Targeting pre-mRNA splicing in cancers: roles, inhibitors, and therapeutic opportunities

Accumulating evidence has indicated that pre-mRNA splicing plays critical roles in a variety of physiological processes, including development of multiple diseases. In particular, alternative splicing is profoundly involved in cancer progression through abnormal expression or mutation of splicing factors. Small-molecule splicing modulators have recently attracted considerable attention as a novel class of cancer therapeutics, and several splicing modulators are currently being developed for the treatment of patients with various cancers and are in the clinical trial stage. Novel molecular mechanisms modulating alternative splicing have proven to be effective for treating cancer cells resistant to conventional anticancer drugs. Furthermore, molecular mechanism-based combination strategies and patient stratification strategies for cancer treatment targeting pre-mRNA splicing must be considered for cancer therapy in the future. This review summarizes recent progress in the relationship between druggable splicing-related molecules and cancer, highlights small-molecule splicing modulators, and discusses future perspectives of splicing modulation for personalized and combination therapies in cancer treatment

Polygenic architecture informs potential vulnerability to drug-induced liver injury

Drug-Induced-Liver-Injury (DILI) is a leading cause of termination in drug development programs and removal of drugs from the market, and this is partially due to the inability to identify patients who are at risk1. Here, we developed a polygenic risk score (PRS) for DILI by aggregating effects of numerous genome-wide loci identified from previous large-scale genome-wide association studies (GWAS)2. The PRS predicted the susceptibility to DILI in patients treated with fasiglifam, amoxicillin-clavulanate or flucloxacillin, and in primary hepatocytes and stem cell-derived organoids from multiple donors treated with over 10 different drugs. Pathway analysis highlighted processes previously implicated in DILI, including unfolded protein responses and oxidative stress. In silico screening identified compounds that elicit transcriptomic signatures present in hepatocytes from individuals with elevated PRS, supporting mechanistic links and suggesting a novel screen for safety of new drug candidates. This genetic-, cellular-, organoid- and human-scale evidence underscored the polygenic architecture underlying DILI vulnerability at the level of hepatocytes, thus facilitating future mechanistic studies. Moreover, the proposed “polygenicity-in-a-dish” strategy might potentially inform designs of safer, more efficient, and robust clinical trials

Gene regulatory network analysis defines transcriptome landscape with alternative splicing of human umbilical vein endothelial cells during replicative senescence

Background Endothelial cell senescence is the state of permanent cell cycle arrest and plays a critical role in the pathogenesis of age-related diseases. However, a comprehensive understanding of the gene regulatory network, including genome-wide alternative splicing machinery, involved in endothelial cell senescence is lacking. Results We thoroughly described the transcriptome landscape of replicative senescent human umbilical vein endothelial cells. Genes with high connectivity showing a monotonic expression increase or decrease with the culture period were defined as hub genes in the co-expression network. Computational network analysis of these genes led to the identification of canonical and non-canonical senescence pathways, such as E2F and SIRT2 signaling, which were down-regulated in lipid metabolism, and chromosome organization processes pathways. Additionally, we showed that endothelial cell senescence involves alternative splicing. Importantly, the first and last exon types of splicing, as observed in FLT1 and ACACA, were preferentially altered among the alternatively spliced genes during endothelial senescence. We further identified novel microexons in PRUNE2 and PSAP, each containing 9 nt, which were altered within the specific domain during endothelial senescence. Conclusions These findings unveil the comprehensive transcriptome pathway and novel signaling regulated by RNA processing, including gene expression and splicing, in replicative endothelial senescence.Medicine, Faculty ofNon UBCPathology and Laboratory Medicine, Department ofReviewedFacultyResearcherOthe

