Machine learning classification of archaea and bacteria identifies novel predictive genomic features.

BACKGROUND: Archaea and Bacteria are distinct domains of life that are adapted to a variety of ecological niches. Several genome-based methods have been developed for their accurate classification, yet many aspects of the specific genomic features that determine these differences are not fully understood. In this study, we used publicly available whole-genome sequences from bacteria ( N = 2546 ) and archaea ( N = 109 ). From these, a set of genomic features (nucleotide frequencies and proportions, coding sequences (CDS), non-coding, ribosomal and transfer RNA genes (ncRNA, rRNA, tRNA), Chargaff's, topological entropy and Shannon's entropy scores) was extracted and used as input data to develop machine learning models for the classification of archaea and bacteria. RESULTS: The classification accuracy ranged from 0.993 (Random Forest) to 0.998 (Neural Networks). Over the four models, only 11 examples were misclassified, especially those belonging to the minority class (Archaea). From variable importance, tRNA topological and Shannon's entropy, nucleotide frequencies in tRNA, rRNA and ncRNA, CDS, tRNA and rRNA Chargaff's scores have emerged as the top discriminating factors. In particular, tRNA entropy (both topological and Shannon's) was the most important genomic feature for classification, pointing at the complex interactions between the genetic code, tRNAs and the translational machinery. CONCLUSIONS: tRNA, rRNA and ncRNA genes emerged as the key genomic elements that underpin the classification of archaea and bacteria. In particular, higher nucleotide diversity was found in tRNA from bacteria compared to archaea. The analysis of the few classification errors reflects the complex phylogenetic relationships between bacteria, archaea and eukaryotes.

TumFlow: An AI Model for Predicting New Anticancer Molecules.

Melanoma is the fifth most common cancer in the United States. Conventional drug discovery methods are inherently time-consuming and costly, which imposes significant limitations. However, the advent of Artificial Intelligence (AI) has opened up new possibilities for simulating and evaluating numerous drug candidates, thereby mitigating the requisite time and resources. In this context, normalizing flow models by employing machine learning techniques to create new molecular structures holds promise for accelerating the discovery of effective anticancer therapies. This manuscript introduces TumFlow, a novel AI model designed to generate new molecular entities with potential therapeutic value in cancer treatment. It has been trained on the NCI-60 dataset, encompassing thousands of molecules tested across 60 tumour cell lines, with an emphasis on the melanoma SK-MEL-28 cell line. The model successfully generated new molecules with predicted improved efficacy in inhibiting tumour growth while being synthetically feasible. This represents a significant advancement over conventional generative models, which often produce molecules that are challenging or impossible to synthesize. Furthermore, TumFlow has also been utilized to optimize molecules known for their efficacy in clinical melanoma treatments. This led to the creation of novel molecules with a predicted enhanced likelihood of effectiveness against melanoma, currently undocumented on PubChem.

Apoptosis, a Metabolic "Head-to-Head" between Tumor and T Cells: Implications for Immunotherapy.

Induction of apoptosis represents a promising therapeutic approach to drive tumor cells to death. However, this poses challenges due to the intricate nature of cancer biology and the mechanisms employed by cancer cells to survive and escape immune surveillance. Furthermore, molecules released from apoptotic cells and phagocytes in the tumor microenvironment (TME) can facilitate cancer progression and immune evasion. Apoptosis is also a pivotal mechanism in modulating the strength and duration of anti-tumor T-cell responses. Combined strategies including molecular targeting of apoptosis, promoting immunogenic cell death, modulating immunosuppressive cells, and affecting energy pathways can potentially overcome resistance and enhance therapeutic outcomes. Thus, an effective approach for targeting apoptosis within the TME should delicately balance the selective induction of apoptosis in tumor cells, while safeguarding survival, metabolic changes, and functionality of T cells targeting crucial molecular pathways involved in T-cell apoptosis regulation. Enhancing the persistence and effectiveness of T cells may bolster a more resilient and enduring anti-tumor immune response, ultimately advancing therapeutic outcomes in cancer treatment. This review delves into the pivotal topics of this multifaceted issue and suggests drugs and druggable targets for possible combined therapies.

