Barbara Zellinger1,2, Ulrich Bodenhofer3,4, Immanuela A Engländer1,5, Cornelia Kronberger2, Peter Strasser6, Brane Grambozov5, Gerd Fastner5, Markus Stana5, Roland Reitsamer7, Karl Sotlar2, Felix Sedlmayer1,5, Franz Zehentmayr1,5. 1. radART-Institute for Research and Development on Advanced Radiation Technologies, Paracelsus Medical University, Müllner Hauptstrasse 48, 5020 Salzburg, Austria. 2. Department of Pathology, Paracelsus Medical University, SALK, Müllner Hauptstrasse 48, 5020 Salzburg, Austria. 3. School of Informatics, Communications and Media, University of Applied Sciences Upper Austria, Softwarepark 11, 4232 Hagenberg, Austria. 4. Institute for Machine Learning, Campus Science Park 3, Johannes Kepler University, Altenbergerstrasse 69, 4040 Linz, Austria. 5. Department of Radiation Oncology, Paracelsus Medical University, SALK, Müllner Hauptstrasse 48, 5020 Salzburg, Austria. 6. Department of Laboratory Medicine, Paracelsus Medical University, SALK, Müllner Hauptstrasse 48, 5020 Salzburg, Austria. 7. Department of Gynecology and Obstetrics, Paracelsus Medical University, SALK, Müllner Hauptstrasse 48, 5020 Salzburg, Austria.
Abstract
BACKGROUND: In order to characterize the various subtypes of breast cancer more precisely and improve patients selection for breast conserving therapy (BCT), molecular profiling has gained importance over the past two decades. MicroRNAs, which are small non-coding RNAs, can potentially regulate numerous downstream target molecules and thereby interfere in carcinogenesis and treatment response via multiple pathways. The aim of the current two-phase study was to investigate whether hsa-miR-375-signaling through RASD1 could predict local control (LC) in early breast cancer. RESULTS: The patient and treatment characteristics of 81 individuals were similarly distributed between relapse (n = 27) and control groups (n = 54). In the pilot phase, the primary tumors of 28 patients were analyzed with microarray technology. Of the more than 70,000 genes on the chip, 104 potential hsa-miR-375 target molecules were found to have a lower expression level in relapse patients compared to controls (p-value < 0.2). For RASD1, a hsa-miR-375 binding site was predicted by an in silico search in five mRNA-miRNA databases and mechanistically proven in previous pre-clinical studies. Its expression levels were markedly lower in relapse patients than in controls (p-value of 0.058). In a second phase, this finding could be validated in an independent set of 53 patients using ddPCR. Patients with enhanced levels of hsa-miR-375 compared to RASD1 had a higher probability of local relapse than those with the inverse expression pattern of the two markers (log-rank test, p-value = 0.069). CONCLUSION: This two-phase study demonstrates that hsa-miR-375/RASD1 signaling is able to predict local control in early breast cancer patients, which-to our knowledge-is the first clinical report on a miR combined with one of its downstream target proteins predicting LC in breast cancer.
BACKGROUND: In order to characterize the various subtypes of breast cancer more precisely and improve patients selection for breast conserving therapy (BCT), molecular profiling has gained importance over the past two decades. MicroRNAs, which are small non-coding RNAs, can potentially regulate numerous downstream target molecules and thereby interfere in carcinogenesis and treatment response via multiple pathways. The aim of the current two-phase study was to investigate whether hsa-miR-375-signaling through RASD1 could predict local control (LC) in early breast cancer. RESULTS: The patient and treatment characteristics of 81 individuals were similarly distributed between relapse (n = 27) and control groups (n = 54). In the pilot phase, the primary tumors of 28 patients were analyzed with microarray technology. Of the more than 70,000 genes on the chip, 104 potential hsa-miR-375 target molecules were found to have a lower expression level in relapse patients compared to controls (p-value < 0.2). For RASD1, a hsa-miR-375 binding site was predicted by an in silico search in five mRNA-miRNA databases and mechanistically proven in previous pre-clinical studies. Its expression levels were markedly lower in relapse patients than in controls (p-value of 0.058). In a second phase, this finding could be validated in an independent set of 53 patients using ddPCR. Patients with enhanced levels of hsa-miR-375 compared to RASD1 had a higher probability of local relapse than those with the inverse expression pattern of the two markers (log-rank test, p-value = 0.069). CONCLUSION: This two-phase study demonstrates that hsa-miR-375/RASD1 signaling is able to predict local control in early breast cancerpatients, which-to our knowledge-is the first clinical report on a miR combined with one of its downstream target proteins predicting LC in breast cancer.
Entities:
Keywords:
RASD1; early stage breast cancer; hsa-miR-375; local control; predictive markers
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