RCN1 binds KIF14 to promote the malignant development of cervical cancer

doi:10.21203/rs.3.rs-5310705/v1

Purpose

The fourth most common cause of cancer-related deaths in women is cervical cancer. Though treatment of early-stage cervical cancer is often effective, middle and advanced stage cervical cancer is hard to treat and prone to recurrence. We sought to explore the mechanism underlying cervical cancer progression to identify new therapeutic approaches.

Methods

Label-free mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins in cervical cancer and normal tissues. The findings were confirmed by Western blotting, RT-qPCR, and immunohistochemistry. The function of RCN1 in tumor invasion, metastasis, and proliferation was investigated using in vitro and in vivo tests. Immunoprecipitation tandem mass spectrometry (IP-MS) was performed in RCNI knockdown cells to identify downstream pathways.

Results

RCN1 expression is elevated in patients with lymph node metastases and recurrent cervical cancer and correlates with poor prognosis. Knockdown and overexpression assays revealed that RCN1 promotes proliferation, migration and invasion of cervical cancer cells. RCN1 overexpression encourages lung metastasis in a mouse xenograft model. Furthermore, RCN1 targets KIF14, an activator of AKT, thus providing a molecular basis that could explain the malignant behavior of RCN1-expressing cervical cancer.

Conclusion

RCN1 is significantly expressed in cervical cancer, which is associated with a poor prognosis, spread and recurrence. By promoting KIF14-induced activation of the PI3K-AKT-mTOR pathway, RCN1 may facilitate the malignant development of cervical cancer.

RCN1 KIF14 cervical cancer PI3K-AKT-mTOR pathway

In women, cervical cancer ranks fourth in terms of cancer diagnoses, and fourth in terms of cancer-related deaths. There were 342,000 estimated cancer-related fatalities worldwide in 2020, along with 604,000 new instances of cervical cancer (Sung et al. 2021). In some industrialized nations, cytology testing and HPV vaccination constitutes a successful preventative program, although global coverage is still low. Patients with early-stage cervical cancer are now advised to consider surgery or radiation therapy, both of which have good clinical results worldwide (Bruni et al. 2016; Cohen et al. 2019).

Nevertheless, the most recent version of China's national cancer statistics, published in February 2022 by the National Cancer Center (NCC), showed that the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) for malignancies of the cervix has increased significantly(Zheng et al. 2022). This is largely attributed to cancers that are detected in later stages; once cervical cancer metastasis and recurrence occur, the treatments are limited and the prognosis is much worse. The search for more effective molecular targets is therefore of great significance for evaluating the prognosis and treatment of recurrent cervical cancer.

Reticulocalbin 1 (RCN1) belongs to the CREC family of compounds. Its carboxyl-terminal sequence contains six EF-hand motifs and an endoplasmic reticulum-retention motif (HDEL) that facilitates its localization to the endoplasmic reticulum. As a Ca2+-binding protein, RCN1 is expressed along the full mammalian cell secretory route and plays a role in regulating Ca2+-dependent processes in the endoplasmic reticulum lumen (Honoré 2009). Breast cancer (Nakakido et al. 2016), colon cancer (Nimmrich et al. 2000), liver cancer (Lu et al. 2015), and lung cancer (Chen et al. 2019) have all been linked to RCN1. Additionally, RCN1 down-regulation has been shown to promote necroptosis and apoptosis in prostate cancer cells (Liu et al. 2018). In particular, RCN1 is involved in the regulation of drug resistance. RCN1 knockdown in nasopharyngeal carcinoma cells and tissues decreases doxorubicin resistance and increases cell death (Huang et al. 2020). These data suggest that RCN1 dysregulation may play a role in the initiation and spread of malignancies. However, neither the biological actions of RCN1 nor their link to prognosis in cervical cancer have been thoroughly studied.