Transcriptomics Studies Reveal Functions of Transglutaminase 2 in Breast Cancer Cells Using Membrane Permeable and Impermeable Inhibitors.

Transglutaminase 2 (TG2) performs many functions both under physiological and pathological conditions. In cancer, its expression is associated with aggressiveness, propensity to epithelial-mesenchymal transition, and metastasis. Since TG2 performs key functions both outside and inside the cell, using inhibitors with different membrane permeability we analyzed the changes in the transcriptome induced in two triple-negative cell lines (MDA-MB-436 and MDA-MB-231) with aggressive features. By characterizing pathways and gene networks, we were able to define the effects of TG2 inhibitors (AA9, membrane-permeable, and NCEG2, impermeable) in relation to the roles of the enzyme in the intra- and extracellular space within the context of breast cancer. The deregulated genes revealed p53 and integrin signaling to be the common pathways with some genes showing opposite changes in expression. In MDA-MB-436, AA9 induced apoptosis, modulated cadherin, Wnt, gastrin and cholecystokinin receptors (CCKR) mediated signaling, with RHOB and GNG2 playing significant roles, and affected the Warburg effect by decreasing glycolytic enzymes. In MDA-MB-231 cells, AA9 strongly impacted HIF-mediated hypoxia, including AKT and mTOR pathway. These effects suggest an anti-tumor activity by blocking intracellular TG2 functions. Conversely, the use of NCEG2 stimulated the expression of ATP synthase and proteins involved in DNA replication, indicating a potential promotion of cell proliferation through inhibition of extracellular TG2. To effectively utilize these molecules as an anti-tumor strategy, an appropriate delivery system should be evaluated to target specific functions and avoid adverse effects. Additionally, considering combinations with other pathway modulators is crucial.

State-of-the-art in transposable element modulation affected by drugs in malignant prostatic cancer cells.

Over recent years, the investigation of transposable elements (TEs) has granted researchers a deeper comprehension of their characteristics and functions, particularly regarding their significance in the mechanisms contributing to cancer development. This manuscript focuses on prostate carcinoma cell lines and offers a comprehensive review intended to scrutinize the associations and interactions between TEs and genes, as well as their response to treatment using various chemical drugs, emphasizing their involvement in cancer progression. We assembled a compendium of articles retrieved from the PubMed database to construct networks demonstrating correlations with genes and pharmaceuticals. In doing so, we linked the transposition of certain TE types to the expression of specific transcripts directly implicated in carcinogenesis. Additionally, we underline that treatment employing different drugs revealed unique patterns of TE reactivation. Our hypothesis gathers the current understanding and guides research toward evidence-based investigations, emphasizing the association between antiviral drugs, chemotherapy, and the reduced expression of TEs in patients affected by prostate cancer.

Effects of Mithramycin on BCL11A Gene Expression and on the Interaction of the BCL11A Transcriptional Complex to γ-Globin Gene Promoter Sequences.

The anticancer drug mithramycin (MTH), has been proposed for drug repurposing after the finding that it is a potent inducer of fetal hemoglobin (HbF) production in erythroid precursor cells (ErPCs) from ß-thalassemia patients. In this respect, previously published studies indicate that MTH is very active in inducing increased expression of γ-globin genes in erythroid cells. This is clinically relevant, as it is firmly established that HbF induction is a valuable approach for the therapy of ß-thalassemia and for ameliorating the clinical parameters of sickle-cell disease (SCD). Therefore, the identification of MTH biochemical/molecular targets is of great interest. This study is inspired by recent robust evidence indicating that the expression of γ-globin genes is controlled in adult erythroid cells by different transcriptional repressors, including Oct4, MYB, BCL11A, Sp1, KLF3 and others. Among these, BCL11A is very important. In the present paper we report evidence indicating that alterations of BCL11A gene expression and biological functions occur during MTH-mediated erythroid differentiation. Our study demonstrates that one of the mechanisms of action of MTH is a down-regulation of the transcription of the BCL11A gene, while a second mechanism of action is the inhibition of the molecular interactions between the BCL11A complex and specific sequences of the γ-globin gene promoter.

