Abstract

   Connector enhancer of kinase suppressor of Ras 2 (CNKSR2) is a scaffold
   protein that mediates mitogen-activated protein kinase pathways.
   However, the molecular function of CNKSR2 in cervical squamous cell
   carcinoma (CESC) remains unknown. This study aimed to characterize the
   role of CNKSR2 in patients with CESC. Immunohistochemistry revealed
   that the expression of CNKSR2 in CESCs is relatively low compared with
   that in normal cells. We also explored the gene expression profile of
   high- and low-CNKSR2 expression in patients with cervical cancer.
   Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and
   Genomes (KEGG) analysis showed that the expression of CNKSR2 was
   upregulated in synapse assembly, which was coordinately regulated using
   the cAMP signaling pathway and calcium signaling pathway. The
   correlation between CNKSR2 and cancer immune cell infiltration was
   investigated via single-sample gene set enrichment analysis (ssGSEA).
   High CNKSR2 expression was associated with better overall survival (OS)
   and disease-free survival (DFS). Interestingly, high CNKSR2 expression
   was a good predictor of the survival outcome in cervical cancer
   patients. Additionally, CNKSR2 expression was strongly correlated with
   diverse immune cells in CESCs, including NK cells and T cells. These
   findings suggest that CNKSR2 is correlated with prognosis and immune
   infiltration, laying the foundation for future studies on the
   functional role of CNKSR2 in CESC.

   Keywords: CNKSR2, cervical squamous cell carcinoma, synapse assembly,
   immune cell infiltration, prognostic value

Introduction

   Cervical squamous cell carcinoma (CESC) is a common malignant
   gynecologic tumor affecting thousands of women [35]^1. More than 500
   000 cases have been diagnosed worldwide [36]^2. CESC often originates
   from cervical intraepithelial neoplasia and is correlated with human
   papilloma virus (HPV) infection [37]^3^-[38]^5. The development of
   surgical and adjunct treatments has improved the quality of life of
   CESC patients [39]^6^-[40]^10, but many patients with CESC are
   diagnosed with advanced disease due to the technical difficulty of
   detection, resulting in poor survival outcomes [41]^11^,[42]^12.
   Therefore, a new prognostic value in the diagnosis of CESC and new
   therapeutic targets for improving the treatment outcome must be
   identified.

   Strategies to prevent CESC have been hampered by a limited
   understanding of the underlying mechanism of this disease. Clinicians
   have gained valuable experience in the pathological testing of CESC
   patients by cervical smear cytology, HPV examination and pathological
   biopsy in colposcopy [43]^13^,[44]^14. Evidence has confirmed that
   numerous genes are associated with independent prognostic factors in
   CESC [45]^15^-[46]^17. The scaffold protein CNKSR2, also known as
   MAGUIN and KSR2, is a negative component in tumorigenesis
   [47]^18^,[48]^19. Previous studies have demonstrated that CNKSR2 plays
   a role in some diseases, including breast cancer and thyroid carcinoma
   [49]^19^,[50]^20. However, the role of CNKSR2 in CESC remains unknown.
   Our study first revealed the functional role of CNSKR2 in CESC using
   The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx)
   database. At present, we have confirmed the effect of CNKSR2 on CESC,
   that is, high expression of CNKSR2 was associated with better survival
   in CESC patients. Enrichment analysis showed that a high-CNKSR2
   expression phenotype was correlated with the regulation of synapse
   assembly. Our results suggest that CNKSR2 serves as an important
   prognostic marker in CESC and an indicator of immune infiltration.

Material and methods

Data Acquisition and Gene Expression Profile Analysis

   The gene expression profile and clinical information on CESC were
   downloaded using UCSC XENA ([51]https://xenabrowser.net/datapages/)
   from TCGA ([52]https://portal.gdc.cancer.gov/) and the GTEx database.
   For data processing, we used RNA-Seq data from TCGA and the GTEx
   database in the TPM format that were uniformly processed using the Toil
   process [53]^21. First, we analyzed the expression level of CNKSR2 in
   304 CESC patients and 13 healthy women. Next, the RNA-Seq gene
   expression profile and clinical characteristics of 304 CESC patients
   were retained and further analyzed (Table [54]1).

