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. 2026 Jan 5;49(1):14. doi: 10.1007/s13402-025-01144-8

ACTG1 promotes breast cancer aggressiveness and confers ribociclib resistance by deubiquitinating HSPA8 through UCHL3

Quhui Wang 1,#, Xiancheng Liu 2,#, Xiaobing Yang 3,4,#, Zhixian He 1,✉, Yangfeng Chen 5,✉
PMCID: PMC12769674  PMID: 41492038

Abstract

In this study, we examined the biological significance of the actin gamma 1 (ACTG1)-UCHL3–HSPA8 axis in breast cancer. Through bioinformatic analysis, we recognized ACTG1 as a potential oncogenic factor in BRCA. By exploiting qRT-qPCR and Western blot analysis, we assessed the expression of ACTG1 and explored its impact on cellular proliferation, migration, and invasion. Our findings suggest that ACTG1 exerts its oncogenic effects in breast cancer cells through the EMT signaling pathway. By mining the BIOGRID database, we identified potential downstream regulatory genes; and co-immunoprecipitation assays confirmed protein interactions between ACTG1 and HSPA8. We also observed that ACTG1 promoted breast cancer cell proliferation, invasion, and migration via its interaction with HSPA8. Importantly, our study elucidated the facilitation by UCHL3 of HSPA8 deubiquitination by ACTG1. In conclusion, our study revealed a key role played by the ACTG1–UCHL3–HSPA8 axis in driving breast cancer progression as well as the role of ribociclib resistance. Our findings provide compelling evidence for the therapeutic potential of targeting this axis in breast cancer treatment strategies.

Supplementary information

The online version contains supplementary material available at 10.1007/s13402-025-01144-8.

Introduction

Actin gamma 1 (ACTG1) encodes the cytoskeletal protein gamma-actin and orchestrates pivotal functions within non-muscle cells. Integral to the dynamics of cellular migration, gamma-actin governs the intricate rearrangement of cytoskeletal networks. Emerging evidence implicates gamma-actin in the pathogenesis of diverse medical conditions that include cancer, brain abnormalities, and hearing impairment [1, 2]. However, little attention has been directed toward elucidating the involvement of ACTG1 in breast cancer.

Heat shock 70 kDa protein 8 (HSPA8 or HSC70) is a principal member of the heat shock protein 70 family and assumes the critical role of a chaperone that oversees protein folding and coordinates chaperone-mediated autophagy (CMA), with CMA selectively targeting proteins for degradation [3]. Given its critical biological role, HSPA8 has garnered considerable interest as a therapeutic target for autoimmune disorders [4]. Recent investigations highlight HSPA8’s upregulation across various cancer types, where it is positioned as a prognostic biomarker [5]. Moreover, HSPA8’s complex involvement in the therapeutic response of numerous cancers to multi-drug regimens suggests its potential as a promising drug target [6].

In contrast, ubiquitin carboxyl-terminal hydrolase isozyme L3 (UCHL3) exerts an anti-tumor influence, limiting the epithelial-mesenchymal transition (EMT) and mitigating the stem-like properties of prostate cancer cells [7, 8]. However, a paradox emerges as UCHL3 is shown to be overexpressed in lung, ovarian, and pancreatic cancers, and melanoma [9–12]. Notably, UCHL3 targets COPS5 and RAD51 for deubiquitination, underscoring its therapeutic potential [13, 14].

The approval of cyclin-dependent kinase inhibitors (CDKIs) has facilitated the development of targeted therapies for advanced breast cancer, and their success in clinical trials has led to their use in combination with endocrine therapy as the standard of care for hormone receptor (HR)-positive and HER2-negative breast cancer. Although phase III studies have confirmed that ribociclib (RIB) can be used as a first-line CDKI [15], whether ACTG1 can improve resistance to RIB in breast cancer remains unclear. In this investigative venture, we uncovered a conspicuous elevation in ACTG1 expression in breast cancer tissues within the TCGA dataset. To ascertain the putative role of ACTG1 in breast cancer, we conducted knockdown experiments in breast cancer cell lines. We subsequently examined the cellular and molecular repercussions of ACTG1 modulation on cellular proliferation, apoptosis, invasion, and migration both in vitro and in vivo. Intriguingly, we discerned a pivotal and exquisite interplay among ACTG1, UCHL3, and HSPA8 in breast cancer pathogenesis. Our findings not only elucidate novel dimensions of breast cancer biology but also show promise for the development of innovative therapeutic avenues.