Kinesins are cargo-carrying molecular motors that travel along microtubules and are ATP-dependent. They are divided into 14 different families, each of which has unique structural and functional traits (Miki et al. 2005). Kinesin family member 14 (KIF14) is a chromokinesin that is located on chromosome 1q32.1 and belongs to the Kinesin-3 superfamily (Ahmed et al. 2012). In hepatocellular carcinoma cells, the loss of KIF14 causes cytokinesis failure and increased amounts of p27Kip1(Gruneberg et al. 2006; Xu et al. 2014). It is commonly acknowledged that KIF14 contributes to carcinogenesis. When KIF14 is overexpressed, mitosis proceeds quickly and incorrectly, resulting in aneuploidy during the tumor-forming process (Corson et al. 2005). Akt also has been implicated in cell division and metastasis (Manning and Cantley 2007) and is known to be activated by KIF14. PI3K-AKT has been confirmed to promote the development of tumors; however, it has not been determined whether RCN1 targets KIF14 to activate the PI3K-AKT pathway.

In this study, we demonstrated that RCN1 is upregulated in cervical carcinoma. To better understand RCN1's potential mode of action, we examined the correlation of RCN1 expression with prognosis and survival. Furthermore, we used cellular and animal assays to elucidate mechanisms by which RCN1 promotes malignant behavior. Our results provide a new biomarker and potential therapeutic target for advanced cervical cancer.

Patient enrollment

Cervical squamous cell carcinoma tissue, cervical adenocarcinoma tissue, and normal cervical control tissue (patients with hysterectomy due to uterine myoma and no cervical disease confirmed by pathology) specimens were collected by gynecological surgical resection at Xuzhou Central Hospital from 2021 to 2023. There were 44 cases of squamous cell carcinoma, 20 cases of adenocarcinoma, and 60 cases of normal cervical tissue. Additionally, Between January 2016 and July 2018, the Department of Gynecology at Xuzhou Central Hospital collected samples and data from 64 patients who were diagnosed with cervical cancer and had radical surgery. Fresh tissue was frozen in liquid nitrogen immediately after removal, formalin fixed and embedded. All samples used in this study were confirmed pathologically. All patients provided written informed consent prior to sample collection, and the Xuzhou Central Hospital's Ethical Committee approved the use of the clinical samples (XZXY-LJ-20210513-052).

Label-free relative quantification proteomics

Label-free MS proteomics quantitation (LC-MS/MS) was performed on three groups of samples: cervical adenocarcinoma tissues, cervical squamous carcinoma tissues and normal control tissues, to detect and analyze the significantly differentially expressed proteins in each group of samples. Maxquant Perseus software was used to analyze the differential expression of omics data. The data were imported to retrieve the output proteinGroups.txt file, and the corresponding LFQ intensity was selected. The data with Reverse, only identified by site and < s:1 > were removed, the LFQ intensity value was taken as the log base of 2, the disease and control groups were classified, and the effective data were screened. Significant differentially expressed genes (up 2-fold or down 0.5-fold Foldchange (FC), p < 0.05) were screened by t-test between the two groups. Proteins with pp-regulated or both down-regulated expression in adenocarcinoma (Adeno) and squamous carcinoma (Squa) tissues were analyzed using the InteractiVenn online analysis tool and presented in Venn diagrams. KEGG functional enrichment analysis was performed to identify differentially expressed proteins. The analyses of up-regulation and down-regulation were conducted separately and together. KEGG pathway enrichment analysis of differentially expressed genes was performed using DAVID 6.8 (or KOBAS) tool, and p < 0.05 was selected as the significant threshold. KEGG mapper was used for pathway map analysis of differentially expressed genes.

Cell culture

The Hela, SiHa, and C33A human cervical cancer cell lines were acquired from Shanghai Gaining Biological Technology Co., Ltd. (Shanghai, China). All cell lines underwent Short Tandem Repeat (STR) profiling authentication. The cells were cultivated in Dulbecco's Modified Eagle's Medium (GIBCO, Billings, MT, United States) supplemented with 10% fetal bovine serum (GIBCO) and 100 IU/mL penicillin-streptomycin combination (Sigma-Aldrich). Cultures of transfected cells were maintained in high-glucose Dulbecco's modified Eagle's medium (GIBCO, USA) supplemented with 10% FBS, 100 U/mL penicillin sodium, and 100 µg/mL streptomycin sulphate (Hyclone, USA). The cells were cultured in a humidified incubator with 5% CO₂ at 37°C.

