The Expression of ZNF268 and Its Role in The Cisplatin-based Chemoresistance of Breast Cancer

Abstract

Objective

Breast cancer is one of the most prevalent cancers in females worldwide and is one of the leading causes of cancer death and disability in women. Multiple therapies have been applied to breast cancer treatment; however, the long-term survival rate remains low. Although cisplatin has been widely utilized for cancer therapy, chemoresistance still influences the outcome.

Methods

After collecting the breast cancer cell line MDA-MB-231 treated with or without cisplatin and sample information from The Cancer Genome Atlas Program (TCGA), we screened out their common parameters and influences on the prognoses of patients' potential targets. Surgical excisional tissue sections of patients with breast cancer who were admitted and treated in the Department of Breast and Thyroid Surgery, Liuzhou People's Hospital from 2017 to 2020 was collected and follow up. After a series of assays combined with clinical information, we tested the reliability of the target.

Results

We found that a high expression level of ZNF268 in breast cancer cell lines significantly enhances the sensitivity to cisplatin, contrary to the effects of low expression. Furthermore, a significantly worse prognosis was observed in patients with a high expression of ZNF268 after cisplatin chemotherapy.

Conclusion

The expression level of ZNF268 in breast cancer patients after cisplatin chemotherapy may become a potential target to predict the chemoresistance of patients to cisplatin. This study provides a novel idea for improving breast cancer treatment and survival rates.

1. Introduction

Breast cancer is one of the most prevalent cancers in females worldwide and is one of the leading causes of cancer death and disability in women [1]. Although multiple treatments have been utilized for breast cancer therapy, including surgery and chemotherapy [2], the long-term survival rate of patients remains low. Cisplatin has an effective killing ability on tumour cells [3], but chemoresistance emerges in most situations [4]. Cisplatin chemoresistance increasingly occurs in patients, thus leading to undesirable chemotherapy outcomes [5]. Knowledge concerning the mechanism of cisplatin chemoresistance is the basis of improving the survival rates of patients [6].

The morbidity tendency of breast cancer has a significant discrepancy in different countries. The age-standardized incidence range in the United States exhibits a downwards tendency compared to the increasing rates in China and Korea [7]. Due to improvements in early diagnosis and treatment ability, the five-year survival rate of breast cancer in the United States increased from 79% between 1984 and 1986 to 91% between 2008 and 2014 [8]. Currently, the provision of personalized therapy has become the future of breast cancer treatment [9]. Moreover, predictive biomarkers that influence the treatment of breast cancer and that provide an early diagnosis are needed; therefore, personalized treatment can be formulated for each patient [10]. Furthermore, novel biomarkers of breast cancer therapy should be analyzed, and stratified markers that predict individual patient responses to chemotherapy should be identified, thereby improving treatment outcomes [11].

After RNA-seq analysis of breast cancer cell lines, the detection of the published database, and a combination of clinical information of breast cancer, we propose that the expression level of ZNF268 in breast cancer patients after cisplatin chemotherapy can influence the sensitivity of cisplatin. Herein, ZNF268 may be a potential biomarker of cisplatin chemoresistance in breast cancer and may represent a novel mechanism to improve the cisplatin condition of breast cancer.

2. Materials and methods

2.1. Cell culture

The breast cancer cell lines MDA-MB-231 and MDA-MB-468 were purchased from the American Type Culture Collection (ATCC). Cells were cultured in DMEM+10% FBS in a humidified incubator containing 5% CO₂ at 37 °C. All of the cell lines were confirmed by using short tandem repeat spectrometry without mycoplasma contamination.

2.2. Measurement of bioinformatics data

By using 15,847 RNA-seq probes, we detected 14,088 gene sequences from MDA-MB-231 cell lines treated with or without cisplatin. Group set of TCGA-BRCA, total of 1496 RNA-seq data from 1178 samples, including 112 normal and 1066 tumour samples, were downloaded from The Cancer Genome Atlas Program (TCGA) (https://cibersortx.stanford.edu/). We identified the significant expression of genes as |log2FC| ≥ 2 and P < 0.05 by using the “edgeR” package [[12], [13], [14]]. We used TIMER2.0 database (TIMER2.0 (cistrome.org)) [15]which enable users to search, filter and analysis results generated from TCGA data to explore relevant genes behavior in cancers [16,17].