Materials and methods

Cell culture and transfection

For our study, BRCA cell lines were generously provided by the American Type Culture Collection (ATCC, USA), and we cultured the cells in DMEM medium fortified with 10% fetal bovine serum. The introduction of plasmids and mimics into the cellular milieu was executed employing Lipofectamine 3000 reagent (Invitrogen, USA), ensuring efficient transfection as confirmed by subsequent Western blot analysis. Consequent experiments were conducted 24 hours post-transfection.

Plasmids and siRNA

The full-length and deletion mutant constructs of UCHL3 and HSPA8 were purchased from Sangon Biotech (Shanghai, China). The plasmids, including Flag-ACTG1, Myc-HSPA8, His-UCHL3, His-UCHL3 ΔC, His-UCHL3 ΔN, His-UCHL3 C95A, and HA-UB, were cloned into the pCDNA3.1(+) vector and obtained from Genepharma (Invitrogen, USA). Small interfering RNAs targeting ACTG1 (shRNA#1: 5′-CCGAGCCGTGTTTCCTTCCAT-3′; shRNA#2: 5′-GGCATTGTCATGGACTCTGGA-3′) were synthesized by Genepharma (Shanghai, China).

RNA extraction and quantitative reverse transcriptase-PCR

To extract total RNA, we employed the RNAiso Plus reagent (TaKaRa) in conjunction with a PrimeScript RT kit (TaKaRa). Following the manufacturer’s protocol, the RNA underwent reverse transcription to generate complementary DNA. qRT-PCR was then conducted using SYBR Green PCR Premix (TaKaRa) on an ABI7500 Fast Real-Time PCR System (Applied Biosystems, USA). Each experiment was performed in triplicate, with GAPDH serving as an internal reference for normalization. Finally, the relative gene expression levels were determined using the 2-ΔΔCt method.

Western blot analysis

Cells were lysed on ice, total cellular proteins were extracted via centrifugation, and protein concentration was quantified using the BCA assay. We added sample buffer to the protein samples, which were then heated to induce denaturation. Proteins were separated by electrophoresis on a 10% SDS-PAGE gel and transferred onto a polyvinylidene fluoride (PVDF) membrane (Bio-Rad). The membrane was then incubated overnight at 4 °C with primary antibodies that targeted ACTG1, HSPA8, UCHL3, E-cadherin, N-cadherin, vimentin, Myc, ubiquitin (UB), BCL-2, BAX, or β-actin (Abcam). The membrane was subsequently incubated with the corresponding secondary antibody conjugates for two hours. Finally, the membrane was treated with a chemiluminescent substrate and imaged using a luminescent imaging system.

CCK-8 assay

We assessed cellular proliferation with the CCK8 assay. Cells (2 × 103 cells/well) were seeded into a 96-well plate at a volume of 100 μL per well. Subsequently, 10 μL of the CCK8 solution was then introduced into each well, and following a continuous 4-hour incubation period, the culture plate was transferred to a microplate reader to quantify absorbance at OD-450 nm. Each experimental group was accompanied by three additional control wells for validation purposes.

Colony formation assay

For the colony formation assay, cells (1 × 103 cells/well) were cultured in 2 mL of media supplemented with 10% FBS in 6-well plates for 2 weeks. Following the incubation period, the colonies were immobilized and stained using a solution comprising 4% paraformaldehyde (PFA) and Giemsa (Beyotime, China).

Cellular apoptosis

Cellular apoptosis was determined using a KeyGEN apoptosis detection kit. Cells were seeded in six-well plates at a density of 1 × 105 cells per well and cultured until they reached their logarithmic growth phase. The cells were then processed in accordance with the manufacturer’s instructions and fixed overnight at 4 °C using 70% ethanol. We evaluated apoptosis by flow cytometry (BD Biosciences, USA).

Cell migration and invasion assay

Following the logarithmic growth phase, cells were resuspended as a single-cell suspension at a concentration of 1 × 104 cells/mL. The Transwell chambers were categorized into two groups: one without Matrigel coating for migration assays and the other with Matrigel coating for invasion assays. After incubation, the migrated cells were fixed with ethanol, stained with 0.1% crystal violet, and quantified under a light microscope.

