suggesting NSD3 as an actionable therapeutic target in metastatic breast cancer.

Cancer Target Gene Screening: a web application for breast cancer target gene screening using multi-omics data analysis.

Breast cancer comprises several molecular subtypes with distinct clinical features and treatment responses, and a substantial portion of each subtype remains incurable. A comprehensive analysis of multi-omics data and clinical profiles is required in order to better understand the biological complexity of this cancer type and to identify new prognostic and therapeutic markers. Thus, there arises a need for useful analytical tools to assist in the investigation and clinical management of the disease. We developed Cancer Target Gene Screening (CTGS), a web application that provides rapid and user-friendly analysis of multi-omics data sets from a large number of primary breast tumors. It allows the investigation of genomic and epigenomic aberrations, evaluation of transcriptomic profiles and performance of survival analyses and of bivariate correlations between layers of omics data. Notably, the genome-wide screening function of CTGS prioritizes candidate genes of clinical and biological significance among genes with copy number alteration, DNA methylation and dysregulated expression by the integrative analysis of different types of omics data in customized subgroups of breast cancer patients. These features may help in the identification of druggable cancer driver genes in a specific subtype or the clinical condition of human breast cancer. CTGS is available at http://ctgs.biohackers.net.

CDK12 drives breast tumor initiation and trastuzumab resistance via WNT and IRS1-ErbB-PI3K signaling.

Cyclin-dependent kinase 12 (CDK12) has emerged as an effective therapeutic target due to its ability to regulate DNA damage repair in human cancers, but little is known about the role of CDK12 in driving tumorigenesis. Here, we demonstrate that CDK12 promotes tumor initiation as a novel regulator of cancer stem cells (CSCs) and induces anti-HER2 therapy resistance in human breast cancer. High CDK12 expression caused by concurrent amplification of CDK12 and HER2 in breast cancer patients is associated with disease recurrence and poor survival. CDK12 induces self-renewal of breast CSCs and in vivo tumor-initiating ability, and also reduces susceptibility to trastuzumab. Furthermore, CDK12 kinase activity inhibition facilitates anticancer efficacy of trastuzumab in HER2+ tumors, and mice bearing trastuzumab-resistant HER2+ tumor show sensitivity to an inhibitor of CDK12. Mechanistically, the catalytic activity of CDK12 is required for the expression of genes involved in the activation of ErbB-PI3K-AKT or WNT-signaling cascades. These results suggest that CDK12 is a major oncogenic driver and an actionable target for HER2+ breast cancer to replace or augment current anti-HER2 therapies.

Author Correction: Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

In the Methods section of this Article, 'greater than' should have been 'less than' in the sentence 'Putative regions of clustered rearrangements were identified as having an average inter-rearrangement distance that was at least 10 times greater than the whole-genome average for the individual sample. '. The Article has not been corrected.

Role of MEL-18 Amplification in Anti-HER2 Therapy of Breast Cancer.

BACKGROUND: Resistance to HER2-targeted therapy with trastuzumab still remains a major challenge in HER2-amplified tumors. Here we investigated the potential role of MEL-18, a polycomb group gene, as a novel prognostic marker for trastuzumab resistance in HER2-positive (HER2+) breast cancer. METHODS: The genetic alteration of MEL-18 and its clinical relevance were examined in multiple breast cancer cohorts including METABRIC (n = 1,980), TCGA (n = 825), and our clinical specimens (n = 213, trastuzumab-treated HER2+ cases). MEL-18 amplification was validated by fluorescence in situ hybridization (FISH) analysis. The MEL-18 effect on trastuzumab response was confirmed by in vitro cell viability assays and an in vivo xenograft experiment (n = 7 per group). Gene expression microarray and receptor tyrosine kinase array were performed to identify the trastuzumab resistance mechanism by MEL-18 loss. All statistical tests were two-sided. RESULTS: MEL-18 was exclusively amplified in approximately 30-50% of HER2+ breast tumors and was associated with a favorable clinical outcome (disease-free survival: P = .02 in HER2+ cases, METABRIC; P = .04 in patients receiving trastuzumab). In MEL-18-amplified HER2+ breast cancer, MEL-18 depletion induced trastuzumab resistance by increasing ADAM sheddase-mediated ErbB ligand production and receptor heterodimerization. MEL-18 epigenetically silenced ADAM10/17 expression in cooperation with polycomb-repressive complex (PRC) 1 and PRC2. Combination treatment with an ADAM10/17 inhibitor and trastuzumab could overcome MEL-18 loss-mediated trastuzumab resistance in vivo (BT474/shMEL-18 xenograft: trastuzumab, mean [SD] tumor volume = 406.1 [50.1] mm3, vs trastuzumab + GW280264 30 mg/kg, mean [SD] tumor volume = 68.4 [15.6] mm3, P < .001). Consistently, trastuzumab-treated patients harboring concomitant MEL-18 amplification and low ADAM17 expression showed prolonged relapse-free survival (P = .02 in our cohort, n = 213). CONCLUSION: MEL-18 serves to prevent ligand-dependent ErbB heterodimerization and trastuzumab resistance, suggesting MEL-18 amplification as a novel biomarker for HER2+ breast cancer.

