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Loss of function screens using shRNA (short hairpin RNA) and CRISPR (clustered regularly interspaced short palindromic repeats) are routinely used to identify genes that modulate responses of tumor cells to anti-cancer drugs. Here, by integrating GSEA (Gene Set Enrichment Analysis) and CMAP (Connectivity Map) analyses of multiple published shRNA screens, we identified a core set of pathways that affect responses to multiple drugs with diverse mechanisms of action. This suggests that these pathways represent "weak points" or "Achilles heels", whose mild disturbance should make cancer cells vulnerable to a variety of treatments. These "weak points" include proteasome, protein synthesis, RNA splicing, RNA synthesis, cell cycle, Akt-mTOR, and tight junction-related pathways. Therefore, inhibitors of these pathways are expected to sensitize cancer cells to a variety of drugs. This hypothesis was tested by analyzing the diversity of drugs that synergize with FDA-approved inhibitors of the proteasome, RNA synthesis, and Akt-mTOR pathways. Indeed, the quantitative evaluation indicates that inhibitors of any of these signaling pathways can synergize with a more diverse set of pharmaceuticals, compared to compounds inhibiting targets distinct from the "weak points" pathways. Our findings described here imply that inhibitors of the "weak points" pathways should be considered as primary candidates in a search for synergistic drug combinations. [ABSTRACT FROM AUTHOR]

Epigenetic alterations my play a role in the aggressive behavior of Non-Small Cell Lung Cancer (NSCLC). Treatment with the histone deacetylase inhibitor suberoylanilide hydroxamic acid (SAHA, vorinostat) has been reported to interfere with the proliferative and invasive potential of NSCLC cells. In addition, the DNA methyltransferase inhibitor azacytidine (AZA, vidaza) can modulate the levels of the metastasis suppressor KiSS-1. Thus, since cisplatin is still clinically available for NSCLC therapy, the aim of this study was to evaluate drug combinations between cisplatin and SAHA as well as AZA using cisplatin-sensitive H460 and -resistant H460/Pt NSCLC cells in relation to KiSS-1 modulation. An analysis of drug interaction according to the Combination-Index values indicated a more marked synergistic effect when the exposure to SAHA or AZA preceded cisplatin treatment with respect to a simultaneous schedule. A modulation of proteins involved in apoptosis (p53, Bax) was found in both sensitive and resistant cells, and compared to the treatment with epigenetic agents alone, the combination of cisplatin and SAHA or AZA increased apoptosis induction. The epigenetic treatments, both as single agents and in combination, increased the release of KiSS-1. Finally, the exposure of cisplatin-sensitive and -resistant cells to the kisspeptin KP10 enhanced cisplatin induced cell death. The efficacy of the combination of SAHA and cisplatin was tested in vivo after subcutaneous inoculum of parental and resistant cells in immunodeficient mice. A significant tumor volume inhibition was found when mice bearing advanced tumors were treated with the combination of SAHA and cisplatin according to the best schedule identified in cellular studies. These results, together with the available literature, support that epigenetic drugs are amenable for the combination treatment of NSCLC, including patients bearing cisplatin-resistant tumors. [ABSTRACT FROM AUTHOR]

The role of the epidermal growth factor receptor (EGFR) in tumor progression and survival is often underplayed. Its expression and/or dysregulation is associated with disease advancement and poor patient outcome as well as drug resistance in breast cancer. EGFR is often overexpressed in breast cancer and particularly triple-negative breast cancer (TNBC), which currently lacks molecular targets. We examined the synergistic potential of an EGFR inhibitor (EGFRi) in combination with doxorubicin (Dox) in estrogen-positive (ER+) MCF-7 and MDA-MB-231 TNBC cell lines. The exposure of MDA-MB-231 and MCF-7 to EGFRi produced an IC50s of 6.03 µM and 3.96 µM, respectively. Dox induced MDA-MB-231 (IC50 9.67 µM) and MCF-7 (IC50 1.4 µM) cytotoxicity. Combinations of EGFRi-Dox significantly reduced the IC50 in MCF-7 (0.46 µM) and MBA-MB 231 (0.01 µM). Synergistic drug interactions in both cell lines were confirmed using the Bliss independence model. Pro-apoptotic Caspase-3/7 activation occurred in MCF-7 at 0.1–10 µM of EGFRi and Dox single treatments, whilst 1 μM Dox yielded a more potent effect on MDA-MB-231. EGFRi and Dox individually and in combination downregulated the EGFR gene expression in MCF-7 and MDA-MB-231 (p < 0.001). This study demonstrates EGFRi's potential for eliciting synergistic interactions with Dox, causing enhanced growth inhibition, apoptosis induction, and downregulation of EGFR in both cell lines. [ABSTRACT FROM AUTHOR]

