Niccolò Bassani

Anti-phospholipid induced murine fetal loss: novel protective effect of a peptide targeting the β2 glycoprotein I phospholipid-binding site. Implications for human fetal loss

β2 glycoprotein I (β2GPI)-dependent anti-phospholipid antibodies (aPL) induce thrombosis and affect pregnancy. The CMV-derived synthetic peptide TIFI mimics the PL-binding site of β2GPI and inhibits β2GPI cell-binding in vitro and aPL-mediated thrombosis in vivo. Here we investigated the effect of TIFI on aPL-induced fetal loss in mice. TIFI inhibitory effect on in vitro aPL binding to human trophoblasts was evaluated by indirect immunofluorescence and ELISA. TIFI effect on aPL-induced fetal loss was investigated in pregnant C57BL/6 mice treated with aPL or normal IgG (NHS). Placenta/fetus weight and histology and RNA expression were analyzed. TIFI, but not the control peptide VITT, displayed a dose-dependent inhibition of aPL binding to trophoblasts in vitro. Injection of low doses of aPL at day 0 of pregnancy caused growth retardation and increased fetal loss rate, both significantly reduced by TIFI but not VITT. Consistent with observations in humans, histological analysis showed no evidence of inflammation in this model, as confirmed by the absence of an inflammatory signature in gene expression analysis, which in turn revealed a TIFI-dependent modulation of molecules involved in differentiation and development processes. These findings support the non-inflammatory pathogenic role of aPL and suggest innovative therapeutic approaches to aPL-dependent fetal loss.

Epithelial-to-mesenchymal transition, cell polarity and stemness-associated features in malignant pleural mesothelioma

Epithelial-to-mesenchymal transition (EMT) is the fundamental process by which an epithelial cell loses its epithelial characteristics including cell polarity and acquires mesenchymal and stemness-related features. Therefore, we investigated whether malignant pleural mesothelioma (MPMs) histologies were associated with specific patterns of expression of a selected set of genes related to EMT, cell polarity and stemness features. The association between MPM histologies and genes expression were explored using active and passive Principal Components Analysis-based biplots and PAM analysis that provided evidence that with respect to normal tissues, MPMs histologies were better characterized by specific patterns of expression of genes involved in EMT activation, cell polarity and stemness.

Transcriptional profiling of melanoma sentinel nodes identify patients with poor outcome and reveal an association of CD30(+) T lymphocytes with progression.

Sentinel lymph nodes set the stance of the immune system to a localized tumor and are often the first site to be colonized by neoplastic cells that metastasize. To investigate how the presence of neoplastic cells in sentinel lymph nodes may trigger pathways associated with metastatic progression, we analyzed the transcriptional profiles of archival sentinel node biopsy specimens obtained from melanoma patients. Biopsies from positive nodes were selected for comparable tumor infiltration, presence or absence of further regional node metastases, and relapse at 5-year follow-up. Unsupervised analysis of gene expression profiles revealed immune response to be a major gene ontogeny represented. Among genes upregulated in patients with progressing disease, the TNF receptor family member CD30/TNFRSF8 was confirmed in biopsy specimens from an independent group of patients. Immunohistochemical analysis revealed higher numbers of CD30(+) lymphocytes in nodes from progressing patients compared with nonprogressing patients. Phenotypic profiling demonstrated that CD30(+) lymphocytes comprised a broad population of suppressive or exhausted immune cells, such as CD4(+)Foxp3(+) or PD1(+) subpopulations and CD4(-)CD8(-) T cells. CD30(+) T lymphocytes were increased in peripheral blood lymphocytes of melanoma patients at advanced disease stages. Our findings reinforce the concept that sentinel nodes act as pivotal sites for determining progression patterns, revealing that the presence of CD30(+) lymphocytes at those sites associate positively with melanoma progression.