Xenograft model

An animal model was established using 5-week-old BALB/c nude mice. Briefly, cells were first subjected to digestion and centrifugation, followed by culture and collection. The cells were then subcutaneously inoculated into each mouse at a volume of 200 μL that contained approximately 5 × 105 cells per 100 μL. During tumor development, tumor dimensions were monitored by measuring length (L) and width (W) with a caliper, and tumor volume was calculated using the formula V = (L × W2) × 0.5. On day 20 post-inoculation, the animals were humanely euthanized, and the tumor masses were recorded. All experimental procedures involving animals were conducted in accordance with the guidelines approved by the Animal Ethics Committee of the Affiliated Hospital of Nantong University.

Co-immunoprecipitation

Total cell lysates were incubated overnight at 4 °C with 5 μg of primary antibody or IgG control antibody. Thereafter, 5 μl of agarose A + G beads (Absin, Shanghai, China) was added, the incubation was continued at 4 °C for an additional 2 hours, and the resulting protein-antibody complexes were washed three times with phosphate-buffered saline (PBS). Protein detection was conducted using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) followed by Western blot analysis.

Bioinformatic analysis

We downloaded breast cancer RNA-seq count data and corresponding clinical information from the TCGA database (https://portal.gdc.cancer.gov) using STAR counts. The TPM (Transcripts Per Million) format of the data was extracted and subsequently normalized using a log2 (TPM + 1) transformation. After retaining only the samples that contained both RNA-seq data and clinical information, a total of 1101 samples were selected for further analysis. GTEx data (version V8) were also applied to this study, and detailed information can be found on the official GTEx website (https://gtexportal.org/home/datasets). We conducted statistical analyses using R software version 4.0.3, with a p value less than 0.05 considered to be statistically significant.

Drug sensitivity analysis

The assessment of treatment response encompasses drug sensitivity and immunotherapy efficacy analysis. We conducted a drug sensitivity analysis for breast cancer patients using the “oncoPredict” R package (Version 1.2). The primary rationale behind this method is to construct statistical models from gene expression data obtained from a vast array of cancer cell lines, and subsequently apply these models to gene expression data from target samples [16]. We calculated the IC50 values of various therapeutic agents in patients with high and low expression of the ACTG1 gene, and employed the “ggpubr” package to generate violin plots illustrating drugs with distinct IC50 values (p < 0.05). Furthermore, we examined the correlation between ACTG1 expression levels and drug IC50 values using the Spearman correlation test (p < 0.05), and utilized the “ggplot2” package to create scatter plots demonstrating the association between ACTG1 and drug IC50 values.

Statistical analysis

We adopted SPSS 28.0 software to statistically process the raw data obtained in this experiment, and these raw data were all expressed as mean ± standard deviation (SD). The independent-sample t test was applied for the comparison between two groups, and a one-way analysis of variance was executed for comparisons among 3+ groups. We designated statistical significance at p < 0.05.

Results

Overexpression of ACTG1 in BRCA

We analyzed the expression of ACTG1 across 33 cancer types using the online platform GEPIA (http://gepia.cancer-pku.cn). Compared to normal tissues, ACTG1 showed significantly elevated expression levels in multiple malignancies, including lung adenocarcinoma, breast cancer, and hepatocellular carcinoma (Fig. 1A). Further investigation underscored the pronounced upregulation of ACTG1 specifically in breast cancer tissues (Fig. 1B). To corroborate these findings, our exploration via database mining on proteinatlas.org revealed a consistent increase in ACTG1 expression within breast cancer tissues (Fig. 1C). Subsequent Western blot analysis on the same tissue pairs confirmed the augmented expression of ACTG1 in the breast cancer tissues (Fig. 1D). We ultimately conducted PCR analysis on 32 pairs of breast cancer tissues and corresponding adjacent tissues and reaffirmed the heightened expression of ACTG1 in breast cancer (Fig. 1E). When MDA-MB-231 and BT-549 cells were transfected with ACTG1-interfering plasmids (sh-ACTG1#1, sh-ACTG1#2) along with control plasmids (NC), we found that SH-ACTG1 significantly inhibited the expression of ACTG1 protein by Western blot analysis (Fig.s. 1F–G). In addition, the inhibitory effect of sh-ACTG1 on ACTG1 mRNA was also determined by PCR (Fig. 1H). Finally, we tested the effect of ATCG1 knockdown on the growth of breast cancer cells in nude mice and ascertained that the tumor-forming ability of the breast cancer cells was significantly attenuated after ACTG1 knockdown (Fig.s. 1I–K).

Fig. 1.

