Published online Jul 21, 2026. doi: 10.3748/wjg.118071
Revised: February 6, 2026
Accepted: March 26, 2026
Published online: July 21, 2026
Processing time: 203 Days and 18.1 Hours
Identification of potential gastric cancer (GC) biomarkers is crucial for enhancing prognosis and developing therapy. During cell division, kinetochore-associated protein (KNTC) 1 ensures that chromosomes are separated properly during mito
To evaluate the prognostic significance of KNTC1 and delineate its influence on GC development.
KNTC1 expression in GC was evaluated through experimental methods and bioinformatics analysis. Clinical data were used to stratify patients, and Kaplan-Meier and Cox regression analyses assessed the prognostic significance of KNTC1. The relationship between KNTC1 expression and immune infiltration was explored using The Cancer Genome Atlas datasets.
KNTC1 exhibited elevated expression levels in GC cell lines. Elevated KNTC1 abundance showed a robust relationship with age, pathologic M, pathologic N, and poor prognosis. KNTC1 significantly influenced immune cell infiltration. Finally, phenotypic assays and xenograft models of GC demonstrated that KNTC1 promoted tumor progression.
Elevated KNTC1 correlates with poor outcomes of GC patients, suggesting that KNTC1 could serve as a potential biomarker in GC.
Core Tip: This study identifies kinetochore-associated protein (KNTC) 1, a key regulator of mitotic chromosome segregation, as a novel oncogenic factor in gastric cancer (GC). We demonstrated that KNTC1 was overexpressed in GC and closely associated with advanced clinicopathological features and poor prognosis. Importantly, KNTC1 expression correlated with immune cell infiltration and promoted tumor growth in vitro and in vivo. These findings highlight KNTC1 as a potential prognostic biomarker and therapeutic target for GC.
- Citation: Li YF, Weng CY, Wang M. Kinetochore-associated protein 1 as a prognostic biomarker in gastric cancer: Integrative bioinformatics and experimental validation. World J Gastroenterol 2026; 32(27): 118071
- URL: https://www.wjgnet.com/1007-9327/full/v32/i27/118071.htm
- DOI: https://dx.doi.org/10.3748/wjg.118071
Based on worldwide cancer data, gastric cancer (GC) ranks among the most commonly diagnosed cancers and is a leading cause of cancer-related mortality[1]. In its early stages, GC often presents with vague symptoms like mild indigestion, which are easily ignored[2]. By the time more significant signs manifest, such as early satiety and reflux, the cancer is frequently advanced and may have already metastasized, posing a significant challenge to healthcare systems worldwide. Identification of effective diagnostic and prognostic factors may enhance treatment strategies for GC patients and extend their survival.
Kinetochore-associated proteins (KNTCs) are crucial for maintaining cell cycle checkpoints, ensuring accurate chromosome alignment and spindle formation during cell division[3]. KNTC1 is responsible for producing a mito
This study confirmed KNTC1 expression using bioinformatics and laboratory-based experiments. We identified the clinicopathological characteristics, prognostic features and immune infiltration of GC patients with high KNTC1 ex
The TIMER-Gene module within the TIMER 2.0 platform was used to evaluate immune cell infiltration associated with KNTC1 expression[9,10]. Clinical data for GC patients were retrieved from The Cancer Genome Atlas (TCGA) dataset, with samples selected based on the availability of expression and clinical data. Immune infiltration analysis was con
To ensure accurate comparison between tumor and normal tissue expression data from TCGA and Genotype-Tissue Expression (GTEx), we performed normalization and batch correction using the specific method or tool (e.g., ComBat, limma, or other relevant methods). This process was applied to account for potential platform and batch effects, ensuring that tumor-normal differences were not confounded by these factors. The normalized data were then used for downstream analyses, including differential expression comparisons and survival analyses.
KNTC1 expression and prognosis data were sourced from the XIANTAO platform. GSE65801 dataset was downloaded from the Gene Expression Omnibus database. The Immune Infiltration panel was performed to evaluate the correlation between KNTC1 expression and immune cells.
The cBioPortal database[11] was utilized to investigate the frequency, copy number alteration, and mutation type of KNTC1 in TCGA pan-cancer atlas studies.
Patients were divided into high- and low-expression groups based on median KNTC1 levels. The Kaplan-Meier Plotter[12] was used to analyze overall survival (OS), progression-free survival (PFS), and post-progression survival (PPS).
