Evaluation of Cytotoxic and Anti-cancer Potential of Capsaicin on Lung Cancer Cell Line: An In Vitro Investigation.

Background The leading cause of cancer-related deaths worldwide is lung cancer. Approximately 1.8 million new cases were diagnosed, and 1.6 million individuals died. Available treatment options are inefficient leading to tumour recurrence. Hence there is a need for novel therapeutic advancements in lung cancer treatment. Capsaicin, a naturally occurring protoalkaloid, was found to possess several potential benefits. Aim The aim of the study was to examine capsaicin's cytotoxic and anti-cancer effects in the lung cancer cell line (A549). Materials and methods The cell viability of lung cancer cells treated with capsaicin was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. A549 cells were treated with capsaicin at concentrations ranging from 25 to 150 µM/mL for 24 hours. Changes in cell morphology were observed using a phase-contrast microscope. Nuclear morphological alterations in the lung cancer cells were examined through acridine orange/ethidium bromide (AO/EtBr) staining and viewed under a fluorescent microscope to identify apoptotic nuclei. Gene expression analysis was performed using quantitative real-time PCR (Polymerase Chain Reaction) to evaluate the expression of apoptotic genes, transforming growth factor-beta (TGF-ß), and suppressor of mothers against decapentaplegic 2 (SMAD2). Capsaicin's anti-migratory properties were assessed using a scratch wound healing assay. Result Our study demonstrated that treating lung cancer cells with capsaicin dramatically decreased their vitality, with a statistically significant difference (p<0.05) between the treatment and control groups. In lung cancer cells, we measured the inhibitory concentration (IC-50) at 101.2µM/ml. Following treatment, the number of cells decreased, and those that remained exhibited cytoplasmic membrane blebbing and shrunk. With AO/EtBr staining, treated cells showed an increased number of apoptotic cells. The study's findings showed that after receiving capsaicin, there was a significant downregulation of TGF-ß and SMAD2. Moreover, when compared to control cells, capsaicin-treated cells' migration was markedly reduced. Through modification of the TGF-ß/SMAD2 signaling system, capsaicin therapy dramatically promotes apoptosis and inhibits migration. Conclusion In conclusion, the study's results indicate that capsaicin may have anti-tumor effects on lung cancer cells. To fully comprehend the mechanism underlying capsaicin's anticancer potential and its therapeutic application, further studies are much needed.

Discovery of small molecule inhibitors of neddylation catalyzing enzymes for anticancer therapy.

Protein neddylation, a type of post-translational modifications, involves the transfer of the ubiquitin-like protein NEDD8 to the lysine residues of a target substrate, which is catalyzed by the NEDD8 activating enzyme (E1), NEDD8 conjugating enzyme (E2), and NEDD8 ligase (E3). Cullin family proteins, core components of Cullin-RING E3 ubiquitin ligases (CRLs), are the most well-known physiological substrates of neddylation. CRLs, activated upon cullin neddylation, promote the ubiquitination of a variety of key signaling proteins for proteasome degradation, thereby regulating many critical biological functions. Abnormal activation of neddylation enzymes as well as CRLs has been frequently observed in various human cancers and is associated with poor prognosis for cancer patients. Consequently, targeting neddylation has emerged as a promising strategy for the development of novel anticancer therapeutics. This review first briefly introduces the properties of protein neddylation and its role in cancer, and then systematically summarizes all reported chemical inhibitors of the three neddylation enzymes, providing a focused, up to date, and comprehensive resource in the discovery and development of these small molecule inhibitors.

Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer.

With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated with their use has become one of the most urgent scientific and societal issues. To this end, the European Union passed the EU AI Act, proposing solution strategies that can be summarized under the umbrella term trustworthiness. In anti-cancer drug sensitivity prediction, machine learning (ML) methods are developed for application in medical decision support systems, which require an extraordinary level of trustworthiness. This review offers an overview of the ML landscape of methods for anti-cancer drug sensitivity prediction, including a brief introduction to the four major ML realms (supervised, unsupervised, semi-supervised, and reinforcement learning). In particular, we address the question to what extent trustworthiness-related properties, more specifically, interpretability and reliability, have been incorporated into anti-cancer drug sensitivity prediction methods over the previous decade. In total, we analyzed 36 papers with approaches for anti-cancer drug sensitivity prediction. Our results indicate that the need for reliability has hardly been addressed so far. Interpretability, on the other hand, has often been considered for model development. However, the concept is rather used intuitively, lacking clear definitions. Thus, we propose an easily extensible taxonomy for interpretability, unifying all prevalent connotations explicitly or implicitly used within the field.