A Novel Time-Dependent CENP-E Inhibitor with Potent Antitumor Activity

<div><p>Centromere-associated protein E (CENP-E) regulates both chromosome congression and the spindle assembly checkpoint (SAC) during mitosis. The loss of CENP-E function causes chromosome misalignment, leading to SAC activation and apoptosis during prolonged mitotic arrest. Here, we describe the biological and antiproliferative activities of a novel small-molecule inhibitor of CENP-E, Compound-A (Cmpd-A). Cmpd-A inhibits the ATPase activity of the CENP-E motor domain, acting as a time-dependent inhibitor with an ATP-competitive-like behavior. Cmpd-A causes chromosome misalignment on the metaphase plate, leading to prolonged mitotic arrest. Treatment with Cmpd-A induces antiproliferation in multiple cancer cell lines. Furthermore, Cmpd-A exhibits antitumor activity in a nude mouse xenograft model, and this antitumor activity is accompanied by the elevation of phosphohistone H3 levels in tumors. These findings demonstrate the potency of the CENP-E inhibitor Cmpd-A and its potential as an anticancer therapeutic agent.</p></div

PK/PD and antitumor efficacy of Cmpd-A in a COLO205 xenograft nude mouse model.

<p>(A) Expression of pHH3 in COLO205 xenografts at the indicated time points after the intraperitoneal administration of Cmpd-A at a dose of 100 mg/kg. (B) Time-dependent PK and PD of Cmpd-A. The green, blue, and red lines indicate plasma concentration, tumor concentration, and tumor pHH3 intensity, respectively. The pHH3 intensity was quantified using the results shown in (A). (C) Immunohistochemistry of pHH3 in the tumor sections from COLO205 xenograft nude mice 24 h after the intraperitoneal administration of Cmpd-A at 100 mg/kg. Black arrows indicate misaligned chromosomes in sections from COLO205 xenografts treated with Cmpd-A. (D) Antitumor efficacy of Cmpd-A in the COLO205 xenograft nude mouse model. COLO205 xenografted nude mice intraperitoneally injected with Cmpd-A at 100 mg/kg or vehicle three times (at 0, 8, and 24 h) on the first day of the study. Representative tumors 8 days after the administration of vehicle or Cmpd-A are shown. (E) Efficacy data plotted as the mean tumor volume (mm³ ± standard error of the mean; n = 5) in COLO205 xenograft nude mice treated with Cmpd-A (red) or vehicle (black). Statistical analysis was performed using Student’s t-test. Differences were considered significant at P ≤ 0.05 (*) and P ≤ 0.01 (**). (F) Bodyweight comparison of COLO205 xenograft nude mice 8 days after the administration of Cmpd-A (red) or vehicle (black). Data are presented as mean ± standard deviation (n = 5). Statistical analysis was performed using Student’s t-test. Differences were considered significant at P ≤ 0.05 (*) and P ≤ 0.01 (**).</p

Cmpd-A exhibits potent antiproliferative activity in multiple cancer cell lines.

<p>(A) Antiproliferative activity of Cmpd-A in multiple cancer cell lines. DU145, COLO205, NIH-OVCAR3, RKO, ES2, SK-OV3, PC-3, SW620, and CAPAN-2 cell lines were treated with Cmpd-A for 3 days at the indicated concentrations. The relative ATP concentration was calculated based on the chemiluminescence compared with the 0 nM chemiluminescence value (control). Data are presented as mean ± standard deviation (n = 3). (B) Correlation between the antiproliferative activity of Cmpd-A and CENP-E mRNA expression in cancer cell lines. The X and Y axes indicate the relative ATP level at 300 nM Cmpd-A treatment and CENP-E mRNA levels in the 14 indicated cancer cell lines, respectively. The relative ATP concentration was calculated based on chemiluminescence compared with the 0 nM chemiluminescence value (control) in each cell line. The raw data of CENP-E mRNA expression was downloaded from the Cancer Cell Line Encyclopedia (<a href="http://www.broadinstitute.org/ccle/data/browseData" target="_blank">http://www.broadinstitute.org/ccle/data/browseData</a>) and processed with MAS 5.0 algorithm.</p

CENP-E inhibitor Cmpd-A induces chromosome misalignment during mitosis.