2.3. Data selection

We obtained the interaction to identify significant differentially expressed genes in MDA-MB-231 cell lines and TCGA data groups. Subsequently, the Pearson correlation test was performed for the selected genes by using the “Corrplot” package (GitHub - taiyun/corrplot: A visual exploratory tool on correlation matrix).

2.4. Knockdown of the target gene via siRNA

Cell lines MDA-MB-231 and MDA-MB-468 were implanted in 6-well plates. After 24 h, small interfering RNAs (siRNAs) were transiently transfected into cells. The siRNAs used to target the genes were synthesized by IGE Biotechnology (Guangzhou, China). Transfection was performed with Lipofectamine 3000 reagent (Invitrogen, USA) according to the manufacturer's protocol. The siRNA sequences are shown in Table 1.

Table 1.

The siRNA sequences.

Gene	Sense (5′-3′)	Antisense (5′-3′)
ZNF268 Si1#	CGGGAAAUCCUUUAGUUUCAATT	UUGAAACUAAAGGAUUUCCCGTT
ZNF268 Si2#	CCAGCUUGUUUCACACCAGAATT	UUCUGGUGUGAAACAAGCUGGTT

2.5. Building the overexpression of cells

The DNA sequence of the cDNA of the target gene was provided by cell lines MDA-MB-231 and MDA-MB-468. By designing upstream and downstream specific amplification primers (including the enzyme restriction site design), the coding sequences of the target gene was obtained by using PCR amplification and cloned into the vector pCDH-2x-Flag-Puro by using BamH1 and NotI restriction enzymes. The overexpression plasmid was then constructed. For stable expression, lentiviral plasmids harbouring the desired gene were first transfected into 293T cells together with the packaging plasmids pSPAX2 and pMD2. G at a ratio of 5:3:2. HEK293 cells were plated into a 10-cm plate and cultured as previously described. After reaching 80% confluence, the cells were transfected with 6 μg of psPAX2, 3 μg of pMD2. G, and 10 μg of transfer vector by using Lipofectamine 8000 reagent (Beyotime Biotechnology, China). Forty-eight hours after transfection, the supernatants were collected and used to infect MDA-MB-231 and MDA-MB-468 cells for another 48 h. The puromycin-tolerant MDA-MB-231 and MDA-MB-468 cells, which are pooled clones, were selected.

2.6. mRNA expression analysis

After 24 h of transfection, cells were collected via trypsinization. RNA was extracted by using RNA extraction kit (EZBioscience, USA) and reverse transcribed to cDNA via a reverse transcription kit (Vazyme, China) following the manufacturer's protocol. One microlitre of cDNA and primers (Table 2) were mixed with 2xChamQ Universal SYBR qPCR Master Mix in 10 reaction volumes. Relative mRNA expression was detected by using a LightCycler 480 II Real-time PCR instrument (Roche, Swiss).

Table 2.

The primer sequences.

Gene	Forward	Reverse
ZNF268	TTGTGGATTTTACCTGGGAGGA	TGCACCATACACAGCTCTTCT
GAPDH	GAGTCAACGGATTTGGTCGT	GACAAGCTTCCCGTTCTCAG

2.7. Cell proliferation assay

After 48 h of transfection, cells were collected, and 2 × 10³ cells/well were plated into 96-well plates. Cell proliferation was determined by using the Cell Counting Kit-8 (Dojindo, Kyushu, Japan). After 24 h, 48 h, 72 h, 96 h, and 120 h, the medium of each well was removed, and a mixture of 10 μl CCK-8 and 90 μl of 10% FBS DMED was added. The plates were incubated for an additional 30 min, and the absorbance at 450 nm was measured by using a microplate reader (Multiskan MK3; Thermo Electric, Shanghai, China).

2.8. Cytotoxicity assay

After 48 h of transfection, cells were collected, and 6 × 10³ cells/well were plated into 96-well plates. The next day, different concentrations of cisplatin were added into the wells with equal volumes and then incubated for 24 h. The medium of each well was removed, and a mixture of 10 μl CCK-8 and 90 μl of 10% FBS DMED was added. The plates were incubated for an additional 30 min, and the absorbance at 450 nm was measured by using a microplate reader.

