Differential BMI1, TWIST1, SNAI2 mRNA expression pattern correlation with malignancy type in a spectrum of common cutaneous malignancies: basal cell carcinoma, squamous cell carcinoma, and melanoma

Purpose. Melanoma, squamous cell carcinoma (SCC), and basal cell carcinoma (BCC) can be used as a unique model to identify molecular mechanisms to distinguish rarely metastatic (BCC), often metastatic (SCC) and most metastatic (melanoma) cancer. It is known that epithelial-mesenchymal transition and stemness transcription factors (TWIST1, SNAI2/SLUG, and BMI1) play an important role in metastasis and their dysregulation has been demonstrated in metastatic cancers. We hypothesized that this spectrum of cutaneous cancers (BCC, SCC, and melanoma) would be a unique cancer model system to elucidate steps toward cancer invasion and metastasis. Methods. We evaluated the mRNA expression level of BMI1, TWIST1, and SNAI2/SLUG and studied clinicopathological features in 170 skin cancers along with normal tissue samples. Results. We demonstrate downregulation of BMI1 mRNA expression in BCC samples compared with controls (p = 0.0001), SCC (p = 0.001), and melanoma (p = 0.0001) samples. Downregulation of TWIST1 mRNA expression is seen in only BCC samples compared with controls (p = 0.031). High SNAI2 mRNA expression is represented in melanoma samples compared with controls (p = 0.022) and SCC samples (p = 0.031). High mRNA expression of TWIST1 is seen in patients with positive history of cancers. Extremely low mRNA expression of BMI1 is detected in patients with positive history of cancers other than skin cancer. Conclusions. These findings provide support for the hypothesis that the spectrum of cutaneous cancers could be better understood as a series of gene dosage-dependent entities with distinct molecular events. Oncogene-induced senescence, mechanism of which is still unclear, could be one explanation for these results (AU)

No disponible

Generalized paired-agent kinetic model for in vivo quantification of cancer cell-surface receptors under receptor saturation conditions.

New precision medicine drugs oftentimes act through binding to specific cell-surface cancer receptors, and thus their efficacy is highly dependent on the availability of those receptors and the receptor concentration per cell. Paired-agent molecular imaging can provide quantitative information on receptor status in vivo, especially in tumor tissue; however, to date, published approaches to paired-agent quantitative imaging require that only 'trace' levels of imaging agent exist compared to receptor concentration. This strict requirement may limit applicability, particularly in drug binding studies, which seek to report on a biological effect in response to saturating receptors with a drug moiety. To extend the regime over which paired-agent imaging may be used, this work presents a generalized simplified reference tissue model (GSRTM) for paired-agent imaging developed to approximate receptor concentration in both non-receptor-saturated and receptor-saturated conditions. Extensive simulation studies show that tumor receptor concentration estimates recovered using the GSRTM are more accurate in receptor-saturation conditions than the standard simple reference tissue model (SRTM) (% error (mean ± sd): GSRTM 0 ± 1 and SRTM 50 ± 1) and match the SRTM accuracy in non-saturated conditions (% error (mean ± sd): GSRTM 5 ± 5 and SRTM 0 ± 5). To further test the approach, GSRTM-estimated receptor concentration was compared to SRTM-estimated values extracted from tumor xenograft in vivo mouse model data. The GSRTM estimates were observed to deviate from the SRTM in tumors with low receptor saturation (which are likely in a saturated regime). Finally, a general 'rule-of-thumb' algorithm is presented to estimate the expected level of receptor saturation that would be achieved in a given tissue provided dose and pharmacokinetic information about the drug or imaging agent being used, and physiological information about the tissue. These studies suggest that the GSRTM is necessary when receptor saturation exceeds 20% and highlight the potential for GSRTM to accurately measure receptor concentrations under saturation conditions, such as might be required during high dose drug studies, or for imaging applications where high concentrations of imaging agent are required to optimize signal-to-noise conditions. This model can also be applied to PET and SPECT imaging studies that tend to suffer from noisier data, but require one less parameter to fit if images are converted to imaging agent concentration (quantitative PET/SPECT).

Differential BMI1, TWIST1, SNAI2 mRNA expression pattern correlation with malignancy type in a spectrum of common cutaneous malignancies: basal cell carcinoma, squamous cell carcinoma, and melanoma.

PURPOSE: Melanoma, squamous cell carcinoma (SCC), and basal cell carcinoma (BCC) can be used as a unique model to identify molecular mechanisms to distinguish rarely metastatic (BCC), often metastatic (SCC) and most metastatic (melanoma) cancer. It is known that epithelial-mesenchymal transition and stemness transcription factors (TWIST1, SNAI2/SLUG, and BMI1) play an important role in metastasis and their dysregulation has been demonstrated in metastatic cancers. We hypothesized that this spectrum of cutaneous cancers (BCC, SCC, and melanoma) would be a unique cancer model system to elucidate steps toward cancer invasion and metastasis. METHODS: We evaluated the mRNA expression level of BMI1, TWIST1, and SNAI2/SLUG and studied clinicopathological features in 170 skin cancers along with normal tissue samples. RESULTS: We demonstrate downregulation of BMI1 mRNA expression in BCC samples compared with controls (p = 0.0001), SCC (p = 0.001), and melanoma (p = 0.0001) samples. Downregulation of TWIST1 mRNA expression is seen in only BCC samples compared with controls (p = 0.031). High SNAI2 mRNA expression is represented in melanoma samples compared with controls (p = 0.022) and SCC samples (p = 0.031). High mRNA expression of TWIST1 is seen in patients with positive history of cancers. Extremely low mRNA expression of BMI1 is detected in patients with positive history of cancers other than skin cancer. CONCLUSIONS: These findings provide support for the hypothesis that the spectrum of cutaneous cancers could be better understood as a series of gene dosage-dependent entities with distinct molecular events. Oncogene-induced senescence, mechanism of which is still unclear, could be one explanation for these results.