The in-silico strategy of identifying novel uses for already existing drugs, known as drug repositioning, has enhanced drug discovery. Previous studies have shown a positive correlation between expression changes induced by the anticancer agent trabectedin and those caused by irinotecan, a topoisomerase I inhibitor. Leveraging the availability of transcriptional datasets, we developed a general in-silico drug-repositioning approach that we applied to investigate novel trabectedin synergisms. We set a workflow allowing the identification of genes selectively modulated by a drug and possible novel drug interactions. To show its effectiveness, we selected trabectedin as a case-study drug. We retrieved eight transcriptional cancer datasets including controls and samples treated with trabectedin or its analog lurbinectedin. We compared gene signature associated with each dataset to the 476,251 signatures from the Connectivity Map database. The most significant connections referred to mitomycin-c, topoisomerase II inhibitors, a PKC inhibitor, a Chk1 inhibitor, an antifungal agent, and an antagonist of the glutamate receptor. Genes coherently modulated by the drugs were involved in cell cycle, PPARalpha, and Rho GTPases pathways. Our in-silico approach for drug synergism identification showed that trabectedin modulates specific pathways that are shared with other drugs, suggesting possible synergisms. [ABSTRACT FROM AUTHOR]

The development of in vitro/in vivo translational methods and a clinical trial framework for synergistically acting drug combinations are needed to identify optimal therapeutic conditions with the most effective therapeutic strategies. We performed physiologically based pharmacokinetic–pharmacodynamic (PBPK/PD) modelling and virtual clinical trial simulations for siremadlin, trametinib, and their combination in a virtual representation of melanoma patients. In this study, we built PBPK/PD models based on data from in vitro absorption, distribution, metabolism, and excretion (ADME), and in vivo animals' pharmacokinetic–pharmacodynamic (PK/PD) and clinical data determined from the literature or estimated by the Simcyp simulator (version V21). The developed PBPK/PD models account for interactions between siremadlin and trametinib at the PK and PD levels. Interaction at the PK level was predicted at the absorption level based on findings from animal studies, whereas PD interaction was based on the in vitro cytotoxicity results. This approach, combined with virtual clinical trials, allowed for the estimation of PK/PD profiles, as well as melanoma patient characteristics in which this therapy may be noninferior to the dabrafenib and trametinib drug combination. PBPK/PD modelling, combined with virtual clinical trial simulation, can be a powerful tool that allows for proper estimation of the clinical effect of the above-mentioned anticancer drug combination based on the results of in vitro studies. This approach based on in vitro/in vivo extrapolation may help in the design of potential clinical trials using siremadlin and trametinib and provide a rationale for their use in patients with melanoma. [ABSTRACT FROM AUTHOR]