Pycnogenol's Dual Impact: Inducing Apoptosis and Suppressing Migration via Vascular Endothelial Growth Factor/Fibroblast Growth Factor Signaling Pathways in Breast Cancer Cells.

BACKGROUND: The leading cause of cancer-related fatalities in women globally is breast cancer. Chemotherapy is one of the traditional therapies for breast cancer, even though it does not target cancer cells directly and has major side effects. As a result, the development of novel therapeutic techniques with improved safety and effectiveness is constantly required. AIM:  This study aimed to investigate the pro-apoptotic and anti-migrative effects of pycnogenol in a breast cancer cell line. METHODOLOGY:  By using the 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) method, the cell viability of breast cancer cells treated with pycnogenol was evaluated. Pycnogenol was applied to the MCF-7 cells in a range of concentrations (20-120 µg/ml) for 24 hours. A phase contrast microscope is used to evaluate changes in cell morphology. In breast cancer cells, acridine orange (AO) and ethidium bromide (EtBr) dual staining were employed to analyze the nuclear morphological alterations. A fluorescent microscope was used to see the apoptotic nuclei. A scratch wound healing assay was performed to evaluate the anti-migrative potential of pycnogenol. Gene expression analysis was performed using quantitative real-time PCR to determine the levels of proapoptotic and vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) genes mRNA expression.  Results: In our investigation, breast cancer cells treated with pycnogenol displayed a substantial reduction in cell viability and a statistically significant p<0.05 between the control and treatment groups. We observed inhibitory concentrations (IC-50) at 80 µg/mL in breast cancer cells. After treatment, fewer cells were present, and those that were there shrank and showed cytoplasmic membrane blebbing. Under AO/EtBr staining, treated cells show chromatin condensation and nuclear fragmentation. The results of this study revealed a significant downregulation of Bcl-2, VEGF/FGF, and p53 mRNA expression following treatment with pycnogenol. Furthermore, the impact of pycnogenol on cell migration decreased significantly when compared to control cells. Pycnogenol treatment significantly induces apoptosis and inhibits migration by altering the VEGF signaling pathway.  Conclusion: Overall, this study highlights the promising role of pycnogenol as a proapoptotic and antimigrative agent through the inhibition of anti-apoptotic and VEGF/FGF signaling molecules gene expression, offering new prospects for improving breast cancer treatment.

The SRC family kinase inhibitor NXP900 demonstrates potent antitumor activity in squamous cell carcinomas.

NXP900 is a selective and potent SRC family kinase (SFK) inhibitor, currently being dosed in a phase 1 clinical trial, that locks SRC in the "closed" conformation, thereby inhibiting both kinase-dependent catalytic activity and kinase-independent functions. In contrast, several multi-targeted kinase inhibitors that inhibit SRC, including dasatinib and bosutinib, bind their target in the active "open" conformation, allowing SRC and other SFKs to act as a scaffold to promote tumorigenesis through non-catalytic functions. NXP900 exhibits a unique target selectivity profile with sub-nanomolar activity against SFK members over other kinases. This results in highly potent and specific SFK pathway inhibition. Here, we demonstrate that esophageal squamous cell carcinomas and head and neck squamous cell carcinomas are exquisitely sensitive to NXP900 treatment in cell culture and in vivo, and we identify a patient population that could benefit from treatment with NXP900.

In silico-guided discovery and in vitro validation of novel sugar-tethered lysinated carbon nanotubes for targeted drug delivery of doxorubicin.

