Purpose. Nerve growth factor efficacy was demonstrated for corneal lesions treatment, and recombinant human NGF (rhNGF) was approved for neurotrophic keratitis therapy. However, NGF-induced molecular responses in cornea are still largely unknown. We analyzed microRNAs expression in human epithelial corneal cells after time-dependent rhNGF treatment. Methods. Nearly 700 microRNAs were analyzed by qRT-PCR. MicroRNAs showing significant expression differences were examined by DIANA-miRpath v.3.0 to identify target genes and pathways. Immunoblots were performed to preliminarily assess the strength of the in silico results. Results. Twenty-one microRNAs (miR-26a-1-3p, miR-30d-3p, miR-27b-5p, miR-146a-5p, miR-362-5p, mir-550a-5p, mir-34a-3p, mir-1227-3p, mir-27a-5p, mir-222-5p, mir-151a-5p, miR-449a, let7c-5p, miR-337-5p, mir-29b-3p, miR-200b-3p, miR-141-3p, miR-671-3p, miR-324-5p, mir-411-3p, and mir-425-3p) were significantly regulated in response to rhNGF. In silico analysis evidenced interesting target genes and pathways, including that of neurotrophin, when analyzed in depth. Almost 80 unique target genes (e.g., PI3K, AKT, MAPK, KRAS, BRAF, RhoA, Cdc42, Rac1, Bax, Bcl2, FasL) were identified as being among those most involved in neurotrophin signaling and in controlling cell proliferation, growth, and apoptosis. AKT and RhoA immunoblots demonstrated congruence with microRNA expression, providing preliminary validation of in silico data. Conclusions. MicroRNA levels in response to rhNGF were for the first time analyzed in corneal cells. Novel insights about microRNAs, target genes, pathways modulation, and possible biological responses were provided. Importantly, given the putative role of microRNAs as biomarkers or therapeutic targets, our results make available data which might be potentially exploitable for clinical applications.

In the rapidly evolving field of genomics, understanding the genetic basis of complex diseases like breast cancer, particularly its familial/hereditary forms, is crucial. Current methods often examine genomic variants—such as Single Nucleotide Variants (SNVs), insertions/deletions (Indels), and Copy Number Variations (CNVs)—separately, lacking an integrated approach. Here, we introduced a robust, flexible methodology for a comprehensive variants’ analysis using Whole Exome Sequencing (WES) data. Our approach uniquely combines meticulous validation with an effective variant filtering strategy. By reanalyzing two germline WES datasets from BRCA1/2 negative breast cancer patients, we demonstrated our tool’s efficiency and adaptability, uncovering both known and novel variants. This contributed new insights for potential diagnostic, preventive, and therapeutic strategies. Our method stands out for its comprehensive inclusion of key genomic variants in a unified analysis, and its practical resolution of technical challenges, offering a pioneering solution in genomic research. This tool presents a breakthrough in providing detailed insights into the genetic alterations in genomes, with significant implications for understanding and managing hereditary breast cancer.

As the first FDA-approved tyrosine kinase inhibitor for treatment of patients with myelofibrosis (MF), ruxolitinib improves clinical symptoms but does not lead to eradication of the disease or significant reduction of the mutated allele burden. The resistance of MF clones against the suppressive action of ruxolitinib may be due to intrinsic or extrinsic mechanisms leading to activity of additional pro-survival genes or signalling pathways that function independently of JAK2/STAT5. To identify alternative therapeutic targets, we applied a pooled-shRNA library targeting ~5000 genes to a JAK2^V617F-positive cell line under a variety of conditions, including absence or presence of ruxolitinib and in the presence of a bone marrow microenvironment-like culture medium. We identified several proteasomal gene family members as essential to HEL cell survival. The importance of these genes was validated in MF cells using the proteasomal inhibitor carfilzomib, which also enhanced lethality in combination with ruxolitinib. We also showed that proteasome gene expression is reduced by ruxolitinib in MF CD34⁺ cells and that additional targeting of proteasomal activity by carfilzomib enhances the inhibitory action of ruxolitinib in vitro. Hence, this study suggests a potential role for proteasome inhibitors in combination with ruxolitinib for management of MF patients.

Reproducibility is a crucial aspect of scientific research that involves the ability to independently replicate experimental results by analysing the same data or repeating the same experiment. Over the years, many works have been proposed to make the results of the experiments actually reproducible. However, very few address the importance of data reproducibility, defined as the ability of independent researchers to retain the same dataset used as input for experimentation. Properly addressing the problem of data reproducibility is crucial because often just providing a link to the data is not enough to make the results reproducible. In fact, also proper metadata (e.g., preprocessing instruction) must be provided to make a dataset fully reproducible. In this work, our aim is to fill this gap by proposing a decision tree to sheperd researchers through the reproducibility of their datasets. In particular, this decision tree guides researchers through identifying if the dataset is actually reproducible and if additional metadata (i.e., additional resources needed to reproduce the data) must also be provided. This decision tree will be the foundation of a future application that will automate the data reproduction process by automatically providing the necessary metadata based on the particular context (e.g., data availability, data preprocessing, and so on). It is worth noting that, in this paper, we detail the steps to make a dataset retrievable, while we will detail other crucial aspects for reproducibility (e.g., dataset documentation) in future works.