Chemotherapy is the main treatment for most early-stage cancers; nevertheless, its efficacy is usually limited by drug resistance, toxicity, and tumor heterogeneity. Cell-penetrating peptides (CPPs) are small peptide sequences that can be used to increase the delivery rate of chemotherapeutic drugs to the tumor site, therefore contributing to overcoming these problems and enhancing the efficacy of chemotherapy. The drug combination is another promising strategy to overcome the aforementioned problems since the combined drugs can synergize through interconnected biological processes and target different pathways simultaneously. Here, we hypothesized that different peptides (P1–P4) could be used to enhance the delivery of chemotherapeutic agents into three different cancer cells (HT-29, MCF-7, and PC-3). In silico studies were performed to simulate the pharmacokinetic (PK) parameters of each peptide and antineoplastic agent to help predict synergistic interactions in vitro. These simulations predicted peptides P2–P4 to have higher bioavailability and lower Tmax, as well as the chemotherapeutic agent 5-fluorouracil (5-FU) to have enhanced permeability properties over other antineoplastic agents, with P3 having prominent accumulation in the colon. In vitro studies were then performed to evaluate the combination of each peptide with the chemotherapeutic agents as well as to assess the nature of drug interactions through the quantification of the Combination Index (CI). Our findings in MCF-7 and PC-3 cancer cells demonstrated that the combination of these peptides with paclitaxel (PTX) and doxorubicin (DOXO), respectively, is not advantageous over a single treatment with the chemotherapeutic agent. In the case of HT-29 colorectal cancer cells, the combination of P2–P4 with 5-FU resulted in synergistic cytotoxic effects, as predicted by the in silico simulations. Taken together, these findings demonstrate that these CPP6-conjugates can be used as adjuvant agents to increase the delivery of 5-FU into HT-29 colorectal cancer cells. Moreover, these results support the use of in silico approaches for the prediction of the interaction between drugs in combination therapy for cancer. [ABSTRACT FROM AUTHOR]

Cancer is a very challenging disease to treat, both in terms of therapeutic efficiency and harmful side effects, which continues to motivate the pursuit for novel molecules with potential anticancer activity. Herein, we have designed, synthesized, and evaluated the cytotoxicity of different brominated coelenteramines, which are metabolic products and synthesis precursors of the chemi-/bioluminescent system of marine coelenterazine. The evaluation of the anticancer potential of these molecules was carried out for both prostate and breast cancer, while also exploring their potential for use in combination therapy. Our results provided further insight into the structure–activity relationship of this type of molecule, such as their high structural specificity, as well highlighting the 4-bromophenyl moiety as essential for the anticancer activity. The obtained data also indicated that, despite their similarity, the anticancer activity displayed by both brominated coelenteramines and coelenterazines should arise from independent mechanisms of action. Finally, one of the studied coelenteramines was able to improve the profile of a known chemotherapeutic agent, even at concentrations in which its anticancer activity was not relevant. Thus, our work showed the potential of different components of marine chemi-/bioluminescent systems as novel anticancer molecules, while providing useful information for future optimizations. [ABSTRACT FROM AUTHOR]

Bladder cancer is the 10th most common cancer worldwide. Due to the lack of understanding of the oncogenic mechanisms between muscle-invasive bladder cancer (MIBC) and advanced bladder cancer (ABC) and the limitations of current treatments, novel therapeutic approaches are urgently needed. In this study, we utilized the systems biology method via genome-wide microarray data to explore the oncogenic mechanisms of MIBC and ABC to identify their respective drug targets for systems drug discovery. First, we constructed the candidate genome-wide genetic and epigenetic networks (GWGEN) through big data mining. Second, we applied the system identification and system order detection method to delete false positives in candidate GWGENs to obtain the real GWGENs of MIBC and ABC from their genome-wide microarray data. Third, we extracted the core GWGENs from the real GWGENs by selecting the significant proteins, genes and epigenetics via the principal network projection (PNP) method. Finally, we obtained the core signaling pathways from the corresponding core GWGEN through the annotations of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway to investigate the carcinogenic mechanisms of MIBC and ABC. Based on the carcinogenic mechanisms, we selected the significant drug targets NFKB1, LEF1 and MYC for MIBC, and LEF1, MYC, NOTCH1 and FOXO1 for ABC. To design molecular drug combinations for MIBC and ABC, we employed a deep neural network (DNN)-based drug-target interaction (DTI) model with drug specifications. The DNN-based DTI model was trained by drug-target interaction databases to predict the candidate drugs for MIBC and ABC, respectively. Subsequently, the drug design specifications based on regulation ability, sensitivity and toxicity were employed as filter criteria for screening the potential drug combinations of Embelin and Obatoclax for MIBC, and Obatoclax, Entinostat and Imiquimod for ABC from their candidate drugs. In conclusion, we not only investigated the oncogenic mechanisms of MIBC and ABC, but also provided promising therapeutic options for MIBC and ABC, respectively. [ABSTRACT FROM AUTHOR]

