Journal of Pharmaceutical and Biomedical Analysis

Exploring the mechanism of Bruceine D against cervical cancer by network pharmacology and the effect of Bruceine D on the EGFR pathway

Cervical cancer (CC) remains a formidable challenge in oncology due to its high incidence and mortality rates. Despite recent advances in treatment, an immediate necessity exists for innovating advanced pharmacological interventions boasting augmented effectiveness. Bruceine D (BD), a quassinoid derived from the traditional Chinese medicinal plant Brucea javanica, has been demonstrated to possess notable anticancer properties against a range of malignant conditions, including lung, liver, leukemia, and pancreatic cancers. However, its specific effects on CC have not been thoroughly explored. This study sought to decode the effects of BD on CC through a combined method involving molecular docking analysis, network pharmacology, and data mining. From the PharmMapper database, we identified 58 potential targets of BD, and through GeneCards, we pinpointed 14 intersecting targets relevant to CC. A protein-protein interaction (PPI) network highlighted pivotal targets such as ESR1, HSP90AA1, ANXA5, EGFR, CASP7, and CCNA2. GO and KEGG enrichment analyses underscored significant biological processes and pathways, notably the EGFR signaling pathway. Molecular docking analysis revealed a strong binding affinity of BD to EGFR. Cell-based assays demonstrated that BD potently curtailed the viability, colony formation, adhesion, and mobility of Hela and Caski cells, escalating apoptosis in a dose-proportional manner. Supplementary evidence via western blot evaluations underscored BD's capability to obstruct the EGFR signaling pathway. These findings suggest that BD exerts potent anticancer effects against CC through multiple mechanisms, positioning it as a promising therapeutic agent for further investigation and clinical validation.

Plasma-based proteomic and metabolomic characterization of lung and lymph node metastases in cervical cancer patients

Metastasis is the leading cause of mortality in cervical cancer (CC), with a particular prevalence of lymph node and lung metastases. Patients with CC who have developed distant metastases typically face a poor prognosis, and there is a scarcity of non-invasive strategies for predicting CC metastasis. In this study, we utilized label-free proteomics and untargeted metabolomics to analyze plasma samples from 25 non-metastatic, 14 with lung metastasis, and 15 with lymph node metastasis CC patients. Pathway enrichment analysis revealed a shared inflammatory process between the two metastatic groups, while the central carbon metabolism in cancer showed distinct features in the lung metastasis cohort. Additionally, cholesterol metabolism, hypoxia-inducible factor 1, and ferroptosis signaling pathways were specifically altered in the lymph node metastasis group. Utilizing the receiver operating characteristic curve analysis and Random Forest algorithm, we identified two distinct biomarker panels for the prediction of lung metastasis and lymph node metastasis, respectively. The lung metastasis panel includes properdin, neural cell adhesion molecule 1, and keratin 6 A, whereas the lymph node metastasis panel consists of quiescin sulfhydryl oxidase 1, paraoxonase 1, and keratin 6 A. Each panel exhibited significant diagnostic potential, with high area under the curve (AUC) values for lung metastasis (training set: 0.989, testing set: 0.789) and lymph node metastasis (training set: 0.973, testing set: 0.900). This study conducted an integrated proteomic and metabolomic analysis to clarify the factors contributing to lung and lymph node metastases in CC and has successfully established two biomarker panels for their prediction.

Evaluation of transport mechanisms of methotrexate in human choriocarcinoma cell lines by LC-MS/MS

