Lisa X. Xu

Serum Metabolite Profiling of Human Colorectal Cancer Using GC−TOFMS and UPLC−QTOFMS

Colorectal carcinogenesis involves the overexpression of many immediate-early response genes associated with growth and inflammation, which significantly alters downstream protein synthesis and small-molecule metabolite production. We have performed a serum metabolic analysis to test the hypothesis that the distinct metabolite profiles of malignant tumors are reflected in biofluids. In this study, we have analyzed the serum metabolites from 64 colorectal cancer (CRC) patients and 65 healthy controls using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and Acquity ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (Acquity UPLC-QTOFMS). Orthogonal partial least-squares discriminate analysis (OPLS-DA) models generated from GC-TOFMS and UPLC-QTOFMS metabolic profile data showed robust discrimination from CRC patients and healthy controls. A total of 33 differential metabolites were identified using these two analytical platforms, five of which were detected in both instruments. These metabolites potentially reveal perturbation of glycolysis, arginine and proline metabolism, fatty acid metabolism and oleamide metabolism, associated with CRC morbidity. These results suggest that serum metabolic profiling has great potential in detecting CRC and helping to understand its underlying mechanisms.

Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignancy in the world with high morbidity and mortality rate. Identification of novel biomarkers in HCC remains impeded primarily because of the heterogeneity of the disease in clinical presentations as well as the pathophysiological variations derived from underlying conditions such as cirrhosis and steatohepatitis. The aim of this study is to search for potential metabolite biomarkers of human HCC using serum and urine metabolomics approach. Sera and urine samples were collected from patients with HCC (n = 82), benign liver tumor patients (n = 24), and healthy controls (n = 71). Metabolite profiling was performed by gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography-quadrupole time of flight mass spectrometry in conjunction with univariate and multivariate statistical analyses. Forty three serum metabolites and 31 urinary metabolites were identified in HCC patients involving several key metabolic pathways such as bile acids, free fatty acids, glycolysis, urea cycle, and methionine metabolism. Differentially expressed metabolites in HCC subjects, such as bile acids, histidine, and inosine are of great statistical significance and high fold changes, which warrant further validation as potential biomarkers for HCC. However, alterations of several bile acids seem to be affected by the condition of liver cirrhosis and hepatitis. Quantitative measurement and comparison of seven bile acids among benign liver tumor patients with liver cirrhosis and hepatitis, HCC patients with liver cirrhosis and hepatitis, HCC patients without liver cirrhosis and hepatitis, and healthy controls revealed that the abnormal levels of glycochenodeoxycholic acid, glycocholic acid, taurocholic acid, and chenodeoxycholic acid are associated with liver cirrhosis and hepatitis. HCC patients with alpha fetoprotein values lower than 20 ng/ml was successfully differentiated from healthy controls with an accuracy of 100% using a panel of metabolite markers. Our work shows that metabolomic profiling approach is a promising screening tool for the diagnosis and stratification of HCC patients.

Urinary metabonomic study on colorectal cancer.

After our serum metabonomic study of colorectal cancer (CRC) patients recently published in J. Proteome Res., we profiled urine metabolites from the same group of CRC patients (before and after surgical operation) and 63 age-matched healthy volunteers using gas chromatography-mass spectrometry (GC-MS) in conjunction with a multivariate statistics technique. A parallel metabonomic study on a 1,2-dimethylhydrazine (DMH)-treated Sprague-Dawley rat model was also performed to identify significantly altered metabolites associated with chemically induced precancerous colorectal lesion. The orthogonal partial least-squares-discriminant analysis (OPLS-DA) models of metabonomic results demonstrated good separations between CRC patients or DMH-induced model rats and their healthy counterparts. The significantly increased tryptophan metabolism, and disturbed tricarboxylic acid (TCA) cycle and the gut microflora metabolism were observed in both the CRC patients and the rat model. The urinary metabolite profile of postoperative CRC subjects altered significantly from that of the preoperative stage. The significantly down-regulated gut microflora metabolism and TCA cycle were observed in postoperative CRC subjects, presumably due to the colon flush involved in the surgical procedure and weakened physical conditions of the patients. The expression of 5-hydroxytryptophan significantly decreased in postsurgery samples, suggesting a recovered tryptophan metabolism toward healthy state. Abnormal histamine metabolism and glutamate metabolism were found only in the urine samples of CRC patients, and the abnormal polyamine metabolism was found only in the rat urine. This study assessed the important metabonomic variations in urine associated with CRC and, therefore, provided baseline information complementary to serum/plasma and tissue metabonomics for the complete elucidation of the underlying metabolic mechanisms of CRC.

Distinct urinary metabolic profile of human colorectal cancer.

