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Piemonti L.,San Raffaele Scientific Institute | Everly M.J.,Terasaki Foundation Laboratory | Maffi P.,San Raffaele Scientific Institute | Scavini M.,San Raffaele Scientific Institute | And 15 more authors.
Diabetes | Year: 2013

Long-term clinical outcome of islet transplantation is hampered by the rejection and recurrence of autoimmunity. Accurate monitoring may allow for early detection and treatment of these potentially compromising immune events. Islet transplant outcome was analyzed in 59 consecutive pancreatic islet recipients in whom baseline and de novo posttransplant autoantibodies (GAD antibody, insulinoma-associated protein 2 antigen, zinc transporter type 8 antigen) and donor-specific alloantibodies (DSA) were quantified. Thirty-nine recipients (66%) showed DSA or autoantibody increases (de novo expression or titer increase) after islet transplantation. Recipients who had a posttransplant antibody increase showed similar initial performance but significantly lower graft survival than patients without an increase (islet autoantibodies P < 0.001, DSA P < 0.001). Posttransplant DSA or autoantibody increases were associated with HLA-DR mismatches (P = 0.008), induction with antithymocyte globulin (P = 0.0001), and pretransplant panel reactive alloantibody >15% in either class I or class II (P = 0.024) as independent risk factors and with rapamycin as protective (P = 0.006) against antibody increases. DSA or autoantibody increases after islet transplantation are important prognostic markers, and their identification could potentially lead to improved islet cell transplant outcomes. © 2013 by the American Diabetes Association.

Callari M.,Fondazione Istituto Nazionale Dei Tumori | Cappelletti V.,Fondazione Istituto Nazionale Dei Tumori | D'Aiuto F.,Fondazione Istituto Nazionale Dei Tumori | Musella V.,Fondazione Istituto Nazionale Dei Tumori | And 9 more authors.
Clinical Cancer Research | Year: 2016

Purpose: In spite of improvements of average benefit from adjuvant/neoadjuvant treatments, there are still individual patients with early breast cancer at high risk of relapse. We explored the association with outcome of robust gene cluster based metagenes linked to proliferation, ER-related genes, and immune response to identify those high-risk patients. Experimental Design: A total of 3,847 publicly available geneexpression profiles were analyzed (untreated, N = 826; tamoxifen- treated, N = 685; chemotherapy-treated, N = 1,150). Genes poorly performing in formalin-fixed samples were removed. Outcomes of interest were pathologic-complete response (PCR) and distant metastasis-free survival (DMFS). In ERHER2, the proliferation and ER-related metagenes were combined to define three risk groups. In HER2 and ER HER2 risk groups were defined by tertiles of an immune-related metagene. Results: The high-proliferation/low-ER group of ERHER2 breast cancer had significantly higher PCR rate [OR, 5.01 (1.76 17.99), P = 0.005], but poorer outcome [HR = 3.73 (1.638.51), P = 0.0018] than the low-proliferation/high-ER. A similar association with outcome applied to patients with residual disease (RD) after neoadjuvant chemotherapy (P = 0.01). In ER HER2 and HER2 breast cancer, immune metagene in the high tertile was linked to higher PCR [33.7% vs. 11.6% in high and low tertile, respectively; OR, 3.87 (1.798.95); P = 0.0009]. In ER HER2, after adjuvant/neoadjuvant chemotherapy, 5-year DMFS was 85.4% for high-tertile immune metagene, and 43.9% for low tertile. The outcome association was similar in patients with RD (P = 0.0055). In HER2 breast cancer treated with chemotherapy the association with risk of relapse was not significant. Conclusions: Wedeveloped metagene-based predictors able to define low and high risk of relapse after adjuvant/neoadjuvant therapy. High-risk patients so defined should be preferably considered for trials with investigational agents. © 2015 American Association for Cancer Research.

