Fluoxetine regulates cell growth inhibition of interferon-α

Fluoxetine inactivates STAT3/NF-κB signaling and promotes sensitivity to cisplatin in bladder cancer

Bladder cancer is known as one of the top ten most common cancer types worldwide and can be majorly divided into muscles invasive bladder cancer (MIBC) and non-muscles invasive type (NMIBC). However, the prognosis of BC remains poor under standard treatment including radical cystectomy or concurrent chemoradiotherapy. Numerous studies have reported that the prognosis of BC is associated with the activation of signal transducer and activator of transcription (STAT3) and nuclear factor kappa-B (NF-κB). Fluoxetine, a well-known anti-depressant, has been reported to against various type of cancers. However, it is unclear whether fluoxetine has the capacity to inhibit BC progression by targeting STAT3 and NF-κB-mediated signaling. Here, we used cell viability, apoptosis assay, wound healing assay, invasion/migration assay, Western blotting assay, immunofluorescence staining, as well as animal experiments, to elucidate the efficacy of fluoxetine on in vitro and in vivo BC models. We found that fluoxetine may induce cytotoxicity and intrinsic/extrinsic apoptosis in BC and enhance the potential of cisplatin. Fluoxetine promoted both caspase-dependent and caspase-independent apoptosis signaling by activating caspase-3, 8, 9, apoptosis-inducing factor (AIF), and EndG. Furthermore, fluoxetine suppressed invasion and migration ability and the expression of metastasis-associated genes. Fluoxetine was also found to inactivate the phosphorylation of STAT3 (Tyr705) and NF-κB (Ser536) and suppress the nuclear translocation of NF-κB. In MB49-bearing mice, fluoxetine effectively delayed the progression of BC without inducing general toxicity. In summary, the induction of apoptosis and the inhibition of invasion triggered by fluoxetine are associated with the inactivation of STAT3 and NF-κB.

The application of antidepressant drugs in cancer treatment

Antidepressants refer to psychotropic drugs which are used to treat mental illness with prominent emotional depression symptoms. It was reported that antidepressants had associated with anti-carcinogenic function which was associated with various signaling pathways and changing of microenvironment. Its mechanism includes cell apoptosis, antiproliferative effects, mitochondria-mediated oxidative stress, DNA damaging, changing of immune response and inflammatory conditions, and acting by inhibiting multidrug resistance of cancer cells. Accumulated studies showed that antidepressants influenced the metabolic pathway of tumor cells. This review summarized recent developments with the impacts and mechanisms of 10 kinds of antidepressants in carcinostasis. Antidepressants are also used in combination therapy with typical anti-tumor drugs which shows a synergic effect in anti-tumor. By contrast, the promotion roles of antidepressants in increasing cancer recurrence risk, mortality, and morbidity are also included. Further clinical experiments and mechanism analyses needed to be achieved. A full understanding of the underlying mechanisms of antidepressants-mediated anticarcinogenic effects may provide new clues for cancer prevention and clinical treatment.

Cell cycle abnormality is a cellular phenotype in OCD

Abnormal indices of cell cycle regulation have been reported in multiple psychiatric disorders. Though reports specific to Obsessive Compulsive Disorder (OCD) are scant, numerous studies have highlighted partly common underlying biology in psychiatric disorders, cell cycle regulation being one such process. In this study, we therefore aimed to explore cell cycle in OCD. To the best of our knowledge, this is the first study to investigate these effects in OCD. We also evaluated the effect of in vitro fluoxetine, commonly used serotonin reuptake inhibitor (SRI) in OCD patients, on cell cycle regulation. The effects of both disease (OCD) and treatment (SRI) were assessed using lymphoblastoid cell lines (LCLs), derived from OCD patients and healthy controls, as a model system. LCLs were treated with 10μM of fluoxetine for 24 h, and the percentage of cells in each phase of the cell cycle was determined by flow cytometry. We observed a lower proportion of cells in the G2/M phase in OCD cases than controls. The findings suggest that cell cycle dysregulation could be peripheral cellular phenotype for OCD. Among cases, all of whom had been systematically characterized for SRI treatment response, LCLs from non-responders to SRI treatment had a lower proportion of cells in G2/M phase than responders.

Interferon-inducer antivirals: Potential candidates to combat COVID-19

Coronavirus disease 2019 (COVID-19) is an infective disease generated by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the pandemic urgency and lack of an effective cure for this disease, drug repurposing could open the way for finding a solution. Lots of investigations are ongoing to test the compounds already identified as antivirals. On the other hand, induction of type I interferons are found to play an important role in the generation of immune responses against SARS-CoV-2. Therefore, it was opined that the antivirals capable of triggering the interferons and their signaling pathway, could rationally be beneficial for treating COVID-19. On this basis, using a database of antivirals, called drugvirus, some antiviral agents were derived, followed by searches on their relevance to interferon induction. The examined list included drugs from different categories such as antibiotics, immunosuppressants, anti-cancers, non-steroidal anti-inflammatory drugs (NSAID), calcium channel blocker compounds, and some others. The results as briefed here, could help in finding potential drug candidates for COVID-19 treatment. However, their advantages and risks should be taken into account through precise studies, considering a systemic approach. Even though the adverse effects of some of these drugs may overweight their benefits, considering their mechanisms and structures may give a clue for designing novel drugs in the future. Furthermore, the antiviral effect and IFN-modifying mechanisms possessed by some of these drugs might lead to a synergistic effect against SARS-CoV-2, which deserve to be evaluated in further investigations.

