Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Feb 10;10(1):2262.
doi: 10.1038/s41598-020-59057-5.

SETD3 Acts as a Prognostic Marker in Breast Cancer Patients and Modulates the Viability and Invasion of Breast Cancer Cells

Affiliations
Free PMC article

SETD3 Acts as a Prognostic Marker in Breast Cancer Patients and Modulates the Viability and Invasion of Breast Cancer Cells

Nourhan Hassan et al. Sci Rep. .
Free PMC article

Abstract

In several carcinomas, the SET Domain Containing 3, Actin Histidine Methyltransferase (SETD3) is associated with oncogenesis. However, there is little knowledge about the role of SETD3 in the progression and prognosis of breast cancer. In this study, we first analyzed the prognostic value of SETD3 in breast cancer patients using the database of the public Kaplan-Meier plotter. Moreover, in vitro assays were performed to assess the role of SETD3 in the viability and capacity of invasion of human breast cancer cell lines. We observed that the high expression of SETD3 was associated with better relapse-free survival (RFS) of the whole collective of 3,951 patients, of Estrogen Receptor-positive, and of Luminal A-type breast cancer patients. However, in patients lacking expression of estrogen-, progesterone- and HER2-receptor, and those affected by a p53-mutation, SETD3 was associated with poor RFS. In vitro analysis showed that SETD3 siRNA depletion affects the viability of triple-negative cells as well as the cytoskeletal function and capacity of invasion of highly invasive MDA-MB-231 cells. Interestingly, SETD3 regulates the expression of other genes associated with cancer such as β-actin, FOXM1, FBXW7, Fascin, eNOS, and MMP-2. Our study suggests that SETD3 expression can act as a subtype-specific biomarker for breast cancer progression and prognosis.

