Synthetic lethal hubs associated with vincristine resistant neuroblastoma

Nanoparticle-mediated tumor vaccines for personalized therapy: preparing tumor antigens in vivo or ex vivo?

Tumor vaccines, focusing on tailoring individual tumor antigens, have gained much attention in personalized tumor therapy. Recently, breakthroughs have been made in the development of tumor vaccines thanks to the progress in nanotechnology. We will summarize nanoparticle-mediated tumor vaccines for personalized therapy in this review. ROS/heat generating nanoparticles and molecules could induce immunogenic cell death and tumor antigen release in vivo. This strategy often includes chemotherapy, radiotherapy, photodynamic therapy, photothermal therapy, magneto-thermal therapy, etc. On the other hand, ex vivo technologies have been applied for processing of tumor cells/tissues to form effective tumor antigens, in which nanotechnology has shown very good prospects in delivering tumor antigens. In in vivo and ex vivo strategies, nanotechnology also could improve the immune effect through enhancing the uptake by targeting cells, reducing therapeutic drugs/agents, further encapsulating immuno-modulatory molecules or combining with other therapy treatments. Thus, therapeutic vaccines based on nanoparticles have the potential to enhance the immune response and reduce the side effects.

RNA-binding protein DDX3 mediates posttranscriptional regulation of androgen receptor: A mechanism of castration resistance

Prostate cancer (CaP) driven by androgen receptor (AR) is treated with androgen deprivation; however, therapy failure results in lethal castration-resistant prostate cancer (CRPC). AR-low/negative (ARL/-) CRPC subtypes have recently been characterized and cannot be targeted by hormonal therapies, resulting in poor prognosis. RNA-binding protein (RBP)/helicase DDX3 (DEAD-box helicase 3 X-linked) is a key component of stress granules (SG) and is postulated to affect protein translation. Here, we investigated DDX3-mediated posttranscriptional regulation of AR mRNA (messenger RNA) in CRPC. Using patient samples and preclinical models, we objectively quantified DDX3 and AR expression in ARL/- CRPC. We utilized CRPC models to identify DDX3:AR mRNA complexes by RNA immunoprecipitation, assess the effects of DDX3 gain/loss-of-function on AR expression and signaling, and address clinical implications of targeting DDX3 by assessing sensitivity to AR-signaling inhibitors (ARSI) in CRPC xenografts in vivo. ARL/- CRPC expressed abundant AR mRNA despite diminished levels of AR protein. DDX3 protein was highly expressed in ARL/- CRPC, where it bound to AR mRNA. Consistent with a repressive regulatory role, DDX3 localized to cytoplasmic puncta with SG marker PABP1 in CRPC. While induction of DDX3-nucleated SGs resulted in decreased AR protein expression, inhibiting DDX3 was sufficient to restore 1) AR protein expression, 2) AR signaling, and 3) sensitivity to ARSI in vitro and in vivo. Our findings implicate the RBP protein DDX3 as a mechanism of posttranscriptional regulation for AR in CRPC. Clinically, DDX3 may be targetable for sensitizing ARL/- CRPC to AR-directed therapies.

Gene Expression Signature of Acquired Chemoresistance in Neuroblastoma Cells

Drug resistance of childhood cancer neuroblastoma is a serious clinical problem. Patients with relapsed disease have a poor prognosis despite intense treatment. In the present study, we aimed to identify chemoresistance gene expression signatures in vincristine resistant neuroblastoma cells. We found that vincristine-resistant neuroblastoma cells formed larger clones and survived under reduced serum conditions as compared with non-resistant parental cells. To identify the possible mechanisms underlying vincristine resistance in neuroblastoma cells, we investigated the expression profiles of genes known to be involved in cancer drug resistance. This specific gene expression patterns could predict the behavior of a tumor in response to chemotherapy and for predicting the prognosis of high-risk neuroblastoma patients. Our signature could help chemoresistant neuroblastoma patients in avoiding useless and harmful chemotherapy cycles.

Synthetic lethality guiding selection of drug combinations in ovarian cancer

BACKGROUND

Synthetic lethality describes a relationship between two genes where single loss of either gene does not trigger significant impact on cell viability, but simultaneous loss of both gene functions results in lethality. Targeting synthetic lethal interactions with drug combinations promises increased efficacy in tumor therapy.

