Search

The Bromodomain and Extra-terminal domain (BET) proteins are promising targets in treating cancers. Although BET inhibitors have been in clinical trials, they are limited by lacking of suitable biomarkers to indicate drug responses in different cancers. Here we identify DHRS2, ETV4 and NOTUM as potential biomarkers to indicate drug resistance in liver cancer cells of a recently discovered BET inhibitor, Hjp-6-171. Furthermore, we confirm that reactivation of WNT pathway, the target of NOTUM, contributes to the drug sensitivity restoration in Hjp-6-171 resistant cells. Specially, combinations of Hjp-6-171 and a GSK3β inhibitor CHIR-98014 show remarkable therapeutic effects in vitro and in vivo. Integrating RNA-seq and ChIP-seq data, we reveal the expression signature of β-catenin regulated genes is contrary in sensitive cells to that in resistant cells. We propose WNT signaling molecules such as β-catenin and ETV4 to be candidate biomarkers to indicate BET inhibitor responses in liver cancer patients.

The remarkable advances in next-generation sequencing technology have enabled the wide usage of sequencing as a clinical tool. To promote the advance of precision oncology for breast cancer in China, here we report a large-scale prospective clinical sequencing program using the Fudan-BC panel, and comprehensively analyze the clinical and genomic characteristics of Chinese breast cancer. The mutational landscape of 1,134 breast cancers reveals that the most significant differences between Chinese and Western patients occurred in the hormone receptor positive, human epidermal growth factor receptor 2 negative breast cancer subtype. Mutations in p53 and Hippo signaling pathways are more prevalent, and 2 mutually exclusive and 9 co-occurring patterns exist among 9 oncogenic pathways in our cohort. Further preclinical investigation partially suggests that NF2 loss-of-function mutations can be sensitive to a Hippo-targeted strategy. We establish a public database (Fudan Portal) and a precision medicine knowledge base for data exchange and interpretation. Collectively, our study presents a leading approach to Chinese precision oncology treatment and reveals potentially actionable mutations in breast cancer., Chinese breast cancer patients have not been well represented in clinical sequencing studies. Here the authors analyse the mutational landscape of 1,134 Chinese breast cancer patients, finding actionable targets and a higher prevalence of p53 and Hippo pathway mutations compared to Western cohorts.

Background: Triple-negative breast cancer (TNBC) is an aggressive malignancy with high heterogeneity. However, the alternative polyadenylation (APA) profiles of TNBC remain unknown. Here, we aimed to define the characteristics of the APA events at post-transcription level among TNBCs. Methods: Using transcriptome microarray data, we analyzed APA profiles of 165 TNBC samples and 33 paired normal tissues. A pooled short hairpin RNA screen targeting 23 core cleavage and polyadenylation (C/P) genes was used to identify key C/P factors. Results: We established an unconventional APA subtyping system composed of four stable subtypes: 1) luminal androgen receptor (LAR), 2) mesenchymal-like immune-activated (MLIA), 3) basal-like (BL), 4) suppressed (S) subtypes. Patients in the S subtype had the worst disease-free survival comparing to other patients (log-rank p = 0.021). Enriched clinically actionable pathways and putative therapeutic APA events were analyzed among each APA subtype. Furthermore, CPSF1 and PABPN1 were identified as the master C/P factors in regulating APA events and TNBC proliferation. The depletion of CPSF1 or PABPN1 weakened cell proliferation, enhanced apoptosis, resulted in cell cycle redistribution and a reversion of APA events of genes associated with tumorigenesis, proliferation, metastasis and chemosensitivity in breast cancer. Conclusions: Our findings advance the understanding of tumor heterogeneity regulation in APA and yield new insights into therapeutic target identification in TNBC.

Circular RNAs (circRNAs) are emerging species of mRNA splicing products with largely unknown functions. Although several computational pipelines for circRNA identification have been developed, these methods strictly rely on uniquely mapped reads overlapping back-splice junctions (BSJs) and lack approaches to model the statistical significance of the identified circRNAs. Here, we reported a systematic computational approach to identify circRNAs by simultaneously utilizing BSJ overlapping reads and discordant BSJ spanning reads to identify circRNAs. Moreover, we developed a novel procedure to estimate the P-values of the identified circRNAs. A computational cross-validation and experimental validations demonstrated that our method performed favorably compared to existing circRNA detection tools. We created a standalone tool, CircRNAFisher, to implement the method, which might be valuable to computational and experimental scientists studying circRNAs.

