The regenerative medicine, a new discipline that merges biological sciences and the fundamental of engineering to develop biological substitutes, has greatly benefited from recent advances in the material engineering and the role of stem cells in tissue regeneration. Regenerative medicine strategies, involving the combination of biomaterials/scaffolds, cells, and bioactive agents, have been of great interest especially for the repair of damaged bone and bone regrowth. In the last few years, the life expectancy of our population has progressively increased. Aging has highlighted the need for intervention on human bone with biocompatible materials that show high performance for the regeneration of the bone, efficiently and in a short time. In this review, the different aspects of tissue engineering applied to bone engineering were taken into consideration. The first part of this review introduces the bone cellular biology/molecular genetics. Data on biomaterials, stem cells, and specific growth factors for the bone regrowth are reported in this review.

Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4×10⁻³). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associated variants. Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2×10⁻⁵) and the risk of type 2 diabetes (P=6.1×10⁻⁴) associated with the risk of diabetic kidney disease. We also found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1×10⁻⁴). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0×10⁻⁶), and pentose and glucuronate interconversions (P=3.0×10⁻⁶) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.

Detecting somatic mutations in whole exome sequencing data of cancer samples has become a popular approach for profiling cancer development, progression and chemotherapy resistance. Several studies have proposed software packages, filters and parametrizations. However, many research groups reported low concordance among different methods. We aimed to develop a pipeline which detects a wide range of single nucleotide mutations with high validation rates. We combined two standard tools – Genome Analysis Toolkit (GATK) and MuTect – to create the GATK-LODN method. As proof of principle, we applied our pipeline to exome sequencing data of hematological (Acute Myeloid and Acute Lymphoblastic Leukemias) and solid (Gastrointestinal Stromal Tumor and Lung Adenocarcinoma) tumors. We performed experiments on simulated data to test the sensitivity and specificity of our pipeline. The software MuTect presented the highest validation rate (90 %) for mutation detection, but limited number of somatic mutations detected. The GATK detected a high number of mutations but with low specificity. The GATK-LODN increased the performance of the GATK variant detection (from 5 of 14 to 3 of 4 confirmed variants), while preserving mutations not detected by MuTect. However, GATK-LODN filtered more variants in the hematological samples than in the solid tumors. Experiments in simulated data demonstrated that GATK-LODN increased both specificity and sensitivity of GATK results. We presented a pipeline that detects a wide range of somatic single nucleotide variants, with good validation rates, from exome sequencing data of cancer samples. We also showed the advantage of combining standard algorithms to create the GATK-LODN method, that increased specificity and sensitivity of GATK results. This pipeline can be helpful in discovery studies aimed to profile the somatic mutational landscape of cancer genomes.

Background: Aneuploidy occurs in more than 20% of acute myeloid leukemia (AML) cases and correlates with an adverse prognosis. Methods: To understand the molecular bases of aneuploid acute myeloid leukemia (A‐AML), this study examined the genomic profile in 42 A‐AML cases and 35 euploid acute myeloid leukemia (E‐AML) cases. Results: A‐AML was characterized by increased genomic complexity based on exonic variants (an average of 26 somatic mutations per sample vs 15 for E‐AML). The integration of exome, copy number, and gene expression data revealed alterations in genes involved in DNA repair (eg, SLX4IP , RINT1 , HINT1 , and ATR ) and the cell cycle (eg, MCM2 , MCM4 , MCM5 , MCM7 , MCM8 , MCM10 , UBE2C , USP37 , CK2 , CK3 , CK4 , BUB1B , NUSAP1 , and E2F ) in A‐AML, which was associated with a 3‐gene signature defined by PLK1 and CDC20 upregulation and RAD50 downregulation and with structural or functional silencing of the p53 transcriptional program. Moreover, A‐AML was enriched for alterations in the protein ubiquitination and degradation pathway (eg, increased levels of UHRF1 and UBE2C and decreased UBA3 expression), response to reactive oxygen species, energy metabolism, and biosynthetic processes, which may help in facing the unbalanced protein load. E‐AML was associated with BCOR / BCORL1 mutations and HOX gene overexpression. Conclusions: These findings indicate that aneuploidy‐related and leukemia‐specific alterations cooperate to tolerate an abnormal chromosome number in AML, and they point to the mitotic and protein degradation machineries as potential therapeutic targets.