Table 1.

   Baseline characteristics of CESC patients in TCGA
   Characteristic Level Patients (n=304)
   Age(years) 46.00 (38.00,56.25)
   Average Height(cm) 160.00 (157.00,165.00)
   Average Weight(kg) 70.00 (58.00,83.00)
   T stage (n/%) T1 140 (58.1%)
   T2 71 (29.5%)
   T3 20 (8.3%)
   T4 10 (4.1%)
   N stage (n/%) N0 133 (68.9%)
   N1 60 (31.1%)
   M stage (n/%) M0 116 (92.1%)
   M1 10 (7.9%)
   Clinical stage (n/%) Stage I 162 (54.5%)
   Stage II 69 (23.2%)
   Stage III 45 (15.2%)
   Stage IV 21 (7.1%)
   Radiation therapy (n/%) No 122 (40.1%)
   Yes 182 (59.9%)
   Primary therapy outcome (n/%) CR 181 (83.4%)
   PD 22 (10.1%)
   PR 8 (3.7%)
   SD 6 (2.8%)
   Race (n/%) Asian 20 (7.7%)
   Black or African American 30 (11.6%)
   White 209 (80.7%)
   Histological type (n/%) Adenosquamous 52 (17.1%)
   Squamous cell carcinoma 252 (82.9%)
   Histologic grade (n/%) G1 18 (6.6%)
   G2 135 (49.6%)
   G3 118 (43.4%)
   G4 1 (0.4%)
   Menopause status (n/%) Peri 25 (10.8%)
   Post 82 (35.5%)
   Pre 124 (53.7%)
   Birth control pill history (n/%) No 89 (56.7%)
   Yes 68 (43.3%)
   Presence of keratinizing squamous cell carcinoma (n/%) No 119 (39.1%)
   Yes 185 (60.9%)
   Smoker (n/%) No 144 (55.2%)
   Yes 117 (44.8%)
   PIK3CA status (n/%) Mut 82 (28.7%)
   WT 204 (71.3%)
   [55]Open in a new tab

Functional Enrichment Analysis

   To elucidate the significant biological process, cellular components
   and molecular function in the differential CNKSR2 expression groups,
   Gene Ontology (GO) analysis was performed by R programming of
   clusterProfiler (3.8.0) [56]^22. The enriched GO terms were selected
   using an adjusted P-value<0.05 and count>3. Additionally, we performed
   KEGG analysis to identify CNKSR2-related differentially expressed genes
   in pathway enrichment analysis with the selection criteria of a false
   discovery rate (FDR)<0.05.

Protein-Protein Interaction (PPI) Network Construction

   The PPI network was constructed using 673 differentially expressed
   genes using the STRING database ([57]http://www.string-db.org/) with an
   interaction score >0.4 [58]^23. We used Cytoscape 3.8.0 to visualize
   the PPI network, and differentially expressed genes were labeled in
   different colors [59]^24. Subsequently, the CNKSR2-related genes were
   analyzed using the Molecular Complex Detection (MCODE) plugin to
   identify the top 10 genes with the strongest interaction in the PPI
   network. Using topological algorithms including degree, bottleneck,
   closeness and betweenness, the hub genes in different clusters from the
   network were further screened using the CytoHubba plugin in Cytoscape
   [60]^25.

Immune Cell Infiltration Analysis

   Normalized CNKSR2 expression profiles for CESC projects from the TCGA
   database were collected and compared with different immunocyte
   signatures using the GSVA package from the R program based on the
   ssGSEA method [61]^26. ssGSEA classifies different immune cell
   infiltrations in tumors. Using the signatures of adaptive and innate
   immune cell types, we quantified the relative tumor infiltration levels
   of 24 types of immune cell types with published signature lists.