2.9. Western blotting

After 48 h of transfection, cells were extracted with RIPA (Strong) containing protease inhibitor (#CW2200S, CWBIO, China) and centrifuged at 4 °C at 12,000 rpm for 30 min after lysis on ice for 30 min. The protein was quantified by using a BCA kit (#CW0014S, CWBIO, China) and mixed and diluted by using SDS‒PAGE loading buffer (#CW0027S, CWBIO, China). The protein was denatured by reaction at 95 °C for 5 min.

After electric transfer (85 V, 1 h), the protein was transferred to a PVDF membrane (#P0021S, Beyotime, China) (300 mA, 2 h). The PVDF membrane was incubated in TBST (TRIS-buffered saline) containing 5% skim milk and 0.1% Tween-20 for 1 h. Primary antibody (ZNF268, # NBP2-94146, Biotechne, USA) and GAPDH (#60004-1-Ig, Proteintech, USA) were incubated at 4 °C for 18 h. After TBST cleaning, the membranes were incubated with rabbit secondary antibody (#sc-2004, Santa Cruz, USA) and mouse secondary antibody (#sc-2005, Santa Cruz Biotechnology, USA) at room temperature for 1 h. Subsequently, chemical exposure was performed, and photographs were taken.

2.10. Plate colony formation assay

Cells were cultured for 24 h in a constant temperature incubator at 37 °C and 5% CO₂ saturated humidity in a six-well plate at a density of 2000/well. The cells were treated with cisplatin (5 μM/ml) and cultured in humidified medium containing 5% carbon dioxide at 37 °C for 24 h. The next day, the culture medium containing cisplatin was removed, and the fresh complete medium was replaced. The culture was continued for 14 days. When the clonal particles were visible to the naked eye, the medium was removed; subsequently, the cells were immobilized with 4% paraformaldehyde, stained with 0.1% crystal violet, and photographed with AID vSpot Spectrum (Germany). Finally, the number of cell colonies was detected.

2.11. Clinical samples and follow-up data collection

Fifty breast cancer patients were admitted and treated in the Department of Breast and Thyroid Surgery, Liuzhou People's Hospital from 2017 to 2020. All patients underwent cisplatin chemotherapy treatment and post-chemotherapy surgery. Samples were collected by biopsy examination before chemotherapy, after chemotherapy, and surgical excision. Frozen sections were used to confirm that the surgical boundary was expanded to the normal range during the surgery. The pathological diagnosis was determined by the pathology department of Liuzhou People's Hospital. Clinical staging was according to the eighth edition of TNM staging for breast cancer as specified by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). Patient follow-up information was collected through telephone contacts and follow-up visits.

2.12. Immunohistochemistry and evaluation

Immunohistochemical staining was performed according to standard protocols [18]. Briefly, antigen retrieval was conducted using Tris-EDTA buffer (#C1038, Solarbio) in a microwave oven for 15 min after paraffinization. sections were Blocked sequentially with 3% hydrogen peroxide and normal serum, sections were then incubated with primary antibodies (ZNF268, # NBP2-13562, Biotechne, USA) at 4 °C overnight. The tissues were incubated with a biotinylated secondary antibody and conjugated with a streptavidin-HRP complex (ready-to-use SP kit; Zhongshan Co., China) in the second day. Sections were visualized with 3-3-diaminobenzidine, counterstained with hematoxylin and mounted.

The number of positive cells and the intensity of the staining results were assessed by two pathologists. Positive stains were evaluated using a semiquantitative scoring system. The percentage of positive cells was scored as follows: 0 (no staining), 1 (<1/3 staining), 2 (1/3 to 2/3 staining), and 3 (>2/3 staining). Staining intensity was identified following scored: 0 (negative), 1 (weak positive), 2 (medium positive), and 3 (strong positive). Low expression was defined as the score of 0–2, while a score >2 was defined as high expression.

2.13. Statistical analysis

The statistical analyses were performed by using R software (V 4.1.2). The Kaplan‒Meier method was used to analyse the survival rates of the clinical patients, and the log-rank method was used to test the significance of the differences between survival curves. Multivariate COX regression was used for the multivariate survival correlation analysis. Multivariate analysis of variance, Fisher's exact four-cell table test, and the Pearson's correlation test were used for the correlation analysis.