CONTEXT: Multiwalled carbon nanotubes (MWCNTs) functionalized with lysine via 1,3-dipolar cycloaddition and conjugated to galactose or mannose are potential nanocarriers that can effectively bind to the lectin receptor in MDA-MB-231 or MCF-7 breast cancer cells. In this work, a method based on molecular dynamics (MD) simulation was used to predict the interaction of these functionalized MWCNTs with doxorubicin and obtain structural evidence that allows a better understanding of the drug loading and release process. The MD simulations showed that while doxorubicin only interacted with pristine MWCNTs through π-π stacking interactions, functionalized MWCNTs were also able to establish hydrogen bonds, suggesting that the functionalized groups improve doxorubicin loading. Moreover, the elevated adsorption levels observed for functionalized nanotubes further support this enhancement in loading efficiency. MD simulations also shed light on the intratumoral pH-specific release of doxorubicin from functionalized MWCNTs, which is induced by protonation of the daunosamine moiety. The simulations show that this change in protonation leads to a lower absorption of doxorubicin to the MWCNTs. The MD studies were then experimentally validated, where functionalized MWCNTs showed improved dispersion in aqueous medium compared to pristine MWCNTs and, in agreement with the computational predictions, increased drug loading capacity. Doxorubicin-loaded functionalized MWCNTs demonstrated specific release of doxorubicin in tumor microenvironment (pH = 5.0) with negligible release in the physiological pH (pH = 7.4). Furthermore, doxorubicin-free MWNCT nanoformulations exhibited insignificant cytotoxicity. The experimental studies yielded nearly identical results to the MD studies, underlining the usefulness of the method. Our functionalized MWCNTs represent promising non-toxic nanoplatforms with enhanced aqueous dispersibility and the potential for conjugation with ligands for targeted delivery of anti-cancer drugs to breast cancer cells. METHODS: The computational model of a pristine carbon nanotube was created with the buildCstruct 1.2 Python script. The lysinated functionalized groups were added with PyMOL and VMD. The carbon nanotubes and doxorubicin molecules were parameterized using the general AMBER force field, and RESP charges were determined using Gaussian 09. Molecular dynamics simulations were carried out with the AMBER 20 software package. Adsorption levels were calculated using the water-shell function of cpptraj. Cytotoxicity was evaluated via a MTT assay using MDA-MB-231 and MCF-7 breast cancer cells. Drug uptake of doxorubicin and doxorubicin-loaded MWCNTs was measured by fluorescence microscopy.

A sensitive bioanalytical ultra-high-performance liquid chromatography-tandem mass spectrometry method for the simultaneous quantitation of lactone and carboxylate forms of topotecan in plasma and vitreous.

Topotecan (TPT) is used in the treatment of retinoblastoma, the most common malignant intraocular tumor in children. TPT undergoes pH-dependent hydrolysis of the lactone ring to the ring-opened carboxylate form, with the lactone form showing antitumor activity. A selective, and highly sensitive ultra-high-performance liquid chromatography-tandem mass spectrometry method was developed for the determination of both forms of TPT in one mobile phase composition in plasma and vitreous humor matrices. The method showed an excellent linear range of 0.375-120 ng/mL for the lactone. For the carboxylate, the linear range was from 0.75 to 120 ng/mL. The matrix effect and the recovery for the lactone ranged from 98.5% to 106.0% in both matrices, for the carboxylate form, it ranged from 94.9% to 101.2%. The dynamics of the transition between TPT lactone and TPT carboxylate were evaluated at different pH environments. The stability of TPT forms was assessed in plasma and vitreous humor at 8 and 37°C and a very fast conversion of lactone to carboxylate form occurred at 37°C in both matrices. The method developed facilitates the investigation of TPT pharmacodynamics and the release kinetics in the development of the innovative local drug delivery systems.

HDAC9 and miR-512 Regulate CAGE-Promoted Anti-Cancer Drug Resistance and Cellular Proliferation.

Histone deacetylase 9 (HDAC9) is known to be upregulated in various cancers. Cancer-associated antigens (CAGEs) are cancer/testis antigens that play an important role in anti-cancer drug resistance. This study aimed to investigate the relationship between CAGEs and HDAC9 in relation to anti-cancer drug resistance. AGSR cells with an anti-cancer drug-resistant phenotype showed higher levels of CAGEs and HDAC9 than normal AGS cells. CAGEs regulated the expression of HDAC9 in AGS and AGSR cells. CAGEs directly regulated the expression of HDAC9. Rapamycin, an inducer of autophagy, increased HDAC9 expression in AGS, whereas chloroquine decreased HDAC9 expression in AGSR cells. The downregulation of HDAC9 decreased the autophagic flux, invasion, migration, and tumor spheroid formation potential in AGSR cells. The TargetScan analysis predicted that miR-512 was a negative regulator of HDAC9. An miR-512 mimic decreased expression levels of CAGEs and HDAC9. The miR-512 mimic also decreased the autophagic flux, invasion, migration, and tumor spheroid forming potential of AGSR cells. The culture medium of AGSR increased the expression of HDAC9 and autophagic flux in AGS. A human recombinant CAGE protein increased HDAC9 expression in AGS cells. AGSR cells displayed higher tumorigenic potential than AGS cells. Altogether, our results show that CAGE-HDAC9-miR-512 can regulate anti-cancer drug resistance, cellular proliferation, and autophagic flux. Our results can contribute to the understanding of the molecular roles of HDAC9 in anti-cancer drug resistance.

