Eosinophils and drugs for eosinophilia are associated with the risk of colorectal cancer: a Mendelian randomization study.

Eosinophils have the potential to exhibit both anti-tumor properties and tumor-promoting effects. However, the impact of eosinophil levels in the bloodstream on tumorigenesis risk remains inadequately explored. Furthermore, investigations regarding the association between drugs regulating eosinophils and cancer risk are currently absent. In this study, we conducted a Mendelian randomization (MR) analysis utilizing eosinophil count and eosinophil percentage as exposures. In both cohorts, a significant association was observed between eosinophil count and the risk of colorectal cancer and skin malignancies. However, upon conducting a sensitivity analysis, heterogeneity was detected specifically in relation to skin malignancies. Subsequent reverse Mendelian randomization analysis did not indicate any evidence of reverse causality. Furthermore, the multivariate Mendelian randomization analysis results suggested that eosinophils act as a mediating factor in reducing the risk of colorectal cancer and skin malignancies in individuals with asthma. And the use of drugs that modulate eosinophilia may increase the risk of colorectal cancer. It is evident that the statistical evidence supporting a negative correlation between eosinophils count and the susceptibility to colorectal cancer is particularly robust. And, it is plausible to suggest that pharmaceutical interventions aimed at modulating eosinophilia may potentially heighten the risk of colorectal cancer. Hence, it is imperative to exercise caution and remain mindful of the potential risk of colorectal cancer when employing these medications.

Amino acids and risk of colon adenocarcinoma: a Mendelian randomization study.

BACKGROUND: The existence of amino acid metabolic reprogramming in tumor cells is well established. However, the potential correlation between blood amino acids and the risk of colon adenocarcinoma remains largely unexplored. METHODS: We utilized Mendelian randomization (MR) analysis to examine the association between 20 amino acids in the blood and the risk of colon adenocarcinoma. Additionally, reverse MR analysis was employed to identify the presence of reverse causality. A two-step MR analysis was conducted to ascertain the potential mediating effect. Lastly, the alanine detection data from colon adenocarcinoma patients in our hospital were utilized to investigate the differences in alanine levels among healthy individuals and patients with colon cancer, as well as among patients with different stages and locations of colon cancer. Furthermore, a Kaplan-Meier curve was employed to examine the correlation between alanine and overall survival, followed by the implementation of COX univariate analysis. RESULTS: The results of our study indicate that there is an inverse correlation between alanine and the risk of colon adenocarcinoma. Additionally, we found no significant evidence to support a causal relationship between colon adenocarcinoma and alanine. Furthermore, our analysis revealed that alanine aminotransferase (ALT) and blood glucose do not act as mediators in this causal pathway. Moreover, individuals diagnosed with colon adenocarcinoma exhibited a significant decrease in alanine levels, particularly in cases of stage IV colon adenocarcinoma with distant metastasis. Additionally, elevated alanine levels were associated with improved overall survival rates among colon adenocarcinoma patients. CONCLUSIONS: The results of this study indicate that alanine exhibits protective characteristics against the onset of colon adenocarcinoma and may play a role in promoting a more favorable disease prognosis. Consequently, dietary interventions aimed at increasing alanine intake may serve as a potential strategy for the prevention and treatment of colon adenocarcinoma.

A prospective, open-label, multicenter phase IV clinical trial on the safety and efficacy of lobaplatin-based chemotherapy in advanced breast cancer.