Fig. 1

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ACTG1 is highly expressed in breast cancer and promotes the growth of breast cancer cells. (A) ACTG1 demonstrated elevated expression across various cancers, as evidenced by the GEPIA database. (B) TCGA database analysis highlighted the upregulation of ACTG1 in breast cancer tissues. (C) Examination of ACTG1 expression in BRCA tissues via the ProteinAtlas database. (D) Western blot analysis depicting the expression levels of ACTG1 in seven pairs of BRCA tissues and corresponding adjacent tissues. (E) qPCR analysis of ACTG1 in 32 pairs of BRCA tissues and corresponding adjacent tissues. (F-G) The effects of sh-ACTG1#1 and sh-ACTG1#2 on the expression of ACTG1 protein in breast cancer cells were determined by Western blot analysis. (H) The effects of sh-ACTG1#1 and sh-ACTG1#2 on the expression of ACTG1 protein in breast cancer cells were determined by qPCR. (I) Visual comparison of tumor size after ACTG1 knockdown. (J) Tumor weight comparison after ACTG1 knockdown. (K) Tumor volume comparison after ACTG1 knockdown. ** p < 0.01

Knockdown of ACTG1 inhibits the proliferation, invasion, and migration of breast cancer cells and promotes apoptosis

To further elucidate the impact of ACTG1 knockdown on breast cancer cell behaviors (including proliferation, apoptosis, invasion, and migration), we employed the clonal formation assay to assess proliferation; and these experiments revealed a notable reduction in the proliferative ability of breast cancer cells following ACTG1 knockdown (Fig. 2A). Next, we utilized flow cytometry to evaluate apoptosis levels and our results demonstrated a significant promotion of apoptosis in both MDA-MB-231 and BT-549 cells upon knockdown of ACTG1 (Fig. 2B). We then investigated the influence of ACTG1 on breast cancer cell migration and invasion using the Transwell assay and demonstrated that ACTG1 knockdown effectively suppressed the invasive and migratory capacities of MDA-MB-231 and BT-549 cells (Figs. 2C and 2D). To investigate the mechanism by which ACTG1 influences the invasion and migration of breast cancer cells, we examined its effect on the EMT signaling pathway using Western blot analysis and found that ACTG1 overexpression led to a downregulation of E-cadherin and an upregulation of N-cadherin and vimentin expression (Fig. 2E). Conversely, ACTG1 knockdown resulted in increased E-cadherin expression and diminished expression of N-cadherin and vimentin (Fig. 2F).

Fig. 2.

Fig. 2

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ACTG1 affects the apoptotic, invasive, and migratory capabilities of breast cancer cells. (A) Clonal formation experiments revealed a significant reduction in breast cancer cell proliferation following ACTG1 knockdown. (B) Flow-cytometric analysis demonstrating increased apoptosis in MDA-MB-231 and BT-549 cells upon ACTG1 knockdown. (C-D) Transwell assay results indicated inhibition of breast cancer cell migration and invasion upon ACTG1 knockdown. (E) Overexpression of ACTG1 led to downregulation of E-cadherin and upregulation of N-cadherin and vimentin expression. (F) Knockdown of ACTG1 resulted in increased E-cadherin expression and decreased N-cadherin and vimentin expression. ** p < 0.01

ACTG1 interacts with HSPA8 protein

We predicted potential protein interactions between ACTG1 and HSPA8 using the BIOGRID database (https://thebiogrid.org/), and subsequent docking analysis further affirmed their proximity and the likely physical interaction between ACTG1 and HSPA8 proteins (Figs. 3A–3B). This interaction was validated through both endogenous and exogenous co-immunoprecipitation (co-IP) assays. Endogenous co-IP assays demonstrated protein interaction between ACTG1 and HSPA8 in MDA-MB-231and BT-549 cells (Fig. 3C), and this was further validated by exogenous co-IP assays (Fig. 3D). We then investigated the effect of ACTG1 overexpression on HSPA8 expression by transfecting MDA-MB-231 and BT-549 cells with an ACTG1 overexpression plasmid, and discerned that the expression of HSPA8 was markedly and consistently increased with ACTG1 overexpression (Fig. 3E). When we transfected the MDA-MB-231 and BT-549 cells with ACTG1-interfering plasmids (sh-ACTG1#1, sh-ACTG1#2) along with control plasmids (NC), we observed a significant reduction in HSPA8 expression in both cell lines post-ACTG1 knockout (Fig. 3F).

Fig. 3.