Survival Analysis and Hazard Model Construction

   To evaluate the prognostic value of CNKSR2, we used Cox regression and
   the Kaplan-Meier method. We calculated the overall survival and
   disease-specific survival rates of CNKSR2 in CESC patients using the
   survminer package 27. Multivariate Cox analysis was used to compare the
   influence of CNKSR2 and other clinicopathologic
   characteristics—including T stage, N stage, clinical stage, primary
   therapy outcome, radiation therapy, histological type, menopause
   status, histologic grade, and presence of keratinizing squamous cell
   carcinoma—on the survival of CESC patients from TCGA. According to the
   results of Cox regression, a nomogram model was used to calculate the
   predictive value of CNKSR2 in estimating the prognosis of CESC
   patients. We also performed a calibration plot to assess the
   effectiveness of the model.

Tissue Samples

   A total of 30 CESC patients undergoing cervical cancer radical surgery
   between 2020 and 2022 in the Affiliated Sir Run Run Shaw Hospital of
   Zhejiang University School of Medicine were included in this study.
   This study was approved by the institutional review board of our
   hospital. We have already got our ethical approval (Approval
   NO:2023-0153). All methods were performed in accordance with the
   relevant guidelines and regulations. All patients gave written informed
   consent.

   Patients' eligibility criteria: (i) cervical cancer patients and no
   other underlying diseases; (ii) undergoing cervical cancer radical
   surgery.

   Patients' exclusion criteria: (i) other malignant tumors such as breast
   cancers, ovarian cancer and so on. (ii) abnormal karyotype; (iii)
   endocrine or metabolic disorders; (iv) autoimmune diseases; (v)
   neurological diseases; (vi) improper drug treatment, exposure to
   chemicals or radiation.

Tissue immunohistochemical staining

   Immunohistochemistry was performed using formalin‐fixed
   paraffin‐embedded histologic sections using anti-CNKSR2 (1:200, Abcam,
   [62]Ab239026) antibodies. IHC staining was carried out according to the
   manufacturer's instructions. Then, Color was developed using
   3,3′-diaminobenzidine (DAB) for 5 min and histologic sections
   counterstained with Hematoxylin. Staining was visualized using a Nikon
   microscope.

Statistical Analysis

   R (v.3.6.3) was used to statistically analyze the expression level and
   other clinical parameters in CESC. The Wilcoxon rank-sum test was used
   to compare the differential expression of CNKSR2 in CESC samples from
   TCGA cohorts and the GTEx database. Furthermore, logistic regression
   was conducted to elucidate the relationship between clinical parameters
   and CNKSR2. To estimate the predictive value of CNKSR2 in CESC,
   receiver operating characteristic (ROC) curve analysis was performed,
   and the area under the curve (AUC) was calculated to determine the
   authenticity of the testing method.

Results

Deleted Expression of CNKSR2 in CESCs

   We initially evaluated the transcriptional level of CNKSR2 in multiple
   tumors from TCGA and the GTEx database. Analysis of multiple cancers
   revealed that compared to adjacent normal tissues, the mRNA expression
   of CNKSR2 was significantly lower in cancers—such as ovarian serous
   cystadenocarcinoma (OV), pancreatic cancer (PAAD), pheochromocytoma and
   paraganglioma (PCPG), prostate cancer (PRAD), rectal cancer (READ),
   skin melanoma (SKCM), gastric cancer (STAD), testicular cancer (TGCT),
   thyroid cancer (THCA), thymic cancer (THYM) and endometrial carcinoma
   (UCEC) (Figure [63]1A). Data from TCGA and the GTEx database indicated
   that CNKSR2 was extremely downregulated in CESCs in terms of mRNA
   expression (Figure [64]1B). The characteristics of CESC patients are
   listed in Table [65]1.

Figure 1.

