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In complex systems, it's crucial to uncover latent mechanisms and their context-dependent relationships. This is especially true in medical research, where identifying unknown cancer mechanisms and their impact on phenomena like drug resistance is vital. Directly observing these mechanisms is challenging due to measurement complexities, leading to an approach that infers latent mechanisms from observed variable distributions. Despite machine learning advancements enabling sophisticated generative models, their black-box nature complicates the interpretation of complex latent mechanisms. A promising method for understanding these mechanisms involves estimating latent factors through linear projection, though there's no assurance that inferences made under specific conditions will remain valid across contexts. We propose a novel solution, suggesting data, even from systems appearing complex, can often be explained by sparse dependencies among a few common latent factors, regardless of the situation. This simplification allows for modeling that yields significant insights across diverse fields. We demonstrate this with datasets from finance, where we capture societal trends from stock price movements, and medicine, where we uncover new insights into cancer drug resistance through gene expression analysis.
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Neoplasias , Humanos , Neoplasias/genética , Neoplasias/metabolismo , Aprendizado de Máquina , Resistencia a Medicamentos AntineoplásicosRESUMO
Anticancer chemo-immunotherapy has gained considerable attention across various scientific domains as a prospective approach for the comprehensive eradication of malignant tumors. Recent research has particularly been focused on traditional anthracycline chemo drugs, such as doxorubicin and mitoxantrone. These compounds trigger apoptosis in tumor cells and evoke immunogenic cell death (ICD). ICD is a pivotal initiator of the cancer-immunity cycle by facilitating the release of damage-associated molecular patterns (DAMPs). The resultant DAMPs released from cancer cells effectively activate the immune system, resulting in an increase in tumor-infiltrating T cells. In this study, we have innovated a co-delivery strategy involving folate-modified liposomes to deliver doxorubicin and monophosphoryl lipid A (MPLA) simultaneously to tumor tissue. The engineered liposomes exploit the overexpression of folate receptors within the tumor tissues. Delivered doxorubicin initiates ICD at the tumor cells, further enhancing the immunogenic stimulus. Additionally, MPLA helps T cell priming by activating antigen-presenting cells. This intricate interplay culminates in a synergistic effect, ultimately resulting in an augmented and potentiated anticancer chemo-immunotherapeutic liposomal treatment.
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Doxorrubicina , Morte Celular Imunogênica , Imunoterapia , Lipídeo A , Lipossomos , Receptor 4 Toll-Like , Lipossomos/química , Doxorrubicina/farmacologia , Doxorrubicina/química , Animais , Morte Celular Imunogênica/efeitos dos fármacos , Humanos , Receptor 4 Toll-Like/agonistas , Receptor 4 Toll-Like/metabolismo , Camundongos , Lipídeo A/análogos & derivados , Lipídeo A/química , Lipídeo A/farmacologia , Neoplasias/tratamento farmacológico , Neoplasias/imunologia , Neoplasias/terapia , Linhagem Celular Tumoral , Feminino , Antineoplásicos/química , Antineoplásicos/farmacologia , Ácido Fólico/químicaRESUMO
Uncovering acquired drug resistance mechanisms has garnered considerable attention as drug resistance leads to treatment failure and death in patients with cancer. Although several bioinformatics studies developed various computational methodologies to uncover the drug resistance mechanisms in cancer chemotherapy, most studies were based on individual or differential gene expression analysis. However the single gene-based analysis is not enough, because perturbations in complex molecular networks are involved in anti-cancer drug resistance mechanisms. The main goal of this study is to reveal crucial molecular interplay that plays key roles in mechanism underlying acquired gastric cancer drug resistance. To uncover the mechanism and molecular characteristics of drug resistance, we propose a novel computational strategy that identified the differentially regulated gene networks. Our method measures dissimilarity of networks based on the eigenvalues of the Laplacian matrix. Especially, our strategy determined the networks' eigenstructure based on sparse eigen loadings, thus, the only crucial features to describe the graph structure are involved in the eigenanalysis without noise disturbance. We incorporated the network biology knowledge into eigenanalysis based on the network-constrained regularization. Therefore, we can achieve a biologically reliable interpretation of the differentially regulated gene network identification. Monte Carlo simulations show the outstanding performances of the proposed methodology for differentially regulated gene network identification. We applied our strategy to gastric cancer drug-resistant-specific molecular interplays and related markers. The identified drug resistance markers are verified through the literature. Our results suggest that the suppression and/or induction of COL4A1, PXDN and TGFBI and their molecular interplays enriched in the Extracellular-related pathways may provide crucial clues to enhance the chemosensitivity of gastric cancer. The developed strategy will be a useful tool to identify phenotype-specific molecular characteristics that can provide essential clues to uncover the complex cancer mechanism.