Natural compound Alternol exerts a broad anti-cancer spectrum and a superior therapeutic safety index in vivo.

Introduction: Alternol is a natural compound isolated from the fermentation of a mutated fungus. We have demonstrated its potent anti-cancer effect via the accumulation of radical oxygen species (ROS) in prostate cancer cells in vitro and in vivo. In this study, we tested its anti-cancer spectrum in multiple platforms. Methods: We first tested its anti-cancer spectrum using the National Cancer Institute-60 (NCI-60) screening, a protein quantitation-based assay. CellTiter-Glo screening was utilized for ovarian cancer cell lines. Cell cycle distribution was analyzed using flow cytometry. Xenograft models in nude mice were used to assess anti-cancer effect. Healthy mice were tested for the acuate systemic toxicity. Results: Our results showed that Alternol exerted a potent anti-cancer effect on 50 (83%) cancer cell lines with a GI50 less than 5 µM and induced a lethal response in 12 (24%) of those 50 responding cell lines at 10 µM concentration. Consistently, Alternol displayed a similar anti-cancer effect on 14 ovarian cancer cell lines in an ATP quantitation-based assay. Most interestingly, Alternol showed an excellent safety profile with a maximum tolerance dose (MTD) at 665 mg/kg bodyweight in mice. Its therapeutic index was calculated as 13.3 based on the effective tumor-suppressing doses from HeLa and PC-3 cell-derived xenograft models. Conclusion: Taken together, Alternol has a broad anti-cancer spectrum with a safe therapeutic index in vivo.

Sulfoxide-containing polymers conjugated prodrug micelles with enhanced anticancer activity and reduced intestinal toxicity.

Poly(ethylene glycol) (PEG) is widely utilized as a hydrophilic coating to extend the circulation time and improve the tumor accumulation of polymeric micelles. Nonetheless, PEGylated micelles often activate complement proteins, leading to accelerated blood clearance and negatively impacting drug efficacy and safety. Here, we have crafted amphiphilic block copolymers that merge hydrophilic sulfoxide-containing polymers (psulfoxides) with the hydrophobic drug 7-ethyl-10-hydroxylcamptothecin (SN38) into drug-conjugate micelles. Our findings show that the specific variant, PMSEA-PSN38 micelles, remarkably reduce protein fouling, prolong blood circulation, and improve intratumoral accumulation, culminating in significantly increased anti-cancer efficacy compared with PEG-PSN38 counterpart. Additionally, PMSEA-PSN38 micelles effectively inhibit complement activation, mitigate leukocyte uptake, and attenuate hyperactivation of inflammatory cells, diminishing their ability to stimulate tumor metastasis and cause inflammation. As a result, PMSEA-PSN38 micelles show exceptional promise in the realm of anti-metastasis and significantly abate SN38-induced intestinal toxicity. This study underscores the promising role of psulfoxides as viable PEG substitutes in the design of polymeric micelles for efficacious anti-cancer drug delivery.

Self-Immolative Domino Dendrimers as Anticancer-Drug Delivery Systems: A Review.

Worldwide cancer statistics have indicated about 20 million new cancer cases and over 10 million deaths in 2022 (according to data from the International Agency for Research on Cancer). One of the leading cancer treatment strategies is chemotherapy, using innovative drug delivery systems (DDSs). Self-immolative domino dendrimers (SIDendr) for triggered anti-cancer drugs appear to be a promising type of DDSs. The present review provides an up-to-date survey on the contemporary advancements in the field of SIDendr-based anti-cancer drug delivery systems (SIDendr-ac-DDSs) through an exhaustive analysis of the discovery and application of these materials in improving the pharmacological effectiveness of both novel and old drugs. In addition, this article discusses the designing, chemical structure, and targeting techniques, as well as the properties, of several SIDendr-based DDSs. Approaches for this type of targeted DDSs for anti-cancer drug release under a range of stimuli are also explored.

