A comprehensive look of poly(ADP-ribose) polymerase inhibition strategies and future directions for cancer therapy

A review of poly(ADP-ribose)polymerase-1 (PARP1) role and its inhibitors bearing pyrazole or indazole core for cancer therapy

Cancer is a disease with a high mortality rate characterized by uncontrolled proliferation of abnormal cells. The hallmarks of cancer evidence the acquired cells characteristics that promote the growth of malignant tumours, including genomic instability and mutations, the ability to evade cellular death and the capacity of sustaining proliferative signalization. Poly(ADP-ribose) polymerase-1 (PARP1) is a protein that plays key roles in cellular regulation, namely in DNA damage repair and cell survival. The inhibition of PARP1 promotes cellular death in cells with homologous recombination deficiency, and therefore, the interest in PARP protein has been rising as a target for anticancer therapies. There are already some PARP1 inhibitors approved by Food and Drug Administration (FDA), such as Olaparib and Niraparib. The last compound presents in its structure an indazole core. In fact, pyrazoles and indazoles have been raising interest due to their various medicinal properties, namely, anticancer activity. Derivatives of these compounds have been studied as inhibitors of PARP1 and presented promising results. Therefore, this review aims to address the importance of PARP1 in cell regulation and its role in cancer. Moreover, it intends to report a comprehensive literature review of PARP1 inhibitors, containing the pyrazole and indazole scaffolds, published in the last fifteen years, focusing on structure-activity relationship aspects, thus providing important insights for the design of novel and more effective PARP1 inhibitors.

Computational investigation of FDA approved drugs as selective PARP-1 inhibitors by targeting BRCT domain for cancer therapy

Poly(ADP-ribose) polymerase-1 is a promising target for the treatment of cancer due to its involvement in base excision repair pathways for repairing DNA single-strand breaks. However, available PARP-1 inhibitors target a highly conserved PARPs catalytic domain, which causes toxicity due to the off-target activity. Therefore, the present study was hypothesized to identify selective inhibitors by targeting specific protein-protein interacting (PPI) PARP-1 BRCT domain. Moreover, PPI hotspot residues (Gly399, Lys400, Leu401, Lys441 & Lys442) and a druggable pocket was detected to screen small molecule inhibitors. Hence, two FDA approved drug molecules (levoleucovorin and balsalazide) were recognized to fit in the druggable pocket. Since they are already under investigation for anti-cancer activity, thus could be further explored in PARP-1 sensitive cancer cells to expand their selectivity and develop as effective anti-cancer agents. Besides, the study also provides detailed structural insight of PARP-1 and XRCC1 complex through their BRCT domains.

Triazol: a privileged scaffold for proteolysis targeting chimeras

Current traditional drugs such as enzyme inhibitors and receptor agonists/antagonists present inherent limitations due to occupancy-driven pharmacology as the mode of action. Proteolysis targeting chimeras (PROTACs) are composed of an E3 ligand, a connecting linker and a target protein ligand, and are an attractive approach to specifically knockdown-targeted proteins utilizing an event-driven mode of action. The length, hydrophilicity and rigidity of connecting linkers play important role in creating a successful PROTAC. Some PROTACs with a triazole linker have displayed promising anticancer activity. This review provides an overview of PROTACs with a triazole scaffold and discusses its structure-activity relationship. Important milestones in the development of PROTACs are addressed and a critical analysis of this drug discovery strategy is also presented.

Integration of Bioinformatics Resources Reveals the Therapeutic Benefits of Gemcitabine and Cell Cycle Intervention in SMAD4-Deleted Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most common and aggressive type of pancreatic cancer. The five-year survival rate of PDAC is very low (less than 8%), which is associated with the late diagnosis, high metastatic potential, and resistance to therapeutic agents. The identification of better prognostic or therapeutic biomarker may have clinical benefits for PDAC treatment. SMAD4, a central mediator of transforming growth factor beta (TGFβ) signaling pathway, is considered a tumor suppressor gene. SMAD4 inactivation is frequently found in PDAC. However, its role in prognosis and therapeutics of PDAC is still unclear. In this study, we applied bioinformatics approaches, and integrated publicly available resources, to investigate the role of SMAD4 gene deletion in PDAC. We found that SMAD4 deletion was associated with poorer disease-free, but not overall, survival in PDAC patients. Cancer hallmark enrichment and pathway analysis suggested that the upregulation of cell cycle-related genes in SMAD4-deleted PDAC. Chemotherapy response profiling of PDAC cell lines and patient-derived organoids revealed that SMAD4-deleted PDAC was sensitive to gemcitabine, the first-line treatment for PDAC, and specific cell cycle-targeting drugs. Taken together, our study provides an insight into the prognostic and therapeutic roles of SMAD4 gene deletion in PDAC, and SMAD4 gene copy numbers may be used as a therapeutic biomarker for PDAC treatment.