Background: Since lobaplatin (LBP) has been approved to treat metastatic breast cancer in China, this study aimed to evaluate the safety and efficacy of LBP-based chemotherapy in clinical practice. Methods: This trial was a prospective, open-label, multicenter phase IV clinical trial that enrolled patients with unresectable locally advanced or recurrent/metastatic breast cancer from 34 sites between July 2013 and March 2017. Patients were treated with LBP monotherapy or in combination for four to six cycles. The primary endpoint was safety. Secondary endpoints included progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). Results: A total of 1179 patients were analyzed; 59 (5.0%) were treated with LBP alone, 134 (11.4%) with LBP plus paclitaxel, 263 (22.3%) with LBP plus docetaxel, 237 (20.1%) with LBP plus gemcitabine, 403 (34.2%) with LBP plus vinorelbine, and 83 (7.0%) with other LBP-based regimens. The overall incidence of adverse events (AEs) was 95.2%, and 57.9% of patients had grade >3 AEs. The most common grade >3 AEs were neutropenia (43.9%), leukopenia (39.4%), anemia (17.8%), and thrombopenia (17.7%). LBP monotherapy showed the lowest incidence of grade >3 AEs (39.0%), followed by LBP plus docetaxel (52.9%), LBP plus paclitaxel (59.0%), LBP plus vinorelbine (62.5%), and LBP plus gemcitabine (62.9%). The ORR and DCR were 36.8 and 77.0%, respectively. The median PFS was 5.5 months (95% confidence interval: 5.2-5.9). Conclusion: LBP-based chemotherapy shows favorable efficacy in patients with advanced breast cancer, with manageable safety profile. Trial registration: This trial was registered with ChiCTR.org.cn, ChiCTR-ONC-13003471.

Metabolite biomarker discovery for human gastric cancer using dried blood spot mass spectrometry metabolomic approach.

As one of the most common malignancies, gastric cancer (GC) is the third leading cause of cancer-related deaths in China. GC is asymptomatic in early stages, and the majority of GC mortality is due to delayed symptoms. It is an urgent task to find reliable biomarkers for the identification of GC in order to improve outcomes. A combination of dried blood spot sampling and direct infusion mass spectrometry (MS) technology was used to measure blood metabolic profiles for 166 patients with GC and 183 healthy individuals, and 93 metabolites including amino acids, carnitine/acylcarnitines and their derivatives, and related ratios were quantified. Multiple algorithms were used to characterize the changes of metabolic profiles in patients with GC compared to healthy individuals. A biomarker panel was identified in training set, and assessed by tenfold cross-validation and external test data set. After systematic selection of 93 metabolites, a biomarker panel consisting of Ala, Arg, Gly, Orn, Tyr/Cit, Val/Phe, C4-OH, C5/C3, C10:2 shows the potential to distinguish patients with GC from healthy individuals in tenfold cross-validation model (sensitivity: 0.8750, specificity: 0.9006) and test set (sensitivity: 0.9545, specificity: 0.8636). This metabolomic analysis makes contribution to the identification of disease-associated biomarkers and to the development of new diagnostic tools for patients with GC.

Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer.

Background: The value of plasma threonine, cysteine, and piperonamide as diagnostic biomarkers for non-small cell lung cancer (NSCLC) has been rarely explored. The lack of a validation set containing confounders is common to most previous metabolomics studies. The purpose of this study was to explore and validate the value of plasma amino acids and piperonamide as diagnostic biomarkers for NSCLC using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Methods: A total of 250 participants were included in this study, including 167 patients with pathologically confirmed NSCLC and 83 healthy controls (HCs). These participants were divided into training set, validation set 1, and validation set 2 in chronological order and in a certain proportion. The plasma levels of 22 amino acids and 1 piperonamide in these pre-treatment NSCLC patients and HCs were measured by LC-MS/MS. Metabolic biomarkers were identified after multivariate analysis, univariate analysis, receiver operating characteristic (ROC) analysis. Furthermore, these biomarkers and transcriptomic data were subjected to joint pathway analysis. Results: The area under the ROC curve (AUC) values for threonine, piperonamide, arginine, alanine, cysteine, methionine, and histidine in the integrated data set were 0.911, 0.848, 0.909, 0.869, 0.786, 0.597 and 0.637, respectively. This panel composed of these 7 metabolites showed good diagnostic capability for NSCLC (the AUC of this diagnostic panel in each data set was greater than 0.9). The specificity of this diagnostic panel in validation set 2, which included confounders, was 0.970, similar to that of the other datasets. The presence of confounding factors had little effect on the diagnostic accuracy of this panel. The ROC analysis of this diagnostic panel between all stage I NSCLC patients and HCs showed AUC, sensitivity, and specificity of 1.000, 1.000, and 0.988, respectively. Moreover, PSAT1, SHMT2, AOC3, and MAOB were found to be involved in the metabolism of threonine and cysteine. Conclusions: Plasma amino acids and piperonamide have potential as diagnostic biomarkers in NSCLC. This metabolic biomarker panel appears useful for the diagnosis and screening of NSCLC. In addition, metabolomic and transcriptomic integration pathway analysis may help elucidate the mechanism of NSCLC occurrence and development and even reveal new treatment vulnerabilities.

