Introduction

According to estimates from the World Health Organization (WHO) in 2020, cancer ranks as the second leading cause of death in 112 countries and the primary cause of mortality before the age of 70 1. Given the increasing cancer mortality rate, early detection and treatment serve as the most effective means of preventing cancer and reducing mortality. Consequently, the identification of the precise underlying biological mechanisms of cancer and the development of novel cancer biomarkers and therapeutic strategies remain highly challenging endeavors.

Breast cancer, one of the most often diagnosed diseases in women, accounts for 7%–10% of all malignant tumors2. Although an increasing number of patients are being treated at an early stage with a combination of mainly surgical interventions. Still, the existing treatments remain insufficient in mitigating the life-threatening consequences of breast cancer for individuals with advanced and recurrent conditions.3. A more profound understanding of the development of novel prognostic markers is necessary for the enhancement of prognosis.

Mitochondria play an important multifunctional role in the progression of malignant tumors. It has been shown that mutations in enzymes involved in the mitochondrial tricarboxylic acid cycle and abnormalities in the mitochondrial electron transport chain can induce cancer4. In addition, some well-known tumor suppressors and oncogenes, such as p535,6, c-Myc7,8, and HIF9,10 can regulate mitochondrial function directly or indirectly, leading to mitochondrial dysfunction, which in turn affects tumorigenesis. Hence, it is imperative to enhance our comprehension of the impact exerted by mitochondrial DNA mutations and abnormalities in mitochondrial-associated proteins on the development and progression of cancer.

As a member of the family of genes encoding mitochondrial membrane gap proteins, TIMM8A (Translocase of Inner Mitochondrial Membrane 8A) plays a prominent role in the transport of mitochondrial membrane material. It has been shown that loss of TIMM8A leads to abnormal mitochondrial morphology 11,12. In neuroblastoma, TIMM8A interacts with COX17 in the assembly of Complex IV, which in turn affects mitochondrial metabolism and redox homeostasis. Moreover, TIMM8A loss sensitizes cells to Bcl-2 regulation and cystathione-dependent apoptosis 13. Recent research has shown that TIMM8A is associated with immune infiltration and prognosis in endometrial cancer14,15,16. The precise role and underlying molecular mechanism of TIMM8A in the pathophysiology of cancer remain poorly understood, and it remains uncertain whether TIMM8A could be utilized as a biomarker or therapeutic target for cancer. This study aimed to elucidate the expression profile of TIMM8A in various types of cancer and its association with prognosis. Specifically, we concentrated on breast cancer, the cancer type exhibiting the strongest correlation between TIMM8A levels and prognosis. The investigation focused on exploring the impact of TIMM8A on the malignant behavior of breast cancer and investigating its upstream and downstream molecular mechanisms.

Methods

Data source

Transcriptomic RNA-seq data and clinical information were obtained from TCGA databases (https://portal.gdc.cancer.gov/) and UCSC XENA (https://xenabrowser.net/datapages/) for tumor tissue, paracancerous tissue, and normal tissue for each cancer species. The median of expression was used as the cut-off point to split the samples into TIMM8A high-expression and low-expression groups. Cell line information was collected from the Human Protein Atlas (HPA) and the Cancer Cell Line Encyclopedia (CCLE).

Bioinformatics analysis

TIMM8A mRNA expression levels were analyzed using R software (version 4.0.5) and visualized with the “ggplot2” R package. Univariate survival analysis determined the correlation of TIMM8A expression with patient survival, including OS (overall survival), PFS (progression-free survival), and DSS (disease-free survival). The diagnostic value of TIMM8A was assessed by plotting ROC curves. Visualization was done with the “ggplot2” R package. TIMM8A-related genes were obtained through the STRING database (https://cn.string-db.org/) and The GeneMANIA prediction server. Subsequently, the “org.Hs.eg.db” R package was applied for ID conversion and enrichment analysis was performed with the “clusterProfiler” R package17. The “clusterProfiler” R package was also used for GSEA (gene set enrichment analysis) analysis of TIMM8A-related genes for HALLMARK terms and REACTOME pathways18. Visualization was done with the " pheatmap " R package. TISCH (http://tisch.comp-genomics.org/ ) 19 and CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/home.jsp )20 were used for the acquisition and profiling of single-cell data. Several target gene prediction databases were used to predict the miRNAs that TIMM8A will bind upstream. Both starBase (http://starbase.sysu.edu.cn/) and TargetScan (http://www.targetscan.org/vert_72/) predicted miRNAs that specifically target TIMM8A.

Cell culture and transfection

Breast cancer cells and HEK-293 T cells were cultured in Dulbecco’s modified eagle medium (DMEM) (Yeasen, China) containing 10% fetal bovine serum (FBS) (ExCell, China), 100 mg/ml streptomycin, and 100 U/ml penicillin. MCF10A cell-specific media (Pricella, China) was used to culture MCF10A cells. Cells were cultured and maintained in a 37 °C incubator with 5% CO2. TIMM8A-siRNA and miR-10b-5p-mimic were purchased from GenePharma (China). The jetPRIME™ reagent (Polyplus-Transfection, France) was used for siRNA, mimic, and plasmid vector transfection following the manufacturer’s recommendations. Transfection of siRNA was performed when cells were fused to 30%. Take a 6-well plate as an example, and add 20 μM siRNA and 4μL reagent to each well. Cells need to be fused to 50% when transfecting plasmids. DNA:jetPRIME = 1:2 (W/V).

