Yongmei Song

Integrated ionization approach for RRLC-MS/MS-based metabonomics: finding potential biomarkers for lung cancer.

An integrated ionization approach of electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI) combining with rapid resolution liquid chromatography mass spectrometry (RRLC-MS) has been developed for performing global metabonomic analysis on complex biological samples. This approach was designed to overcome the low ionization efficiencies of endogenous metabolites due to diverse physicochemical properties as well as ion suppression, and obtain comprehensive metabolite profiles in LC-MS analysis. Ionization capability and applicability were manifested by improved ionization efficiency and enlarged metabolite coverage in analysis on typical urinary metabolite standards and urine samples from healthy volunteers. The method was validated by the limit of detection and precision. When applied to the global metabonomic studies of lung cancer, more comprehensive biomarker candidates were obtained to reflect metabolic traits between healthy volunteers and lung cancer patients, including 74 potential biomarkers in positive ion mode and 59 in negative ion mode. Taking identical potential biomarkers of any two or three ionization methods into account, analysis using ESI-MS in positive (+) and negative (-) ion mode contributed to 70 and 64% of the total potential biomarkers, respectively. The biomarker discovery capability of (+/-) APCI-MS accounted for 45 and 42% of the overall; meanwhile (+/-) APPI-MS amounted for 39 and 54%. These results indicated that potential biomarkers with vital biological information could be missed if only a single ionization method was used. Furthermore, 11 potential biomarkers were identified including amino acids, nucleosides, and a metabolite of indole. They revealed elevated amino acid and nucleoside metabolism as well as protein degradation in lung cancer patients. This proposed approach provided a more comprehensive picture of the metabolic changes and further verified identical biomarkers that were obtained simultaneously using different ionization methods.

DNA methylation mediated repression of miR-886-3p predicts poor outcome of human small cell lung cancer

Small cell lung cancer (SCLC) is one of the most aggressive types of cancer, yet the pathologic mechanisms underlying its devastating clinical outcome remain elusive. In this report, we surveyed 924 miRNA (miR) for their expressions in the formalin-fixed paraffin-embedded specimens from 42 patients with SCLC, and found that the downregulated miR-886-3p is closely correlated with the shorter survival of SCLC. This correlation was validated with another 40 cases. It was further discovered that loss of miR-886-3p expression was mediated by DNA hypermethylation of its promoter in both cultured SCLC cells and tumor samples. Moreover, miR-886-3p potently repressed cell proliferation, migration, and invasion of NCI-H446 cell in cell culture via suppression of the expression of its target genes: PLK1 and TGF-β1 at posttranscription levels. Forced upregulation of miR-886-3p greatly inhibited in vivo tumor growth, bone/muscle invasion, and lung metastasis of NCI-H446 cells. This newly identified miR-886-3p-PLK1/TGF-β1 nexus that modulates SCLC aggression suggests that both loss of miR-886-3p expression and hypermethylation of the miR-886 promoter are the promising indicators for poor outcome of as well as new therapeutic targets for SCLC.

Global and Targeted Metabolomics of Esophageal Squamous Cell Carcinoma Discovers Potential Diagnostic and Therapeutic Biomarkers

Diagnostic and therapeutic biomarkers useful for esophageal squamous cell carcinoma (ESCC) have the ability to increase the long term survival of cancer patients. A metabolomics study, using plasma from four groups including ESCC patients before, during, and after chemoradiotherapy (CRT) and healthy controls, was originally carried out by LC-MS to determine global alterations in the metabolic profiles and find biomarkers potentially applicable to diagnosis and monitoring treatment effects. It is worth pointing out that a clear clustering and separation of metabolic data from the four groups was observed, which indicated that disease status and treatment intervention resulted in specific metabolic perturbations in the patients. A series of metabolites were found to be significantly altered in ESCC patients versus healthy controls and in pre- versus post-treatment patients based on multivariate statistical data analysis (MVDA). To further validate the reliability of these potential biomarkers, an independent validation was performed by using the selected reaction monitoring (SRM) based targeted approach. Finally, 18 most significantly altered plasma metabolites in ESCC patients, relative to healthy controls, were tentatively identified as lysophosphatidylcholines (lysoPCs), fatty acids, l-carnitine, acylcarnitines, organic acids, and a sterol metabolite. The classification performance of these metabolites were analyzed by receiver operating characteristic (ROC)1 analysis and a biomarker panel was generated. Together, biological significance of these metabolites was discussed. Comparison between pre- and post-treatment patients generated 11 metabolites as potential therapeutic biomarkers that were tentatively identified as amino acids, acylcarnitines, and lysoPCs. Levels of three of these (octanoylcarnitine, lysoPC(16:1), and decanoylcarnitine) were closely correlated with treatment effect. Moreover, variation of these three potential biomarkers was investigated over the treatment course. The results suggest that these biomarkers may be useful in diagnosis, as well as in monitoring therapeutic responses and predicting outcomes of the ESCC.