A full spectrum of metabolic aberrations that are directly linked to colorectal cancer (CRC) at early curable stages is critical for developing and deploying molecular diagnostic and therapeutic approaches that will significantly improve patient survival. We have recently reported a urinary metabonomic profiling study on CRC subjects (n = 60) and health controls (n = 63), in which a panel of urinary metabolite markers was identified. Here, we report a second urinary metabonomic study on a larger cohort of CRC (n = 101) and healthy subjects (n = 103), using gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Consistent with our previous findings, we observed a number of dysregulated metabolic pathways, such as glycolysis, TCA cycle, urea cycle, pyrimidine metabolism, tryptophan metabolism, polyamine metabolism, as well as gut microbial-host co-metabolism in CRC subjects. Our findings confirm distinct urinary metabolic footprints of CRC patients characterized by altered levels of metabolites derived from gut microbial-host co-metabolism. A panel of metabolite markers composed of citrate, hippurate, p-cresol, 2-aminobutyrate, myristate, putrescine, and kynurenate was selected, which was able to discriminate CRC subjects from their healthy counterparts. A receiver operating characteristic curve (ROC) analysis of these markers resulted in an area under the receiver operating characteristic curve (AUC) of 0.993 and 0.998 for the training set and the testing set, respectively. These potential metabolite markers provide a novel and promising molecular diagnostic approach for the early detection of CRC.

Metabonomics identifies serum metabolite markers of colorectal cancer.

Recent studies suggest that biofluid-based metabonomics may identify metabolite markers promising for colorectal cancer (CRC) diagnosis. We report here a follow-up replication study, after a previous CRC metabonomics study, aiming to identify a distinct serum metabolic signature of CRC with diagnostic potential. Serum metabolites from newly diagnosed CRC patients (N = 101) and healthy subjects (N = 102) were profiled using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS). Differential metabolites were identified with statistical tests of orthogonal partial least-squares-discriminant analysis (VIP > 1) and the Mann-Whitney U test (p < 0.05). With a total of 249 annotated serum metabolites, we were able to differentiate CRC patients from the healthy controls using an orthogonal partial least-squares-discriminant analysis (OPLS-DA) in a learning sample set of 62 CRC patients and 62 matched healthy controls. This established model was able to correctly assign the rest of the samples to the CRC or control groups in a validation set of 39 CRC patients and 40 healthy controls. Consistent with our findings from the previous study, we observed a distinct metabolic signature in CRC patients including tricarboxylic acid (TCA) cycle, urea cycle, glutamine, fatty acids, and gut flora metabolism. Our results demonstrated that a panel of serum metabolite markers is of great potential as a noninvasive diagnostic method for the detection of CRC.

A distinct metabolic signature of human colorectal cancer with prognostic potential.

Purpose: Metabolic phenotyping has provided important biomarker findings, which, unfortunately, are rarely replicated across different sample sets due to the variations from different analytical and clinical protocols used in the studies. To date, very few metabolic hallmarks in a given cancer type have been confirmed and validated by use of a metabolomic approach and other clinical modalities. Here, we report a metabolomics study to identify potential metabolite biomarkers of colorectal cancer with potential theranostic value. Experimental Design: Gas chromatography–time-of-flight mass spectrometry (GC–TOFMS)–based metabolomics was used to analyze 376 surgical specimens, which were collected from four independent cohorts of patients with colorectal cancer at three hospitals located in China and City of Hope Comprehensive Cancer Center in the United States. Differential metabolites were identified and evaluated as potential prognostic markers. A targeted transcriptomic analysis of 29 colorectal cancer and 27 adjacent nontumor tissues was applied to analyze the gene expression levels for key enzymes associated with these shared metabolites. Results: A panel of 15 significantly altered metabolites was identified, which demonstrates the ability to predict the rate of recurrence and survival for patients after surgery and chemotherapy. The targeted transcriptomic analysis suggests that the differential expression of these metabolites is due to robust metabolic adaptations in cancer cells to increased oxidative stress as well as demand for energy, and macromolecular substrates for cell growth and proliferation. Conclusions: These patients with colorectal cancer, despite their varied genetic background, mutations, pathologic stages, and geographic locations, shared a metabolic signature that is of great prognostic and therapeutic potential. Clin Cancer Res; 20(8); 2136–46. ©2014 AACR.

Identification of EFEMP2 as a serum biomarker for the early detection of colorectal cancer with lectin affinity capture assisted secretome analysis of cultured fresh tissues.