Immunohistochemistry (IHC)

RCN1 was investigated by IHC in cervical cancer tissues that were fixed in formalin and paraformaldehyde. PowerVisionTM Two-Step Histostaining Reagent (Zhongshan Golden Bridge Biotechnology, Beijing, China) was used for IHC staining. Cytoplasmic staining was independently evaluated by two pathologists in a double-blind fashion. Scores were assigned to the cytoplasm staining intensity (SI) as follows: 0 for negative, 1 for weak, 2 for moderate, or 3 for strong staining. Additionally, scores were assigned for the proportion (PP) of stained cells as follows: 0 (less than 5%), 1 (6–25%), 2 (26–50%), 3 (51–75%), and 4 (more than 75%). Finally, the histoscore (Q) was determined using the following formula: Q = SI×PP. For pathology evaluation, an immunoreactivity score (IRS) of 1–6 was considered low expression of RCN1, while IRS 8–12 was considered strong expression of RCN1.

Survival analysis

Cervical cancer samples were separated into high and low RCN1 groups using the optimal cutoff in the R survMisc package. Kaplan-Meier analysis was performed using log-rank test to investigate the relationship between the expression of RCN1 and survival.

Real-time quantitative PCR (RT-qPCR)

Total RNA was extracted from cervical cancer tissues or cell lines and reverse transcribed into cDNA. Then, RCN1 mRNA expression was assessed by RT-qPCR, as previously described. The primer sequences were as follows:

RCN1 FORWARD primer GGGAGGAGTTCACTGCCTTTCTG

RCN1 REVERSE primer TCATCCTGATCCACAAACCCATCC

GAPDH FORWARD primer CAGGAGGCATTGCTGATGAT

GAPDH REVERSE primer GAAGGCTGGGGCTCATTT

Western blot assay

As directed by the manufacturer, fresh tissues and cell extracts were generated using cell lysis reagent (Sigma-Aldrich, St. Louis, MO, USA), and the protein was measured using a BCA assay (P0010, Biyuntian Institute of Biotechnology, China). Equivalent amounts of protein were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and then detected using a rabbit monoclonal anti-RCN1 antibody (P0023D) from the Biyuntian Institute of Biotechnology in China. GAPDH was evaluated as a loading control. Experiments were performed in triplicate.

Vectors construction and transfection

GeneChem Corporation (Shanghai, China) designed and constructed lentiviral particles harboring shRNA targeting RCN1 (sh-RCN1) and negative control shRNA (sh-NC). The shRNA targeting sequences are provided in Supplementary Table S1. One day before transfection, the C33A or Hela cells were plated in six-well plates. The cells were transfected with the lentiviruses for 12 hours, and then they were selected in puromycin for seven days. Western blotting and PCR were used to validate RCN-1 overexpression and knockdown.

Cell Counting Kit 8 (CCK-8) assay

To determine cell viability, the Cell Counting Kit 8 (TAOSHU, Japan) was utilized. Rapidly proliferating cells were seeded onto 96-well plates, and the optical density at 450 nm was measured using the Gen5 system (BioTek, Winooski, VT, USA) once every 24 hours for five days.

Scratch tests

Control and RCN1 overexpression cells were seeded at the same concentration (5×10⁵ cells/well) in 6-well cell culture plates. After 24 h, a straight line was made perpendicularly in each well using a 200 µL lance tip. Serum-free medium was then added, and the plates were cultured an incubator with 5% CO2 at 37°C. The cell migration distance was measured under a light microscope at 0 and 24 hours.

Transwell assays

Transwell invasion assays were conducted using Transwell inserts (Corning, MA, USA) in 24-well plates, either with or without pre-coated Matrigel. Five hundred and forty-eight cells per well were seeded in the top chamber in 200 µL of 2% FBS and 500 µL of 20%. The medium in the lower chamber was supplemented with FBS. After a full day, the lower surface was fixed with methanol and stained with hematoxylin and eosin (H&E), while the upper surface was carefully removed using a cotton swab. Four fields of vision that were chosen at random were measured under a microscope.

IP-MS

C33A sh-RNA cell lines were detected and quantitatively analyzed by mass spectrometry, and the FLQ Intensity (relative quantitative signal values) was evaluated by T-testing. The FLQ Intensity Ratios in samples with p value < 0.05 were used as screening criteria to identify and screen highly possible interacting proteins.

