A new biomarker panel of ultraconserved long non-coding RNAs for bladder cancer prognosis by a machine learning based methodology.

BACKGROUND: Recent studies have indicated that a special class of long non-coding RNAs (lncRNAs), namely Transcribed-Ultraconservative Regions are transcribed from specific DNA regions (T-UCRs), 100[Formula: see text] conserved in human, mouse, and rat genomes. This is noticeable, as lncRNAs are usually poorly conserved. Despite their peculiarities, T-UCRs remain very understudied in many diseases, including cancer and, yet, it is known that dysregulation of T-UCRs is associated with cancer as well as with human neurological, cardiovascular, and developmental pathologies. We have recently reported the T-UCR uc.8+ as a potential prognostic biomarker in bladder cancer. RESULTS: The aim of this work is to develop a methodology, based on machine learning techniques, for the selection of a predictive signature panel for bladder cancer onset. To this end, we analyzed the expression profiles of T-UCRs from surgically removed normal and bladder cancer tissues, by using custom expression microarray. Bladder tissue samples from 24 bladder cancer patients (12 Low Grade and 12 High Grade), with complete clinical data, and 17 control samples from normal bladder epithelium were analysed. After the selection of preferentially expressed and statistically significant T-UCRs, we adopted an ensemble of statistical and machine learning based approaches (i.e., logistic regression, Random Forest, XGBoost and LASSO) for ranking the most important diagnostic molecules. We identified a signature panel of 13 selected T-UCRs with altered expression profiles in cancer, able to efficiently discriminate between normal and bladder cancer patient samples. Also, using this signature panel, we classified bladder cancer patients in four groups, each characterized by a different survival extent. As expected, the group including only Low Grade bladder cancer patients had greater overall survival than patients with the majority of High Grade bladder cancer. However, a specific signature of deregulated T-UCRs identifies sub-types of bladder cancer patients with different prognosis regardless of the bladder cancer Grade. CONCLUSIONS: Here we present the results for the classification of bladder cancer (Low and High Grade) patient samples and normal bladder epithelium controls by using a machine learning application. The T-UCR's panel can be used for learning an eXplainable Artificial Intelligent model and develop a robust decision support system for bladder cancer early diagnosis providing urinary T-UCRs data of new patients. The use of this system instead of the current methodology will result in a non-invasive approach, reducing uncomfortable procedures (such as cystoscopy) for the patients. Overall, these results raise the possibility of new automatic systems, which could help the RNA-based prognosis and/or the cancer therapy in bladder cancer patients, and demonstrate the successful application of Artificial Intelligence to the definition of an independent prognostic biomarker panel.

Antiproliferative and Proapoptotic Effects of Erucin, a Diet-Derived H2S Donor, on Human Melanoma Cells.

Melanoma is the most dangerous form of skin cancer and is characterized by chemotherapy resistance and recurrence despite the new promising therapeutic approaches. In the last years, erucin (ERU), the major isothiocyanate present in Eruca sativa, commonly known as rocket salads, has demonstrated great efficacy as an anticancer agent in different in vitro and in vivo models. More recently, the chemopreventive effects of ERU have been associated with its property of being a H2S donor in human pancreatic adenocarcinoma. Here, we investigated the effects of ERU in modulating proliferation and inducing human melanoma cell death by using multiple in vitro approaches. ERU significantly reduced the proliferation of different human melanoma cell lines. A flow cytometry analysis with annexin V/PI demonstrated that ERU was able to induce apoptosis and cell cycle arrest in A375 melanoma cells. The proapoptotic effect of ERU was associated with the modulation of the epithelial-to-mesenchymal transition (EMT)-related cadherins and transcription factors. Moreover, ERU thwarted the migration, invasiveness and clonogenic abilities of A375 melanoma cells. These effects were associated with melanogenesis impairment and mitochondrial fitness modulation. Therefore, we demonstrated that ERU plays an important role in inhibiting the progression of melanoma and could represent a novel add-on therapy for the treatment of human melanoma.