p27 transcriptionally coregulates cJun to drive programs of tumor progression.

p27 shifts from CDK inhibitor to oncogene when phosphorylated by PI3K effector kinases. Here, we show that p27 is a cJun coregulator, whose assembly and chromatin association is governed by p27 phosphorylation. In breast and bladder cancer cells with high p27pT157pT198 or expressing a CDK-binding defective p27pT157pT198 phosphomimetic (p27CK-DD), cJun is activated and interacts with p27, and p27/cJun complexes localize to the nucleus. p27/cJun up-regulates TGFB2 to drive metastasis in vivo. Global analysis of p27 and cJun chromatin binding and gene expression shows that cJun recruitment to many target genes is p27 dependent, increased by p27 phosphorylation, and activates programs of epithelial-mesenchymal transformation and metastasis. Finally, human breast cancers with high p27pT157 differentially express p27/cJun-regulated genes of prognostic relevance, supporting the biological significance of the work.

Learning Explainable Time-Morphology Patterns for Automatic Arrhythmia Classification from Short Single-Lead ECGs.

Automatic detection of abnormal heart rhythms, including atrial fibrillation (AF), using signals obtained from a single-lead wearable electrocardiogram (ECG) device, is useful for daily cardiac health monitoring. In this study, we propose a novel image-based deep learning framework to classify single-lead ECG recordings of short variable length into several different rhythms associated with arrhythmias. By transforming variable-length 1D ECG signals into fixed-size 2D time-morphology representations and feeding them to the beat-interval-texture convolutional neural network (BIT-CNN) model, we aimed to learn the comprehensible characteristics of beat shape and inter-beat patterns over time for arrhythmia classification. The proposed approach allows feature embedding vectors to provide interpretable time-morphology patterns focused at each step of the learning process. In addition, this method reduces the number of model parameters needed to be trained and aids visual interpretation, while maintaining similar performance to other CNN-based approaches to arrhythmia classification. For experiments, we used the PhysioNet/CinC Challenge 2017 dataset and achieved an overall F1_NAO of 81.75% and F1_NAOP of 76.87%, which are comparable to those of the state-of-the-art methods for variable-length ECGs.

Driving Stress Detection Using Multimodal Convolutional Neural Networks with Nonlinear Representation of Short-Term Physiological Signals.

Mental stress can lead to traffic accidents by reducing a driver's concentration or increasing fatigue while driving. In recent years, demand for methods to detect drivers' stress in advance to prevent dangerous situations increased. Thus, we propose a novel method for detecting driving stress using nonlinear representations of short-term (30 s or less) physiological signals for multimodal convolutional neural networks (CNNs). Specifically, from hand/foot galvanic skin response (HGSR, FGSR) and heart rate (HR) short-term input signals, first, we generate corresponding two-dimensional nonlinear representations called continuous recurrence plots (Cont-RPs). Second, from the Cont-RPs, we use multimodal CNNs to automatically extract FGSR, HGSR, and HR signal representative features that can effectively differentiate between stressed and relaxed states. Lastly, we concatenate the three extracted features into one integrated representation vector, which we feed to a fully connected layer to perform classification. For the evaluation, we use a public stress dataset collected from actual driving environments. Experimental results show that the proposed method demonstrates superior performance for 30-s signals, with an overall accuracy of 95.67%, an approximately 2.5-3% improvement compared with that of previous works. Additionally, for 10-s signals, the proposed method achieves 92.33% classification accuracy, which is similar to or better than the performance of other methods using long-term signals (over 100 s).

Inferring Genes and Biological Functions That Are Sensitive to the Severity of Toxicity Symptoms.

