Keratin 17 Drives Endometrial Cancer Aggressiveness via Epithelial-Mesenchymal Transition: A Single-Cell Transcriptomic and Integrative Bioinformatics Study

Keratin 17 Drives Endometrial Cancer Aggressiveness via Epithelial-Mesenchymal Transition: A Single-Cell Transcriptomic and Integrative Bioinformatics Study | 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 Keratin 17 Drives Endometrial Cancer Aggressiveness via Epithelial-Mesenchymal Transition: A Single-Cell Transcriptomic and Integrative Bioinformatics Study Xiaole Song, Xuerou Chen, Qianwen Liu, Yajuan Ma, Xiaoran Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9264510/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Endometrial cancer (EC) is a common gynecological malignancy with increasing incidence, and advanced or recurrent cases have limited treatment options. The role of Keratin 17 (KRT17), a type I intermediate filament protein implicated in tumor progression in other cancers, remains unclear in EC. This study aimed to investigate the expression, prognostic significance, and functional mechanisms of KRT17 in EC. Bioinformatics analysis revealed significant upregulation of KRT17 in EC tissues, with elevated expression strongly correlated with adverse clinical outcomes and reduced overall survival. Single-cell RNA sequencing (scRNA-seq) analysis elucidated the distribution and expression profiles of KRT17 in malignant epithelial cells of endometrial cancer, and differential expression analysis combined with gene set enrichment analysis (GSEA) further confirmed the significant enrichment of KRT17 in the EMT pathway. In vitro functional assays confirmed that stable knockdown of KRT17 significantly inhibited the proliferation, migration, invasion, and spheroid formation of EC cells, and altered the expression of key EMT markers. In vivo animal models demonstrated that KRT17 knockdown effectively suppressed tumor growth and reversed the EMT process. Collectively, KRT17 functions as an oncogene in EC by activating EMT to drive malignant progression, representing a potential therapeutic target. Endometrial cancer Epithelial mesenchymal transition KRT17 Migration Proliferation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Endometrial cancer (EC) represents one of the most prevalent malignancies of the female reproductive system globally, with a continuously rising incidence. In 2020 alone, EC was responsible for over 417,000 new cases and approximately 97,000 deaths worldwide. Within China, EC constituted 3.9% of all new cancer diagnoses in women, with a concerning trend toward earlier onset (Henley et al., 2020; Morice, Leary, Creutzberg, Abu-Rustum, & Darai, 2016; Sung et al., 2021). While patients with early-stage disease typically achieve favorable outcomes through surgery and adjuvant therapy, the prognosis for those with advanced-stage (FIGO 2009 Stage III-IV) EC remains dismal, with a median overall survival (OS) of less than three years (Kalampokas et al., 2022). The advent of molecular classification has revolutionized the understanding of EC, categorizing it into four distinct subtypes based on genomic and histopathological features: POLE-mutated, TP53-abnormal, microsatellite instability-high (MSI-H)/mismatch repair-deficient (dMMR), and no specific molecular profile (NSMP). This molecular classification framework provides a critical foundation for precision medicine in EC; however, significant disparities in treatment response and clinical outcomes persist among the different subtypes (Kandoth et al., 2013). For instance, patients with MSI-H/dMMR tumors exhibit favorable responses to immune checkpoint inhibitors due to their high tumor mutational burden (O'Malley et al., 2022; Talhouk et al., 2017). However, targeted therapy options remain extremely limited for the NSMP subtype, which accounts for 40%–50% of cases. Therefore, there is an urgent need to identify novel biomarkers and therapeutic targets that are specific to distinct molecular subtypes (Karpel, Slomovitz, Coleman, & Pothuri, 2023). Keratin 17 (KRT17) is a type I intermediate filament protein that polymerizes into non-covalent filament networks, contributing to structural integrity and repair processes in epithelial tissues (Baraks et al., 2022). Pan-cancer analysis revealed significant upregulation of KRT17 in endometrial carcinoma tissues compared with normal endometrial tissues (Bai et al., 2019), suggesting its potential oncogenic role in endometrial carcinoma pathogenesis. Accumulating evidence indicates that KRT17 is aberrantly overexpressed in various malignancies, including head and neck cancer, non-small cell lung cancer, and gastric carcinoma (H. Hu et al., 2018; W. Wang et al., 2022; Z. Wang et al., 2019). In gynecological oncology, KRT17 is significantly upregulated in cervical cancer. Its elevated expression correlates strongly with histological poor differentiation, lymph node metastasis, and human