The KNTC1-binding protein network was generated using the Online STRING database[13]. The top 100 genes associated with KNTC1 were identified, and the relationships between KNTC1 and the top three associated genes were analyzed using data from Gene Expression Profiling Interactive Analysis 2; a web server that processes RNA sequencing data from the TCGA and GTEx project[14].
GC and adjacent normal tissues were obtained from patients at the Wenzhou TCM Hospital of Zhejiang Chinese Medical University, with informed consent from all participants. The study was approved by the Institutional Ethics Committee, No. WZY2026-KT-011-01. Participants were recruited between March 15, 2019 and June 30, 2024. Except for incubation with anti-KNTC1 antibody (1:200), all procedures followed the previously described protocol[15]. Negative controls were processed in parallel by omitting the primary antibody. Stained sections were evaluated independently by two blinded pathologists. The H-score was calculated as ∑(IS × AP), where IS (0-3) represents staining intensity and AP (0-4) denotes the percentage of positive tumor cells.
The MKN45 and NUGC3 GC cell lines and the GES-1 normal gastric epithelial cell line were obtained from American Type Culture Collection (Shanghai, China). All cells were cultured in RPMI-1640 containing 10% fetal bovine serum. The sequence of short hairpin RNA (shRNA) targeting KNTC1 (shKNTC1) was as follows: 5'-TGAGTTTATGGGATATTTA-3'. The KNTC1 shRNA and vector control lentiviruses were produced by Genechem (Shanghai, China).
Protein extraction as well as sodium-dodecyl sulfate gel electrophoresis and membrane transfer procedures were performed as previously described[15]. Membranes were blocked with a non-protein blocking solution for 1 hour at room temperature and incubated overnight at 4 °C with primary antibodies against KNTC1 (1:1000, #ab85996; Abcam, MA, United States); cyclin-dependent kinase 4 (CDK4; 1:1000, #ab108357; Abcam, MA, United States); CDK6 (1:1000, #ab124821; Abcam, MA, United States); cyclin D1 (1:1000, #ab16663; Abcam, MA, United States); and glyceraldehyde-3-phosphate dehydrogenase (1:1000, #ab59164; Abcam, MA, United States). After rinsing, blots were treated with horseradish-peroxidase-linked secondary antibodies for 1 hour and developed by electrochemiluminescence.
For the wound healing assay, NUGC-3 cells were plated in a Culture-Insert (ibidi Biotechnology Company, Germany). After the insert was removed, the cell migration distance was captured at 0 and 48 hours. For colony formation, 1000 NUGC-3 cells were distributed onto 35-mm dishes and cultured for 2 weeks. For the Transwell assays, 5 × 105 NUGC-3 cells were seeded in Transwell chambers in serum-free medium for 48 hours, with or without Matrigel. Cells on the dishes and Transwell membranes were then fixed, stained and counted.
BALB/c-nude mice (male, age 5 weeks) were obtained from the Hangzhou Qizhen Animal Company, China. Animals were maintained under routine laboratory conditions with unrestricted food and water, and their health status was checked daily. Humane endpoints (≥ 20% body weight loss, severe lethargy, impaired mobility, or labored breathing) were predefined, and animals meeting these criteria were immediately killed by CO2 inhalation followed by cervical dislocation. A total of 12 (n = 6 per group) animals were used in the study. Animal welfare was strictly observed, with appropriate anesthesia applied to reduce discomfort, and all personnel were trained in proper animal handling.
The experiment adhered to the ARRIVE guidelines. Mice were randomly assigned to experimental groups (control vector or KNTC1 shRNA lentivirus) using a random number generator, and the assignment was blinded to the investigator during tumor volume assessment. A priori calculations indicated that enrolling six subjects per arm would provide 80% power to detect the expected effect at a two-sided significance threshold of 0.05.
A total of 5 × 106 NUGC-3 cells transfected with control vector or KNTC1 shRNA lentivirus were injected into the left armpits of mice. Tumor diameters were measured weekly, and tumor volumes were calculated using the formula: (long diameter × short diameter2)/2. At the end of the observation, mice were killed. Tumor images were photographed and tumor weights were recorded. All animal procedures were approved by the Animal Ethics and Welfare Committee of Zhejiang Chinese Medical University, No. IACUC-202304-0266.