Statins as anti-tumor agents: A paradigm for repurposed drugs.

BACKGROUND: Statins, frequently prescribed medications, work by inhibiting the rate-limiting enzyme HMG-CoA reductase (HMGCR) in the mevalonate pathway to reduce cholesterol levels. Due to their multifaceted benefits, statins are being adapted for use as cost-efficient, safe and effective anti-cancer treatments. Several studies have shown that specific types of cancer are responsive to statin medications since they rely on the mevalonate pathway for their growth and survival. RECENT FINDINGS: Statin are a class of drugs known for their potent inhibition of cholesterol production and are typically prescribed to treat high cholesterol levels. Nevertheless, there is growing interest in repurposing statins for the treatment of malignant neoplastic diseases, often in conjunction with chemotherapy and radiotherapy. The mechanism behind statin treatment includes targeting apoptosis through the BCL2 signaling pathway, regulating the cell cycle via the p53-YAP axis, and imparting epigenetic modulations by altering methylation patterns on CpG islands and histone acetylation by downregulating DNMTs and HDACs respectively. Notably, some studies have suggested a potential chemo-preventive effect, as decreased occurrence of tumor relapse and enhanced survival rate were reported in patients undergoing long-term statin therapy. However, the definitive endorsement of statin usage in cancer therapy hinges on population based clinical studies with larger patient cohorts and extended follow-up periods. CONCLUSIONS: The potential of anti-cancer properties of statins seems to reach beyond their influence on cholesterol production. Further investigations are necessary to uncover their effects on cancer promoting signaling pathways. Given their distinct attributes, statins might emerge as promising contenders in the fight against tumorigenesis, as they appear to enhance the efficacy and address the limitations of conventional cancer treatments.

Treatment Strategies for Non-Small-Cell Lung Cancer with Comorbid Respiratory Disease; Interstitial Pneumonia, Chronic Obstructive Pulmonary Disease, and Tuberculosis.

Non-small cell lung cancer (NSCLC) patients are often complicated by other respiratory diseases, including interstitial pneumonia (IP), chronic obstructive pulmonary disease (COPD), and pulmonary tuberculosis (TB), and the management of which can be problematic. NSCLC patients with IP sometimes develop fatal acute exacerbation induced by pharmacotherapy, and the establishment of a safe treatment strategy is desirable. For advanced NSCLC with IP, carboplatin plus nanoparticle albumin-bound paclitaxel is a relatively safe and effective first-line treatment option. Although the safety of immune checkpoint inhibitors (ICIs) for these populations remains controversial, ICIs have the potential to provide long-term survival. The severity of COPD is an important prognostic factor in NSCLC patients. Although COPD complications do not necessarily limit treatment options, it is important to select drugs with fewer side effects on the heart and blood vessels as well as the lungs. Active TB is complicated by 2-5% of NSCLC cases during their disease course. Since pharmacotherapy, especially ICIs, reportedly induces the development of TB, the possibility of developing TB should always be kept in mind during NSCLC treatment. To date, there is no coherent review article on NSCLC with these pulmonary complications. This review article summarizes the current evidence and discusses future prospects for treatment strategies for NSCLC patients complicated with IP, severe COPD, and TB.

Defeating MYC with drug combinations or dual-targeting drugs.

Members of the MYC family of proteins are a major target for cancer drug discovery, but the development of drugs that block MYC-driven cancers has not yet been successful. Approaches to achieve success may include the development of combination therapies or dual-acting drugs that target MYC at multiple nodes. Such treatments hold the possibility of additive or synergistic activity, potentially reducing side effect profiles and the emergence of resistance. In this review, we examine the prominent MYC-related targets and highlight those that have been targeted in combination and/or dual-target approaches. Finally, we explore the challenges of combination and dual-target approaches from a drug development perspective.

Prediction of anti-cancer drug synergy based on cross-matching network and cancer molecular subtypes.