Methotrexate (MTX) is commonly prescribed as the initial treatment for gestational trophoblastic neoplasia (GTN), but MTX monotherapy may not be effective for high-risk GTN and choriocarcinoma. The cellular uptake of MTX is essential for its pharmacological activity. Thus, our study aimed to investigate the cellular pharmacokinetics and transport mechanisms of MTX in choriocarcinoma cells. For the quantification of MTX concentrations in cellular matrix, a liquid chromatography-tandem mass spectrometry method was created and confirmed initially. MTX accumulation in BeWo, JEG-3, and JAR cells was minimal. Additionally, the mRNA levels of folate receptor α (FRα) and breast cancer resistance protein (BCRP) were relatively high in the three choriocarcinoma cell lines, whereas proton-coupled folate transporter (PCFT), reduced folate carrier (RFC), and organic anion transporter (OAT) 4 were low. Furthermore, the expression of other transporters was either very low or undetectable. Notably, the application of inhibitors and small interfering RNAs (siRNAs) targeting FRα, RFC, and PCFT led to a notable decrease in the accumulation of MTX in BeWo cells. Conversely, the co-administration of multidrug resistance protein 1 (MDR1) and BCRP inhibitors increased MTX accumulation. In addition, inhibitors of OATs and organic-anion transporting polypeptides (OATPs) reduced MTX accumulation, while peptide transporter inhibitors had no effect. Results from siRNA knockdown experiments and transporter overexpression cell models indicated that MTX was not a substrate of nucleoside transporters. In conclusion, the results indicate that FRα and multiple transporters such as PCFT, RFC, OAT4, and OATPs are likely involved in the uptake of MTX, whereas MDR1 and BCRP are implicated in the efflux of MTX from choriocarcinoma cells. These results have implications for predicting transporter-mediated drug interactions and offer potential directions for further research on enhancing MTX sensitivity.

HPLC-ESI/MS-MS metabolic profiling of white pitaya fruit and cytotoxic potential against cervical cancer: Comparative studies, synergistic effects, and molecular mechanistic approaches

Natural approach became a high demand for the prevention and treatment of such diseases for their proven safety and efficacy. This study is aimed to perform comparative phytochemical analysis of white pitaya (Hylocereus undatus) peel, pulp and seed extracts via determination of total flavonoid content, phenolic content, and antioxidant capacity, coupled with HPLC-ESI/MS-MS analysis. Further, we evaluated the synergistic cytotoxic potential with Cisplatin against cervical cancer cells with investigation of underlying mechanism. The highest content of phenolics and antioxidants were found in both seed and peel extracts. The HPLC-ESI/MS-MS revealed identification of flavonoids, phenolic acids, anthocyanin glycosides, lignans, stilbenes, and coumarins. The cytotoxicity effects were evaluated by MTT assay against prostate, breast and cervical (HeLa) and Vero cell lines. The seed and peel extracts showed remarkable cytotoxic effect against all tested cell lines. Moreover, the selectivity index confirmed high selectivity of pitaya extracts to cancer cells and safety on normal cells. The combined therapy with Cisplatin effectively enhanced its efficacy and optimized the treatment outcomes, through the apoptotic ability of pitaya extracts in HeLa cells, as evaluated by flow cytometry. Besides, RT-PCR and western blotting analysis showed downregulation of Bcl-2 and overexpression of P53, BAX among HeLa cells treated with pitaya extracts, which eventually activated apoptosis process. Thus, pitaya extract could be used as adjuvant therapy with cisplatin for treatment of cervical cancer. Furthermore, in-vivo extensive studies on the seed and peel extracts, and their compounds are recommended to gain more clarification about the required dose, and side effects.

On the chemical composition of psammoma bodies microcalcifications in thyroid cancer tissues

Recently the knowledge of chemical composition of pathological mineralizations is an important topic extensively studied because it could give more in-depth information to understand pathologies themselves and to improve prevention methods. In this work, psammoma bodies (PBs) microcalcifications in thyroid cancer tissue are investigated by different and complementary analytical methods as: micro-Fourier transformed spectroscopy, X-ray fluorescence spectroscopy, Inductively Coupled plasma Optical Emission Spectroscopy (ICP-OES) and scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy imaging (EDX). For the first time the micro-FTIR analysis of the only inorganic phase isolated from PBs was reported. Signals of the recorded spectrum showed that the main component of the calcifications is the amorphous carbonated calcium phosphate, and the IR spectrum of thyroid PBs is strongly consistent with that of PBs in human ovarian tumors. The XRF and the ICP analysis detected also the presence of iron ad zinc in thyroid PBs. These results are validated by scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy imaging (EDX) carried out on tissue samples of the papillary thyroid carcinoma. By these analytical methods magnesium and sodium were detected within PBs while the presence of iron was confirmed by the Perls test. Summarizing the results of applied analytical methods, the main detected elements within the thyroid psammoma bodies are Ca, P, Mg, Na, Fe and Zn. Magnesium and sodium are found in malignant breast cancer microcalcifications, thus they seem correlated to neoplastic transformation. The Fe and Zn elements could give information about the origin of these pathological microcalcifications.