papillomavirus type 16 (HPV16) infection, and serves as an independent predictor of poor prognosis beyond conventional serum biomarkers. Mechanistically, KRT17 attenuates the efficacy of platinum-based chemotherapy by modulating the Hippo signaling pathway and microtubule-mediated cell migration, thereby indirectly inducing chemoresistance and promoting lymph node metastasis in vivo (Escobar-Hoyos et al., 2014). Given that endometrial carcinoma is also an epithelial-derived malignancy and KRT17 has been established as an oncogenic driver in cervical and other gynecological cancers, its functional role in endometrial carcinoma warrants dedicated investigation. Notably, the clinical implications of KRT17 are highly context-dependent: in human epidermal growth factor receptor 2 (HER2)-positive breast cancer, high KRT17 expression associates with favorable survival outcomes (S. Tang et al., 2022), underscoring that its functional duality is shaped by tumor type and microenvironmental cues. At the molecular level, KRT17 drives tumorigenesis through multiple signaling axes. KRT17 upregulation activates protein kinase B (AKT) signaling, inducing EMT—a process marked by loss of epithelial polarity and cell-cell junctions coupled with acquisition of mesenchymal traits—thereby enhancing tumor cell migration and invasion. This mechanism underpins KRT17-mediated progression in esophageal and bladder cancers (Liu et al., 2020; Wu et al., 2017; P. Zhang et al., 2025). Additionally, KRT17 regulates metabolic reprogramming in osteosarcoma via the AKT/mechanistic target of rapamycin (mTOR)/hypoxia-inducible factor 1-alpha (HIF-1α) pathway (Yan et al., 2020). Emerging evidence also implicates KRT17 in immune microenvironment modulation: in colorectal cancer, KRT17 promotes ubiquitin-proteasome–mediated degradation of YTH N6-methyladenosine RNA binding protein 2 (YTHDF2), thereby alleviating N6-methyladenosine (m⁶A)-dependent repression of C-X-C motif chemokine ligand 10 (CXCL10), enhancing T lymphocyte infiltration, and potentiating response to immunotherapy (Liang et al., 2023). These findings collectively highlight KRT17’s multifaceted and context-dependent roles in tumor progression and tumor–immune crosstalk. 2. Materials and Methods 2.1 Cell Culture All human endometrial cancer cell lines were maintained at 37°C in a humidified 5% CO₂ atmosphere, using culture media supplemented with 10% fetal bovine serum (FBS; Procell, Cat# 164210) and 1% penicillin–streptomycin (Solarbio, Cat# P1400). Specifically, Ishikawa cells were cultured in Dulbecco’s Modified Eagle Medium (Gibco, Cat# C11965500BT), and HEC-1-A cells were cultured in McCoy’s 5A Medium (Gibco, Cat# 16600082). Upon reaching 60%–70% confluency, cells were passaged with 0.25% trypsin-EDTA (Solarbio, Cat# T1300), and all functional assays were performed during the logarithmic growth phase. 2.2 Bioinformatics Analysis This study utilized publicly accessible data from the uterine corpus endometrial carcinoma (UCEC) cohort within The Cancer Genome Atlas (TCGA) database, systematically integrating transcriptomic profiles and comprehensive clinical information—including disease stage, histological grade, lymph node metastasis status, and survival outcomes (Z. Tang et al., 2017). To investigate the clinical significance of KRT17 in endometrial carcinoma, the study first employed one-way analysis of variance (ANOVA) to evaluate the correlation between KRT17 expression levels and key clinical parameters, thereby clarifying its association patterns with critical indicators of tumor progression. Building on this foundation, Kaplan-Meier survival curves were constructed and Log-rank tests were applied to quantitatively analyze the association between KRT17 expression levels and patient survival outcomes, with specific emphasis on evaluating its independent predictive value for overall survival (OS) and disease-specific survival (DSS). To elucidate the functional mechanisms of KRT17, the study incorporated previously published single-cell RNA sequencing (scRNA-seq) datasets (https://ngdc.cncb.ac.cn/gsa-human/browse/; ID: HRA006322) from the research team to systematically characterize the expression patterns of KRT17 in endometrial carcinoma (Ren et al., 2024). Subsequently, based on the results of differential gene expression analysis, gene set enrichment analysis (GSEA) was performed using the Hallmark gene set to explore the key signaling pathways potentially implicated in tumorigenesis and progression associated with KRT17. 2.3 Cell Transfection The human KRT17 gene (Gene ID: HGNC:6427) was retrieved from the GeneCards database. Three distinct short hairpin RNA (shRNA) sequences specifically designed to target KRT17 were synthesized (Supplementary Table 1). Logarithmically growing Ishikawa and HEC-1-A cells were seeded in 6-well plates (2×10⁵ cells/well) and cultured for 24 hours. Upon reaching 50-60% confluence, the cells were subjected to viral transduction using lentiviral particles. To establish stable knockdown pools, puromycin (Cat# BL528A, Biosharp, China) selection was initiated at a concentration of 2 μg/mL at 48 hours after transduction. 