Quantitative RT-PCR

The cells’ total RNA was extracted using Trizol Reagent (Genstar, Chian). The Hifair® III 1st Strand cDNA Synthesis SuperMix for qPCR (Yeasen, China) and the Hifair® miRNA 1st Strand cDNA Synthesis Kit (Yeasen, China) were used for generating the cDNA. According to the manufacturer’s recommendations, StepOne Plus (Applied Biosystems, USA) was used for qRT-PCR using Hieff® qPCR SYBR Green Master Mix (Yeasen, China). U-6 and -actin were utilized as the endogenous controls. The sequences of primers used are listed in Table 1.

Table 1 All primer sequences and oligonucleotide sequences.
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Cell viability assay

Using the CCK-8 kit (Yeasen, China) in accordance with the manufacturer’s recommendations, cell viability was assessed. Separately suspended in 100μl of media, 7,000 MCF7 cells and 3,000 MDA-MB-231 cells were seeded in triplicate in 96-well plates and cultured at 37 °C in an incubator with 5% CO2 overnight. Following that, siRNA was transfected. At 24, 48, and 72 h after transfection, the original medium was changed to medium containing 10% CCK8, followed by a 30-min incubation at 37 °C. The absorbance at 450 nm was then measured by a microplate reader.

Colony formation assay

Following a 24-h transfection, MCF-7 and MDA-MB-231 cells (500/1,000/2,000 cells/well) were seeded onto 6-well plates and grown in DMEM at 37 °C for 14 days. During this period, change the medium every 3 days. The medium was discarded after 14 days, rinsed with PBS, and allowed to air dry. To fix the cells for 30 min at room temperature, 500ul of 4% paraformaldehyde was added to each well. PBS was then washed. Subsequently, 300 μl of 0.1% crystalline violet was added to each well and stained at room temperature for 30 min, then rinsed well with PBS and air dried. Finally, the staining results were photographed and the number of clones formed was calculated using ImageJ software. Clonal formation rate = effective clones/plating cell numbers × 100%.

Cell cycle analysis

AnnexCell Cycle Kit (Biosharp, China) was used for used for cell cycle analysis. After starving the cells, which means that the serum concentration in the medium was reduced to 1% for 8 h, cells were gathered, washed with PBS, and fixed overnight in pre-chilled 70% ethanol at 4 °C following a 24-h transfection. The cells were washed again with PBS and resuspended in 0.5 mL of staining buffer with 25 μl of PI staining solution and 10 μl of RNase A. Incubation was carried out at 37 °C for 30 min protected from light. Flow cytometry was used to determine the proportion of cell cycle phases using Cytflex (Beckman, USA). The result was analyzed by Modfit LT 5.0. Coefficients of variation less than 10% and G2/G1 between 1.8 and 2.0 were considered valid data.

Cell apoptosis assay

Annexin V-FITC/PI Apoptosis Assay Kit (Yeasen, China) was used to detect the onset of apoptosis. Briefly, 24 h after siRNA transfection, MCF-7, and MDA-MB-231 cells were collected and washed twice in PBS at 4 °C. Cells (1 × 106) were counted and resuspended in 100 µL binding Buffer for apoptosis assessments. After that, 10 mL of propidium iodide (PI) and 5 mL of annexin V-FITC were added, and the mixture was incubated at room temperature for 15 min in the dark. Flow cytometry was used to determine the proportion of apoptotic cells using Cytflex (Beckman, USA). The result was analyzed by FlowJo v10.9.0. The gating criterion was set by setting the cross-gate according to the results of single stained tubes: Annexin V single stained tubes were used to differentiate between the FITC negative and positive groups, and PI single stained tubes were used to differentiate between the PE negative and positive groups. The set crossgate should be applied to all tubes. Percentage of apoptotic cells (%) = Percentage of cells in the right upper quadrant (%) + Percentage of cells in the right lower quadrant (%).

Scratch wound-healing migration assay

After performing siRNA transfection, when the cells reached 80–90% confluence in the culture plate wells, three lines were scraped out of the cells in each culture well with a sterile plastic pipette tip and the medium was replaced with DMEM containing 1% FBS. The cells were washed twice in warm PBS medium to remove cellular debris. Using an Eclipse TS100 microscope (Nikon, Japan), photographs of three different fields of view were taken during the doubling time of the cell line i.e., 0, 10, 20 and 30 h after making the initial scratch. Using ImageJ software, the area of the scratch was determined and the area recovery rate was calculated. Area Recovery (%) = (initial scratch area—final scratch area)/initial scratch area × 100%.

Transwell invasion and migration experiments

The two types of transwell experiments were invasion and migration experiments. The fundamental procedures were as follows: the transwell chamber (invasion assay: Matrigel® invasion chamber 8.0micron, Corning, USA; migration assay: 24 well multiwell insert System 8.0micron, Falcon, USA) is placed in the 24-well plate, the chamber is called the upper chamber and the plate is called the lower chamber. Cells were resuspended in serum-free media and inoculated into the upper chamber 24 h after siRNA transfection (MCF-7: 70,000 cells/well, MDA-MB-231: 30,000 cells/well). DMEM containing 10% FBS was then added to the lower chamber. After 28h incubation in the incubator, the medium was aspirated from the upper chamber of the cell and washed twice with PBS. After being fixed for 15 min with 4% paraformaldehyde, the chambers were stained for 30 min with a 0.1% crystal violet staining solution. Subsequently, the chambers were washed with distilled water, and the cells in the upper chamber that had not migrated were gently swabbed away with a cotton swab. Representative images were captured at 10X magnification with an Eclipse TS100 microscope (Nikon, Japan).