Cell-Impermeable Inhibitors Confirm That Intracellular Human Transglutaminase 2 Is Responsible for the Transglutaminase-Associated Cancer Phenotype.

Transglutaminase 2 (TG2) is a multifunctional enzyme primarily responsible for crosslinking proteins. Ubiquitously expressed in humans, TG2 can act either as a transamidase by crosslinking two substrates through formation of an Nε(ɣ-glutaminyl)lysine bond or as an intracellular G-protein. These discrete roles are tightly regulated by both allosteric and environmental stimuli and are associated with dramatic changes in the conformation of the enzyme. The pleiotropic nature of TG2 and multi-faceted activities have resulted in TG2 being implicated in numerous disease pathologies including celiac disease, fibrosis, and cancer. Targeted TG2 therapies have not been selective for subcellular localization, such that currently no tools exist to selectively target extracellular over intracellular TG2. Herein, we have designed novel TG2-selective inhibitors that are not only highly potent and irreversible, but also cell impermeable, targeting only extracellular TG2. We have also further derivatized the scaffold to develop probes that are intrinsically fluorescent or bear an alkyne handle, which target both intra- and extracellular TG2, in order to facilitate cellular labelling and pull-down assays. The fluorescent probes were internalized and imaged in cellulo, and provide the first implicit experimental evidence that by comparison with their cell-impermeable analogues, it is specifically intracellular TG2, and presumably its G-protein activity, that contributes to transglutaminase-associated cancer progression.

Metabolic characterisation of transglutaminase 2 inhibitor effects in breast cancer cell lines.

Transglutaminase 2 (TG2), which mediates post-translational modifications of multiple intracellular enzymes, is involved in the pathogenesis and progression of cancer. We used 1 H-NMR metabolomics to study the effects of AA9, a novel TG2 inhibitor, on two breast cancer cell lines with distinct phenotypes, MCF-7 and MDA-MB-231. AA9 can promote apoptosis in both cell lines, but it is particularly effective in MD-MB-231, inhibiting transamidation reactions and decreasing cell migration and invasiveness. This metabolomics study provides evidence of a major effect of AA9 on MDA-MB-231 cells, impacting glutamate and aspartate metabolism, rather than on MCF-7 cells, characterised by choline and O-phosphocholine decrease. Interestingly, AA9 treatment induces myo-inositol alteration in both cell lines, indicating action on phosphatidylinositol metabolism, likely modulated by the G protein activity of TG2 on phospholipase C. Considering the metabolic deregulations that characterise various breast cancer subtypes, the existence of a metabolic pathway affected by AA9 further points to TG2 as a promising hot spot. The metabolomics approach provides a powerful tool to monitor the effectiveness of inhibitors and better understand the role of TG2 in cancer.

Protein Kinase C at the Crossroad of Mutations, Cancer, Targeted Therapy and Immune Response.

The frequent PKC dysregulations observed in many tumors have made these enzymes natural targets for anticancer applications. Nevertheless, this considerable interest in the development of PKC modulators has not led to the expected therapeutic benefits, likely due to the complex biological activities regulated by PKC isoenzymes, often playing ambiguous and protective functions, further driven by the occurrence of mutations. The structure, regulation and functions of PKCs have been extensively covered in other publications. Herein, we focused on PKC alterations mostly associated with complete functional loss. We also addressed the modest yet encouraging results obtained targeting PKC in selected malignancies and the more frequent negative clinical outcomes. The reported observations advocate the need for more selective molecules and a better understanding of the involved pathways. Furthermore, we underlined the most relevant immune mechanisms controlled by PKC isoforms potentially impacting the immune checkpoint inhibitor blockade-mediated immune recovery. We believe that a comprehensive examination of the molecular features of the tumor microenvironment might improve clinical outcomes by tailoring PKC modulation. This approach can be further supported by the identification of potential response biomarkers, which may indicate patients who may benefit from the manipulation of distinctive PKC isoforms.