Measurement of plasma renin concentration instead of plasma renin activity decreases the positive aldosterone-to-renin ratio tests in treated patients with essential hypertension

Background: The plasma aldosterone-to-renin ratio (ARR) for the diagnosis of primary aldosteronism is normally calculated with plasma renin activity (PRA) as denominator. However, new direct renin assays that measure plasma renin concentration (PRC) are progressively replacing PRA because these are faster, simpler, and more reproducible. Objective: To assess whether the calculation of ARR with a direct assay (ARRD, ng/dl/mU/l) instead of PRA (ARRP, ng/dl/ng/ml/h) affects the rate of positive tests in patients on liberal antihypertensive treatment. Design and participants: PRA, PRC, and plasma aldosterone concentration (PAC) were measured in 88 patients with essential hypertension, both in the supine position and after 60 min of active standing while on treatment with a variety of antihypertensive medications. The same measurements were carried out, for comparison, in 10 patients with proven aldosterone-producing adenoma. Setting: Single center, outpatient hypertension clinic in a tertiary care hospital. Results: In patients with essential hypertension, median ARRP was 12 (range 0–71) in the supine position and 13 (range 0–80) after standing. The corresponding values of ARRD were 0.4 (range 0.01–3) and 0.5 (range 0.02–7.8). Between ARRP and ARRD, there was a linear, highly significant relationship both in supine and standing position (r = 0.88 and r = 0.92, respectively). Using as threshold of normalcy for ARRP a value less than 30, as it is recommended by guidelines, there were 13 (15%) and 18 (20%) false positives, respectively in supine and standing position, whereas with the threshold of 3.7 for ARRD, there were no false positives in recumbent position and four (5%) after standing. Accordingly, the specificity of ARRP was 0.85 and 0.78 and that of ARRD 1 and 0.95. In 10 patients with primary aldosteronism, median supine ARRP was 298 (range 48–1222) and ARRD 34 (range 2.8–244). Among these patients, no false negatives were found with ARRP and just one with ARRD. Conclusion: The rate of positive tests calculating ARR with PRC is lower than with PRA, the lower rate being found in patients studied in the recumbent position and apparently it is not affected by ongoing antihypertensive treatment.

Verification of the harmonization of human epididymis protein 4 assays.

Abstract Background: Serum human epididymis protein 4 (HE4) has gained relevance as an ovarian cancer (OC) biomarker and new automated methods have replaced the first released manual EIA by tracing results to it. We verified agreement and bias of automated methods vs. EIA as well as possible effects on patients’ management. Methods: One hundred and fifteen serum samples were measured by Abbott Architect i2000, Fujirebio Lumipulse G1200, Roche Modular E170, and Fujirebio EIA. Passing-Bablok regression was used to compare automated assays to EIA and agreement between methods was estimated by Lin’s concordance correlation coefficient (CCC). The bias vs. EIA was estimated and compared to specifications derived from HE4 biological variation. Results: Median (25th–75th percentiles) HE4 concentrations (pmol/L) were 84.5 (60.1–148.8) for EIA, 82.7 (50.3–153.9) for Abbott, 89.1 (55.2–154.9) for Roche, and 112.2 (67.8–194.2) for Fujirebio. Estimated regressions and agreements (95% confidence interval) were: Abbott=1.01(0.98–1.03) EIA–4.8(–7.5/–2.6), CCC=0.99(0.99–1.00); Roche=0.91(0.89–0.93) EIA+5.7(4.2/8.0), CCC=0.98(0.98–0.99); Fujirebio=1.20(1.17–1.24) EIA+ 2.4(–0.6/4.9), CCC=0.97(0.96–0.98). The average bias vs. EIA resulted within the desirable goal for Abbott [–3.3% (–6.1/–0.5)] and Roche [–0.2% (–3.0/2.5)]. However, while for Abbott the bias was constant and acceptable along the measurement concentration range, Roche bias increased up to –28% for HE4 values >250 pmol/L. Lumipulse showed a markedly positive bias [25.3% (21.8/28.8)]. Conclusions: Abbott and Roche assays exhibited a good comparability in the range of HE4 values around the previously recommended 140 pmol/L cut-off. For patient monitoring, however, the assay used for determining serial HE4 must not be changed as results from different systems in lower and higher concentration ranges can markedly differ.

