CCT7 indicates a poor prognosis and is associated with immune infiltration in colonic adenocarcinoma

CCT7 indicates a poor prognosis and is associated with immune infiltration in colonic adenocarcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CCT7 indicates a poor prognosis and is associated with immune infiltration in colonic adenocarcinoma Wenxu Li, Qizhong Shi, Yonghui Mu, Chenglei Li, Wenchao Zhao, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7271196/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Journal of Molecular Histology → Version 1 posted 13 You are reading this latest preprint version Abstract Objective CCT7, a member of the t-complex polypeptide 1 chaperone family, facilitates protein folding in an ATP-dependent manner. To date, the role of CCT7 in the onset and progression of malignant tumors remains unclear. This study investigated the expression of CCT7 in colonic adenocarcinoma (COAD) and its role in the initiation and development of COAD. Methods The bioinformatic databases were used to examine the CCT7 expression in COAD, and the results were verified using human clinical specimens by immunohistochemistry (IHC) assay. The association of CCT7 expression with prognosis was evaluated by Kaplan-Meier method and Cox regression analysis. Gene Ontology-Biological Process (GO-BP) enrichment analysis was used to investigate the potential biological functions of CCT7 in COAD. CCK-8, colony formation and Transwell assays were carried out to explore the effect of CCT7 on proliferation, migration and invasion of human COAD cells. The correlations of CCT7 expression with immune infiltration, immunotherapy and drug sensitivity were determined by single sample gene set enrichment analysis (ssGSEA) and correlation analysis. Results CCT7 expression was up-regulated statistically in COAD tissues compared with normal colonic tissues ( P < 0.05) and high expression of CCT7 predicted poor prognosis of COAD patients ( P < 0.05). GO-BP enrichment analysis revealed that CCT7 was mainly involved in the processes of cell proliferation and microtubule activities( P < 0.05), and down-regulation of CCT7 inhibited the proliferation, migration and invasion of COAD cells ( P < 0.05). CCT7 was negatively associated with infiltration of most immunocytes and the scores for PD-1 and CTLA-4 therapy ( P < 0.05). Moreover, drug sensitivity analyses showed that CCT7 affected the sensitivity of COAD samples to several anti-cancer drugs ( P < 0.001). Conclusion CCT7 may function as an oncogene to promote the malignant phenotype of COAD, and serve as a promising biomarker for prognosis as well as a reference for clinical treatment in COAD. colonic adenocarcinoma CCT7 prognosis immune infiltration drug sensitivity Wenchao Zhao [email protected] Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Colorectal cancer (CRC) ranks as the third most common gastrointestinal malignancy globally(Morgan et al. 2023 ). The International Agency for Research on Cancer (IARC) estimated about 20 million new cancer cases and 9.7 million cancer-related deaths worldwide in 2022. Colorectal cancer accounted for 9.6% of new cancer cases and 9.3% of cancer-related deaths, with approximately 2 million new cases and an estimated 900,000 fatalities(Bray et al. 2024 ). Colonic adenocarcinoma (COAD) is the predominant pathological subtype of CRC(Yang et al. 2022 ). Despite significant progress in cancer treatment, the overall survival (OS) for COAD patients remains suboptimal. Thus, there is an urgent need to elucidate the pathogenesis of COAD and identify reliable prognostic biomarkers and therapeutic targets. The chaperonin containing t-complex 1 (CCT) is a molecular chaperone present in the cytoplasm of all eukaryotes, comprising eight distinct subunits designated as CCT1-8(Brackley and Grantham 2009 ; Vallin and Grantham 2019 ). Actin and tubulin, the main folding substrates of CCT, require interaction with CCT for proper folding both in vivo and in vitro(Valpuesta et al. 2002 ). Given their close association with cancer development, studying CCT's role in cancer is important(Khromova et al. 2024 ; Parker et al. 2014 ). Previous studies reveal CCT3 fuels lung adenocarcinoma progression via glycolysis and EIF3G-mediated translation(Chen et al. 2022 ). CCT4 enhances glucose metabolism and chemotherapy resistance in esophageal squamous cell carcinoma through the AMPK/AKT/NRF2 pathway(Fang et al. 2022 ). Roles of CCT1, CCT2, CCT5, CCT6A, and CCT8 in cancer have also been documented(Cai et al. 2022 ; Chang et al. 2020 ; Li et al. 2022 ; Tang et al. 2020 ; Yang et al. 2018 ). However, CCT7's role, especially in COAD, remains poorly understood. Bioinformatics analyses show elevated CCT7 mRNA levels in colorectal cancer tissues compared to adjacent normal tissues(Lim et al. 2022 ), but its function in COAD is unclear and warrants further investigation. Tumor development is closely associated with the tumor microenvironment (TME), with immune infiltrating cells as key TME components gaining increasing attention(Erasha et al. 2025 ; Guo and Xu 2024 ). Immune checkpoints, molecules expressed on immune cells, play an important role in regulating immune cell activity and affecting tumor prognosis(Arafat 2024; Franzin et al. 2020 ). The emergence and significant efficacy of immunotherapy have enhanced the value of immune-related biomarkers. However, little is known about the relationship between CCT7 and immune infiltrating cells or immune checkpoints in COAD. This study aims to explore CCT7 expression in COAD, its role and mechanisms in COAD development, its association with COAD immune infiltration and its influence on immunotherapy and chemotherapy. Materials and methods Patients and tissue samples All clinical tissue specimens used in this study were sourced from the Second Affiliated Hospital of Zhengzhou University and verified by histopathology. We conducted immunohistochemical staining on 60 COAD tissues and their paired adjacent normal colon tissues. Written informed consent was obtained from the patients for the use of these clinical materials in research, and approval was granted by the Institutional Research Ethics Committee of the Second Affiliated Hospital of Zhengzhou University. The study adhered to all relevant ethical regulations regarding human participants. The clinical characteristics of COAD patients are shown in Table 1 . Table 1 Clinical characteristics of COAD patients from COAD clinical specimens Characteristics Number of samples(%) Age(years) ≤ 65 30(50.0) > 65 30(50.0) Gender Male Female M stage M0 M1 N stage N0 N1 N2 T stage T1 T2 T3 T4 Tumor location Right Left Loss of MMR protein No Yes Lymphatic invasion No Yes Non nodal tumor deposits No Yes PostopTreat No Yes Venous invasion No Yes Grade Well differentiated Moderately differentiated Poorly differentiated Overall survival Alive Dead 30(50.0) 30(50.0) 54(90.0) 6(10.0) 39(65.0) 15(25.0) 6(10.0) 4(6.7) 9(15.0) 40(66.6) 7(11.7) 30(50.0) 30(50.0) 43(71.7) 17(28.3) 28(46.7) 32(53.3) 43(71.7) 17(28.3) 14(23.3) 46(76.7) 43(71.7) 17(28.3) 11(18.3) 40(66.7) 9(15.0) 42(70.0) 18(30.0) TCGA and GEO Data Collection and Processing The RNA-sequencing data of COAD and the related clinical data (Table 2 ) were obtained from The Cancer Genome Atlas (TCGA) ( https://portal.gdc.cancer.gov/repository)(Weinstein et al. 2013 ). TCGA-COAD was used for the investigation of CCT7 expression and its prognostic value, Gene Ontology-Biological Process (GO-BP) enrichment analysis, immune-related analysis, and drug sensitivity. Table 2 Clinical characteristics of COAD patients from TCGA database Characteristics Number of samples(%) Age(years) ≤ 68 153(45.5) > 68 183(54.5) Gender Male Female M stage M0 M1 N stage N0 N1 N2 T stage T1 T2 T3 T4 Tumor location Right Left Unknown Loss of MMR protein No Yes Unknown Lymphatic invasion No Yes Unknown Non nodal tumor deposits No Yes Unknown Cancer status Tumor free With tumor Unknown PostopTreat No Yes Unknown Venous invasion No Yes Unknown Overall survival Alive Dead 180(53.6) 156(46.4) 280(83.3) 56(16.7) 201(59.8) 76(22.6) 59(17.6) 8(2.4) 60(17.9) 231(68.8) 37(11.0) 140(41.7) 112(33.3) 84(25) 230(68.5) 37(11.0) 69(20.5) 176(52.4) 130(38.7) 30(8.9) 133(39.6) 26(7.7) 177(52.7) 206(61.3) 55(16.4) 75(22.3) 184(54.8) 106(31.5) 46(13.7) 221(65.8) 74(22.0) 41(12.2) 268(79.8) 68(20.2) Microarray data of GSE39582, GSE41258, GSE37364, GSE44076 and GSE17538 were retrieved from Gene Expression Omnibus (GEO) ( https://www.ncbi.nlm.nih.gov/geo/)(Marisa et al. 2013 ; Sheffer et al. 2009 ; Smith et al. 2010 ; Solé et al. 2014 ; Valcz et al. 2014 ). GSE39582 was applied for CCT7 expression and GO-BP enrichment analysis. GSE39582, GSE44076 and GSE41258 were analyzed for CCT7 expression. GSE17538 was taken for survival analysis. Cell lines and culture The human COAD cell lines (RKO, HCT-116) and the normal colon epithelial cell line (NCM460) were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). RKO and HCT-116 cells were cultured in 1640 medium, while NCM460 cells were cultured in DMEM medium. All media were supplemented with 10% fetal bovine serum (FBS) (Genial Biologicals, Inc.) and 1% penicillin-streptomycin mixture. Cells were incubated in a humidified atmosphere with 5% CO₂ at 37°C. Construction of siRNA knockdown target gene cell lines Transient transfection siRNA (siCCT7, siNC) was provided by GenePharma (GenePharma, Shanghai, China). Cultured COAD cells (RKO, HCT-116) were seeded in a six-well plate at equal densities using complete medium. When cell confluence reached approximately 50%, the mixed reagent was mixed with 100 µL of buffer per well, with 5.85 µL of transfection reagent (Polyplus-transfection®, jetPRIME®, France) added. The mixture was incubated with 4.5 µL of siRNA at room temperature for 10 minutes and then added to the six-well plate. The siRNA targeting CCT7 used in this study had the following sequences: sense 5'-CAUUCUCUAUGACAAGUUAGA-3' and antisense 5'-UAACUUGUCAUAGAGAAUGUU-3'. The negative control siRNA sequences were: sense 5'-UUCUCCGAACGUGUCACGUTT-3' and antisense 5'-ACGUGACACGUUCGGAGAATT-3'. Quantitative real-time polymerase chain reaction (qRT-PCR) Total RNA was extracted using TRIzol reagent (Invitrogen, USA) following the manufacturer's instructions. cDNA was synthesized using a reverse transcription kit (Vazyme, Nanjing). qRT-PCR was performed in a 20 µL reaction mixture using SYBR Green qPCR Master Mix (Vazyme, Nanjing) and the Applied ABI QuantStudio 3 Real-Time PCR System (Thermo Fisher Scientific, Inc.). The primer pairs used for qRT-PCR were: CCT7 forward primer 5'-GCTGGTGTTGCATTCAAGAAG-3' and reverse primer 5'-TTGCCTGATAATCCTCAACTGTG-3'; GAPDH forward primer 5'-GGAGCGAGATCCCTCCAAAAT-3' and reverse primer 5'-GGCTGTTGTCATACTTCTCATGG-3'. Relative expression was normalized to the internal reference gene GAPDH using the 2-ΔΔCt method. Western blotting Cells were lysed using a radio-immunoprecipitation assay buffer (Cwbio, Jiangsu, China), and the protein concentration was determined using a bicinchoninic acid protein assay kit (Beyotime, Shanghai, China). Protein samples (30 µg/lane) were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis on 10% gels and transferred onto polyvinylidene fluoride membranes. The membranes were blocked with 10% skim milk at room temperature for 2 hours, then incubated overnight at 4°C with primary antibodies against CCT7 (15994-1-AP; Proteintech, China) and β-actin (AC026; Abclonal, China). After incubation, the membranes were treated with anti-rabbit horseradish peroxidase secondary antibody (SA00001-2; Proteintech, China) at room temperature for 1 hour. Protein bands were visualized using an enhanced chemiluminescence reagent kit (Abbkine Scientific Co., Ltd, China) and scanned with an imaging system (ProteinSimple, Inc.). Protein band densities were quantified using ImageJ software v1.8.0. Cell counting Kit-8 (CCK-8) assay Cell proliferation ability was assessed using the CCK-8 assay (Abbkine Scientific Co., Ltd, China). Transfected siNC and siCCT7 cells were seeded in 96-well plates and