Beads were washed three times by adding 500 µL TBS, vortexing, centrifuging for 30 s at 5000 g and removing the supernatant. Beads were digested in 100 µL of Buffer 1 (containing 2 M urea, 50 mM Tris-HCl pH 7.5 and 5 µg/mL Trypsin) for 30 m 27°C in a thermomixer, shaking at 800 rpm. After the initial digestion, the samples were centrifuged for 30 s at 7000 rpm, and the supernatant was removed and collected into fresh buffer. The beads were washed twice in 50 µL of buffer 2 (containing 2 M urea, 50 mM Tris-HCl pH 7.5 and 1 mM DTT), and the supernatants were pooled. The samples were left on the bench to continue digesting overnight at room temperature. Then, the samples were treated with 1 µL trifluoroacetic acid (TFA) to stop the digestion and were desalted in C18 stagetips. Tryptic peptides were desalted and centrifuged in a speedvac to dry. Then, Tryptic peptides were dissolved in 0.1% FA.

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)

For LC-MS/MS analysis, the peptides were separated by a 60 min gradient elution at a flow rate of 0.22 µl/min with a Thermo Scientific EASY-nLC 1000 HPLC system, which was directly interfaced with a Thermo Scientific Orbitrap Exploris 480 mass spectrometer that was operated in the data-dependent acquisition mode using Xcalibur 3.0 software. This included a single full-scan mass spectrum in the orbitrap (300–2000 m/z, 70,000 resolution) followed by 20 data-dependent MS/MS scans at 27% normalized collision energy (HCD).

MS/MS spectra from raw data were imported to Proteome Discoverer (version 3.0, Thermo Scientific), and a database search was performed using MS CHIMERYS™ with a combination of human proteins (uniprot reference, version 2022-02-03, 20,509 entries) as well as common contaminants (PD_Contaminants, 344 entries). The intensity from PD was further processed in the Perseus computational platform (v 1.6.7.0). LFQ intensity values were log2 transformed, and the samples were grouped into experimental categories. Proteins not identified in 3 out of 3 replicates in at least one group were also removed. Missing values were imputed using normally distributed values with a 1.8 downshift (log2) and randomized 0.3 width (log2) for whole matrix values. Statistical analysis was performed to determine which proteins were significantly enriched in the C33A cell compared to the C93 cell samples or isotype IgG control sample (t-test with permutation-based False Discovery Rate (FDR) = 0.05 and S0 = 0.1).

In vivo assays

Two sets of BALB/c-nu mice were utilized to monitor tumor growth: oe-C33A-NC [mice implanted with control C33A cells (n = 8) that were infected with scrambled oeRNA]; and oe-C33A-RCN1 [mice inoculated with RCN1 oeRNA-infected C33A cells (n = 8)]. The mice were subcutaneously injected with 5×10⁶ cells/100 µl. Every three days, the longest and shortest diameters of the developing tumors were measured using calipers, and the tumor volume (V) was calculated using the formula: V = (the longest diameter the shortest diameter2)/2. Cervical cancer metastasis was determined using a model of pulmonary metastasis. Live imaging was conducted once every 3 days, and the mice were euthanized 1 month after injection.

Statistical analysis

Categorical variables were quantified with n (%), whereas continuous variables were calculated using the meanSD of at least three independent experiments. Data analysis was done with SPSS 24.0 or Rstudio. Wilcoxon rank-sum tests were applied for two groups. Statistical significance was determined using the Student's two-tailed t-test, a parametric generalized linear model with random effects for the growth curve, and one-way ANOVA with LSD-t test for multiple groups. The Spearman's rank correlation test and the chi-square test were used in correlation analyses. In each two-sided statistical test, p value < 0.05 was considered statistically significant.