Fig. 3

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ACTG1 interacts with the HSPA8 protein. (A-B) Molecular docking analysis illustrating the interaction between ACTG1 and HSPA8. (C) Protein interaction between ACTG1 and HSPA8 in MDA-MB-231 and BT-549 cells. (D) Exogenous co-IP showing protein interaction between ACTG1 and HSPA8 in MDA-MB-231 and BT-549 cells. (E) Western blot analysis showing that HSPA8 protein was expressed in MDA-MB-231 and BT-549 cells after ACTG1 overexpression. (F) Western blot analysis showing the expression of HSPA8 protein in MDA-MB-231 and BT-549 cells transfected with sh-ACTG1#1 and sh-ACTG1#2. ** p < 0.01

ACTG1 increases the stability of HSPA8 in breast cancer cells

To further delineate the role of ACTG1 in regulating HSPA8 stability, cells were treated with the protein synthesis inhibitor cycloheximide (CHX). Intriguingly, overexpression of ACTG1 led to an extension in the half-life of the HSPA8 protein, thereby enhancing its stability both in MDA-MB-231and BT-549 cells (Fig. 4A). To explore the interplay between ACTG1 and HSPA8 in breast cancer cell lines, we transfected ACTG1-interfering plasmids and HSPA8-overexpressing plasmids individually, and subsequent co-IP experiments revealed that ACTG1 knockdown significantly potentiated the ubiquitination ability of HSPA8 in both MDA-MB-231 and BT549 cells (Fig. 4B). Additional Western blot analyses showed that ACTG1 knockdown markedly suppressed the expression of HSPA8, while HSPA8 overexpression circumvented the inhibitory effects of sh-ACTG1 on HSPA8 expression (Fig. 4C).

Fig. 4.

Fig. 4

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ACTG1 increases the stability of HSPA8 in breast cancer cells. (A) Overexpression of ACTG1 resulted in a prolonged half-life of HSPA8 protein. (B) ACTG1 knockdown significantly potentiated the ubiquitination ability of HSPA8 in both MDA-MB-231 and BT549 cells. (C) Western blot analyses demonstrating the inhibitory effect of ACTG1 knockdown on HSPA8 expression, and its reversal by HSPA8 overexpression. ** p < 0.01

UCHL3 increases the stability of HSPA8 in breast cancer cells

We uncovered via BIOGRID (https://thebiogrid.org/) and mass spectrometric analysis that UCHL3 might interact with HSPA8, and our endogenous co-IP assays demonstrated protein interaction between ACTG1 and HSPA8 in MDA-MB-231and BT-549 cells (Fig. 5A). By constructing a UCHL3 overexpression plasmid, we determined that UCHL3 significantly increased the expression of HSPA8 protein (Fig. 5B). We then demonstrated that overexpression of ACTG1 in MDA-MB-231 cells resulted in a prolonged half-life of HSPA8 protein, thereby enhancing its stability (Fig. 5C). To study the domain involved in the UCHL3 and HSPA8 interaction, we constructed truncated forms of UCHL3 and HSPA8, respectively, and found that the △N-terminal of UCHL3 interacted with HSPA8 and that the △C terminal of HSPA8 interacted with HSPA8 (Fig. 5D). Further exploration revealed that UCHL3 diminished the ubiquitination ability of HSPA8 and that mutation of UCHL3 at C95A did not influence this deubiquitination capability (Fig. 5F). Western blot experiments showed that although UCHL3 overexpression promoted the expression of HSPA8, mutation of UCHL3 eliminated its regulatory effect on HSPA8 expression (Fig. 5G).

Fig. 5.

Fig. 5

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UCHL3 increases the stability of HSPA8 in breast cancer cells. (A) Co-IP assays demonstrated protein interaction between UCHL3 and HSPA8 in MDA-MB-231 and BT-549 cells. (B) UCHL3 significantly increased the expression of HSPA8 protein. (C) Overexpression of ACTG1 in MDA-MB-231 cells resulted in a prolonged half-life of HSPA8 protein. (D-E) Interaction domain between UCHL3 and HSPA8. (F) Mutation of UCHL3 at C95A did not influence the deubiquitination ability of HSPA8. (G) Western blot experiments showed that the UCHL3 mutation eliminated its regulatory effects on HSPA8 expression

ACTG1 stabilizes HSPA8 by deubiquitinating HSPA8 through UCHL3

In our investigation of MDA-MB-231 and BT-549 cells, we identified protein interactions between ACTG1 and UCHL3 through co-IP experiments (Fig. 6A) and found that the interaction between UCHL3 and HSPA8 was impeded upon ACTG1 knockdown (Fig. 6B). Further exploration revealed that UCHL3 diminished the ubiquitination ability of HSPA8, with ACTG1 enhancing the deubiquitination ability of UCHL3 on HSPA8 (Fig. 6C). Intriguingly, mutation of UCHL3 at C95A did not influence the deubiquitination by ACTG1 (Fig. 6D), and we further observed that overexpression of UCHL3 reversed the ubiquitination action of sh-ACTG1 on HSPA8 (Fig. 6E).