Callari M.,Fondazione Istituto Nazionale Dei Tumori | Lembo A.,University of Turin | Musella V.,Fondazione Istituto Nazionale Dei Tumori | Cappelletti V.,Fondazione Istituto Nazionale Dei Tumori | And 3 more authors.
PLoS ONE | Year: 2014

Formalin fixed paraffin-embedded (FFPE) tumor specimens are the conventionally archived material in clinical practice, representing an invaluable tissue source for biomarkers development, validation and routine implementation. For many prospective clinical trials, this material has been collected allowing for a prospective-retrospective study design which represents a successful strategy to define clinical utility for candidate markers. Gene expression data can be obtained even from FFPE specimens with the broadly used Affymetrix HG-U133 Plus 2.0 microarray platform. Nevertheless, important major discrepancies remain in expression data obtained from FFPE compared to fresh-frozen samples, prompting the need for appropriate data processing which could help to obtain more consistent results in downstream analyses. In a publicly available dataset of matched frozen and FFPE expression data, the performances of different normalization methods and specifically designed Chip Description Files (CDFs) were compared. The use of an alternative CDFs together with fRMA normalization significantly improved frozen-FFPE sample correlations, frozen-FFPE probeset correlations and agreement of differential analysis between different tumor subtypes. The relevance of our optimized data processing was assessed and validated using two independent datasets. In this study we demonstrated that an appropriate data processing can significantly improve the reliability of gene expression data derived from FFPE tissues using the standard Affymetrix platform. Tools for the implementation of our data processing algorithm are made publicly available at http://www.biocut.unito.it/cdf-ffpe/. © 2014 Callari et al.

Starmans M.H.W.,Ontario Cancer Institute | Starmans M.H.W.,Maastricht University | Pintilie M.,A+ Network | Chan-Seng-Yue M.,Ontario Cancer Institute | And 25 more authors.
Clinical Cancer Research | Year: 2015

Purpose: While the dysregulation of specific pathways in cancer influences both treatment response and outcome, few current prognostic markers explicitly consider differential pathway activation. Here we explore this concept, focusing on K-Ras mutations in lung adenocarcinoma (present in 25%-35% of patients). Experimental Design: The effect of K-Ras mutation status on prognostic accuracy of existing signatures was evaluated in 404 patients. Genes associated with K-Ras mutation status were identified and used to create a RAS pathway activation classifier to provide a more accurate measure of RAS pathway status. Next, 8 million random signatures were evaluated to assess differences in prognosing patients with or without RAS activation. Finally, a prognostic signature was created to target patients with RAS pathway activation. Results: We first show that K-Ras status influences the accuracy of existing prognostic signatures, which are effective in K-Ras-wild-type patients but fail in patients with K-Ras mutations. Next, we show that it is fundamentally more difficult to predict the outcome of patients with RAS activation (RASmt) than that of those without (RASwt). More importantly, we demonstrate that different signatures are prognostic in RASwt and RASmt. Finally, to exploit this discovery, we create separate prognostic signatures for RASwt and RASmt patients and show that combining them significantly improves predictions of patient outcome. Conclusions: Wepresent a nestedmodel for integrated genomic and transcriptomic data. Thismodel is general and is not limited to lung adenocarcinomas but can be expanded to other tumor types and oncogenes. © 2015 American Association for Cancer Research.

Cittaro D.,Center for Translational Genomics and Bioinformatics | Lazarevic D.,Center for Translational Genomics and Bioinformatics | Provero P.,Center for Translational Genomics and Bioinformatics | Provero P.,University of Turin
F1000Research | Year: 2016

The epigenetic modifications are organized in patterns determining the functional properties of the underlying genome. Such patterns, typically measured by ChIP-seq assays of histone modifications, can be combined and translated into musical scores, summarizing multiple signals into a single waveform. As music is recognized as a universal way to convey meaningful information, we wanted to investigate properties of music obtained by sonification of ChIP-seq data. We show that the music produced by such quantitative signals is perceived by human listeners as more pleasant than that produced from randomized signals. Moreover, the waveform can be analyzed to predict phenotypic properties, such as differential gene expression. © 2016 Cittaro D et al.

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