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
TCGA analysis of SETD3 expression in different types of cancers. Frequency of SETD3 expression in different types of solid tumors. RNA-seq data in 17 cancer types are plotted as median number fragments per kilobase of exon per million reads generated by The Cancer Genome Atlas (TCGA). Points are displayed as outliers if they are above or below 1.5 times the interquartile range. The cancer types are color-coded according to which type of normal organ cancer originates from.
Figure 2
Figure 2
The prognostic value of the expression of SETD3 in patients with breast cancer stratified by hormone receptor status. Kaplan-Meier relapse-free survival curves are plotted based on: (A) all breast cancer patients (n = 3951), (B) Estrogen receptor (ER) positive status, ER+ (n = 3,082) (C) Progesterone receptor negative (PR) status, PR- (n = 549), and (D) triple-negative expression of ER, PR, and Her2 (n = 196). Log-rank p values and hazard ratios (HRs; 95% confidence interval in parentheses) are shown. The corresponding Affymetrix IDs is: 212465_at_SETD3.
Figure 3
Figure 3
The prognostic value of the expression of SETD3 in patients with breast cancer stratified by p53 status. Kaplan-Meier relapse-free survival curves are plotted based on (A) p53 status, p53 mutated (n = 188) and according to the status of p53 and the expression of (B) ER, (C) PR and (D) the intrinsic molecular classification Luminal B. Log-rank p values and hazard ratios (HRs; 95% confidence interval in parentheses) are shown. The corresponding Affymetrix IDs is: 212465_at_SETD3.
Figure 4
Figure 4
Expression of SETD3 in breast cancer cell lines. (A) Relative expression of SETD3 was quantified by qRT-PCR in 7 breast cancer cell lines representative of the luminal (MCF-7 and T47D), Her2-positive (BT474 and SKBR3), and basal (MDA-MB-231, -453 and -468) subtype. Individual experiments were normalized against β-ACTIN and the relative expression was represented by 2-ΔCt. (B,C) The expression of SETD3 was blocked with an siRNA in basal breast cancer cell lines MDA-MB-231 and -468, and Luminal cell lines MCF-7 and T47D. Knockdown of SETD3 was confirmed by B) qRT-PCR and C) western blot. Western blot images are composites of individual blots as indicated by separated boxes. Tubulin signals are derived from the same stripped and reprobed membranes as the corresponding SETD3 signals shown in the upper panels. Full-length blots are shown in the Supplementary File, Supplementary Fig. S1. Data represent the mean ± SEM (standard error of the mean) from 3 independent experiments in triplicates. Bars with asterisks represent comparisons with statistically significant differences (P < 0.05).
Figure 5
Figure 5
The inhibition of SETD3 expression blocks the viability and invasive phenotype of MDA-MB-231 breast cancer cells. (A) MTT assay reveals a significant effect of SETD3 on cell viability in the aggressive basal cell lines MDA-MB-231 and MDA-MB-468. (B) After 48 hours of culture with siRNA to inhibit the expression of SETD3, a Matrigel transwell invasion was performed. MCF-7 cells are poorly invasive luminal cells while MDA-MB-231 cells are highly invasive basal cells. (C) Collagen contraction, and (D) immunofluorescence assays were performed in MDA-MB-231 cells. Upper (B) and left (C) panels show representative images of invasion and collagen contraction respectively, and the  ratio of invasive cells or the percent of contraction collagen area were graphed. Data represent the mean ± SEM from 3 independent experiments in triplicates. Bars or points with asterisks represent comparisons with statistically significant differences (P < 0.05). For immunofluorescence (D) representative images are shown. Actin filaments were stained with phalloidin (red) and nuclei with 4′,6′-diamidino-2-phenylindole (DAPI, blue). White arrows represent the normal cells (left panel) and those that have modified their morphology after the depletion of SETD3 (right panel). Magnification 200×.
Figure 6
Figure 6
SETD3 regulates the expression of different potential effector genes. SETD3 siRNA was transfected into MDA-MB-231 (A), MDA-MB-468 (B), MCF-7 (C) and T47D (D) cells and the expression of ACTB (β-actin), FOXM1, ASMA, Gamma-actin, Fascin, and FBXW7-beta was analyzed. The expression of MMP-2, KLC4, iNOS, and eNOS were analyzed in MCF-7 (E) and MDA-MB-231 (F). Individual experiments were normalized against GAPDH and the fold change was performed using the ∆∆Ct method taking the SETD3 expressed cells as a control. Data represent the mean ± SEM from 3 independent experiments in duplicates. Bars with asterisks represent comparisons with statistically significant differences (P < 0.05).
Figure 7
Figure 7
The network of SETD3, FOXM1, FBXW7, ACTB (β-actin), Fascin, MMP-2, KLC4, iNOS, and eNOS interactors. (A) STRING database output depicting functional and physical interactors of SETD3, FOXM1, FBXW7, ACTB, and Fascin obtained from http://string-db.org/. The analyzed proteins are highlighted in red boxes. (B) GO (gene ontology) analysis of SETD3, FOXM1, FBXW7, ACTB (β-actin), Fascin, MMP-2, KLC4, iNOS, and eNOS. The 10 most significantly (p < 0.05) enriched GO terms in molecular function (yellow), cellular component (orange), and biological process (red) branches are presented. (C) KEGG pathway analysis. All the adjusted statistically significant values of the terms were negative 10-base log-transformed.

Similar articles

See all similar articles

References

    1. WHO. Latest global cancer data: Cancer burden rises to 18.1 million new cases and 9.6 million cancer deaths in 2018. IARC (2018).
    1. Tong CWS, Wu M, Cho WCS, To KKW. Recent Advances in the Treatment of Breast Cancer. Front. Oncol. 2018;8:227–227. doi: 10.3389/fonc.2018.00227. - DOI - PMC - PubMed
    1. Sørlie T, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Nat. Acad. Sci. 2001;98:10869–10874. doi: 10.1073/pnas.191367098. - DOI - PMC - PubMed
    1. Lehmann BD, et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J. Clin. Invest. 2011;121:2750–2767. doi: 10.1172/JCI45014. - DOI - PMC - PubMed
    1. Zardavas D, Irrthum A, Swanton C, Piccart M. Clinical management of breast cancer heterogeneity. Nat. Rev. Clin. Oncol. 2015;12:381–394. doi: 10.1038/nrclinonc.2015.73. - DOI - PubMed
Feedback