Plasma metabolomics of immune-related adverse events for patients with lung cancer treated with PD-1/PD-L1 inhibitors.

BACKGROUND: Metabolomics has the characteristics of terminal effects and reflects the physiological state of biological diseases more directly. Several current biomarkers of multiple omics were revealed to be associated with immune-related adverse events (irAEs) occurrence. However, there is a lack of reliable metabolic biomarkers to predict irAEs. This study aims to explore the potential metabolic biomarkers to predict risk of irAEs and to investigate the association of plasma metabolites level with survival in patients with lung cancer receiving PD-1/PD-L1 inhibitor treatment. METHODS: The study collected 170 plasmas of 85 patients with lung cancer who received immune checkpoint inhibitors (ICIs) treatment. 58 plasma samples of 29 patients with irAEs were collected before ICIs treatment and at the onset of irAEs. 112 plasma samples of 56 patients who did not develop irAEs were collected before ICIs treatment and plasma matched by treatment cycles to onset of irAEs patients. Untargeted metabolomics analysis was used to identify the differential metabolites before initiating ICIs treatment and during the process that development of irAEs. Kaplan-Meier curves analysis was used to detect the associations of plasma metabolites level with survival of patients with lung cancer. RESULTS: A total of 24 differential metabolites were identified to predict the occurrence of irAEs. Baseline acylcarnitines and steroids levels are significantly higher in patients with irAEs, and the model of eight acylcarnitine and six steroid metabolites baseline level predicts irAEs occurrence with area under the curve of 0.91. Patients with lower concentration of baseline decenoylcarnitine(AcCa(10:1) 2, decenoylcarnitine(AcCa(10:1) 3 and hexanoylcarnitine(AcCa(6:0) in plasma would have better overall survival (OS). Moreover, 52 differential metabolites were identified related to irAEs during ICIs treatment, dehydroepiandrosterone sulfate, corticoserone, cortisol, thyroxine and sphinganine 1-phaosphate were significantly decreased in irAEs group while oxoglutaric acid and taurocholic acid were significantly increased in irAEs group. CONCLUSIONS: High levels of acylcarnitines and steroid hormone metabolites might be risk factor to development of irAEs, and levels of decenoylcarnitine (AcCa(10:1) 2, decenoylcarnitine (AcCa(10:1) 3 and hexanoylcarnitine (AcCa(6:0) could be used to predict OS for patients with lung cancer received ICIs treatment.

Clinical significance and biological function of interferon regulatory factor 1 in non-small cell lung cancer.

The clinical application and biological function of interferon regulatory factor 1 (IRF1) in non-small cell lung cancer (NSCLC) patients undergoing chemoimmunotherapy remain elusive. The aim of this study was to investigate the predictive and prognostic significance of IRF1 in NSCLC patients. We employed the cBioPortal database to predict frequency changes in IRF1 and explore its target genes. Bioinformatic methods were utilized to analyze the relationship between IRF1 and immune regulatory factors. Retrospective analysis of clinical samples was conducted to assess the predictive and prognostic value of IRF1 in chemoimmunotherapy. Additionally, A549 cells with varying IRF1 expression levels were constructed to investigate its effects on NSCLC cells, while animal experiments were performed to study the role of IRF1 in vivo. Our findings revealed that the primary mutation of IRF1 is deep deletion and it exhibits a close association with immune regulatory factors. KRAS and TP53 are among the target genes of IRF1, with interferon and IL-2 being the predominantly affected pathways. Clinically, IRF1 levels significantly correlate with the efficacy of chemoimmunotherapy. Patients with high IRF1 levels exhibited a median progression-free survival (mPFS) of 9.5 months, whereas those with low IRF1 levels had a shorter mPFS of 5.8 months. IRF1 levels positively correlate with PD-L1 distribution and circulating IL-2 levels. IL-2 enhances the biological function of IRF1 and recapitulates its role in vivo in the knockdown group. Therefore, IRF1 may possess predictive and prognostic value for chemoimmunotherapy in NSCLC patients through the regulation of the IL-2 inflammatory pathway.