RRLC-MS/MS-based metabonomics combined with in-depth analysis of metabolic correlation network: finding potential biomarkers for breast cancer

A metabonomics strategy based on rapid resolution liquid chromatography/tandem mass spectrometry (RRLC-MS/MS), multivariate statistics and metabolic correlation networks has been implemented to find biologically significant metabolite biomarkers in breast cancer. RRLC-MS/MS analysis by electrospray ionization (ESI) in both positive and negative ion modes was employed to investigate human urine samples. The resulting data matrices were analyzed using multivariate analysis. Application of orthogonal projections to latent structures discriminate analysis (OPLS-DA) allowed us to extract several discriminated metabolites reflecting metabolic characteristics between healthy volunteers and breast cancer patients. Correlation network analysis between these metabolites has been further applied to select more reliable biomarkers. Finally, high resolution MS and MS/MS analyses were performed for the identification of the metabolites of interest. We identified 12 metabolites as potential biomarkers including amino acids, organic acids, and nucleosides. They revealed elevated tryptophan and nucleoside metabolism as well as protein degradation in breast cancer patients. These studies demonstrate the advantages of integrating metabolic correlation networks with metabonomics for finding significant potential biomarkers: this strategy not only helps identify potential biomarkers, it also further confirms these biomarkers and can even provide biochemical insights into changes in breast cancer.

Gadd45a Interacts with Aurora-A and Inhibits Its Kinase Activity

Centrosome stability is required for successful mitosis in mammalian cells. Amplification of the centrosome leads to chromosomal missegregation and generation of aneuploidy, which are closely associated with cell transformation and tumorigenesis (Doxsey, S. J. (2001) Nat. Cell Biol. 3, E105-E108; Hinchcliffe, E. H., and Sluder, G. (2001) Genes Dev. 15, 1167-1181; Pihan, G. A., Purohit, A., Wallace, J., Malhotra, R., Liotta, L., and Doxsey, S. J. (2001) Cancer Res. 61, 2212-2219). However, there are currently limited insights into mechanism(s) for this critical biological event. Here we show that Gadd45a, a DNA damage-inducible protein that is regulated by tumor suppressors p53 and BRCA1, participates in the maintenance of centrosome stability. Mouse embryonic fibroblasts derived from gadd45a knock-out mice exhibit centrosome amplification (designated as increased centrosome numbers). Introduction of exogenous Gadd45a into mouse embryonic fibroblasts isolated from gadd45a-null mice substantially restored the normal centrosome profile. In contrast to p21waf1/cip1, which ensures coordinated initiation of centrosome, Gadd45a had no significant effect on centrosome duplication in S phase. Interestingly Gadd45a was found to physically associate with Aurora-A protein kinase, whose deregulated expression results in centrosome abnormality. Furthermore Gadd45a was demonstrated to strongly inhibit Aurora-A kinase activity and to antagonize Aurora-A-induced centrosome amplification. These findings identify a novel mechanism for Gadd45a in the maintenance of centrosome stability and broaden understandings of p53- and BRCA1-regulated signaling pathways in maintaining genomic fidelity.

Liquid chromatography-tandem mass spectrometry-based plasma metabonomics delineate the effect of metabolites' stability on reliability of potential biomarkers.

Metabonomics is an important platform for investigating the metabolites of integrated living systems and their dynamic responses to changes caused by both endogenous and exogenous factors. A metabonomics strategy based on liquid chromatography-mass spectrometry/mass spectrometry in both positive and negative ion modes was applied to investigate the short-term and long-term stability of metabolites in plasma. Principal components analysis and ten types of identified metabolites were used to summarize the time-dependent change rules in metabolites systematically at different temperatures. The long-term stability of metabolites in plasma specimens stored at -80 °C for five years was also studied. Analysis of these subjects identified 36 metabolites with statistically significant changes in expression (p < 0.05) and found a kind of metabolite with a hundred-fold change. The stability of metabolites in blood at 4 °C for 24 h was also investigated. These studies show that a thorough understanding of the effects of metabolite stability are necessary for improving the reliability of potential biomarkers.

Centrosomal Nlp is an oncogenic protein that is gene-amplified in human tumors and causes spontaneous tumorigenesis in transgenic mice

Disruption of mitotic events contributes greatly to genomic instability and results in mutator phenotypes. Indeed, abnormalities of mitotic components are closely associated with malignant transformation and tumorigenesis. Here we show that ninein-like protein (Nlp), a recently identified BRCA1-associated centrosomal protein involved in microtubule nucleation and spindle formation, is an oncogenic protein. Nlp was found to be overexpressed in approximately 80% of human breast and lung carcinomas analyzed. In human lung cancers, this deregulated expression was associated with NLP gene amplification. Further analysis revealed that Nlp exhibited strong oncogenic properties; for example, it conferred to NIH3T3 rodent fibroblasts the capacity for anchorage-independent growth in vitro and tumor formation in nude mice. Consistent with these data, transgenic mice overexpressing Nlp displayed spontaneous tumorigenesis in the breast, ovary, and testicle within 60 weeks. In addition, Nlp overexpression induced more rapid onset of radiation-induced lymphoma. Furthermore, mouse embryonic fibroblasts (MEFs) derived from Nlp transgenic mice showed centrosome amplification, suggesting that Nlp overexpression mimics BRCA1 loss. These findings demonstrate that Nlp abnormalities may contribute to genomic instability and tumorigenesis and suggest that Nlp might serve as a potential biomarker for clinical diagnosis and therapeutic target.

