scholarly journals Gene networks in basal cell carcinoma of the eyelid, analyzed using gene expression profiling

2018 ◽  
Author(s):  
Tatsuya Yunoki ◽  
Yoshiaki Tabuchi ◽  
Tetsushi Hirano ◽  
Shigeharu Miwa ◽  
Johji Imura ◽  
...  
Keyword(s):  
Gene Expression ◽  
Basal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Gene Expression Profiling ◽  
Basal Cell ◽  
Expression Profiling ◽  
Gene Networks

Molecular classification of basal cell carcinoma of skin by gene expression profiling

2014 ◽  
Vol 54 (12) ◽  
pp. 1605-1612 ◽  
Author(s):  
Byul A. Jee ◽  
Hyoseob Lim ◽  
So Mee Kwon ◽  
Yuna Jo ◽  
Myong Chul Park ◽  
...  
Keyword(s):  
Gene Expression ◽  
Basal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Gene Expression Profiling ◽  
Basal Cell ◽  
Expression Profiling ◽  
Molecular Classification

scholarly journals Methyltransferases in the Pathogenesis of Keratinocyte Cancers

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3402
Author(s):  
Eun Kyung Ko ◽  
Brian C. Capell
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Basal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Basal Cell ◽  
Histone Methylation ◽  
Cutaneous Squamous Cell Carcinoma ◽  
Therapeutic Approaches ◽  
Novel Therapeutic

Recent evidence suggests that the disruption of gene expression by alterations in DNA, RNA, and histone methylation may be critical contributors to the pathogenesis of keratinocyte cancers (KCs), made up of basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), which collectively outnumber all other human cancers combined. While it is clear that methylation modifiers are frequently dysregulated in KCs, the underlying molecular and mechanistic changes are only beginning to be understood. Intriguingly, it has recently emerged that there is extensive cross-talk amongst these distinct methylation processes. Here, we summarize and synthesize the latest findings in this space and highlight how these discoveries may uncover novel therapeutic approaches for these ubiquitous cancers.

scholarly journals Assessing Various Control Samples for Microarray Gene Expression Profiling of Laryngeal Squamous Cell Carcinoma

Biomolecules ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 588
Author(s):  
Adam Ustaszewski ◽  
Magdalena Kostrzewska-Poczekaj ◽  
Joanna Janiszewska ◽  
Malgorzata Jarmuz-Szymczak ◽  
Malgorzata Wierzbicka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Epithelial Cells ◽  
Cell Carcinoma ◽  
Gene Expression Profiling ◽  
Cell Lines ◽  
Squamous Cell ◽  
Expression Profiling ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Control Samples

Selection of optimal control samples is crucial in expression profiling tumor samples. To address this issue, we performed microarray expression profiling of control samples routinely used in head and neck squamous cell carcinoma studies: human bronchial and tracheal epithelial cells, squamous cells obtained by laser uvulopalatoplasty and tumor surgical margins. We compared the results using multidimensional scaling and hierarchical clustering versus tumor samples and laryngeal squamous cell carcinoma cell lines. A general observation from our study is that the analyzed cohorts separated according to two dominant factors: “malignancy”, which separated controls from malignant samples and “cell culture-microenvironment” which reflected the differences between cultured and non-cultured samples. In conclusion, we advocate the use of cultured epithelial cells as controls for gene expression profiling of cancer cell lines. In contrast, comparisons of gene expression profiles of cancer cell lines versus surgical margin controls should be treated with caution, whereas fresh frozen surgical margins seem to be appropriate for gene expression profiling of tumor samples.

scholarly journals Combining differential expression, chromosomal and pathway analyses for the molecular characterization of renal cell carcinoma

2012 ◽  
Vol 1 (2S) ◽  
Author(s):  
Kyle A. Furge ◽  
Karl Dykema ◽  
David Petillo ◽  
Michael Westphal ◽  
Zhongfa Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Gene Expression Profiling ◽  
Cancer Cells ◽  
Expression Profiling ◽  
Renal Cell ◽  
Molecular Signatures ◽  
Genetic Makeup ◽  
Papillary Rcc

Using high-throughput gene-expression profiling technology, we can now gaina better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup ofthe cancer cells. This abnormal genetic makeup can have profound effectson cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeuticagents and radiation. These approaches will lead to better molecularsubclassification of tumours, the basis of personalized medicine. We have, todate, done whole-genome microarray gene-expression profiling on several hundredsof kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used toidentify both cytogenetic abnormalities and molecular pathways that are deregulatedin renal cell carcinoma (RCC). For example, we have identified the deregulationof the VHL-hypoxia pathway in clear-cell RCC, as previously known,and the c-Myc pathway in aggressive papillary RCC. Besides the more commonclear-cell, papillary and chromophobe RCCs, we are currently characterizingthe molecular signatures of rarer forms of renal neoplasia such ascarcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosomeXp11 translocations associated with papillary RCC, renal medullarycarcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response.

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