Association of variations in the CAT and prognosis in lung cancer patients with platinum-based chemotherapy.

PURPOSE: To explore the relationship between ATM, ATR and CAT polymorphisms and prognosis of lung cancer patients received platinum-based chemotherapy. METHODS: 404 patients with lung cancer who received platinum-chemotherapy were enrolled and DNA typing was performed. Cox regression analysis and stratification analyses was performed to assess relationships between OS and PFS with SNPs genotypes. The prognosis of lung adenocarcinomaand squamous cell carcinomapatients was analyzed with The Cancer Genome Atlas (TCGA) database according to the grouping of CAT expression. RESULTS: CAT rs769217 was significantly related to PFS of patients with lung cancer who received platinum-chemotherapy. In the Additive model, rs769217 was associated with PFS (HR = 0.747, 95% CI = 0.581-0.960, p = 0.023). In the Dominant model, CT and TT genotypes led to lung cancer progression 0.738 times more than CC genotype. In stratification analyses of association between CAT rs769217 polymorphisms and PFS, the HR of patients at stage IV in additive model was 0.73, and HR was 0.745 (p = 0.034) in dominant model. For OS analyses, HR was 0.672 in the older lung cancer patients (>55 years old) in additive model. Meanwhile, in the Dominant model, it was found that the older patients with CT and TT genotypes had better prognosis, and the risk of death after receiving platinum-based chemotherapy was 0.692 times that of patients with CC genotype (p = 0.037). TCGA data shows that LUAD patients with high CAT expression have longer OS (p = 0.020). CONCLUSION: CAT rs769217 is significantly related to PSF of platinum-based chemotherapy in lung cancer patients and may be a biomarker for predicting the prognosis of lung cancer patients with platinum-based chemotherapy.

Risk investigation of in-stent restenosis after initial implantation of intracoronary drug-eluting stent in patients with coronary heart disease.

Objective: To analyze the risk factors of in-stent restenosis (ISR) after the first implantation of drug-eluting stent (DES) patients with coronary heart disease (CHD) and to establish a nomogram model to predict the risk of ISR. Methods: This study retrospectively analyzed the clinical data of patients with CHD who underwent DES treatment for the first time at the Fourth Affiliated Hospital of Zhejiang University School of Medicine from January 2016 to June 2020. Patients were divided into an ISR group and a non-ISR (N-ISR) group according to the results of coronary angiography. The least absolute shrinkage and selection operator (LASSO) regression analysis was performed on the clinical variables to screen out the characteristic variables. Then we constructed the nomogram prediction model using conditional multivariate logistic regression analysis combined with the clinical variables selected in the LASSO regression analysis. Finally, the decision curve analysis, clinical impact curve, area under the receiver operating characteristic curve, and calibration curve were used to evaluate the nomogram prediction model's clinical applicability, validity, discrimination, and consistency. And we double-validate the prediction model using ten-fold cross-validation and bootstrap validation. Results: In this study, hypertension, HbA1c, mean stent diameter, total stent length, thyroxine, and fibrinogen were all predictive factors for ISR. We successfully constructed a nomogram prediction model using these variables to quantify the risk of ISR. The AUC value of the nomogram prediction model was 0.806 (95%CI: 0.739-0.873), indicating that the model had a good discriminative ability for ISR. The high quality of the calibration curve of the model demonstrated the strong consistency of the model. Moreover, the DCA and CIC curve showed the model's high clinical applicability and effectiveness. Conclusions: Hypertension, HbA1c, mean stent diameter, total stent length, thyroxine, and fibrinogen are important predictors for ISR. The nomogram prediction model can better identify the high-risk population of ISR and provide practical decision-making information for the follow-up intervention in the high-risk population.

