An innovative approach in lung cancer: from RNA expression to exosomal miRNA sequencing in lung adenocarcinoma derived tissue explants

Lung cancer (LC) ranks among the most common cancers worldwide both for incidence and mortality rates. It can be classified into two main categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NCSLC is further classified into several histological subtypes with lung adenocarcinoma (LUAD) emerging as the most frequent. High-quality RNA is essential for reliable gene- expression studies, yet tissue preparation remains a key source of technical variability. Mechanical disaggregation is widely used due to its simplicity and efficiently, but its operator- dependance can lead to inconsistent results. In this study, we evaluated the impact of manual versus automated mechanical tissue disruption on RNA quality obtained from fresh lung biopsies. To address this, 106 fresh human lung tissues, half tumoral and half non tumoral, were collected from patients who underwent lobectomy. Each sample was split into two specimens to be processed with (w R) and without Rigeneracons (w/o R)- a new medical device, in order to obtain a lysate from which RNA was extracted. RNA integrity was verified primarily with 2% agarose gel electrophoresis, then by Real-Time Quantitative Reverse Transcription PCR (q-RT-PCR). The results demonstrated that samples processed with the automated divide exhibiting higher RNA integrity compared to those processed manually, with median fragmentation index values of 0.86 and 0.71, respectively. This difference was statistically significant (p=0.0084). overall, these findings suggest that the use of automated mechanical disaggregation can effectively reduce technical biases associated with the processing of fresh tissues.