Western blotting

Using RIPA buffer (Beyotime, China) containing phenylmethylsulphonyl fluoride (PMSF), protease inhibitors, and phosphatase inhibitors, the total protein was extracted from the cells. Using a 12.5% SDS-PAGE gel (Yeasen, China), total protein was separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) before being transferred to a polyvinylidene difluoride (PVDF) membrane (Millipore, USA). After being blocked with 5% skim milk powder in PBS containing 0.1% Tween 20 (PBST) for 1 h at room temperature, the membranes were probed with primary antibody against TIMM8A (1:1500, Proteintech, China), p-BIK (1:1000, Abmart, China), BIK (1:5000, Proteintech, China), Bcl-2 (1:5000, Proteintech, China), NF-κB p65 (1:1000, Proteintech, China), Caspase 9 (1:700, Proteintech, China), Caspase 3 (1:750, Abmart, China), Vimentin (1:5000, Proteintech, China), α-SMA (1:2000, Proteintech, China), E-cadherin (1:1000, PTM biolab, China), N-cadherin (1:1000, PTM biolab, China) and GAPDH (1:10,000, Proteintech, China) overnight at 4 °C. Following three times of PBST washes, the membranes were incubated for 1 h with the appropriate secondary antibodies. In order to determine the expression levels of the target proteins, the bands were lastly analyzed using Immobilob™ Western Chemiluminescent HRP Substrate (Millipore, USA).

Dual-luciferase reporter assay

HEK-293T cells were initially cultured in 24-well plates and subsequently co-transfected with luciferase reporter plasmids (pmirGLO) containing either miR-10b-5p-TIMM8A binding sequences or mutant sequences, along with miR-10b-5p mimics or N.C mimics. Following a 48-h incubation period, cell lysate was collected to quantify firefly luciferase (FL) and Renilla luciferase (RL) activity, utilizing a dual-luciferase reporter assay kit (Yeasen, China) following the manufacturer’s guidelines. The relative ratio of FL/RL was employed to normalize any discrepancies in transfection efficiency.

Statistical Analysis

To compare gene expression differences, the Wilcox test was used. Pearson’s correlation test was conducted to determine whether two variables are correlated. The univariate and multivariate analysis of the effect of each variable on survival was performed using the Cox proportional hazards regression model. The GraphPad Prism (Version 8.0) and SPSS 20.0 software were used to analyze the experimental results, which were shown as the mean ± SD of at least three different trials. The student’s t-test or one-way ANOVA was used to detect the differences among groups. There were no one-sided tests, and P < 0.05 was considered statistically significant.

Results

Expression Landscape of TIMM8A in pan-cancer

To determine the expression levels of TIMM8A in both normal and malignant tissues, we initially examined the levels of TIMM8A expression in 33 normal tissues using the GTEx dataset (Fig. 1A). Among these tissues, the liver, heart muscle, and skeletal muscle exhibited the highest levels of TIMM8A expression. Additionally, analysis of the CCLE dataset revealed that TIMM8A was highly expressed in 288 tumor cell lines of ATCC, particularly in ovarian serous cystadenocarcinoma, neuroblastoma, stomach adenocarcinoma, lymphoid neoplasm diffused large B-cell lymphoma, and breast invasive carcinoma (Fig. 1B). demonstrated that the cell lines HMC-1, HEL, NTERA-2, U-937, and K-562 exhibited the highest levels of TIMM8A RNA enrichment (Fig. 1C). Analysis of the TCGA dataset revealed that, except for KIRC, LAML, PCDG, and THCA, TIMM8A expression was significantly elevated in nearly all cancer samples when compared to normal controls (Fig1D, E).

Fig. 1
figure 1

Expression profile of TIMM8A. (A) Expression of TIMM8A in normal tissues. (B) Expression of TIMM8A in tumor cell lines from the CCLE dataset. (C) Expression of TIMM8A in cell lines from the HPA dataset. (D) Differential expression of TIMM8A in cancerous and paraneoplastic tissues in pan-cancer. (E) Differential expression of TIMM8A in cancerous and normal tissues in pan-cancer. Wilcox test was used to compare gene expression differences. *P < 0.05; **P < 0.01; ***P < 0.001. ACC, adrenocortical carcinoma; BLCA, bladder urothelial carcinoma; BRCA, breast invasive carcinoma; CESC, cervical and endocervical cancers; CHOL, cholangiocarcinoma; COAD, colon adenocarcinoma; DLBC, lymphoid neoplasm diffuse large B-cell lymphoma; ESCA, esophageal carcinoma; GBM, glioblastoma multiforme; HNSC, head and neck squamous cell carcinoma; KICH, kidney chromophobe; KIRC, kidney renal clear cell carcinoma; KIRP, kidney renal papillary cell carcinoma; LAML, acute myeloid leukemia; LGG, brain lower grade glioma; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; MESO, mesothelioma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PCPG, pheochromocytoma and paraganglioma; PRAD, prostate adenocarcinoma; READ, rectum adenocarcinoma; SARC, sarcoma; SKCM, skin cutaneous melanoma; STAD, stomach adenocarcinoma; STES, stomach and esophageal carcinoma; TGCT, testicular germ cell tumors; THCA, thyroid carcinoma; THYM, thymoma; UCEC, uterine corpus endometrial carcinoma; UCS, uterine carcinosarcoma; UVM, uveal melanoma.

