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Efficacy based ginger fingerprinting reveals potential antiproliferative analytes for triple negative breast cancer.

ABSTRACT: Ginger (Zingiber officinale) is one of the most widely consumed dietary supplements worldwide. Its anticancer potential has been demonstrated in various studies. However, ginger roots obtained from different geographical locations showed extensive variability in their activities, mainly due to differences in the levels of bioactive compounds. Here we evaluated the effect of these differences on the anticancer activity of ginger by performing efficacy-based fingerprinting. We characterized the fingerprint profiles of 22 ginger samples using liquid chromatography-mass spectroscopy, followed by a principal component analysis (PCA) and pearson correlation analysis. We also evaluated the anti-proliferative effects (IC50) of these samples on triple-negative breast cancer cells using the MTT assays. The supervised PCA identified a subset of analytes whose abundance strongly associated with the IC50 values of the ginger extracts, providing a link between ginger extract composition and in vitro anticancer efficacy. This study demonstrated that variation in the ginger fingerprint profiles resulting from differences in their chemical composition could have a significant impact on efficacy and bioactivity of ginger extracts. Also, this first-of-a-kind efficacy-based fingerprinting approach proposed here can identify potent anticancer candidates from the ginger fingerprint without the need for isolating individual components from the extracts.

SUBMITTER: Zhao L

PROVIDER: S-EPMC7644756 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Efficacy based ginger fingerprinting reveals potential antiproliferative analytes for triple negative breast cancer.

Zhao Lihan L Rupji Manali M Choudhary Ishita I Osan Remus R Kapoor Shobhna S Zhang Hong-Jie HJ Yang Chunhua C Aneja Ritu R

Scientific reports 20201105 1

Ginger (Zingiber officinale) is one of the most widely consumed dietary supplements worldwide. Its anticancer potential has been demonstrated in various studies. However, ginger roots obtained from different geographical locations showed extensive variability in their activities, mainly due to differences in the levels of bioactive compounds. Here we evaluated the effect of these differences on the anticancer activity of ginger by performing efficacy-based fingerprinting. We characterized the fi ...[more]

PMID: 33154433

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Project description:(1) Background: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high intra-tumoral heterogeneity. The epithelial-mesenchymal transition (EMT) is one of the inducers of cancer metastasis and migration. However, the description of the EMT process in TNBC using single-cell RNA sequencing (scRNA-seq) remains unclear. (2) Methods: In this study, we analyzed 8938 cellular gene expression profiles from five TNBC patients. We first scored each malignant cell based on functional pathways to determine its EMT characteristics. Then, a pseudo-time trajectory analysis was employed to characterize the cell trajectories. Furthermore, CellChat was used to identify the cellular communications. (3) Results: We identified 888 epithelium-like and 846 mesenchyme-like malignant cells, respectively. A further pseudo-time trajectory analysis indicated the transition trends from epithelium-like to mesenchyme-like in malignant cells. To characterize the potential regulators of the EMT process, we identified 10 dysregulated transcription factors (TFs) between epithelium-like and mesenchyme-like malignant cells, in which overexpressed forkhead box protein A1 (FOXA1) was recognized as a poor prognosis marker of TNBC. Furthermore, we dissected the cell-cell communications via ligand-receptor (L-R) interactions. We observed that tumor-associated macrophages (TAMs) may support the invasion of malignant epithelial cells, based on CXCL-CXCR2 signaling. The tumor necrosis factor (TNF) signaling pathway secreted by TAMs was identified as an outgoing communication pattern, mediating the communications between monocytes/TAMs and malignant epithelial cells. Alternatively, the TNF-related ligand-receptor (L-R) pairs showed promising clinical implications. Some immunotherapy and anti-neoplastic drugs could interact with the L-R pairs as a potential strategy for the treatment of TNBC. In summary, this study enhances the understanding of the EMT process in the TNBC microenvironment, and dissections of EMT-related cell communications also provided us with potential treatment targets.

Project description:PurposeTriple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC.MethodsThe TNBC patients' data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC.ResultsWe obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database.ConclusionThe prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC.

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Efficacy based ginger fingerprinting reveals potential antiproliferative analytes for triple negative breast cancer.

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Efficacy based ginger fingerprinting reveals potential antiproliferative analytes for triple negative breast cancer.

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