Somatic and Germline Variants Affect Prognosis and Susceptibility in Prostate Cancer.

BACKGROUND/AIM: Prostate cancer (PCa) is one of the most common tumors in men accounting for the 7.3% of all cancer-associated diseases in 2020. In advanced stage, this pathology is a lethal disease and is the fifth cause of cancer death in men worldwide. The diagnosis of PCa is performed by prostate-specific antigen (PSA) detection combined with direct rectal examination (DRE). However, high PSA levels can be detected in non-malignant conditions leading to overtreatment of non-oncological patients. Moreover, PSA levels are not associated with disease progression; therefore, the research of novel biomarkers could improve diagnosis and prognosis of this tumor. In this regard, genetic polymorphisms may affect PCa outcome as well as to be associated with cancer familiarity. In fact, germline variations detected in different genes including BRCA1, BRCA2, ATM and HOXB13 seem to be associated with PCa susceptibility and progression. MATERIALS AND METHODS: Somatic and germline polymorphisms were detected by next generation sequencing (NGS) in 48 PCa subjects and paired controls. Gene variants were matched with patient outcome and cancer familiarity to identify mutations linked to prognosis and tumor predisposition. RESULTS: NGS sequencing has allowed to identify different genetic polymorphisms that could be linked to cancer outcome and predisposition. In particular, somatic and germline mutations found in ATM, FOXA1 and SPOP genes correlate with poor prognosis and/or high Gleason score. Moreover, germline variants lying mainly in ATM, but also in ZFHX3, SPOP, CHD1, CDK12 and APC seem to be associated with hereditary-predisposing cancer syndrome. CONCLUSION: Variants correlating with poor prognosis and cancer susceptibility could be usable as possible tumor biomarkers in prostate cancer.

Inverse Impact of Cancer Drugs on Circular and Linear RNAs in Breast Cancer Cell Lines.

Altered expression of circular RNAs (circRNAs) has previously been investigated in breast cancer. However, little is known about the effects of drugs on their regulation and relationship with the cognate linear transcript (linRNA). We analyzed the dysregulation of both 12 cancer-related circRNAs and their linRNAs in two breast cancer cell lines undergoing various treatments. We selected 14 well-known anticancer agents affecting different cellular pathways and examined their impact. Upon drug exposure circRNA/linRNA expression ratios increased, as a result of the downregulation of linRNA and upregulation of circRNA within the same gene. In this study, we highlighted the relevance of identifying the drug-regulated circ/linRNAs according to their oncogenic or anticancer role. Interestingly, VRK1 and MAN1A2 were increased by several drugs in both cell lines. However, they display opposite effects, circ/linVRK1 favors apoptosis whereas circ/linMAN1A2 stimulates cell migration, and only XL765 did not alter the ratio of other dangerous circ/linRNAs in MCF-7. In MDA-MB-231 cells, AMG511 and GSK1070916 decreased circGFRA1, as a good response to drugs. Furthermore, some circRNAs might be associated with specific mutated pathways, such as the PI3K/AKT in MCF-7 cells with circ/linHIPK3 correlating to cancer progression and drug-resistance, or NHEJ DNA repair pathway in TP-53 mutated MDA-MB-231 cells.

Circular RNAs Could Encode Unique Proteins and Affect Cancer Pathways.

circRNAs constitute a novel class of RNA, generally considered as non-coding RNAs; nonetheless, their coding potential has been under scrutiny. In this work, we systematically explored the predicted proteins of more than 160,000 circRNAs detected by exome capture RNA-sequencing and collected in the MiOncoCirc pan-cancer compendium, including normal and cancer samples from different types of tissues. For the functional evaluation, we compared their primary structure and domain composition with those derived from the same linear mRNAs. Among the 4362 circRNAs potentially encoding proteins with a unique primary structure and 1179 encoding proteins with a novel domain composition, 183 were differentially expressed in cancer. In particular, eight were associated with prognosis in acute myeloid leukemia. The functional classification of the dysregulated circRNA-encoded polypeptides showed an enrichment in the heme and cancer signaling, DNA-binding, and phosphorylation processes, and disclosed the roles of some circRNA-based effectors in cancer.