The effective development of new drugs relies on the identification of genes that are related to the symptoms of toxicity. Although many researchers have inferred toxicity markers, most have focused on discovering toxicity occurrence markers rather than toxicity severity markers. In this study, we aimed to identify gene markers that are relevant to both the occurrence and severity of toxicity symptoms. To identify gene markers for each of four targeted liver toxicity symptoms, we used microarray expression profiles and pathology data from 14,143 in vivo rat samples. The gene markers were found using sparse linear discriminant analysis (sLDA) in which symptom severity is used as a class label. To evaluate the inferred gene markers, we constructed regression models that predicted the severity of toxicity symptoms from gene expression profiles. Our cross-validated results revealed that our approach was more successful at finding gene markers sensitive to the aggravation of toxicity symptoms than conventional methods. Moreover, these markers were closely involved in some of the biological functions significantly related to toxicity severity in the four targeted symptoms.

Becoming an International Scientist in South Korea: Ho Wang Lee's Research Activity about Epidemic Hemorrhagic Fever.

In the 1960-70s, South Korea was still in the position of a science latecomer. Although the scientific research environment in South Korea at that time was insufficient, there was a scientist who achieved outcomes that could be recognized internationally while acting in South Korea. He was Ho Wang Lee(1928~ ) who found Hantann Virus that causes epidemic hemorrhagic fever for the first time in the world. It became a clue to identify causative viruses of hemorrhagic diseases that were scattered here and there throughout the world. In addition, these outcomes put Ho Wang Lee on the global center of research into epidemic hemorrhagic fever. This paper examines how a Korean scientist who was in the periphery of virology could go into the central area of virology. Also this article shows the process through which the virus found by Ho Wang Lee was registered with the international academia and he proceeded with follow-up research based on this progress to reach the level at which he generalized epidemic hemorrhagic fever related studies throughout the world. While he was conducting the studies, experimental methods that he had never experienced encountered him as new difficulties. He tried to solve the new difficulties faced in his changed status through devices of cooperation and connection. Ho Wang Lee's growth as a researcher can be seen as well as a view of a researcher that grew from a regional level to an international level and could advance from the area of non-mainstream into the mainstream. This analytic tool is meaningful in that it can be another method of examining the growth process of scientists in South Korea or developing countries.

An integrative model of multi-organ drug-induced toxicity prediction using gene-expression data.

BACKGROUND: In practice, some drugs produce a number of negative biological effects that can mitigate their effectiveness as a remedy. To address this issue, several studies have been performed for the prediction of drug-induced toxicity from gene-expression data, and a significant amount of work has been done on predicting limited drug-induced symptoms or single-organ toxicity. Since drugs often lead to some injuries in several organs like liver or kidney, however, it would be very useful to forecast the drug-induced injuries for multiple organs. Therefore, in this work, our aim was to develop a multi-organ toxicity prediction model using an integrative model of gene-expression data. RESULTS: To train our integrative model, we used 3708 in-vivo samples of gene-expression profiles exposed to one of 41 drugs related to 21 distinct physiological changes divided between liver and kidney (liver 11, kidney 10). Specifically, we used the gene-expression profiles to learn an ensemble classifier for each of 21 pathology prediction models. Subsequently, these classifiers were combined with weights to generate an integrative model for each pathological finding. The integrative model outputs the likeliness of presenting the trained pathology in a given test sample of gene-expression profile, called an integrative prediction score (IPS). For the evaluation of an integrative model, we estimated the prediction performance with the k-fold cross-validation. Our results demonstrate that the proposed integrative model is superior to individual pathology prediction models in predicting multi-organ drug-induced toxicities over all the targeted pathological findings. On average, the AUC of the integrative models was 88% while the AUC of individual pathology prediction models was 68%. CONCLUSIONS: Not only does this integrative model produce comparable prediction performance to existing approaches, but also it produces very stable performance overall. In addition, our approach is easily expandable to a variety of other multi-organ toxicology applications.

Promising Therapeutic Approach in Pancreatic Cancer: Metabolism-Related Genes.