Androgen-ablation therapies, which are the standard treatment for metastatic prostate cancer, invariably lead to acquired resistance. Hence, a systematic identification of additional drivers may provide useful insights into the development of effective therapies. Numerous microRNAs that are critical for metastasis are dysregulated in metastatic prostate cancer, but the underlying molecular mechanism is poorly understood. We perform an integrative analysis of transcription factor (TF) and microRNA expression profiles and computationally identify three master TFs, AR, HOXC6 and NKX2-2, which induce the aberrant metastatic microRNA expression in a mutually exclusive fashion. Experimental validations confirm that the three TFs co-dysregulate a large number of metastasis-associated microRNAs. Moreover, their overexpression substantially enhances cell motility and is consistently associated with a poor clinical outcome. Finally, the mutually exclusive overexpression between AR, HOXC6 and NKX2-2 is preserved across various tissues and cancers, suggesting that mutual exclusivity may represent an intrinsic characteristic of driver TFs during tumorigenesis., Dysregulation of microRNAs is thought to be important for metastasis in castration-resistant prostate cancer (CRPC), but its drivers are unknown. Here, the authors use computational analysis to identify HOXC6 and NKX2-2 in addition to AR as alternative drivers of dysregulated miRNA expression in CRPC.

Rationale: Paclitaxel resistance is a major concern when treating triple-negative breast cancer (TNBC) patients. We aimed to identify candidates causing paclitaxel resistance and explore their significance in TNBC therapeutics. Methods: A genome-wide CRISPR screening, integrated with transcriptome analyses, was performed to identify candidates involved in paclitaxel-resistant TNBCs. Cell proliferation, cytotoxicity, immunofluorescent staining, and xenograft assays were conducted to verify the phenotypes of paclitaxel resistance induced by candidate genes, both in vitro and in vivo. RNA sequencing, Western blotting, and chromatin immunoprecipitation assays were used to explore the underlying mechanisms. Results: MEF2-interacting transcriptional repressor (MITR), the truncated isoform of histone deacetylase 9 (HDAC9) lacking the deacetylation domain, was enriched in paclitaxel-resistant cells. Elevated MITR expression resulted in increased interleukin-11 (IL11) expression and activation of downstream JAK/STAT3 signaling. Mechanistically, MITR counteracted MEF2A-induced transcriptional suppression of IL11, ultimately causing paclitaxel resistance. By contrast, pharmacological inhibition of JAK1/2 by ruxolitinib reversed paclitaxel resistance both in vitro and in vivo. Conclusion: Our in vitro and in vivo genetic and cellular analyses elucidated the pivotal role of MITR/MEF2A/IL11 axis in paclitaxel resistance and provided a novel therapeutic strategy for TNBC patients to overcome poor chemotherapy responses.

Purpose: The tumor microenvironment has a profound impact on prognosis and immunotherapy. However, the landscape of the triple-negative breast cancer (TNBC) microenvironment has not been fully understood. Experimental Design: Using the largest original multi-omics dataset of TNBC (n = 386), we conducted an extensive immunogenomic analysis to explore the heterogeneity and prognostic significance of the TNBC microenvironment. We further analyzed the potential immune escape mechanisms of TNBC. Results: The TNBC microenvironment phenotypes were classified into three heterogeneous clusters: cluster 1, the “immune-desert” cluster, with low microenvironment cell infiltration; cluster 2, the “innate immune-inactivated” cluster, with resting innate immune cells and nonimmune stromal cells infiltration; and cluster 3, the “immune-inflamed” cluster, with abundant adaptive and innate immune cells infiltration. The clustering result was validated internally with pathologic sections and externally with The Cancer Genome Atlas and METABRIC cohorts. The microenvironment clusters had significant prognostic efficacy. In terms of potential immune escape mechanisms, cluster 1 was characterized by an incapability to attract immune cells, and MYC amplification was correlated with low immune infiltration. In cluster 2, chemotaxis but inactivation of innate immunity and low tumor antigen burden might contribute to immune escape, and mutations in the PI3K-AKT pathway might be correlated with this effect. Cluster 3 featured high expression of immune checkpoint molecules. Conclusions: Our study represents a step toward personalized immunotherapy for patients with TNBC. Immune checkpoint inhibitors might be effective for “immune-inflamed” cluster, and the transformation of “cold tumors” into “hot tumors” should be considered for “immune-desert” and “innate immune-inactivated” clusters.