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Resistencia a Medicamentos Antineoplásicos , Redes Reguladoras de Genes , Neoplasias Gástricas , Neoplasias Gástricas/genética , Neoplasias Gástricas/tratamento farmacológico , Humanos , Resistencia a Medicamentos Antineoplásicos/genética , Biologia Computacional/métodos , Regulação Neoplásica da Expressão Gênica , Método de Monte Carlo , Algoritmos , Perfilação da Expressão Gênica/métodos , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêuticoRESUMO
Immunogenic cell death (ICD) holds the potential for in situ tumor vaccination while concurrently eradicating tumors and stimulating adaptive immunity. Most ICD inducers, however, elicit insufficient immune responses due to negative feedback against ICD biomarkers, limited infiltration of antitumoral immune cells, and the immunosuppressive tumor micro-environment (TME). Recent findings highlight the pivotal roles of stimulators of interferon gene (STING) activation, particularly in stimulating antigen-presenting cells (APCs) and TME reprogramming, addressing ICD limitations. Herein, we introduced 'tumor phagocytosis-driven STING activation', which involves the activation of STING in APCs during the recognition of ICD-induced cancer cells. We developed a polypeptide-based nanocarrier encapsulating both doxorubicin (DOX) and diABZI STING agonist 3 (dSA3) to facilitate this hypothesis in vitro and in vivo. After systemic administration, nanoparticles predominantly accumulated in tumor tissue and significantly enhanced anticancer efficacy by activating tumor phagocytosis-driven STING activation in MC38 and TC1 tumor models. Immunological activation of APCs occurred within 12 h, subsequently leading to the activation of T cells within 7 days, observed in both the TME and spleen. Furthermore, surface modification of nanoparticles with cyclic RGD (cRGD) moieties, which actively target integrin αvß3, enhances tumor accumulation and eradication, thereby verifying the establishment of systemic immune memory. Collectively, this study proposes the concept of tumor phagocytosis-driven STING activation and its effectiveness in generating short-term and long-term immune responses.
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Background: Malnutrition is common in patients undergoing hemodialysis and is a powerful predictor of morbidity and mortality. This study aimed to investigate the effect of nutritional status on permanent catheter patency in elderly patients aged >75 years of age undergoing dialysis using tunneled dialysis catheters; Methods: Records of 383 patients whose nutritional factors and body cell mass (BCM) were measured simultaneously at the start of dialysis between 14 January 2020 and 30 September 2023, at Chungnam National University Hospital, were retrospectively reviewed. The relationships between permanent catheter patency at 180 days and BCM parameters and clinical parameters were studied using Kaplan-Meier survival curves and multivariate Cox proportional hazards analysis. Results: Age and sexual differences were significant (p ≤ 0.05), and most of the BCM parameters and BCM were not significant (p ≤ 0.05), except for intracellular water. Permanent catheter patency was superior at low controlling nutritional status (CONUT) scores (p < 0.05). After adjustment for covariates, the CONUT score remained an independent factor associated with permanent catheter-patency survival; Conclusions: CONUT scores measured before the start of dialysis are expected to play an important role in predicting the prognosis of permanent catheter-patency survival in patients aged >75 years.