Translation of the synergy between the Siremadlin (MDM2 inhibitor) and Trametinib (MEK inhibitor) combination observed in vitro into in vivo synergistic efficacy in melanoma requires estimation of the interaction between these molecules at the pharmacokinetic (PK) and pharmacodynamic (PD) levels. The cytotoxicity of the Siremadlin and Trametinib combination was evaluated in vitro in melanoma A375 cells with MTS and RealTime-Glo assays. Analysis of the drug combination matrix was performed using Synergy and Synergyfinder packages. Calculated drug interaction metrics showed high synergy between Siremadlin and Trametinib: 23.12%, or a 7.48% increase of combined drug efficacy (concentration-independent parameter β from Synergy package analysis and concentration-dependent δ parameter from Synergyfinder analysis, respectively). In order to select the optimal PD interaction parameter which may translate observed in vitro synergy metrics into the in vivo setting, further PK/PD studies on cancer xenograft animal models coupled with PBPK/PD modelling are needed. [ABSTRACT FROM AUTHOR]

Prostate and lung cancers are among the most common cancer types, and they still need more therapeutics. For this purpose, saquinavir (SAQ) was tested alone and in combination with 5-fluorouracil (5-FU). PC-3 and A549 cells were exposed to increasing concentrations of both drugs alone or in combination, with simultaneous or sequential administration. Cell viability was obtained using the MTT assay and synergism values using CompuSyn software. Results showed that SAQ was the more cytotoxic of both drugs in PC-3 cells, while 5-FU was the most cytotoxic in A549 cells. When these drugs were used in combination, the more synergistic combination in PC-3 cells was the IC50 of SAQ with various concentrations of 5-FU, particularly when 5-FU was only applied 24 h later. Meanwhile for A549 the most promising combination was 5-FU with delayed SAQ, but with a weaker effect than all combinations demonstrated in PC-3 cells. These results demonstrate that SAQ could be used as a new repurposed drug for the treatment of prostate cancer and this treatment potential could be even greater if SAQ is combined with the anticancer drug 5-FU, while for lung cancer it is not as efficient and, therefore, not of as much interest. [ABSTRACT FROM AUTHOR]

Compared to single-drug therapy, drug combinations have shown great potential in cancer treatment. Most of the current methods employ genomic data and chemical information to construct drug–cancer cell line features, but there is still a need to explore methods to combine topological information in the protein interaction network (PPI). Therefore, we propose a network-embedding-based prediction model, NEXGB, which integrates the corresponding protein modules of drug–cancer cell lines with PPI network information. NEXGB extracts the topological features of each protein node in a PPI network by struc2vec. Then, we combine the topological features with the target protein information of drug–cancer cell lines, to generate drug features and cancer cell line features, and utilize extreme gradient boosting (XGBoost) to predict the synergistic relationship between drug combinations and cancer cell lines. We apply our model on two recently developed datasets, the Oncology-Screen dataset (Oncology-Screen) and the large drug combination dataset (DrugCombDB). The experimental results show that NEXGB outperforms five current methods, and it effectively improves the predictive power in discovering relationships between drug combinations and cancer cell lines. This further demonstrates that the network information is valid for detecting combination therapies for cancer and other complex diseases. [ABSTRACT FROM AUTHOR]