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Prognostic Value of TIMM8A in pan-cancer

Subsequently, a KM analysis was conducted to examine the prognostic significance of TIMM8A across various types of cancer. The analysis revealed that TIMM8A exhibited significant predictive value for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in certain tumor types (Fig 2A-C). Specifically, upregulated TIMM8A expression was associated with shorter OS in BRCA, KICH, SARC, and UCEC (P < 0.05). Furthermore, elevated TIMM8A expression was linked to decreased DSS in BRCA, KIRP, SARC, and UCEC, while it was associated with prolonged DSS in KIRC (P < 0.05). Additionally, elevated TIMM8A expression was correlated with shorter PFI in BRCA, KIRP, PAAD, PCPG, PRAD, SARC, and THYM, and conversely, with longer PFI in STAD and KIRC (P < 0.05). Given the observed correlation between TIMM8A expression in breast cancer and the prognosis of all three types, our investigation sought to further examine the prognostic value of TIMM8A in breast cancer. The utilization of ROC curves demonstrated the efficacy of TIMM8A expression levels in predicting overall survival specifically in BRCA (Fig. 2D). Moreover, the outcomes of both univariate and multivariate analyses indicated that TIMM8A may serve as an independent prognostic indicator for breast cancer (Table 2). Consequently, based on the findings of the multivariate analysis, we created a nomogram for estimating the likelihood that patients with invasive breast cancer will survive (Fig. 2E). The calibration curve suggested that the nomogram had good predictive efficacy when used to predict the 3-year survival probability (Fig. 2F).

Fig. 2
figure 2

Prognostic analysis of TIMM8A in pan-cancer. (A) Relationship between TIMM8A expression and OS in pan-cancer. (B) Relationship between TIMM8A expression and DSS in pan-cancer. (C) Relationship between TIMM8A expression and PFI in pan-cancer. (D) Predictive efficiency of TIMM8A expression on OS in breast invasive carcinoma patients. (E) Nomogram built to predict the survival probability in breast invasive carcinoma patients based on the multivariate analysis. (F) Calibration curve for evaluating 3-year survival probability. OS, overall survival; PFS, progression-free survival; DSS, disease-free survival.

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Table 2 Univariate analysis and multivariate analysis based on TIMM8A expression and clinical characteristics.
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Functional analysis of TIMM8A

To investigate the potential role of TIMM8A in cancer, we employed the GeneMANIA prediction server (Fig. 3A) and the STRING database (Fig. 3B) to elucidate the TIMM8A-related genes. Twenty-five TIMM8A-related genes from both databases were used for subsequent enrichment analysis. The GSEA results revealed a negative correlation between TIMM8A levels and the activity of inflammatory factor-related pathways, such as IL6 and IL2, in cancers other than OV, while a positive correlation was observed with cell cycle and MYC-related pathways (Fig. 3C). Additionally, analysis of single-cell sequencing datasets from CancerSEA provided evidence for the relevance of TIMM8A across 14 functional states of cancer (Fig. 3D). The results of the prognostic analyses suggested that TIMM8A levels showed a closer relationship with breast cancer prognosis. Therefore, we paid extra attention to the potential function of TIMM8A in breast cancer. A positive correlation between TIMM8A expression and DNA damage and repair, invasion, and apoptosis was observed in breast cancer. In contrast, there was a negative correlation between TIMM8A expression and apoptosis. In addition, GSEA analysis using the REACTOME pathway suggested that the involvement of TIMM8A in breast cancer progression may be associated with the NF-κB pathway and the cell cycle (Fig. 3E−G.). In subsequent experimental studies, we validated the above bioinformatics analysis results at the cellular level.

Fig. 3
figure 3

Functional analysis of TIMM8A in pan-cancer. (A) Network of TIMM8A and its related genes from GeneMANIA. (B) Network of TIMM8A and its associated genes from the STRING database. (C) Gene set enrichment analysis of TIMM8A-related genes for HALLMARK terms (D) Relevance of TIMM8A across 14 functional states based on single-cell sequencing datasets. (E–G) The GSEA results of TIMM8A in TCGA-BRCA cohort using REACTOME pathways.

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TIMM8A expressions in breast cancer tissues and cell lines

Based on bioinformatics analyses, it was determined that TIMM8A exhibited a stronger correlation with breast cancer prognosis compared to other cancer types, and it was also implicated in multiple signaling pathways associated with tumor progression. Consequently, our investigation proceeded to examine the expression of TIMM8A specifically in breast cancer cell lines. Utilizing data from the CCLE database, the expression pattern of TIMM8A in breast cancer cell lines was analyzed. Notably, BT549, MCF7, and MDA-MB-231 cells exhibited higher levels of TIMM8A expression (Fig. 4A). Furthermore, the expression of TIMM8A in breast cancer metastatic cell lines exhibited a significant increase compared to its expression in the primary site of the cancer, suggesting a potential association between TIMM8A and the progression of breast cancer (Fig. 4B). Moreover, a pairwise analysis utilizing the TCGA database revealed a notably higher expression of TIMM8A in breast cancer tissues compared to paracancerous tissues (Fig. 4C). According to the findings from qRT-PCR and western blot analysis (Fig. 4D–F), the expression of TIMM8A was notably higher in breast cancer cell lines, namely BT549, MCF7, and MDA-MB-231 cells, at both the mRNA and protein levels, in comparison to the normal breast epithelial cell line MCF10A. Meanwhile, among the three breast cancer cell lines, MCF7 and MDA-MB-231 cells showed higher levels of TIMM8A expression. Therefore, we would select these two cell lines for subsequent experiments. We further analyzed the prognostic impact of TIMM8A in the breast cancer subtypes represented by these two cell lines(Fig. 4G–H). The results of survival analysis suggested that high expression of TIMM8A in both luminal A and claudin-low subtypes was significantly associated with poor overall survival.

