The neuromuscular junction has retained through evolution the capacity to regenerate after damage, but little is known on the inter‐cellular signals involved in its functional recovery from trauma, autoimmune attacks, or neurotoxins. We report here that CXCL12α, also abbreviated as stromal‐derived factor‐1 (SDF‐1), is produced specifically by perisynaptic Schwann cells following motor axon terminal degeneration induced by α‐latrotoxin. CXCL12α acts via binding to the neuronal CXCR4 receptor. A CXCL12α‐neutralizing antibody or a specific CXCR4 inhibitor strongly delays recovery from motor neuron degeneration in vivo. Recombinant CXCL12α in vivo accelerates neurotransmission rescue upon damage and very effectively stimulates the axon growth of spinal cord motor neurons in vitro. These findings indicate that the CXCL12α‐CXCR4 axis plays an important role in the regeneration of the neuromuscular junction after motor axon injury. The present results have important implications in the effort to find therapeutics and protocols to improve recovery of function after different forms of motor axon terminal damage. Synopsis Motor axon terminal degeneration induces perisynaptic Schwann cells to release the chemokine CXCL12α, which binds to neuronal CXCR4 receptors promoting axonal growth to reform a functional neuromuscular junction. The levels of both CXCL12α mRNA and the encoded protein increase in perisynaptic Schwann cells upon nerve terminal degeneration induced by the spider toxin α‐latrotoxin. In vivo neutralization of the chemokine by a specific antibody or inhibition of its receptor CXCR4 delay neuromuscular junction functional recovery after neurodegeneration. In vivo administration of recombinant CXCL12α accelerates neuroregeneration most likely by promoting the growth of motor axons.

Acid ceramidase (AC) is a lysosomal cysteine hydrolase that catalyzes the conversion of ceramide into fatty acid and sphingosine. This reaction lowers intracellular ceramide levels and concomitantly generates sphingosine used for sphingosine-1-phosphate (S1P) production. Since increases in ceramide and consequent decreases of S1P reduce proliferation of various cancers, AC might offer a new target for anti-tumor therapy. Here we used CrispR-Cas9-mediated gene editing to delete the gene encoding for AC, ASAH1, in human A375 melanoma cells. ASAH1-null clones show significantly greater accumulation of long-chain saturated ceramides that are substrate for AC. As seen with administration of exogenous ceramide, AC ablation blocks cell cycle progression and accelerates senescence. Importantly, ASAH1-null cells also lose the ability to form cancer-initiating cells and to undergo self-renewal, which is suggestive of a key role for AC in maintaining malignancy and self-renewal of invasive melanoma cells. The results suggest that AC inhibitors might find therapeutic use as adjuvant therapy for advanced melanoma.

Papillary thyroid cancer is the most common endocrine malignancy. The most sensitive and specific diagnostic tool for thyroid nodule diagnosis is fine-needle aspiration (FNA) biopsy with cytological evaluation. Nevertheless, FNA biopsy is not always decisive leading to “indeterminate” or “suspicious” diagnoses in 10 %–30 % of cases. BRAF V600E detection is currently used as molecular test to improve the diagnosis of thyroid nodules, yet it lacks sensitivity. The aim of the present study was to identify novel molecular markers/computational models to improve the discrimination between benign and malignant thyroid lesions. We collected 118 pre-operative thyroid FNA samples. All 118 FNA samples were characterized for the presence of the BRAF V600E mutation (exon15) by pyrosequencing and further assessed for mRNA expression of four genes (KIT, TC1, miR-222, miR-146b) by quantitative polymerase chain reaction. Computational models (Bayesian Neural Network Classifier, discriminant analysis) were built, and their ability to discriminate benign and malignant tumors were tested. Receiver operating characteristic (ROC) analysis was performed and principal component analysis was used for visualization purposes. In total, 36/70 malignant samples carried the V600E mutation, while all 48 benign samples were wild type for BRAF exon15. The Bayesian neural network (BNN) and discriminant analysis, including the mRNA expression of the four genes (KIT, TC1, miR-222, miR-146b) showed a very strong predictive value (94.12 % and 92.16 %, respectively) in discriminating malignant from benign patients. The discriminant analysis showed a correct classification of 100 % of the samples in the malignant group, and 95 % by BNN. KIT and miR-146b showed the highest diagnostic accuracy of the ROC curve, with area under the curve values of 0.973 for KIT and 0.931 for miR-146b. The four genes model proposed in this study proved to be highly discriminative of the malignant status compared with BRAF assessment alone. Its implementation in clinical practice can help in identifying malignant/benign nodules that would otherwise remain suspicious.