Diffuse large B cell lymphoma (DLBCL) is an aggressive heterogeneous disease. The most common subtypes of DLBCL include germinal center b-cell (GCB) type and activated b-cell (ABC) type. To learn more about the pathogenesis of two DLBCL subtypes (i.e., DLBCL ABC and DLBCL GCB), we firstly construct a candidate genome-wide genetic and epigenetic network (GWGEN) by big database mining. With the help of two DLBCL subtypes' genome-wide microarray data, we identify their real GWGENs via system identification and model order selection approaches. Afterword, the core GWGENs of two DLBCL subtypes could be extracted from real GWGENs by principal network projection (PNP) method. By comparing core signaling pathways and investigating pathogenic mechanisms, we are able to identify pathogenic biomarkers as drug targets for DLBCL ABC and DLBCL GCD, respectively. Furthermore, we do drug discovery considering drug-target interaction ability, drug regulation ability, and drug toxicity. Among them, a deep neural network (DNN)-based drug-target interaction (DTI) model is trained in advance to predict potential drug candidates holding higher probability to interact with identified biomarkers. Consequently, two drug combinations are proposed to alleviate DLBCL ABC and DLBCL GCB, respectively. [ABSTRACT FROM AUTHOR]

Mature T-cell lymphomas (MTCLs) represent a heterogeneous group of aggressive non-Hodgkin lymphomas comprising different entities. Anthracycline-based regimens are considered the standard of care in the front-line treatment. However, responses to these approaches have been neither adequate nor durable, and new treatment strategies are urgently needed to improve survival. Genomic instability is a common feature of cancer cells and can be caused by aberrations in the DNA damage response (DDR) and DNA repair mechanisms. Consistently, molecules involved in DDR are being targeted to successfully sensitize cancer cells to chemotherapy. Recent studies showed that some hematological malignancies display constitutive DNA damage and intrinsic DDR activation, but these features have not been investigated yet in MTCLs. In this study, we employed a panel of malignant T cell lines, and we report for the first time the characterization of intrinsic DNA damage and basal DDR activation in preclinical models in T-cell lymphoma. Moreover, we report the efficacy of targeting the apical kinase ATM using the inhibitor AZD0156, in combination with standard chemotherapy to promote apoptotic cell death. These findings suggest that DDR is an attractive pathway to be pharmacologically targeted when developing novel therapies and improving MTCL patients' outcomes. [ABSTRACT FROM AUTHOR]

Drug combinatorial therapy is a promising strategy for combating complex diseases due to its fewer side effects, lower toxicity and better efficacy. However, it is not feasible to determine all the effective drug combinations in the vast space of possible combinations given the increasing number of approved drugs in the market, since the experimental methods for identification of effective drug combinations are both labor- and time-consuming. In this study, we conducted systematic analysis of various types of features to characterize pairs of drugs. These features included information about the targets of the drugs, the pathway in which the target protein of a drug was involved in, side effects of drugs, metabolic enzymes of the drugs, and drug transporters. The latter two features (metabolic enzymes and drug transporters) were related to the metabolism and transportation properties of drugs, which were not analyzed or used in previous studies. Then, we devised a novel improved naïve Bayesian algorithm to construct classification models to predict effective drug combinations by using the individual types of features mentioned above. Our results indicated that the performance of our proposed method was indeed better than the naïve Bayesian algorithm and other conventional classification algorithms such as support vector machine and K-nearest neighbor. [ABSTRACT FROM AUTHOR]