Aurora-A interacts with Cyclin B1 and enhances its stability

The mitotic regulator Aurora-A is an oncogenic protein that is over-expressed in many types of human tumors. However, the underlying mechanism through which Aurora-A promotes tumorigenesis remains unclear. Here, we show that overexpression of Aurora-A causes an elevation of Cyclin B1 expression. Cyclin B1 degradation is delayed in Aurora-A over-expressing cells, which depends on Aurora-A kinase activity. In contrast, Aurora-A RNAi enhances Cyclin B1 degradation. Furthermore, we found that Aurora-A interacts with Cyclin B1, and that Aurora-A overexpression reduces the interaction of Cyclin B1 with APC subunits. In human esophageal squamous cell carcinomas (ESCC), overexpression of Aurora-A was correlated with deregulated expression of Cyclin B1. Taken together, these findings suggest that overexpression of Aurora-A may stabilize Cyclin B1 through inhibiting its degradation. These results provide new insight into the mechanism of how deregulated Aurora-A contributes to genomic instability and carcinogenesis.

Migfilin Protein Promotes Migration and Invasion in Human Glioma through Epidermal Growth Factor Receptor-mediated Phospholipase C-γ and STAT3 Protein Signaling Pathways

Background: The oncogenesis and developmental mechanisms of glioma must be clarified to control the disease. Results: Migfilin relates to pathological grades, prognosis of glioma, and regulates motility of glioma cells. Conclusion: Migfilin mediates migration and invasion through EGFR-induced PLC-γ and STAT3 pathways. Significance: Migfilin helps us better understand the pathogenesis of glioma, and Migfilin may be a molecular marker in diagnosis and an indicator in prognosis. Migfilin is critical for cell shape and motile regulation. However, its pathological role in glioma is unknown. Using an immunohistochemical staining assay, we demonstrate that there is a significant correlation between expression of Migfilin and pathological tumor grade in 217 clinical glioma samples. High Migfilin expression is associated with poor prognosis for patients with glioma. Investigation of the molecular mechanism shows that Migfilin promotes migration and invasion in glioma cells. Moreover, Migfilin positively modulates the expression and activity of epidermal growth factor receptor, and Migfilin-mediated migration and invasion depend on epidermal growth factor receptor-induced PLC-γ and STAT3-signaling pathways. Our results may provide significant clinical application, including use of Migfilin as a molecular marker in glioma for early diagnosis and as an indicator of prognosis.

Analysis of multiplex endogenous estrogen metabolites in human urine using ultra-fast liquid chromatography-tandem mass spectrometry: a case study for breast cancer.

A rapid, sensitive, specific and accurate analytical method of ultra-fast liquid chromatography combined with tandem mass spectrometry (UFLC-MS/MS) was established for simultaneous quantitative analysis of 16 distinct endogenous estrogens and their metabolites (EMs) in postmenopausal female urine. The quantitative method utilized a hydrolysis/extraction/derivatization step and a UFLC system to achieve separation in 16 min. The lower limit of quantitation for each estrogen metabolite was 2 pg mL(-1) with the percent recovery of a known added amount of estrogen at 93.2-109.3%. The intra-batch accuracy and precision for all analytes were 87.5-107.7% and 0.6-11.7%, respectively, while inter-batch accuracy and precision were 87.0-105.8% and 1.2-10.2%, respectively. Using this developed and validated method, the comprehensive metabolic profiling of 16 EMs in urine samples of 86 postmenopausal female breast cancer patients and 36 healthy controls was investigated by systematic statistical analysis. As a result, the circulating levels of 6 EMs were found to be different by a comparison of patients and healthy controls. The parent estrogens, estrone (E1) and 17β-estradiol (E2), as well as 2-hydroxyestradiol (2-OHE2) and 4-hydroxyestradiol (4-OHE2) were produced in higher abundance, whereas 16α-hydroxyestrone (16α-OHE1) and 2-methoxyestradiol (2-MeOE2) were decreased in the breast cancer group. 2-OHE2 and 4-OHE2 in particular showed significant elevation in patients, which are consistent with the carcinogenic mechanism hypothesis that catechol estrogens can react with DNA via quinones, resulting in mutations to induce breast cancer. Thus, 2,4-hydroxylation may be the dominant metabolic pathway for parent estrogens rather than 16α-hydroxylation. The lower level of 2-MeOE2 in the breast cancer group was believed to correlate with its protective effect against tumor formation. This study could provide valuable information on the association of the EM metabolic pathway with carcinogenesis as well as identify potential biomarkers for estrogen-induced breast cancer risk.