Pharmacogenomics-a New Frontier for Individualized Treatment of Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disease with a significant public health burden. It is characterized by the gradual degeneration of dopamine neurons in the central nervous system. Although symptomatic pharmacological management remains the primary therapeutic method for PD, clinical experience reveals significant inter-individual heterogeneity in treatment effectiveness and adverse medication responses. The mechanisms behind the observed interindividual variability may be elucidated by investigating the role of genetic variation in human-to-human variances in medication responses and adverse effects. OBJECTIVE: This review aims to explore the impact of gene polymorphism on the efficacy of antiparkinsonian drugs. The identification of factors associated with treatment effectiveness variability might assist the creation of a more tailored pharmacological therapy with higher efficacy, fewer side outcomes, and cheaper costs. METHODS: In this review, we conducted a thorough search in databases such as PubMed, Web of Science, and Google Scholar, and critically examined current discoveries on Parkinson's disease pharmacogenetics. The ethnicity of the individuals, research methodologies, and potential bias of these studies were thoroughly compared, with the primary focus on consistent conclusions. RESULTS: This review provides a summary of the existing data on PD pharmacogenetics, identifies its limitations, and offers insights that may be beneficial for future research. Previous studies have investigated the impact of gene polymorphism on the effectiveness and adverse effects of levodopa. The trendiest genes are the COMT gene, DAT gene, and DRD2 gene. However, limited study on other anti-Parkinson's drugs has been conducted. CONCLUSION: Therefore, In order to develop an individualized precision treatment for PD, it is an inevitable trend to carry out multi-center, prospective, randomized controlled clinical trials of PD pharmacogenomics covering common clinical anti-PD drugs in large, homogeneous cohorts.

Association of variations in the Fanconi anemia complementation group and prognosis in Non-small cell lung cancer patients with Platinum-based chemotherapy.

PURPOSE: To explore the associations between FANC (FANCA, FANCC, FANCE, FANCF, and FANCJ) single nucleotide polymorphisms (SNPs) and prognosis of non-small cell lung cancer (NSCLC) patients with platinum-based chemotherapy. METHODS: According to the inclusion criteria, we selected 395 DNA samples from NSCLC patients for genotyping and combined with clinical data for Cox regression analysis and stratification analyses to assess relationships between overall survival (OS) and progression free survival (PFS) with SNPs genotypes. RESULTS: The results revealed that patients with FANCE rs6907678 TT genotype have a longer OS than TC and CC genotype (Additive model: P = 0.004, HR = 1.696, 95% CI = 1.186-2.425). In stratification analyses, Longer PFS is found in female, age ≤ 55 years old and non-smoking patients with FANCE rs6907678 TT genotype, and patients with TT genotypes were significantly had longer OS in male, age ＞55 years old, non-smoking, squamous cell carcinoma and stage IV stratification. CONCLUSION: Our data demonstrates that patients with FANCE rs6907678 TT genotype are contributed to better prognosis. FANCE rs6907678 may be used as a clinical biomarker for predicting the prognosis of NSCLC patients with platinum-based chemotherapy.

7-O-geranylquercetin contributes to reverse P-gp-mediated adriamycin resistance in breast cancer.

AIMS: To investigate the effect of 7-O-geranylquercetin (GQ), a derivative of quercetin (Q), on reversing drug resistance in breast cancer MCF-7/ADR cells and reveal the mechanisms related to P-glycoprotein (P-gp). MAIN METHODS: Cell viability was determined by MTT assay. Accumulation of adriamycin (ADR) in cells was determined by confocal fluorescence microscope and microplate reader while that of rhodamine (Rh) was measured by flow cytometry. Expression levels of P-gp and MDR1 gene in cells were detected by western blot and Real-Time PCR, respectively. Molecular docking of GQ and Q with P-gp was conducted using AutoDock program. Xenograft model was established by inoculating MCF-7/ADR cells in BALB/c-nude mice. Tumor bearing mice were administered with ADR via tail vein injection and/or GQ (Q) by gavage. Expression levels of P-gp in tissues were detected by western blot and immunohistochemistry. KEY FINDINGS: GQ could reverse drug resistance of MCF-7/ADR cells to ADR. GQ inhibited the efflux of ADR by down-regulating the expression of P-gp protein and its encoding gene MDR1 in MCF-7/ADR cells. Molecular modeling showed that GQ matched with P-gp better than Q. GQ enhanced the antitumor effects of ADR and decreased the expression of P-gp in mice and its activities were higher than that of Q. GQ could reverse drug resistance of MCF-7/ADR cells by down-regulating the expression of P-gp in vitro and in vivo. SIGNIFICANCES: The reversal effect of GQ on P-gp-mediated drug resistance indicates its potential as a reversal agent for drug resistance in cancer chemotherapy.