Chemotherapy is the main treatment for most early-stage cancers; nevertheless, its efficacy is usually limited by drug resistance, toxicity, and tumor heterogeneity. Cell-penetrating peptides (CPPs) are small peptide sequences that can be used to increase the delivery rate of chemotherapeutic drugs to the tumor site, therefore contributing to overcoming these problems and enhancing the efficacy of chemotherapy. The drug combination is another promising strategy to overcome the aforementioned problems since the combined drugs can synergize through interconnected biological processes and target different pathways simultaneously. Here, we hypothesized that different peptides (P1-P4) could be used to enhance the delivery of chemotherapeutic agents into three different cancer cells (HT-29, MCF-7, and PC-3). In silico studies were performed to simulate the pharmacokinetic (PK) parameters of each peptide and antineoplastic agent to help predict synergistic interactions in vitro. These simulations predicted peptides P2-P4 to have higher bioavailability and lower T max , as well as the chemotherapeutic agent 5-fluorouracil (5-FU) to have enhanced permeability properties over other antineoplastic agents, with P3 having prominent accumulation in the colon. In vitro studies were then performed to evaluate the combination of each peptide with the chemotherapeutic agents as well as to assess the nature of drug interactions through the quantification of the Combination Index (CI). Our findings in MCF-7 and PC-3 cancer cells demonstrated that the combination of these peptides with paclitaxel (PTX) and doxorubicin (DOXO), respectively, is not advantageous over a single treatment with the chemotherapeutic agent. In the case of HT-29 colorectal cancer cells, the combination of P2-P4 with 5-FU resulted in synergistic cytotoxic effects, as predicted by the in silico simulations. Taken together, these findings demonstrate that these CPP6-conjugates can be used as adjuvant agents to increase the delivery of 5-FU into HT-29 colorectal cancer cells. Moreover, these results support the use of in silico approaches for the prediction of the interaction between drugs in combination therapy for cancer.

The rapid development in the field of transcriptomics provides remarkable biomedical insights for drug discovery. In this study, a transcriptome signature reversal approach was conducted to identify the agents against influenza A virus (IAV) infection through dissecting gene expression changes in response to disease or compounds' perturbations. Two compounds, nifurtimox and chrysin, were identified by a modified Kolmogorov–Smirnov test statistic based on the transcriptional signatures from 81 IAV-infected patients and the gene expression profiles of 1309 compounds. Their activities were verified in vitro with half maximal effective concentrations (EC50s) from 9.1 to 19.1 μM against H1N1 or H3N2. It also suggested that the two compounds interfered with multiple sessions in IAV infection by reversing the expression of 28 IAV informative genes. Through network-based analysis of the 28 reversed IAV informative genes, a strong synergistic effect of the two compounds was revealed, which was confirmed in vitro. By using the transcriptome signature reversion (TSR) on clinical datasets, this study provides an efficient scheme for the discovery of drugs targeting multiple host factors regarding clinical signs and symptoms, which may also confer an opportunity for decelerating drug-resistant variant emergence. [ABSTRACT FROM AUTHOR]

In a wide range of lymphoid neoplasms, the process of malignant transformation is associated with somatic mutations in B cells that affect the epigenetic machinery. Consequential alterations in histone modifications contribute to disease-specific changes in the transcriptional program. Affected genes commonly play important roles in cell cycle regulation, apoptosis-inducing signal transduction, and DNA damage response, thus facilitating the emergence of malignant traits that impair immune surveillance and favor the emergence of different B-cell lymphoma subtypes. In the last two decades, the field has made a major effort to develop therapies that target these epigenetic alterations. In this review, we discuss which epigenetic alterations occur in B-cell non-Hodgkin lymphoma. Furthermore, we aim to present in a close to comprehensive manner the current state-of-the-art in the preclinical and clinical development of epigenetic drugs. We focus on therapeutic strategies interfering with histone methylation and acetylation as these are most advanced in being deployed from the bench-to-bedside and have the greatest potential to improve the prognosis of lymphoma patients. [ABSTRACT FROM AUTHOR]

Preclinical, clinical, and epidemiological studies indicate that vitamin D3 (VD) deficiency is a risk factor for the development of breast cancer. Underlying mechanisms include the ability of calcitriol to induce cell differentiation, inhibit oncogenes expression, and modify different signaling pathways involved in the control of cell proliferation. In addition, calcitriol combined with different kinds of antineoplastic drugs has been demonstrated to enhance their beneficial effects in an additive or synergistic fashion. However, a recognized adjuvant regimen based on calcitriol for treating patients with breast cancer has not yet been fully established. Accordingly, in the present work, we review and discuss the preclinical and clinical studies about the combination of calcitriol with different oncological drugs, aiming to emphasize its main therapeutic benefits and opportunities for the treatment of this pathology. [ABSTRACT FROM AUTHOR]