Characterization by Gene Expression Analysis of Two Groups of Dopaminergic Cells Isolated from the Mouse Olfactory Bulb.

The olfactory bulb (OB) is one of two regions of the mammalian brain which undergo continuous neuronal replacement during adulthood. A significant fraction of the cells added in adulthood to the bulbar circuitry is constituted by dopaminergic (DA) neurons. We took advantage of a peculiar property of dopaminergic neurons in transgenic mice expressing eGFP under the tyrosine hydroxylase (TH) promoter: while DA neurons located in the glomerular layer (GL) display full electrophysiological maturation, eGFP+ cells in the mitral layer (ML) show characteristics of immature cells. In addition, they also display a lower fluorescence intensity, possibly reflecting different degrees of maturation. To investigate whether this difference in maturation might be confirmed at the gene expression level, we used a fluorescence-activated cell sorting technique on enzymatically dissociated cells of the OB. The cells were divided into two groups based on their level of fluorescence, possibly corresponding to immature ML cells and fully mature DA neurons from the GL. Semiquantitative real-time PCR was performed to detect the level of expression of genes linked to the degree of maturation of DA neurons. We showed that indeed the cells expressing low eGFP fluorescence are immature neurons. Our method can be further used to explore the differences between these two groups of DA neurons.

The rs368698783 (G>A) Polymorphism Affecting LYAR Binding to the Aγ-Globin Gene Is Associated with High Fetal Hemoglobin (HbF) in ß-Thalassemia Erythroid Precursor Cells Treated with HbF Inducers

The human homologue of mouse Ly-1 antibody reactive clone protein (LYAR) is a putative novel regulator of γ-globin gene transcription. The LYAR DNA-binding motif (5'-GGTTAT-3') is located within the 5'-UTR of the Aγ-globin gene. The LYAR rs368698783 (G>A) polymorphism is present in ß-thalassemia patients and decreases the LYAR binding efficiency to the Aγ-globin gene. The objective of this study was to stratify ß-thalassemia patients with respect to the rs368698783 (G>A) polymorphism and to verify whether their erythroid precursor cells (ErPCs) differentially respond in vitro to selected fetal hemoglobin (HbF) inducers. The rs368698783 (G>A) polymorphism was detected by DNA sequencing, hemoglobin production by HPLC, and accumulation of globin mRNAs by RT-qPCR. We found that the LYAR rs368698783 (G>A) polymorphism is associated with high basal and induced production of fetal hemoglobin in ß-thalassemia patients. The most striking association was found using rapamycin as an HbF inducer. The results presented here could be considered important not only for basic biomedicine but also in applied translational research for precision medicine in personalized therapy of ß-thalassemia. Accordingly, our data suggest that the rs368698783 polymorphism might be considered among the parameters useful to recruit patients with the highest probability of responding to in vivo hydroxyurea (HU) treatment.

The inhibition of MDM2 slows cell proliferation and activates apoptosis in ADPKD cell lines.