Fig. 4
figure 4

Expression of TIMM8A in breast cancer. (A) Expression of TIMM8A in breast cancer cell lines from the CCLE dataset. (B) Differential expression of TIMM8A breast cancer primary site cell lines and breast cancer metastatic site cell lines. (C) Differential expression of TIMM8A in cancerous and paraneoplastic tissues in breast cancer. (D–F) Expression of TIMM8A in mammary epithelial cell lines and several breast cancer cell lines analyzed by qRT-PCR and Western blot, (G) Kaplan–Meier analysis of the effect of TIMM8A on overall survival in luminal A subtype breast cancer based on the METABRIC database, (H) Kaplan–Meier analysis of the effect of TIMM8A on overall survival in claudin-low subtype breast cancer based on the METABRIC database. The results shown are representative of at least three independent experiments. qRT-PCR, quantitative real-time PCR. The student’s t-test or one-way ANOVA was used to detect the differences among groups. *P < 0.05; **P < 0.01; ***P < 0.001. Samples were derived from the same experiment and gels/blots were processed in parallel. Original blots/gels are presented in the Supplementary File.

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TIMM8A promoted the proliferation of breast cancer cells

A knockdown model of TIMM8A was generated through the transfection of siRNA. The findings from qRT-PCR and western blot analyses indicated a significant reduction in TIMM8A expression at both the mRNA and protein levels in MCF7 and MDA-MB-231 cells following TIMM8A siRNA transfection, as compared to the Negative siRNA (NC-siRNA) transfection group (Fig. 5A,D). Among the three siRNA sequences tested, siRNA-2 and siRNA-3 with higher knockdown efficiency for the subsequent experiments.

Fig. 5
figure 5

TIMM8A knockdown inhibited the of breast cancer in vitro. (A, B) Knockdown efficiency of TIMM8A via siRNA transfection analyzed proliferation by qRT-PCR and Western blot. (C, D) Proliferative capacity of MCF7 and MDA-MB-231 cells after knockdown of TIMM8A assayed by CCK8. (E–G) Clonal formation ability of TIMM8A-knockdown MCF7 and MDA-MB-231 cells. Clonal formation rate = effective clones/plating cell numbers × 100%. (H-J) Cell cycle profiles of TIMM8A-knockdown MCF7 and MDA-MB-231 cells generated by flow cytometry using PI staining. The results shown are representative of at least three independent experiments. The student’s t-test or one-way ANOVA was used to detect the differences among groups. *P < 0.05, ***P < 0.001. Samples were derived from the same experiment and gels/blots were processed in parallel. Original blots/gels are presented in the Supplementary File.

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The results obtained from the CCK8 assay demonstrated a significant decrease in the proliferation capacity of MCF7 and MDA-MB-231 cells following the knockdown of TIMM8A (Fig. 5C,D). Furthermore, the findings from the colony formation experiment indicated a notable reduction in the rate of clonal formation upon TIMM8A knockdown, thereby indicating a decrease in the proliferation ability of individual cells within the MCF7 and MDA-MB-231 cell lines (Fig. 5E-G).

TIMM8A involved in the cell cycle regulation of breast cancer cells

Subsequently, we proceeded to assess the distribution of the cell cycle as it exerts a significant influence on cell growth. Our cell cycle analyses revealed that the knockdown of TIMM8A resulted in a halt in the cell cycle progression (Fig. 5H–J). Following the knockdown of TIMM8A, MCF7 cells exhibited a predominant arrest in the GOG1 phase, while MDA-MB-231 cells displayed a predominant arrest in the S phase. This observation suggests that breast cancer cells were unable to progress into the M-phase, the mitotic phase, upon TIMM8A knockdown. The disparity in the duration of arrest between MCF7 and MDA-MB-231 cells may be attributed to inherent differences between these cell lines.

TIMM8A inhibited apoptosis of breast cancer cells

Furthermore, an investigation was conducted to examine the impact of TIMM8A on apoptosis in breast cancer cells. The results revealed a significant increase in the proportion of apoptotic cells in both MCF7 and MDA-MB-231 cell lines following the knockdown of TIMM8A (Fig. 6A-C). Additionally, a western blot analysis was performed to elucidate the expression levels of various proteins associated with apoptosis. Notably, the expression of pro-apoptotic cleaved caspase 3, cleaved caspase 9, and p-BIK exhibited an increase upon TIMM8A knockdown, while the expression of anti-apoptotic Bcl-2 demonstrated a decrease (Fig. 6D-N). According to these findings, the knockdown of TIMM8A could inhibit breast cancer cell proliferation by promoting apoptosis in vitro.