incubated at 37°C for 24, 48, 72, and 96 hours. After adding 10 µL of CCK-8 reagent to each well and incubating in the dark for 1.5 hours, absorbance was measured at 450 nm. Colony formation assays Colony formation assay was employed to evaluate the cloning capability of COAD cells with stable CCT7 knockdown. The transfected siNC and siCCT7 cells were seeded in six-well plates at approximately 1000 cells per well. After 15 days of culture, RKO and HCT-116 cells were fixed with 4% fixative solution and stained with 0.1% crystal violet staining solution (Solarbio Life Sciences, Beijing, China). Colonies were washed with distilled water, photographed, and counted using ImageJ software. Cell invasion assay RKO and HCT-116 cells were digested and resuspended in serum-free 1640 medium at a density of 1 × 10⁵ cells/mL. Cell invasion ability was assessed using the Transwell assay. The lower chamber of each well was filled with 600 µL of complete medium containing 10% FBS. Matrigel was diluted 1:8 with serum-free medium, and 100 µL of this mixture was added to the upper chamber. Subsequently, 200 µL of the cell suspension was seeded into the upper chamber of a 24-well Transwell insert with a polycarbonate membrane (8.0 µm pore size). After 48 hours of incubation, cells on the lower surface of the membrane were fixed, stained, and counted. Cell migration assay RKO and HCT-116 cells were digested and resuspended in serum-free 1640 medium at a density of 1 × 10⁵ cells/mL. Cell migration ability was assessed using the Transwell assay. The lower chamber of each well was filled with 600 µL of complete medium containing 10% FBS. Subsequently, 200 µL of the cell suspension was seeded into the upper chamber of a 24-well Transwell insert with a polycarbonate membrane (8.0 µm pore size). After 48 hours of incubation, cells on the lower surface of the membrane were fixed, stained, and counted. Immunohistochemistry (IHC) assay The 60 COAD specimens were cut into 4-µm sections and fixed on glass slides for microscopy. The tissue sections on the slides were then deparaffinized and rehydrated using gradient concentrations of malondialdehyde and ethanol. Next, the slides were immersed in boiling Tris/ ethylenediaminetetraacetic acid (pH 9.0) for 20 minutes for antigen retrieval. The slides were subsequently immersed in 3% H₂O₂ for 10 minutes to inhibit endogenous peroxidase. Then, the slides were incubated with a primary antibody against CCT7 (1:250; 15994-1-AP; Proteintech, China), followed by the HRP secondary antibody (RGAR011; Proteintech, China), and were washed three times with phosphate-buffered saline. Finally, the sections were stained with 3,3'-diaminobenzidine and substrate chromogen (Dako) for 2 minutes at room temperature and then counterstained with hematoxylin for 40 seconds. Slides incubated only with the secondary antibody without the primary antibody were used as the negative control. The staining of each section was evaluated by two independent researchers blinded to the clinicopathological parameters. Immunoreactivity for CCT7 expression was evaluated using semi-quantitative immunoreactivity score (IRS) system, according to the intensity of staining (IS) (0-negative; 1-weak; 2-moderate; 3-strong) and area of positivity (AP) (0, 0–25%; 1, 25–50%; 3, 50–75%; 4, 75–100%), and recorded with H-score. The final H-score was obtained by multiplying the IS and AP. In this study, CCT7 expression was regarded as low expression when the score was < 6, and high expression when the score was ≥ 6. The immunohistochemical staining was assessed by two separate pathologists who were blinded to patients’ information. GO-BP enrichment analyses Spearman's test was conducted using R software based on TCGA-COAD and GSE39582. CCT7-related genes ( P < 0.05 and absolute value of correlation coefficient ≥ 0.35) were subjected to GO-BP enrichment analyses using the Metascape database ( http://metascape.org/ ). Immune Infiltration Analysis Single sample gene set enrichment analysis (ssGSEA) was applied for determination of immune infiltration based upon the immune gene sets(Charoentong et al. 2017 ). Evaluation of drug sensitivity The R language and the "oncopredict" package were employed to calculate the sensitivity score of each sample in the TCGA-COAD dataset for 199 anticancer drugs, with a higher sensitivity score indicating lower drug sensitivity. Calculation of the scores for immune checkpoint inhibitor therapy The R language and the weighted analysis were utilized to calculate the scores for PD-1 and CTLA-4 inhibitor therapies. Statistical analysis Statistical analyses were performed using SPSS 26.0 (IBM, USA) and GraphPad Prism 8 (version 8.0.2, GraphPad Software, San Diego, CA, USA). Data are presented as mean ± standard deviation (SD). The independent-samples t-test or paired-samples t-test was used for comparisons between two groups, while one-way analysis of variance (ANOVA) was applied for three or more groups. Non-parametric tests were used if data were not normally distributed or had non-homogeneous variances. The Kaplan-Meier method with Log-Rank test was employed to evaluate the impact of CCT7 on COAD prognosis. Cox regression analysis was performed for univariate and multivariate analyses of CCT7 and clinicopathological parameters. In univariate regression, variables with a p-value less than 0.2 were included in the multivariate regression. Pearson correlation was used for normally distributed samples, while Spearman correlation was applied for non-normally distributed ones. Categorical data are presented as frequencies and percentages (%), and inter-group comparisons were conducted using the χ² test. P < 0.05 was considered statistically significant Results Abnormal high expression of CCT7 in COAD The expression of CCT7 in COAD was analyzed using TCGA-COAD and GEO datasets. Results revealed significantly higher CCT7 mRNA expression in COAD cancer tissues than in pericancerous tissues (Fig. 1 A-F, P < 0.05). To validate these findings, western blotting and qRT-PCR were performed to detect CCT7 expression in COAD cell lines. The results indicated that the protein and mRNA expression of CCT7 were markedly elevated in COAD cancer cells (RKO and HCT-116 cells) compared to normal colon epithelial cells (NCM460 cells) (Fig. 1 G and H, P < 0.05). Immunohistochemical analysis showed that CCT7 was mainly localized in the cell cytoplasm (Fig. 1 I). Representative immunohistochemical results of tumor tissues and corresponding adjacent normal tissues are shown in Fig. 1 I. The final H-scores indicated that CCT7 protein was highly expressed in 38 of 60 (63.3%) COAD samples compared to 11 of 60 (18.3%) adjacent normal samples, with a statistically significant difference ( χ² = 25.145, P < 0.0001). High expression of CCT7 in COAD cancer tissues is significantly associated with poor prognosis Kaplan-Meier and Log-Rank analyses based on TCGA-COAD and GSE17538 datasets, and COAD clinical specimens revealed that COAD patients with high CCT7 expression had significantly reduced survival time compared to those with low CCT7 expression (Fig. 2 A, P < 0.05). To evaluate the independent prognostic significance of CCT7 expression, Cox regression analyses were performed using TCGA-COAD dataset and COAD clinical specimens. In TCGA-COAD dataset, univariate analysis identified age, M stage, N stage, T stage, loss of MMR protein, lymphatic invasion, cancer status, PostopTreat, venous invasion, and CCT7 expression as predictors of prognosis. Multivariate analysis indicated that M stage, N stage, non-nodal tumor deposits, cancer status, and CCT7 expression were independent predictors of prognosis (Fig. 2 B, P < 0.05). By using COAD clinical specimens, univariate analysis showed that M stage, N stage, T stage, loss of MMR protein, venous invasion, and CCT7 expression were predictors of prognosis. Multivariate analysis indicated that N stage, tumor location, venous invasion, and CCT7 expression were independent predictors of prognosis (Fig. 2 C, P < 0.05). GO-BP enrichment analysis for biological functions of CCT7 To explore CCT7's specific functions in COAD development, we conducted Gene Ontology-Biological Process (GO-BP) enrichment analysis using TCGA-COAD and GSE39582 datasets. First, the correlations between CCT7 expression and other genes in the two databases were analyzed. Genes with |rs| ≥ 0.35 and P < 0.05 were selected for enrichment analysis (Fig. 3 A and B). The results indicated that CCT7 may be involved in regulating biological processes related to cell proliferation and microtubule activities in COAD (Fig. 3 C and D, P < 0.05). These findings suggest that CCT7 might play significant roles in regulating COAD cell proliferation and metastasis. Knocking down CCT7 inhibited the proliferation, migration and invasion of COAD cells RKO and HCT-116 cells, which exhibit relatively high CCT7 expression, were chosen for further study. After transfection with siCCT7 and a negative control siNC, we measured the mRNA and protein levels of CCT7. The results showed that both mRNA and protein expression of CCT7 were markedly reduced in siCCT7-transfected cells compared to siNC-transfected controls (Fig. 4 A and B, P < 0.05). This indicates successful transfection of RKO and HCT-116 cells, which are suitable for subsequent experiments. The impact of CCT7 expression on cell proliferation was assessed using the CCK-8 assay. The results revealed that RKO and HCT-116 cells with CCT7 knockdown developed a significant reduction in proliferation compared to control cells at 96 h after transfection (Fig. 4 C, P < 0.05). The colony formation assay was conducted to evaluate the multiplication of RKO and HCT-116 cells transfected with siCCT7. Results indicated that compared to the control group, the siCCT7 transfection group exhibited a marked decrease in the number of newly formed colonies, along with impaired colony formation ability (Fig. 4 D, P < 0.01). Transwell assays were performed to evaluate the migration and invasion of RKO and HCT-116 cells. Compared to the siNC group, the number of migrated and invaded cells was significantly reduced in the siCCT7 group (Fig. 4 E and F, P < 0.01). Correlations between CCT7 expression and infiltrating immune cells Based on the TCGA-COAD dataset, the associations of immune infiltration with CCT7 expression were investigated using ssGSEA algorithm and Spearman's correlation analysis. The results indicated that CCT7 expression was negatively associated with most immune cells, including central memory CD4 and CD8 T cells, effector memory CD4 and CD8 T cells, T follicular helper cell, type 1 and type 2 T helper cells (Table 3 , P < 0.05). To validate the above findings, the correlation between the expression of CCT7 and the expression of immune cell markers was investigated. It is revealed that CCT7 expression negatively correlated with the expression of most immune cell markers (Table 4 , P < 0.05). These results suggest that CCT7 expression levels may influence the immune infiltration characteristics of COAD. Table 3 The correlation between CCT7 expression and immune infiltration in colonic adenocarcinoma Table 4 The correlation between CCT7 expression level and immune cell marker expression level in colonic adenocarcinoma Impact of CCT7 Expression on the Efficacy of Immune Checkpoint Inhibitor Therapy To elucidate the impact of CCT7 expression on the therapeutic efficacy of immune checkpoint inhibitors in the treatment of COAD, this study examined the correlations between CCT7 expression and the expression of immune checkpoints programmed cell death 1 (PD-1) and cytotoxic T-lymphocyte associated protein 4 (CTLA-4), as well as their ligands PD ligand 1 (PD-L1), PD ligand 2 (PD-L2), CD80 and CD86, using the TCGA-COAD dataset. Although there was no correlation between the expression of CCT7 and that of PD-1 (Fig. 5 A, P = 0.181), the results demonstrated that CCT7 expression negatively correlated with the expression of CTLA-4, PD-L1, PD-L2, CD80, and CD86 (Fig. 5 B-F, P < 0.001). Subsequently, immune checkpoint inhibitor therapy