Validated LC-MS/MS method for cisplatin quantification in plasma, whole blood, and cervical cancer tissue via diethyldithiocarbamate derivatization: Clinical application in cervical cancer

The objective of this research was to establish an LC-MS/MS method with high sensitivity and selectivity for the quantification of cisplatin in human plasma, whole blood, and cervical cancer tissue samples. This approach employed diethyldithiocarbamate (DDTC) as a derivatizing agent for cisplatin, and analyte detection was conducted using the multiple reaction monitoring (MRM) mode. The method demonstrated lower limits of quantification (LLOQ) of 1 ng/mL for both plasma and tissue, while for whole blood, the LLOQ was determined to be 5 ng/mL. This method demonstrated remarkable linearity (R² >0.98), precision (coefficient of variation <15 %), accuracy (85 %-115 %), and minor matrix effects in all matrices. Stability assessments confirmed the robustness of the method under various conditions, including freeze-thaw cycles, short-term storage, and reinjection. Clinical samples from cervical cancer patients treated with intravenous 40 mg/m² cisplatin over 1 h revealed concentrations from below the LLOQ to 4250 ng/mL in plasma, 55-1673 ng/mL in whole blood, and 197-1613 ng/mL in tissue. The successful application of this method enables precise pharmacokinetic and tissue distribution studies of cisplatin, facilitating personalized dosing strategies to improve treatment outcomes for cervical cancer patients.

A reliable LC-MS/MS method for the quantification of natural amino acids in human plasma and its application in clinic

A simple and fast LC-MS/MS method was developed and validated for simultaneous quantification of 20 L-amino acids (AAs) in human plasma. Chromatographic separation was achieved on an Agilent AdvanceBio Hilic column within 15 min via gradient elution with an aqueous solution containing 5 mM ammonium formate, 5 mM ammonium acetate and 0.1 % formic acid and an organic mobile phase containing 0.1 % formic acid, 5 mM ammonium formate and 5 mM ammonium acetate acetonitrile-water (90:10, v/v) at the flow rate of 0.25 mL/min. Individual AAs and internal standard were analyzed by multiple reaction monitoring (MRM) in positive ion mode under optimized conditions. Method validation consisted of linearity, sensitivity, accuracy and precision, recovery, matrix effect, and stability, and the results demonstrated this LC-MS/MS method as a specific, accurate, and reliable assay. The method was thus utilized to compare the dynamics of individual plasma AAs between healthy females and patients with ovarian tumors. Our results revealed that, in cancer group, plasma 3-Methyl-L-Histidine, L-Proline, L-Phenylalanine and L-Lysine concentrations were significantly increased in patients with malignant ovarian tumors while L-Leucine and L-Isoleucine levels were sharply decreased. These findings support the utilities of this LC-MS/MS method and the promise of specific AAs as possible biomarkers for ovarian cancer.

Combination of plasma-based lipidomics and machine learning provides a useful diagnostic tool for ovarian cancer

Ovarian cancer (OC), the second leading cause of death among gynecological cancers, is often diagnosed at an advanced stage due to its asymptomatic nature at early stages. This study aimed to explore the diagnostic potential of plasma-based lipidomics combined with machine learning (ML) in OC. Non-targeted lipidomics analysis was conducted on plasma samples from participants with epithelial ovarian cancer (EOC), benign ovarian tumor (BOT), and healthy control (HC). The samples were randomly divided into a train set and a test set. Differential lipids between groups were selected using two-tailed Student's t-test and partial least squares discriminant analysis (PLS-DA). Both single lipid-based receiver operating characteristic (ROC) model, and multiple lipid-based ML model, were constructed to investigate the diagnostic value of the differential lipids. The results showed several lipids with significant diagnostic potential. ST 27:2;O achieved the highest prediction accuracy of 0.92 in distinguishing EOC from HC. DG 42:2 had the highest prediction accuracy of 0.96 in diagnosing BOT from HC. Cer d18:1/18:0 had the highest prediction accuracy of 0.65 in differentiating EOC from BOT. Furthermore, multiple lipid-based ML models illustrated better diagnostic performance. K-nearest neighbors (k-NN), partial least squares (PLS), and random forest (RF) models achieved the highest prediction accuracy of 0.96 in discriminating EOC from HC. The support vector machine (SVM) model reached the highest prediction accuracy both in distinguishing BOT from HC, and in differentiating EOC from BOT, with accuracies of 1.00 and 0.74, respectively. In conclusion, this study revealed that the combination of plasma-based lipidomics and ML algorithms is an effective method for diagnosing OC.

