The role of death receptor 5 (DR5), a well-known cell surface pro-apoptotic protein, in the negative regulation of invasion and metastasis of human cancer cells and the underlying mechanisms are largely unknown and were hence the focus of this study. In this report, we have demonstrated that DR5 functions to suppress invasion and metastasis of human cancer cells, as evidenced by enhanced cancer cell invasion and metastasis upon genetic suppression of DR5 either by gene knockdown or knockout. When DR5 is suppressed, FADD and caspase-8 may recruit and stabilize TRAF2 to form a metastasis and invasion signaling complex, resulting in activation of ERK and JNK/AP-1 signaling that mediate the elevation and activation of matrix metalloproteinase-1 (MMP1) and eventual promotion of cancer invasion and metastasis. Our findings thus highlight a novel non-apoptotic function of DR5 as a suppressor of human cancer cell invasion and metastasis and suggest a basic working model elucidating the underlying biology.
The oxidative pentose phosphate pathway (PPP) contributes to tumour growth, but the precise contribution of 6-phosphogluconate dehydrogenase (6PGD), the third enzyme in this pathway, to tumorigenesis remains unclear. We found that suppression of 6PGD decreased lipogenesis and RNA biosynthesis and elevated ROS levels in cancer cells, attenuating cell proliferation and tumour growth. 6PGD-mediated production of ribulose-5-phosphate (Ru-5-P) inhibits AMPK activation by disrupting the active LKB1 complex, thereby activating acetyl-CoA carboxylase 1 and lipogenesis. Ru-5-P and NADPH are thought to be precursors in RNA biosynthesis and lipogenesis, respectively; thus, our findings provide an additional link between the oxidative PPP and lipogenesis through Ru-5-P-dependent inhibition of LKB1-AMPK signalling. Moreover, we identified and developed 6PGD inhibitors, physcion and its derivative S3, that effectively inhibited 6PGD, cancer cell proliferation and tumour growth in nude mice xenografts without obvious toxicity, suggesting that 6PGD could be an anticancer target.
Hyperspectral imaging (HSI) is an emerging modality for medical applications and holds great potential for noninvasive early detection of cancer. It has been reported that early cancer detection can improve the survival and quality of life of head and neck cancer patients. In this paper, we explored the possibility of differentiating between premalignant lesions and healthy tongue tissue using hyperspectral imaging in a chemical induced oral cancer animal model. We proposed a novel classification algorithm for cancer detection using hyperspectral images. The method detected the dysplastic tissue with an average area under the curve (AUC) of 0.89. The hyperspectral imaging and classification technique may provide a new tool for oral cancer detection.
Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.
Despite widespread interest in chemoprevention and therapy due to the high margin of safety of dietary natural compounds, clinical intervention with single agents has failed to yield the expected outcomes, mostly due to poor bioavailability and low potency. Combinations of natural agents with synergistic effects are gaining increasing attention. In the present study, in vitro and in vivo antitumor effects of a combination of two natural dietary agents, green tea epigallocatechin gallate (EGCG) and resveratrol were investigated. It was revealed that their combination at low doses (at which single agents induce minimal apoptosis) synergistically increased apoptosis (combination index <1) in head and neck cancer cell lines. Synergistic apoptosis was also supported by caspase-3 and PARP cleavage. The combination also significantly inhibited growth of xenografted head and neck tumors in nude mice as supported by significant inhibition of tumor volume, tumor weight and Ki67 expression, and increase in TUNEL-positive cells. Mechanistic studies revealed that the combination inhibited AKT-mTOR signaling both in vitro and in vivo. In addition, overexpression of constitutively active AKT protected cells from apoptosis induced by the combination of EGCG and resveratrol. Collectively, the present results for the first time suggest that the combination of EGCG and resveratrol has synergistic growth inhibitory effects and provide an important rationale for future clinical development for chemoprevention and treatment of head and neck cancer.
As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management.