Comprehensive analysis to identify noncoding RNAs mediated upregulation of maternal embryonic leucine zipper kinase (MELK) correlated with poor prognosis in hepatocellular carcinoma.

OBJECT: Maternal embryonic leucine zipper kinase (MELK) is involved in the development and progression of various cancers. This work investigated the usefulness of MELK in the prediction of hepatocellular carcinoma (HCC) prognosis. METHODS: Information on MELK expression was obtained by pan-cancer analysis using The Cancer Genome Atlas (TCGA) database. The TCGA-liver hepatic cancer (TCGA-LIHC), Oncomine datasets, International Cancer Genome Consortium (ICGC) datasets were used to investigate MELK expression in HCC. The prognostic roles of MELK in HCC were assessed by univariate and multivariate survival analyses. The underlying mechanism for noncoding RNAs (ncRNAs) involved in MELK expression was investigated by in silico studies, correlation, methylation, and survival analyses. The relationships between MELK expression and immune cells, immune markers, and checkpoint markers were also analyzed. RESULTS: (1) MELK was identified as an independent predictor of overall survival (OS) in HCC patients (MELK high vs. low expression, HR 2.469; 95% CI 1.217-5.008; p = 0.012) in a multivariate Cox analysis, with a concordance index (C-index) value of 0.727 (95% CI 0.750-0.704). (2) The noncoding RNA miR3142HG and the LINC00265/has-miR-101-3p axis were found to regulate MELK expression in HCC tissue. (3) MELK levels were linked to various immune functions, including tumor infiltration and the expression of immune checkpoints and biomarkers in HCC. CONCLUSION: MELK may have an oncogenic function in HCC and was found to be up-regulated by ncRNAs and associated with immune cell infiltration and unfavorable prognosis.

A new pyroptosis model can predict the immunotherapy response and immune microenvironment characteristics and prognosis of patients with cutaneous melanoma based on TCGA and GEO databases.

Background: Recent studies have shown that pyroptosis is related to cancer development. Our previous study also found that gasdermins (GSDMs) was associated with the tumor immune microenvironment. Therefore, we wanted to observe the relationship between pyroptosis and the immune microenvironment and prognosis of skin cutaneous melanoma (SKCM). Methods: Pyroptosis-related genes were used for pan-cancer prognostic analysis using the GEPIA2 online analysis website. Prognosis-related genes were clustered using R software and related R packages, and the best clustering results were screened for prognosis analysis. The prognosis-related genes were also used to establish a prognosis-related model. Assess the predictive power of a model by comparing area under the curve (AUC). The t-test was used to analyze the differences of immune-related indicators between the two clusters and between high and low risk groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed on the differential genes. Results: By clustering the prognosis-related genes, SKCM could be divided into 2 clusters with significant differences in prognosis P<0.05. A prognostic model can be established using prognosis-related genes. The AUC value of 1 year, 2 years and 3 years was 0.696, 0.702 and 0.664, respectively. The risk score was significantly associated with prognosis in both univariate and multivariate Cox analyses P<0.001. The low-risk group or C2 cluster with better prognosis had higher expression of pyroptosis-related genes, and tended to have a lower exclusion score, greater chemokine expression, more immune cells and higher immune score. However, the C2 cluster or low-risk group was also associated with a higher dysfunction score. At the same time, the C2 or low-risk group was more suitable for immunotherapy because of the higher immunophenoscore (IPS) score P<0.001. Correlation analysis also demonstrated that the risk score was positively correlated with the gene expression of most immunoinhibitors, MHC molecules, immunostimulators, and chemokines and their receptors. Conclusions: Pyroptosis is associated with melanoma immune microenvironment, immunotherapy response, and prognoses. The constructed risk scores could effectively predict the characteristics of the immune microenvironment, the sensitivity to immunotherapy, and the prognosis of melanoma patients.