Fig. 6.

Fig. 6

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ACTG1 stabilizes HSPA8 by deubiquitinating HSPA8 through UCHL3. (A) Protein interactions among UCHL3, ACTG1, and HSPA8 were identified through co-IP experiments in MDA-MB-231 and BT-549 cells. (B) Inhibition of the interaction between UCHL3 and HSPA8 upon ACTG1 knockdown. (C) UCHL3 reduced the ubiquitination ability of HSPA8, while ACTG1 enhanced the deubiquitination ability of UCHL3 on HSPA8. (D) UCHL3 mutation at C95A did not affect ACTG1 deubiquitination. (I, J) The deubiquitination of ACTG1 on HSPA8 was initiated at UCHL3 and disappeared upon UCHL3 mutation. (E) Reversal of sh-ACTG1-induced ubiquitination on HSPA8 by overexpressed UCHL3

ACTG1 regulates the proliferation, invasion, and migration of breast cancer cells through HSPA8

To delve deeper into the impact of ACTG1 on the proliferation, invasion, and migration of breast cancer cells as mediated by HSPA8, we conducted clonal formation experiments to assess the effect of ACTG1 overexpression on proliferation. ACTG1 knockdown markedly hindered the proliferation of breast cancer cells, with HSPA8 knockdown reversing the inhibitory effect of sh-ACTG1 on proliferation (Fig. 7A). We also scrutinized the effect of ACTG1 on breast cancer cell migration and invasion using the Transwell assay, and found that ACTG1 knockdown impeded the invasion of breast cancer cells, and that HSPA8 knockdown effectively reversed the inhibitory effect of sh-ACTG1 on invasion (Fig. 7B). Similarly, knockdown of ACTG1 constrained the migration of breast cancer cells, while knockdown of HSPA8 ameliorated the migratory inhibition generated by sh-ACTG1 (Fig. 7C).

Fig. 7.

Fig. 7

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ACTG1 regulates the proliferation, invasion, and migration of breast cancer cells via HSPA8. (A) Clonal formation experiments illustrating the inhibitory effect of ACTG1 knockdown on breast cancer cell proliferation and its reversal by overexpression of HSPA8. (B, C) Transwell assay depicting the inhibitory impact of ACTG1 knockdown on breast cancer cell invasion and migration, with its reversal observed upon overexpression of HSPA8. ** p < 0.01

ACTG1 improves resistance to rib in breast cancer cells via HSAP8

Here we first explored the genes that might be associated with ACTG1 resistance through bioinformatic analysis. The three antitumor drugs, RIB, afatinib, and crizotinib, were screened (Fig. 8A), and the cellular viability of the BT-549 and MDA-MB-231 cells was measured after 48 hours of continuous exposure to multiple concentrations of RIB. To establish the IC50 value (i.e., the concentration that reduced cell viability by 50%), we applied the variable Hill slope model and estimated the IC50 value by nonlinear regression. Using BT-549 and MDA-MB-231 cells, we showed that while knockdown of ACTG1 led to hypersensitivity to RIB (Fig. 8B), overexpression of HSPA8 led to decreased RIB sensitivity of the breast cancer cells (Fig. 8C). It is important to note that the overexpression of HSPA8 effectively counteracted the enhanced RIB sensitivity induced by ACTG1 knockdown in BT-549 and MDA-MB-231 cells (Fig. 8D).

Fig. 8.

Fig. 8

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ACTG1 improves resistance to ribociclib in breast cancer cells via HSAP8 (A) Database mining of drugs associated with ACTG1. (B) Knockdown of ACTG1 led to hypersensitivity to ribociclib in BT-549 and MDA-MB-231 cells. (C) Overexpression of HSPA8 led to decreased RIB sensitivity of breast cancer cells. (D) The overexpression of HSPA8 effectively counteracted the enhanced ribociclib sensitivity induced by ACTG1 knockdown in BT-549 and MDA-MB-231 cells. ** p < 0.01

Functional role of the ACTG1 gene in BT-549 and MDA-MB-231 cell lines and its influence on apoptosis

