We investigated the roles of interleukin-6 (IL-6) and parathyroid hormone-related peptide (PTHrP) in oral squamous cell carcinoma (OSCC)-induced osteoclast formation. Microarray analyses performed on 43 human OSCC specimens revealed that many of the specimens overexpressed PTHrP mRNA, but a few overexpressed IL-6 mRNA. Immunohistochemical analysis revealed that IL-6 was expressed not only in cancer cells but also in fibroblasts and osteoclasts at the tumor-bone interface. Bone invasion by various malignant tumors causes diverse complications in patients. In the case of oral cancers, such invasion leads to physical damage of the bone and has a critical influence on patient prognosis.
An accurate assessment of the cervical lymph node metastasis status in oral cavity cancer not only helps predict the prognosis of patients, but also helps surgeons to perform the appropriate treatment. We investigated the utilization of microarray technology focusing on the differences in gene expression profiles between primary tumors of oral squamous cell carcinoma that had metastasized to cervical lymph nodes and those that had not metastasized in the hope of finding new biomarkers to serve for diagnosis and treatment of oral cavity cancer. To design this experiment, we prepared two groups: the learning case group with 30 patients and the test case group with 13 patients. All tissue samples were performed using laser captured microdissection to yield cancer cells, and RNA was isolated from purified cancer cells. To identify a predictive gene expression signature, the different gene expressions between the two groups with and without metastasis in the learning case (n = 30) were analyzed, and the 85 genes expressed differentially were selected. Subsequently, to construct a more accurate prediction model, we further selected the genes with a high power for prediction from the 85 genes using the AdaBoost algorithm. The eight candidate genes, DCTD, IL-15, THBD, GSDML, SH3GL3, PTHLH, RP5-1022P6 and C9orf46, were selected to achieve the minimum error rate. Quantitative reverse transcription-polymerase chain reaction was carried out to validate the selected genes. From these statistical methods, the prediction model was constructed including the eight genes and this model was evaluated by using the test case group. The results in 12 of 13 cases (∼ ∼ ∼ ∼92.3%) were predicted correctly. (Cancer Sci 2007; 98: [740][741][742][743][744][745][746]
Evasion from apoptotic cell death is a characteristic of cancer; genes that modulate this process may be optimal for therapeutic attack. Identifying key regulators of apoptosis is thus a central goal in cancer therapy. Here, we describe a loss-of-function screen that uses RNA interference libraries to identify genes required for induction of apoptosis. We used a short-hairpin RNA expressing vector with high gene-expression silencing activity that contained fetal brain cDNAs. Survived cells from genotoxic stress were isolated to determine knock-down of molecules that are crucial for induction of apoptosis. We identified TBP-associated factor 1 (TAF1), a gene previously implicated as an essential component of transcription machinery. Depletion of TAF1 was associated with substantial attenuation of apoptosis induced by oxidative as well as genotoxic stress. Microarray analysis further demonstrated that a number of genes were transcriptionally declined in cells silenced for TAF1. Surprisingly, knocking down TAF1 exhibited a marked decrease in p27Kip1 expression, allowing cells resistant from oxidative stress-induced apoptosis. These results suggest that TAF1 regulates apoptosis by controlling p27Kip1 expression. Our system provides a novel approach to identifying candidate genes that modulate apoptosis.
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