Assessing Agreement between miRNA Microarray Platforms

Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland–Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland–Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland–Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.

Bioinformatics and Nanotechnologies: Nanomedicine

In this chapter we focus on the bioinformatics strategies for translating genome-wide expression analyses into clinically useful cancer markers with a specific focus on breast cancer with a perspective on new diagnostic device tools coming from the field of nanobiotechnology and the challenges related to high-throughput data integration, analysis, and assessment from multiple sources. Great progress in the development of molecular biology techniques has been seen since the discovery of the structure of deoxyribonucleic acid (DNA) and the implementation of a polymerase chain reaction (PCR) method. This started a new era of research on the structure of nucleic acids molecules, the development of new analytical tools, and DNA-based analyses that allowed the sequencing of the human genome, the completion of which has led to intensified efforts toward comprehensive analysis of mammalian cell struc ture and metabolism in order to better understand the mechanisms that regulate normal cell behavior and identify the gene alterations responsible for a broad spectrum of human diseases, such as cancer, diabetes, cardiovascular diseases, neurodegenerative disorders, and others.

Assessing Agreement between microRNA Microarray Platforms via Linear Measurement Error Models

Over the last years miRNA microarray platforms have provided insights in the biological mechanisms underlying onset and development of several diseases and have thus become a very popular instrument for profiling thousands of miRNA simultaneously. However, because of large variety of microarray platforms available, an assessment of their performance in terms of both within-platform reliability and between-platform agreement is needful. In particular, assessment of platform concordance has been a very relevant issue in the past decade. To date, only a few studies have evaluated this problem in the field of miRNA microarray, and mostly by using improper statistical methods such as the Pearson and Spearman correlation coefficients. In this work we suggest to use a recently proposed modified version of the classical Bland-Altman approach for comparing clinical measurement methods. This modified version is useful in that allows not only to evaluate agreement between different miRNA microarray platforms, but also to assess which are the potential sources of disagreement/bias between them.

Validation of Gene Expression Profiles in Genomic Data through Complementary Use of Cluster Analysis and PCA-Related Biplots

High-throughput genomic assays are used in molecular biology to explore patterns of joint expression of thousands of genes. These methodologies had relevant developments in the last decade, and concurrently there was a need for appropriate methods for analyzing the massive data generated. Identifying sets of genes and samples characterized by similar values of expression and validating these results are two critical issues related to these investigations because of their clinical implication. From a statistical perspective, unsupervised class discovery methods like Cluster Analysis are generally adopted. However, the use of Cluster Analysis mainly relies on the use of hierarchical techniques without considering possible use of other methods. This is partially due to software availability and to easiness of representation of results through a heatmap, which allows to simultaneously visualize clusterization of genes and samples on the same graphical device. One drawback of this strategy is that clusters’ stability is often neglected, thus leading to over-interpretation of results. Moreover, validation of results using external datasets is still subject of discussion, since it is well known that batch effects may condition gene expression results even after normalization. In this paper we compared several clustering algorithms (hierarchical, k-means, model-based, Affinity Propagation) and stability indices to discover common patterns of expression and to assess clustering reliability, and propose a rank-based passive projection of Principal Components for validation purposes. Results from a study involving 23 tumor cell lines and 76 genes related to a specific biological pathway and derived from a publicly available dataset, are presented.

Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models

MiRNAs are short ribonucleic acid (RNA) molecules, acting as post-transcriptional regulators. Intensity levels of thousand of miRNAs are commonly measured via microarray platforms,with pros and cons similar to those for gene expression arrays.