Most pancreatic cancers are pancreatic ductal adenocarcinomas. This is an extremely lethal disease with poor prognosis and almost no treatment choices. Considering the profound role of the pancreas in the human body, malfunction of this organ can significantly affect quality of life. Although multiple metabolic pathways are altered in cancer cells, certain metabolic gene signatures may be critical for immunotherapy. The reprogrammed metabolism of glucose, amino acids, and lipids can nourish the tumor microenvironment (TME). Previous studies have also shown that reprogrammed metabolism influences immune responses. Tumor-infiltrating immune cells in the TME can adapt their metabolism to blunt the immune system, leading to immunosuppression and tumor progression. The identification of metabolism-related genes (MRGs) associated with immune reactions in pancreatic cancer may lead to improved treatments. This review highlights the characteristics of MRGs in pancreatic cancer and suggests that enhanced anti-cancer therapies could be used to overcome resistance to immunotherapy.

The Description and Analysis of the Complete Genome of Dermacoccus barathri FBCC-B549 Strain.

Dermacoccus barathri is the first reported pathogen within the Dermacoccus genus to cause a catheter-related bloodstream infection, which occurred in 2015. In this study, the complete genome assembly of Dermacoccus barathri was constructed, and the complete genome of Dermacoccus barathri FBCC-B549 consists of a single chromosome (3,137,745 bp) without plasmids. The constructed genome of D. barathri was compared with those of two closely related species within the Dermacoccus genus. D. barathri exhibited a pattern similar to Dermacoccus abyssi in terms of gene clusters and synteny analysis. Contrary to previous studies, biosynthetic gene cluster (BGC) analysis for predicting secondary metabolites revealed the presence of the LAP biosynthesis pathway in the complete genome of D. barathri, predicting the potential synthesis of the secondary metabolite plantazolicin. Furthermore, an analysis to investigate the potential pathogenicity of D. barathri did not reveal any antibiotic resistance genes; however, nine virulence factors were identified in the Virulence Factor Database (VFDB). According to these matching results in the VFDB, despite identifying a few factors involved in biofilm formation, further research is required to determine the actual impact of D. barathri on pathogenicity. The complete genome of D. barathri is expected to serve as a valuable resource for future studies on D. barathri, which currently lack sufficient genomic sequence information.

C-terminally phosphorylated p27 activates self-renewal driver genes to program cancer stem cell expansion, mammary hyperplasia and cancer.

In many cancers, a stem-like cell subpopulation mediates tumor initiation, dissemination and drug resistance. Here, we report that cancer stem cell (CSC) abundance is transcriptionally regulated by C-terminally phosphorylated p27 (p27pT157pT198). Mechanistically, this arises through p27 co-recruitment with STAT3/CBP to gene regulators of CSC self-renewal including MYC, the Notch ligand JAG1, and ANGPTL4. p27pTpT/STAT3 also recruits a SIN3A/HDAC1 complex to co-repress the Pyk2 inhibitor, PTPN12. Pyk2, in turn, activates STAT3, creating a feed-forward loop increasing stem-like properties in vitro and tumor-initiating stem cells in vivo. The p27-activated gene profile is over-represented in STAT3 activated human breast cancers. Furthermore, mammary transgenic expression of phosphomimetic, cyclin-CDK-binding defective p27 (p27CK-DD) increases mammary duct branching morphogenesis, yielding hyperplasia and microinvasive cancers that can metastasize to liver, further supporting a role for p27pTpT in CSC expansion. Thus, p27pTpT interacts with STAT3, driving transcriptional programs governing stem cell expansion or maintenance in normal and cancer tissues.

The Assistant and Feature of China Medical Board(CMB) in Korea in the 1950s-70s: Focusing on the Annual Reports of CMB.