Toripalimab plus chemotherapy in treatment-naïve, advanced esophageal squamous cell carcinoma (JUPITER-06): A multi-center phase 3 trial.

Platinum-based chemotherapy is the standard first-line treatment for advanced esophageal squamous cell carcinoma (ESCC). In this phase 3 study (ClinicalTrial.gov: NCT03829969), 514 patients with treatment-naïve advanced ESCC were randomized (1:1) to receive toripalimab or placebo in combination with paclitaxel plus cisplatin (TP) every 3 weeks for up to 6 cycles, followed by toripalimab or placebo maintenance. At the prespecified final analysis of progression-free survival (PFS), a significant improvement in PFS is observed for the toripalimab arm over the placebo arm (hazard ratio [HR] = 0.58; 95% CI, 0.46-0.74; p < 0.0001). The prespecified interim analysis of overall survival (OS) also reveals a significant OS improvement for patients treated with toripalimab plus TP over placebo plus TP (HR = 0.58; 95% CI, 0.43-0.78; p = 0.0004). The incidences of grade ≥3 treatment-emergent adverse events are similar between the two arms. Toripalimab plus TP significantly improves PFS and OS in patients with treatment-naïve, advanced ESCC, with a manageable safety profile.

A metabolomics strategy to identify potential biomarkers associated with human laryngeal cancer based on dried blood spot mass spectrometry approach.

ABSTRACT: Laryngeal cancer (LC) as one of common malignant tumors in the head and neck region accounted for 1% to 5% of new cancer cases and was ranked as the third otolaryngology cancer. However, some patients with LC were diagnosed at the advanced stage, which can cause delayed diagnosis and treatment. It is an urgent task to seek effective biomarkers for the early diagnosis of LC aimed at alleviating suffering.A combination of dried blood spot sampling and direct infusion mass spectrometry technology was applied to 39 patients with LC and 53 healthy individuals. Multiple algorithms towards 93 metabolites including amino acids and carnitine/acylcarnitines were run for selecting differential metabolites. Furthermore, leave-one-out cross-validation method was used to evaluate diagnostic performance of selected metabolite biomarkers.A biomarker panel consisting of arginine, proline, hexacosanoic carnitine, ornithine /citrulline, and 3-hydroxy-octadecenoylcarnitine exhibited potential to distinguish patients with LC from healthy individuals, with a sensitivity of 0.8974 and a specificity of 0.8302 in leave-one-out cross-validation model.The metabolomic analysis of LC patients is beneficial to screen disease-associated biomarkers and develop new diagnostic approaches.

Abnormal arginine metabolism is associated with prognosis in patients of gastric cancer.

BACKGROUND: Metabolic disorder is a key factor in the occurrence and development of tumors. Metabolomics methods can explore a variety of prognostic markers for tumors. METHODS: The 454 patients included in this study comprised 92 cases of gastric cancer, 51 cases of gastric ulcers, 206 cases of gastric polyps, and 105 cases of gastritis. The plasma levels of 23 amino acids in patients before treatment were detected by liquid chromatography-tandem mass spectrometry, and t-test was used to determine the difference of amino acids levels between the gastric cancer group and other groups. Shared different amino acids were selected to analyze their relationship with staging, differentiation and prognosis. The TCGA database was used to explore the changes of genes expression related to the synthesis and degradation of different amino acids, and the relationship between the genes and stage, differentiation and prognosis. RESULTS: The plasma arginine level in the gastric cancer group was significantly higher than that in the gastric ulcer, gastric polyp, and gastritis groups (P values 0.0065, 0.0306, 0.0004, respectively).The level of plasma arginine in patients with non-metastatic gastric cancer was significantly higher than that in patients with metastatic gastric cancer (P=0.0013). Compared with the normal control, the key metabolic enzyme ASS1 gene was highly expressed in gastric cancer, and the survival time of gastric cancer patients with high expression of ASS1 was longer. Patients with high arginine expression had significantly longer survival (log-rank test P=0.0003). CONCLUSIONS: Increased plasma arginine level in gastric cancer patients was related to overexpression of ASS1 by TCGA database analysis. High expression of ASS1 prolonged the overall survival of gastric cancer patients, and the arginine level before treatment could be used as a prognostic factor.

