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Identification of afzelin potential targets in inhibiting triple-negative breast cancer cell migration using reverse docking.

ABSTRACT: Background: Triple-negative breast cancer (TNBC) tends to be aggressive and metastatic, characteristics attributable to its cellular migration capabilities. Afzelin is a chemical compound with anti-metastatic potentials. This study aimed to predict proteins involved in TNBC cell migration which could be inhibited by afzelin.

Methods: The protein database was constructed from the Kyoto Encyclopedia of Genes and Genomes pathways collection which related to cell motility, then screened for druggability using SuperTarget and Therapeutic Target Database. The involvement of druggable proteins in the TNBC metastasis process was investigated through existing publications in The National Center for Biotechnology Information PubMed database. Inhibitory potential of afzelin toward target proteins was compared to the proteins' known-inhibitor, using the reverse docking method.

Results: Ten proteins identified as potential targets of afzelin, with the top 3 being ERK2, KRas, and FAK, respectively. Afzelin's 3-O-rhamnoside group played a dominant role in forming hydrogen bonds with the target proteins. Further analysis with STRING suggested that afzelin might be able to inhibit chemotaxis and haptotaxis of TNBC cells.

Conclusions: Afzelin was predicted to inhibit TNBC cell motility, by targeting ERK2, KRas, and FAK activation.

SUBMITTER: Rachmi E

PROVIDER: S-EPMC7710241 | biostudies-literature | 2020 Nov-Dec

REPOSITORIES: biostudies-literature

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Identification of afzelin potential targets in inhibiting triple-negative breast cancer cell migration using reverse docking.

Rachmi Eva E Purnomo Basuki Bambang BB Endharti Agustina Tri AT Fitri Loeki Enggar LE

Porto biomedical journal 20201124 6

<h4>Background</h4>Triple-negative breast cancer (TNBC) tends to be aggressive and metastatic, characteristics attributable to its cellular migration capabilities. Afzelin is a chemical compound with anti-metastatic potentials. This study aimed to predict proteins involved in TNBC cell migration which could be inhibited by afzelin.<h4>Methods</h4>The protein database was constructed from the Kyoto Encyclopedia of Genes and Genomes pathways collection which related to cell motility, then screened ...[more]

PMID: 33283065

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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.

Project description:Triple negative breast cancer (TNBC) is high-risk due to its rapid drug resistance and recurrence, metastasis, and lack of targeted therapy. So far, no molecularly targeted therapeutic agents have been clinically approved for TNBC. It is imperative that we discover new targets for TNBC therapy.A large volume of cancer genomics data are emerging and advancing breast cancer research. We may integrate different types of TNBC genomic data to discover molecular targets for TNBC therapy.We used publicly available TNBC tumor tissue genomic data in the Cancer Genome Atlas database in this study.We integratively explored genomic profiles (gene expression, copy number, methylation, microRNA [miRNA], and gene mutation) in TNBC and identified hyperactivated genes that have higher expression, more copy numbers, lower methylation level, or are targets of miRNAs with lower expression in TNBC than in normal samples. We ranked the hyperactivated genes into different levels based on all the genomic evidence and performed functional analyses of the sets of genes identified. More importantly, we proposed potential molecular targets for TNBC therapy based on the hyperactivated genes.Some of the genes we identified such as FGFR2, MAPK13, TP53, SRC family, MUC family, and BCL2 family have been suggested to be potential targets for TNBC treatment. Others such as CSF1R, EPHB3, TRIB1, and LAD1 could be promising new targets for TNBC treatment. By utilizing this integrative analysis of genomic profiles for TNBC, we hypothesized that some of the targeted treatment strategies for TNBC currently in development are more likely to be promising, such as poly (ADP-ribose) polymerase inhibitors, while the others are more likely to be discouraging, such as angiogenesis inhibitors.The findings in this study need to be experimentally validated in the future.This is a systematic study that combined 5 different types of genomic data to molecularly characterize TNBC and identify potential targets for TNBC therapy. The integrative analysis of genomic profiles for TNBC could assist in identifying potential new therapeutic targets and predicting the effectiveness of a targeted treatment strategy for TNBC therapy.

Dataset Information

Identification of afzelin potential targets in inhibiting triple-negative breast cancer cell migration using reverse docking.

Publications

Identification of afzelin potential targets in inhibiting triple-negative breast cancer cell migration using reverse docking.

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