At present, anti-cancer drug synergy therapy is one of the most important methods to overcome drug resistance and reduce drug toxicity in cancer treatment. High-throughput screening through deep learning can effectively improve the efficiency of discovering synergistic drugs. Nowadays, most of the existing deep learning algorithms for anti-cancer drug synergy prediction use deep neural networks and can only implicitly perform feature interaction. This study proposes a deep learning algorithm, named MolCross, which combines implicit feature interaction with explicit features to improve the accuracy of prediction of the anti-cancer drug synergy score. MolCross uses a deep autoencoder to extract features from high-dimensional input, uses the drug-specific subnetworks and cross-network to perform implicit feature interaction and explicit feature interaction respectively, and finally uses a synergy prediction network to combine the two feature interaction methods to obtain the final prediction results. We adopted a five-fold cross validation and compared MolCross with other four anti-cancer drug synergy prediction models. The results show that MolCross has better prediction performance than other models. MolCross also has good performance in terms of cross-cell line and cross-tissue type. Existing studies have demonstrated that cancer molecular subtypes have different sensitivities to targeted therapy. In this study, the features of cancer molecular subtype were introduced in the model using an embedding layer in MolCross to explore the effect of cancer molecular subtype on anti-cancer drug synergy. We also found that the cancer molecular subtype is one of the main factors affecting the synergy between drugs.

An inexpensive "do-it-yourself" device for rapid generation of uniform tumor spheroids.

Three-dimensional (3D) cancer cell culture models such as tumor spheroids better recapitulate in vivo tumors than conventional two-dimensional (2D) models. However, two major challenges limit the routine use of 3D tumor spheroids. Firstly, most existing methods of generating tumor spheroids are not high-throughput. Secondly, tumor spheroids generated using current methods are highly variable in dimension. Here, we describe a simple 'Do-It-Yourself (DIY)' device that can be assembled for less than $7 of parts and generate uniform tumor spheroids in a high-throughput manner. We used a simple phone coin vibrating motor to superimpose the vibration for breaking a laminar jet of cell-loaded alginate solution into equally sized spherical beads. We generated 3,970 tumor spheroids/min, which exhibited a hypoxic core recapitulating in vivo tumors and could be used to test the diffusion efficacy of anticancer drugs. Such low-cost, easy-to-fabricate, simple-to-operate systems with high-throughput outcomes are essential to democratize and standardize cancer research.

[Evaluation of Contractile Function Using Human iPS Cell-derived Cardiomyocytes].

Cardiotoxicity induced by anti-cancer drugs is a significant concern for patients undergoing cancer treatment. Some anti-cancer drugs can damage cardiac muscle cells directly or indirectly, potentially leading to severe heart failure. Various risk factors, including the type and dosage of chemotherapy agents as well as patient background, contribute to the development of cardiotoxicity. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), which enable patient-specific toxicity prediction, hold great promise in this regard. However, the practical implementation of hiPSC-CMs-based prediction of anti-cancer drug-induced cardiotoxicity still faces hurdles. One major challenge involves establishing and optimizing experimental systems for evaluating contractile dysfunction, the ultimate output of heart failure, using hiPSC-CMs. Such efforts are currently underway globally, focusing on tailoring functional evaluation systems to the characteristics of hiPSC-CMs. In this paper, we provide an overview of the contraction mechanisms of cardiac cells and introduce a method of measuring contraction that we have developed, and discuss the current status of contractile function evaluation methods using hiPSC-CMs.

Differential Gene Regulatory Network Analysis between Azacitidine-Sensitive and -Resistant Cell Lines.

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.

The High Stability and Selectivity of Electrochemical Sensor Using Low-Cost Diamond Nanoparticles for the Detection of Anti-Cancer Drug Flutamide in Environmental Samples.

In this study, a novel electrochemical sensor was created by fabricating a screen-printed carbon electrode with diamond nanoparticles (DNPs/SPCE). The successful development of the sensor enabled the specific detection of the anti-cancer drug flutamide (FLT). The DNPs/SPCE demonstrated excellent conductivity, remarkable electrocatalytic activity, and swift electron transfer, all of which contribute to the advantageous monitoring of FLT. These qualities are critical for monitoring FLT levels in environmental samples. Various structural and morphological characterization techniques were employed to validate the formation of the DNPs. Remarkably, the electrochemical sensor demonstrated a wide linear response range (0.025 to 606.65 µM). Additionally, it showed a low limit of detection (0.023 µM) and high sensitivity (0.403 µA µM-1 cm-2). Furthermore, the practicability of DNPs/SPCE can be successfully employed in FLT monitoring in water bodies (pond water and river water samples) with satisfactory recoveries.