Anti-TTK (aa 1-30) polyclonal antibody

Our goal was to noninvasively measure chemotherapy-induced changes in the expression of critical tumor growth genes. To achieve this goal, we used radionuclide and optical methods to measure changes in human telomerase reverse transcriptase (hTERT) gene expression in tumor cells before and after 5-fluorouracil treatment. Methods: A fusion reporter construct, containing humanized Renilla luciferase (hrl, for bioluminescent imaging), monomeric red fluorescence protein 1 (mrfp1, for fluorescent imaging), and a truncated thymidine kinase (ttk, for imaging of radiolabeled acycloguanosines), was placed under the control of hTERT promoter fragments. These constructs were introduced into tumor cell lines with and without hTERT expression. Transfected cells were treated with 5-fluorouracil, a chemotherapeutic that decreases hTERT gene expression, and treatment-induced changes in hTERT promoter activity were imaged. Results: When the fusion construct is introduced into cell lines that express hTERT, all 3 reporter systems are highly expressed and hTERT promoter activity can be visualized. Cell lines lacking hTERT transcription show no significant reporter expression. Decreases in hTERT gene expression caused by 5-fluorouracil treatment could be visualized in living 293T cells by both fluorescent microscopy and bioluminescent imaging. Conclusion: hTERT promoter activity can be monitored by 1 radionuclide and 2 optical reporter systems using a single reporter construct. This in vitro study provides evidence that our multimodality reporter construct can be used to study the expression of a critical tumor growth gene in living subjects.

Background: Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. Methods: Gene transcripts per million (TPM) data were downloaded from the UCSC Xena database, which included ACC (The Cancer Genome Atlas, n = 77) and normal samples (Genotype Tissue Expression, n = 128). We used weighted gene co-expression network analysis to identify gene connections. Overall survival (OS) was determined using the univariate Cox model. A protein-protein interaction (PPI) network was constructed by the search tool for the retrieval of interacting genes. Results: To determine the critical genes involved in ACC progression, we obtained 2,953 significantly differentially expressed genes and nine modules. Among them, the blue module demonstrated significant correlation with the "Stage" of ACC. Enrichment analysis revealed that genes in the blue module were mainly enriched in cell division, cell cycle, and DNA replication. Combined with the PPI and co-expression networks, we identified four hub genes (i.e., TOP2A, TTK, CHEK1, an d CENPA) that were highly expressed in ACC and negatively correlated with OS. Thus, these identified genes may play important roles in the progression of ACC and serve as potential biomarkers for future diagnosis.