INTRODUCTION: Autosomal dominant polycystic kidney disease (ADPKD) is characterised by progressive cysts formation and renal enlargement that in most of cases leads to end stage of renal disease (ESRD). This pathology is caused by mutations of either PKD1 or PKD2 genes that encode for polycystin-1 (PC1) and polycystin-2 (PC2), respectively. These proteins function as receptor-channel complex able to regulate calcium homeostasis. PKD1/2 loss of function impairs different signalling pathways including cAMP and mTOR that are considered therapeutic targets for this disease. In fact, Tolvaptan, a vasopressin-2 antagonist that reduces cAMP levels, is the only drug approved for ADPKD treatment. Nevertheless, some ADPKD patients developed side effects in response to Tolvaptan including liver damage. Conversely, mTOR inhibitors that induced disease regression in ADPKD animal models failed the clinical trials. RESULTS: Here, we show that the inhibition of mTOR causes the activation of autophagy in ADPKD cells that could reduce therapy effectiveness by drug degradation through the autophagic vesicles. Consistently, the combined treatment with rapamycin and chloroquine, an autophagy inhibitor, potentiates the decrease of cell proliferation induced by rapamycin. To overcome the dangerous activation of autophagy by mTOR inhibition, we targeted MDM2 (a downstream effector of mTOR signalling) that is involved in TP53 degradation by using RG7112, a small-molecule MDM2 inhibitor used for the treatment of haematologic malignancies. The inhibition of MDM2 by RG7112 prevents TP53 degradation and increases p21 expression leading to the decrease of cell proliferation and the activation of apoptosis. CONCLUSION: The targeting of MDM2 by RG7112 might represent a new therapeutic option for the treatment of ADPKD.

Machine Learning Algorithms Highlight tRNA Information Content and Chargaff's Second Parity Rule Score as Important Features in Discriminating Probiotics from Non-Probiotics.

Probiotic bacteria are microorganisms with beneficial effects on human health and are currently used in numerous food supplements. However, no selection process is able to effectively distinguish probiotics from non-probiotic organisms on the basis of their genomic characteristics. In the current study, four Machine Learning algorithms were employed to accurately identify probiotic bacteria based on their DNA characteristics. Although the prediction accuracies of all algorithms were excellent, the Neural Network returned the highest scores in all the evaluation metrics, managing to discriminate probiotics from non-probiotics with an accuracy greater than 90%. Interestingly, our analysis also highlighted the information content of the tRNA sequences as the most important feature in distinguishing the two groups of organisms probably because tRNAs have regulatory functions and might have allowed probiotics to evolve faster in the human gut environment. Through the methodology presented here, it was also possible to identify seven promising new probiotics that have a higher information content in their tRNA sequences compared to non-probiotics. In conclusion, we prove for the first time that Machine Learning methods can discriminate human probiotic from non-probiotic organisms underlining information within tRNA sequences as the most important genomic feature in distinguishing them.

New Therapeutic Interventions for Kidney Carcinoma: Looking to the Future.

Patients suffering from metastatic renal cell carcinoma (mRCC) show an overall survival rate of lower than 10% after 5 years from diagnosis. Currently, the first-line treatment for mRCC patients is based on antiangiogenic drugs that are able to inhibit tyrosine kinase receptors (TKI) in combination with immuno-oncology (IO) therapy or IO-IO treatments. Second-line therapy involves the use of other TKIs, immunotherapeutic drugs, and mTOR inhibitors. Nevertheless, many patients treated with mTOR and TK inhibitors acquire drug resistance, making the therapy ineffective. Therefore, the research of new therapeutic targets is crucial for improving the overall survival and quality of life of mRCC patients. The investigation of the molecular basis of RCC, especially in clear cell renal cell carcinoma (ccRCC), has led to the identification of different signaling pathways that are involved in renal carcinogenesis. Most of ccRCCs are associated with mutation in VHL gene, which mediates the degradation of hypoxia-inducible factors (HIFs), that, in turn, regulate the pathways related to tumorigenesis, including angiogenesis and invasion. Renal tumorigenesis is also associated with the activation of tyrosine kinases that modulate the PI3K-Akt-mTOR pathway, promoting cell proliferation and survival. In ccRCC, the abnormal activity of mTOR activates the MDM2 protein, which leads to the degradation of tumor suppressor p53 via proteasome machinery. In addition, p53 may be degraded by autophagy in a mechanism involving the enzyme transglutaminase 2 (TG2). Suppression of wild-type p53 promotes cell growth, invasion, and drug resistance. Finally, the activation of ferroptosis appears to inhibit cancer progression in RCC. In conclusion, these pathways might represent new therapeutic targets for mRCC.