We experimentally elucidated the functional role of the ACTG1 gene in BT-549 and MDA-MB-231 cell lines and its influence on apoptosis by additionally systematically evaluating the regulatory actions of HSPA8 overexpression and RIB treatment in modulating the apoptotic process. We demonstrated in both BT-549 and MDA-MB-231 cells that ACTG1 knockdown (sh-ACTG1) significantly elevated the proportion of apoptotic cells, and that overexpression of HSPA8 (OV-HSPA8) partially counteracted the pro-apoptotic effect induced by ACTG1 knockdown. In ACTG1-knockdown cells, treatment with the apoptosis-inducing drug RIB further augmented the proportion of apoptotic cells, while HSPA8 overexpression attenuated this effect (Fig. 9A–C). Western blot analysis demonstrated that ACTG1 knockdown markedly downregulated the expression of the anti-apoptotic protein BCL2 and upregulated the pro-apoptotic protein BAX. HSPA8 overexpression also partially restored BCL2 levels and suppressed the upregulation of BAX. Following RIB treatment, BAX expression was further elevated, whereas BCL2 expression was further reduced, indicating that RIB may have potentiated pro-apoptotic signaling pathways. Moreover, HSPA8 overexpression significantly mitigated the changes in apoptosis and the expression levels of apoptosis-related proteins precipitated by ACTG1 knockdown (Fig. 9D).

Fig. 9.

Fig. 9

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Functional role of the ACTG1 gene in BT-549 and MDA-MB-231 cell lines and its influence on apoptosis. (A-C) Cellular apoptosis was quantitatively assessed using TUNEL and DAPI staining. (D) Western blot analysis was conducted to evaluate the expression levels of apoptosis-related proteins (BCL2 and BAX). ** p < 0.01

Mechanistic model of the ACTG1–UCHL3–HSPA8 axis in breast cancer

In summary, ACTG1 overexpression stabilizes HSPA8 through deubiquitination mediated by its interaction with UCHL3. This mechanism suppresses apoptosis in breast cancer cells, enhances resistance to Ribociclib, and concurrently promotes proliferation, migration, and invasion of breast cancer cells, thereby driving tumor progression (Fig. 10).

Fig. 10.

Fig. 10

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Schematic depiction of the mechanism underlying how ACTG1 promotes breast cancer aggressiveness and confers ribociclib resistance through stabilization of HSPA8 by deubiquitination

Discussion

Actin is a widely conserved protein of the cytoskeleton that plays a pivotal role in cytoskeletal formation and cellular mobility. The ACTG1 gene is responsible for encoding a specific isomer of actin that is significantly involved in numerous cancer types and that serves as an early cancer detection marker [17]. Xiao and colleagues identified ACTG1 as a critical biomarker for prostate cancer metastasis, primarily via its interaction with the MAPK/ERK signaling pathway [18]. Similarly, Dong and associates demonstrated the influence of ACTG1 on the growth and movement of skin cancer cells via the ROCK signaling pathway [19]. Additional studies have shown that overexpression of ACTG1 disrupted the inhibition of miR-145-5p on bladder cancer (BC) cells, and that this effect was mediated by ultrasound-targeted microbubble destruction (UTMD). This process effectively suppresses the aggressive traits of BC cells by targeting miR-145-5p so as to reduce ACTG1 levels [20]. Moreover, our investigations revealed an elevated expression of ACTG1 in breast cancer samples, as confirmed by Western blot analysis. ACTG1 is also implicated in modulating breast cancer cell proliferation, invasion, migration, and apoptosis as assessed by clonal formation and Transwell assays and by flow-cytometric methods.

Co-immunoprecipitation (co-IP) experiments have verified interactions between ACTG1 and HSPA8, indicating that HSPA8 acts as a downstream effector in pathways that involve ACTG1. HSPA8, a component of the heat shock protein 70 (HSP70) family and commonly referred to as HSC70 or heat shock cognate 70, is ubiquitously expressed and functions as a molecular chaperone [21]. Localized to the cytoplasm, nucleus, and exosomes [22], HSPA8 plays crucial roles in protein folding and degradation. Researchers have established that the E3 ubiquitin ligase CHIP works with both stress-induced HSP70 and constitutive HSC70 to facilitate protein sorting, refolding, and the ubiquitination of substrates. In the absence of client proteins, CHIP promotes the polyubiquitination and proteasomal degradation of these chaperones [23]. Our findings suggested that in cells that overexpressed ACTG1, the degradation of HSPA8 was notably diminished following cycloheximide (CHX) treatment, extending the half-life of HSPA8 due to ACTG1-mediated stabilization via deubiquitination processes. We further demonstrated that ACTG1 influenced the proliferation, invasion, and migration of breast cancer cells through its regulatory effects on HSPA8.