We comprehensively analyzed clinical, genomic, and transcriptomic data of a cohort of 465 primary triple-negative breast cancer (TNBC). PIK3CA mutations and copy-number gains of chromosome 22q11 were more frequent in our Chinese cohort than in The Cancer Genome Atlas. We classified TNBCs into four transcriptome-based subtypes: (1) luminal androgen receptor (LAR), (2) immunomodulatory, (3) basal-like immune-suppressed, and (4) mesenchymal-like. Putative therapeutic targets or biomarkers were identified among each subtype. Importantly, the LAR subtype showed more ERBB2 somatic mutations, infrequent mutational signature 3 and frequent CDKN2A loss. The comprehensive profile of TNBCs provided here will serve as a reference to further advance the understanding and precision treatment of TNBC.

We designed and synthesized a series of 2-thioxo-4-thiazolidinone derivatives and evaluated them on peroxisome proliferator activated receptor γ (PPARγ) binding activities. Through the biological assays, compounds 18 and 38 were highlighted with Ki values of 12.15 nmol/L and 14.46 nmol/L, respectively. Then structure–activity relationship (SAR) was analyzed to screen privileged structural modifications. Moreover, molecular fitting of these compounds onto the approved drug Rosiglitazone in the PPARγ ligand binding domain was performed to elucidate the SAR and explore potential receptor–ligand interactions. These results demonstrate that the 2-thioxo-4-thiazolidinones can be considered as new promising molecular probes with excellent binding activities to PPARγ.

The competitive endogenous RNA (ceRNA) hypothesis suggests an intrinsic mechanism to regulate biological processes. However, whether the dynamic changes of ceRNAs can modulate miRNA activities remains controversial. Here, we examine the dynamics of ceRNAs during TGF-β-induced epithelial-to-mesenchymal transition (EMT). We observe that TGFBI, a transcript highly induced during EMT in A549 cells, acts as the ceRNA for miR-21 to modulate EMT. We further identify FN1 as the ceRNA for miR-200c in the canonical SNAIL-ZEB-miR200 circuit in MCF10A cells. Experimental assays and computational simulations demonstrate that the dynamically induced ceRNAs are directly coupled with the canonical double negative feedback loops and are critical to the induction of EMT. These results help to establish the relevance of ceRNA in cancer EMT and suggest that ceRNA is an intrinsic component of the EMT regulatory circuit and may represent a potential target to disrupt EMT during tumorigenesis.

A series of novel indolin-2-ones inhibitors against p90 ribosomal S6 protein kinase 2 (RSK2) were designed and synthesized and their structure-activity relationship (SAR) was studied. The most potent inhibitor, compound 3s, exhibited potent inhibition against RSK2 with an IC50 value of 0.5 μM and presented a satisfactory selectivity against 23 kinases. The interactions of these inhibitors with RSK2 were investigated based on the proposed binding poses with molecular docking simulation. Four compounds and six compounds exhibited moderate anti-proliferation activities against PC 3 cells and MCF-7 cells, respectively.