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Azacitidine, a DNA methylation inhibitor, is employed for the treatment of acute myeloid leukemia (AML). However, drug resistance remains a major challenge for effective azacitidine chemotherapy, though several studies have attempted to uncover the mechanisms of azacitidine resistance. With the aim to identify the mechanisms underlying acquired azacitidine resistance in cancer cell lines, we developed a computational strategy that can identify differentially regulated gene networks between drug-sensitive and -resistant cell lines by extending the existing method, differentially coexpressed gene sets (DiffCoEx). The technique specifically focuses on cell line-specific gene network analysis. We applied our method to gene networks specific to azacitidine sensitivity and identified differentially regulated gene networks between azacitidine-sensitive and -resistant cell lines. The molecular interplay between the metallothionein gene family, C19orf33, ELF3, GRB7, IL18, NRN1, and RBM47 were identified as differentially regulated gene network in drug resistant cell lines. The biological mechanisms associated with azacitidine and AML for the markers in the identified networks were verified through the literature. Our results suggest that controlling the identified genes (e.g., the metallothionein gene family) and "cellular response"-related pathways ("cellular response to zinc ion", "cellular response to copper ion", and "cellular response to cadmium ion", where the enriched functional-related genes are MT2A, MT1F, MT1G, and MT1E) may provide crucial clues to address azacitidine resistance in patients with AML. We expect that our strategy will be a useful tool to uncover patient-specific molecular interplay that provides crucial clues for precision medicine in not only gastric cancer but also complex diseases.
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Leucemia Mieloide Aguda , Neuropeptídeos , Humanos , Azacitidina/farmacologia , Azacitidina/uso terapêutico , Redes Reguladoras de Genes , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/metabolismo , Linhagem Celular Tumoral , Metalotioneína/genética , Metalotioneína/metabolismo , Neuropeptídeos/metabolismo , Proteínas Ligadas por GPI/metabolismo , Proteínas de Ligação a RNA/genéticaRESUMO
Gastric cancer is a leading cause of cancer-related deaths globally and chemotherapy is widely accepted as the standard treatment for gastric cancer. However, drug resistance in cancer cells poses a significant obstacle to the success of chemotherapy, limiting its effectiveness in treating gastric cancer. Although many studies have been conducted to unravel the mechanisms of acquired drug resistance, the existing studies were based on abnormalities of a single gene, that is, differential gene expression (DGE) analysis. Single gene-based analysis alone is insufficient to comprehensively understand the mechanisms of drug resistance in cancer cells, because the underlying processes of the mechanism involve perturbations of the molecular interactions. To uncover the mechanism of acquired gastric cancer drug resistance, we perform for identification of differentially regulated gene networks between drug-sensitive and drug-resistant cell lines. We develop a computational strategy for identifying phenotype-specific gene networks by extending the existing method, CIdrgn, that quantifies the dissimilarity of gene networks based on comprehensive information of network structure, that is, regulatory effect between genes, structure of edge, and expression levels of genes. To enhance the efficiency of identifying differentially regulated gene networks and improve the biological relevance of our findings, we integrate additional information and incorporate knowledge of network biology, such as hubness of genes and weighted adjacency matrices. The outstanding capabilities of the developed strategy are validated through Monte Carlo simulations. By using our strategy, we uncover gene regulatory networks that specifically capture the molecular interplays distinguishing drug-sensitive and drug-resistant profiles in gastric cancer. The reliability and significance of the identified drug-sensitive and resistance-specific gene networks, as well as their related markers, are verified through literature. Our analysis for differentially regulated gene network identification has the capacity to characterize the drug-sensitive and resistance-specific molecular interplays related to mechanisms of acquired drug resistance that cannot be revealed by analysis based solely on abnormalities of a single gene, for example, DGE analysis. Through our analysis and comprehensive examination of relevant literature, we suggest that targeting the suppressors of the identified drug-resistant markers, such as the Melanoma Antigen (MAGE) family, Trefoil Factor (TFF) family, and Ras-Associated Binding 25 (RAB25), while enhancing the expression of inducers of the drug sensitivity markers [e.g., Serum Amyloid A (SAA) family], could potentially reduce drug resistance and enhance the effectiveness of chemotherapy for gastric cancer. We expect that the developed strategy will serve as a useful tool for uncovering cancer-related phenotype-specific gene regulatory networks that provide essential clues for uncovering not only drug resistance mechanisms but also complex biological systems of cancer.
