Maria Daidone

Publications (4)4.43 Total impact

• Article: miR-21: an oncomir on strike in prostate cancer

  Marco Folini, Paolo Gandellini, Nicole Longoni, Valentina Profumo, Maurizio Callari, Marzia Pennati, Maurizio Colecchia, Rosanna Supino, Silvia Veneroni, Roberto Salvioni, Riccardo Valdagni, Maria Daidone, Nadia Zaffaroni
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  ABSTRACT: Abstract Background Aberrant expression of microRNAs, small non-coding RNA molecules that post-transcriptionally repress gene expression, seems to be causatively linked to the pathogenesis of cancer. In this context, miR-21 was found to be overexpressed in different human cancers (e.g. glioblastoma, breast cancer). In addition, it is thought to be endowed with oncogenic properties due to its ability to negatively modulate the expression of tumor-suppressor genes (e.g. PTEN ) and to cause the reversion of malignant phenotype when knocked- down in several tumor models. On the basis of these findings, miR-21 has been proposed as a widely exploitable cancer-related target. However, scanty information is available concerning the relevance of miR-21 for prostate cancer. In the present study, we investigated the role of miR-21 and its potential as a therapeutic target in two prostate cancer cell lines, characterized by different miR-21 expression levels and PTEN gene status. Results We provide evidence that miR-21 knockdown in prostate cancer cells is not sufficient per se i) to affect the proliferative and invasive potential or the chemo- and radiosensitivity profiles or ii) to modulate the expression of the tumor-suppressors PTEN and Pdcd4, which in other tumor types were found to be regulated by miR-21. We also show that miR-21 is not differently expressed in carcinomas and matched normal tissues obtained from 36 untreated prostate cancer patients subjected to radical prostatectomy. Conclusions Overall, our data suggest that miR-21 is not a central player in the onset of prostate cancer and that its single hitting is not a valuable therapeutic strategy in the disease. This supports the notion that the oncogenic properties of miR-21 could be cell and tissue dependent and that the potential role of a given miRNA as a therapeutic target should be contextualized with respect to the disease.
  Molecular Cancer. 01/2010;
• Article: Impact of biospecimens handling on biomarker research in breast cancer

  De Cecco Loris, Valeria Musella, Silvia Veneroni, Vera Cappelletti, Italia Bongarzone, Maurizio Callari, Barbara Valeri, Marco Pierotti, Maria Daidone
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  ABSTRACT: Abstract Background Gene expression profiling is moving from the research setting to the practical clinical use. Gene signatures able to correctly identify high risk breast cancer patients as well as to predict response to treatment are currently under intense investigation. While technical issues dealing with RNA preparation, choice of array platforms, statistical analytical tools are taken into account, the tissue collection process is seldom considered. The time elapsed between surgical tissue removal and freezing of samples for biological characterizations is rarely well defined and/or recorded even for recently stored samples, despite the publications of standard operating procedures for biological sample collection for tissue banks. Methods Breast cancer samples from 11 patients were collected immediately after surgical removal and subdivided into aliquots. One was immediately frozen and the others were maintained at room temperature for respectively 2, 6 and 24 hrs. RNA was extracted and gene expression profile was determined using cDNA arrays. Phosphoprotein profiles were studied in parallel. Results Delayed freezing affected the RNA quality only in 3 samples, which were not subjected to gene profiling. In the 8 breast cancer cases with apparently intact RNA also in sample aliquots frozen at delayed times, 461 genes were modulated simply as a function of freezing timing. Some of these genes were included in gene signatures biologically and clinically relevant for breast cancer. Delayed freezing also affected detection of phosphoproteins, whose pattern may be crucial for clinical decision on target-directed drugs. Conclusion Time elapsed between surgery and freezing of samples appears to have a strong impact and should be considered as a mandatory variable to control for clinical implications of inadequate tissue handling.
  BMC Cancer. 01/2009;
• Article: Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen

  Sherene Loi, Benjamin Haibe-Kains, Christine Desmedt, Pratyaksha Wirapati, Françoise Lallemand, Andrew Tutt, Cheryl Gillet, Paul Ellis, Kenneth Ryder, James Reid, Maria Daidone, Marco Pierotti, Els Berns, Maurice Jansen, John Foekens, Mauro Delorenzi, Gianluca Bontempi, Martine Piccart, Christos Sotiriou
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  ABSTRACT: Abstract Background Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30–40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings. Results We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29–3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response. Conclusion We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
  BMC Genomics. 01/2008;
• Article: Invasiveness gene signature predicts a favorable outcome also in estrogen receptor-positive primary breast cancers treated with adjuvant tamoxifen.

  Danila Coradini, Manuela Gariboldi, Maya Fedeli, Marco A Pierotti, Maria Grazia Daidone
  Breast Cancer Research and Treatment 11/2007; 111(2):389-90. · 4.43 Impact Factor