Integrated network analysis and machine learning approach for the identification of key genes of triple-negative breast cancer

Triple-negative breast cancer (TNBC) has attracted more attention compared with other breast cancer subtypes due to its aggressive nature, poor prognosis, and chemotherapy remains the mainstay of treatment with no other approved targeted therapy. Therefore, the study aimed to discover more promising therapeutic targets and investigating new insights of biological mechanism of TNBC. Six microarray data sets consisting of 463 non-TNBC and 405 TNBC samples were mined from Gene Expression Omnibus. The data sets were integrated by meta-analysis and identified 1075 differentially expressed genes. Protein-protein interaction network was constructed which consists of 486 nodes and 1932 edges, where 29 hub genes were obtained with high topological measures. Further, 16 features (hub genes), 12 upregulated (AURKB, CCNB2, CDC20, DDX18, EGFR, ENO1, MYC, NUP88, PLK1, PML, POLR2F, and SKP2) and four downregulated ( CCND1, GLI3, SKP1, and TGFB3) were selected through machine learning correlation based feature selection method on training data set. A naïve Bayes based classifier built using the expression profiles of 16 features (hub genes) accurately and reliably classify TNBC from non-TNBC samples in the validation test data set with a receiver operating curve of 0.93 to 0.98. Subsequently, Gene Ontology analysis revealed that the hub genes were enriched in mitotic cell cycle processes and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that they were enriched in cell cycle pathways. Thus, the identified key hub genes and pathways highlighted in the study would enhance the understanding of molecular mechanism of TNBC which may serve as potential therapeutic target.

Adaptive phenotype drives resistance to androgen deprivation therapy in prostate cancer

Background

Prostate cancer (PCa), the second most common cancer affecting men worldwide, shows a broad spectrum of biological and clinical behaviour representing the epiphenomenon of an extreme heterogeneity. Androgen deprivation therapy is the mainstay of treatment for advanced forms but after few years the majority of patients progress to castration-resistant prostate cancer (CRPC), a lethal form that poses considerable therapeutic challenges.

Methods

Western blotting, immunocytochemistry, invasion and reporter assays, and in vivo studies were performed to characterize androgen resistant sublines phenotype in comparison to the parental cell line LNCaP. RNA microarray, mass spectrometry, integrative transcriptomic and proteomic differential analysis coupled with GeneOntology and multivariate analyses were applied to identify deregulated genes and proteins involved in CRPC evolution.

Results

Treating the androgen-responsive LNCaP cell line for over a year with 10 μM bicalutamide both in the presence and absence of 0.1 nM 5-α-dihydrotestosterone (DHT) we obtained two cell sublines, designated PDB and MDB respectively, presenting several analogies with CRPC. Molecular and functional analyses of PDB and MDB, compared to the parental cell line, showed that both resistant cell lines were PSA low/negative with comparable levels of nuclear androgen receptor devoid of activity due to altered phosphorylation; cell growth and survival were dependent on AKT and p38MAPK activation and PARP-1 overexpression; their malignant phenotype increased both in vitro and in vivo. Performing bioinformatic analyses we highlighted biological processes related to environmental and stress adaptation supporting cell survival and growth. We identified 15 proteins that could direct androgen-resistance acquisition. Eleven out of these 15 proteins were closely related to biological processes involved in PCa progression.

Conclusions

Our models suggest that environmental factors and epigenetic modulation can activate processes of phenotypic adaptation driving drug-resistance. The identified key proteins of these adaptive phenotypes could be eligible targets for innovative therapies as well as molecules of prognostic and predictive value.

Electronic supplementary material

The online version of this article (10.1186/s12964-017-0206-x) contains supplementary material, which is available to authorized users.