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Antineoplásicos , Neoplasias Gástricas , Humanos , Neoplasias Gástricas/genética , Redes Reguladoras de Genes , Reprodutibilidade dos Testes , Antineoplásicos/uso terapêutico , Linhagem Celular , Perfilação da Expressão Gênica/métodosRESUMO
RNA-binding motif protein 10 (RBM10) is a frequently mutated tumor suppressor in lung adenocarcinoma (LUAD). Yet, it remains unknown whether cancer-derived mutant RBM10 compromises its tumor suppression function and, if so, the molecular insight of the underlying mechanisms. Here, we show that wild-type RBM10 suppresses lung cancer cell growth and proliferation by inactivating c-Myc that is essential for cancer cell survival. RBM10 directly binds to c-Myc and promotes c-Myc's ubiquitin-dependent degradation, while RBM10 knockdown leads to the induction of c-Myc level and activity. This negative action on c-Myc is further boosted by ribosomal proteins (RPs) uL18 (RPL5) and uL5 (RPL11) via their direct binding to RBM10. Cancer-derived mutant RBM10-I316F fails to bind to uL18 and uL5 and to inactivate c-Myc, thus incapable of suppressing tumorigenesis. Our findings uncover RBM10 as a pivotal c-Myc repressor by cooperating with uL18 and uL5 in lung cancer cells, as its failure to do so upon mutation favors tumorigenesis.
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Neoplasias Pulmonares , Proteínas Proto-Oncogênicas c-myc , Proteínas de Ligação a RNA , Proteínas Ribossômicas , Humanos , Carcinogênese , Proliferação de Células/genética , Transformação Celular Neoplásica , Neoplasias Pulmonares/genética , Proteínas Proto-Oncogênicas c-myc/genética , Proteínas Proto-Oncogênicas c-myc/metabolismo , Proteínas Ribossômicas/genética , Proteínas Ribossômicas/metabolismo , Motivos de Ligação ao RNA , Proteínas de Ligação a RNA/genética , Proteínas de Ligação a RNA/metabolismoRESUMO
OBJECTIVE: To establish the lower limits of normative values of the physical work capacity for Korean farmers in healthy working individual. METHODS: We developed a comprehensive set of physical work capacity evaluation items that encompass common farming tasks. These items include measurements of trunk flexion/extension angles, strength (hand grip, trunk flexion/extension, leg/back lifting, and pushing/pulling), and positional tolerances. We calculated the normative values for the items and defined the normal range in 124 healthy volunteers aged 20-79 years. We calculated the intraclass correlation coefficient (ICC) to validate the test-retest reliability of the measurements protocol. RESULTS: The normal values for each measurement item were as follows: trunk flexion and extension angle (65.3°±11.6° and 29.6°±6.6°), dominant hand grip strength (32.2±10.5 kgf), trunk flexion and extension strength (288.4±119.0 N and 297.3±129.9 N), leg and back lifting strength (452.9±233.5 N and 349.2±166.7 N), pushing and pulling strength (214.7±75.1 N and 221.7±63.3 N), and positional tolerance time (squat: 76.8±9.0 seconds, front: 73.8±7.7 seconds, twist: 82.2±8.8 seconds, upward: 71.9±11.3 seconds). Regarding test-retest reliability, all strength measurements demonstrated excellent absolute agreement (ICC, 0.91-0.96). However, positional tolerance showed poor-to-moderate absolute agreement (ICC, 0.37-0.58). CONCLUSION: We conducted measurements of muscle strength and positional tolerance in healthy participants of various ages, focusing on tasks commonly performed by Korean farmers. The outcomes hold significant value as they offer a pertinent instrument for assessing the appropriateness of workers, thereby carrying implications for rehabilitation objectives, legal evaluations, and work capacity assessments within the agricultural domain.