Identification of differentially expressed proteins by proteomic and bioinformatics methods

To evaluate differentially expressed proteins in cervical cancer, we performed label-free mass spectrometry (LC-MS/MS) of 6 paired cervical cancer (3 squamous cell carcinoma and 3 adenocarcinoma) and 6 normal tissue samples. A total of 547 up-regulated genes and 222 down-regulated genes were differentially expressed in both squamous cell carcinoma and adenocarcinoma (Fig. 1a). Heat maps of the top 20 elevated and decreased proteins are shown (Fig. 1b). Notably, this includes RCN1, a Ca2+-binding protein that has been shown to be overexpressed in a variety of other cancer types. According to KEGG function enrichment analysis, “protein processing in endoplasmic reticulum” was the primary pathway that was differentially regulated in cervical cancer (Fig. 1c). Given that RCN1 resides in the endoplasmic reticulum, these results are consistent with the possibility that RCN1 expression may contribute to cervical cancer.

RCN1 is highly expressed in cervical cancer

To verify the elevated expression of RCN1 in cervical cancer, we assessed the degree of RCN1 expression in 64 cervical cancer samples and nontumor tissues by immunohistochemistry (IHC) analysis. The results revealed that RCN1 is highly expressed in both squamous carcinoma and adenocarcinoma as compared to normal cervix tissues (Fig. 2a). These findings were confirmed by RT-qPCR and Western blot analyses (Fig. 2b, c). Furthermore, RCN1 was expressed at higher levels in cervical cancer cell lines (C33A, Hela, and SiHa) as compared to normal cervical epithelial cells (N) (Fig. 2d). These results confirm the elevated expression of RCN1 in cervical cancer.

Poor prognosis is indicated by high expression of RCN1 in cervical cancer

To further elucidate the clinical importance of RCN1 in cervical cancer, we assessed the association between RCN1 expression and clinicopathological features of cervical cancer using Fisher's exact test. Based on the Immunoreactivity score (IRS) from the IHC assays, we divide the cervical cancer tissue samples into those with high (51.6%, 33/64) and low (48.4%, 31/64) RCN1 expression. A positive association of high RCN1 expression was observed with tumor lymph node metastasis (p = 0.039) and recurrence (p = 0.018); however, a correlation was not observed with age, tumor size, differentiation, FIGO 2018 stage, or pathological tumor type (Table 1).

Table 1 Relationships between clinicopathological features and RCN1 expression in cervical cancer

Feathers	Total (n = 64)	Low (n = 31)	High (n = 33)	p-value
Age				0.817
≤50	29	16	13
>50	35	15	20
Tumor size				0.697
<4 cm	42	19	23
≥4 cm	22	12	10
Differentiation				0.560
Highly and moderately	47	22	25
Lowly	17	9	8
Lymphatic metastasis No	57	29	28	0.039*
Yes	7	2	5
FIGO 2018 stage				0.671
I	41	29	12
II-III	23	10	13
Recurrence				0.018*
Yes	8	2	6
No	56	29	27
Pathological				0.561
Squamous carcinoma	44	247	20
Adenocarcinoma	20	7	13

For additional prognostic verification, we evaluated RCN1 expression according to data in the TCGA database. There was a statistically significant difference in the disease-free survival and overall survival of patients with cervical cancer who had high vs. low expression of RCN1 (Fig. 3). These results suggest that high RCN1 expression in cervical cancer patients may be a useful prognostic marker for metastasis, recurrence and survival.

We have removed the table cell "RCN1 expression", which was the only cell in the first line.

Patients with cervical cancer who expressed high levels of RCN1 in the TCGA database showed a shorter disease-free survival time and a shorter overall survival time (p < 0.05) than patients who expressed low levels of RCN1

RCN1 promotes cervical cancer cell invasion, migration, and proliferation

To investigate the role of RCN1 in cervical cancer, we knocked down RCN1 in C33A and Hela cervical cancer cells (Fig. 4a, b). Cell counting kit-8 (CCK8) assays demonstrated that RCN1 knockdown inhibited cervical cancer cell proliferation. (Fig. 4c, d). Furthermore, RCN1 knockdown decreased the migratory and invasive characteristics of cervical cells, as indicated by Transwell and cell wound scratch assays (Fig. 4e–h).

For additional verification, we overexpressed RCN1 in C33A and Hela cells (Fig. 5a, b). CCK-8 assays demonstrated that RCN1 overexpression promotes cervical cancer cell proliferation (Fig. 5c, d). Furthermore, scratch tests and Transwell assays revealed that RCN1 overexpression markedly increases migration and invasion. (Fig. 5e–h). These findings confirm that RCN1 expression promotes cervical cancer cell growth and metastasis.