Fig. 6
figure 6

TIMM8A knockdown promoted apoptosis of breast cancer cells. (A–C) Proportion of apoptotic TIMM8A-knockdown MCF7 and MDA-MB-231 cells generated by flow cytometry using Annexin V-FITC/PI staining. (D–N) The expression levels of apoptotic-related proteins, including BIK, p-BIK, Bcl-2, Caspase-3, and Caspase-9, in MCF7 and MDA-MB-231 cells after knockdown of TIMM8A. GAPDH was used as a loading control. p-BIK levels were normalized with reference to BIK levels. Cleaved-caspase3/9 levels were normalized with reference to pro-caspase3/9 levels. The results shown were representative of at least three independent experiments. The student’s t-test or one-way ANOVA was used to detect the differences among groups. *P < 0.05, **P < 0.01, ***P < 0.001. Samples were derived from the same experiment and gels/blots were processed in parallel. Original blots/gels are presented in the Supplementary File.

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TIMM8A promoted the migration of breast cancer cells

We performed scratch assays and Transwell migration assays to determine the migration ability of the cells. Within the doubling time of the cell lines after making the scratches, the scratches of MCF7 and MDA-MB-231 cells in the NC-siRNA transfection group were significantly narrower and the area recovery rate was significantly increased compared to the TIMM8A knockdown group (Fig. 7A-C). Transwell migration assay findings also revealed that TIMM8A knockdown significantly lowered the number of cells moving to the lower chamber (Fig. 7D-F).

Fig. 7
figure 7

TIMM8A knockdown inhibited the migration and invasion of breast cancer in vitro. (A–C) Migration capacity of MCF7 and MDA-MB-231 cells after knockdown of TIMM8A assayed by scratch experiment. Area Recovery (%) = (initial scratch area—final scratch area)/initial scratch area × 100%. (D–F) Migration capacity of MCF7 and MDA-MB-231 cells after knockdown of TIMM8A assayed by transwell migration assay. (G–I) Invasion capacity of MCF7 and MDA-MB-231 cells after knockdown of TIMM8A assayed by transwell invasion assay. (J–R) The expression levels of NF-κB p65 and EMT-related proteins, including α-SMA, Vimentin, E-cadherin and N-cadherin in MCF7 and MDA-MB-231 cells after knockdown of TIMM8A. GAPDH was used as a loading control. The results shown are representative of at least three independent experiments. EMT, epithelial-mesenchymal transition. The student’s t-test or one-way ANOVA was used to detect the differences among groups. *P < 0.05, **P < 0.01, ***P < 0.001. Samples were derived from the same experiment and gels/blots were processed in parallel. Original blots/gels are presented in the Supplementary File.

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TIMM8A promoted the invasion of breast cancer cells

We performed a matrigel invasion experiment to see if knockdown TIMM8A had an impact on the invasion of MCF7 and MDA-MB-231 cells. The matrigel invasion assay verified, as shown in Fig. 7G-I, that the invasion ability of TIMM8A knockdown MCF7 and MDA-MB-231 cells decreased significantly as compared to the NC-siRNA transfection group.

Furthermore, we evaluated the expression of EMT-related proteins through western blot. Due to the phenotypic properties of the cell lines, MCF7 cells do not express N-cadhrin, and MDA-MB-231 cells do not express E-cadhrin21,22,23. Therefore, we examined E-cadhrin only in MCF7 cells and N-cadhrin only in MDA-MB-231 cells. We also examined the levels of their equally expressed Vimentin and α-SMA levels. The expression of N-cadherin, Vimentin and α-SMA associated with mesenchymal phenotype was downregulated after knockdown of TIMM8A. While at the same time epithelial phenotype related E-adhesin expression was upregulated in MCF7 cells. (Fig. 7J-R). According to the aforementioned findings, the knockdown of TIMM8A was able to inhibit breast cancer cell migration and invasion via EMT in vitro.

Furthermore, we discovered that TIMM8A knockdown significantly lowered the expression of NF-κB p65. This suggested that TIMM8A may promote the malignant biological behavior of breast cancer through the NF-κB pathway (Fig. 7J-R).

miR-10b-5p directly targets TIMM8A in breast cancer

To explore the miRNAs involved in regulating TIMM8A in breast cancer, we performed prediction by starBase and TargetScan databases and identified a total of 77 miRNAs. The association between these miRNAs and TIMM8A was then examined using information from the TCGA breast cancer database (Supplementary Table 1). It is well known that miRNAs can inversely regulate gene expression. Only 5 miRNAs were negatively correlated with the expression of TIMM8A (P < 0.05). Among them, miR-10b-5p had the strongest correlation (Fig. 8A). Furthermore, compared to normal tissues, the expression of miR-10b-5p was decreased in breast cancer tissues. (Fig. 8B). The results of survival analysis, then, suggested that miR-10b-5p downregulation was significantly associated with PFI shortening (Fig. 8C). In addition, we classified breast cancer patients into miR-10b-5p low /TIMM8A high, miR-10b-5p low/TIMM8A low, miR-10b-5p high/TIMM8A low, and miR-10b-5p high /TIMM8A high based on the TCGA database. The results of Kaplan–Meier analysis suggested a significant difference in PFI among the above four groups (P < 0.05). Compared with miR-10b-5p low /TIMM8A high group, patients in miR-10b-5p high /TIMM8A low group had better PFI (P < 0.05). However, no significant difference was seen between the PFI of the remaining two groups and that of the miR-10b-5p low /TIMM8A high group.

