1, 8-cineole attenuates cardiac hypertrophy in heart failure by inhibiting the miR-206-3p/SERP1 pathway

BACKGROUND

1,8-Cineole (1,8-CIN) is a monoterpene found in diverse dietary and medicinal herbs that has been reported to be effective against cardiovascular diseases.

PURPOSE

The present research was designed to elucidate the treatment effects and the underlying mechanism of 1,8-CIN on heart failure (HF).

METHOD

An in vitro cardiac hypertrophy model and an in vivo heart failure (HF) model induced by isoprenaline (ISO) were established and treated with or without 1,8-CIN. In vitro miR-206-3p mimic or inhibitors were created. MiR-206-3p, SERP1 and related mRNAs or proteins were detected using qPCR or western blotting. Cell viability was tested by MTT assay, and apoptosis was measured using TUNEL assay, AO/EB assay and flow cytometry. Actin was stained with FITC-phalloidin. MiR-206-3p and related mRNAs or proteins in cardiac muscle tissues were measured using qPCR or western blotting, HE staining, Masson staining.

RESULTS

ISO subcutaneous injection increased cardiac hypertrophy, cytoplasmic vacuole formation, myofiber loss and fibrosis and decreased cardiomyocyte viability. 1,8-CIN treatment improved cardiomyocyte viability and reduced cardiac hypertrophy, cytoplasmic vacuole formation, myofibre loss and fibrosis. We found that 1,8-CIN attenuated apoptosis. We observed that expression of miR-206-3p was dramatically increased in ISO-exposed cardiomyocytes or ISO-treated rat hearts. MiR-206-3p was identified to target the 3'UTR of SERP1, resulting in the accumulation of un- or misfolded proteins, leading to endoplasmic reticulum (ER) stress.

CONCLUSION

These results suggest that 1,8-CIN reduces the apoptosis induced by ER stress through inhibiting miR-206-3p, which inhibits the expression of SERP1.

Identifying molecular targets for reverse aging using integrated network analysis of transcriptomic and epigenomic changes during aging

Aging is associated with widespread physiological changes, including skeletal muscle weakening, neuron system degeneration, hair loss, and skin wrinkling. Previous studies have identified numerous molecular biomarkers involved in these changes, but their regulatory mechanisms and functional repercussions remain elusive. In this study, we conducted next-generation sequencing of DNA methylation and RNA sequencing of blood samples from 51 healthy adults between 20 and 74 years of age and identified aging-related epigenetic and transcriptomic biomarkers. We also identified candidate molecular targets that can reversely regulate the transcriptomic biomarkers of aging by reconstructing a gene regulatory network model and performing signal flow analysis. For validation, we screened public experimental data including gene expression profiles in response to thousands of chemical perturbagens. Despite insufficient data on the binding targets of perturbagens and their modes of action, curcumin, which reversely regulated the biomarkers in the experimental dataset, was found to bind and inhibit JUN, which was identified as a candidate target via signal flow analysis. Collectively, our results demonstrate the utility of a network model for integrative analysis of omics data, which can help elucidate inter-omics regulatory mechanisms and develop therapeutic strategies against aging.

Transmembrane tumor necrosis factor alpha attenuates pressure-overload cardiac hypertrophy via tumor necrosis factor receptor 2

Tumor necrosis factor-alpha (TNF-α) plays an important pathogenic role in cardiac hypertrophy and heart failure (HF); however, anti-TNF is paradoxically negative in clinical trials and even worsens HF, indicating a possible protective role of TNF-α in HF. TNF-α exists in transmembrane (tmTNF-α) and soluble (sTNF-α) forms. Herein, we found that TNF receptor 1 (TNFR1) knockout (KO) or knockdown (KD) by short hairpin RNA or small interfering RNA (siRNA) significantly alleviated cardiac hypertrophy, heart dysfunction, fibrosis, and inflammation with increased tmTNF-α expression, whereas TNFR2 KO or KD exacerbated the pathological phenomena with increased sTNF-α secretion in transverse aortic constriction (TAC)- and isoproterenol (ISO)-induced cardiac hypertrophy in vivo and in vitro, respectively, indicating the beneficial effects of TNFR2 associated with tmTNF-α. Suppressing TNF-α converting enzyme by TNF-α Protease Inhibitor-1 (TAPI-1) to increase endogenous tmTNF-α expression significantly alleviated TAC-induced cardiac hypertrophy. Importantly, direct addition of exogenous tmTNF-α into cardiomyocytes in vitro significantly reduced ISO-induced cardiac hypertrophy and transcription of the pro-inflammatory cytokines and induced proliferation. The beneficial effects of tmTNF-α were completely blocked by TNFR2 KD in H9C2 cells and TNFR2 KO in primary myocardial cells. Furthermore, we demonstrated that tmTNF-α displayed antihypertrophic and anti-inflammatory effects by activating the AKT pathway and inhibiting the nuclear factor (NF)-κB pathway via TNFR2. Our data suggest that tmTNF-α exerts cardioprotective effects via TNFR2. Specific targeting of tmTNF-α processing, rather than anti-TNF therapy, may be more useful for the treatment of hypertrophy and HF.