Development and validation of a sensitive LC–MS/MS method for the assay of four PARP inhibitors in human plasma and its application in ovarian cancer patients

PARP inhibitors have demonstrated marked efficacy in ovarian cancer patients with BRCA1/2 loss-of-function mutations. In this study, we established and validated a liquid chromatography-tandem mass spectrometry (LC-MS/MS) based method to simultaneously quantify the four frequently prescripted PARP inhibitors, namely niraparib, olaparib，fluzoparib, and pamiparib, in ovarian cancer. The mobile phase was 50 % methanol with 0.1 % formic acid at a flow rate of 0.3 mL/min, within 8 min run time. Four PARP inhibitors were separated on a Hypersil GOLD™ aQ C18 Polar Endcapped LC column (50 × 2.1 mm, 1.9 µm) at 35 ℃ and subjected to mass analysis using positive electro-spray ionization (ESI). The linear range of this method was 10-2000 ng/mL, 25-5000 ng/mL, and 50-10,000 ng/mL for niraparib, olaparib and fluzoparib, and pamiparib, respectively, with the correlation coefficients (r

Serum lipid profiling analysis and potential marker discovery for ovarian cancer based on liquid chromatography–Mass spectrometry

Low early diagnosis rate and unclear pathogenesis are the primary reasons for the high mortality of epithelial ovarian cancer (EOC). Lipidomics is a powerful tool for marker discovery and mechanism explanation. Hence, a ultra high-performance liquid chromatography-mass spectrometry based non-targeted lipidomics analysis was performed to acquire lipid profiling of 153 serum samples including healthy control (HC, n = 50), benign ovarian tumor (BOT, n = 41), and EOC (n = 62) to reveal lipid disturbance, then differential lipids were verified in another sample set including 187 sera. Significant lipid disturbance occurred in BOT and EOC, fatty acid, lyso-phosphatidylcholine, and lyso-phosphatidylethanolamine were observed to be increased in BOT and EOC subjects, while phosphatidylcoline, ether phosphatidylcoline (PC-O), ether phosphatidylethanolamine (PE-O), and sphingomyelin significantly decreased. Compared with BOT, PC-Os and PE-Os presented a greater reduction in EOC, and serum ceramide increased only in EOC. Moreover, potential markers consisting of 4 lipids were defined and validated for EOC diagnosis. High areas under the curve (0.854∼0.865 and 0.903∼0.923 for distinguishing EOC and early EOC from non-cancer, respectively) as well as good specificity and sensitivity were obtained. This study not only revealed the characteristics of lipid metabolism in EOC, but also provided a potential marker pattern for aiding EOC diagnosis.

Ultrasensitive and label-free electrochemical immunosensor for the detection of the ovarian cancer biomarker CA125 based on CuCo-ONSs@AuNPs nanocomposites

Integrated proteomic and lipidomic analysis revealed potential plasma biomarkers for cervical cancer

Cervical cancer (CC) remains the most prevalent malignant tumor in the female reproductive system. However, the absence of specific biomarkers and typical clinical manifestations in the early stages significantly impedes early diagnosis, prevention, and treatment efforts. Sensitive, non-invasive biomarkers are urgently necessary for the early detection of CC. This study leveraged proteomic and lipidomic analyses on plasma samples from 115 high-grade squamous intraepithelial lesion (HSIL) patients, 133 CC patients, and 88 healthy controls (CT) and develops robust models for effectively predicting CC. Proteomic profiles revealed 48 differentially abundant proteins in HSIL and CC patients, respectively, most of which were duplicated in two patient groups. HSIL displayed specific lipid accumulation in both discovery and validation cohorts. The elevated lipids were enriched in triglycerides (TG) and phosphatidylcholines (PC), while the lower lipids were enriched in fatty acids (FA). Random Forest classifier results suggest that 4 CC-specific plasma proteins [fibrinogen, complement C3 (C3), hemoglobin subunit alpha, alpha-1-antitrypsin (SERPINA1)], 2 of which were core lipid-interacted proteins (C3, SERPINA1), show predictive ability for CC in both discovery and validation cohorts (AUC 0.97 and 0.64). Our results suggest that lipid and protein perturbations exhibit differential sensitivity towards HSIL and CC and may be used as non-invasive diagnostic markers.