RCN1 binds KIF14 in cervical cancer cells

To further investigate proteins that interact with RCN1 in cervical cancer cells, we performed immunoprecipitation tandem mass spectrometry (IP-MS) quantitative difference comparison. A total of 345 proteins were significantly enriched and bound to RCN1 in shRCN1 vs shNC C33A cells (Fig. 6a); and 100 proteins were significantly enriched in the RCN1 antibody vs IgG group (Fig. 6b). At the intersection, 20 proteins with RCN1 binding specificity were identified (Fig. 6c). This includes, KIF14, a downstream protein of RCN1 that promotes phosphorylation of AKT, leading to malignant behavior of cervical cancer.

RCN1 promotes cervical cancer cell growth and metastasis in vivo

To determine whether RCN1 expression regulates cervical cancer progression in vivo, we generated a cervical cancer model using BALB/c-nu mice injected with control C33A cells or C33A cells overexpressing RCN1. The group with upregulated RCN1 had a higher average tumor volume and more lung metastasis (Fig. 7a, b). These results confirm that RCN1 promotes cervical cancer growth and metastasis in vivo.

Despite the availability of protective vaccines, cervical cancer is one of the most significant gynecological issues. Its high incidence and death rate largely are attributed to countries with low and medium incomes (LaVigne et al. 2017). China and India account for over a third of the cervical burden worldwide, with 106 000 cases and 48 000 deaths in China and 97 000 cases and 60 000 deaths in India each year (Arbyn et al. 2020). Most cervical cancer patients who receive contemporary treatment are cured; however, 13% of individuals with cervical cancer receive a diagnosis at an advanced stage. For metastatic cervical cancer, the 5-year survival rate is only 16.5% (Li et al. 2016). Even with pelvic dissection, the 5-year survival rate for individuals with R1 resection following recurrent cervical cancer is close to zero (Höckel and Dornhöfer 2006; Marnitz et al. 2006). Because of the poor prognosis and lack of available therapeutic options, recurrent cervical cancer remains a significant challenge (Cohen et al. 2019). Therefore, finding reliable molecular indicators of cervical cancer malignancy is crucial.

In this study, we detected the proteins in clinically collected cervical cancer specimens using LC-MS/MS technology and conducted differential protein screening using bioinformatics approaches. In KEGG functional enrichment analysis, "protein processing endoplasmic reticulum", "proteasome", "phagosome", "spliceosome" and "complement and coagulation cascade" were the top five pathways. The endoplasmic reticulum is linked to several cellular processes, including protein synthesis, transcription, cell maturation, secretion, membrane protein folding, and Ca2 + homeostasis. Furthermore, the endoplasmic reticulum is a crucial regulator of cell homeostasis (Stefan et al. 2011; Braakman and Bulleid 2011). Various endogenous or exogenous stimuli, such as hypoxia, nutrient deficiency, and chemotherapy drugs, can interfere with or disrupt endoplasmic reticulum homeostasis, triggering a cell state called "endoplasmic reticulum stress (ERS)." To overcome stress and restore protein stability, ERS activates the unfolded protein response (UPR). This initiates a cascade of subsequent signals to preserve endoplasmic reticulum homeostasis (Hetz et al. 2020). ERS can be induced by hypoxia, hypoglycemia, chemotherapy drugs or other environmental stimuli during the growth, leading to invasion and metastasis of tumor cells (Zheng et al. 2019). Tumor cells are considerably less sensitive to chemotherapeutic medications in this stage (Zhu et al. 2019; Kong et al. 2020). Therefore, the identification of these KEGG pathways is consistent with a role for ERS in contributing to the poor response to treatment in the advanced stages of cervical cancer.