Circulating microRNAs Suggest Networks Associated with Biological Functions in Aggressive Refractory Type 2 Celiac Disease.

Despite following a gluten-free diet, which is currently the only effective therapy for celiac disease, about 5% of patients can develop serious complications, which in the case of refractory type 2 could evolve towards intestinal lymphoma. In this study, we have identified a set of 15 microRNAs in serum discriminating between the two types of refractory disease. Upregulated miR-770-5p, miR-181b-2-3p, miR-1193, and miR-1226-3p could be useful for the better stratification of patients and the monitoring of disease development, while miR-490-3p was found to be dysregulated in patients with refractory type 1. Finally, by using bioinformatic tools applied to the analysis of the targets of dysregulated microRNAs, we have completed a more precise assessment of their functions. These mainly include the pathway of response to Transforming Growth Factor ß cell-cell signaling by Wnt; epigenetic regulation, especially novel networks associated with transcriptional and post-transcriptional alterations; and the well-known inflammatory profiles.

Vav1 Selectively Down-Regulates Akt2 through miR-29b in Certain Breast Tumors with Triple Negative Phenotype.

Triple negative breast cancer (TNBC) represents the most aggressive breast tumor, showing a high intrinsic variability in terms of both histopathological features and response to therapies. Blocking the Akt signaling pathway is a well-studied approach in the treatment of aggressive breast tumors. The high homology among the Akt isoforms and their distinct, and possibly opposite, oncogenic functions made it difficult to develop effective drugs. Here we investigated the role of Vav1 as a potential down-regulator of individual Akt isozymes. We revealed that the over-expression of Vav1 in triple negative MDA-MB-231 cells reduced only the Akt2 isoform, acting at the post-transcriptional level through the up-modulation of miR-29b. The Vav1/miR-29b dependent decrease in Akt2 was correlated with a reduced lung colonization of circulating MDA-MB-231 cells. In cell lines established from PDX, the Vav1 induced down-modulation of Akt2 is strongly dependent on miR-29b and occurs only in some TNBC tumors. These findings may contribute to better classify breast tumors having the triple negative phenotype, and suggest that the activation of the Vav1/miR-29b axis, precisely regulating the amount of an Akt isozyme crucial for tumor dissemination, could have great potential for driving more accurate therapies to TNBCs, often not eligible or resistant to treatments.

Detection of disease-causing mutations in prostate cancer by NGS sequencing.

Gene mutations may affect the fate of many tumors including prostate cancer (PCa); therefore, the research of specific mutations associated with tumor outcomes might help the urologist to identify the best therapy for PCa patients such as surgical resection, adjuvant therapy or active surveillance. Genomic DNA (gDNA) was extracted from 48 paraffin-embedded PCa samples and normal paired tissues. Next, gDNA was amplified and analyzed by next-generation sequencing (NGS) using a specific gene panel for PCa. Raw data were refined to exclude false-positive mutations; thus, variants with coverage and frequency lower than 100× and 5%, respectively were removed. Mutation significance was processed by Genomic Evolutionary Rate Profiling, ClinVar, and Varsome tools. Most of 3000 mutations (80%) were single nucleotide variants and the remaining 20% indels. After raw data elaboration, 312 variants were selected. Most mutated genes were KMT2D (26.45%), FOXA1 (16.13%), ATM (15.81%), ZFHX3 (9.35%), TP53 (8.06%), and APC (5.48%). Hot spot mutations in FOXA1, ATM, ZFHX3, SPOP, and MED12 were also found. Truncating mutations of ATM, lesions lying in hot spot regions of SPOP and FOXA1 as well as mutations of TP53 correlated with poor prognosis. Importantly, we have also found some germline mutations associated with hereditary cancer-predisposing syndrome. gDNA sequencing of 48 cancer tissues by NGS allowed to detect new tumor variants as well as confirmed lesions in genes linked to prostate cancer. Overall, somatic and germline mutations linked to good/poor prognosis could represent new prognostic tools to improve the management of PCa patients.