Real-time quantitative PCR analysis of human collecting lymphatic vessels

The aim of this feasibility study was to assess whether inflammatory status of the lymphatic vessels (LVs) and/or changes in the miRNA profile of the LVs have potential prognostic and predictive value for overall outcome and risk of relapse. Tissue specimens were obtained from the external iliac vessels draining the pelvic region of patients undergoing debulking surgery (n=10). The tissue was transported directly from surgical theatre to the laboratory in ice-cold sterile Phosphate Buffered Saline. LVs were identified and isolated along with a small amount of surrounding tissue under a dissection microscope within a sterile laminar flow cabinet. Each vessel was divided into two sections. One half of each vessel was further cleaned of surrounding fatty tissue, placed in RNA stabilising solution, frozen on dry ice and stored at -20°C. The miRNAs were extracted with an miRNA easy kit and reverse-transcribed to cDNA using a miScript II RT Kit . Subsequent qPCR was carried out using a miScriptSybrGreen real-time PCR kit and pre-defined miScript miRNA PCR Array. Quantification of the inflammatory state (low, medium and high) and presence of cancer-infiltration of each LV was carried out using immunohistochemistry with the remaining half of each vessel. The LV miRNA expression profiling was then analysed in the context of high versus low inflammation, and cancer-infiltrated versus non-cancer-infiltrated. Results were correlated with clinical outcome data including relapse with an average follow-up time of 13.3 months. qPCR miRNA expression profiling. Each sample contains miRNA extracted from the LVs of a single patient (n=10). RNA concentration per sample was quantified using absorbance ratios and an estimated equal amount of total RNA was reverse transcribed per sample. Well G06 was used as a negative control. Housekeeping gene at H06 was used to normalise the data after analysis to identify the most stable housekeeping gene with NormFinder and GeNorm software.