Gene Signatures of Progression and Metastasis in Renal Cell Cancer

Jones, J. R.; Otu, Hasan H.; Spentzos, Dimitrios; Kolia, Shakirahmed; Blaheta, Roman A.; Jonas, Dietger; Libermann, Towia A.

doi:10.1055/s-2006-947390

Cited by 28 publications

(46 citation statements)

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“…In the present study, we performed microarray-based screening of prognostic markers for conventional RCC. To our knowledge, Wve groups have previously reported gene signatures that deWned RCC outcome based on transcriptional gene expression proWling (Takahashi et al 2001;Vasselli et al 2003;Jones et al 2005;Kosari et al 2005;Sultmann et al 2005). Strikingly, there is almost no overlap among each set of signiWcant genes identiWed in these studies.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, several studies have reported a set of genes that is associated with RCC prognosis (Takahashi et al 2001;Vasselli et al 2003;Jones et al 2005;Kosari et al 2005;Sultmann et al 2005). However, the routine use of microarrays for predicting the RCC outcome is impractical because microarray facilities are expensive and are not commonly available.…”

Section: Introductionmentioning

confidence: 99%

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Microarray-based identification of CUB-domain containing protein 1 as a potential prognostic marker in conventional renal cell carcinoma

Awakura

Nakamura

Takahashi

et al. 2008

J Cancer Res Clin Oncol

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Microarray-based identification of CUB-domain containing protein 1 as a potential prognostic marker in conventional renal cell carcinoma

Awakura

Nakamura

Takahashi

et al. 2008

J Cancer Res Clin Oncol

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“…DNA microarray analysis of human tumor specimens to identify metastasis-related genes has been reported in several types of cancers [20,[25][26][27][28]. Recently, Roepman et al identified 102 genes in primary tumors as an expression profile for prediction of lymph node metastases from primary SCCHN tumors [29].…”

Section: Rbmentioning

confidence: 99%

Understanding metastatic SCCHN cells from unique genotypes to phenotypes with the aid of an animal model and DNA microarray analysis

Zhang

Pirani

et al. 2006

Clin Exp Metastasis

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Metastasis of squamous cell carcinoma of the head and neck (SCCHN) is a significant health-care problem worldwide. The 5-year survival rate is less than 50% for patients with lymph node metastases. Understanding the molecular basis of SCCHN metastasis would facilitate the development of new therapeutic approaches to the disease. To identify proteins that mediate SCCHN metastasis, we established a SCCHN xenograft mouse model and performed in vivo selection from a SCCHN cell line using the model. In the fourth round of in vivo selection, significant incidences of metastases in lymph nodes (7/10) and lungs (6/10) were achieved from a derived SCCHN cell line as compared with its parental cells, 1/5 in lymph nodes and 0/5 in lungs. Metastatic cell lines from lymph node metastases and parental cell lines from non-metastatic xenograft tumors were subjected to DNA microarray analysis using an Affymetrix gene chip HG-U133A, followed by data mining studies. The identified metastasis-related genes were further evaluated for their encoding protein products and the metastatic cells were examined by biological analyses. DNA microarray analysis highlighted molecular features of the metastatic SCCHN cells, including alteration of expression of cell-cell adhesion proteins, epithelial cell markers, apoptosis and cell cycle regulatory molecules. Further biological analyses of phenotypic alterations revealed that the metastatic cells gained epithelial-mesenchymal transition (EMT) features and were more resistant to anoikis, which are two of the important phenotypes for metastatic SCCHN.

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“…In recent years, researchers have shifted focus from tumor-specific markers toward tissue-specific markers, as they seek to take advantage of the differential gene expression of HNSCC cells and other tissues [14,15]. DNA microarray analysis of human tumor specimens to identify tumor cell-related genes has been reported in several types of cancers [16][17][18]. Roepman et al [19] identified 102 genes in primary tumors as an expression profile for prediction of lymph node metastases from primary HNSCC tumors.…”

Section: Discussionmentioning

confidence: 99%

Gene expression analysis of SCC tumor cells in muscle tissue

Hundt

Yuh

Burbelko

et al. 2011

Eur Arch Otorhinolaryngol

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The purpose of this study was to evaluate microarray technology of HNSCC cells in muscle tissue. 200 SCCVII tumor cells were injected intramuscularly into the right flank of ten C3H/Km mice each. One week later the animals were killed and the tissue taken out. Histology (H&E staining) and microarray of the tissue were performed. Histology showed a few tumor cells between the muscle fibers. Microarray technology showed different gene expression pattern of the muscle tissue with SCCVII cells in comparison with normal muscle tissue. Only those genes showing a fold change difference of 5 or higher were considered. Gene expression analysis revealed changes in the expression levels of SCCVII cells in muscle tissue in 220 genes. Significant gene expression differences between SCCVII cells in muscle tissue and pure muscle tissue could be seen.

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Gene Signatures of Progression and Metastasis in Renal Cell Cancer

Cited by 28 publications

References 0 publications

Microarray-based identification of CUB-domain containing protein 1 as a potential prognostic marker in conventional renal cell carcinoma

Microarray-based identification of CUB-domain containing protein 1 as a potential prognostic marker in conventional renal cell carcinoma

Understanding metastatic SCCHN cells from unique genotypes to phenotypes with the aid of an animal model and DNA microarray analysis

Gene expression analysis of SCC tumor cells in muscle tissue

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