Several classes of non-steroid 11β-HSD1 inhibitors have been developed as promising treatments for Type 2 Diabetes (T2D). Using a human 11β-HSD1 selective inhibitor as a starting point, we designed and synthesized a new class of derivatives of 1-arylsulfonyl piperidine-3-carboxamides. It was found that the large lipophilic group on the amino moiety may lead to cross-species potency towards human and mouse, allowing drug development by evaluating compounds in rodent model. By exploring structure–activity-relationship, the (R)-(+)-bornylamine derivative is identified as the most potent inhibitor of mouse enzyme 11β-HSD1 with an IC50 of 18 nM. Docking studies revealed the different possible interaction modes of the S-enantiomer and R-enantiomer bound to h11β-HSD1, and explained why the S-enantiomer is more active than the R-enantiomer. Finally, two potent and isoform-selective compounds, (+)-isopinocampheylamine derivative 8m and (R)-(+)-bornylamine derivative 8l, with suitable in vitro properties, could be selected for future PK/PD evaluation in rodent models. Then, 8l was subjected a pharmacodynamics study in vivo with rodent model. It was shown that 8l have 71% and 63% inhibition in adipose and liver tissue at 1 h after administration, but it was a short-acting compound displaying a significant drop in potency in the subsequent 3 h. This study not only provides compounds as novel h11β-HSD1 inhibitors, but also presents structure–activity relationships for designing potent human/mouse 11β-HSD1 inhibitors suitable for in vivo evaluation in rodent models.

We described a prospective application of ligand-based virtual screening program SHAFTS to discover novel inhibitors for p90 ribosomal S6 protein kinase 2 (RSK2). Taking the putative 3D conformations of two weakly binding RSK2 NTKD inhibitors as query templates, SHAFTS was used to perform 3D similarity based virtual screening because of a lack of crystal structure of RSK2 protein, thus leading to the identification of several novel scaffolds that would have been missed by conventional 2D fingerprint methods. The most potent hit compounds show low micromolar inhibitory activities against RSK2. In particular, one of the hit compounds exhibits potent antimigration activity against the MDA-MB-231 tumor cell. The results exemplified SHAFTS' application in active enrichment and scaffold hopping, which is of general interest for lead identification in drug discovery endeavors and also provides novel scaffolds that lay the foundation for uncovering new RSK2 regulatory mechanisms.

Epithelial-to-mesenchymal transition (EMT) is a complex multistep process in which phenotype switches are mediated by a network of transcription factors (TFs). Systematic characterization of all dynamic TFs controlling EMT state transitions, especially for the intermediate partial-EMT state, represents a highly relevant yet largely unexplored task. Here, we performed a computational analysis that integrated time-course EMT transcriptomic data with public cistromic data and identified three synergistic master TFs (ETS2, HNF4A and JUNB) that regulate the transition through the partial-EMT state. Overexpression of these regulators predicted a poor clinical outcome, and their elimination readily abolished TGF-β-induced EMT. Importantly, these factors utilized a clique motif, physically interact and their cumulative binding generally characterized EMT-associated genes. Furthermore, analyses of H3K27ac ChIP-seq data revealed that ETS2, HNF4A and JUNB are associated with super-enhancers and the administration of BRD4 inhibitor readily abolished TGF-β-induced EMT. These findings have implications for systematic discovery of master EMT regulators and super-enhancers as novel targets for controlling metastasis.

Competing endogenous RNA (ceRNA) interactions form a multilayered network that regulates gene expression in various biological pathways. Recent studies have demonstrated novel roles of ceRNA interactions in tumorigenesis, but the dynamics of the ceRNA network in cancer remain unexplored. Here, we examine ceRNA network dynamics in prostate cancer from the perspective of alternative cleavage and polyadenylation (APA) and reveal the principles of such changes. Analysis of exon array data revealed that both shortened and lengthened 3'UTRs are abundant. Consensus clustering with APA data stratified cancers into groups with differing risks of biochemical relapse and revealed that a ceRNA subnetwork enriched with cancer genes was specifically dysregulated in high-risk cancers. The novel connection between 3'UTR shortening and ceRNA network dysregulation was supported by the unusually high number of microRNA response elements (MREs) shared by the dysregulated ceRNA interactions and the significantly altered 3'UTRs. The dysregulation followed a fundamental principle in that ceRNA interactions connecting genes that show opposite trends in expression change are preferentially dysregulated. This targeted dysregulation is responsible for the majority of the observed expression changes in genes with significant ceRNA dysregulation and represents a novel mechanism underlying aberrant oncogenic expression.