Statistical analysis was performed using SPSS 25.0, with data presented as mean ± SD deviation and each experiment was conducted a minimum of three times. Group comparisons were performed using an unpaired Student’s t test for two groups, and one-way analysis of variance followed by Tukey’s post hoc test was used for multiple group comparisons. Tamhane-T2 and least significant difference tests were used for additional multiple comparisons. P < 0.05 was considered statistically significant.
KNTC1 mRNA expression in 33 cancer types was analyzed using TCGA and GTEx data via the XIANTAO online platform. KNTC1 was significantly overexpressed in 18 cancer types, including GC (Figure 1A). Compared with normal tissues, KNTC1 expression was markedly increased in GC tumor tissues (Figure 1B). Paired analyses of tumor and adjacent nontumorous tissues confirmed significantly higher KNTC1 expression in tumor samples, consistent with previous pan-cancer findings (Figure 1C). Immunohistochemical staining of five paired GC and adjacent tissues, together with western blot analysis of three paired samples, demonstrated consistently elevated KNTC1 expression in tumor tissues relative to adjacent normal tissues (Figure 1D-F). Consistent results were also observed in the GSE65801 dataset (Figure 1G). Receiver operating characteristic analysis revealed a 1-year area under the curve of 0.959 (Figure 1H), indicating strong predictive accuracy of KNTC1 expression for GC prognosis and supporting its potential value as a diagnostic biomarker.
To further explore the clinical relevance of KNTC1 expression in GC, its association with various clinicopathological features was analyzed using the XIANTAO platform. KNTC1 expression was significantly upregulated in gastric tumor tissues compared with normal tissues in both male and female patients (Figure 2A). In addition, KNTC1 expression showed a positive correlation with T stage, with higher expression observed in advanced T stages (Figure 2B). No significant associations were detected between KNTC1 expression and N stage, M stage, or histological grade, although elevated expression was observed among these subgroups relative to that in normal tissues (Figure 2C-E). Higher KNTC1 expression was detected in advanced pathological stages (III-IV) (Figure 2F). No significant association was observed between KNTC1 expression and Helicobacter pylori infection status (Figure 2G).
Patients with GC were categorized according to the median level of KNTC1, and survival analyses indicated that elevated expression corresponded to reduced OS and PPS (Figure 3A-C). Subgroup analyses revealed that KNTC1 expression was significantly correlated with prognosis across multiple clinicopathological features (Figure 3D-F). Specifically, elevated KNTC1 expression was associated with poorer OS in well-differentiated tumors (Figure 3D) and poorer PPS in mode
| Characteristics | Total (n) | Univariate analysis | Multivariate analysis | ||
| Hazard ratio (95%CI) | P value | Hazard ratio (95%CI) | P value | ||
| Age | 367 | ||||
| ≤ 65 | 163 | Reference | Reference | ||
| > 65 | 204 | 1.620 (1.154-2.276) | 0.005 | 1.803 (1.242-2.618) | 0.002 |
| Pathologic T stage | 362 | ||||
| T1-T2 | 96 | Reference | Reference | ||
| T3-T4 | 266 | 1.719 (1.131-2.612) | 0.011 | 1.529 (0.971-2.409) | 0.067 |
| Pathologic N stage | 352 | ||||
| N0-N1 | 204 | Reference | Reference | ||
| N2-N3 | 148 | 1.650 (1.182-2.302) | 0.003 | 1.630 (1.150-2.311) | 0.006 |
| Pathologic M stage | 352 | ||||
| M0 | 327 | Reference | Reference | ||
| M1 | 25 | 2.254 (1.295-3.924) | 0.004 | 2.110 (1.196-3.721) | 0.010 |
| Histologic grade | 361 | ||||
| G1 | 10 | Reference | |||
| G2 | 134 | 1.648 (0.400-6.787) | 0.489 | ||
| G3 | 217 | 2.174 (0.535-8.832) | 0.278 | ||
| KNTC1 | 370 | ||||
| Low | 185 | Reference | Reference | ||
| High | 185 | 0.697 (0.502-0.969) | 0.032 | 0.701 (0.497-0.988) | 0.043 |
Protein-protein interaction analysis using the STRING database identified several proteins interacting with KNTC1 (Figure 4A). The Gene Expression Profiling Interactive Analysis 2 database was used to identify the top 100 genes posi
Ontology-based over-representation testing suggested that transcripts linked to KNTC1 clustered primarily within annotations involving “organelle fission”, “chromosomal region”, “catalytic activity”, and “DNA helicase activity” (Figure 5A-C). Pathway over-representation mapping using the Kyoto Encyclopedia of Genes and Genomes database showed a clear concentration of cell cycle, DNA replication, and homologous recombination (Figure 5D). Genetic alteration analysis using cBioPortal showed that KNTC1 alterations occurred in < 6% of GC patients and included gene amplification, missense mutations, splice mutations, truncating mutations, and deep deletions (Figure 5E and F).
