Early diagnosis of epithelial ovarian cancer (EOC) would significantly decrease the morbidity and mortality from this disease but is difficult in the absence of physical symptoms. Here, we report a blood test, based on the simultaneous quantization of four analytes (leptin, prolactin, osteopontin, and insulin-like growth factor-II), that can discriminate between disease-free and EOC patients, including patients diagnosed with stage I and II disease, with high efficiency (95%). Microarray analysis was used initially to determine the levels of 169 proteins in serum from 28 healthy women, 18 women newly diagnosed with EOC, and 40 women with recurrent disease. Evaluation of proteins that showed significant differences in expression between controls and cancer patients by ELISA assays yielded the four analytes. These four proteins then were evaluated in a blind cross-validation study by using an additional 106 healthy females and 100 patients with EOC (24 stage I͞II and 76 stage III͞IV). Upon sample decoding, the results were analyzed by using three different classification algorithms and a binary code methodology. The four-analyte test was further validated in a blind binary code study by using 40 additional serum samples from normal and EOC cancer patients. No single protein could completely distinguish the cancer group from the healthy controls. However, the combination of the four analytes exhibited the following: sensitivity 95%, positive predictive value (PPV) 95%, specificity 95%, and negative predictive value (NPV) 94%, a considerable improvement on current methodology.insulin-like growth factor-II ͉ leptin ͉ osteopontin ͉ prolactin E pithelial ovarian cancer (EOC) is the fourth leading cause of cancer-related death in women in the U.S. and the leading cause of gynecologic cancer death. EOC is characterized by few early symptoms, presentation at an advanced stage, and poor survival. Despite being one tenth as common as breast cancer, EOC is three times more lethal. This year Ϸ22,220 women will be newly diagnosed with ovarian cancer, and 16,210 will die from the disease (1). The high mortality rate is due to the difficulties with the early detection of ovarian cancer. Indeed, Ϸ80% of patients are diagnosed with advanced staged disease. In patients who are diagnosed with early disease (stage I or II), the 5-yr survival ranges from 60% to 90%, depending on the degree of tumor differentiation (2, 3). In patients with advanced disease, 80-90% will initially respond to chemotherapy, but Ͻ10-15% will remain in permanent remission (4). Although advances in treatment have led to an improved 5-yr survival rate approaching 45%, overall survival has not been enhanced (2, 5).Two alternative strategies have been reported for early detection by using serum biomarkers. One approach is the analysis of serum samples by mass spectrometry to find proteins or protein fragments of unknown identity that detect the presence͞absence of cancer (6-8). Alternatively, analysis of the presence͞absence͞abundance of known proteins͞peptides ...

Although hepatocellular carcinoma (HCC) has been subjected to continuous investigation and its symptoms are well known, early-stage diagnosis of this disease remains difficult and the survival rate after diagnosis is typically very low (3–5%). Early and accurate detection of metabolic changes in the sera of patients with liver cirrhosis can help improve the prognosis of HCC and lead to a better understanding of its mechanism at the molecular level, thus providing patients with in-time treatment of the disease. In this study, we compared metabolite levels in sera of 40 HCC patients and 49 cirrhosis patients from Egypt by using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (UPLC-QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from cirrhotic controls are selected by statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. The identities of some of the putative identifications are verified by comparing their MS/MS fragmentation patterns and retention times with those from authentic compounds. Finally, the serum samples are reanalyzed for quantitation of selected metabolites along with other metabolites previously selected as candidate biomarkers of HCC. This quantitation was performed using isotope dilution by selected reaction monitoring (SRM) on a triple quadrupole linear ion trap (QqQLIT) coupled to UPLC. Statistical analysis of the UPLC-QTOF data identified 274 monoisotopic ion masses with statistically significant differences in ion intensities between HCC cases and cirrhotic controls. Putative identifications were obtained for 158 ions by mass based search against databases. We verified the identities of selected putative identifications including glycholic acid (GCA), glycodeoxycholic acid (GDCA), 3beta, 6beta-dihydroxy-5beta-cholan-24-oic acid, oleoyl carnitine, and Phe-Phe. SRM-based quantitation confirmed significant differences between HCC and cirrhotic controls in metabolite levels of bile acid metabolites, long chain carnitines and small peptide. Our study provides useful insight into appropriate experimental design and computational methods for serum biomarker discovery using LC-MS/MS based metabolomics. This study has led to the identification of candidate biomarkers with significant changes in metabolite levels between HCC cases and cirrhotic controls. This is the first MS-based metabolic biomarker discovery study on Egyptian subjects that led to the identification of candidate metabolites that discriminate early stage HCC from patients with liver cirrhosis.

Natural products are chemical compounds or substances produced naturally by living organisms. With the development of modern technology, more and more plant extracts have been found to be useful to medical practice. Both micromolecules and macromolecules have been reported to have the ability to inhibit tumour progression, a novel weapon to fight cancer by targeting its 10 characteristic hallmarks. In this review, we focus on summarizing plant natural compounds and their derivatives with anti-tumour properties, into categories, according to their potential therapeutic strategies against different types of human cancer. Taken together, we present a well-grounded review of these properties, hoping to shed new light on discovery of novel anti-tumour therapeutic drugs from known plant natural sources.

Associating changes in protein levels with the onset of cancer has been widely investigated to identify clinically relevant diagnostic biomarkers. In the present study, we analyzed sera from 205 patients recruited in the U.S. and Egypt for biomarker discovery using label-free proteomic analysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We performed untargeted proteomic analysis of sera to identify candidate proteins with statistically significant differences between hepatocellular carcinoma (HCC) and patients with liver cirrhosis. We further evaluated the significance of 101 proteins in sera from the same 205 patients through targeted quantitation by multiple reaction monitoring (MRM) on a triple quadrupole mass spectrometer. This led to the identification of 21 candidate protein biomarkers that were significantly altered in both the U.S. and Egyptian cohorts. Among the 21 candidates, 10 were previously reported as HCC-associated proteins (eight exhibiting consistent trends with our observation), whereas 11 are new candidates discovered by this study. Pathway analysis based on the significant proteins reveals up-regulation of the complement and coagulation cascades pathway and down-regulation of the antigen processing and presentation pathway in HCC cases versus patients with liver cirrhosis. The results of this study demonstrate the power of combining untargeted and targeted quantitation methods for a comprehensive serum proteomic analysis, to evaluate changes in protein levels and discover novel diagnostic biomarkers.