Role of RBP2-Induced ER and IGF1R-ErbB Signaling in Tamoxifen Resistance in Breast Cancer.

Background: Despite the benefit of endocrine therapy, acquired resistance during or after treatment still remains a major challenge in estrogen receptor (ER)-positive breast cancer. We investigated the potential role of histone demethylase retinoblastoma-binding protein 2 (RBP2) in endocrine therapy resistance of breast cancer. Methods: Survival of breast cancer patients according to RBP2 expression was analyzed in three different breast cancer cohorts including METABRIC (n = 1980) and KM plotter (n = 1764). RBP2-mediated tamoxifen resistance was confirmed by invitro sulforhodamine B (SRB) colorimetric, colony-forming assays, and invivo xenograft models (n = 8 per group). RNA-seq analysis and receptor tyrosine kinase assay were performed to identify the tamoxifen resistance mechanism by RBP2. All statistical tests were two-sided. Results: RBP2 was associated with poor prognosis to tamoxifen therapy in ER-positive breast cancer (P = .04 in HYU cohort, P = .02 in KM plotter, P = .007 in METABRIC, log-rank test). Furthermore, RBP2 expression was elevated in patients with tamoxifen-resistant breast cancer (P = .04, chi-square test). Knockdown of RBP2 conferred tamoxifen sensitivity, whereas overexpression of RBP2 induced tamoxifen resistance invitro and invivo (MCF7 xenograft: tamoxifen-treated control, mean [SD] tumor volume = 70.8 [27.9] mm3, vs tamoxifen-treated RBP2, mean [SD] tumor volume = 387.9 [85.1] mm3, P < .001). Mechanistically, RBP2 cooperated with ER co-activators and corepressors and regulated several tamoxifen resistance-associated genes, including NRIP1, CCND1, and IGFBP4 and IGFBP5. Furthermore, epigenetic silencing of IGFBP4/5 by RBP2-ER-NRIP1-HDAC1 complex led to insulin-like growth factor-1 receptor (IGF1R) activation. RBP2 also increased IGF1R-ErbB crosstalk and subsequent PI3K-AKT activation via demethylase activity-independent ErbB protein stabilization. Combinational treatment with tamoxifen and PI3K inhibitor could overcome RBP2-mediated tamoxifen resistance (RBP2-overexpressing cells: % cell viability [SD], tamoxifen = 89.0 [3.8]%, vs tamoxifen with BKM120 = 41.3 [5.6]%, P < .001). Conclusions: RBP2 activates ER-IGF1R-ErbB signaling cascade in multiple ways to induce tamoxifen resistance, suggesting that RBP2 is a potential therapeutic target for ER-driven cancer.

Gene-based comparative analysis of tools for estimating copy number alterations using whole-exome sequencing data.

Accurate detection of copy number alterations (CNAs) using next-generation sequencing technology is essential for the development and application of more precise medical treatments for human cancer. Here, we evaluated seven CNA estimation tools (ExomeCNV, CoNIFER, VarScan2, CODEX, ngCGH, saasCNV, and falcon) using whole-exome sequencing data from 419 breast cancer tumor-normal sample pairs from The Cancer Genome Atlas. Estimations generated using each tool were converted into gene-based copy numbers; concordance for gains and losses and the sensitivity and specificity of each tool were compared to validated copy numbers from a single nucleotide polymorphism reference array. The concordance and sensitivity of the tumor-normal pair methods for estimating CNAs (saasCNV, ExomeCNV, and VarScan2) were better than those of the tumor batch methods (CoNIFER and CODEX). SaasCNV had the highest gain and loss concordances (65.0%), sensitivity (69.4%), and specificity (89.1%) for estimating copy number gains or losses. These findings indicate that improved CNA detection algorithms are needed to more accurately interpret whole-exome sequencing results in human cancer.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

The topography of mutational processes in breast cancer genomes.

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Furthermore, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.

MEL-18 loss mediates estrogen receptor-α downregulation and hormone independence.