Immune infiltration analysis revealed that high KNTC1 expression was associated with increased CD8+ T-cell infiltration and decreased macrophage infiltration in GC, while no significant associations were observed with CD4+ T cells or B cells (Figure 6A). Further analysis of 24 immune cell subtypes showed that high KNTC1 expression was associated with increased activated dendritic cells, Th1 cells, central memory T cells, and Th2 cells, whereas B cells, macrophages, mast cells, and conventional dendritic cells were reduced (Figure 6B). Spearman correlation analysis demonstrated that 12 of the 24 immune cell subtypes were negatively correlated with KNTC1 expression (Figure 6C).
TIMER2.0 was used to examine links between KNTC1 expression and cancer-associated fibroblast (CAF) infiltration. Increased CAF infiltration was observed in adrenocortical carcinoma, esophageal carcinoma, liver hepatocellular carcinoma, mesothelioma, prostate adenocarcinoma, and thyroid carcinoma, whereas reduced CAF infiltration was observed in testicular germ cell tumor, and diffuse large B-cell lymphoma (Figure 7A). Correlation scatterplots are shown in Figure 7B-I. Although elevated KNTC1 abundance corresponded to improved outcomes in some immune subtypes, it was linked to poorer survival in GC patients with reduced CD4+ and CD8+ T-cell infiltration (Figure 8), suggesting that KNTC1 influences GC prognosis through modulation of immune infiltration.
KNTC1 expression was markedly higher in GC cell lines compared with normal gastric mucosal cells, with the highest expression observed in NUGC-3 cells (Figure 9A). Stable KNTC1 knockdown was established in NUGC-3 cells using lentiviral shRNA, resulting in effective downregulation of KNTC1 protein expression (Figure 9B). Colony formation assays showed a significant reduction in colony numbers following KNTC1 knockdown (Figure 9C and D). Wound-healing and Transwell assays demonstrated that KNTC1 depletion significantly impaired the migratory and invasive capacities of GC cells (Figure 9E-I). Functional analysis indicated suppression of cell-cycle-related pathways, accom
To assess the in vivo impact of KNTC1 silencing, subcutaneous xenografts were generated in mice. Tumors in the knockdown cohort displayed markedly slower expansion, with smaller volumes than those in the control group (Figure 9K). Mice were killed 60 days after tumor cell injection, and tumors were excised, photographed and weighed. Consistently, KNTC1 silencing resulted in significantly smaller tumor size and lower tumor weight (Figure 9L and M). Raw tumor volume data are provided in Supplementary Tables 1 and 2.
Prognostic biomarkers offer crucial insights into tumor progression and prognosis in untreated cases, playing a crucial role in personalized and precision medicine by preventing inappropriate treatment. In our research, KNTC1 was overexpressed in GC tumor tissues compared to para-cancerous or normal gastric tissues in the TCGA database, consistent with GC cell lines. Analysis of the TCGA database illustrated a positive connection between KNTC1 expression and tumor tumor-node-metastasis stage or histological grade, indicating a potential role for KNTC1 in the progression and spread of GC. OS, PFS and PPS among various subgroups revealed that elevated KNTC1 expression resulted in poor survival rates, especially in patients receiving 5-fluorouracil-based adjuvant therapy. Our findings indicate that KNTC1 is a reliable prognostic predictor in GC.