Early diagnosis plays a decisive role in the outcome of colorectal cancer (CRC) therapy. The ex vivo culture of fresh CRC tissues and paired normal colorectal tissues provides a feasible way to explore potential serum biomarkers for CRC early detection under near-physiological conditions. In the present work, we applied a lectin affinity based approach to enrich and increase the detection number of secreted proteins in the conditioned media of cultured tissues. The captured proteins were then analyzed by the proteomic strategy of one-dimensional gel electrophoresis coupled to liquid chromatography-tandem mass spectrometry. By quantification with label-free spectral counting, we found 123 differentially expressed secreted proteins (DESPs) with 68 DESPs up-regulated in CRC tissues. EFEMP2, one of the top 10 up-regulated DESPs, was further validated by immunohistochemistry at tissue level and enzyme-linked immunosorbent assay at serum level. We found the expression level of EFEMP2 was dramatically increased in CRC patients, even at the early stage. Moreover, the diagnostic accuracy of EFEMP2 was superior to the established CRC biomarker carcinoembryonic antigen evidenced by the area under the receiver operating characteristic curve for the two biomarkers were 0.923 and 0.728, respectively. These results indicated EFEMP2 is a promising serum biomarker for CRC early detection.

Discovery of IL-18 as a novel secreted protein contributing to doxorubicin resistance by comparative secretome analysis of MCF-7 and MCF-7/Dox.

Background Resistance to chemotherapy is the major cause of failure in breast cancer treatment. Recent studies suggest that secreted proteins may play important roles in chemoresistance. We sought to systematically characterize secreted proteins associated with drug resistance, which may represent potential serum biomarkers or novel drug targets. Methodology/Principal Findings In the present work, we adopted the proteomic strategy of one-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry to compare the secretome of MCF-7 and doxorubicin-resistant MCF-7/Dox. A total of 2,084 proteins were identified with at least two unique peptides in the conditioned media of two cell lines. By quantification with label-free spectral counting, 89 differentially expressed secreted proteins (DESPs) between the two cell lines were found. Among them, 57 DESPs were first found to be related to doxorubicin resistance in this work, including 24 extracellular matrix related proteins, 2 cytokines and 31 unclassified proteins. We focused on 13 novel DESPs with confirmed roles in tumor metastasis. Among them, the elevated expression of IL-18 in doxorubicin-resistant cell lines and breast tumor tissues was validated and its role in doxorubicin resistance was further confirmed by cell viability experiments in the presence or absence of this protein. Conclusions/Significance Comparative analysis of the secretome of MCF-7 and MCF-7/Dox identified novel secreted proteins related to chemotherapy resistance. IL-18 was further validated to contribute to doxorubicin resistance, in addition to its confirmed role in breast cancer metastasis. Due to its dual roles in both drug resistance and tumor metastasis, IL-18 may represent a useful drug target for breast cancer therapy.

Differential secretome analysis reveals CST6 as a suppressor of breast cancer bone metastasis

Bone metastasis is a frequent complication of breast cancer and a common cause of morbidity and mortality from the disease. During metastasis secreted proteins play crucial roles in the interactions between cancer cells and host stroma. To characterize the secreted proteins that are associated with breast cancer bone metastasis, we preformed a label-free proteomic analysis to compare the secretomes of four MDA-MB-231 (MDA231) derivative cell lines with varied capacities of bone metastasis. A total of 128 proteins were found to be consistently up-/down-regulated in the conditioned medium of bone-tropic cancer cells. The enriched molecular functions of the altered proteins included receptor binding and peptidase inhibition. Through additional transcriptomic analyses of breast cancer cells, we selected cystatin E/M (CST6), a cysteine protease inhibitor down-regulated in bone-metastatic cells, for further functional studies. Our results showed that CST6 suppressed the proliferation, colony formation, migration and invasion of breast cancer cells. The suppressive function against cancer cell motility was carried out by cancer cell-derived soluble CST6. More importantly, ectopic expression of CST6 in cancer cells rescued mice from overt osteolytic metastasis and deaths in the animal study, while CST6 knockdown markedly enhanced cancer cell bone metastasis and shortened animal survival. Overall, our study provided a systemic secretome analysis of breast cancer bone tropism and established secreted CST6 as a bona fide suppressor of breast cancer osteolytic metastasis.

Comparative serum proteome analysis of human lymph node negative/positive invasive ductal carcinoma of the breast and benign breast disease controls via label-free semiquantitative shotgun technology.

Serum proteomics provides a useful tool to identify potential biomarkers associated with cancer progression. In the present study, a two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) on a linear ion trap was utilized to identify and compare serum proteins from breast cancer patients. Three groups of 21 human sera, 7 from patients with lymph node-negative invasive ductal carcinoma (IDCB), 7 from patients with lymph node-positive IDCB, and 7 controls from patients with benign breast diseases, were analyzed. Through proteomic analysis, a total of 2,078 proteins were identified with at least two unique peptide hits. By quantification with label-free spectral counting, a fruitful list of serum proteins with significant differences in abundance accompanying the progression of breast cancer was found. Through hierarchical cluster analysis based on the differently expressed proteins in selection, we found that different groups of sera could be distinguished. Among the selected proteins, tenascin-XB (TNXB) was further validated by the ELISA method in 131 serum samples as a promising biomarker for early metastasis of breast cancer. These experiments revealed the valuable potential of label-free quantitative 2D-LC-MS/MS for identification of novel biomarkers for disease progression.