We also identified the Ca2+-binding protein RCN1 as a differentially upregulated protein in cervical cancer. RCN1 regulates Ca2+-dependent activity in the lumen of the endoplasmic reticulum. Our study is the first to evaluate its role in cervical cancer, but prior research on RCN1 has shown that the gene is linked to non-small cell lung cancer, liver cancer, colorectal cancer, and breast cancer. In addition, current studies on the RCN1 pathway focus on ERS and other endoplasmic reticulum-related pathways. These findings are consistent with the possibility that RCN1 may promote the development of cervical cancer through ERS (Liu et al. 2018). We confirmed that RCN1 is highly expressed in cervical cancer tissues and cell lines. According to our research, patients with cervical cancer who express high levels of RCN1 have a worse prognosis and a greater likelihood of lymph node metastases. Notably, we demonstrated that RCN1 promotes tumor growth in xenograft mice and is essential for the effective spread of cervical cancer cells to the lung and peritoneal cavity. Our investigation links RCN1 to unfavorable outcomes in cervical cancer patients for the first time, thus providing insight into mechanisms that could lead to new strategies for intervention.

In this study, we also examined potential downstream targets of RCN1 by using IP-MS technology to screen for interacting proteins. Among the putative RCN1 binding partners, KIF14 acts as an oncogene in prostate cancer and has been demonstrated to be a novel and useful predictive biomarker (Zhang et al. 2017). Furthermore, it has been documented that through the activation of Akt, KIF14 has an oncogenic role in glioma/glioblastoma and functions as a potential molecular target and prognostic marker for human gliomas (Wang et al. 2013; Huang et al. 2015). It is well established that activated PI3K/AKT signaling promotes invasion, migration, and EMT of tumor cells (Daisy Precilla et al. 2022; Mortazavi et al. 2022; Paskeh et al. 2023). Therefore, our findings are consistent with the possibility that by specifically activating KIF14, RCN1 may contribute to the malignant behavior of cervical cancer.

In summary, using LC-MS/MS, we discovered that RCN1 is significantly expressed in cervical cancer tissues. The elevated expression level of RCN1 was confirmed in vivo, and additional in vitro and in vivo studies demonstrated its promotion of tumor invasion, growth, and metastasis. Subsequently, IP-MS indicated that RCN1 may target KIF14, which provides a potential mechanism for its involvement in the malignant progression of cervical cancer. Research has demonstrated that KIF14 can stimulate the PI3K/AKT signaling pathway to encourage tumor cell invasion, migration, and EMT (Meng and Zhang 2024), and future experiments will further investigate the putative role of this signaling pathway.

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Ethics approval

This study was performed in line with the Review Board of the Xuzhou Central Hospital. Approval was granted by the Xuzhou Medical University Institutional Animal Care and Use Committee (No. XZXY-LJ-20210513-052).

Consent to participate

According to its retrospective nature and in line with the ethics committees approval, written patient consent was not applicable to this study. This is in line with local ethical standards

Consent to publication

All the authors agree for the publication.

Funding

This work was supported by the Xuzhou Medical University affiliated hospital development fund surface project (XYFM202206), Xuzhou Health Commission Special Fund Planning Project (NO. 2019TD005), the Xuzhou science and technology project (KC23181).

Author Contribution

BZ, Y-YLand QW participated in the study design. J-YZ, LC, X-PZ ,M-Y C and J-BZ searched the databases and conducted the in vitro and in vivo experiments. Y-NZ,HC and Y-YL helped draft the manuscript. BZ and QW carried out the statistical analysis of the data.

Acknowledgement

Thank you to the Pathology Department, Imaging Department, and Laboratory for providing auxiliary examination materials for this article, and thank you to the laboratory colleagues for their companionship.

Data availability

No datasets were generated or analysed during thecurrent study.

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No competing interests reported.

RCN1 binds KIF14 to promote the malignant development of cervical cancer

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Materials and methods

Patient enrollment

Label-free relative quantification proteomics

Cell culture

Immunohistochemistry (IHC)

Survival analysis

Real-time quantitative PCR (RT-qPCR)

Western blot assay

Vectors construction and transfection

Cell Counting Kit 8 (CCK-8) assay

Scratch tests

Transwell assays

IP-MS

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)

In vivo assays

Statistical analysis

Results

Discussion

Declarations

Competing interests

Ethics approval

Consent to publication

Funding

Author Contribution

Acknowledgement

Data availability

References

Additional Declarations

Status:

Version 1