   [66]Figure 1
   [67]Open in a new tab

   Comparison of CNKSR2 gene expression between cancers and normal tissues
   in the TCGA and GTEx cohorts. (A) Expression level of CNKSR2 in
   different cancers and normal tissues from the TCGA and GTEx cohorts.
   ^***P<0.001, ^**P<0.01, ns: no sense. (B) CNKSR2 expression level in
   CESC projects from TCGA and normal tissues from TCGA and GTEx cohorts.
   (c) CNKSR2 expression levels in CESC patients with different T stages.
   (D) CNKSR2 expression levels in CESC patients with different clinical
   stages. (E) CNKSR2 expression levels in CESC patients with different
   histologic types. (F) CNKSR2 expression levels in CESC patients with
   the presence of different keratinizing squamous cell carcinomas. TCGA,
   The Cancer Genome Atlas.

   Further subgroup analysis of multiple clinicopathological features of
   CESC samples showed that the deleted transcriptional levels was
   consistent with previous findings. The expression of CNKSR2 was
   significantly lower in CESC patients than in normal controls in
   subgroups based on T stage, clinical stage, histological type and
   keratinizing squamous cell carcinoma (Figure [68]1C-F). Additionally,
   high CNKSR2 expression was found in CESC patients with histological
   type (P<0.001) and keratinizing squamous cell carcinoma (P = 0.026)
   according to logistic analysis (Table [69]2). Therefore, CNKSR2
   expression may play a prominent role in CESC patients.

Table 2.

   Logistic regression of CESC patients with different CNKSR2 expression
   levels
   Characteristic Odds Ratio (OR) P value
   T stage (T2 & T3 & T4 vs. T1) 0.70 (0.42-1.18) 0.181
   N stage (N1 vs. N0) 0.79 (0.43-1.46) 0.455
   M stage (M1 vs. M0) 1.07 (0.28-4.04) 0.917
   Clinical stage (Stage II & Stage III & Stage IV vs. Stage I) 0.64
   (0.40-1.01) 0.057
   Primary therapy outcome (CR vs. PD & SD & PR) 2.04 (0.99-4.39) 0.059
   Histological type (squamous cell carcinoma vs. adenosquamous) 0.21
   (0.10-0.42) <0.001
   Histologic grade (G3 & G4 vs. G1 & G2) 1.02 (0.63-1.65) 0.927
   Presence of keratinizing squamous cell carcinoma (Yes vs. No) 1.70
   (1.07-2.71) 0.026
   PIK3CA status (Mut vs. WT) 1.60 (0.96-2.70) 0.074
   [70]Open in a new tab

Enrichment Analysis of CNKSR2 Co-expressed Genes in CESC

   To identify the CNKSR2-related biological process in CESC, we evaluated
   the CNKSR2 co-expression mode in the CESC cohort from TCGA. 744 genes
   (orange dots) were positively correlated with CNKSR2, and 134 genes
   were negatively correlated with CNKSR2 (Figure [71]2A). The top 10
   significant genes which positively and negatively associated with
   CNKSR2 were shown in the heat map (Figure [72]2B). CNKSR2 had a strong
   positive correlation with the expression of RP11-159H10.3 (r=0.50;
   P=1.09E-20), CCDC74B (r=0.49; P=1.02E-19), RNF150 (r=0.49; P=1.63E-19),
   ZCCHC18 (r=0.49; P=2.40E-19), and SLIT2 (r=0.48; P=7.69E-19).

Figure 2.

   [73]Figure 2
   [74]Open in a new tab

   Differentially expressed genes in the high- and low-CNKSR2 expression
   groups in the CESC cohorts. (A) Differentially expressed genes between
   different CNKSR2 expression groups. (B) CNKSR2-correlated gene
   expression in CESC cohorts. (C) KEGG pathway enrichment analysis of
   CNKSR2 coexpression genes. (D) Biological process terms of CNKSR2
   coexpression genes. (E) Cellular component terms of CNKSR2 coexpression
   genes. (F) Molecular function terms of CNKSR2 coexpression genes.