A validated LC-MS/MS method for determination of neuro-pharmacokinetic behavior of niraparib in brain tumor patients

Mechanisms underlying the therapeutic effects of Amygdalin in treating Cervical Cancer based on multi-omics analysis

Cervical cancer is a malignant gynecological tumor, and cancer cell metastasis remains poorly controlled despite surgery, radiotherapy, and chemotherapy. Traditional Chinese medicine, with advantages of multi-target effects and low toxicity, has emerged as an important therapeutic approach. In this study, we screened Amygdalin-related targets and cervical cancer differentially expressed genes using databases (SwissTargetPrediction, TCGA). Key modules were identified via WGCNA, and core targets (CA9 and HK2) were determined through PPI network analysis and the MCODE algorithm. Single-cell RNA sequencing further localized Amygdalin-affected cell populations. Molecular docking and molecular dynamics simulations verified the binding affinity of Amygdalin to CA9 and HK2, which were further confirmed by enzymatic activity assays. These key targets were upregulated in cervical cancer tissues, significantly correlated with patient survival, and exhibited good diagnostic value (ROC curve AUC > 0.9). Cell experiments have shown that Amygdalin inhibits the proliferation of cervical cancer HeLa and SiHa cells in a dose- and time-dependent manner, and induces cell apoptosis. Amygdalin-treated HeLa cells were arrested at the G1 phase, while Amygdalin-treated SiHa cells were arrested at the G2 phase. Finally, RNA-seq transcriptomics analysis elucidated the pathway regulation mechanisms. Collectively, this study systematically confirms that Amygdalin exerts significant anti-cervical cancer effects by targeting CA9 and HK2 to regulate multiple pathways, providing an experimental and theoretical basis for its development as a candidate drug for cervical cancer treatment.

Metal-polymer hybrid nanomaterial for impedimetric detection of human papillomavirus in cervical specimens

The human papillomavirus (HPV) is one of the main sexually transmitted pathogens that infect the anogenital epithelium and mucous membranes. HPV genotypes can be classified as high and low oncogenic risk, with infection by the former resulting in cervical cancer in approximately 100 % of the cases. In this work, we developed an ultrasensitive electrochemical biosensor for the detection and identification of different HPV genotypes. A nanostructured platform based on a matrix of polyaniline (PANI) containing gold nanoparticles (AuNps) was designed for the chemical immobilization of a DNA probe capable of recognizing different HPV types. Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and atomic force microscopy (AFM) were used to characterize the genosensor. The impedimetric responses indicate that the proposed sensor was able to detect HPV (types 6, 11, 16, 31, 33, 45, and 58) in cervical specimens (cDNA samples). We obtained different profiles of electrochemical responses for the high and low-risk HPV genotypes. By adopting a three-dimensional quantitative analysis of impedance response variables, it was possible to identify the existence of a pattern of association for samples of high oncogenic risk, which may lead to the differential diagnosis of HPV. The biosensor demonstrated an excellent analytical performance for the detection of HPV genotypes with high sensibility and selectivity. The genosensor exhibited a linear range of response in the 1 pg μL

Biogenic platinum nanoparticles using black cumin seed and their potential usage as antimicrobial and anticancer agent

Herein, the biogenic platinum nanoparticles (Pt NPs) were synthesized by using black cumin seed (Nigella sativa L.) extract as a reducing agent. The biogenic platinum nanoparticles synthesized by black cumin seed extract was characterized in detail by Transmission Electron Microscopy (TEM), UV-vis spectrophotometer, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS). According to TEM analysis, Pt nanoparticles have spherical shapes and sizes between 1-6 nm. Moreover, the biogenic Pt NPs was assessed for its cytotoxicity effect on MDA-MB-231 breast and HeLa cervical cancer lines and their antibacterial effect against selected strains of gram-positive and negative bacteria. The cytotoxicity and bacterial tests showed the effectiveness of biogenic Pt nanoparticles. Dose-dependent toxicity effects were shown in the MDA-MB-231 breast and HeLa cervical cancer lines (IC50: 36.86 μg/mL and 19.83 μg/mL, respectively). In addition, Pt NPs showed high zone diameters against gram-positive and gram-negative bacteria at concentrations of 100 and 500 μg/ml. These results contribute to the development of the pharmaceutical industry as a potential antibacterial and anticancer agent.