Induction of cell death and inhibition of cell survival are the main principles of cancer therapy. Resistance to chemotherapeutic agents is a major problem in oncology, which limits the effectiveness of anticancer drugs. A variety of factors contribute to drug resistance, including host factors, specific genetic or epigenetic alterations in the cancer cells and so on. Although various mechanisms by which cancer cells become resistant to anticancer drugs in the microenvironment have been well elucidated, how to circumvent this resistance to improve anticancer efficacy remains to be defined. Autophagy, an important homeostatic cellular recycling mechanism, is now emerging as a crucial player in response to metabolic and therapeutic stresses, which attempts to maintain/restore metabolic homeostasis through the catabolic lysis of excessive or unnecessary proteins and injured or aged organelles. Recently, several studies have shown that autophagy constitutes a potential target for cancer therapy and the induction of autophagy in response to therapeutics can be viewed as having a prodeath or a prosurvival role, which contributes to the anticancer efficacy of these drugs as well as drug resistance. Thus, understanding the novel function of autophagy may allow us to develop a promising therapeutic strategy to enhance the effects of chemotherapy and improve clinical outcomes in the treatment of cancer patients.

A LC-MS based method, which utilizes both reversed-performance (RP) chromatography and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of renal cell carcinoma (RCC) patients and healthy controls. The HILIC was found necessary for a comprehensive serum metabonomic profiling as well as RP separation. The feasibility of using serum metabonomics for the diagnosis and staging of RCC has been evaluated. One-hundred percent sensitivity in detection has been achieved, and a satisfactory clustering between the early stage and advanced-stage patients is observed. The results suggest that the combination of LC-MS analysis with multivariate statistical analysis can be used for RCC diagnosis and has potential in the staging of RCC. The MS/MS experiments have been carried out to identify the biomarker patterns that made great contribution to the discrimination. As a result, 30 potential biomarkers for RCC are identified. It is possible that the current biomarker patterns are not unique to RCC but just the result of any malignancy disease. To further elucidate the pathophysiology of RCC, related metabolic pathways have been studied. RCC is found to be closely related to disturbed phospholipid catabolism, sphingolipid metabolism, phenylalanine metabolism, tryptophan metabolism, fatty acid beta-oxidation, cholesterol metabolism, and arachidonic acid metabolism.

The purpose of this study was to use metabonomic profiling to identify a potential specific biomarker pattern in urine as a noninvasive bladder cancer (BC) detection strategy. A liquid chromatography-mass spectrometry based method, which utilized both reversed phase liquid chromatography and hydrophilic interaction chromatography separations, was performed, followed by multivariate data analysis to discriminate the global urine profiles of 27 BC patients and 32 healthy controls. Data from both columns were combined, and this combination proved to be effective and reliable for partial least squares-discriminant analysis. Following a critical selection criterion, several metabolites showing significant differences in expression levels were detected. Receiver operating characteristic analysis was used for the evaluation of potential biomarkers. Carnitine C9:1 and component I, were combined as a biomarker pattern, with a sensitivity and specificity up to 92.6% and 96.9%, respectively, for all patients and 90.5% and 96.9%, respectively for lowgrade BC patients. Metabolic pathways of component I and carnitine C9:1 are discussed. These results indicate that metabonomics is a practicable tool for BC diagnosis given its high efficacy and economization. The combined biomarker pattern showed better performance than single metabolite in discriminating bladder cancer

Bladder cancer (BC) and kidney cancer (KC) are the first two commonly occurring genitourinary cancers in China. In this study, a comprehensive LC-MS-based method, which utilizes both reversed phase liquid chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of BC, KC, and noncancer controls. An independent test set consisting of different patients has been used to objectively evaluate the predictive ability of the analysis platform. Excellent sensitivity and specificity have been achieved in detection of KC and BC. The results suggest that serum metabolic profiling could be used for different types of genitourinary cancer diagnosis. Furthermore, cancer type-specific biomarkers were found through a critical selection criterion. As a result, eicosatrienol, azaprostanoic acid, docosatrienol, retinol, and 14'-apo-beta-carotenal  were found as specific biomarkers for BC; and PE(P-16:0e/0:0), glycerophosphorylcholine, ganglioside GM3 (d18:1/22:1), C17 sphinganine, and SM(d18:0/16:1(9Z)) were found as specific biomarkers for KC. Receiver operating characteristic (ROC) analysis was used for the preliminary evaluation of the biomarkers. These biomarkers have great potential to be used in the clinical diagnosis after further rigorous assessment.

Nano-CaCO 3 /polypropylene (PP) composites modified with polypropylene grafted with acrylic acid (PP-g-AA) or acrylic acid with and without dicumyl peroxide (DCP) were prepared by a twin-screw extruder. The crystallization and melting behavior of PP in the composites were investigated by DSC. The experimental results showed that the crystallization temperature of PP in the composites increased with increasing nano-CaCO 3 content. Addition of PP-g-AA further increased the crystallization temperatures of PP in the composites. It is suggested that PP-g-AA could improve the nucleation effect of nano-CaCO 3 . However, the improvement in the nucleation effect of nano-CaCO 3 would be saturated when the PP-g-AA content of 5 phf (parts per hundred based on weight of filler) was used. The increase in the crystallization temperature of PP was observed by adding AA into the composites and the crystallization temperature of the composites increased with increasing AA content. It is suggested that the AA reacted with nano-CaCO 3 and the formation of Ca(AA) 2 promoted the nucleation of PP. In the presence of DCP, the increment of the AA content had no significant influence on the crystallization temperature of PP in the composites.

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