<p>(A) Cmpd-A is a time-dependent inhibitor with an ATP competitive-like behavior. Red and black lines indicate the dose-dependent activity of Cmpd-A in the presence of low (1.25 μM) and high (500 μM) concentrations of ATP, respectively. The blue line indicates the activity of Cmpd-A with a high concentration of ATP, following 1 h of preincubation with CENP-E. The X-axis and Y-axis indicate the concentration of Cmpd-A and % inhibition of CENP-E ATPase activity, respectively. (B) Representative mitotic HeLa cells treated with Cmpd-A (200 nM) or DMSO. Arrows indicate misaligned chromosomes. Blue, green, and red signals indicate 4′,6-diamidino-2-phenylindole (DAPI)-stained DNA, α-tubulin, and CENP-B (kinetochores), respectively. (C) Quantitative analysis of mitotic morphology in the DMSO- or Cmpd-A-treated HeLa cells. The cells were treated for 3 h with 200 nM Cmpd-A or DMSO after dT block release. The DMSO- and Cmpd-A-treated mitotic cells (105 and 106 cells, respectively) were then counted. (D) Inter-kinetochore distance of aligned and misaligned chromosomes in HeLa cells treated with Cmpd-A or DMSO. Prometaphase (left) and metaphase (middle) cells were used as controls for misaligned and aligned chromosomes, respectively. The inter-kinetochore distance was measured between the outer kinetochore markers (HEC1) of individual chromosomes. Statistical analysis was performed using Student’s t-test. Differences were considered significant at P ≤ 0.05 (*) and P ≤ 0.01 (**).</p

Cmpd-A induces prolonged mitotic arrest accompanied by SAC activation.

<p>(A) Cell cycle histogram of synchronous HeLa cells treated with Cmpd-A (200 nM) or DMSO. Cmpd-A was added at the G2 phase (7 h after dT block release), and the cells were collected at the indicated time points for FACS analysis. (B) pHH3 in synchronous HeLa cells treated with Cmpd-A (200 nM) or DMSO. Cmpd-A was added at the G2 phase (7 h after dT block release), and the cells were collected 12 h after dT block release. Representative results are shown. (C) pHH3 elevation in synchronous HeLa cells treated with Cmpd-A (200 nM) or DMSO. Cmpd-A was added at the G2 phase (7 h after dT block release), and the cells were collected at the indicated time points for FACS analysis of pHH3 staining. The graph indicates quantified pHH3-positive cells (mean ± standard deviation; n = 3). Red and blue lines indicate Cmpd-A- and DMSO-treated HeLa cells, respectively. (D) Immunoblotting of mitosis markers in synchronous HeLa cells treated with Cmpd-A or DMSO. The cells were treated with Cmpd-A or DMSO as described in Fig 2A and collected 12 h after dT block release for immunoblotting.</p

Time-dependent antiproliferative activity of Cmpd-A in HeLa cells.

<p>(A) Experimental schemes to asses time-dependent antiproliferative activity of Cmpd-A. HeLa cells were treated with Cmpd-A at the indicated concentrations for 4, 8, 24, 48, and 72 h (red arrows) and then the cells were cultured in Cmpd-A-free medium for 72 h (black arrows). Cells were collected 72 h after treatment for cell viability analysis. (B) Time-dependent antiproliferative activity of Cmpd-A in HeLa cells. The relative ATP concentration was calculated based on chemiluminescence compared with the 0 nM chemiluminescence value (control). Data are presented as mean ± standard deviation (n = 8). (C) Quantitative RT-PCR analysis of CENP-E in cancer cell lines and human skin fibroblasts (MRC5). CENP-E expression ratios were quantified using GAPDH expression in each cell line as a control. Data are presented as mean ± standard deviation (n = 3).</p