Fig. 8
figure 8

miR-10b-5p was an upstream miRNA of TIMM8A in breast cancer. (A) The expression correlation of miR-10b-5p with TIMM8A in breast cancer. (B) Expression of miR-10b-5p in breast cancer and normal tissues based on TCGA database. (C) Kaplan–Meier analysis based on the TCGA database of the effect of miR-10b-5p on progression-free survival in breast cancer. (D) Kaplan–Meier analysis of the 4 patient groups as patients with miR-10b-5p low /TIMM8A high, patients with miR-10b-5p low /TIMM8A low, patients with miR-10b-5p high /TIMM8A low, patients with miR-10b-5p high /TIMM8A high on PFI in breast cancer based on the TCGA database. The median of the ratio was used as the cutoff value. Bonferroni test was used to detect the differences among groups. (E) mRNA expression levels of TIMM8A in MCF7 cells and MDA-MB-231 cells after transfection with miR-10b-5p-mimic analyzed by qRT-PCR. (F–H) Protein expression levels of TIMM8A in MCF7 cells and MDA-MB-231 cells after transfection with miR-10b-5p-mimic analyzed by Western blot. (I) Luciferase reporter plasmids containing the 3’UTR of TIMM8A, with and without mutant miR-10b-5p binding sites. (J) Results of luciferase activity assays. The student’s t-test or one-way ANOVA was used to detect the differences among groups. * P < 0.05, **P < 0.01, ***P < 0.001. Samples were derived from the same experiment and gels/blots were processed in parallel. Original blots/gels are presented in the Supplementary File.

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By conducting qRT-PCR and western blot, our investigation revealed a significant decrease in TIMM8A expression at both the mRNA and protein levels in MCF7 and MDA-MB-231 cells following transfection with miR-10b-5p-mimic, as compared to the NC group (Fig. 8E–H). Furthermore, we successfully generated luciferase reporter plasmids containing the 3’UTR of TIMM8A, with and without mutant miR-10b-5p binding sites. Notably, luciferase activity assays demonstrated a substantial reduction in 3’UTR-WT luciferase activity upon overexpression of miR-10b-5p in HEK-293 T cells, while no significant impact on the luciferase activity of 3’UTR-MUT was observed (Fig. 8I–J). In light of these results, the tumor suppressive miR-10b-5p was shown to directly target TIMM8A in breast cancer.

Figure 8: miR-10b-5p was an upstream miRNA of TIMM8A in breast cancer. (A) The expression correlation of miR-10b-5p with TIMM8A in breast cancer. (B) Expression of miR-10b-5p in breast cancer and normal tissues based on TCGA database. (C) Kaplan–Meier analysis based on the TCGA database of the effect of miR-10b-5p on progression-free survival in breast cancer. (D) Kaplan–Meier analysis of the 4 patient groups as patients with miR-10b-5p low /TIMM8A high, patients with miR-10b-5p low /TIMM8A low, patients with miR-10b-5p high /TIMM8A low, patients with miR-10b-5p high /TIMM8A high on PFI in breast cancer based on the TCGA database. The median of the ratio was used as the cutoff value. Bonferroni test was used to detect the differences among groups. (E) mRNA expression levels of TIMM8A in MCF7 cells and MDA-MB-231 cells after transfection with miR-10b-5p-mimic analyzed by qRT-PCR. (F–H) Protein expression levels of TIMM8A in MCF7 cells and MDA-MB-231 cells after transfection with miR-10b-5p-mimic analyzed by Western blot. (I) Luciferase reporter plasmids containing the 3’UTR of TIMM8A, with and without mutant miR-10b-5p binding sites. (J) Results of luciferase activity assays. The student’s t-test or one-way ANOVA was used to detect the differences among groups. * P < 0.05, **P < 0.01, ***P < 0.001. Samples were derived from the same experiment and gels/blots were processed in parallel. Original blots/gels are presented in the Supplementary File.

Discussion

At present, as researchers improve their understanding of the translocase of the outer and inner mitochondrial membrane protein complexes, numerous members of the TIMM protein family are connected with the genesis and progression of tumors 24. In recent years, scientists have noticed that TIMM8A was associated with prognosis and immune infiltration in BRCA and UCEC14,16. The specific mechanisms by which TIMM8A contributes to the growth of various cancers and its potential role in promoting carcinogenesis remain unknown. Moreover, it has been shown that ncRNAs-mediated up-regulation of TIMM8A is associated with poor prognosis in breast cancer and promotes breast cancer cell proliferation in vitro and tumor growth in vivo15. However, these studies only focused on the function of TIMM8A in pro-tumor cell proliferation and did not evaluate the migratory invasive ability. It also lacked the analysis of the downstream signaling pathways of TIMM8A, and only predicted the relevant pathways by GSEA and KEGG, but did not perform the detection of key molecular markers. On this basis, this study performed a pan-cancer analysis of TIMM8A, assessed its effect on the migratory invasive ability of breast cancer cells, examined key markers of the downstream pathway, and also identified new potential upstream regulatory molecules of TIMM8A.

