High-Throughput Screen of Natural Compounds and Biomarkers for NSCLC Treatment by Differential Expression and Weighted Gene Coexpression Network Analysis (WGCNA).

Lung cancer is known as the leading cause which presents the highest fatality rate worldwide; non-small-cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with high severity and affects 80% of patients with lung malignancies. Up to now, the general treatment for NSCLC includes surgery, chemotherapy, and radiotherapy; however, 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 lung cancer. Therefore, it is necessary to investigate the chemical composition and underlying antitumor mechanisms of TCM, so as to get a better understanding of the potential natural ingredient for lung cancer treatment. In this study, we selected 78 TCM to treat NSCLC cell line (A549) and obtained 92 transcriptome data; differential expression and WGCNA were applied to screen the potential natural ingredient and target genes. The sample which was treated with A. pierreana generated the most significant DEG set, including 6130 DEGs, 2479 upregulated, and 3651 downregulated. KEGG pathway analyses found that four pathways (MAPK, NF-kappa B, p53, and TGF-beta signaling pathway) were significantly enriched; 16 genes were significantly regulated in these four pathways. Interestingly, some of them such as EGFR, DUSP4, IL1R1, IL1B, MDM2, CDKNIA, and IDs have been used as the target biomarkers for cancer diagnosis and therapy. In addition, classified samples into 14 groups based on their pharmaceutical effects, WGCNA was used to identify 27 modules. Among them, green and darkgrey were the most relevant modules. Eight genes in the green module and four in darkgrey were identified as hub genes. In conclusion, we screened out three new TCM (B. fruticose, A. pierreana, and S. scandens) that have the potential to develop natural anticancer drugs and obtained the therapeutic targets for NSCLC therapy. Our study provides unique insights to screen the natural components for NSCLC therapy using high-throughput transcriptome analysis.

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

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.

HGFDB: a collective database of helmeted guinea fowl genomics.

As a vigorous and hardy and an almost disease-free game bird, the domestic helmeted guinea fowl (Numida meleagris, hereafter HGF) has attracted considerable attention in a large number of genetic study projects. However, none of the current/recent avian databases are related to this agriculturally and commercially important poultry species. To address this data gap, we developed Helmeted Guinea Fowl Database (HGFDB), which manages and shares HGF genomic and genetic data. By processing the data of genome assembly, sequencing reads and genetic variations, we organized them into eight modules, which correspond to 'Home', 'Genome', 'Re-sequence', 'Gene', 'Variation', 'Download', 'Tools' and 'Help', HGFDB provides the most comprehensive view of the HGF genome to date and will be relevant for future studies on HGF structural and functional genomics and genetic improvement. Database URL: http://hgfdb.ynau.edu.cn/.

FishDB: an integrated functional genomics database for fishes.

BACKGROUND: Hundreds of genomes and transcriptomes of fish species have been sequenced in recent years. However, fish scholarship currently lacks a comprehensive, integrated, and up-to-date collection of fish genomic data. RESULTS: Here we present FishDB, the first database for fish multi-level omics data, available online at http://fishdb.ihb.ac.cn . The database contains 233 fish genomes, 201 fish transcriptomes, 5841 fish mitochondrial genomes, 88 fish gene sets, 16,239 miRNAs of 65 fishes, 1,330,692 piRNAs and 4852 lncRNAs of Danio rerio, 59,040 Mb untranslated regions (UTR) of 230 fishes, and 31,918 Mb coding sequences (CDS) of 230 fishes. Among these, we newly generated a total of 11 fish genomes and 53 fish transcriptomes. CONCLUSIONS: This release contains over 410,721.67 Mb sequences and provides search functionality, a BLAST server, JBrowse, and PrimerServer modules.