scores and their correlations with CCT7 expression were analyzed using the TCGA-COAD dataset. The outcomes suggested that the CCT7 expression was negatively associated with the scores for PD-1 and CTLA-4 inhibitor therapies (Fig. 5 G and H, P < 0.01). In summary, these results suggest that patients with high CCT7-expressing COAD may have a poor response to immune checkpoint inhibitors. Drug Sensitivity Analysis To elucidate the impact of CCT7 expression on the efficacy of various anticancer drugs in treating COAD, this study analyzed the sensitivity scores of individual COAD samples from the TCGA-COAD dataset to multiple anticancer drugs, with higher scores indicating lower drug sensitivity (i.e., reduced responsiveness), and investigated the correlation between drug sensitivity and CCT7 expression. The results showed that the CCT7 expression was negatively correlated with the sensitivity scores of OSI-027, 5-Fluorouracil, VX-11e, MK-1775, Palbociclib, Oxaliplatin, and Vorinostat (Fig. 6 A-G, P < 0.001). Additionally, there was a positive correlation between the CCT7 expression and the drug sensitivity scores of AZD6482, AZD8186, NU7441, ZM447439, JQ1, and Doramapimod (Fig. 6 H-M, P < 0.001) Discussion CCT is essential for maintaining cellular protein homeostasis, as it facilitates the folding of major cytoskeletal proteins, including tubulin and actin. Research has demonstrated that the protein expression of CCT is elevated in 18 types of cancer cell lines when compared to normal paired cells(Boudiaf-Benmammar et al. 2013 ). Various CCT subunits have been implicated in cancer: CCT2 drives CRC proliferation and metastasis via the Hedgehog pathway under hypoxia(Park et al. 2020 ); HOXB2 upregulates CCT6A to enhance CRC proliferation and invasion(Yang et al. 2022 ); CCT8 promotes CRC progression through the P53 pathway(Liao et al. 2021 ). Although bioinformatics reveals CCT7 overexpression in CRC tissues(Lim et al. 2022 ), its role in COAD development remains unclear. This study investigated the role of CCT7 in COAD development and its correlations with immunotherapy and chemotherapy. In line with the increased expression of CCT2, CCT5 and CCT7 in CRC tissues(Ahmed et al. 2025 ; Liu et al. 2021 ; Park et al. 2020 ), the present study, through analyzing the TCGA and GEO databases, found that the mRNA expression of CCT7 was statistically significantly elevated in COAD tissues compared with normal samples. Similar results were also obtained in colon cancer cells, normal colon cells, and COAD clinical specimens using qRT-PCR, western blotting, and IHC techniques. In addition, Kaplan–Meier and Log-Rank methods showed that high CCT7 expression was associated with worse prognosis in COAD patients and Cox regression analysis indicated that high CCT7 expression was an independent factor for prediction of poor prognosis, which was consistent with the prognostic value of CCT2 in breast cancer, CCT5 in gastric cancer and CCT3 in head and neck squamous cell carcinoma (HNSCC) and cervical cancer(Chen et al. 2024 ; Dou and Zhang 2021 ; Li et al. 2022 ; Wang et al. 2021 ). Collectively, these investigations suggested that CCT7 probably served as an oncogene in COAD and was a potential prognostic biomarker for COAD patients. To define the detailed functions of CCT7 in COAD, GO-BP enrichment analysis was used to determine CCT7-related biological processes. The results revealed that CCT7 exerted a possible role in the regulation of cell proliferation and the activities of microtubules in COAD. Microtubules, crucial tracks for transporting organelles and molecules via motor proteins, facilitate cell migration through the transport of essential proteins and signaling molecules to the cell front. During cell migration, microtubules and actin collaborate in transferring mechanical forces: microtubules provide flexural stiffness, while actin filaments generate contractile force, synergistically ensuring efficient cell movement. To further validate the aforementioned results, the effect of CCT7 on biological behaviors of COAD cells was examined. It was reported that CCT2, CCT3 and CCT8 possessed the ability to promote proliferation of tumor cells in breast cancer, HNSCC, cervical cancer and CRC respectively(Chen et al. 2024 ; Dou and Zhang 2021 ; Liao et al. 2021 ; Wang et al. 2021 ; Xu et al. 2020 ). Likewise, our functional experiments showed that knockdown of CCT7 suppressed proliferation of COAD cells, which was in accord with the results of enrichment analysis. Moreover, CCT2, CCT3 and CCT8 enhanced the metastatic phenotype of cancer cells in breast cancer, HNSCC, cervical cancer and CRC respectively (Chen et al. 2024 ; Dou and Zhang 2021 ; Liao et al. 2021 ; Wang et al. 2021 ; Xu et al. 2020 ), and the similar effects of CCT7 on COAD cells were found by the present study, which were consistent with the results of enrichment analysis. Taken together, our results demonstrated that high CCT7 expression correlated with malignant progression of COAD. Combining the research findings on the prognostic significance of elevated CCT7 expression in COAD patients, the roles and mechanisms of CCT7 in the tumorigenesis and progression of COAD have been partially determined. Furthermore, this study investigated the influence of CCT7 expression on the efficacy of immunotherapy and chemotherapy. Results from ssGSEA immune infiltration analysis and correlation analysis revealed a negative correlation between CCT7 expression and the infiltration of most immune cells, as well as a negative correlation with the expression levels of most immune cell markers. These findings implied that high expression of CCT7 may reduce the infiltration of immune cells, thereby compromising the effectiveness of immune-activating agents in the therapy of COAD. Additionally, CCT7 expression showed a negative correlation with PD-L1, PD-L2, CTLA-4, CD80, and CD86, along with the scores for PD-1 and CTLA-4 inhibitor therapies, indicating that COAD tumors with high CCT7 expression may respond poorly to immune checkpoint inhibitors. These findings provide a basis for studying CCT7-targeted therapy combined with immunotherapy. Drug sensitivity analysis demonstrated that COAD samples with high CCT7 expression developed high sensitivity to 5-Fluorouracil and Oxaliplatin, both of which are well-established clinical agents for COAD treatment(Shaham et al. 2025 ). Consequently, high CCT7 expression may enhance the therapeutic efficacy of conventional clinical drugs for COAD. Moreover, our results also indicated that COAD samples with high CCT7 expression exhibited high sensitivity to OSI-027, VX-11e, MK-1775, Palbociclib, and Vorinostat, while showing low sensitivity to AZD6482, AZD8186, NU7441, ZM447439, JQ1, and Doramapimod. These findings offer crucial insights for clinical drug selection. There exist several limitations in our study. Firstly, the signaling pathways responsible for the effect of CCT7 on the biological behaviors of COAD cells were unclear and should be identified in future research. Secondly, the associations of CCT7 expression with immune infiltration and immunotherapy score were determined based on bioinformatic databases and therefore, in vivo and in vitro experiments should be employed to investigate the effect of CCT7 on immunotherapy and the underlying mechanisms. Lastly, in vivo and in vitro experiments should be conducted to confirm the influence of CCT7 expression on chemotherapy, as the impact of CCT7 on drug sensitivity was obtained only through bioinformatics analysis. Conclusion In summary, our research demonstrates that the elevated expression of CCT7 in COAD may impact the proliferation, migration, and invasion of tumor cells, and ultimately influence the prognosis of patients. Moreover, our findings also indicate that the expression level of CCT7 can affect the efficacy of both immunotherapy and chemotherapy, thereby serving as a valuable reference for clinical treatment. Declarations Ethics Approval and Consent to Participate Our study has been approved by the Institutional Research Ethics Committee of the Second Affiliated Hospital of Zhengzhou University and written informed consent was provided by every patient. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This work was supported by grants from the Henan Provincial Natural Science Foundation (No. 252300421368), the Top Talents Funding of the Second Affiliated Hospital of Zhengzhou University (No. 2020BJRCB04), and BEIJING SCIENCE AND TECHNOLOGY INNOVATION MEDICAL DEVELOPMENT FOUNDATION (No. KC2023-JX-0186-FM054). Author Contribution Z.W.C. and H.N. contributed to the conception and design of the study. L.W.X. wrote the first draft of the manuscript. Z.W.C., H.N. and L.W.X. analyzed the bioinformatical data. S.Q.Z., M.Y.H. and H.N. provided COAD samples and detected CCT7 expression. L.W.X. conducted cell-based experiments and performed statistical analysis. Z.W.C. and H.N. supervised all the work. All authors contributed to the article and approved the submitted version. Acknowledgments The authors thank the contributors of TCGA ( https://portal.gdc.cancer.gov/repository ) and GEO ( https://www.ncbi.nlm.nih.gov/geo/ ) for sharing the related data. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. References Ahmed MZ et al (2025) Pan-cancer analysis reveals immunological and prognostic significance of CCT5 in human tumors. Sci Rep 15(1):14405 Arafat Hossain M (2024) A comprehensive review of immune checkpoint inhibitors for cancer treatment. Int Immunopharmacol 143(Pt 2):113365 Boudiaf-Benmammar C et al (2013) The cytosolic chaperonin CCT/TRiC and cancer cell proliferation. PLoS ONE 8(4):e60895 Brackley KI, Grantham J (2009) Activities of the chaperonin containing TCP-1 (CCT): implications for cell cycle progression and cytoskeletal organisation. Cell Stress Chaperones 14(1):23–31 Bray F et al (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 74(3):229–263 Cai Y et al (2022) CCT6A expression in hepatocellular carcinoma and its correlation with clinical characteristics, liver function indexes, tumor markers and prognosis. Clin Res Hepatol Gastroenterol 46(3):101796 Chang Y et al (2020) Chaperonin-Containing TCP-1 Promotes Cancer Chemoresistance and Metastasis through the AKT-GSK3β-β-Catenin and XIAP-Survivin Pathways. Cancers (Basel) 12(12):3865 Charoentong P et al (2017) Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade. Cell Rep 18(1):248–262 Chen S et al (2022) Suppression of CCT3 Inhibits Tumor Progression by Impairing ATP Production and Cytoplasmic Translation in Lung Adenocarcinoma. Int J Mol Sci 23(7):3983 Chen X et al (2024) Trim21-mediated CCT2 ubiquitination suppresses malignant progression and promotes CD4(+)T cell activation in breast cancer. Cell Death Dis 15(7):542 Dou L, Zhang X (2021) Upregulation of CCT3 promotes cervical cancer progression through FN1. Mol Med Rep 24(6):856 Erasha AM et al (2025) The Role of the Tumor Microenvironment (TME) in Advancing Cancer Therapies: Immune System Interactions, Tumor-Infiltrating Lymphocytes (TILs), and the Role of Exosomes and Inflammasomes. Int J Mol Sci 26(6):2716 Fang J et al (2022) CCT4 knockdown enhances the sensitivity of cisplatin by inhibiting glycolysis in human esophageal squamous cell carcinomas. Mol Carcinog 61(11):1043–1055 Franzin R et al (2020) The Use of Immune Checkpoint Inhibitors in Oncology and the Occurrence of AKI: Where Do We Stand? Front Immunol 11:574271 Guo T, Xu J (2024) Cancer-associated fibroblasts: a versatile mediator in tumor progression, metastasis, and targeted therapy. Cancer Metastasis Rev 43(3):1095–1116 Khromova N et al (2024) Actin-Dependent Mechanism of Tumor Progression Induced by a Dysfunction of p53 Tumor Suppressor. Cancers (Basel) 16(6):1123 Li Y et al (2022) CCT5 induces epithelial-mesenchymal transition to promote gastric cancer lymph node metastasis by activating the Wnt/β-catenin signalling pathway. Br J Cancer 126(12):1684–1694 Liao Q et al (2021) CCT8 recovers WTp53-suppressed cell cycle evolution and EMT to promote colorectal cancer progression. Oncogenesis 