Myocardial fibrosis (MF) is a deleterious consequence of aortic valve stenosis (AVS). Global longitudinal strain (GLS) is a novel left ventricular (LV) functional parameter potentially useful to non-invasively estimate MF. MicroRNAs (miRNAs) are non-coding small ribonucleic acids (RNA) modulating genes function, mainly through RNA degradation. miRNA-21 is a biomarker associated with MF in pressure overload. The aim of the present study was to find an integrated algorithm for detection of MF using a combined approach with both bio- and functional markers. Thirty-six patients (75.2 ± 8 y.o.; 63 % Female) with severe AVS and preserved LV ejection fraction (EF), candidate to surgical aortic valve replacement (sAVR) were enrolled. Clinical, bio-humoral evaluation (including plasmatic miRNA-21 collected using specific tubes, PAXgene, for stabilization of peripheral RNA) and a complete echocardiographic study, including GLS and septal strain, were performed before sAVR. Twenty-eight of those patients underwent sAVR and, in 23 of them, an inter-ventricular septum biopsy was performed. Tissues were fixed in formalin and embedded in paraffin. Sections were stained with Hematoxylin and Eosin for histological evaluation and with histochemical Masson trichrome for collagen fibers. The different components were calculated and expressed as micrometers2. To evaluate tissue miRNA components, sections 2-μm thick were cut using a microtome blade for each slide. Regression analysis was performed to test association between dependent variable and various predictors included in the model. Despite a preserved EF (66 ± 11 %), patients presented altered myocardial deformation parameters (GLS −14,02 ± 3.8 %; septal longitudinal strain, SSL −9.63 ± 2.9 %; septal longitudinal strain rate, SL-Sr −0.58 ± 0.17 1/s; Septal Longitudinal early-diastolic strain rate, SL-SrE 0.62 ± 0.32 1/s). The extent of MF showed an inverse association with both GLS and septal longitudinal deformation indices (GLS: R2 = 0.30; p = 0.02; SSL: R2 = 0.36; p = 0.01; SL-Sr: R2 = 0.39; p < 0.001; SL-SrE: R2 = 0.35; p = 0.001). miRNA-21 was mainly expressed in fibrous tissue (p < 0.0001). A significant association between MF and plasmatic miRNA-21, alone and weighted for measures of structural (LVMi R2 = 0.50; p = 0.0005) and functional (SSL R2 = 0.35; p = 0.006) remodeling, was found. In AVS, MF is associated with alterations of regional and global strain. Plasmatic miRNA-21 is directly related to MF and associated with LV structural and functional impairment.

High-throughput screening of drug sensitivity of cancer cell lines (CCLs) holds the potential to unlock anti-tumor therapies. In this study, we leverage such datasets to predict drug response using cell line transcriptomics, focusing on models’ interpretability and deployment on patients’ data. We use large language models (LLMs) to match drug to mechanisms of action (MOA)-related pathways. Genes crucial for prediction are enriched in drug-MOAs, suggesting that our models learn the molecular determinants of response. Furthermore, by using only LLM-curated, MOA-genes, we enhance the predictive accuracy of our models. To enhance translatability, we align RNAseq data from CCLs, used for training, to those from patient samples, used for inference. We validated our approach on TCGA samples, where patients’ best scoring drugs match those prescribed for their cancer type. We further predict and experimentally validate effective drugs for the patients of two highly lethal solid tumors, i.e., pancreatic cancer and glioblastoma.

Background: Glioblastoma (GB) is the most severe form of brain cancer, with a 12-15 month median survival. Surgical resection, temozolomide (TMZ) treatment, and radiotherapy remain the primary therapeutic options for GB, and no new therapies have been introduced in recent years. This therapeutic standstill is primarily due to preclinical approaches that do not fully respect the complexity of GB cell biology and fail to test efficiently anti-cancer treatments. Therefore, better treatment screening approaches are needed. In this study, we have developed a novel functional precision medicine approach to test the response to anticancer treatments in organoids derived from the resected tumors of glioblastoma patients.Methods: GB organoids were grown for a short period of time to prevent any genetic and morphological evolution and divergence from the tumor of origin. We chose metabolic imaging by NAD(P)H fluorescence lifetime imaging microscopy (FLIM) to predict early and non-invasively ex-vivo anti-cancer treatment responses of GB organoids. TMZ was used as the benchmark drug to validate the approach. Whole-transcriptome and whole-exome analyses were performed to characterize tumor cases stratification.Results: Our functional precision medicine approach was completed within one week after surgery and two groups of TMZ Responder and Non-Responder tumors were identified. FLIM-based metabolic tumor stratification was well reflected at the molecular level, confirming the validity of our approach, highlighting also new target genes associated with TMZ treatment and identifying a new 17-gene molecular signature associated with survival. The number of MGMT gene promoter methylated tumors was higher in the responsive group, as expected, however, some non-methylated tumor cases turned out to be nevertheless responsive to TMZ, suggesting that our procedure could be synergistic with the classical MGMT methylation biomarker.Conclusions: For the first time, FLIM-based metabolic imaging was used on live glioblastoma organoids. Unlike other approaches, ex-vivo patient-tailored drug response is performed at an early stage of tumor culturing with no animal involvement and with minimal tampering with the original tumor cytoarchitecture. This functional precision medicine approach can be exploited in a range of clinical and laboratory settings to improve the clinical management of GB patients and implemented on other cancers as well.