The polycomb protein MEL-18 has been proposed as a tumor suppressor in breast cancer; however, its functional relevance to the hormonal regulation of breast cancer remains unknown. Here, we demonstrated that MEL-18 loss contributes to the hormone-independent phenotype of breast cancer by modulating hormone receptor expression. In multiple breast cancer cohorts, MEL-18 was markedly downregulated in triple-negative breast cancer (TNBC). MEL-18 expression positively correlated with the expression of luminal markers, including estrogen receptor-α (ER-α, encoded by ESR1). MEL-18 loss was also associated with poor response to antihormonal therapy in ER-α-positive breast cancer. Furthermore, whereas MEL-18 loss in luminal breast cancer cells resulted in the downregulation of expression and activity of ER-α and the progesterone receptor (PR), MEL-18 overexpression restored ER-α expression in TNBC. Consistently, in vivo xenograft experiments demonstrated that MEL-18 loss induces estrogen-independent growth and tamoxifen resistance in luminal breast cancer, and that MEL-18 overexpression confers tamoxifen sensitivity in TNBC. MEL-18 suppressed SUMOylation of the ESR1 transactivators p53 and SP1, thereby driving ESR1 transcription. MEL-18 facilitated the deSUMOylation process by inhibiting BMI-1/RING1B-mediated ubiquitin-proteasomal degradation of SUMO1/sentrin-specific protease 1 (SENP1). These findings demonstrate that MEL-18 is a SUMO-dependent regulator of hormone receptors and suggest MEL-18 expression as a marker for determining the antihormonal therapy response in patients with breast cancer.

Immunization, hybridoma generation, and selection for monoclonal antibody production.

Monoclonal antibodies (MAbs) produced by a single clone of cells with homogeneous binding specificity for an antigenic determinant have been used in diagnostics and therapeutics. Many new methods have been devised by scientists for making hybridomas and MAbs. The three major steps for producing MAbs are immunization, immortalization, and isolation. Here, we describe technical details of the three important steps for generating mouse hybridomas and MAbs.

Affinity maturation of monoclonal antibodies by multi-site-directed mutagenesis.

High-affinity antibodies are crucial for development of monoclonal antibody (MAb)-based therapeutics for human diseases. Many new detailed methods for affinity maturation have been developed to improve MAb qualities by site-directed mutagenesis, chain shuffling, and error-prone PCR. Site-directed mutagenesis on hotspots in variable heavy (VH) complementary-determining region (CDR) 3 is a commonly used method for improving therapeutic potency and efficacy of targeted MAbs. Strategies for affinity maturation via multi-site-directed mutagenesis in VH-CDR3 described here are for valuable technical tool in the armamentarium of immunologists for development of fast-performance MAbs. Our strategy includes (1) selection of targeted MAb, (2) replacement of certain amino acid residues (e.g., negative or neutral charge to positive amino acids) in VH-CDR3, and (3) determination of binding activity to a target antigen.

Production and characterization of chimeric monoclonal antibodies against Burkholderia pseudomallei and B. mallei using the DHFR expression system.

Burkholderia pseudomallei (BP) and B. mallei (BM) are closely related gram-negative, facultative anaerobic bacteria which cause life-threatening melioidosis in human and glanders in horse, respectively. Our laboratory has previously generated and characterized more than 100 mouse monoclonal antibodies (MAbs) against BP and BM, according to in vitro and in vivo assay. In this study, 3 MAbs (BP7 10B11, BP7 2C6, and BP1 7F7) were selected to develop into chimeric mouse-human monoclonal antibodies (cMAbs) against BP and/or BM. For the stable production of cMAbs, we constructed 4 major different vector systems with a dihydrofolate reductase (DHFR) amplification marker, and optimized transfection/selection conditions in mammalian host cells with the single-gene and/or double-gene expression system. These 3 cMAbs were stably produced by the DHFR double mutant Chinese hamster ovarian (CHO)-DG44 cells. By ELISA and Western blot analysis using whole bacterial antigens treated by heat (65°C/90 min), sodium periodate, and proteinase K, the cMAb BP7 10B11 (cMAb CK1) reacted with glycoproteins (34, 38, 48 kDa in BP; 28, 38, 48 kDa in BM). The cMAb BP7 2C6 (cMAb CK2) recognized surface-capsule antigens with molecular sizes of 38 to 52 kDa, and 200 kDa in BM. The cMAb CK2 was weakly reactive to 14∼28, 200 kDa antigens in BP. The cMAb BP1 7F7 (cMAb CK3) reacted with lipopolysaccharides (38∼52 kDa in BP; 38∼60 kDa in B. thailandensis). Western blot results with the outer surface antigens of the 3 Burkholderia species were consistent with results with the whole Burkholderia cell antigens, suggesting that these immunodominant antigens reacting with the 3 cMAbs were primarily present on the outer surface of the Burkholderia species. These 3 cMAbs would be useful for analyzing the role of the major outer surface antigens in Burkholderia infection.