   GO terms and KEGG pathway analysis using the clusterProfiler package
   revealed that the cAMP signaling pathway and calcium signaling pathway
   were enriched (Figure [75]2C and Table [76]3). Additionally, GO
   analysis showed that CNKSR2 co-expressed genes primarily participate in
   the regulation of synapse assembly and are particularly expressed in
   synaptic membranes, glutamatergic synapses, intrinsic components of
   synaptic membranes, integral components of synaptic membranes and
   presynaptic membranes (Figure [77]2D-F). These results suggest the
   widespread impact of different expression levels of CNKSR2.

Table 3.

   Enrichment analysis of CNKSR2-correlated genes
   Term ID Description Counts
   KEGG pathways hsa04080 neuroactive ligand-receptor interaction 24
   hsa04971 gastric acid secretion 8
   hsa04024 cAMP signaling pathway 13
   hsa05033 nicotine addiction 5
   hsa04950 maturity onset diabetes of the young 4
   hsa04020 calcium signaling pathway 11
   hsa04973 carbohydrate digestion and absorption 5
   BP terms GO:0030900 forebrain development 31
   GO:0051963 regulation of synapse assembly 16
   GO:0051965 positive regulation of synapse assembly 13
   GO:0007416 synapse assembly 19
   GO:0021537 telencephalon development 22
   GO:1905606 regulation of presynapse assembly 8
   GO:0099174 regulation of presynapse organization 8
   GO:0099054 presynapse assembly 9
   CC terms GO:0097060 synaptic membrane 32
   GO:0099056 integral component of presynaptic membrane 12
   GO:0045211 postsynaptic membrane 25
   GO:0098793 presynapse 32
   GO:0099634 postsynaptic specialization membrane 13
   GO:0099060 integral component of postsynaptic specialization membrane
   11
   GO:0098948 intrinsic component of postsynaptic specialization membrane
   11
   GO:0098982 GABA-ergic synapse 10
   MF terms GO:0022803 passive transmembrane transporter activity 30
   GO:0015267 channel activity 29
   GO:0022838 substrate-specific channel activity 27
   GO:0008509 anion transmembrane transporter activity 22
   GO:0022839 ion gated channel activity 22
   GO:0005216 ion channel activity 25
   GO:0022836 gated channel activity 22
   GO:0015276 ligand-gated ion channel activity 13
   [78]Open in a new tab

Gene Co-Occurrence of CNKSR2 Alteration in CESC

   To further explore the gene co-occurrence of CNKSR2 in CESC, we
   analyzed the functional relationships of genetic risk factors (Figure
   [79]3A). The frequently correlated genes were dopamine receptor D2
   (DRD2; degree=19), adenylate cyclase 2 (ADCY2; degree=18), somatostatin
   receptor 2 (SSTR2; degree=12), proenkephalin (PENK; degree=21), opioid
   receptor kappa 1 (OPRK1; degree = 16), glutamate metabotropic receptor
   7 (GRM7; degree=13), G protein subunit alpha transducin 3 (GNAT3;
   degree=14), C-C motif chemokine ligand 25 (CCL25; degree=11),
   insulin-like 5 (INSL5; degree=9), and neuronal differentiation 1
   (NEUROD1; degree=22) (Figure [80]3B). Three clusters had significant
   co-occurrence with CNKSR2 (Figure [81]3C-E).

Figure 3.

   [82]Figure 3
   [83]Open in a new tab

   CNKSR2 co-occurrence profiles in CESC. (A) Network of co-occurrence
   genes along with CNKSR2. (B) Top 10 CNKSR2-related genes in the
   network. (C)-(E) Three clusters with high interaction degrees were
   calculated using CytoHubba.