The deubiquitinase enzyme UCHL3 is increasingly recognized for its pivotal position in cancer biology, particularly in enhancing the stability of the YAP protein in anaplastic thyroid cancer via its deubiquitinating actions—advancing cancer progression and metastasis [24]. Additionally, UCHL3 enhances stem-like traits and the tumorigenic potential in non-small cell lung cancer by modulating aromatic ubiquitin receptors [25]. We herein identified HSPA8 as a novel target for UCHL3 in breast cancer (BRCA), wherein UCHL3 mediated the stabilization of HSPA8 by removing ubiquitin tags in breast cancer cells. Although further exploration revealed a cooperative interaction between ACTG1 and UCHL3 in the deubiquitination of HSPA8, we noted that the influence of ACTG1 on the deubiquitination of HSPA8 relied on the presence of UCHL3.

In this study, we demonstrated an anti-apoptotic role for the ACTG1 gene in breast cancer cells, and that its knockdown promoted apoptosis by downregulating BCL2 and upregulating BAX. Overexpression of HSPA8 partially offset the pro-apoptotic effect induced by ACTG1 knockdown, suggesting that HSPA8 exerted a protective function by modulating the expression levels of apoptosis-related proteins. Furthermore, treatment with the drug RIB significantly amplified the apoptotic effect in cells with ACTG1 knockdown, while HSPA8 overexpression mitigated this process. Collectively, these findings deepen our understanding of the molecular mechanisms underlying breast cancer progression and provide a theoretical basis for the development of novel therapeutic strategies.

This investigation established a significant upregulation of ACTG1 in breast cancer tissues and underscored its critical functions in fostering cellular proliferation, migration, and invasion while also suppressing apoptosis in these cells. Furthermore, treatment with RIB significantly amplified the apoptotic effect in ACTG1-knockdown cells, while HSPA8 overexpression mitigated this process. Crucially, ACTG1 has been proven to enhance the stability of HSPA8 by regulating the expression of UCHL3, which in turn modulated the biological behaviors of breast cancer cells, marking a significant advancement in our understanding of cancer biology. These insights into the ACTG1–UCHL3–HSPA8 pathway not only deepen our understanding of the mechanisms underlying breast cancer but also suggest potential new markers and therapeutic targets that offer innovative approaches for the clinical management of breast cancer.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (1.2MB, pdf)

Acknowledgements

We thank LetPub (http://www.letpub.com.cn) for its linguistic assistance during the preparation of this manuscript.

Author contributions

Contributions: (I) Conception and design: Q Wang; (II) Administrative support: X Yang; (III) Provision of study materials or patients:, X Liu; (IV) Collection and assembly of data: Z He; (V) Data analysis and interpretation: Y Chen; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Funding

This research received financial support through grants from the Jiangsu Province Maternal and Child Health Research Project (F201953) and the Nantong Science and Technology Project (JC2020067), both awarded to ZH. These funds facilitated the conduct of the study, highlighting the backing from regional scientific and health-related funding bodies in supporting valuable medical research.

Data availability

The original contributions from this study are detailed in the main article and the Supplementary Materials section. For further inquiries or detailed discussions, please contact the corresponding authors, whose contact details are provided in the publication. This approach ensures direct communication with the researchers for additional insights or clarifications regarding the study’s findings and methodologies.

Declarations

Ethical approval

This study was approved by the institutional ethics committee of the Affiliated Hospital of Nantong University (2023-L084). The animal research protocol was approved by the Animal Ethics Committee of Nantong University (P20230222-001), in compliance with institutional guidelines for the care and use of animals.

Consent to participate

All authors approve the manuscript and agree to submit and publish it.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Quhui Wang, Xiancheng Liu and Xiaobing Yang Contributed equally to this work.

Contributor Information

Zhixian He, Email: hezhixaings@sina.com.

Yangfeng Chen, Email: cyf755755@163.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary material 1 (1.2MB, pdf)

Data Availability Statement

The original contributions from this study are detailed in the main article and the Supplementary Materials section. For further inquiries or detailed discussions, please contact the corresponding authors, whose contact details are provided in the publication. This approach ensures direct communication with the researchers for additional insights or clarifications regarding the study’s findings and methodologies.

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