Traditional treatments like chemotherapy and radiotherapy, as well as newer immunotherapies such as immune checkpoint inhibitors (ICIs), can combat the tumor immunosuppressive environment[16]. In recent years, immunotherapy has emerged as a promising option for GC, particularly with the advent of ICIs targeting programmed cell death protein-1/programmed cell death ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated antigen 4[17]. The approval of pembrolizumab and nivolumab for GC patients with microsatellite instability-high or PD-L1-positive tumors represents a significant breakthrough, offering durable responses in a subset of patients. However, the response rate remains modest, and many patients do not benefit from immunotherapy due to the immunosuppressive tumor microenvironment and lack of sufficient immune infiltration. In our study, we found that KNTC1 was correlated with immune infiltration. Therefore, targeting KNTC1 may hold promise as a therapeutic strategy for GC and enhance the sensitivity of tumors to conventional chemotherapy and emerging immunotherapy. Further experimental studies are required to elucidate the exact mechanisms by which KNTC1 modulates chemotherapy and immunotherapy responses and to explore its potential as a therapeutic target to improve cancer treatment outcomes.
In GC, multiple efforts have been made to link CD8+ T-cell density with patient prognosis as well as treatment response. While CD8+ T cells are considered crucial for tumor-fighting response in the tumor microenvironment, studies on the role of intratumoral CD8+ T cells in GC have yielded inconsistent results[18-20]. A prior study[19] indicated a link between CD8+ T cells and reduced OS, contrasting with the findings of a subsequent study[20]. These results highlight the contentious predictive value and varied traits of CD8+ T cells in GC[21,22]. In our study, KNTC1 expression was associated with immune infiltration estimates, including altered CD8+ T-cell and macrophage signals. Importantly, accumulating evidence suggests that CD8+ T-cell quantity alone is insufficient. Functional state matters, and inactive CD8+ T-cell-rich tumors may still portend poor outcomes in GC[23]. Meta-analytic data also indicate that the prognostic impact of tumor-infiltrating lymphocytes varies by subtype and spatial distribution, which may explain inconsistencies among cohorts[24]. CAFs can drive immune exclusion and suppressive cytokine/extracellular matrix remodeling, and recent reviews highlight CAF reprogramming as a potential strategy to improve ICI efficacy[25]. These data support a working model in which KNTC1 may be linked to an immune context that is quantitatively infiltrated yet variably functional. Integration of immunotherapy-response annotations (e.g., microsatellite instability/tumor mutation burden, PD-L1 combined positive score, and ICI-treated cohorts) will be essential to clarify whether KNTC1 has predictive value beyond prognostic associations.
Given the potential link between high KNTC1 expression and cancer genesis, reducing KNTC1 expression may serve as a strategy to delay tumor growth. Previous research has demonstrated that KNTC1 silencing suppresses tumor cell proliferation, invasion and migration. KNTC1 knockdown significantly reduces the progression of several cancers, including colon cancer[26], esophageal squamous cell carcinoma[8] and bladder cancer[27]. Consist with previous studies, we demonstrated that downregulated KNTC1 suppressed the growth, migration and invasion of GC cells in vitro. Furthermore, inhibition of KNTC1 similarly suppressed GC tumor growth in a xenograft model[7]. Our results offer compelling support that KNTC1 silencing significantly impedes GC progression.
Notwithstanding the contributions of the present study, a number of limitations merit consideration. Firstly, the in silico approach used relied on public datasets, which are inherently predictive and may not fully capture the complexity of individual patient cases. These datasets, though widely used, are subject to limitations in terms of data quality, completeness and potential bias inherent in their collection. Moreover, the limited number of cases included for immunohistochemical evaluation may have undermined analytical sensitivity and restricted stratified comparisons. Secondly, while the xenograft models provided valuable information on tumor biology and the role of KNTC1, they may not have completely reproduced the human immune microenvironment. Differences between human tumors and the immune environment in mouse models could have introduced artifacts that affected the interpretation of our results. Using more sophisticated models, such as patient-derived xenografts or organoid cultures, may offer more relevant insights. Finally, while experiments confirmed the oncogenic function of KNTC1 in vitro and in vivo, the underlying mechanisms driving GC initiation and proliferation remain unclear. The lack of prospective validation in independent cohorts further limits the robustness of our conclusions. Future studies incorporating prospective clinical validation, as well as multicenter datasets, would strengthen the reliability and applicability of our findings.
By integrating publicly accessible gene expression datasets of cancer patients and experimental validation on GC cells, we investigated the significance of KNTC1, proposing it as a promising indicator for diagnosis and a potential therapeutic target.
We express our gratitude to The Cancer Genome Atlas, Gene Expression Omnibus, Human Protein Atlas, University of Alabama at Birmingham CANcer data analysis Portal, Wanderer, MethSurv, STRING, Gene Expression Profiling Interactive Analysis 2, cBioportal and similar online databases.
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