The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.
Background
Epidermal growth factor receptor (EGFR) has been reported to downregulate E-cadherin (E-cad); however, whether the downregulation of E-cad has any effect on EGFR expression has not been elucidated. Our previous studies have found an inverse correlation between EGFR and E-cad expression in tissue specimens of squamous cell carcinoma of the head and neck (SCCHN). To understand the biological mechanisms underlying this clinical observation, we knocked down E-cad expression utilizing E-cad siRNA in four SCCHN cell lines.
Results
It was observed that downregulation of E-cad upregulated EGFR expression compared with control siRNA-transfected cells after 72 hours. Cellular membrane localization of EGFR was also increased. Consequently, downstream signaling molecules of the EGFR signaling pathway, p-AKT, and p-ERK, were increased at 72 hours after the transfection with E-cad siRNA. Reverse transcriptase-polymerase chain reaction (RT-PCR) showed EGFR mRNA was upregulated by E-cad siRNA as early as 24 hours. In addition, RT-PCR revealed this upregulation was due to the increase of EGFR mRNA stability, but not protein stability. Sulforhodamine B (SRB) assay indicated growth of E-cad knocked down cells was enhanced up to 2-fold more than that of control siRNA-transfected cells at 72-hours post-transfection. The effect of E-cad reduction on cell proliferation was blocked by treating the E-cad siRNA-transfected cells with 1 μM of the EGFR-specific tyrosine kinase inhibitor erlotinib.
Conclusion
Our results suggest for the first time that reduction of E-cad results in upregulation of EGFR transcriptionally. It also suggests that loss of E-cad may induce proliferation of SCCHN by activating EGFR and its downstream signaling pathways.
Patient-derived xenograft (PDX) models for cancer research have recently attracted considerable attention in both the academy and industry (Hidalgo et al., 2014; Wilding and Bodmer, 2014). PDX models have been developed from different tumor types including lung cancer to improve the drug development process. These models are used for pre-clinical drug evaluation and can be used for the predictive results of clinical outcomes because they conserve original tumor characteristics such as heterogeneity, complexity and molecular diversity (Kopetz et al., 2012). Additionally, PDX model provides the potential tool for the personalized drug therapy. In this protocol, we present methods for the establishment of PDX in mice using primary tumor tissues from patients with small cell lung cancer (SCLC).
BACKGROUND: p16 overexpression is a highly sensitive yet moderately specific biomarker for predicting human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC). Nuclear β-catenin translocation has been linked to HPV-positive OPSCC. However, whether the strategy of combining β-catenin with p16 can better predict HPV-associated OPSCC remains unknown. METHODS: We evaluated the expression of p16 and β-catenin (nuclear and membrane) by immunohistochemistry staining in 101 OPSCC tissues and HPV status by HPV DNA in situ hybridization. Logistic regression models were used to evaluate single or multiple biomarkers for HPV prediction. The prediction power, sensitivity, and specificity were determined by receiver operating characteristic (ROC) analyses. RESULTS: Our data showed that upon univariate analysis, p16 and nuclear β-catenin were positively correlated with HPV status, while membrane β-catenin was inversely correlated with HPV status (P < 0.01). p16 showed the highest HPV predictive power, with area under the curve (AUC) of 0.9074 compared to 0.6762 for nuclear β-catenin and 0.7635 for membrane β-catenin, respectively, indicating differential accuracies for HPV prediction. Multivariable analysis showed that p16 was significantly correlated with HPV, while nuclear and membrane β-catenin showed marginal significance. The three-biomarker model was similarly sensitive (98.9% vs. 100%) but more specific (88.9% vs. 81%) than p16 alone, which also showed a good predictive value for overall (P = 0.0002) survival and disease-free (P = 0.0158) survival. CONCLUSION: Our study suggests a novel model of combining p16 and subcellular β-catenin for prediction of HPV-associatred OPSCC, and this finding deserves further validation.