3. Results

3.1. Identification of common and significantly expressed genes

For the search of highly frequent and significant expression genes, we decided to filter data sequences by using |log2FC|≥2 and P < 0.05 (Fig. 1A–B). The results of the two groups were intersected, and we observed that 24 genes were significantly expressed in both groups: FRAS1, GJD3, TGM2, ACSM3, TFCP2L1, ZNF254, ZFPM1, CEP83, BNIPL, TUBB2B, PCSK4, ZNF268, CCDC33, LACC1, DHDH, ZNF567, DCAKD, CATSPER2, AKR1C3, SLC2A9, TRPS1, ARHGAP40, ESPN, and RGPD6 (Fig. 1C). However, according to the TCGA clinical information, the heatmap showed that some genes had various expression levels in different patients (Fig. 1D). For example, there was high expression of TGM2 in some patients but low expression in other patients. It is possible that these genes are related to each other.

Fig. 1.

Difference analysis was conducted based on cell line sequencing results and TCGA database data:

A: Volcano map after difference analysis of MDA-MB-231 cell line data;

B: Volcano map after difference analysis of TCGA clinical sample data;

C: MDA-MB-231 cell line data had 24 identical differentially expressed genes in TCGA data.

D: TCGA clinical data heat map.

E: Correlation heat map.

F：Relative expression of ZNF268 in variety of cancers. (*: p-value <0.05; **: p-value <0.01; ***: p-value <0.001).

3.2. Complex correlation in genes

The correlation analysis via the “corrplot” package showed that there was a very complex correlation with these genes (Fig. 1E). For example, the correlation heatmap showed that TRPS1, CEP83, ZNF268, ZNF254, ZNF567, LACC1, and RGPD6 were correlated with each other. Additionally, SLC2A9 had a significant correlation with CEP823, ZNF268, ZNF254, ZNF567, and LACC1. The mechanism of cisplatin chemosensitivity in breast cancer is very complex. Therefore, researchers must conduct more in-depth analyses to determine the potential role of cisplatin chemoresistance in breast cancer.

3.3. ZNF268 may be a potential target of cisplatin resistance in breast cancer

For exploring the mechanism of chemoresistance of breast cancer, we downloaded 1496 breast cancer genes from TCGA and correlated this information with 24 genes that we previously analyzed. Multivariate Cox regression analysis demonstrated that the expression levels of ZNF268, LACC1, and ZNF567 had the most significant correlation with the prognosis of breast cancer patients (P < 0.001) (Table 3). One of the reasons for this result is that there is less research on ZNF268 in breast cancer, and the mechanism of cisplatin chemoresistance has not yet been reported. Meanwhile, The result of analysis by the TIMER2.0 database shows that, not only in breast cancer, the expression of ZNF268 in tumor specimens have significant different compared to normal specimens in multiple kinds of cancer (BRCA, CHOL, GBM, HNSC, KICH, KIRC, KIRP, LUSC, PRAD, SKCM, STAD, THCA, and UCEC), suggesting that ZNF268 has many potential mechanisms that play a crucial role in cancer(Fig. 1F). Herein, we decided to explore the cisplatin chemoresistance of ZNF268 in breast cancer.

Table 3.

Result of multivariate Cox regression.

	coef	exp(coef)	se(coef)	z	Pr(>|z|)
BNIPL	0.0019576	0.0019576	0.0019576	2.099	0.03584 *
ZNF268	−0.0045642	0.9954462	0.9954462	−2.860	0.00424 **
LACC1	0.0047143	1.0047254	0.0016319	2.889	0.00387 **
ZNF567	−0.0065864	0.9934353	0.0023918	−2.754	0.00589 **
SLC2A9	0.0034516	1.0034575	0.0018740	1.842	0.06550.
ESPN	−0.0019849	0.9980171	0.0009851	−2.015	0.04391 *
FRAS1	0.0019450	1.0019469	0.0011534	1.686	0.09173.
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1

	exp(coef)	exp(-coef)	lower .95	upper .95
BNIPL	1.0020	0.9980	1.0001	1.0038
ZNF268	0.9954	1.0046	0.9923	0.9986
LACC1	1.0047	0.9953	1.0015	1.0079
ZNF567	0.9934	1.0066	0.9888	0.9981
SLC2A9	1.0035	0.9966	0.9998	1.0072
ESPN	0.9980	1.0020	0.9961	0.9999
FRAS1	1.0019	0.9981	0.9997	1.0042
Concordance = 0.757 (se = 0.028)
Likelihood ratio test = 33.65 on 7 df, p = 2e-05
Wald test = 25.57 on 7 df, p = 6e-04
Score (logrank) test = 26.07 on 7 df, p = 5e-04