This study analyzes the annual reports of CMB in order to examine CMB's assistance of Korea. CMB originally assisted medical education in China, and it turned to assist Asia with changes in the international situation. This paper examines three periods spanning from 1953 to 1980 when Korea received CMB assist. The first period was from 1953 to 1962, when Korea received help with material resources that were lacking after the Korean War. The second period was from 1963 to 1972 during which the scale of assistance further expanded. Additionally, Seoul National University began to have human resources with the necessary support for education and research with the assistance from CMB. The third period was from 1973 to 1980, when the CMB newly established the overall direction of aid, the contents of assistance for Korea also changed. Throughout this period, Korean medicine was able to lay the foundation for independence, and public health, including community medicine, came to be considered as an important aspect of society.

Method for Solving Difficulties in Rhythm Classification Caused by Few Samples and Similar Characteristics in Electrocardiograms.

A method for accurately analyzing electrocardiograms (ECGs), which are obtained from electrical signals generated by cardiac activity, is essential in heart disease diagnosis. However, rhythms are typically obtained with relatively few data samples and similar characteristics, making them difficult to classify. To solve these issues, we proposed a novel method that distinguishes a given ECG rhythm using a beat score map (BSM) image. Through the proposed method, the associations between beats and previously used features, such as the R-R interval, were considered. Rhythm classification was implemented by training a convolutional neural network model and using transfer learning with the created BSM image. As a result, the proposed method for ECG rhythms with small data samples showed significant results. It also showed good performance in differentiating atrial fibrillation (AFIB) and atrial flutter (AFL) rhythms, which are difficult to distinguish due to their similar characteristics. The performance for rhythms with a small number of samples of the proposed method is 20% better than an existing method. In addition, the performance based on the F-1 score for classifying AFIB and AFL of the proposed method is 30% better than the existing method. This study solved the previous limitations caused by small sample numbers and similar rhythms.

Overview of Solid Lipid Nanoparticles in Breast Cancer Therapy.

Lipid nanoparticles (LNPs), composed of ionized lipids, helper lipids, and cholesterol, provide general therapeutic effects by facilitating intracellular transport and avoiding endosomal compartments. LNP-based drug delivery has great potential for the development of novel gene therapies and effective vaccines. Solid lipid nanoparticles (SLNs) are derived from physiologically acceptable lipid components and remain robust at body temperature, thereby providing high structural stability and biocompatibility. By enhancing drug delivery through blood vessels, SLNs have been used to improve the efficacy of cancer treatments. Breast cancer, the most common malignancy in women, has a declining mortality rate but remains incurable. Recently, as an anticancer drug delivery system, SLNs have been widely used in breast cancer, improving the therapeutic efficacy of drugs. In this review, we discuss the latest advances of SLNs for breast cancer treatment and their potential in clinical use.

Transcriptomic Profiling Reveals Claudin 18.2 as a Diagnostic Biomarker of Ménétrier's Disease and the Role of Hedgehog Signaling in Pathogenesis.

Both Ménétrier's disease (MD) and juvenile polyposis syndrome (JPS) are rare premalignant conditions that can lead to gastric cancer development. MD is an acquired disease without known causative mutations. MD patients are characterized by an increased expression of EGF receptor (EGFR) ligand and transforming growth factor alpha (TGF-α) in the stomach. JPS is inherited in an autosomal dominant pattern and is caused by BMPR1A or SMAD4 mutations. It is characterized by multiple polyps throughout the gastrointestinal tract along with certain SMAD4 mutations that can result in gastric polyposis. Although there are many distinct clinico- endoscopic and histopathologic features that differ between the two diseases, they also share similar features that often lead to misdiagnosis. This study aimed to identify markers that can help distinguish MD from JPS and to better understand the pathogenesis of MD by comparing differential gene expression patterns. Upon examination of MD and JPS microscopically, we found almost all cases have patchy areas mimicking each other, making it difficult to make a correct diagnosis with histopathologic examination alone. Comparative analysis between MD and JPS using ingenuity pathway analysis (IPA) revealed both common and differential gene signatures. Common gene signatures included estrogen receptor signaling, integrin signaling, mTOR signaling, and others, which may be responsible for histopathologic similarities. Among differential gene signatures, we found that claudin 18 ( CLDN18 ) is upregulated in MD and confirmed that CLDN18.2 (isoform of CLDN18) protein expression is higher in MD than JPS by immunohistochemistry. Comparative analysis between MD and normal control revealed the hedgehog (Hh) signaling pathway is upregulated in MD. Treatment with a hedgehog pathway inhibitor partially rescued the histopathologic phenotypes in a MD mouse model. The current study provides valuable insight into the potential underlying mechanism of why MD and JPS show similar clinico-pathologic features. We also identified a diagnostic marker CLDN18.2 that can help distinguish MD from JPS, genetically. Furthermore, it also shows that Hh signaling plays an important role in the pathogenesis of MD and can function as a potential therapeutic target.

