Inhibition of metastatic progression of SSTR2 gene transfection mediated by adenovirus in human pancreatic carcinoma cells

Loss of somatostatin receptor subtype 2 in prostate cancer is linked to an aggressive cancer phenotype, high tumor cell proliferation and predicts early metastatic and biochemical relapse

Somatostatin receptor subtype 2 (SSTR2) is the most frequently expressed SSTR subtype in normal human tissues. SSTR2 expression is differentially regulated in various tumor types and therapeutic somatostatin analogs binding to SSTR2 are in clinical use. In prostate cancers highly contradictory results in terms of SSTR2 expression and its consequences have been published over the past years. The aim of this study was to clarify prevalence and clinical significance of SSTR2 expression in prostate cancer. Therefore, quantitative immunohistochemistry (IHC) using a tissue microarray containing samples from 3,261 prostate cancer patients with extensive clinical and molecular cancer characteristics and oncological follow-up data was performed. IHC data was compared to publicly available Gene Expression Omnibus datasets of human prostate cancer gene expression arrays. While membranous SSTR2 staining was always seen in normal prostate epithelium, SSTR2 staining was absent in more than half (56.1%) of 2,195 interpretable prostate cancer samples. About 13% of all analyzed prostate cancers showed moderate to strong cytoplasmic and membranous SSTR2 staining. Staining intensities were inversely correlated with high Gleason grade, advanced pT category, high tumor cell proliferation (p<0.0001 each), high pre-operative PSA levels, (p = 0.0011) and positive surgical margins (p = 0.006). In silico analysis confirmed lower SSTR2 gene expression in prostate cancers vs. normal adjacent tissue (p = 0.0424), prostate cancer metastases vs. primary cancers (p = 0.0011) and recurrent vs. non-recurrent prostate cancers (p = 0.0438). PSA-free survival gradually declined with SSTR2 staining intensity (p<0.0001). SSTR2-negative cancers were more likely to develop metastases over time (p<0.05). In conclusion, most prostate cancers are indeed SSTR2-negative and loss of SSTR2 strongly predicts an unfavorable tumor phenotype and poor prognosis. Therefore, SSTR2 expression seems an important factor in the pathogenesis of prostate cancer and re-introduction of the receptor in SSTR2-negative prostate cancers may feature a promising target for novel gene therapy approaches.

Defining the cancer master switch

BACKGROUND

Recent research has focused on signaling cascades and their interactions yielding considerable insight into which genetic pathways are targeted and how they tend to be altered in tumors. Therapeutic interventions now can be designed based on the knowledge of pathways vital to tumor growth and survival. These critical targets for intervention, master switches for cancer, are termed so because the tumor attempts to "flip the switch" in a way that promotes its survival, whereas molecular therapy aims to "switch off" signals important for tumor-related processes.

METHODS

Literature review.

CONCLUSIONS

Defining useful targets for therapy depends on identifying pathways that are crucial for tumor growth, survival, and metastasis. Because not all signaling cascades are created equal, selecting master switches or targets for intervention needs to be done in a systematic fashion. This discussion proposes a set of criteria to define what it means to be a cancer master switch and provides examples to illustrate their application.

A gene signature of primary tumor identifies metastasized seminoma

BACKGROUND

The aim of this study was the prediction of metastatic status in seminoma based on examination of the primary tumor.

METHODS

Total RNA was isolated from metastasized seminoma (n = 10, T1N1-2M0), non-metastasized seminoma (n = 21, T1-3N0M0), and corresponding normal tissues. Pooled RNA from 10 biopsies of each tissue type was hybridized on whole genome microarrays for screening purposes. Ninety-two selected gene candidates were quantitatively examined using real-time quantitative polymerase chain reaction (RTQ-PCR).

RESULTS

Agreement in gene expression was 88% between the whole genome microarrays and RTQ-PCR. Metastasized seminoma showed 1,912 up-regulated and 2,179 down-regulated genes with ≥ 2-fold differences in gene expression compared non-metastasized seminoma. RTQ-PCR of selected genes showed that mean gene expression values were significantly reduced in metastasized compared with non-metastasized seminoma. The presence of metastases could be predicted based on an 85-gene expression signature by using logistic regression. Sensitivity and accuracy of the 10-fold cross-validation model were 77.8% and 84.2%, respectively.

CONCLUSION

A logistic regression model using an 85 gene expression signature allowed identification of metastasized seminoma from the primary tumor with a sensitivity of 77.8%.