This current study represents the first comprehensive investigation of TIMM8A expression across multiple cancer types, revealing its involvement in the development and advancement of several common malignancies. The study revealed a strong association between the prognosis of the patient and the levels of TIMM8A, which exhibited significantly higher expression in cancer samples compared to normal control samples in the majority of malignancies. These findings, in conjunction with previous research, underscored the favorable prognostic significance of TIMM8A across various cancer types. Notably, in breast cancer, TIMM8A demonstrated a particularly robust correlation with tumor prognosis. Consequently, this study established TIMM8A as a potential independent predictor for breast cancer prognosis. The prognostic model constructed based on TIMM8A and other clinical characteristics had good predictive efficacy.

Functional studies on TIMM8A have mainly focused on Mohr-Tranebjaerg syndrome (MTS) and other neurological disorders. It has been shown that a loss-of-function mutation in TIMM8A affecting protein input into mitochondria, which in turn affects mitochondrial function and makes cells sensitive to oxidative stress-induced apoptosis, is a potential pathogenesis of MTS 12,13,25. The in vitro studies in malignant tumors such as neuroblastoma had shown that TIMM8A was involved in mitochondrial energy metabolism, mitosis, and apoptosis in tumor cells 13,15. Bioinformatics analysis also suggested that TIMM8A may be involved in tumor progression by regulating the tumor immune microenvironment14. The findings of the enrichment analysis indicated the potential involvement of TIMM8A and its associated genes in various cellular processes, including protein targeting to the mitochondrion, autophagy, respiratory chain complex IV assembly, and signal sequence binding, all of which were closely associated with mitochondrial function. Furthermore, the experimental evidence supported the notion that TIMM8A played a role in the pathogenesis of breast cancer. We first observed that knockdown of TIMM8A significantly inhibited the proliferation of breast cancer cells. Further results of cell cycle and apoptosis assays suggested that knockdown of TIMM8A inhibited cell proliferation through pro-apoptosis as well as cell cycle blockade. Knockdown of TIMM8A significantly inhibited migration and invasion of breast cancer cells. We observed a significant difference in the rate of area recovery only 10–20 h after scratch making. In addition, the changes in the levels of EMT-related proteins suggested that the breast cancer cells were transformed to the epithelial type after knocking down TIMM8A. Thus, in breast cancer, TIMM8A is simultaneously involved in the regulation of the cell cycle, apoptosis, and EMT, thereby promoting the proliferation and metastatic invasion of breast cancer cells. Changes in cellular phenotype as described above may be closely related to the importance of TIMM8A for mitochondrial function. This also suggested that in the future we need to carry out a series of experiments to clarify the role of TIMM8A in regulating mitochondrial function in breast cancer cells.

In addition, functional analysis in breast cancer suggested that TIMM8A may be involved in tumor progression through the NF-κB pathway. We also found down-regulation of NF-κB p65 levels in breast cancer cells after the knockdown of TIMM8A. One of the most well-known molecular pathways in cancer, NF-κB influences tumorigenesis by upregulating genes related to cell proliferation, metastasis, angiogenesis, and apoptosis inhibition 26. Inactive NF-κB proteins are locked away in the cytoplasm of normal cells in combination with inhibitor-κB (I-κB) 27,28. It has been proven that constitutive NF-κB activation is a crucial mechanism promoting tumorigenic processes in a variety of solid malignancies, including breast cancer 29,30. By binding to the cyclin D1 promoter, the NF-κB signaling cascade activates the cyclin D1 gene, which in turn promotes retinoblastoma protein phosphorylation, a need for cell cycle progression from G1 to S phase and cell proliferation 31. Meanwhile, Bcl-2, a negative regulator of apoptosis, has had its promoter identified as an NF-κB binding site 32,33. In addition, NF-κB can bind to the promoter regions of EMT transcription factors, WIST1, SLUG, and SIP1, in breast cancer to directly regulate epithelial-mesenchymal transition 34. Therefore, combining the findings of this study and the above findings, we could assume that the upregulation of TIMM8A to promote breast cancer cell proliferation and metastasis may be via the NF-κB pathway.

Previous studies had reported that miR-10b-5p exerts tumor suppressive effects in breast cancer by regulating the cell cycle 35,36. By integrating miRNA prediction, expression measurement, and survival analysis, miR-10b-5p was found to be the most likely upstream miRNA for TIMM8A in breast cancer in this study. Low miR-10b-5p expression and high TIMM8A expression as risk factors for poor prognosis in breast cancer patients. When they were both observed, patients had the worst PFI. This corroborated with the function of TIMM8A in this study and previous studies on miR-10b-5p. Subsequent luciferase assay also confirmed that miR-10b-5p can directly target TIMM8A to regulate its expression in breast cancer. Although demonstrating miRNA binding to target genes only by dual-luciferase reporter assays was insufficient and may be unreliable. These findings still offered valuable insights for further comprehensive investigations into the underlying mechanism of miR-10b-5p in the progression of breast cancer.

In conclusion, TIMM8A was commonly upregulated in pan-cancer and negatively correlated with prognosis. TIMM8A, a critical oncoprotein, was regulated by miR-10b-5p and could activate NF-κB signaling cascade response, promote Bcl-2 and then inhibit cleaved caspase 3 and cleaved caspase 9 expression, while regulating EMT-related protein expression, thereby stimulating proliferation, migration and invasion of breast cancer cells. It provided a direction to deepen the understanding of the regulatory mechanism of mitochondrial protein import mechanism and the development of related anti-tumor targeting drugs.