As the major issue to limit the use of drugs, drug safety leads to the attrition or failure in clinical trials of drugs. Therefore, it would be more efficient to minimize therapeutic risks if it could be predicted before large-scale clinical trials. Here, we integrated a network topology analysis with cheminformatics measurements on drug information from the DrugBank database to detect the discrepancies between approved drugs and withdrawn drugs and give drug safety indications. Thus, 47 approved drugs were unfolded with higher similarity measurements to withdrawn ones by the same target and confirmed to be already withdrawn or discontinued in certain countries or regions in subsequent investigations. Accordingly, with the 2D chemical fingerprint similarity calculation as a medium, the method was applied to predict pharmacovigilance for natural products from an in-house traditional Chinese medicine (TCM) database. Among them, Silibinin was highlighted for the high similarity to the withdrawn drug Plicamycin although it was regarded as a promising drug candidate with a lower toxicity in existing reports. In summary, the network approach integrated with cheminformatics could provide drug safety indications effectively, especially for compounds with unknown targets or mechanisms like natural products. It would be helpful for drug safety surveillance in all phases of drug development.

The 90 kDa ribosomal S6 kinases (RSKs), especially RSK2, have attracted attention for the development of new anticancer agents. Through structural optimization of the hit compound 1 from our previous study, a series of barbituric acid aryl hydrazone analogues were designed and synthesized as potential RSK2 inhibitors. The most potent one, compound 9, showed a higher activity against RSK2 with an IC50 value of 1.95 μM. To analyze and elucidate their structure-activity relationship, the homology model of RSK2 N-terminal kinase domain was built and molecular docking simulations were performed, which provide helpful clues to design new inhibitors with desired activities.

The introduction of the multi-objective optimization has dramatically changed the virtual combinatorial library design, which can consider many objectives simultaneously, such as synthesis cost and drug-likeness, thus may increase positive rates of biological active compounds. Here we described a software called CCLab (Combinatorial Chemistry Laboratory) for combinatorial library design based on the multi-objective genetic algorithm. Tests of the convergence ability and the ratio to re-take the building blocks in the reference library were conducted to assess the software in silico, and then it was applied to a real case of designing a 5 × 6 HDAC inhibitor library. Sixteen compounds in the resulted library were synthesized, and the histone deactetylase (HDAC) enzymatic assays proved that 14 compounds showed inhibitory ratios more than 50% against tested 3 HDAC enzymes at concentration of 20 μg/mL, with IC50 values of 3 compounds comparable to SAHA. These results demonstrated that the CCLab software could enhance the hit rates of the designed library and would be beneficial for medicinal chemists to design focused library in drug development (the software can be downloaded at: http://202.127.30.184:8080/drugdesign.html ).

The insulin-like growth factors (IGF) and their receptors play pivotal roles in cellular signaling transduction and thus regulate cell growth, differentiation, apoptosis, transformation and other important physiological progresses. The insulin-like growth factor 1 receptor (IGF-1R) mainly engages in the Ras/mitogen-activated protein kinase (MAPK) pathway and the phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) pathway, and also forms cross-talk with the epidermal growth factor receptor (EGFR) pathway. Currently, it draws more attention since its overexpression has been demonstrated in various human cancers, such as colorectal cancer, breast cancer, prostate cancer and lung tumors, thus the strategy targeting the IGF-1R would be promising in treatment of these cancers. There are already dozens of agents developed for the inhibition of IGF-1R, which are categorized into monoclonal antibodies, small molecule inhibitors and so on. While in this review, small molecule inhibitors would be the focus for detailed discussion. Herein, we updated previously reported research papers and reviews in this field and summarized developments of small molecule inhibitors up to 2011. Finally, we proposed the application of network pharmacology methods to reconsider the clinical use of inhibitors with concomitant IR inhibition or other kinases inhibition, hoping that more optimal combinations would be obtained for cancer therapy.

Several potent and novel 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1) inhibitors were discovered from in silico screening the commercially available Maybridge database. Among them, seven hit compounds showed good affinity, with IC(50) values lower than 100 nM and the best one 3.7 nM. To select the lead for further optimization, computational ADME/T prediction, the CYP3A4 inhibition and 11β-HSD1 over 11β-HSD2 selectivity test were also performed. Taking all of the above factors into consideration, two promising compounds were selected as lead structures for further development. The employed hierarchical virtual screening protocol not only demonstrates its efficiency, but also provides novel and selective compounds for developing 11β-HSD1 inhibitors to protect against metabolic syndrome.