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This study assessed the potential of back extensor strength as an alternative marker of frailty. A total of 560 farmers were included. Computed tomography scans measured fat and muscle mass volumes at the mid-L4 vertebral level. Back extensor strength was measured in a seated posture. Multivariate linear regression was used to analyze the associations between back extensor strength and trunk muscle/fat compositions. The participants were divided into two groups based on back extensor strength. Propensity score matching, multivariate logistic regression, and Extreme Gradient Boosting (XGBoost) were employed to evaluate the relationship between Fried's frailty criteria and back extensor strength. Back extensor strength exhibited positive associations with abdominal muscle volume (r = 1.12) as well as back muscle volume (r = 0.89) (p < 0.05). Back extensor strength was linked to more frail status, such as reduced grip strength, walking speed, and frequent self-reported exhaustion. Multivariate logistic regression indicated that back extensor strength was associated with higher frail status (OR = 0.990), and XGBoost analysis identified back extensor strength as the most important predictor (gain = 0.502) for frailty. The prediction models using grip strength produced similar results (OR = 0.869, gain = 0.482). These findings suggested the potential of back extensor strength as an alternative frailty marker.
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Understanding complex disease mechanisms requires a comprehensive understanding of the gene regulatory networks, as complex diseases are often characterized by the dysregulation and dysfunction of molecular networks, rather than abnormalities in single genes. Specifically, the exploration of cell line-specific gene networks can provide essential clues for precision medicine, as this methodology can uncover molecular interplays specific to particular cell line statuses, such as drug sensitivity, cancer progression, etc. In this article, we provide a comprehensive review of computational strategies for cell line-specific gene network analysis: (1) cell line-specific gene regulatory network estimation and analysis of gene networks under varying epithelial-mesenchymal transition (EMT) statuses of cell lines; and (2) an explainable artificial intelligence approach for interpreting the estimated massive multiple EMT-status-specific gene networks. The objective of this review is to help readers grasp the concept of computational network biology, which holds significant implications for precision medicine by offering crucial clues.
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Inteligência Artificial , Transição Epitelial-Mesenquimal , Transição Epitelial-Mesenquimal/genética , Redes Reguladoras de Genes , Linhagem Celular , Biologia ComputacionalRESUMO
Biological condition-responsive gene network analysis has attracted considerable research attention because of its ability to identify pathways or gene modules involved in the underlying mechanisms of diseases. Although many condition-specific gene network identification methods have been developed, they are based on partial or incomplete gene regulatory network information, with most studies only considering the differential expression levels or correlations among genes. However, a single gene-based analysis cannot effectively identify the molecular interactions involved in the mechanisms underlying diseases, which reflect perturbations in specific molecular network functions rather than disorders of a single gene. To comprehensively identify differentially regulated gene networks, we propose a novel computational strategy called comprehensive analysis of differential gene regulatory networks (CIdrgn). Our strategy incorporates comprehensive information on the networks between genes, including the expression levels, edge structures and regulatory effects, to measure the dissimilarity among networks. We extended the proposed CIdrgn to cell line characteristic-specific gene network analysis. Monte Carlo simulations showed the effectiveness of CIdrgn for identifying differentially regulated gene networks with different network structures and scales. Moreover, condition-responsive network identification in cell line characteristic-specific gene network analyses was verified. We applied CIdrgn to identify gastric cancer and itsf chemotherapy (capecitabine and oxaliplatin) -responsive network based on the Cancer Dependency Map. The CXC family of chemokines and cadherin gene family networks were identified as gastric cancer-specific gene regulatory networks, which was verified through a literature survey. The networks of the olfactory receptor family with the ASCL1/FOS family were identified as capecitabine- and oxaliplatin sensitive -specific gene networks. We expect that the proposed CIdrgn method will be a useful tool for identifying crucial molecular interactions involved in the specific biological conditions of cancer cell lines, such as the cancer stage or acquired anticancer drug resistance.