10(12):84 Lim Y et al (2022) Proteomic identification of arginine-methylated proteins in colon cancer cells and comparison of messenger RNA expression between colorectal cancer and adjacent normal tissues. Ann Coloproctol 38(1):60–68 Liu Q et al (2021) Molecular and Clinical Characterization of CCT2 Expression and Prognosis via Large-Scale Transcriptome Profile of Breast Cancer. Front Oncol 11:614497 Marisa L et al (2013) Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med 10(5):e1001453 Morgan E et al (2023) Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut 72(2):338–344 Park SH et al (2020) Activating CCT2 triggers Gli-1 activation during hypoxic condition in colorectal cancer. Oncogene 39(1):136–150 Parker AL et al (2014) Microtubules and their role in cellular stress in cancer. Front Oncol 4:153 Shaham SH et al (2025) Advances in Targeted and Chemotherapeutic Strategies for Colorectal Cancer: Current Insights and Future Directions. Biomedicines 13(3):642 Sheffer M et al (2009) Association of survival and disease progression with chromosomal instability: a genomic exploration of colorectal cancer. Proc Natl Acad Sci U S A 106(17):7131–7136 Smith JJ et al (2010) Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer. Gastroenterology 138(3):958–968 Solé X et al (2014) Discovery and validation of new potential biomarkers for early detection of colon cancer. PLoS ONE 9(9):e106748 Tang N et al (2020) TCP1 regulates Wnt7b/β-catenin pathway through P53 to influence the proliferation and migration of hepatocellular carcinoma cells. Signal Transduct Target Ther 5(1):169 Valcz G et al (2014) Myofibroblast-derived SFRP1 as potential inhibitor of colorectal carcinoma field effect. PLoS ONE 9(11):e106143 Vallin J, Grantham J (2019) The role of the molecular chaperone CCT in protein folding and mediation of cytoskeleton-associated processes: implications for cancer cell biology. Cell Stress Chaperones 24(1):17–27 Valpuesta JM et al (2002) Structure and function of a protein folding machine: the eukaryotic cytosolic chaperonin CCT. FEBS Lett 529(1):11–16 Wang Y et al (2021) Identification of CCT3 as a prognostic factor and correlates with cell survival and invasion of head and neck squamous cell carcinoma. Biosci Rep 41(10):BSR20211137 Weinstein JN et al (2013) The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45(10):1113–1120 Xu G et al (2020) Suppression of CCT3 inhibits the proliferation and migration in breast cancer cells. Cancer Cell Int 20:218 Yang X et al (2018) Chaperonin-containing T–complex protein 1 subunit 8 promotes cell migration and invasion in human esophageal squamous cell carcinoma by regulating α-actin and β-tubulin expression. Int J Oncol 52(6):2021–2030 Yang X et al (2022) HOXB2 increases the proliferation and invasiveness of colon cancer cells through the upregulation of CCT6A. Mol Med Rep 25(5):174 Yang Y et al (2022) MicroRNAs (miRNAs): Novel potential therapeutic targets in colorectal cancer. Front Oncol 12:1054846 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Jan, 2026 Read the published version in Journal of Molecular Histology → Version 1 posted Editorial decision: Revision requested 07 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 01 Oct, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 24 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviews received at journal 27 Aug, 2025 Reviewers agreed at journal 25 Aug, 2025 Reviewers invited by journal 03 Aug, 2025 Editor assigned by journal 03 Aug, 2025 Submission checks completed at journal 02 Aug, 2025 First submitted to journal 01 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7271196","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495360275,"identity":"5aa5c84e-ed7c-48a4-bb70-59bf905b4b9e","order_by":0,"name":"Wenxu Li","email":"","orcid":"","institution":"The Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wenxu","middleName":"","lastName":"Li","suffix":""},{"id":495360278,"identity":"c97b83ec-cb01-4751-b7db-0322e6fbbf10","order_by":1,"name":"Qizhong Shi","email":"","orcid":"","institution":"The Third Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qizhong","middleName":"","lastName":"Shi","suffix":""},{"id":495360281,"identity":"44f0444f-de0d-4928-ae70-98f2e269d027","order_by":2,"name":"Yonghui Mu","email":"","orcid":"","institution":"General Practice School of Xinxiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yonghui","middleName":"","lastName":"Mu","suffix":""},{"id":495360282,"identity":"c93273c2-aa85-4449-8a69-292e622993b7","order_by":3,"name":"Chenglei Li","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Chenglei","middleName":"","lastName":"Li","suffix":""},{"id":495360283,"identity":"46f5b9b3-40b2-4b4e-ad51-6b1e29aa621b","order_by":4,"name":"Wenchao Zhao","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wenchao","middleName":"","lastName":"Zhao","suffix":""},{"id":495360284,"identity":"458269a6-408d-4f32-93a0-52914261b2bd","order_by":5,"name":"Na Han","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACAxDB2AAimQ9AhA4Qr4UtgWQtPAbEaTFnP3vswc8ddnnmEjmfP/5sY5Dju5HA+LkAjxbLnrx0w94zycWWM3I3GEi2MRhL3khglp6Bz2EHcswkeNuYEzfcyN2QYNjGAGQksDHz4NNy/o2Z5N+2eqDKnAcHEtsY6glruZFjJs3bdhikhbHhYBtDggFhLW/MpGXbjhdb9jwzZmw4J2E488zDZmn8Dssxk3zbVp1nzp78+OOPMht5vuPJBz/j0wIDCQYCCSBaggEWTURo4T9AlMJRMApGwSgYgQAA6FlQzmQZh04AAAAASUVORK5CYII=","orcid":"","institution":"The Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"Na","middleName":"","lastName":"Han","suffix":""}],"badges":[],"createdAt":"2025-08-01 12:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7271196/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7271196/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10735-026-10715-4","type":"published","date":"2026-01-28T15:59:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88414778,"identity":"35a98d45-19e9-4db4-b3f5-d2bdd0bd2c8f","added_by":"auto","created_at":"2025-08-06 08:49:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27741847,"visible":true,"origin":"","legend":"\u003cp\u003eCCT7 was upregulated in human COAD tissue. (\u003cstrong\u003eA-F\u003c/strong\u003e) Analyses based on TCGA-COAD (\u003cstrong\u003eA\u003c/strong\u003e), GSE39582 (\u003cstrong\u003eB\u003c/strong\u003e), GSE41258 (\u003cstrong\u003eC\u003c/strong\u003e), GSE37364 (\u003cstrong\u003eD\u003c/strong\u003e), GSE44076 (\u003cstrong\u003eE\u003c/strong\u003e) and GSE41328 (\u003cstrong\u003eF\u003c/strong\u003e) datasets demonstrated significantly higher CCT7 mRNA expression in COAD cancer tissues than in paracancerous tissues. (\u003cstrong\u003eG\u003c/strong\u003e and \u003cstrong\u003eH\u003c/strong\u003e) Increased protein (\u003cstrong\u003eG\u003c/strong\u003e) and mRNA (\u003cstrong\u003eH\u003c/strong\u003e) levels of CCT7 in the COAD cell lines RKO and HCT-116 compared with normal colon cell line NCM460. (\u003cstrong\u003eI\u003c/strong\u003e) Representative images of IHC detection for CCT7 expression in cancerous and paired noncancerous samples obtained from COAD patients. The left image, showing normal colon tissues, indicated that CCT7 was not detected, and the middle and right images demonstrated the low and high expression of CCT7 respectively in COAD tissues. Magnification for all photomicrographs was ×200. ****\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.0001, *\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05. All data were representative of at least three independent experiments (\u003cem\u003en\u003c/em\u003e= 3; error bar, SD)\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7271196/v1/b85b2535803e3b552d71ca30.png"},{"id":88414758,"identity":"8106c4b3-a4dd-460e-82bb-851058aa36fa","added_by":"auto","created_at":"2025-08-06 08:49:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6846879,"visible":true,"origin":"","legend":"\u003cp\u003eCCT7 overexpression in COAD tissues predicted poor prognosis. (\u003cstrong\u003eA\u003c/strong\u003e) Kaplan-Meier and Log-Rank were used to analyze the correlation between the expression of CCT7 and the prognosis of COAD patients. (\u003cstrong\u003eB\u003c/strong\u003e and \u003cstrong\u003eC\u003c/strong\u003e) Univariate and multivariate Cox regression analyses based upon TCGA-COAD dataset (\u003cstrong\u003eB\u003c/strong\u003e) and COAD clinical specimens (\u003cstrong\u003eC\u003c/strong\u003e). (MMR: Mismatch Repair Proteins; PostopTreat: Postoperative treatment)\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7271196/v1/8d1055d0319bd1a86c17486e.png"},{"id":88416170,"identity":"c748dbf2-db66-4d5f-b112-69ab64d0fcc1","added_by":"auto","created_at":"2025-08-06 08:57:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5957775,"visible":true,"origin":"","legend":"\u003cp\u003eGO-BP enrichment analysis of genes associated with CCT7. (\u003cstrong\u003eA\u003c/strong\u003e and \u003cstrong\u003eB\u003c/strong\u003e) The correlation between each gene and CCT7 expression was analyzed using the TCGA-COAD (\u003cstrong\u003eA\u003c/strong\u003e) and GSE39582 (\u003cstrong\u003eB\u003c/strong\u003e) datasets. (\u003cstrong\u003eC\u003c/strong\u003e and \u003cstrong\u003eD\u003c/strong\u003e) GO-BP enrichment analysis of CCT7 was conducted using the TCGA-COAD (\u003cstrong\u003eC\u003c/strong\u003e) and GSE39582 (\u003cstrong\u003eD\u003c/strong\u003e) datasets. (\u003cem\u003ers\u003c/em\u003e: correlation coefficient)\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7271196/v1/e670833ff3b17ef9b3d9f190.png"},{"id":88414768,"identity":"5404faa5-6be3-46e3-af2d-0869dc686e00","added_by":"auto","created_at":"2025-08-06 08:49:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":25753143,"visible":true,"origin":"","legend":"\u003cp\u003eDownregulation of CCT7 repressed the proliferation, migration and invasion of COAD cells. (\u003cstrong\u003eA\u003c/strong\u003eand \u003cstrong\u003eB\u003c/strong\u003e) mRNA and protein expression levels of CCT7 in the RKO (\u003cstrong\u003eA\u003c/strong\u003e) and HCT-116 (\u003cstrong\u003eB\u003c/strong\u003e) cell lines. (\u003cstrong\u003eC\u003c/strong\u003e) The CCK-8 assay was performed to investigate the proliferation of COAD cells that were transfected with siNC or siCCT7. (\u003cstrong\u003eD\u003c/strong\u003e) Efficacy of siCCT7 on colony formation of COAD cells. (\u003cstrong\u003eE\u003c/strong\u003eand \u003cstrong\u003eF\u003c/strong\u003e) The migration and invasion abilities of RKO (\u003cstrong\u003eE\u003c/strong\u003e) and HCT-116 cells (\u003cstrong\u003eF\u003c/strong\u003e) were evaluated using Transwell analysis (×200). ****\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. All data were representative of at least three independent experiments (\u003cem\u003en\u003c/em\u003e = 3; error bar, SD)\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7271196/v1/7991133b5376b4956d398f99.png"},{"id":88414763,"identity":"f05f1518-2b56-4d29-be6b-303782a4527b","added_by":"auto","created_at":"2025-08-06 08:49:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5264711,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of CCT7 expression on the efficacy of immune checkpoint inhibitor therapy. (\u003cstrong\u003eA-F\u003c/strong\u003e) The correlation between PD-1(\u003cstrong\u003eA\u003c/strong\u003e) and CTLA-4(\u003cstrong\u003eD\u003c/strong\u003e), as well as their ligands PD-L1(\u003cstrong\u003eB\u003c/strong\u003e), PD-L2(\u003cstrong\u003eC\u003c/strong\u003e), CD80(\u003cstrong\u003eE\u003c/strong\u003e) and CD86(\u003cstrong\u003eF\u003c/strong\u003e) and CCT7 mRNA expression. (\u003cstrong\u003eG\u003c/strong\u003e and \u003cstrong\u003eH\u003c/strong\u003e) The correlations between PD-1 and CTLA-4 inhibitor immunotherapy scores and CCT7 mRNA expression\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7271196/v1/5ebc31953e4c1f73d1604940.png"},{"id":88414773,"identity":"51841709-1ac0-4633-9ede-50fb305cfdae","added_by":"auto","created_at":"2025-08-06 08:49:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":7079710,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations between CCT7 expression and drug sensitivity based on TCGA-COAD dataset. (\u003cstrong\u003eA-G\u003c/strong\u003e) Negative correlations between the sensitivity scores of OSI-027 (\u003cstrong\u003eA\u003c/strong\u003e), 5-Fluorouracil (\u003cstrong\u003eB\u003c/strong\u003e), VX-11e (\u003cstrong\u003eC\u003c/strong\u003e), MK-1775 (\u003cstrong\u003eD\u003c/strong\u003e), Palbociclib (\u003cstrong\u003eE\u003c/strong\u003e), Oxaliplatin (\u003cstrong\u003eF\u003c/strong\u003e), and Vorinostat (\u003cstrong\u003eG\u003c/strong\u003e) and CCT7 mRNA expression. (\u003cstrong\u003eH-M\u003c/strong\u003e) Positive correlations between the sensitivity scores of AZD6482 (\u003cstrong\u003eH\u003c/strong\u003e), AZD8186 (\u003cstrong\u003eI\u003c/strong\u003e), NU7441 (\u003cstrong\u003eJ\u003c/strong\u003e), ZM447439 (\u003cstrong\u003eK\u003c/strong\u003e), JQ1 (\u003cstrong\u003eL\u003c/strong\u003e), and Doramapimod (\u003cstrong\u003eM\u003c/strong\u003e) and CCT7 mRNA expression\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7271196/v1/ffb250bffe7157470b379c57.png"},{"id":101691945,"identity":"f7441ae3-529a-4815-b5f1-c68eebd3b046","added_by":"auto","created_at":"2026-02-02 16:16:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":71966148,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7271196/v1/695343ff-30ff-49fa-9fb3-027c34476351.