Potential Therapeutic Targets in Ovarian Cancer: Autophagy and Metabolism.

Ovarian cancer (OC) is characterized by high mortality rates owing to late diagnosis and resistance to chemotherapy. Autophagy and metabolism play essential roles in the pathological process of cancer and have recently been proposed as potential targets for anticancer therapies. Autophagy is responsible for the catabolic clearance of functionally misfolded proteins and plays different roles depending on the stage and type of cancer. Thus, understanding and controlling autophagy is relevant for treating cancer. Autophagy intermediates can communicate with each other by providing substrates for glucose, amino acid, and lipid metabolism. Metabolites and metabolic regulatory genes modulate autophagy and influence the immune response. Therefore, autophagy and the functional manipulation of metabolism during starvation or overnutrition are being investigated as potential therapeutic targets. This review discusses the role of autophagy and metabolism in OC and highlights effective therapeutic strategies targeting these processes.

Construction of Streptomyces coelicolor A3(2) mutants that exclusively produce NA4/NA6 intermediates of agarose metabolism through mutation induction.

NA4/NA6, an intermediate degradation product of ß-agarase, is a high value-added product with anticancer, anti-obesity, and anti-diabetic effects. Therefore, a method that enables the efficient production of NA4/NA6 would be useful from economic and medical perspectives. In this study, we aimed to generate a Streptomyces coelicolor A3(2) mutant M22-2C43 that produces NA4/NA6 as a final product; this method serves as a more efficient alternative to the enzymatic conversion of ß-agarase for the generation of these products. The M22-2C43 strain was generated through two rounds of mutagenesis and screening for increased ß-agarase activity and effective production of NA4/NA6. We assembled the complete genomes of two mutants, M22 and M22-2C43, which were identified following a two-round screening. Large and small genetic changes were found in these two mutants, including the loss of two plasmids present in wild-type S. coelicolor A3(2) and chromosome circularization of mutant M22-2C43. These findings suggest that mutant M22-2C43 can produce NA4/NA6 as a degradation product due to functional inactivation of the dagB gene through a point mutation (G474A), ultimately preventing further degradation of NA4/NA6 to NA2. To our knowledge, this is the first report of a microbial strain that can effectively produce NA4/NA6 as the main degradation product of ß-agarase, opening the door for the use of this species for the large-scale production of this valuable product.

Cellular Metabolomics Profiles Associated With Drug Chemosensitivity in AML.