Synergistic effects of 7-O-geranylquercetin and siRNAs on the treatment of human breast cancer.

AIMS: To investigate the antitumor effect of 7-O-geranylquercetin (GQ) combining with survivin siRNA (siSuvi) or IL-10 siRNA (siIL-10) to breast cancer. MAIN METHODS: Xenograft tumor model was established by subcutaneously inoculating human breast cancer MCF-7 cells in BALB/c nude mice. Transfection efficiency of siRNA mediated by cationic liposome CDO14 in MCF-7 cells and tumor bearing mice was measured by flow cytometer and living imaging sysytem, respectively. Cell viability was detected using CCK-8 assay. Cell apoptosis was determined by Hoechst33342 staining and AV-PI staining. Tumors bearing mice were administered with GQ by gavage, and/or with liposome CDO14 mediated siRNAs via tail intravenous injection. Expression levels of proteins and cytokines were detected by western blot and ELISA, respectively. KEY FINDINGS: Liposome CDO14 could deliver siRNA to tumor effectively. Combination of GQ and siSuvi promoted the antiproliferation and pro-apoptosis effects of GQ or siSuvi to MCF-7 cells, and reduced the level of survivin and raised the level of caspase-7 in cells. GQ combining with siSuvi inhibited the growth of tumor, down-regulated the expression of survivin and up-regulated the expression of caspase-7 in tumor tissue. Similarly, GQ combining with siIL-10 inhibited the growth of tumor, decreased the level of IL-10 and increased the level of TNF-α. These results revealed that GQ enhanced the pro-apoptosis effect of siSuvi on tumor cells and the modulating effect of siIL-10 on tumor microenvironment. SIGNIFICANCES: Synergistic anti-tumor effect of GQ and siRNAs against breast cancer proved that chemical drugs combining with siRNAs is a promising antitumor strategy.

Fabrication and Optimization of High Aspect Ratio Through-Silicon-Vias Electroplating for 3D Inductor.

In this study, the filling process of high aspect ratio through-silicon-vias (TSVs) under dense conditions using the electroplating method was efficiently achieved and optimized. Pulsed power was used as the experimental power source and the electroplating solution was prepared with various additive concentrations. Designed control variable experiments were conducted to determine the optimized method. In the control variable experiments, the relationship of multiple experimental variables, including current density (0.25⁻2 A/dm²), additive concentration (0.5⁻2 mL/L), and different shapes of TSVs (circle, oral, and square), were systematically analyzed. Considering the electroplating speed and quality, the influence of different factors on experimental results and the optimized parameters were determined. The results showed that increasing current density improved the electroplating speed but decreased the quality. Additives worked well, whereas their concentrations were controlled within a suitable range. The TSV shape also influenced the electroplating result. When the current density was 1.5 A/dm² and the additive concentration was 1 mL/L, the TSV filling was relatively better. With the optimized parameters, 500-µm-deep TSVs with a high aspect ratio of 10:1 were fully filled in 20 h, and the via density reached 70/mm². Finally, optimized parameters were adopted, and the electroplating of 1000-µm-deep TSVs with a diameter of 100 µm was completed in 45 h, which is the deepest and smallest through which a three-dimensional inductor has ever been successfully fabricated.