3.4. Low expression of ZNF268 in breast cancer cell lines enhances sensitivity to cisplatin

The transfection of siRNA into the breast cancer cell lines MDA-MB-231 and MDA-MB-468, as well as the RT‒qPCR and west blotting data, demonstrated that the expression level of ZNF268 was downregulated (Fig. 2A–B). Thus, we were able to examine the influence of ZNF268 expression on the sensitivity of breast cancer cells.

Fig. 2.

siRNA transfection reduces the expression of ZNF268 in breast cancer cells(*: p-value <0.05; **: p-value <0.01; ***: p-value <0.001):

A: qPCR confirmed that siRNA transfection reduced the expression level of ZNF268.

B: Western Blotting experiments showed that the expression level of ZNF268 decreased.

C: Compared with the control group, the IC50 value of cisplatin in MDA-MB-231 cell lines and MDA-MB-468 cell lines was significantly decreased after the expression level of ZNF268 was reduced.

D: After cisplatin treatment, the proliferation levels of MDA-MB-231 and MDA-MB-468 cell lines with low expression of ZNF268 were decreased compared with the control group.

E: After siRNA transfection, the cloning ability of MDA-MB-231 cell lines and MDA-MB-468 cell lines decreased with the decrease of the expression level of ZNF268.

First, we transfected siRNA into MDA-MB-231 and MDA-MB-468 cell lines. After treatment with cisplatin, we found that the downregulation of ZNF268 decreased the IC50 in breast cancer cells (regardless of MDA-MB-231 or MDA-MB-468). This result demonstrated that breast cancer cells can be more sensitive to cisplatin when ZNF268 is expressed at low levels (Fig. 2C). Compared with the control group, a lower proliferation tendency was observed in both cell lines when they were transfected with siRNA (Fig. 2D). Moreover, the number of clones formed by cells transfected with siRNA after treatment with cisplatin was much lower than that in the control group (Fig. 2E).

3.5. Low cisplatin sensitivity in breast cancer cells with high ZNF268 expression

Next, we transfected plasmids into MDA-MB-231 and MDA-MB-468 cell lines to generate breast cancer cells with high ZNF268 expression (Fig. 3A–B). After being treated with cisplatin, cells overexpressing ZNF268 exhibited significantly low sensitivity to the drug (Fig. 3 C). Furthermore, the high expression of ZNF268 prompted the proliferation of breast cancer cells (Fig. 3 D). The same phenomenon was observed in the plate colony formation assay. Additionally, the number of clone formations was significantly increased in ZNF268 overexpression cells compared to the control group (Fig. 3 E). These assays demonstrated that the expression of ZNF268 can influence the sensitivity of breast cancer cells to cisplatin.

Fig. 3.

ZNF268 was overexpressed in breast cancer cells by transfection of plasmids(*: p-value <0.05; **: p-value <0.01; ***: p-value <0.001):

A: qPCR confirmed that parenchymal plasmid transfection increased the expression level of ZNF268.

B: Western Blotting showed that ZNF268 was overexpressed in the cell line.

C: Compared with the control group, the IC50 value of cisplatin in MDA-MB-231 and MDA-MB-468 cell lines was significantly increased after overexpression of ZNF268.

D: After cisplatin treatment, the proliferation level of MDA-MB-231 and MDA-MB-468 cell lines overexpressing ZNF268 was increased compared with the control group.

E: When ZNF268 was overexpressed, the clonal formation ability of breast cancer cells was significantly enhanced.