BACKGROUND: Acute myeloid leukemia (AML) is a hematological malignancy with a dismal prognosis. For over four decades, AML has primarily been treated by cytarabine combined with an anthracycline. Although a significant proportion of patients achieve remission with this regimen, roughly 40% of children and 70% of adults relapse. Over 90% of patients with resistant or relapsed AML die within 3 years. Thus, relapsed and resistant disease following treatment with standard therapy are the most common clinical failures that occur in treating this disease. In this study, we evaluated the relationship between AML cell line global metabolomes and variation in chemosensitivity. METHODS: We performed global metabolomics on seven AML cell lines with varying chemosensitivity to cytarabine and the anthracycline doxorubicin (MV4.11, KG-1, HL-60, Kasumi-1, AML-193, ME1, THP-1) using ultra-high performance liquid chromatography - mass spectrometry (UHPLC-MS). Univariate and multivariate analyses were performed on the metabolite peak intensity values from UHPLC-MS using MetaboAnalyst to identify cellular metabolites associated with drug chemosensitivity. RESULTS: A total of 1,624 metabolic features were detected across the leukemic cell lines. Of these, 187 were annotated to known metabolites. With respect to doxorubicin, we observed significantly greater abundance of a carboxylic acid (1-aminocyclopropane-1-carboxylate) and several amino acids in resistant cell lines. Pathway analysis found enrichment of several amino acid biosynthesis and metabolic pathways. For cytarabine resistance, nine annotated metabolites were significantly different in resistance vs. sensitive cell lines, including D-raffinose, guanosine, inosine, guanine, aldopentose, two xenobiotics (allopurinol and 4-hydroxy-L-phenylglycine) and glucosamine/mannosamine. Pathway analysis associated these metabolites with the purine metabolic pathway. CONCLUSION: Overall, our results demonstrate that metabolomics differences contribute toward drug resistance. In addition, it could potentially identify predictive biomarkers for chemosensitivity to various anti-leukemic drugs. Our results provide opportunity to further explore these metabolites in patient samples for association with clinical response.

Alteration of Gut Microbiota After Antibiotic Exposure in Finishing Swine.

Subclinical doses of antimicrobials are commonly used in the swine industry to control infectious diseases and growth performance. Accumulating evidence suggests that swine administered with antibiotics are susceptible to disease development due to disruption of the beneficial gut microbial community, which is associated with host immune regulation, nutrient digestion, and colonization resistance against pathogens. In this study, we found that finishing swine administered with lincomycin showed gut dysbiosis and increased diarrhea incidence compared with control swine. 16S rRNA amplicon sequencing was used to analyze the gut microbiota in finishing swine administered with lincomycin. The relative abundance of detrimental microbes, such as species of Clostridium, Aerococcus, Escherichia-Shigella, and Corynebacterium was increased in the feces of lincomycin-administered finishing swine, but that of bacteria associated with fiber degradation, such as species of Treponema, Succinivibrio, Fibrobacter, and Cellulosilyticum was decreased. Moreover, administration of lincomycin significantly increased the enrichment of metabolic pathways related to pathogenicity and deficiency of polysaccharide degradation. These results suggest that lincomycin treatment could cause severe disruption of the commensal microbiota in finishing swine.

Finding the key to solving problems in the hepatitis kingdom: A Study on the Development of Hepatitis B Vaccine by Kim Chung Young in the 1960-70s.

This paper analyzes the research process of Kim Chung Yong (henceforth referred to as KIM), who presented the hepatitis B vaccine in South Korea. In South Korea, which had been called the Hepatitis Kingdom, KIM developed a vaccine material for hepatitis B. Through his research achievements, South Korea, emerged from a country ignorant of hepatitis to a country with a hepatitis B vaccine. It is not easy to achieve remarkable results in developing countries where scientific development is lagging. This environment, however, helped KIM achieve his research. This article explains that the two circumstances affected his achievement in his research. First, KIM got a chance to study in the U.S. when he was his starting as a researcher. In the 1960s, the scientific and medical education environment in Korea was still poor. KIM left for Harvard University with the support of CMB, where he was able to advance his studies. This experience was an opportunity to further enhance his research skills. Second, Korea's poor health and hygiene environment in the 1970s worked in favor of verifying the effectiveness of vaccine materials he developed. South Korea, where hepatitis B was prevalent, became a good research site to secure enough test subjects. KIM also used blood sellers to find out the effects of the vaccine material he developed. Blood sellers are people who earn their living by selling their own blood and were commonly found in Korea at that time. The situation in Korea in the 1970s with prevailing hepatitis and the presence of blood sellers played an important role in KIM's research. His research on vaccine development for hepatitis B was hard to imagine in the scientific research environment of South Korea at the time. However, it was also this context and environment of South Korea at the time that enabled his achievement of developing a hepatitis B vaccine.

