Anil K. Sood

Exosome cargoes are highly varied and include proteins, small RNAs, and genomic DNA (gDNA). The presence of gDNA suggests that different intracellular compartments contribute to exosome loading, resulting in distinct exosome subpopulations. However, the loading of gDNA and other nuclear contents into exosomes (nExo) remains poorly understood. Here, we identify the relationship between cancer cell micronuclei (MN), which are markers of genomic instability, and nExo formation. Imaging flow cytometry analyses reveal that 10% of exosomes derived from cancer cells and <1% of exosomes derived from blood and ascites from patients with ovarian cancer carry nuclear contents. Treatment with genotoxic drugs resulted in increased MN and nExos both in vitro and in vivo. We observed that multivesicular body precursors and exosomal markers, such as the tetraspanins, directly interact with MN. Collectively, this work provides new insights related to nExos, which have implications for cancer biomarker development.

The purpose of this study was to assess heterogeneity of tumor microcirculation determined by dynamic contrast-enhanced magnetic resonance (MR) imaging and its prognostic value for tumor radiosensitivity and long-term tumor control using pixel-by-pixel analysis of the dynamic contrast enhancement. Sixteen patients with advanced cervical cancer were examined with dynamic contrast-enhanced MR imaging at the time of radiation therapy. Pixel-by-pixel statistical analysis of the ratio of post- to precontrast relative signal intensity (RSI) values in the tumor region was performed to generate pixel RSI distributions of dynamic enhancement patterns. Histogram parameters were correlated with subsequent tumor control based on long-term cancer follow-up (median follow-up 4.6 years; range 3.8-5.2 years). The RSI distribution histograms showed a wide spectrum of heterogeneity in the dynamic enhancement pattern within the tumor. The quantity of low-enhancement regions (10th percentile RSI < 2.5) significantly predicted subsequent tumor recurrence (88% vs. 0%, P = 0.0004). Discriminant analysis based on both 10th percentile RSI and pixel number (reflective of tumor size) further improved the prediction rate (100% correct prediction of subsequent tumor control vs. recurrence). These preliminary results suggest that quantification of the extent of poor vascularity regions within the tumor may be useful in predicting long-term tumor control and treatment outcome in cervical cancer. J. Magn. Reson. Imaging 2000;12:1027-1033.