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"CCT7 indicates a poor prognosis and is associated with immune infiltration in colonic adenocarcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) ranks as the third most common gastrointestinal malignancy globally(Morgan et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The International Agency for Research on Cancer (IARC) estimated about 20\u0026nbsp;million new cancer cases and 9.7\u0026nbsp;million cancer-related deaths worldwide in 2022. Colorectal cancer accounted for 9.6% of new cancer cases and 9.3% of cancer-related deaths, with approximately 2\u0026nbsp;million new cases and an estimated 900,000 fatalities(Bray et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Colonic adenocarcinoma (COAD) is the predominant pathological subtype of CRC(Yang et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite significant progress in cancer treatment, the overall survival (OS) for COAD patients remains suboptimal. Thus, there is an urgent need to elucidate the pathogenesis of COAD and identify reliable prognostic biomarkers and therapeutic targets.\u003c/p\u003e\u003cp\u003eThe chaperonin containing t-complex 1 (CCT) is a molecular chaperone present in the cytoplasm of all eukaryotes, comprising eight distinct subunits designated as CCT1-8(Brackley and Grantham \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Vallin and Grantham \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Actin and tubulin, the main folding substrates of CCT, require interaction with CCT for proper folding both in vivo and in vitro(Valpuesta et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Given their close association with cancer development, studying CCT's role in cancer is important(Khromova et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Parker et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Previous studies reveal CCT3 fuels lung adenocarcinoma progression via glycolysis and EIF3G-mediated translation(Chen et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). CCT4 enhances glucose metabolism and chemotherapy resistance in esophageal squamous cell carcinoma through the AMPK/AKT/NRF2 pathway(Fang et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Roles of CCT1, CCT2, CCT5, CCT6A, and CCT8 in cancer have also been documented(Cai et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Chang et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, CCT7's role, especially in COAD, remains poorly understood. Bioinformatics analyses show elevated CCT7 mRNA levels in colorectal cancer tissues compared to adjacent normal tissues(Lim et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), but its function in COAD is unclear and warrants further investigation.\u003c/p\u003e\u003cp\u003eTumor development is closely associated with the tumor microenvironment (TME), with immune infiltrating cells as key TME components gaining increasing attention(Erasha et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Guo and Xu \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Immune checkpoints, molecules expressed on immune cells, play an important role in regulating immune cell activity and affecting tumor prognosis(Arafat 2024; Franzin et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The emergence and significant efficacy of immunotherapy have enhanced the value of immune-related biomarkers. However, little is known about the relationship between CCT7 and immune infiltrating cells or immune checkpoints in COAD. This study aims to explore CCT7 expression in COAD, its role and mechanisms in COAD development, its association with COAD immune infiltration and its influence on immunotherapy and chemotherapy.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003ePatients and tissue samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll clinical tissue specimens used in this study were sourced from the Second Affiliated Hospital of Zhengzhou University and verified by histopathology. We conducted immunohistochemical staining on 60 COAD tissues and their paired adjacent normal colon tissues. Written informed consent was obtained from the patients for the use of these clinical materials in research, and approval was granted by the Institutional Research Ethics Committee of the Second Affiliated Hospital of Zhengzhou University. The study adhered to all relevant ethical regulations regarding human participants. The clinical characteristics of COAD patients are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical characteristics of COAD patients from COAD clinical specimens\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of samples(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003eM stage\u003c/p\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003cp\u003eN stage\u003c/p\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003cp\u003eT stage\u003c/p\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003cp\u003eTumor location\u003c/p\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003cp\u003eLoss of MMR protein\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eLymphatic invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNon nodal tumor deposits\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003ePostopTreat\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eVenous invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003cp\u003eWell differentiated\u003c/p\u003e\n \u003cp\u003eModerately differentiated\u003c/p\u003e\n \u003cp\u003ePoorly differentiated\u003c/p\u003e\n \u003cp\u003eOverall survival\u003c/p\u003e\n \u003cp\u003eAlive\u003c/p\u003e\n \u003cp\u003eDead\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(50.0)\u003c/p\u003e\n \u003cp\u003e30(50.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e54(90.0)\u003c/p\u003e\n \u003cp\u003e6(10.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39(65.0)\u003c/p\u003e\n \u003cp\u003e15(25.0)\u003c/p\u003e\n \u003cp\u003e6(10.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4(6.7)\u003c/p\u003e\n \u003cp\u003e9(15.0)\u003c/p\u003e\n \u003cp\u003e40(66.6)\u003c/p\u003e\n \u003cp\u003e7(11.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30(50.0)\u003c/p\u003e\n \u003cp\u003e30(50.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43(71.7)\u003c/p\u003e\n \u003cp\u003e17(28.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28(46.7)\u003c/p\u003e\n \u003cp\u003e32(53.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43(71.7)\u003c/p\u003e\n \u003cp\u003e17(28.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14(23.3)\u003c/p\u003e\n \u003cp\u003e46(76.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43(71.7)\u003c/p\u003e\n \u003cp\u003e17(28.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11(18.3)\u003c/p\u003e\n \u003cp\u003e40(66.7)\u003c/p\u003e\n \u003cp\u003e9(15.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42(70.0)\u003c/p\u003e\n \u003cp\u003e18(30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTCGA and GEO Data Collection and Processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNA-sequencing data of COAD and the related clinical data (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) were obtained from The Cancer Genome Atlas (TCGA) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/repository)(Weinstein et al. 2013\u003c/span\u003e\u003c/span\u003e). TCGA-COAD was used for the investigation of CCT7 expression and its prognostic value, Gene Ontology-Biological Process (GO-BP) enrichment analysis, immune-related analysis, and drug sensitivity.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical characteristics of COAD patients from TCGA database\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of samples(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e153(45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e183(54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003eM stage\u003c/p\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003cp\u003eN stage\u003c/p\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003cp\u003eT stage\u003c/p\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003cp\u003eTumor location\u003c/p\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003eLoss of MMR protein\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003eLymphatic invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003eNon nodal tumor deposits\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003eCancer status\u003c/p\u003e\n \u003cp\u003eTumor free\u003c/p\u003e\n \u003cp\u003eWith tumor\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003ePostopTreat\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003eVenous invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003eOverall survival\u003c/p\u003e\n \u003cp\u003eAlive\u003c/p\u003e\n \u003cp\u003eDead\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e180(53.6)\u003c/p\u003e\n \u003cp\u003e156(46.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e280(83.3)\u003c/p\u003e\n \u003cp\u003e56(16.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e201(59.8)\u003c/p\u003e\n \u003cp\u003e76(22.6)\u003c/p\u003e\n \u003cp\u003e59(17.6)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8(2.4)\u003c/p\u003e\n \u003cp\u003e60(17.9)\u003c/p\u003e\n \u003cp\u003e231(68.8)\u003c/p\u003e\n \u003cp\u003e37(11.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e140(41.7)\u003c/p\u003e\n \u003cp\u003e112(33.3)\u003c/p\u003e\n \u003cp\u003e84(25)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e230(68.5)\u003c/p\u003e\n \u003cp\u003e37(11.0)\u003c/p\u003e\n \u003cp\u003e69(20.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e176(52.4)\u003c/p\u003e\n \u003cp\u003e130(38.7)\u003c/p\u003e\n \u003cp\u003e30(8.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e133(39.6)\u003c/p\u003e\n \u003cp\u003e26(7.7)\u003c/p\u003e\n \u003cp\u003e177(52.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e206(61.3)\u003c/p\u003e\n \u003cp\u003e55(16.4)\u003c/p\u003e\n \u003cp\u003e75(22.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e184(54.8)\u003c/p\u003e\n \u003cp\u003e106(31.5)\u003c/p\u003e\n \u003cp\u003e46(13.