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Neoplasias Gástricas , Humanos , Neoplasias Gástricas/tratamento farmacológico , Neoplasias Gástricas/genética , Redes Reguladoras de Genes , Capecitabina , Oxaliplatina , CaderinasRESUMO
Patients undergoing dialysis through a permanent catheter often experience infection or malfunction. However, few studies have clarified the predictors of permanent catheter patency survival in patients undergoing hemodialysis. We assessed the relationship between the parameters of body composition monitoring (BCM), determined before the initiation of dialysis, and the patency survival of the permanent catheters inserted in 179 patients who commenced hemodialysis between 14 January 2020 and 31 August 2021. The relationships between permanent catheter patency at 6 weeks and BCM parameters, laboratory tests, age, sex, comorbidities, and medications at baseline were studied using Kaplan-Meier survival curves. Permanent catheter patency was observed to be superior at high extracellular-to-intracellular (ECW/ICW) ratio (p < 0.005). After adjustment for covariates, the ECW/ICW ratio remained an independent factor associated with permanent catheter patency survival. When patients with non-patent catheters were subdivided into infection and malfunction groups, and the associations of BCM parameters were evaluated in those groups, the ECW/ICW ratio was not significantly associated with permanent catheter patency survival in the infection group (p = 0.327); instead, a significant association was found for the lean tissue index (p < 0.001). In the malfunction group, the ECW/ICW ratio remained significantly associated with permanent catheter patency survival (p < 0.001).
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Colon cancer is a significant health concern. The development of effective drug delivery systems is critical for improving treatment outcomes. In this study, we developed a drug delivery system for colon cancer treatment by embedding 6-mercaptopurine (6-MP), an anticancer drug, in a thiolated gelatin/polyethylene glycol diacrylate hydrogel (6MP-GPGel). The 6MP-GPGel continuously released 6-MP, the anticancer drug. The release rate of 6-MP was further accelerated in an acidic or glutathione environment that mimicked a tumor microenvironment. In addition, when pure 6-MP was used for treatment, cancer cells proliferated again from day 5, whereas a continuous supply of 6-MP from the 6MP-GPGel continuously suppressed the survival rate of cancer cells. In conclusion, our study demonstrates that embedding 6-MP in a hydrogel formulation can improve the efficacy of colon cancer treatment and may serve as a promising minimally invasive and localized drug delivery system for future development.
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OBJECTIVES: This study aimed to determine the agricultural ergonomic burden in Korean farmers and to analyze its correlation with musculoskeletal pain. METHODS: In total, 1001 farmers (525 females and 476 males; mean age, 59.6±7.5years) who owned or rented a farm and belonged to an agricultural cooperative unit were recruited. Ergonomic burdens were assessed using a 20-item Agricultural Work-related Ergonomic Risk Questionnaire (20 agricultural works). The presence of musculoskeletal pain (shoulder, low back, and leg/foot), Farm Stressor Inventory, subjective stress index, and agricultural workload (low, moderate, somewhat hard, or hard) were collected using structured questionnaires. RESULTS: Factor analysis of the Agricultural Work-related Ergonomic Risk Questionnaire revealed a four-factor solution: neck and upper limb, trunk and push - pull, machine and heavy lifting, and repetitive trauma. Cronbach's alpha was greater than 0.65. For 18 of the 20 items, there was a significant association with the Farm Stressor Inventory, subjective stress index, and agricultural workload. The most frequent ergonomic burdens were squatting (51.2%), highly repetitive wrist movements (53.5%), shoulder flexion at 45-90° (51.2%), and trunk flexion or twisting at≥45° (48.8%). Ergonomic burdens were significantly different in 13 items between sexes. The musculoskeletal pain was associated with increased agricultural burdens in 10 items in male farmers and 14 items in female farmers. CONCLUSION: Increased agricultural ergonomic burdens were associated with musculoskeletal pain. Ergonomic burden showed different patterns between male and female farmers, with female farmers appearing to be more affected by ergonomic burden than male farmers.
