Bone and muscle have been recognized as endocrine organs since they produce and secrete “hormone-like factors” that can mutually influence each other and other tissues, giving rise to a “bone–muscle crosstalk”. In our study, we made use of myogenic (C2C12 cells) and osteogenic (2T3 cells) cell lines to investigate the effects of muscle cell-produced factors on the maturation process of osteoblasts. We found that the myogenic medium has inhibitory effects on bone cell differentiation and we identified sclerostin as one of the myokines produced by muscle cells. Sclerostin is a secreted glycoprotein reportedly expressed by bone/cartilage cells and is considered a negative regulator of bone growth due to its role as an antagonist of the Wnt/β-catenin pathway. Given the inhibitory role of sclerostin in bone, we analyzed its expression by muscle cells and how it affects bone formation and homeostasis. Firstly, we characterized and quantified sclerostin synthesis by a myoblast cell line (C2C12) and by murine primary muscle cells by Western blotting, real-time PCR, immunofluorescence, and ELISA assay. Next, we investigated in vivo production of sclerostin in distinct muscle groups with different metabolic and mechanical loading characteristics. This analysis was done in mice of different ages (6 weeks, 5 and 18 months after birth) and revealed that sclerostin expression is dynamically modulated in a muscle-specific way during the lifespan. Finally, we transiently expressed sclerostin in the hind limb muscles of young mice (2 weeks of age) via in vivo electro-transfer of a plasmid containing the SOST gene in order to investigate the effects of muscle-specific overproduction of the protein. Our data disclosed an inhibitory role of the muscular sclerostin on the bones adjacent to the electroporated muscles. This observation suggests that sclerostin released by skeletal muscle might synergistically interact with osseous sclerostin and potentiate negative regulation of osteogenesis possibly by acting in a paracrine/local fashion. Our data point out a role for muscle as a new source of sclerostin.

Background. Biobanks are vital research infrastructures aiming to collect, process, store, and distribute biological specimens along with associated data in an organized and governed manner. Exploiting diverse datasets produced by the biobanks and the downstream research from various sources and integrating bioinformatics and “omics” data has proven instrumental in advancing research such as cancer research. Biobanks offer different types of biological samples matched with rich datasets comprising clinicopathologic information. As digital pathology and artificial intelligence (AI) have entered the precision medicine arena, biobanks are progressively transitioning from mere biorepositories to integrated computational databanks. Consequently, the application of AI and machine learning on these biobank datasets holds huge potential to profoundly impact cancer research. Methods. In this paper, we explore how AI and machine learning can respond to the digital evolution of biobanks with flexibility, solutions, and effective services. We look at the different data that ranges from specimen-related data, including digital images, patient health records and downstream genetic/genomic data and resulting “Big Data” and the analytic approaches used for analysis. Results. These cutting-edge technologies can address the challenges faced by translational and clinical research, enhancing their capabilities in data management, analysis, and interpretation. By leveraging AI, biobanks can unlock valuable insights from their vast repositories, enabling the identification of novel biomarkers, prediction of treatment responses, and ultimately facilitating the development of personalized cancer therapies. Conclusions. The integration of biobanking with AI has the potential not only to expand the current understanding of cancer biology but also to pave the way for more precise, patient-centric healthcare strategies.

Bile-duct cancers (BDC) are a group of solid tumors arising from the biliary tree. Despite their classification as rare cancers, the incidence of BDC is increasing worldwide. Poor prognosis is a common feature of this type of cancer and is mainly determined by the following factors: late diagnosis, lack of effective therapeutic approaches, and resistance to conventional treatments. In the past few years, next-generation sequencing technologies has allowed us to study the genome, exome, and transcriptome of BDC deeper, revealing a previously underestimated class of RNA: the noncoding RNA (ncRNA). MicroRNAs (miRNAs) are small ncRNAs that play an important regulatory role in gene expression. The aberrant expression of miRNAs and their pivotal role as oncogenes or tumor suppressors in biliary carcinogenesis has been widely described in BDC. Due to their ability to regulate multiple gene networks, miRNAs are involved in all cancer hallmarks, including sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing/accessing vasculature, activating invasion and metastasis, reprogramming cellular metabolism, and avoiding immune destruction. Their use as diagnostic, prognostic, and predictive biomarkers has been widely explored in several human cancers, including BDC. Furthermore, miRNA-based therapeutic strategies are currently the subject of numerous clinical trials that are providing evidence of their efficacy as potent anticancer agents. In this review, we will provide a detailed update of miRNAs affecting BDC, discussing their regulatory function in processes underlying the molecular pathology of BDC. Finally, an overview of their potential use as biomarkers or therapeutic tools in BDC will be further addressed.

Nowadays, in the case of suspected prostate cancer (PCa), tissue needle biopsy remains the benchmark for diagnosis despite its invasiveness and poor tolerability, as serum prostate-specific antigen (PSA) is limited by low specificity. The aim of this proteomic study was to identify new diagnostic biomarkers in urine, an easily and non-invasively available sample, able to selectively discriminate cancer from benign prostatic hyperplasia (BPH), evaluating whether the presence of inflammation may be a confounding parameter. The analysis was performed by two-dimensional gel electrophoresis (2-DE), mass spectrometry (LC-MS/MS) and Enzyme-Linked Immunosorbent Assay (ELISA) on urine samples from PCa and BPH patients, divided into subgroups based on the presence or absence of inflammation. Significant quantitative and qualitative differences were found in the urinary proteomic profile of PCa and BPH groups. Of the nine differentially expressed proteins, only five can properly be considered potential biomarkers of PCa able to discriminate the two diseases, as they were not affected by the inflammatory process. Therefore, the proteomic research of novel and reliable urinary biomarkers of PCa should be conducted considering the presence of inflammation as a realistic interfering element, as it could hinder the detection of important protein targets.