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e221(65.8)\u003c/p\u003e\n \u003cp\u003e74(22.0)\u003c/p\u003e\n \u003cp\u003e41(12.2)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e268(79.8)\u003c/p\u003e\n \u003cp\u003e68(20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eMicroarray data of GSE39582, GSE41258, GSE37364, GSE44076 and GSE17538 were retrieved from Gene Expression Omnibus (GEO) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/)(Marisa et al. 2013\u003c/span\u003e\u003c/span\u003e; Sheffer et al. \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e; Smith et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sol\u0026eacute; et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Valcz et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). GSE39582 was applied for CCT7 expression and GO-BP enrichment analysis. GSE39582, GSE44076 and GSE41258 were analyzed for CCT7 expression. GSE17538 was taken for survival analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell lines and culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe human COAD cell lines (RKO, HCT-116) and the normal colon epithelial cell line (NCM460) were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). RKO and HCT-116 cells were cultured in 1640 medium, while NCM460 cells were cultured in DMEM medium. All media were supplemented with 10% fetal bovine serum (FBS) (Genial Biologicals, Inc.) and 1% penicillin-streptomycin mixture. Cells were incubated in a humidified atmosphere with 5% CO₂ at 37\u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction of siRNA knockdown target gene cell lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTransient transfection siRNA (siCCT7, siNC) was provided by GenePharma (GenePharma, Shanghai, China). Cultured COAD cells (RKO, HCT-116) were seeded in a six-well plate at equal densities using complete medium. When cell confluence reached approximately 50%, the mixed reagent was mixed with 100 \u0026micro;L of buffer per well, with 5.85 \u0026micro;L of transfection reagent (Polyplus-transfection\u0026reg;, jetPRIME\u0026reg;, France) added. The mixture was incubated with 4.5 \u0026micro;L of siRNA at room temperature for 10 minutes and then added to the six-well plate. The siRNA targeting CCT7 used in this study had the following sequences: sense 5\u0026apos;-CAUUCUCUAUGACAAGUUAGA-3\u0026apos; and antisense 5\u0026apos;-UAACUUGUCAUAGAGAAUGUU-3\u0026apos;. The negative control siRNA sequences were: sense 5\u0026apos;-UUCUCCGAACGUGUCACGUTT-3\u0026apos; and antisense 5\u0026apos;-ACGUGACACGUUCGGAGAATT-3\u0026apos;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative real-time polymerase chain reaction (qRT-PCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted using TRIzol reagent (Invitrogen, USA) following the manufacturer\u0026apos;s instructions. cDNA was synthesized using a reverse transcription kit (Vazyme, Nanjing). qRT-PCR was performed in a 20 \u0026micro;L reaction mixture using SYBR Green qPCR Master Mix (Vazyme, Nanjing) and the Applied ABI QuantStudio 3 Real-Time PCR System (Thermo Fisher Scientific, Inc.). The primer pairs used for qRT-PCR were: CCT7 forward primer 5\u0026apos;-GCTGGTGTTGCATTCAAGAAG-3\u0026apos; and reverse primer 5\u0026apos;-TTGCCTGATAATCCTCAACTGTG-3\u0026apos;; GAPDH forward primer 5\u0026apos;-GGAGCGAGATCCCTCCAAAAT-3\u0026apos; and reverse primer 5\u0026apos;-GGCTGTTGTCATACTTCTCATGG-3\u0026apos;. Relative expression was normalized to the internal reference gene GAPDH using the 2-\u0026Delta;\u0026Delta;Ct method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were lysed using a radio-immunoprecipitation assay buffer (Cwbio, Jiangsu, China), and the protein concentration was determined using a bicinchoninic acid protein assay kit (Beyotime, Shanghai, China). Protein samples (30 \u0026micro;g/lane) were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis on 10% gels and transferred onto polyvinylidene fluoride membranes. The membranes were blocked with 10% skim milk at room temperature for 2 hours, then incubated overnight at 4\u0026deg;C with primary antibodies against CCT7 (15994-1-AP; Proteintech, China) and \u0026beta;-actin (AC026; Abclonal, China). After incubation, the membranes were treated with anti-rabbit horseradish peroxidase secondary antibody (SA00001-2; Proteintech, China) at room temperature for 1 hour. Protein bands were visualized using an enhanced chemiluminescence reagent kit (Abbkine Scientific Co., Ltd, China) and scanned with an imaging system (ProteinSimple, Inc.). Protein band densities were quantified using ImageJ software v1.8.0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell counting Kit-8 (CCK-8) assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell proliferation ability was assessed using the CCK-8 assay (Abbkine Scientific Co., Ltd, China). Transfected siNC and siCCT7 cells were seeded in 96-well plates and incubated at 37\u0026deg;C for 24, 48, 72, and 96 hours. After adding 10 \u0026micro;L of CCK-8 reagent to each well and incubating in the dark for 1.5 hours, absorbance was measured at 450 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eColony formation assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eColony formation assay was employed to evaluate the cloning capability of COAD cells with stable CCT7 knockdown. The transfected siNC and siCCT7 cells were seeded in six-well plates at approximately 1000 cells per well. After 15 days of culture, RKO and HCT-116 cells were fixed with 4% fixative solution and stained with 0.1% crystal violet staining solution (Solarbio Life Sciences, Beijing, China). Colonies were washed with distilled water, photographed, and counted using ImageJ software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell invasion assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRKO and HCT-116 cells were digested and resuspended in serum-free 1640 medium at a density of 1 \u0026times; 10⁵ cells/mL. Cell invasion ability was assessed using the Transwell assay. The lower chamber of each well was filled with 600 \u0026micro;L of complete medium containing 10% FBS. Matrigel was diluted 1:8 with serum-free medium, and 100 \u0026micro;L of this mixture was added to the upper chamber. Subsequently, 200 \u0026micro;L of the cell suspension was seeded into the upper chamber of a 24-well Transwell insert with a polycarbonate membrane (8.0 \u0026micro;m pore size). After 48 hours of incubation, cells on the lower surface of the membrane were fixed, stained, and counted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell migration assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRKO and HCT-116 cells were digested and resuspended in serum-free 1640 medium at a density of 1 \u0026times; 10⁵ cells/mL. Cell migration ability was assessed using the Transwell assay. The lower chamber of each well was filled with 600 \u0026micro;L of complete medium containing 10% FBS. Subsequently, 200 \u0026micro;L of the cell suspension was seeded into the upper chamber of a 24-well Transwell insert with a polycarbonate membrane (8.0 \u0026micro;m pore size). After 48 hours of incubation, cells on the lower surface of the membrane were fixed, stained, and counted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunohistochemistry (IHC) assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 60 COAD specimens were cut into 4-\u0026micro;m sections and fixed on glass slides for microscopy. The tissue sections on the slides were then deparaffinized and rehydrated using gradient concentrations of malondialdehyde and ethanol. Next, the slides were immersed in boiling Tris/ ethylenediaminetetraacetic acid (pH 9.0) for 20 minutes for antigen retrieval. The slides were subsequently immersed in 3% H₂O₂ for 10 minutes to inhibit endogenous peroxidase. Then, the slides were incubated with a primary antibody against CCT7 (1:250; 15994-1-AP; Proteintech, China), followed by the HRP secondary antibody (RGAR011; Proteintech, China), and were washed three times with phosphate-buffered saline. Finally, the sections were stained with 3,3\u0026apos;-diaminobenzidine and substrate chromogen (Dako) for 2 minutes at room temperature and then counterstained with hematoxylin for 40 seconds. Slides incubated only with the secondary antibody without the primary antibody were used as the negative control.\u003c/p\u003e\n\u003cp\u003eThe staining of each section was evaluated by two independent researchers blinded to the clinicopathological parameters. Immunoreactivity for CCT7 expression was evaluated using semi-quantitative immunoreactivity score (IRS) system, according to the intensity of staining (IS) (0-negative; 1-weak; 2-moderate; 3-strong) and area of positivity (AP) (0, 0\u0026ndash;25%; 1, 25\u0026ndash;50%; 3, 50\u0026ndash;75%; 4, 75\u0026ndash;100%), and recorded with H-score. The final H-score was obtained by multiplying the IS and AP. In this study, CCT7 expression was regarded as low expression when the score was \u0026lt;\u0026thinsp;6, and high expression when the score was \u0026ge;\u0026thinsp;6. The immunohistochemical staining was assessed by two separate pathologists who were blinded to patients\u0026rsquo; information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO-BP enrichment analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpearman\u0026apos;s test was conducted using R software based on TCGA-COAD and GSE39582. CCT7-related genes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and absolute value of correlation coefficient\u0026thinsp;\u0026ge;\u0026thinsp;0.35) were subjected to GO-BP enrichment analyses using the Metascape database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://metascape.org/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmune Infiltration Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSingle sample gene set enrichment analysis (ssGSEA) was applied for determination of immune infiltration based upon the immune gene sets(Charoentong et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEvaluation of drug sensitivity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe R language and the \u0026quot;oncopredict\u0026quot; package were employed to calculate the sensitivity score of each sample in the TCGA-COAD dataset for 199 anticancer drugs, with a higher sensitivity score indicating lower drug sensitivity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCalculation of the scores for immune checkpoint inhibitor therapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe R language and the weighted analysis were utilized to calculate the scores for PD-1 and CTLA-4 inhibitor therapies.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eStatistical analyses were performed using SPSS 26.0 (IBM, USA) and GraphPad Prism 8 (version 8.0.2, GraphPad Software, San Diego, CA, USA). Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). The independent-samples t-test or paired-samples t-test was used for comparisons between two groups, while one-way analysis of variance (ANOVA) was applied for three or more groups. Non-parametric tests were used if data were not normally distributed or had non-homogeneous variances. The Kaplan-Meier method with Log-Rank test was employed to evaluate the impact of CCT7 on COAD prognosis. Cox regression analysis was performed for univariate and multivariate analyses of CCT7 and clinicopathological parameters. In univariate regression, variables with a p-value less than 0.2 were included in the multivariate regression. Pearson correlation was used for normally distributed samples, while Spearman correlation was applied for non-normally distributed ones. Categorical data are presented as frequencies and percentages (%), and inter-group comparisons were conducted using the \u0026chi;\u0026sup2; test. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eAbnormal high expression of CCT7 in COAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe expression of CCT7 in COAD was analyzed using TCGA-COAD and GEO datasets. Results revealed significantly higher CCT7 mRNA expression in COAD cancer tissues than in pericancerous tissues (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA-F, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). To validate these findings, western blotting and qRT-PCR were performed to detect CCT7 expression in COAD cell lines. The results indicated that the protein and mRNA expression of CCT7 were markedly elevated in COAD cancer cells (RKO and HCT-116 cells) compared to normal colon epithelial cells (NCM460 cells) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eG and H, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Immunohistochemical analysis showed that CCT7 was mainly localized in the cell cytoplasm (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eI). Representative immunohistochemical results of tumor tissues and corresponding adjacent normal tissues are shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eI. The final H-scores indicated that CCT7 protein was highly expressed in 38 of 60 (63.3%) COAD samples compared to 11 of 60 (18.3%) adjacent normal samples, with a statistically significant difference (\u003cem\u003e\u0026chi;\u0026sup2;\u003c/em\u003e = 25.145, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHigh expression of CCT7 in COAD cancer tissues is significantly associated with poor prognosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaplan-Meier and Log-Rank analyses based on TCGA-COAD and GSE17538 datasets, and COAD clinical specimens revealed that COAD patients with high CCT7 expression had significantly reduced survival time compared to those with low CCT7 expression (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). To evaluate the independent prognostic significance of CCT7 expression, Cox regression analyses were performed using TCGA-COAD dataset and COAD clinical specimens. In TCGA-COAD dataset, univariate analysis identified age, M stage, N stage, T stage, loss of MMR protein, lymphatic invasion, cancer status, PostopTreat, venous invasion, and CCT7 expression as predictors of prognosis. Multivariate analysis indicated that M stage, N stage, non-nodal tumor deposits, cancer status, and CCT7 expression were independent predictors of prognosis (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). By using COAD clinical specimens, univariate analysis showed that M stage, N stage, T stage, loss of MMR protein, venous invasion, and CCT7 expression were predictors of prognosis. Multivariate analysis indicated that N stage, tumor location, venous invasion, and CCT7 expression were independent predictors of prognosis (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO-BP enrichment analysis for biological functions of CCT7\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore CCT7\u0026apos;s specific functions in COAD development, we conducted Gene Ontology-Biological Process (GO-BP) enrichment analysis using TCGA-COAD and GSE39582 datasets. First, the correlations between CCT7 expression and other genes in the two databases were analyzed. Genes with |rs| \u0026ge; 0.35 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were selected for enrichment analysis (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA and B). The results indicated that CCT7 may be involved in regulating biological processes related to cell proliferation and microtubule activities in COAD (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC and D, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings suggest that CCT7 might play significant roles in regulating COAD cell proliferation and metastasis.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKnocking down CCT7 inhibited the proliferation, migration and invasion of COAD cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRKO and HCT-116 cells, which exhibit relatively high CCT7 expression, were chosen for further study. After transfection with siCCT7 and a negative control siNC, we measured the mRNA and protein levels of CCT7. The results showed that both mRNA and protein expression of CCT7 were markedly reduced in siCCT7-transfected cells compared to siNC-transfected controls (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA and B, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This indicates successful transfection of RKO and HCT-116 cells, which are suitable for subsequent experiments. The impact of CCT7 expression on cell proliferation was assessed using the CCK-8 assay. The results revealed that RKO and HCT-116 cells with CCT7 knockdown developed a significant reduction in proliferation compared to control cells at 96 h after transfection (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The colony formation assay was conducted to evaluate the multiplication of RKO and HCT-116 cells transfected with siCCT7. Results indicated that compared to the control group, the siCCT7 transfection group exhibited a marked decrease in the number of newly formed colonies, along with impaired colony formation ability (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Transwell assays were performed to evaluate the migration and invasion of RKO and HCT-116 cells. Compared to the siNC group, the number of migrated and invaded cells was significantly reduced in the siCCT7 group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eE and F, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelations between CCT7 expression and infiltrating immune cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the TCGA-COAD dataset, the associations of immune infiltration with CCT7 expression were investigated using ssGSEA algorithm and Spearman\u0026apos;s correlation analysis. The results indicated that CCT7 expression was negatively associated with most immune cells, including central memory CD4 and CD8 T cells, effector memory CD4 and CD8 T cells, T follicular helper cell, type 1 and type 2 T helper cells (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). To validate the above findings, the correlation between the expression of CCT7 and the expression of immune cell markers was investigated. It is revealed that CCT7 expression negatively correlated with the expression of most immune cell markers (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These results suggest that CCT7 expression levels may influence the immune infiltration characteristics of COAD.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003cstrong\u003eTable 3 The correlation between CCT7 expression and immune infiltration in colonic adenocarcinoma\u003c/strong\u003e\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003cstrong\u003eTable 4 The correlation between CCT7 expression level and immune cell marker expression level in colonic adenocarcinoma\u003c/strong\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of CCT7 Expression on the Efficacy of Immune Checkpoint Inhibitor Therapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the impact of CCT7 expression on the therapeutic efficacy of immune checkpoint inhibitors in the treatment of COAD, this study examined the correlations between CCT7 expression and the expression of immune checkpoints programmed cell death 1 (PD-1) and cytotoxic T-lymphocyte associated protein 4 (CTLA-4), as well as their ligands PD ligand 1 (PD-L1), PD ligand 2 (PD-L2), CD80 and CD86, using the TCGA-COAD dataset. Although there was no correlation between the expression of CCT7 and that of PD-1 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA, P\u0026thinsp;=\u0026thinsp;0.181), the results demonstrated that CCT7 expression negatively correlated with the expression of CTLA-4, PD-L1, PD-L2, CD80, and CD86 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eB-F, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Subsequently, immune checkpoint inhibitor therapy scores and their correlations with CCT7 expression were analyzed using the TCGA-COAD dataset. The outcomes suggested that the CCT7 expression was negatively associated with the scores for PD-1 and CTLA-4 inhibitor therapies (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eG and H, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In summary, these results suggest that patients with high CCT7-expressing COAD may have a poor response to immune checkpoint inhibitors.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDrug Sensitivity Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the impact of CCT7 expression on the efficacy of various anticancer drugs in treating COAD, this study analyzed the sensitivity scores of individual COAD samples from the TCGA-COAD dataset to multiple anticancer drugs, with higher scores indicating lower drug sensitivity (i.e., reduced responsiveness), and investigated the correlation between drug sensitivity and CCT7 expression. The results showed that the CCT7 expression was negatively correlated with the sensitivity scores of OSI-027, 5-Fluorouracil, VX-11e, MK-1775, Palbociclib, Oxaliplatin, and Vorinostat (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA-G, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, there was a positive correlation between the CCT7 expression and the drug sensitivity scores of AZD6482, AZD8186, NU7441, ZM447439, JQ1, and Doramapimod (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eH-M, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCCT is essential for maintaining cellular protein homeostasis, as it facilitates the folding of major cytoskeletal proteins, including tubulin and actin. Research has demonstrated that the protein expression of CCT is elevated in 18 types of cancer cell lines when compared to normal paired cells(Boudiaf-Benmammar et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Various CCT subunits have been implicated in cancer: CCT2 drives CRC proliferation and metastasis via the Hedgehog pathway under hypoxia(Park et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); HOXB2 upregulates CCT6A to enhance CRC proliferation and invasion(Yang et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); CCT8 promotes CRC progression through the P53 pathway(Liao et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although bioinformatics reveals CCT7 overexpression in CRC tissues(Lim et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), its role in COAD development remains unclear. This study investigated the role of CCT7 in COAD development and its correlations with immunotherapy and chemotherapy.\u003c/p\u003e\u003cp\u003eIn line with the increased expression of CCT2, CCT5 and CCT7 in CRC tissues(Ahmed et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Park et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the present study, through analyzing the TCGA and GEO databases, found that the mRNA expression of CCT7 was statistically significantly elevated in COAD tissues compared with normal samples. Similar results were also obtained in colon cancer cells, normal colon cells, and COAD clinical specimens using qRT-PCR, western blotting, and IHC techniques. In addition, Kaplan\u0026ndash;Meier and Log-Rank methods showed that high CCT7 expression was associated with worse prognosis in COAD patients and Cox regression analysis indicated that high CCT7 expression was an independent factor for prediction of poor prognosis, which was consistent with the prognostic value of CCT2 in breast cancer, CCT5 in gastric cancer and CCT3 in head and neck squamous cell carcinoma (HNSCC) and cervical cancer(Chen et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Dou and Zhang \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Collectively, these investigations suggested that CCT7 probably served as an oncogene in COAD and was a potential prognostic biomarker for COAD patients.\u003c/p\u003e\u003cp\u003eTo define the detailed functions of CCT7 in COAD, GO-BP enrichment analysis was used to determine CCT7-related biological processes. The results revealed that CCT7 exerted a possible role in the regulation of cell proliferation and the activities of microtubules in COAD. Microtubules, crucial tracks for transporting organelles and molecules via motor proteins, facilitate cell migration through the transport of essential proteins and signaling molecules to the cell front. During cell migration, microtubules and actin collaborate in transferring mechanical forces: microtubules provide flexural stiffness, while actin filaments generate contractile force, synergistically ensuring efficient cell movement. To further validate the aforementioned results, the effect of CCT7 on biological behaviors of COAD cells was examined.