Integrated Analysis of mRNA-seq and miRNA-seq to Identify c-MYC, YAP1 and miR-3960 as Major Players in the Anticancer Effects of Caffeic Acid Phenethyl Ester in Human Small Cell Lung Cancer Cell Line

Abstract

Background: Caffeic Acid Phenethyl Ester (CAPE), an active extract of propolis, has recently been reported to have broad applications in various cancers. However, the effects of CAPE on Small Cell Lung Cancer (SCLC) are largely unknown. Therefore, the aim of this study was to determine the anti-proliferative effect of CAPE and explore the underlying molecular mechanisms in SCLC cells using high-throughput sequencing and bioinformatics analysis. Methods: Small-cell lung cancer H446 cells were treated with CAPE, and cell proliferation and apoptosis were then assessed. Additionally, the regulation mediated by miR-3960 after CAPE treatment was explored and the altered signaling pathways were predicted in a bioinformatics analysis. Results: CAPE significantly inhibited cell proliferation and induced apoptosis. CAPE decreased the expression of Yes-Associated Protein 1 (YAP1) and cellular myelocytomatosis oncogene (c-MYC) protein. Moreover, the upregulation of miR-3960 by CAPE contributed to CAPE-induced apoptosis. The knockdown of miR-3960 decreased the CAPE-induced apoptosis. Conclusion: We demonstrated the anti-cancer effect of CAPE in human SCLC cells and studied the mechanism by acquiring a comprehensive transcriptome profile of CAPE-treated cells.

Colon Cancer-Related Genes Identification and Function Study Based on Single-Cell Multi-Omics Integration

“…With the development of different kinds of treatment technologies, the 5-year survival rate of early-stage colon cancer patients has increased up to 90%, however, many urgent problems remain to be solved: for example, the median survival time of colon cancer patients with metastasis is less than 2 years, and 5-year overall survival rate is only 50–65%. Early screening and diagnosis for colon cancer mainly depend on electronic colorectal mirror surgery and pathology, which is expensive and has poor prognosis ( Kiriyama et al, 2012 ; Chiba et al, 2014 ; Missiaglia et al, 2014 ; Fakih, 2015 ; Miller et al, 2016 ; Sewda et al, 2016 ; Marmol et al, 2017 ; White et al, 2017 ; Zhao et al, 2017 ; Hu et al, 2020 ; Mo et al, 2020 ; Hu et al, 2021a ; Hu et al, 2021b ). As a result, molecular biomarkers are vital for verifying the mechanism that promotes colon cancer development and improving early screening, diagnosis, and treatment for colon cancer.…”

Bioinformatics Research on Drug Sensitivity Prediction

“…The capsule network can learn the posture information of different cells from the cancer cell line, and convert the information that might be missed by the traditional CNN network into high-level features, which can be used to predict the sensitivity of drugs to the cancer cell line. The contribution/inhibition relationship between drug groups for specific diseases was obtained using the Shapley value method of cooperative game theory to analyze the convolutional neural network model ( Aumann and Shapley, 1971 ; Karim et al, 2019 ; Cai et al, 2020a ; Cai et al, 2020b ; Mo et al, 2020 ), as well as through calculation and comparative analysis of the marginal contributions between drug groups. The project mainly studied three points: 1) Feature quantification methods oriented at the prior knowledge of genomics and drug targeting information to construct a deep feed-forward network and encode drug fingerprints based on drug targeting relationships.…”

Identification of miRNA Signature Associated With Erectile Dysfunction in Type 2 Diabetes Mellitus by Support Vector Machine-Recursive Feature Elimination

“…MicroRNAs (miRNAs) are small non-coding RNAs of 19–25 nucleotides ( Cheng et al, 2016 ; Lu and Rothenberg, 2018 ; Wu et al, 2019 ; Mo et al, 2020 ). They have been used as important regulators of gene expression in recent decades.…”