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Efficacy of High-Ozonide Oil in Prevention of Cancer Relapses Mechanisms and Clinical Evidence
By psm in Publications on February . / Edit A new research article from the Unit is out.
Cancers have published the manuscript “Efficacy of high-ozonide oil in prevention of cancer relapses. Mechanisms and clinical evidences” by Izzotti A, Fracchia E, Rosano C, Comite A, Belgioia L, Sciacca S, Khalid Z, Congiu M, Colarossi C, Blanco G, Santoro A, Chiara M, Pulliero A. doi: 10.3390/cancers14051174
Abstract
Cancer relapses after chemo-radiotherapies arise from cancer stem cells able to escape cell killing because of their high antioxidants level. The aim of this study was to test the efficacy of ozonized oils to decrease the rate of cancer relapses. In vitro, oils at high ozonide content penetrate inside cancer cells releasing oxygen and reactive oxygen species damaging the thin outer membrane of inactive mitochondria. This event triggers intracellular calcium release and activates apoptosis. In vivo, ozonized oil has been administered by the oral route effectively decreasing blood antioxidants in cancer patients. This approach results in a significant increase in survival rate and decrease of relapses in 115 cancer patients (brain, lung, pancreas, colon, skin) undergoing standard radio-chemotherapy regimens during a 4-years follow up. Obtained results indicate that the administration of ozonized oil represents an integrated approach to decreasing the risk of radio-chemoresistance and cancer relapses in cancer patients.
GeenaR: a web tool for reproducible MALDI-TOF analysis
Frontiers in Genetics have published the manuscript “GeenaR: a web tool for reproducible MALDI-TOF analysis” by Eugenio Del Prete, Angelo Facchiano, Aldo Profumo, Claudia Angelini and Paolo Romano.
doi: 10.3389/fgene.2021.635814.
Abstract
Mass spectrometry is a widely applied technology with a strong impact in the proteomics field. MALDI-TOF is a combined technology in mass spectrometry with many applications in characterizing biological samples from different sources, such as the identification of cancer biomarkers, the detection of food frauds, the identification of doping substances in athletes’ fluids, and so on. The massive quantity of data, in the form of mass spectra, are often biased and altered by different sources of noise. Therefore, extracting the most relevant features that characterize the samples is often challenging and requires combining several computational methods.
Here, we present GeenaR, a novel web tool that provides a complete workflow for pre-processing, analyzing, visualizing, and comparing MALDI-TOF mass spectra. GeenaR is user-friendly, provides many different functionalities for the analysis of the mass spectra, and supports reproducible research since it produces a human-readable report that contains function parameters, results, and the code used for processing the mass spectra.
First, we illustrate the features available in GeenaR. Then, we describe its internal structure. Finally, we prove its capabilities in analyzing oncological datasets by presenting two case studies related to ovarian cancer and colorectal cancer.
GeenaR is available at http://proteomics.hsanmartino.it/geenar/.
Cite the manuscript as follows:
Del Prete E, Facchiano A, Profumo A, Angelini C, Romano P. GeenaR: a web tool for reproducible MALDI-TOF analysis. Front. Genet. 29 March 2021. 12:635814. doi: 10.3389/fgene.2021.635814