Cell-penetrating peptides (CPPs) are small peptide sequences used mainly as cellular delivery agents that are able to efficiently deliver cargo into cells. Some CPPs also demonstrate intrinsic anticancer properties. Previously, our group developed a new family of CPP2-thiazole conjugates that have been shown to effectively reduce the proliferation of different cancer cells. This work aimed to combine these CPP2-thiazole conjugates with paclitaxel (PTX) and 5-fluorouracil (5-FU) in PC-3 prostate and HT-29 colon cancer cells, respectively, to evaluate the cytotoxic effects of these combinations. We also combined these CPP2-thiazole conjugates with clotrimazole (CLZ), an antifungal agent that has been shown to decrease cancer cell proliferation. Cell viability was evaluated using MTT and SRB assays. Drug interaction was quantified using the Chou–Talalay method. We determined that CPP2 did not have significant activity in these cells and demonstrate that N-terminal modification of this peptide enhanced its anticancer activity in both cell lines. Our results also showed an uneven response between cell lines to the proposed combinations. PC-3 cells were more responsive to the combination of CPP2-thiazole conjugates with CLZ than PTX and were more sensitive to these combinations than HT-29 cells. In addition, the interaction of drugs resulted in more synergism in PC-3 cells. These results suggest that N-terminal modification of CPP2 results in the enhanced anticancer activity of the peptide and demonstrates the potential of CPPs as adjuvants in cancer therapy. These results also validate that CLZ has significant anticancer activity both alone and in combination and support the strategy of drug repurposing coupled to drug combination for prostate cancer therapy. [ABSTRACT FROM AUTHOR]

Compelling evidence suggests that pyroglutamate-modified Aβ (pGlu3-Aβ; AβN3pG) peptides play a pivotal role in the development and progression of Alzheimer's disease (AD). Approaches targeting pGlu3-Aβ by glutaminyl cyclase (QC) inhibition (Varoglutamstat) or monoclonal antibodies (Donanemab) are currently in clinical development. Here, we aimed at an assessment of combination therapy of Varoglutamstat (PQ912) and a pGlu3-Aβ-specific antibody (m6) in transgenic mice. Whereas the single treatments at subtherapeutic doses show moderate (16–41%) but statistically insignificant reduction of Aβ42 and pGlu-Aβ42 in mice brain, the combination of both treatments resulted in significant reductions of Aβ by 45–65%. Evaluation of these data using the Bliss independence model revealed a combination index of ≈1, which is indicative for an additive effect of the compounds. The data are interpreted in terms of different pathways, in which the two drugs act. While PQ912 prevents the formation of pGlu3-Aβ in different compartments, the antibody is able to clear existing pGlu3-Aβ deposits. The results suggest that combination of the small molecule Varoglutamstat and a pE3Aβ-directed monoclonal antibody may allow a reduction of the individual compound doses while maintaining the therapeutic effect. [ABSTRACT FROM AUTHOR]

The paucity of currently available therapies for glioblastoma multiforme requires novel approaches to the treatment of this brain tumour. Disrupting cyclic nucleotide-signalling through phosphodiesterase (PDE) inhibition may be a promising way of suppressing glioblastoma growth. Here, we examined the effects of 28 PDE inhibitors, covering all the major PDE classes, on the proliferation of the human U87MG, A172 and T98G glioblastoma cells. The PDE10A inhibitors PF-2545920, PQ10 and papaverine, the PDE3/4 inhibitor trequinsin and the putative PDE5 inhibitor MY-5445 potently decreased glioblastoma cell proliferation. The synergistic suppression of glioblastoma cell proliferation was achieved by combining PF-2545920 and MY-5445. Furthermore, a co-incubation with drugs that block the activity of the multidrug resistance-associated protein 1 (MRP1) augmented these effects. In particular, a combination comprising the MRP1 inhibitor reversan, PF-2545920 and MY-5445, all at low micromolar concentrations, afforded nearly complete inhibition of glioblastoma cell growth. Thus, the potent suppression of glioblastoma cell viability may be achieved by combining MRP1 inhibitors with PDE inhibitors at a lower toxicity than that of the standard chemotherapeutic agents, thereby providing a new combination therapy for this challenging malignancy. [ABSTRACT FROM AUTHOR]