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Doenças Musculoesqueléticas , Dor Musculoesquelética , Doenças Profissionais , Humanos , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Fazendeiros , Ombro , Dor Musculoesquelética/epidemiologia , Perna (Membro) , Doenças Musculoesqueléticas/epidemiologia , Doenças Musculoesqueléticas/etiologia , Extremidade Superior , Ergonomia , Inquéritos e Questionários , República da Coreia/epidemiologia , Fatores de Risco , Doenças Profissionais/epidemiologiaRESUMO
The complex mechanisms of diseases involve the disturbance of the molecular network, rather than disorder in a single gene, implying that single gene-based analysis is insufficient to understand these mechanisms. Gene regulatory networks (GRNs) have attracted a lot of interest and various approaches have been developed for their statistical inference and gene network-based analysis. Although various computational methods have been developed, relatively little attention has been paid to incorporation of biological knowledge into the computational approaches. Furthermore, existing studies on network-based analysis perform prediction/classification of status of cell lines based on preconstructed GRNs, implying that we cannot extract prediction/classification-specific gene networks, leading to difficulty in interpretation of biological mechanisms and marker identification related to the status of cancer cell lines. We developed a novel strategy to build a GRN-based classifier, called a GRN-classifier. The proposed GRN-classifier estimates GRNs and classifies cell lines simultaneously, where the gene network is estimated to minimize error in gene network estimation and the negative log-likelihood for classifying cell lines. Thus, we can identify biological status-specific gene regulatory systems, enabling us to achieve biologically reliable interpretation of the classification. We also propose an algorithm to implement the GRN-classifier based on coordinate descent update. Monte Carlo simulations were conducted to examine performance of the GRN-classifier. Results: Our strategy provides effective results in feature selection in the classification model and edge selection in gene network estimation. The GRN-classifier also shows outstanding classification accuracy. We apply the GRN-classifier to classify cancer cell lines into anticancer drug-related status, that is, 5-fluorouracil (5-FU)-sensitive/resistant and 5-FU target/nontarget cancer cell lines. We then identified 5-FU markers based on 5-FU-related status classification-specific gene networks. The mechanisms of the identified markers were verified through literature survey. Our results suggest that the molecular interplay between MYOF and AHNAK2 may play a crucial role in drug resistance and can provide information on the chemotherapy efficiency of 5-FU. It is also suggested that suppression of the identified 5-FU markers, including MYOF/AHNAK2 and AKR1C1/AKR1C3 may improve 5-FU resistance of cancer cell lines.
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Antineoplásicos , Neoplasias Gástricas , Humanos , Redes Reguladoras de Genes , Neoplasias Gástricas/tratamento farmacológico , Neoplasias Gástricas/genética , Fluoruracila/farmacologia , Biologia Computacional/métodos , AlgoritmosRESUMO
Network biology has garnered tremendous attention in understanding complex systems of cancer, because the mechanisms underlying cancer involve the perturbations in the specific function of molecular networks, rather than a disorder of a single gene. In this article, we review the various computational tactics for gene regulatory network analysis, focused especially on personalized anti-cancer therapy. This paper covers three major topics: (1) cell line's (or patient's) cancer characteristics specific gene regulatory network estimation, which enables us to reveal molecular interplays under varying conditions of cancer characteristics of cell lines (or patient); (2) computational approaches to interpret the multitudinous and massive networks; (3) network-based application to uncover molecular mechanisms of cancer and related marker identification. We expect that this review will help readers understand personalized computational network biology that plays a significant role in precision cancer medicine.