3.6. The expression level of ZNF268 influences cisplatin chemosensitivity in breast cancer patients

Information on fifty breast cancer patients who were admitted and treated in the Department of Breast and Thyroid Surgery, Liuzhou People's Hospital from 2017 to 2020 was collected. All of the patients were treated with cisplatin chemotherapy and subsequently underwent surgical resection. Data on the biopsy of the tissue before and after chemotherapy and the resection of tissue during surgery were obtained. All of the data were examined by using immunochemistry. The results were evaluated by two pathologists. Further histological detection of ZNF268 was performed in the aforementioned patients (Fig. 4A). Immunochemistry results correlated with the clinical follow-up information. We discovered that the expression of ZNF268 in patients changed after cisplatin chemotherapy (Table 4). Although the expression level of ZNF268 had no significant correlation with the T stage, the tumor diameter change was significantly different. The Miller/Payne grading system was an independent predictor of overall patient survival, which assesses the histological response to primary chemotherapy to predict overall survival and disease-free interval in patients with large and locally advanced breast cancers treated with such therapy [19]. This system divides histological results into 5 categories. Grade 1: No change or some alteration to individual malignant cells but no reduction in overall cellularity. Grade 2: A minor loss of tumour cells but overall cellularity still high; up to 30% loss. Grade 3: Between an estimated 30% and 90% reduction in tumour cells. Grade 4: A marked disappearance of tumour cells such that only small clusters or widely dispersed individual cells remain; more than 90% loss of tumour cells. Grade 5: No malignant cells identifiable in sections from the site of the tumour; only vascular fibroelastotic stroma remains often containing macrophages. The M&P analysis showed that the class of M&P had a significant difference between the high expression and the low expression of ZNF268 (both before or after chemotherapy). Moreover, class 1 and class 2 in low expression were decreased after chemotherapy but increased in high expression (Table 5). The results of the statistical analysis showed that there was no significant prognosis difference between high expression and low expression of ZNF268 before cisplatin chemotherapy (P = 0.1441) (Fig. 4B). However, patients with high ZNF268 expression had a worse prognosis than those patients with low ZNF268 expression after cisplatin treatment (P = 0.0008) (Fig. 4C).

Fig. 4.

Clinical tissue samples and follow-up information:

A: Representative immunohistochemical results of clinical tissues before and after chemotherapy.

B: K-M analysis showed that the expression level of ZNF268 before chemotherapy had no significant difference in the prognosis of patients (P = 0.1441).

C: K-M analysis demonstrated significant adverse prognosis in patients with high expression of ZNF268 after chemotherapy (P = 0.0008);

D: No matter the expression level before chemotherapy, the expression level of ZNF268 after chemotherapy can significantly affect the prognosis of patients (P = 0.0098).

Table 4.

Fisher's exact test of ZNF268 expression.

	Before chemotherapy	After chmotherapy	P value
+	23	34	0.0428
-	27	16

Table 5.

Clinical correlation analysis of ZNF268 expression.

	Expression Before Chemotherapy			Expression After Chemotherapy
ZNF268	+	–	P value	+	–	P value
Age	49.84 ± 9.27	49.83 ± 9.35	0.0478	49.84 ± 9.27	49.58 ± 9.57	0.9033
diameter	42.32 ± 18.26		0.0052	25.33 ± 14.86		0.0356
		42.69 ± 28.50	0.0545		25.72 ± 15.03	0.0607
T stage
1	3	1		3	1
2	15	14		22	7
3	3	7		2	8
4	2	5	0.0762	5	2	0.1816
M＆P 1	7	2		9	0
2	6	3		8	1
3	7	11		8	10
4	3	6		5	4
5	0	5	0.0027	2	3	0.0031

Interestingly, some patients exhibited high ZNF268 expression from biopsy before cisplatin therapy, but the surgical resection showed that ZNF268 expression was low after surgery. In contrast, several patients initially had low expression but then exhibited increased expression after cisplatin chemotherapy. The statistical analysis demonstrated that patients with high ZNF268 expression exhibited a worse prognosis than those patients with low ZNF268 expression (P = 0.0098) (Fig. 4D). A series of analyses demonstrated that the expression of ZNF268 in patients after cisplatin chemotherapy plays a very important role in prognoses.