A pan-cancer analysis of the expression of gasdermin genes in tumors and their relationship with the immune microenvironment.

BACKGROUND: Gasdermins (GSDMs) are a class of proteins related to pyrolysis and in humans, consist of GSDMA, GSDMB, GSDMC, GSDMD, DFNA5, and DFNB59. The inflammatory factors and cell contents released during pyrolysis can recruit immune cells and change the microenvironment. However, to date, there is a paucity of studies examining the relationship between GSDMs and the immune microenvironment in tumors. Therefore, this current report analyzed the expression of GSDM genes in tumors and their relationship with the immune microenvironment. METHODS: Apply GSCALite and GEPIA2 online analysis tools to analyze the gene expression levels and the Single nucleotide variant (SNV), copy number variation (CNV), and methylation characteristics of GSDM genes respectively. Use R software or TISIDB online analysis tool to carry out the correlation analysis required in the article. Furthermore, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to examine the role of these GSDM genes in various cancers. RESULTS: The results demonstrated that CNV can cause an increase in GSDM gene expression, and methylation can inhibit GSDM gene expression. The elevated expression of GSDMA, GSDMB, GSDMC, GSDMD, and DFNA5 in some or most tumors was often accompanied by elevated immune scores, increased immune cell infiltration, and high expression of major histocompatibility complex (MHC) molecules, chemokines and their receptors, and immune checkpoint-related genes. However, DFNB59 was often negatively correlated with these indicators in tumors. GSDMD was the most highly expressed GSDM protein in various normal tissues and tumors, and showed the strongest correlation with immune microenvironment-related genes. Moreover, the methylation of GSDMD was accompanied by low immune cell infiltration, low expression of MHC molecule-related genes, low expression of chemokines and receptor-related genes, and low expression of immune checkpoint-related genes. CONCLUSIONS: Therefore, the expression of GSDM-related genes is associated with the tumor immune microenvironment. The GSDM genes, especially GSDMD, may be used as therapeutic targets to predict or change the tumor microenvironment and as biomarkers to predict the therapeutic efficacy of immune checkpoint inhibitors.

Prediction of KRAS, NRAS and BRAF status in colorectal cancer patients with liver metastasis using a deep artificial neural network based on radiomics and semantic features.

There is a critical need for development of improved methods capable of accurately predicting the RAS (KRAS and NRAS) and BRAF gene mutation status in patients with advanced colorectal cancer (CRC). The purpose of this study was to investigate whether radiomics and/or semantic features could improve the detection accuracy of RAS/BRAF gene mutation status in patients with colorectal liver metastasis (CRLM). In this retrospective study, 159 patients who had been diagnosed with CRLM in two hospitals were enrolled. All patients received lung and abdominal contrast-enhanced CT (CECT) scans prior to radiation therapy and chemotherapy. Semantic features were independently assessed by two radiologists. Radiomics features were extracted from the portal venous phase (PVP) of the CT scan for each patient. Seven machine learning algorithms were used to establish three scores based on the semantic, radiomics and the combination of both features. Two semantic and 851 radiomics features were used to predict the mutation status of RAS and BRAF using an artificial neural network method (ANN). This approach performed best out of the seven tested algorithms. We constructed three scores which were based on radiomics, semantic features and the combined scores. The combined score could distinguish between wild-type and mutant patients with an AUC of 0.95 in the primary cohort and 0.79 in the validation cohort. This study proved that the application of radiomics together with semantic features can improve non-invasive assessment of the gene mutation status of RAS (KRAS and NRAS) and BRAF in CRLM.

Real-world EGFR testing in patients with stage IIIB/IV non-small-cell lung cancer in North China: A multicenter, non-interventional study.