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Biologia Computacional , Neoplasias , Humanos , Redes Reguladoras de Genes , Medicina de Precisão , Neoplasias/genética , BiomarcadoresRESUMO
In this issue of Structure, Gihaz and colleagues develop antifungal compounds targeting fungal pantothenate kinase (PanK). Through utilization of high-throughput chemical screening, along with biochemical and functional analyses and newly solved fungal PanK crystal structures, high-affinity inhibitors are produced, and invaluable insights into the mechanisms of fungal PanK are gained.
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Ensaios de Triagem em Larga Escala , Fosfotransferases (Aceptor do Grupo Álcool) , Fosfotransferases (Aceptor do Grupo Álcool)/química , FungosRESUMO
Synthesis, design, characterization, and application of carbon-based nanostructures (CBNSs) as drug carriers have attracted a great deal of interest over the past half of the century because of their promising chemical, thermal, physical, optical, mechanical, and electrical properties and their structural diversity. CBNSs are well-known in drug delivery applications due to their unique features such as easy cellular uptake, high drug loading ability, and thermal ablation. CBNSs, including carbon nanotubes, fullerenes, nanodiamond, graphene, and carbon quantum dots have been quite broadly examined for drug delivery systems. This review not only summarizes the most recent studies on developing carbon-based nanostructures for drug delivery (e.g. delivery carrier, cancer therapy and bioimaging), but also tries to deal with the challenges and opportunities resulting from the expansion in use of these materials in the realm of drug delivery. This class of nanomaterials requires advanced techniques for synthesis and surface modifications, yet a lot of critical questions such as their toxicity, biodistribution, pharmacokinetics, and fate of CBNSs in biological systems must be answered.
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Técnicas Biossensoriais , Nanoestruturas , Nanotubos de Carbono , Neoplasias , Humanos , Nanotubos de Carbono/química , Distribuição Tecidual , Técnicas Biossensoriais/métodos , Nanoestruturas/química , Sistemas de Liberação de Medicamentos/métodos , Neoplasias/tratamento farmacológicoRESUMO
Drug resistance to front-line malarial treatments represents an ongoing threat to control malaria, a vector borne infectious disease. The malarial parasite, Plasmodium falciparum has developed genetic variants, conferring resistance to the current standard therapeutic artemisinin and its derivatives commonly referred to as artemisinin-combination therapies (ACTs). Emergence of multi-drug resistance parasite genotypes is a warning of potential treatment failure, reaffirming the urgent and critical need to find and validate alternate drug targets to prevent the spread of disease. An attractive and novel drug target includes glucose-regulated protein 78 kDa (GRP78, or BiP), an essential molecular chaperone protein involved in the unfolded protein response that is upregulated in ACT treated P. falciparum parasites. We have shown that both sequence and structure are closely related to human GRP78 (hGRP78), a chaperone belonging to the HSP70 class of ATPase proteins, which is often upregulated in cellular stress responses and cancer. By screening a library of nucleoside analogues, we identified eight 'hit' compounds binding at the active site of the ATP binding domain of P. falciparum GRP78 using a high-throughput ligand soaking screen using x-ray crystallography. These compounds were further evaluated using protein thermal shift assays to assess target binding activity. The nucleoside analogues identified from our screen provide a starting point for the development of more potent and selective antimalarial inhibitors. In addition, we have established a well-defined, high-throughput crystal-based screening approach that can be applied to many crystallizable P. falciparum proteins for generating anti-Plasmodium specific compounds.