ABSTRACT
Purpose@#NUT carcinoma (NC) is a solid tumor caused by the rearrangement of NUTM1 that usually develops in midline structures, such as the thorax. No standard treatment has been established despite high lethality. Thus, we investigated whether targeting the junction region of NUTM1 fusion breakpoints could serve as a potential treatment option for NC. @*Materials and Methods@#We designed and evaluated a series of small interfering RNAs (siRNAs) targeting the junction region of BRD4-NUTM1 fusion (B4N), the most common form of NUTM1 fusion. Droplet digital polymerase chain reaction using the blood of patients was also tested to evaluate the treatment responses by the junction sequence of the B4N fusion transcripts. @*Results@#As expected, the majority of NC fusion types were B4N (12 of 18, 67%). B4N fusion-specific siRNA treatment on NC cells showed specific inhibitory effects on the B4N fusion transcript and fusion protein without affecting the endogenous expression of the parent genes, resulting in decreased relative cell growth and attenuation of tumor size. In addition, the fusion transcript levels in platelet-rich-plasma samples of the NC patients with systemic metastasis showed a negative correlation with therapeutic effect, suggesting its potential as a measure of treatment responsiveness. @*Conclusion@#This study suggests that tumor-specific sequences could be used to treat patients with fusion genes as part of precision medicine for a rare but deadly disease.
ABSTRACT
Purpose@#The purpose of this study was to investigate the concordance rate of PIK3CA mutations between primary and matched distant metastatic sites in patients with breast cancer and to verify whether there are differences in the frequency of PIK3CA hotspot mutations depending on the metastatic sites involved. @*Materials and Methods@#Archived formalin-fixed paraffin-embedded (FFPE) specimens of primary breast and matched distant metastatic tumors were retrospectively obtained for 49 patients. Additionally, 40 archived FFPE specimens were independently collected from different breast cancer metastatic sites, which were limited to three common sites: the liver, brain, and lung. PIK3CA mutations were analyzed using droplet digital PCR, including hotspots involving exons 9 and 20. @*Results@#After analysis of 49 breast tumors with matched metastasis sites, 87.8% showed concordance in PIK3CA mutation status. According to PIK3CA hotspot mutation testing in 89 cases of breast cancer metastatic sites, the proportion of PIK3CA mutations at sites of metastasis involving the liver, brain, and lung was 37.5%, 28.6%, and 42.9%, respectively, which did not result in statistical significance. @*Conclusion@#The high concordance of PIK3CA mutation status between primary and matched metastasis sites suggests that metastatic sites, regardless of the metastatic organ, could be considered sample sources for PIK3CA mutation testing for improved therapeutic strategies in patients with metastatic breast cancer.
ABSTRACT
Purpose@#To find biomarkers for disease, there have been constant attempts to investigate the genes that differ from those in the disease groups. However, the values that lie outside the overall pattern of a distribution, the outliers, are frequently excluded in traditional analytical methods as they are considered to be ‘some sort of problem.’ Such outliers may have a biologic role in the disease group. Thus, this study explored new biomarker using outlier analysis, and verified the suitability of therapeutic potential of two genes (TM4SF4 and LRRK2). @*Materials and Methods@#Modified Tukey’s fences outlier analysis was carried out to identify new biomarkers using the public gene expression datasets. And we verified the presence of the selected biomarkers in other clinical samples via customized gene expression panels and tissue microarrays. Moreover, a siRNA-based knockdown test was performed to evaluate the impact of the biomarkers on oncogenic phenotypes. @*Results@#TM4SF4 in lung cancer and LRRK2 in breast cancer were chosen as candidates among the genes derived from the analysis. TM4SF4 and LRRK2 were overexpressed in the small number of samples with lung cancer (4.20%) and breast cancer (2.42%), respectively. Knockdown of TM4SF4 and LRRK2 suppressed the growth of lung and breast cancer cell lines. The LRRK2 overexpressing cell lines were more sensitive to LRRK2-IN-1 than the LRRK2 under-expressing cell lines @*Conclusion@#Our modified outlier-based analysis method has proved to rescue biomarkers previously missed or unnoticed by traditional analysis showing TM4SF4 and LRRK2 are novel target candidates for lung and breast cancer, respectively.