BACKGROUND: Before tyrosine kinase inhibitor (TKI) therapy can be administered in patients with advanced non-small cell lung cancer (NSCLC), EGFR mutation testing is required. However, few studies have evaluated the extent of EGFR testing in real-world practice in China. METHODS: A multicenter, observational study of EGFR testing in NSCLC patients in North China was conducted. Treatment-naïve patients or those with postoperative recurrent stage IIIB/IV NSCLC were enrolled. The primary objective was EGFR testing rate. Secondary objectives included EGFR mutation status, EGFR testing methods and specimens, factors associated with EGFR testing, and overall survival with or without EGFR testing. RESULTS: Overall, 2809 patients with stage IIIB/IV NSCLC were enrolled; 90.78% had adenocarcinoma. The EGFR screening rate was 42.54%. EGFR testing rates were higher in tumor samples obtained by lymph node puncture, and in patients with urban medical insurance, adenocarcinoma, non-smokers, or those located in developed cities (all P < 0.001). The EGFR mutation rate was 46.44%. The most commonly used specimens for EGFR testing were biopsy tumor samples (67.53%). PCR-based methods (72.05%), Sanger sequencing (5.36%), and Luminex liquid chip (5.10%) were the most frequently used testing platforms. Similar positive EGFR mutation rates were achieved with different platforms. TKI therapy was the first-line treatment administered to most EGFR-positive patients (56.22%), and chemotherapy in EGFR-negative patients (84.88%). Overall survival was higher in EGFR-tested than in untested patients (27.50 vs. 19.73 months; P = 0.007). CONCLUSION: Real-world EGFR testing rates for NSCLC in North China were relatively low because of clinical and social factors, including medical insurance coverage.

The Significance of Single-Cell Biomedicine in Stem Cells.

Clinical application of stem cells (SCs) progresses significantly in the treatment of a large number of diseases, e.g. leukemia, respiratory diseases, kidney disease, cerebral palsy, autism, or autoimmune diseases. Of those, the population, biological phenotypes, and functions of individual SCs are mainly concerned, due to the lack of cell separation and purification processes. The single-cell technology, including microfluidic technology and single-cell genome amplification technology, is widely used to study SCs and gains some recognitions. The present review will address the importance of single-cell technologies in the recognition and heterogeneity of SCs and highlight the significance of current single-cell approaches in the understanding of SC phenotypes. We also discuss the values of single-cell studies to overcome the bottleneck in explore of biological mechanisms and reveal the therapeutic potentials of SCs in diseases, especially tumor-related diseases, as new diagnostic and therapeutic strategies.

Discriminating gastric cancer and gastric ulcer using human plasma amino acid metabolic profile.

Patients with gastric ulcer (GU) have a significantly higher risk of developing gastric cancer (GC), especially within 2 years after diagnosis. The main way to improve the prognosis of GC is to predict the tumorigenesis and metastasis in the early stage. The objective of this study was to demonstrate the ability of human plasma amino acid metabolic profile for discriminating GC and GU. In this study, we first used liquid chromatography-tandem mass spectrometry technique to characterize the plasma amino acid metabolism in GC and GU patients. Plasma samples were collected from 84 GC patients and 82 GU patients, and 22 amino acids were detected in each patient. Partial least squares-discriminant analysis model was performed to analyze the data of these amino acids. We observed seven differential amino acids between GC and GU. A regression analysis model was established using these seven amino acids. Finally, a panel of five differential amino acids, including glutamine, ornithine, histidine, arginine and tryptophan, was identified for discriminating GC and GU with good specificity and sensitivity. The receiver operating characteristic curve was used to evaluate diagnostic ability of the regression model and area under the curve was 0.922. In conclusion, this study demonstrated the potential values of plasma amino acid metabolic profile and metabolomic analysis technique in assisting diagnosis of GC. More studies are needed to highlight the theoretical strengths of metabolomics to understand the potential metabolic mechanisms in GC. © 2018 IUBMB Life, 70(6):553-562, 2018.

Differential diagnosis between hepatocellular carcinoma and cirrhosis by serum amino acids and acylcarnitines.

