<i>Toxoplasma gondii</i> suppresses proliferation and migration of breast cancer cells by regulating their transcriptome

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Breast cancer is the most common cancer in women worldwide. Toxoplasma gondii ( T. gondii) has shown anticancer activity in breast cancer mouse models, and exerted beneficial effect on the survival of breast cancer patients, but the mechanism was unclear.

Methods

The effect of tachyzoites of T. gondii (RH and ME49 strains) on human breast cancer cells (MCF-7 and MDA-MB-231 cells) proliferation and migration was assessed using cell growth curve and wound healing assays. Dual RNA-seq was performed for T. gondii-infected and non-infected cells to determine the differentially expressed genes (DEGs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein–Protein Interaction Networks analysis (PPI) were performed to explore the related signaling pathway and hub genes. Hub genes were validated using the Kaplan–Meier plotter database, and Pathogen Host Interaction (PHI-base) database. The results were verified by qRT-PCR.

Results

The tachyzoites of T. gondii decreased the expression of Ki67 and increased the expression of E-cadherin, resulting in suppressing the proliferation and migration of infected human breast cancer cells. The inhibitory effect of T. gondii on breast cancer cells showed a significant dose–response relationship. Compared with the control group, 2321 genes were transcriptionally regulated in MCF-7 cells infected with T. gondii, while 169 genes were transcriptionally regulated in infected MDA-MB-231 cells. Among these genes, 698 genes in infected MCF-7 cells and 67 genes in infected MDA-MB-231 cells were validated by the publicly available database. GO and KEGG analyses suggested that several pathways were involved in anticancer function of T. gondii, such as ribosome, interleukin-17 signaling, coronavirus disease pathway, and breast cancer pathway. BRCA1, MYC and IL-6 were identified as the top three hub genes in infected-breast cancer cells based on the connectivity of PPI analysis. In addition, after interacting with breast cancer cells, the expression of ROP16 and ROP18 in T. gondii increased, while the expression of crt, TgIST, GRA15, GRA24 and MIC13 decreased.

Conclusions

T. gondii transcriptionally regulates several signaling pathways by altering the hub genes such as BRCA1, MYC and IL-6, which can inhibit the breast tumor growth and migration, hinting at a potential therapeutic strategy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-024-03333-1.

Related collections

Most cited references 55

Record: found
Abstract: found
Article: not found

Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Kenneth Livak, Thomas D. Schmittgen (2001)

The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).

0 comments Cited 23525 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

0 comments Cited 23120 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2022)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

0 comments Cited 12729 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Zefang Ren: renzef@mail.sysu.edu.cn

Journal

Journal ID (nlm-ta): Cancer Cell Int

Journal ID (iso-abbrev): Cancer Cell Int

Title: Cancer Cell International

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2867

Publication date (Electronic): 23 April 2024

Publication date PMC-release: 23 April 2024

Publication date Collection: 2024

Volume: 24

Electronic Location Identifier: 144

Affiliations

[1 ]The School of Public Health, Sun Yat-Sen University, ( https://ror.org/0064kty71) 74 Zhongshan 2nd Rd, Guangzhou, 510080 Guangzhou China

[2 ]Public Health Service Center of Bao’an District, Shenzhen, 518102 China

[3 ]Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), ( https://ror.org/03qb7bg95) Shenzhen, 518034 China

[4 ]The Third Affiliated Hospital, Sun Yat-Sen University, ( https://ror.org/0064kty71) Guangzhou, 510630 China

Article

Publisher ID: 3333

DOI: 10.1186/s12935-024-03333-1

PMC ID: 11040860

PubMed ID: 38654350

SO-VID: ee491223-c9d8-4b49-89e5-aceb2518cae1

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 29 December 2023

Date accepted : 18 April 2024

Funding

Funded by: National Natural Science Foundation of China

Award ID: 81973115

Award Recipient : Zefang Ren

Funded by: Science and Technology Planning Project of Guangdong Province, China

Award ID: 2019B030316002

Award Recipient : Zefang Ren

Custom metadata

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: toxoplasma gondii,breast cancer,proliferation,migration,transcriptome

Data availability:

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: toxoplasma gondii, breast cancer, proliferation, migration, transcriptome

Toxoplasma gondii suppresses proliferation and migration of breast cancer cells by regulating their transcriptome

Read this article at

Abstract

Background

Methods

Results

Conclusions

Supplementary Information

Related collections

Karger: Oncology

Most cited references 55

Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Fast gapped-read alignment with Bowtie 2.

Author and article information

Contributors

Journal

Affiliations

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 430

Most referenced authors 1,279