Validating expression and clinical prognostic value by immunohistochemical

   To determine the role of CNKSR2 in the clinical progression of CESC, we
   performed immunohistochemical analysis on the 30 CESC tissue and normal
   adjacent tissues samples. Our results showed that CNKSR2 levels are
   elevated in normal adjacent tissues compared to CESC tissue (Figure
   [84]4A).Then we compared the differences in the survival rates
   considering the stage and CNKSR2 expression by log-rank analysis in
   Kaplan-Meier curves. We found that the disease-specific survival rate
   (HR=0.59; 95% CI: 0.34-1.01) was higher in patients with high CNKSR2
   expression than in those with low CNKSR2 expression in TCGA (Figure
   [85]4B). Additionally, patients with high CNKSR2 expression had a
   higher overall survival rate than those with low CNKSR2 expression in
   TCGA (HR=0.54; 95% CI: 0.33-0.87; P=0.012; Figure [86]4C). The survival
   rate was higher in patients with high CNKSR2 expression than in those
   with low CNKSR2 expression in the histologic grade (G2&G3) group in the
   CESC project of the TCGA cohort (HR: 0.57; 95% CI: 0.33-0.97; P=0.039;
   Figure [87]4D). Additionally, the survival rates were higher in
   patients with high CNKSR2 expression in the clinical stage (Stage I &
   Stage II) group (HR: 0.46; 95% CI: 0.25-0.83; P=0.010) (Figure [88]4E)
   and CESC patients with keratinizing squamous cell carcinoma (HR=0.50;
   95% CI: 0.29-0.86; P=0.012; Figure [89]4f).

Figure 4.

   [90]Figure 4
   [91]Open in a new tab

   (A) CLDN10 expression in PTC tissues and adjacent normal tissues
   assayed by IHC. The scales bar to indicate 50 μm. (B)-(C)
   Characteristics of the clinical parameters and CNKSR2 expression in
   CESC patients from the TCGA cohorts. Kaplan-Meier plot regarding
   disease-specific survival (B) and overall survival (C) in the high- and
   low-CNKSR2 expression groups from the CESC cohorts. (D)-(F) Subgroup
   survival analysis in G2 and G3 (D), Stage I and Stage II (E) and
   keratinizing squamous cell carcinoma (F) groups in high- and low-CNKSR2
   groups from the CESC cohorts.

CNKSR2 Expression is Associated with Survival Outcome

   CNKSR2 was also identified as a possible prognostic biomarker using a
   multivariate hazard model (Figure [92]5A). CNKSR2 had prognostic
   significance in TCGA (Table [93]4; HR: 0.302; 95% CI: 0.115-0.792;
   P=0.015). Based on multivariate analysis, we applied N stage, primary
   therapy outcome and CNKSR2 expression to our nomogram model, which
   indicated that CNKSR2 has prognostic value in CESC (Figure [94]5B).
   Regarding the effectiveness of CNKSR2 as a biomarker in CESC, we
   examined the AUC values in the ROC curves for TCGA (Figure [95]5C). ROC
   analysis revealed that CNKSR2 had stable predictive values in CESC
   patients (AUC=0.820; 95% CI: 0.753-0.886).

Figure 5.

   [96]Figure 5
   [97]Open in a new tab

   (A) Multivariate analysis of the CESC project in TCGA. (B) Nomogram
   model regarding the N stage, primary therapy outcome and CNKSR2 gene
   expression in the TCGA cohorts. (C) Receiver operating characteristic
   (ROC) curves regarding CNKSR2 gene expression in TCGA.

Table 4.