The routine biochemical parameters for hepatocellular carcinoma (HCC) diagnosis are all protein markers. Serum concentrations of these markers can be affected by some benign diseases. Most of the occurrence of HCC has a background of cirrhosis, posing a great challenge to differential diagnosis of HCC from cirrhosis using traditional biochemical parameters. Values of serum small molecular metabolites for HCC diagnosis are not fully evaluated. In this study, a traditionalmass spectrometry-based screening strategy was employed to profile amino acids and acylcarnitines in blood samples collected from HCC and cirrhosis patients. Each whole blood specimen was sampled on filter paper and dried at room temperature. Metabolites in the dried blood spots were extracted using organic solvent and then concentrated for mass spectrometry analysis. It was found that 11 parameters, including amino acids, acylcarnitines and some of their relevant ratios, could be used to construct a satisfied differential diagnosis model. In this model, most of the relevant amino acids were essential amino acids. It was noticed that short-chain acylcarnitines tended to be risk factors for HCC. Long-chain acylcarnitines seemed to be risk factors for cirrhosis. This study demonstrates the value of mass spectrometry-based analysis for differential diagnosis of HCC and cirrhosis. Improved differential diagnosis ability may be achieved by combined use of traditional protein markers along with metabolite markers.

The inhibition of UDP-glucuronosyltransferases (UGTs) by tetraiodothyronine (T4) and triiodothyronine (T3).

1. UDP-glucuronosyltransferases (UGTs) are important drug-metabolizing enzymes (DMEs) catalyzing the glucuronidation elimination of various xenobiotics and endogenous substances. Endogenous substances are important regulators for the activity of various UGT isoforms. Triiodothyronine (T3) and thyroxine (T4) are important thyroid hormones essential for normal cellular differentiation and growth. The present study aims to elucidate the inhibition behavior of T3 and T4 on the activity of UGT isoforms. 2. In vitro recombinant UGTs-catalyzed glucuronidation of 4-methylumbelliferone (4-MU) was used to screen the inhibition potential of T3 and T4 on the activity of various UGT isoforms. Initial screening results showed that T4 exerted stronger inhibition potential than T3 on the activity of various UGT isoforms at 100 µM. Inhibition kinetics was determined for the inhibition of T4 on the representative UGT isoforms, including UGT1A1, -1A3, -1A7, -1A8, -1A10 and -2B7. The results showed that T4 competitively inhibited the activity of UGT1A1, -1A3, -1A7, 1A10 and -2B7, and noncompetitively inhibited the activity of UGT1A8. The inhibition kinetic parameters were calculated to be 1.5, 2.4, 11, 9.6, 4.8 and 3.0 µM for UGT1A1, -1A3, -1A7, -1A8, -1A10 and -2B7, respectively. In silico docking method was employed to demonstrate why T4 exerted stronger inhibition than T3 towards UGT1A1. Stronger hydrogen bonds and hydrophobic interaction between T4 and activity cavity of UGT1A1 than T3 contributed to stronger inhibition of T4 towards UGT1A1. 3. In conclusion, more clinical monitoring should be given for the patients with the elevation of T4 level due to stronger inhibition of UGT isoforms-catalyzed metabolism of drugs or endogenous substances by T4.

Everolimus-inhibited multiple isoforms of UDP-glucuronosyltransferases (UGTs).

1. Everolimus is an inhibitor of mammalian target of rapamycin (mTOR) and has been clinically utilized to prevent the rejection of organ transplants. This study aims to determine the inhibition of everolimus on the activity of phase-II drug-metabolizing enzymes UDP-glucuronosyltransferases (UGTs). 2. The results showed that 100 µM of everolimus exerted more than 80% inhibition toward UGT1A1, UGT-1A3 and UGT-2B7. UGT1A3 and UGT2B7 were selected to elucidate the inhibition mechanism, and in silico docking showed that hydrogen bonds and hydrophobic interactions mainly contributed to the strong binding of everolimus toward the activity cavity of UGT1A3 and UGT2B7. Inhibition kinetic-type analysis using Lineweaver-Burk plot showed competitive inhibition toward all these UGT isoforms. The inhibition kinetic parameters (Ki) were calculated to be 2.3, 0.07 and 4.4 µM for the inhibition of everolimus toward UGT1A1, UGT-1A3 and UGT-2B7, respectively. 3. In vitro-in vivo extrapolation (IVIVE) showed that [I]/Ki value was calculated to be 0.004, 0.14 and 0.002 for UGT1A1, UGT-1A3 and UGT-2B7, respectively. Therefore, high DDI potential existed between everolimus and clinical drugs mainly undergoing UGT1A3-catalyzed glucuronidation.