\u003c/p\u003e\u003cp\u003eIt was reported that CCT2, CCT3 and CCT8 possessed the ability to promote proliferation of tumor cells in breast cancer, HNSCC, cervical cancer and CRC respectively(Chen et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Dou and Zhang \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liao et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Likewise, our functional experiments showed that knockdown of CCT7 suppressed proliferation of COAD cells, which was in accord with the results of enrichment analysis. Moreover, CCT2, CCT3 and CCT8 enhanced the metastatic phenotype of cancer cells in breast cancer, HNSCC, cervical cancer and CRC respectively (Chen et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Dou and Zhang \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liao et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and the similar effects of CCT7 on COAD cells were found by the present study, which were consistent with the results of enrichment analysis. Taken together, our results demonstrated that high CCT7 expression correlated with malignant progression of COAD. Combining the research findings on the prognostic significance of elevated CCT7 expression in COAD patients, the roles and mechanisms of CCT7 in the tumorigenesis and progression of COAD have been partially determined.\u003c/p\u003e\u003cp\u003eFurthermore, this study investigated the influence of CCT7 expression on the efficacy of immunotherapy and chemotherapy. Results from ssGSEA immune infiltration analysis and correlation analysis revealed a negative correlation between CCT7 expression and the infiltration of most immune cells, as well as a negative correlation with the expression levels of most immune cell markers. These findings implied that high expression of CCT7 may reduce the infiltration of immune cells, thereby compromising the effectiveness of immune-activating agents in the therapy of COAD. Additionally, CCT7 expression showed a negative correlation with PD-L1, PD-L2, CTLA-4, CD80, and CD86, along with the scores for PD-1 and CTLA-4 inhibitor therapies, indicating that COAD tumors with high CCT7 expression may respond poorly to immune checkpoint inhibitors. These findings provide a basis for studying CCT7-targeted therapy combined with immunotherapy.\u003c/p\u003e\u003cp\u003eDrug sensitivity analysis demonstrated that COAD samples with high CCT7 expression developed high sensitivity to 5-Fluorouracil and Oxaliplatin, both of which are well-established clinical agents for COAD treatment(Shaham et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Consequently, high CCT7 expression may enhance the therapeutic efficacy of conventional clinical drugs for COAD. Moreover, our results also indicated that COAD samples with high CCT7 expression exhibited high sensitivity to OSI-027, VX-11e, MK-1775, Palbociclib, and Vorinostat, while showing low sensitivity to AZD6482, AZD8186, NU7441, ZM447439, JQ1, and Doramapimod. These findings offer crucial insights for clinical drug selection.\u003c/p\u003e\u003cp\u003eThere exist several limitations in our study. Firstly, the signaling pathways responsible for the effect of CCT7 on the biological behaviors of COAD cells were unclear and should be identified in future research. Secondly, the associations of CCT7 expression with immune infiltration and immunotherapy score were determined based on bioinformatic databases and therefore, in vivo and in vitro experiments should be employed to investigate the effect of CCT7 on immunotherapy and the underlying mechanisms. Lastly, in vivo and in vitro experiments should be conducted to confirm the influence of CCT7 expression on chemotherapy, as the impact of CCT7 on drug sensitivity was obtained only through bioinformatics analysis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, our research demonstrates that the elevated expression of CCT7 in COAD may impact the proliferation, migration, and invasion of tumor cells, and ultimately influence the prognosis of patients. Moreover, our findings also indicate that the expression level of CCT7 can affect the efficacy of both immunotherapy and chemotherapy, thereby serving as a valuable reference for clinical treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics Approval and Consent to Participate\u003c/h2\u003e\u003cp\u003e Our study has been approved by the Institutional Research Ethics Committee of the Second Affiliated Hospital of Zhengzhou University and written informed consent was provided by every patient.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by grants from the Henan Provincial Natural Science Foundation (No. 252300421368), the Top Talents Funding of the Second Affiliated Hospital of Zhengzhou University (No. 2020BJRCB04), and BEIJING SCIENCE AND TECHNOLOGY INNOVATION MEDICAL DEVELOPMENT FOUNDATION (No. KC2023-JX-0186-FM054).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZ.W.C. and H.N. contributed to the conception and design of the study. L.W.X. wrote the first draft of the manuscript. Z.W.C., H.N. and L.W.X. analyzed the bioinformatical data. S.Q.Z., M.Y.H. and H.N. provided COAD samples and detected CCT7 expression. L.W.X. conducted cell-based experiments and performed statistical analysis. Z.W.C. and H.N. supervised all the work. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors thank the contributors of TCGA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/repository\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov/repository\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and GEO (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for sharing the related data.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhmed MZ et al (2025) Pan-cancer analysis reveals immunological and prognostic significance of CCT5 in human tumors. 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Cancer Cell Int 20:218\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang X et al (2018) Chaperonin-containing T\u0026ndash;complex protein 1 subunit 8 promotes cell migration and invasion in human esophageal squamous cell carcinoma by regulating α-actin and β-tubulin expression. Int J Oncol 52(6):2021\u0026ndash;2030\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang X et al (2022) HOXB2 increases the proliferation and invasiveness of colon cancer cells through the upregulation of CCT6A. Mol Med Rep 25(5):174\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang Y et al (2022) MicroRNAs (miRNAs): Novel potential therapeutic targets in colorectal cancer. Front Oncol 12:1054846\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-molecular-histology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hijo","sideBox":"Learn more about [Journal of Molecular Histology](https://www.springer.com/journal/10735)","snPcode":"10735","submissionUrl":"https://submission.springernature.com/new-submission/10735/3","title":"Journal of Molecular Histology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"colonic adenocarcinoma, CCT7, prognosis, immune infiltration, drug sensitivity Wenchao Zhao, [email protected]","lastPublishedDoi":"10.21203/rs.3.rs-7271196/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7271196/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCCT7, a member of the t-complex polypeptide 1 chaperone family, facilitates protein folding in an ATP-dependent manner. To date, the role of CCT7 in the onset and progression of malignant tumors remains unclear. This study investigated the expression of CCT7 in colonic adenocarcinoma (COAD) and its role in the initiation and development of COAD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe bioinformatic databases were used to examine the CCT7 expression in COAD, and the results were verified using human clinical specimens by immunohistochemistry (IHC) assay. The association of CCT7 expression with prognosis was evaluated by Kaplan-Meier method and Cox regression analysis. Gene Ontology-Biological Process (GO-BP) enrichment analysis was used to investigate the potential biological functions of CCT7 in COAD. CCK-8, colony formation and Transwell assays were carried out to explore the effect of CCT7 on proliferation, migration and invasion of human COAD cells. The correlations of CCT7 expression with immune infiltration, immunotherapy and drug sensitivity were determined by single sample gene set enrichment analysis (ssGSEA) and correlation analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCCT7 expression was up-regulated statistically in COAD tissues compared with normal colonic tissues (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05) and high expression of CCT7 predicted poor prognosis of COAD patients (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05). GO-BP enrichment analysis revealed that CCT7 was mainly involved in the processes of cell proliferation and microtubule activities(\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05), and down-regulation of CCT7 inhibited the proliferation, migration and invasion of COAD cells (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05). CCT7 was negatively associated with infiltration of most immunocytes and the scores for PD-1 and CTLA-4 therapy (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05). Moreover, drug sensitivity analyses showed that CCT7 affected the sensitivity of COAD samples to several anti-cancer drugs (\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCCT7 may function as an oncogene to promote the malignant phenotype of COAD, and serve as a promising biomarker for prognosis as well as a reference for clinical treatment in COAD.\u003c/p\u003e","manuscriptTitle":"CCT7 indicates a poor prognosis and is associated with immune infiltration in colonic adenocarcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-06 08:49:43","doi":"10.21203/rs.3.rs-7271196/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-07T18:39:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T16:03:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-01T08:20:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195248008077977913110654625674889501857","date":"2025-09-26T02:06:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"246632982284804624956593240270362124414","date":"2025-09-26T01:12:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72125739951559138589673856979296544661","date":"2025-09-25T01:53:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"15277889309053676415384057431165150734","date":"2025-09-04T16:49:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-27T08:02:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321428132453510202582204134730604568145","date":"2025-08-26T01:15:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-03T18:22:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-03T18:18:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-02T08:10:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Molecular Histology","date":"2025-08-01T12:18:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-molecular-histology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hijo","sideBox":"Learn more about [Journal of Molecular Histology](https://www.springer.com/journal/10735)","snPcode":"10735","submissionUrl":"https://submission.springernature.com/new-submission/10735/3","title":"Journal of Molecular Histology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"44cbd0e9-5e3e-473c-89c6-2e67c0276f52","owner":[],"postedDate":"August 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:12:04+00:00","versionOfRecord":{"articleIdentity":"rs-7271196","link":"https://doi.org/10.1007/s10735-026-10715-4","journal":{"identity":"journal-of-molecular-histology","isVorOnly":false,"title":"Journal of Molecular Histology"},"publishedOn":"2026-01-28 15:59:32","publishedOnDateReadable":"January 28th, 2026"},"versionCreatedAt":"2025-08-06 08:49:43","video":"","vorDoi":"10.1007/s10735-026-10715-4","vorDoiUrl":"https://doi.org/10.1007/s10735-026-10715-4","workflowStages":[]},"version":"v1","identity":"rs-7271196","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7271196","identity":"rs-7271196","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}