High-Throughput In Vitro Gene Expression Profile to Screen of Natural Herbals for Breast Cancer Treatment

Abstract

Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer in women worldwide. Some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in breast cancer. However, the chemical composition and underlying anti-tumor mechanisms of TCM still need to be investigated. The primary aim of this study is to provide unique insights to screen the natural components for breast cancer therapy using high-throughput transcriptome analysis. Differentially expressed genes were identified based on two conditions: single samples and groups were classified according to their pharmaceutical effect. Subsequently, the sample treated with E. cochinchinensis Lour. generated the most significant DEGs set, including 1,459 DEGs, 805 upregulated and 654 downregulated. Similarly, group 3 treatment contained the most DEGs (414 DEGs, 311 upregulated and 103 downregulated). KEGG pathway analyses showed five significant pathways associated with the inflammatory and metastasis processes in cancer, which include the TNF, IL−17, NF-kappa B, MAPK signaling pathways, and transcriptional misregulation in cancer. Samples were classified into 13 groups based on their pharmaceutical effects. The results of the KEGG pathway analyses remained consistent with signal samples; group 3 presents a high significance. A total of 21 genes were significantly regulated in these five pathways, interestingly, IL6, TNFAIP3, and BRIC3 were enriched on at least two pathways, seven genes (FOSL1, S100A9, CXCL12, ID2, PRS6KA3, AREG, and DUSP6) have been reported as the target biomarkers and even the diagnostic tools in cancer therapy. In addition, weighted correlation network analysis (WGCNA) was used to identify 18 modules. Among them, blue and thistle2 were the most relevant modules. A total of 26 hub genes in blue and thistle2 modules were identified as the hub genes. In conclusion, we screened out three new TCM (R. communis L., E. cochinchinensis Lour., and B. fruticosa) that have the potential to develop natural drugs for breast cancer therapy, and obtained the therapeutic targets.

Integrative competing endogenous RNA network analyses identify novel lncRNA and genes implicated in metastatic breast cancer

“…BMP2 from the stage I survival analysis has shown oncogenic function in BC 33 . Only DUSP6 and ACSL1 in stage II have acted as an oncogene and a tumour suppressor in BC, respectively 34,35 . DST and AHNAK genes that were significant from the stage III survival analysis have shown tumour suppressive characteristics in both experimental and computational BC studies [36][37][38][39][40] .…”

Identification of miR‐3182 and miR‐3143 target genes involved in the cell cycle as a novel approach in TNBC treatment: A systems biology approach

“…Kim et al (2020) showed that miR-4516 overexpression could suppress TNBC cells' proliferation by targeting FOSL1. A recent study by Kui et al (2021) using high-throughput transcriptome analysis for breast cancer therapy have reported FOSL1 as a biomarker and even a diagnostic tool in cancer therapy. In this study, FOSL1 was introduced as a critical target of miR-3182 obtained in hub and bottlenecks of motif subnetwork.…”

Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools

“…[4,5] Progress in microarray and RNA-sequencing technology has expanded our understanding of the complex and dynamic nature of the transcriptome. [6] Numerous studies have reported the importance of comparative transcriptome analysis in BC to assess the expression levels of functional genes, key pathways, and activity of cellular regulatory mechanisms, [7][8][9] and, subsequently, provide new insights into the prediction of disease prognosis and the discovery of targeted anticancer therapies.…”