Efficacy of Thalidomide in Preventing Delayed Nausea and Vomiting Induced by Highly Emetogenic Chemotherapy: A Randomized, Multicenter, Double-Blind, Placebo-Controlled Phase III Trial (CLOG1302 study).

Purpose We examined the efficacy and safety of thalidomide (THD) for the prevention of delayed nausea and vomiting in patients who received highly emetogenic chemotherapy (HEC). Patients and Methods In a randomized, double-blind, active-controlled, phase III trial, chemotherapy-naive patients with cancer who were scheduled to receive HEC that contained cisplatin or cyclophosphamide-doxorubicin/epirubincin ≥ 50 mg/m2 regimens were randomly assigned to a THD group (100 mg twice daily on days 1 to 5) or placebo group, both with palonosetron (0.25 mg on day 1) and dexamethasone (12 mg on day 1; 8 mg on days 2 to 4). Primary end point was complete response to vomiting-no emesis or use of rescue medication-in the delayed phase (25 to 120 h). Nausea and anorexia on days 1 to 5 were evaluated by the 4-point Likert scale (0, no symptoms; 3, severe). Quality of life was assessed by the European Organization for Research and Treatment of Cancer QLQ-C30 version 3 questionnaire on days -1 and 6. Results Of 656 patients, 638 were evaluable: 317 in the THD group and 321 in the control group. Compared with placebo, delayed and overall (0 to 120 h) complete response rates to vomiting were significantly higher with THD: 76.9% versus 61.7% ( P < .001) and 66.1% versus 53.3% ( P = .001), respectively. Rates of no nausea were also higher in the THD group (delayed: 47.3% v 33.3%; P < .001; overall: 41% v 29.6%; P = .003), and mean scores of anorexia were lower overall (0.44 ± 0.717 v 0.64 ± 0.844; P = .003). Adverse effects were mild to moderate. The THD group had increased sedation, dizziness, constipation, and dry mouth, but experienced better quality of life after chemotherapy. Conclusion Thalidomide combined with palonosetron and dexamethasone significantly improved HEC-induced delayed nausea and vomiting prevention in chemotherapy-naive patients.

Downregulation of MicroRNA-330 Correlates with the Radiation Sensitivity and Prognosis of Patients with Brain Metastasis from Lung Cancer.

BACKGROUND: The present study sought to explore the role of microRNA-330 (miR-330) in predicting the radiation response and prognosis of patients with brain metastasis (BM) from lung cancer (LC). METHODS: Patients with BM from LC were identified and classified into radiation-sensitive and radiation-resistant groups according to the overall survival rate, local and distant recurrence rate after conventional whole-brain radiation therapy. Quantitative realtime polymerase chain reaction (qRT-PCR) was used to detect miR-330 expression in serum. Receiver operating characteristic (ROC) curves were used to evaluate the prognostic value of miR-330 for the radiation sensitivity of brain metastasis from LC. Related clinical factors for radiation sensitivity were assessed by logistic regression analysis, and a survival analysis was conducted using COX regression and the Kaplan-Meier method. RESULTS: MiR-330 exhibited lower expression in the radiation-sensitive group than in the radiation-resistant group. The area under the ROC curve of miR-330 for predicting radiation sensitivity was 0.898 (optimal cut-off value, 0.815), with a sensitivity of 71.7% and a specificity of 90.1%. After radiation therapy, patients with low miR-330 expression, compared to patients with high miR-330 expression, displayed a lower survival rate and a median survival time. MiR-330 expression was correlated with extracranial metastasis, maximum BM diameter, tumor-node-metastasis (TNM) stage and node (N) stage. Logistic regression and COX regression analyses revealed that extracranial metastasis, TNM stage, N stage and miR-330 expression were factors that influenced both radiation sensitivity and individual prognostic factors in patients with BM from LC. CONCLUSIONS: These findings indicate that the downregulation of miR-330 correlates with radiation sensitivity and poor prognosis in patients with BM from LC.