   Prognostic value of CNKSR2 and other clinical parameters in the TCGA
   cohorts in the multivariate hazard model
   Univariate analysis Multivariate analysis
   Characteristic HR (95% CI) P value HR (95% CI) P value
   T stage (T2 & T3 & T4 vs. T1) 1.846 (1.045-3.260) 0.035 1.203
   (0.455-3.185) 0.709
   N stage (N1 vs. N0) 2.695 (1.358-5.349) 0.005 2.660 (1.082-6.541) 0.033
   Clinical stage (Stage II & Stage III & Stage IV vs. Stage I) 1.429
   (0.896-2.280) 0.134
   Primary therapy outcome (CR vs. PD & SD & PR) 0.074 (0.040-0.138)
   <0.001 0.171 (0.062-0.470) <0.001
   Radiation therapy (Yes vs. No) 1.153 (0.681-1.951) 0.596
   Histological type (squamous cell carcinoma vs. adenosquamous) 1.010
   (0.530-1.926) 0.976
   Menopause status (post vs. pre & peri) 1.275 (0.744-2.185) 0.376
   Histologic grade (G3 & G4 vs. G1 & G2) 0.889 (0.527-1.502) 0.661
   Smoker (Yes vs. No) 1.470 (0.900-2.401) 0.124
   Birth control pill history (Yes vs. No) 0.677 (0.326-1.404) 0.294
   Keratinizing squamous cell carcinoma present (Yes vs. No) 1.395
   (0.813-2.394) 0.227
   Age (>50 vs. ≤50) 1.317 (0.825-2.101) 0.248
   Height (>160 vs. ≤160) 1.092 (0.633-1.883) 0.752
   Weight (>70 vs. ≤70) 0.736 (0.446-1.214) 0.23
   Race (Asian & Black or African American vs. White) 0.841 (0.427-1.658)
   0.618
   PIK3CA status (Mut vs. WT) 1.011 (0.599-1.707) 0.967
   CNKSR2 (High vs. Low) 0.536 (0.330-0.869) 0.012 0.302 (0.115-0.792)
   0.015
   [98]Open in a new tab

Immune Cell Infiltration in CESCs with Different CNKSR2 Expression

   To explore the difference in the immune environment in CESC patients
   with differential expression of CNKSR2 in the TCGA cohort, the data
   were analyzed. Different immune cell infiltration occurred in CESC
   patients with differential CNKSR2 expression (Figure [99]6A). The
   number of NK cells, dendritic cell leakage, T cells, mast cells and
   eosinophils in the high-CNKSR2 expression cohort were all higher than
   those in the low-CNKSR2 expression cohort (Figure [100]6B).

Figure 6.

   [101]Figure 6
   [102]Open in a new tab

   Immune cells in CESC tissues derived from the TCGA cohorts. (A)
   Correlation of different immune cells in the low- and high-CNKSR2
   expression CESC cohorts in the TCGA database. (B) Comparison of
   different immune cells in high- and low-CNKSR2 expression groups in the
   CESC cohorts in the TCGA database.

Discussion

   CNKSR2 is a scaffold gene that participates primarily in signal
   transduction and is a protein that mediates the mitogen-activated
   protein kinase pathway downstream of Ras. CNKSR2 is associated with
   different hereditary diseases, including nonsyndromic X-linked
   intellectual disability, mental retardation and undetermined
   early-onset epileptic encephalopathy. In the present study, we first
   revealed that CNKSR2 was correlated with CESC tumor tissue.
   Additionally, a similar association was found in multiple cancers from
   TCGA.

   Previous studies have revealed that the Smurf2 E3 ubiquitin ligase may
   induce CNKSR2 in cancer cells and participate in cancer cell
   proliferation [103]^18. We performed an enrichment analysis to explore
   the CNKSR2 coexpression genes in cervical cancer progression. CNKSR2
   coexpression genes participate primarily in regulating synapse assembly
   and may couple signal transduction to membrane or cytoskeletal
   remodeling. During tumorigenesis and progression, families of
   immunosuppressive molecules inhibit the activation of tumor reactive T
   cell receptors through immune synapse isolation [104]^28. Additionally,
   NK cells activate T cells by activating dendritic cell precursors to
   generate immune synapses [105]^29. For example, BTN3A1 inhibits the
   activation of tumor-killing αβ T cells and γδ T cells by preventing the
   N-glycosylation process in tumor development. Thus, the development of
   CD277-specific antibodies led to a new therapeutic strategy for tumor
   chemotherapy resistance by targeting BTN3A1 in cancer therapy [106]^28.
   Notably, the efficacy of CAR-modified immune cells (including CAR-T and
   CAR-NK cells) in tumor immunotherapy can also be determined by the
   quality of immune synapses [107]^30. Various immune cells infiltrated
   cervical cancer with high CNKSR2 expression. Therefore, we infer that
   CNKSR2 may participate in the formation of synapses between immune
   cells in the process of tumor immunity, promoting the function of tumor
   immunity and improving the survival outcome of cervical cancer.