MATERIALS AND METHODS

We established a set of synthetic lethal interactions using publicly available data from yeast screens which were mapped to their respective human orthologs using information from orthology databases. This set of experimental synthetic lethal interactions was complemented by a set of predicted synthetic lethal interactions based on a set of protein meta-data like e.g. molecular pathway assignment. Based on the combined set, we evaluated drug combinations used in late stage clinical development (clinical phase III and IV trials) or already in clinical use for ovarian cancer with respect to their effect on synthetic lethal interactions. We furthermore identified a set of drug combinations currently not being tested in late stage ovarian cancer clinical trials that however have impact on synthetic lethal interactions thus being worth of further investigations regarding their therapeutic potential in ovarian cancer.

RESULTS

Twelve of the tested drug combinations addressed a synthetic lethal interaction with the anti-VEGF inhibitor bevacizumab in combination with paclitaxel being the most studied drug combination addressing the synthetic lethal pair between VEGFA and BCL2. The set of 84 predicted drug combinations for example holds the combination of the PARP inhibitor olaparib and paclitaxel, which showed efficacy in phase II clinical studies.

CONCLUSION

A set of drug combinations currently not tested in late stage ovarian cancer clinical trials was identified having impact on synthetic lethal interactions thus being worth of further investigations regarding their therapeutic potential in ovarian cancer.

Identification of synthetic lethality based on a functional network by using machine learning algorithms

Synthetic lethality is the synthesis of mutations leading to cell death. Tumor-specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in molecular biology, such as RNAi and CRISPR/Cas9 gene editing, efforts have been made to systematically identify synthetic lethal interactions, especially for frequently mutated genes in cancers. However, elucidating the mechanism of synthetic lethality remains a challenge because of the complexity of its influencing conditions. In this study, we proposed a new computational method to identify critical functional features that can accurately predict synthetic lethal interactions. This method incorporates several machine learning algorithms and encodes protein-coding genes by an enrichment system derived from gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to represent their functional features. We built a random forest-based prediction engine by using 2120 selected features and obtained a Matthews correlation coefficient of 0.532. We examined the top 15 features and found that most of them have potential roles in synthetic lethality according to previous studies. These results demonstrate the ability of our proposed method to predict synthetic lethal interactions and provide a basis for further characterization of these particular genetic combinations.

Vincristine alleviates adriamycin-induced nephropathy through stabilizing actin cytoskeleton

Antimicrotubule agent vincristine (VCR) has long been known as an alternative treatment for frequent relapse nephrotic syndrome and steroid-dependent nephrotic syndrome (SDNS). However, the mechanism is unknown. Here we found that VCR at a dosage much lower than that as an antimicrotubule agent can alleviate adriamycin (ADR)-induced proteinuria and podocyte foot process effacement. In cultured podocytes, VCR prevents ADR-induced actin fiber disorganization. In both in vitro and in vivo models, VCR suppresses ADR-induced overexpression of α3β1 integrin and focal adhesion kinase (FAK). These data suggest that VCR may relieve ADR-induced nephropathy through inhibiting injury-induced activation of integrin outside-in signaling to prevent actin cytoskeleton remodeling. Hence, our work reveals a novel role of VCR in regulating actin fiber assembly and provides first evidence on the therapeutic mechanism of VCR on nephrotic syndrome.

In-silico human genomics with GeneCards

Since 1998, the bioinformatics, systems biology, genomics and medical communities have enjoyed a synergistic relationship with the GeneCards database of human genes (http://www.genecards.org). This human gene compendium was created to help to introduce order into the increasing chaos of information flow. As a consequence of viewing details and deep links related to specific genes, users have often requested enhanced capabilities, such that, over time, GeneCards has blossomed into a suite of tools (including GeneDecks, GeneALaCart, GeneLoc, GeneNote and GeneAnnot) for a variety of analyses of both single human genes and sets thereof. In this paper, we focus on inhouse and external research activities which have been enabled, enhanced, complemented and, in some cases, motivated by GeneCards. In turn, such interactions have often inspired and propelled improvements in GeneCards. We describe here the evolution and architecture of this project, including examples of synergistic applications in diverse areas such as synthetic lethality in cancer, the annotation of genetic variations in disease, omics integration in a systems biology approach to kidney disease, and bioinformatics tools.