4. Discussion

As an important chemotherapy pharmaceutical regimen, the problem of chemoresistance to cisplatin has significantly influenced the prognosis of breast cancer. It has a very complex mechanism in cisplatin chemoresistance. For example, the overexpression of Bcl-2 and Bcl-xL has a significant correlation with cisplatin chemoresistance [20]. Lin et al. theorized that STC1 can elicit metastasis, lipid metabolism, and cisplatin resistance in cancer cells [21]. In the past, cisplatin was combined with multiple pharmaceutical regimens in cancer treatment to improve the outcome. For instance, gemcitabine and cisplatin plus trastuzumab are used in metastatic breast cancer with HER2 overexpression [22], and high-dose melphalan and cisplatin with peripheral blood progenitor cells support treatment in breast cancer and other malignant tumours [23]. However, multiple drug treatments often increase the damage to the patient. Thus, it is advisable to predict the biomarkers for patients and to provide a personalized therapy plan, thereby improving the outcomes of treatments [24]. Herein, we propose that ZNF268 can become a potential biomarker to predict cisplatin chemoresistance in patients with breast cancer.

As a typical Krüppel-associated box/C2H2 zinc finger protein, ZNF268 has only been observed in higher mammals and not in lower mammals, such as mice [25]. ZNF268 can be regulated by multiple factors. Zeng et al. theorized that GATA-1 is tightly connected with the ZNF268 promoter, thereby regulating its expression. The GATA-1 downregulation of ZNF268 plays an important role in promoting growth and in inhibiting the differentiation of K562 red leukaemia cells [26]. Moreover, Shao et al. discovered that the KRAB domain in the fourth and fifth exon is the key rule in cell differentiation, proliferation, apoptosis, and tumour transformation in ZNF268 [27] and inhibits transcriptional activity [28]. ZNF268 lacking the KRAB domain can localize in the cytoplasm via the spliced form, which plays an important role in the NF-kappaB signal pathway induced by TNF-α interacting with the IKK complex [29]. ZNF268 can be separated into the following two isoforms: ZNF268a and ZNF268b2. ZNF268 is a transcription inhibitor, and ZNF268b is a candidate linkage for IKK to the NF-kB signalling pathway. Compared to normal cervical tissue, cervical carcinoma tissue exhibits high ZNF268a expression but low ZNF268b2 expression. Cervical carcinoma cells can improve their proliferation and cell viability, thus causing ZNF268b2 to lack the KRAB domain [30]. ZNF268b2 (with 24 zinc fingers) straddles the nucleolus and nucleolus, whereas ZNF268a requires nuclear localization via a KRAB located in the nucleolus [31]. Wang et al. found that in the N-terminus of the KRAB domain, there is a transcriptional inhibitor known as KRAB-ZEPs (KRAB-containing zinc finger proteins). High conservation of the A-box in KRAB is the key role of the inhibitor, but the B-box is an auxiliary function [32]. Our research demonstrated that the expression level of ZNF268 is correlated with cell cisplatin sensitivity in breast cancer. The high expression of ZNF268 significantly increased the resistance of cancer cells to cisplatin cytotoxicity, and decreased ZNF268 levels can make breast cancer cells more sensitive to cisplatin. However, the exact mechanism of ZNF268 regulation in breast cancer cisplatin chemoresistance remains poorly understood, encouraging us to continue our study.

5. Conclusion

Combined with clinical information, we not only found that the high expression of ZNF268 correlates with worse prognosis in breast cancer patients but also discovered that the prognosis is related to the high expression of ZNF268 in patients after cisplatin chemotherapy, which is independent of the expression level before chemotherapy. Thus, ZNF268 can be seen as a potential biomarker that predicts cisplatin chemoresistance in breast cancer patients. The expression level of ZNF268 after cisplatin treatment can be consulted for cisplatin chemoresistance.

Author contributions statement

Yaqiang Zhuang and Xingsheng Qiu conceived the ideas, designed the study and directed the work. Weilu Wu, Shucong Yao, Jiapeng Huang, Jialin Qing and Qingmei Shi performed the experiments. Jianping Huang, and Shucong Yao analyzed the Bioinformatics results. Shucong Yao wrote the manuscript. All of the authors contributed to the discussion and editing of the manuscript.

Additional information

No additional information is available for this paper.

Ethics approval and consent to participate

This research was conducted in accordance with international guidelines and the ethical standards outlined in the Declaration of Helsinki. This study was approved by the Liuzhou People's Hospital Institutional Review Board. Written informed consent were obtained from all the patients.

Patient consent for publication

Not applicable.

Availability of data and materials

The datasets used for the current study are available from the corresponding author on reasonable request. All data generated or analyzed during this study are included in this published article.

Funding

This study received no external fund from any institute or authority.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.