   CNKSR2 is involved mainly in synaptic assembly in the high-CNKSR2
   expression group through enrichment analysis. High synapse quality can
   be used as a marker of a good prognosis. Similarly, we assessed CNKSR2
   using various prognostic models and survival curves to evaluate the
   prognostic value of CNKSR2 and found that CNSKR2 has excellent
   effectiveness as an independent prognostic indicator. CNKSR2 is also
   critical in the application of distinguishing cervical cancer from
   healthy women in tumor prediction models in ROC tests (AUC=0.820).
   Therefore, we hypothesized that CNKSR2 might mediate signal
   transduction in tumors through synaptic aggregation, thereby inhibiting
   tumor development. CNKSR2 expression in patients with thyroid papillary
   carcinoma is often increased, particularly in in vitro experiments
   revealing that the knockdown of CNKSR2 inhibits ERK phosphorylation and
   Notch signaling transduction decreases, resulting in damaged tumor
   proliferation [108]^19. Furthermore, the E3 ubiquitin ligase SMUF2
   inhibits the invasion and migration of breast cancer mainly in a
   scaffold protein CNKSR2-dependent manner [109]^18, also suggesting that
   CNKSR2, as a scaffold protein, participates in RAS-dependent signaling
   pathways, highlighting that CNSR2 not only is involved in the signal
   transduction of kinases but also affects the function of ubiquitin
   ligases. Thus, the pathogenesis and mechanism of CNKSR2 in cervical
   cancer warrant further exploration.

   Additionally, considering the infiltration of immune cells, cervical
   cancer patients with high CNKSR2 expression can increase the
   possibility of multiple immune cell infiltrations in the tumor
   environment. We found that the proportion of many immune cells involved
   in tumor immunity, such as NK cells, T cells and dendritic cells, were
   significantly involved in antigen presentation. Interestingly, among
   the immune cells that infiltrated cervical cancer, the increased
   proportion of activated memory CD4+ T cells has a good survival
   prognosis, and vice versa. Additionally, the combination of NK cells,
   activated CD4+ T cells and activated mast cells can improve the ability
   to predict the overall survival of patients with cervical cancer
   [110]^31. Presently, various chemotherapeutic drugs for gynecological
   malignant tumors have been suggested to improve the antibody-dependent
   cell-mediated cytotoxicity (ADCC) function of NK cells and exert their
   antitumor ability, such as rituximab, herceptin, disialoganglioside
   (GD2), cetuximab and panitumumab[111]^32. However, the
   interrelationship among NK cells, mast cells and T cells in the immune
   microenvironment of cervical cancer remains a topic worth exploring.
   Additionally, the effects of high CNKSR2 expression and increased
   numbers of NK cells, mast cells and T cells on synaptic formation
   between different immune cells and tumor immune escape in cervical
   cancer have not been studied, warranting further study.

Conclusion

   Our study confirmed that CNKSR2 participates in synaptic assembly,
   particularly in cervical cancer with high CNKSR2 expression in various
   infiltrating immune cells, and can be used as a good tool for the
   prognosis of cervical cancer patients. Furthermore, the cAMP signaling
   pathway and calcium signaling pathways, which were reported to play a
   role in cervical cancer, were also enriched in cervical cancer tissues
   with high CNKSR2 expression. However, we only used bioinformatics
   algorithms to estimate the biological role of CNKSR2 in cervical
   cancer, and we could not directly observe the biological function of
   CNKSR2 in cervical cancer. Further experimental verification should be
   performed to observe the biological effects of CNKSR2 on cervical
   cancer.

Acknowledgments