In contrast to detrimental effects of soluble tumor necrosis factor-alpha (TNF-α) via TNFR1, this study shows that transmembrane TNF-α protects the heart by suppressing pressure overload-induced cardiac hypertrophy and inflammation via TNFR2. Targeting tmTNF-α processing may be more useful than TNF-antagonist for treatment of hypertrophy and heart failure.

Realizing Cancer Precision Medicine by Integrating Systems Biology and Nanomaterial Engineering

Many clinical trials for cancer precision medicine have yielded unsatisfactory results due to challenges such as drug resistance and low efficacy. Drug resistance is often caused by the complex compensatory regulation within the biomolecular network in a cancer cell. Recently, systems biological studies have modeled and simulated such complex networks to unravel the hidden mechanisms of drug resistance and identify promising new drug targets or combinatorial or sequential treatments for overcoming resistance to anticancer drugs. However, many of the identified targets or treatments present major difficulties for drug development and clinical application. Nanocarriers represent a path forward for developing therapies with these "undruggable" targets or those that require precise combinatorial or sequential application, for which conventional drug delivery mechanisms are unsuitable. Conversely, a challenge in nanomedicine has been low efficacy due to heterogeneity of cancers in patients. This problem can also be resolved through systems biological approaches by identifying personalized targets for individual patients or promoting the drug responses. Therefore, integration of systems biology and nanomaterial engineering will enable the clinical application of cancer precision medicine to overcome both drug resistance of conventional treatments and low efficacy of nanomedicine due to patient heterogeneity.

Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker

Coronary atherosclerosis is one of the major factors causing cardiovascular diseases. However, identifying the tipping point (predisease state of disease) and detecting early-warning signals of human coronary atherosclerosis for individual patients are still great challenges. The landscape dynamic network biomarkers (l-DNB) methodology is based on the theory of dynamic network biomarkers (DNBs), and can use only one-sample omics data to identify the tipping point of complex diseases, such as coronary atherosclerosis. Based on the l-DNB methodology, by using the metabolomics data of plasma of patients with coronary atherosclerosis at different stages, we accurately detected the early-warning signals of each patient. Moreover, we also discovered a group of dynamic network biomarkers (DNBs) which play key roles in driving the progression of the disease. Our study provides a new insight into the individualized early diagnosis of coronary atherosclerosis and may contribute to the development of personalized medicine.

Feedback analysis identifies a combination target for overcoming adaptive resistance to targeted cancer therapy

Targeted drugs aim to treat cancer by directly inhibiting oncogene activity or oncogenic pathways, but drug resistance frequently emerges. Due to the intricate dynamics of cancer signaling networks, which contain complex feedback regulations, cancer cells can rewire these networks to adapt to and counter the cytotoxic effects of a drug, thereby limiting the efficacy of targeted therapies. To identify a combinatorial drug target that can overcome such a limitation, we developed a Boolean network simulation and analysis framework and applied this approach to a large-scale signaling network of colorectal cancer with integrated genomic information. We discovered Src as a critical combination drug target that can overcome the adaptive resistance to the targeted inhibition of mitogen-activated protein kinase pathway by blocking the essential feedback regulation responsible for resistance. The proposed framework is generic and can be widely used to identify drug targets that can overcome adaptive resistance to targeted therapies.