In a wide range of lymphoid neoplasms, the process of malignant transformation is associated with somatic mutations in B cells that affect the epigenetic machinery. Consequential alterations in histone modifications contribute to disease-specific changes in the transcriptional program. Affected genes commonly play important roles in cell cycle regulation, apoptosis-inducing signal transduction, and DNA damage response, thus facilitating the emergence of malignant traits that impair immune surveillance and favor the emergence of different B-cell lymphoma subtypes. In the last two decades, the field has made a major effort to develop therapies that target these epigenetic alterations. In this review, we discuss which epigenetic alterations occur in B-cell non-Hodgkin lymphoma. Furthermore, we aim to present in a close to comprehensive manner the current state-of-the-art in the preclinical and clinical development of epigenetic drugs. We focus on therapeutic strategies interfering with histone methylation and acetylation as these are most advanced in being deployed from the bench-to-bedside and have the greatest potential to improve the prognosis of lymphoma patients.

Resistance in clear cell renal cell carcinoma (ccRCC) against sunitinib is a multifaceted process encompassing numerous molecular aberrations. This induces clinical complications, reducing the treatment success. Understanding these aberrations helps us to select an adapted treatment strategy that surpasses resistance mechanisms, reverting the treatment insensitivity. In this regard, we investigated the dominant mechanisms of resistance to sunitinib and validated an optimized multidrug combination to overcome this resistance. Human ccRCC cells were exposed to single or chronic treatment with sunitinib to obtain three resistant clones. Upon manifestation of sunitinib resistance, morphometric changes in the cells were observed. At the molecular level, the production of cell membrane and extracellular matrix components, chemotaxis, and cell cycle progression were dysregulated. Molecules enforcing the cell cycle progression, i.e., cyclin A, B1, and E, were upregulated. Mass spectrometry analysis revealed the intra- and extracellular presence of N-desethyl sunitinib, the active metabolite. Lysosomal sequestration of sunitinib was confirmed. After treatment with a synergistic optimized drug combination, the cell metabolic activity in Caki-1-sunitinib-resistant cells and 3D heterotypic co-cultures was reduced by >80%, remaining inactive in non-cancerous cells. These results demonstrate geno- and phenotypic changes in response to sunitinib treatment upon resistance induction. Mimicking resistance in the laboratory served as a platform to study drug responses. [ABSTRACT FROM AUTHOR]

Hedgehog (Hh) pathway controls complex developmental processes in vertebrates. Abnormal activation of Hh pathway is responsible for tumorigenesis and maintenance of multiple cancers, and thus addressing this represents promising therapeutic opportunities. In recent years, two Hh inhibitors have been approved for basal cell carcinoma (BCC) treatment and show extraordinary clinical outcomes. Meanwhile, a series of novel agents are being developed for the treatment of several cancers, including lung cancer, leukemia, and pancreatic cancer. Unfortunately, Hh inhibition fails to show satisfactory benefits in these cancer types compared with the success stories in BCC, highlighting the need for better understanding of Hh signaling in cancer. Autophagy, a conserved biological process for cellular component elimination, plays critical roles in the initiation, progression, and drug resistance of cancer, and therefore, implied potential to be targeted. Recent evidence demonstrated that Hh signaling interplays with autophagy in multiple cancers. Importantly, modulating this crosstalk exhibited noteworthy capability to sensitize primary and drug-resistant cancer cells to Hh inhibitors, representing an emerging opportunity to reboot the efficacy of Hh inhibition in those insensitive tumors, and to tackle drug resistance challenges. This review will highlight recent advances of Hh pathway and autophagy in cancers, and focus on their crosstalk and the implied therapeutic opportunities. [ABSTRACT FROM AUTHOR]