The Association between Selective Serotonin Reuptake Inhibitors (SSRIs) Use and the Risk of Bladder Cancer: A Nationwide Population-Based Cohort Study

Background: Past studies suggest mixed associations between selective serotonin reuptake inhibitor (SSRI) prescription and carcinogenic risk. There is no epidemiological study reporting on the association between SSRI use and the incidence of bladder cancer. The aim of this study is to determine whether SSRI use influences the risk of bladder cancer. Methods: We conducted a nationwide retrospective cohort study by Taiwan’s National Health Insurance Research Database from January 1, 1997 to December 31, 2013. 192,392 SSRI prescribed individuals were randomly matched 1 to 1 with 191,786 individuals who had never received any SSRIs by propensity scores match. The Cox Proportional Hazard models were conducted to examine the risk of bladder cancer between individuals prescribed SSRIs and individuals not prescribed SSRIs. Results: SSRIs were associated with significant reduced risk of bladder cancer with 0.5, 1, and 2 year induction periods (adjusted hazard ratio (aHR) = 0.86, 95% CI (confidence interval) = 0.76–0.98, aHR = 0.85, 95% CI = 0.75–0.97, and aHR = 0.77, 95% CI = 0.66–0.89). When examining the effect of specific SSRI, there was significantly lower risk of bladder cancer in individuals prescribed fluoxetine (6 month induction period: aHR = 0.78, 95% CI = 0.65–0.93; 1 year induction period: aHR = 0.78, 95% CI = 0.65–0.94; 2 year induction period: aHR = 0.73, 95% CI = 0.60–0.89), paroxetine (6 month induction period: aHR = 0.78, 95% CI = 0.61–0.99; 1 year induction period: aHR = 0.79, 95% CI = 0.61–1.01; 2 year induction period: aHR = 0.72, 95% CI = 0.54–0.95), and citalopram (6 month induction period: aHR = 0.74, 95% CI = 0.53–1.03; 1 year induction period: aHR = 0.70, 95% CI = 0.50–0.99; 2 year induction period: aHR = 0.60, 95% CI = 0.41–0.88). Conclusions: Individuals prescribed fluoxetine, paroxetine, or citalopram had a reduced risk of bladder cancer in this large, cross-national database.

Antidepressant use and hepatocellular carcinoma in patients with hepatitis C who had received interferon therapy: A population-based cohort study

BACKGROUND

Using data from the National Health Insurance (NHI) of Taiwan, we conducted a nationwide population-based cohort study to investigate the association between antidepressant (ATD) use and the risk of hepatocellular carcinoma (HCC) in patients with hepatitis C virus (HCV) who had received interferon (IFN) therapy.

METHODS

This study included a total of 274,952 HCV-infected patients without hepatitis B virus infection who were enrolled in the NHI program between January 1, 1997 and December 31, 2013. Among these patients, only 10,713 (age ≥18 years) had received IFN therapy between 2004 and 2008. Among the patients who had received IFN therapy, 2014 had received ATDs, and 8684 had not. A Cox proportional hazards regression model was applied after adjusting for age, sex, income, urbanization, medical comorbidity, and medication use.

RESULTS

Compared with non-ATD-treated patients, ATD-treated patients were more likely to receive a diagnosis of alcohol-related disease, diabetes mellitus (DM), hypertension, and hyperlipidemia. ATD-treated patients had a significantly lower incidence of HCC than non-ATD-treated patients (P = 0.0019). Female, older (age ≥50 years), and non-DM patients who had received cumulative high doses of ATDs had a significantly lower risk of HCC than non-ATD-treated patients. After adjustment, only high-dose selective serotonin reuptake inhibitor (SSRI) use was inversely associated with HCC risk (adjusted hazard ratio 0.37, 95% confidence interval 0.19-0.71, P = 0.0027).

CONCLUSIONS

Our study showed that ATD use, especially a relatively high cumulative dose of SSRIs, in HCV-infected patients who had received IFN was associated with reduced HCC risk. Future clinical studies are warranted to explore the underlying mechanisms and to apply them to newer direct-acting antiviral agent treatments.

BTNET : boosted tree based gene regulatory network inference algorithm using time-course measurement data

Background

Identifying gene regulatory networks is an important task for understanding biological systems. Time-course measurement data became a valuable resource for inferring gene regulatory networks. Various methods have been presented for reconstructing the networks from time-course measurement data. However, existing methods have been validated on only a limited number of benchmark datasets, and rarely verified on real biological systems.

Results

We first integrated benchmark time-course gene expression datasets from previous studies and reassessed the baseline methods. We observed that GENIE3-time, a tree-based ensemble method, achieved the best performance among the baselines. In this study, we introduce BTNET, a boosted tree based gene regulatory network inference algorithm which improves the state-of-the-art. We quantitatively validated BTNET on the integrated benchmark dataset. The AUROC and AUPR scores of BTNET were higher than those of the baselines. We also qualitatively validated the results of BTNET through an experiment on neuroblastoma cells treated with an antidepressant. The inferred regulatory network from BTNET showed that brachyury, a transcription factor, was regulated by fluoxetine, an antidepressant, which was verified by the expression of its downstream genes.

Conclusions

We present BTENT that infers a GRN from time-course measurement data using boosting algorithms. Our model achieved the highest AUROC and AUPR scores on the integrated benchmark dataset. We further validated BTNET qualitatively through a wet-lab experiment and showed that BTNET can produce biologically meaningful results.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0547-0) contains supplementary material, which is available to authorized users.