Protein kinases are attractive targets for therapeutic interventions in many diseases. Due to their importance in drug discovery, a kinase family-specific potential of mean force (PMF) scoring function, kinase-PMF, was developed to assess the binding of ATP-competitive kinase inhibitors. It is hypothesized that target-specific PMF scoring functions may achieve increased performance in scoring along with the growth of the PDB database. The kinase-PMF inherits the functions and atom types in PMF04 and uses a kinase data set of 872 complexes to derive the potentials. The performance of kinase-PMF was evaluated with an external test set containing 128 kinase crystal structures. We compared it with eight scoring functions commonly used in computer-aided drug design, either in terms of the retrieval rate of retrieving "right" conformations or a virtual screening study. The evaluation results clearly demonstrate that a target-specific scoring function is a promising way to improve prediction power in structure-based drug design compared with other general scoring functions. To provide this rescoring service for researchers, a publicly accessible Web site was established at http://202.127.30.184:8080/scoring/index.jsp .

The search for molecules whose bioactivities are similar to those of given compounds or to optimize the initial lead compounds from high throughput screening has attracted increasing interest in recent years. Our goal is to provide a publically searchable database of scaffolds out from a large collection of existing chemical molecules. Although a number of in silico methods have emerged to facilitate this process, which has become known as ”scaffold hopping” or “molecular hopping”, there is an urgent need for a database system to provide such valuable data in the drug design field. Here we have systematically analyzed a collection of commercially available small molecule databases and a bioactive compound database to identify unique scaffolds and we have built apublically searchable database. The analysis of approximately 4 800 000 of these compounds identified 241 824 unique scaffolds, which are stored in a relational database ( http://202.127.30.184:8080/db.html ). Each entry in the database is associated with a molecular occurrence and includes its distribution of molecular properties, such as molecular weight, logP, hydrogen bond acceptor number, hydrogen bond donor number, rotatable bond number and ring number. More importantly, for scaffolds derived from the bioactive compounds database, it also contains the original compounds and their target information. This Web-based database system could help researchers in the fields of medicinal and organic chemistry to design novel molecules with properties similar to the original compounds, but built on novel scaffolds.

Background T674I FIP1L1-PDGFRα in a subset of chronic eosinophilic leukemia (CEL) is a gatekeeper mutation that is resistant to many tyrosine kinase inhibitors (TKIs) (e.g., imatinib, nilotinib and dasatinib), similar to T315I Bcr-Abl. Therefore, novel TKIs effective against T674I FIP1L1-PDGFRα are needed. Ponatinib (AP24534) is a novel orally bioavailable TKI against T315I Bcr-Abl, but it is not clear whether ponatinib is effective against T674I FIP1L1-PDGFRα. The purpose of this study was to examine the effect of ponatinib on T674I FIP1L1-PDGFRα. Methods Molecular docking analysis in silico was performed. The effects of ponatinib on PDGFRα signaling pathways, apoptosis and cell cycling were examined in EOL-1, BaF3 cells expressing either wild type (WT) or T674I FIP1L1-PDGFRα. The in vivo antitumor activity of ponatinib was evaluated with xenografted BaF3-T674I FIP1L1-PDGFRα cells in nude mice models. Results Molecular docking analysis revealed that ponatinib could bind to the DFG (Asp-Phe-Gly)-out state of T674I PDGFRα. Ponatinib potently inhibited the phosphorylation of WT and T674I FIP1L1-PDGFRα and their downstream signaling molecules (e.g., Stat3, Stat5). Ponatinib strikingly inhibited the growth of both WT and T674I FIP1L1-PDGFRα-carrying CEL cells (IC50: 0.004–2.5 nM). It induced apoptosis in CEL cells with caspase-3-dependent cleavage of Mcl-1, and inhibited tyrosine phosphorylation of β-catenin to decrease its stability and pro-survival functions. In vivo, ponatinib abrogated the growth of xenografted BaF3-T674I FIP1L1-PDGFRα cells in nude mice. Conclusions Ponatinib is a pan-FIP1L1-PDGFRα inhibitor, and clinical trials are warranted to investigate its efficacy in imatinib-resistant CEL.