Regulatory Effect of Lactobacillus brevis Bmb6 on Gut Barrier Functions in Experimental Colitis.

The integrity of gut barrier functions is closely associated with the pathogenesis of colitis. It is speculated that Lactobacillus brevis Bmb6 alleviates colitis by improving the tight junction (TJ) of the inflamed intestinal epithelial layer. In the present study, the regulatory effects of L. brevis Bmb6 on the TJ barrier to ameliorate colitis-symptoms were investigated. Preliminary screening showed that L. brevis Bmb6 exhibited strong acid and bile acid tolerance, along with antioxidants and ß-galactosidase activities. In a 14-day dextran sulfate sodium (DSS)-induced colitis mouse model, treatment with L. brevis Bmb6 significantly decreased in the disease activity index score. In addition, histological analyses showed that treatment with L. brevis Bmb6 protected the structural integrity of the intestinal epithelial layer and mucin-secreting goblet cells from DSS-induced damage, with only slight infiltration of immune cells. Interestingly, western blotting analyses showed that the expression of the TJ protein, zona occluden-1, was restored in Bmb6-treated mice, but not in DSS-induced mice. Consistently, the gene expression of inflammatory cytokines (tumor necrosis factor-α and interferon-γ) was also suppressed in the Bmb6-treated mice. Hence, our findings suggest that suppression of inflammatory conditions enhanced expression of TJ protein, ZO-1, or vice versa, contributing to a colitis-ameliorating effect in L. brevis Bmb6.

CD33_PGx6_Score Predicts Gemtuzumab Ozogamicin Response in Childhood Acute Myeloid Leukemia: A Report From the Children's Oncology Group.

PURPOSE: The US Food and Drug Administration recently announced reapproval of gemtuzumab ozogamicin (GO) for treatment of CD33-positive acute myeloid leukemia (AML), thus opening up opportunities to develop strategies for effective use of GO. In light of our recent report showing prognostic significance of CD33 splicing single nucleotide polymorphisms (SNPs), the objective of this study was to comprehensively evaluate CD33 SNPs for accurate prediction of patients with AML who are more or less likely to respond to GO. PATIENTS AND METHODS: We investigated the five new CD33 SNPs (rs2455069, rs35112940, rs61736475, rs1803254, and rs201074739) for association with CD33 leukemic cell surface expression and clinical response in pediatric patients with AML enrolled in the Children's Oncology Group AAML0531 trial. We further developed a composite CD33 pharmacogenetics (PGx) score using six CD33 SNPs (CD33_PGx6_score) for association with clinical outcome. RESULTS: Four CD33 SNPs were associated with cell surface CD33 levels and clinical response in the GO versus no-GO arms. Therefore, the CD33_PGx6_score was built using directional genotype scores for the previously reported splicing SNP and five new SNPs. Patients with a CD33_PGx6_score of 0 or higher had higher CD33 expression levels compared with patients with a score of less than 0 (P < .001). In addition, patients with a score of 0 or higher demonstrated an improved disease-free survival in the GO versus no-GO arms (62.5% ± 7.8% v 46.8% ± 8.3%, respectively; P = .008) and a reduced risk of relapse (28.3% ± 7.2% v 49.9% ± 8.4%, respectively; P < .001). No improvement from GO was observed in patients with a CD33-PGx6_score of less than 0. Consistent results were observed across the risk groups. CONCLUSION: In this study, we report a composite CD33_PGx6_score using directional genotype scores of CD33 SNPs. Once validated, our findings hold promise for use of the CD33_PGx6_score to guide efficient use of GO in patients with AML. In addition, because the CD33_PGx6_score considers SNPs with varying abundance in different ethnic groups, it has potential for global application.