In Vitro and In Vivo studies of monoclonal antibodies with prominent bactericidal activity against Burkholderia pseudomallei and Burkholderia mallei.

Our laboratory has developed more than a hundred mouse monoclonal antibodies (MAbs) against Burkholderia pseudomallei and Burkholderia mallei. These antibodies have been categorized into different groups based on their specificities and the biochemical natures of their target antigens. The current study first examined the bactericidal activities of a number of these MAbs by an in vitro opsonic assay. Then, the in vivo protective efficacy of selected MAbs was evaluated using BALB/c mice challenged intranasally with a lethal dose of the bacteria. The opsonic assay using dimethyl sulfoxide-treated human HL-60 cells as phagocytes revealed that 19 out of 47 tested MAbs (40%) have prominent bactericidal activities against B. pseudomallei and/or B. mallei. Interestingly, all MAbs with strong opsonic activities are those with specificity against either the capsular polysaccharides (PS) or the lipopolysaccharides (LPS) of the bacteria. On the other hand, none of the MAbs reacting to bacterial proteins or glycoproteins showed prominent bactericidal activity. Further study revealed that the antigenic epitopes on either the capsular PS or LPS molecules were readily available for binding in intact bacteria, while the epitopes on proteins/glycoproteins were less accessible to the MAbs. Our in vivo study showed that four MAbs reactive to either the capsular PS or LPS were highly effective in protecting mice against lethal bacterial challenge. The result is compatible with that of our in vitro study. The MAbs with the highest protective efficacy are those reactive to either the capsular PS or LPS of the Burkholderia bacteria.

Relationship between antigenicity and pathogenicity for Burkholderia pseudomallei and Burkholderia mallei revealed by a large panel of mouse MAbs.

Burkholderia pseudomallei and Burkholderia mallei are two closely related gram-negative bacterial species classified by the CDC as category B biowarfare agents. To develop monoclonal antibodies (MAbs) that can recognize as many different strains and/or clinical isolates of these two pathogens as possible, we immunized mice with heat-killed bacterial whole cells and membrane preparations from multiple strains and/or clinical isolates of B. pseudomallei and B. mallei. More than 100 different hybridoma clones that produced MAbs strongly reacting to B. pseudomallei and/or B. mallei have been developed. These MAbs were categorized into eight different groups according to their reaction specificity against different species of Burkholderia bacteria as well as the different nature of target antigens (LPS, capsule polysaccharides, proteins, and glycoproteins) on the bacteria they recognized. Characterization of this large panel of MAbs has demonstrated an interesting pattern of various antigenic epitopes shared by the different species of Burkholderia bacteria. More importantly, this study has revealed a pathogenicity-linked antigen epitope(s) on capsule-like polysaccharides found only in the pathogenic species of Burkholderia bacteria and a Burkholderia-specific antigen epitope(s) that did not exist in other gram-negative bacterial species. Our MAbs should prove to be highly valuable in the development of detection, diagnosis, and therapeutic applications against B. mallei and B. pseudomallei infections.

Effects of antiarrhythmic drugs on inappropriate shocks in patients with implantable cardioverter defibrillators.

BACKGROUND: Patients with atrial fibrillation (AF) or congestive heart failure (CHF) are more vulnerable to inappropriate shocks from implantable cardioverter-defibrillators (ICDs), but the effect of antiarrhythmic drugs in these patients remains unknown. METHODS AND RESULTS: A total of 55 patients with AF and/or CHF (New York Heart Association functional class > or =III) who had ICDs were divided into 3 groups [amiodarone (n=24), sotalol (n=12), beta-blocker (n=19)] and the cumulative rates of inappropriate shocks were compared. The baseline characteristics of the 3 groups were not significantly different. The 4-year event rate of inappropriate shocks was 27.3% in the amiodarone group, 54.3% in the sotalol group, and 70.6% in the beta-blocker group (amiodarone vs beta-blocker: log-rank p=0.003; sotalol vs beta-blocker: log-rank p=0.16; amiodarone vs sotalol: log-rank p=0.29). Amiodarone reduced the risk of inappropriate shocks significantly as compared with beta-blockers (hazard ratio (HR) 0.17; 95% confidence interval (CI) 0.05-0.64; p=0.008), whereas sotalol did not (HR 0.57; 95%CI 0.19-1.68; p=0.3). Amiodarone was discontinued in 4 patients (16.7%) because of pulmonary toxicity and the dose was reduced in 4 patients (16.7%) because of a thyroid function abnormality. CONCLUSIONS: Amiodarone is more effective than sotalol or beta-blockers in preventing inappropriate ICD shocks in patients with AF or CHF, but it has a significant risk of drug-related adverse effects.