2.4 RNA Extraction and cDNA Synthesis Total RNA was extracted from EC cell lines and tissues using TRIzol reagent (Cat# 15596026, Invitrogen, USA). RNA purity and concentration were assessed with a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). cDNA was synthesized from 1 μg of total RNA using the NovoScript® Plus All-in-One 1st Strand cDNA Synthesis SuperMix (with gDNA Purge; Cat# E047, Novoprotein, China). The reverse transcription reaction was performed under the following conditions: 50 °C for 15 min, 85 °C for 10 s, and a final hold at 4 °C. 2.5 Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) qRT-PCR was performed using NovoStart® SYBR qPCR SuperMix Plus (Cat# E096, Novoprotein, China). Each 10 µL reaction contained 5 µL of SYBR Mix, 0.5 µL each of forward and reverse primers, 2 µL of cDNA template, and 2 µL of RNase-free water. Amplification was carried out on a LightCycler® 96 Real-Time PCR System (Roche, Switzerland) under the following cycling conditions: initial denaturation at 95 °C for 20 s, followed by 45 cycles of 60 °C for 30 s and 72 °C for 30 s. GAPDH was used as the endogenous control. Relative gene expression was calculated using the 2^(-ΔΔCt) method. The primer sequences utilized in this experiment are displayed in Supplementary Tables 2-3. 2.6 Western Blot Analysis Cells and tissue specimens were lysed in RIPA buffer (Cat# PC101, EpiZyme, China) containing 1% phenylmethylsulfonyl fluoride (Cat# ST506, Beyotime, China). Protein concentrations were quantified with a BCA protein assay kit (Cat# P1513, Pulilai, China) with bovine serum albumin (BSA) as the standard. Equal amounts of protein were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and subsequently transferred onto polyvinylidene fluoride membranes (Cat# BL712A, Biosharp, China). Following blocking with 5% non-fat milk, membranes were immunoprobed with specific primary antibodies at 4 °C overnight, and subsequently with horseradish peroxidase (HRP)-conjugated secondary antibodies for 1 h at room temperature. Protein bands were visualized using an ultrasensitive chemiluminescence substrate (Cat# P1050, Pulilai, China). Antibody details are as follows: KRT17 (abcam, ab51056, 1:1000), GAPDH (Proteintech, 60004-1-Ig, 1:50000), E-Cadherin (Proteintech, 60335-1-Ig, 1:3000), N-Cadherin (Proteintech, 66219-1-Ig, 1:5000), Vimentin (Proteintech, 60330-1-Ig, 1:5000), anti-rabbit IgG-HRP (1:5000, Proteintech, SA00001-2), anti-mouse IgG-HRP (1:5000, Proteintech, SA00001-21). 2.7 Cell Viability Assay Logarithmically growing cells with normal morphology and free of microbial contamination were trypsinized to generate a single-cell suspension. Cells were seeded into 96-well plates at a density of 1,500 cells per well, with the peripheral wells filled with an equal volume of phosphate-buffered saline (PBS) to minimize evaporation-induced edge effects. After seeding, plates were incubated in a humidified incubator at 37 °C with 5% CO₂ for 24 hours, designated as day 1. Cell proliferation was monitored daily for five consecutive days at a consistent time point. For each measurement, 100 μL of freshly prepared Cell Counting Kit-8 (CCK-8) working solution—prepared by diluting CCK-8 reagent (Cat# SC119, SEVENbio, China) in serum-free medium at a 1:10 ratio—was added to each well. Following a 1.5-hour incubation, absorbance was measured at 450 nm using a multifunctional microplate reader. Absorbance values were recorded daily to construct cell proliferation curves. 2.8 EdU Assay Cell proliferation was evaluated using the EdU Cell Proliferation Detection Kit (Cat# C0078S, Beyotime, China). Cells were seeded into 24-well plates at a density of 5×10⁴ cells per well and cultured for 24 hours. The EdU working solution was then added to each well at a final concentration of 50 μmol/L, followed by incubation for 2 hours at 37°C. After removal of the medium, cells were fixed with 4% paraformaldehyde (Cat# P1110, Solarbio, China) and permeabilized with 0.3% Triton X-100 in phosphate-buffered saline. Nuclei were counterstained with Hoechst 33342. Fluorescence images were captured using an inverted fluorescence microscope (IX73, Olympus, Japan). 2.9 Colony Formation Assay Cells from each group were plated in 6-well plates at a density of 1,500 cells per well in triplicate and cultured for 14 days at 37°C with 5% CO₂. The culture medium was refreshed every three days. After the incubation period, cells were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet solution (Cat# C0121, Beyotime, China). ImageJ software was used to count positive colonies and calculate the colony formation rate. 2.10 Sphere Formation Assay Cells from each group were suspended at a density of 7,000 cells per 25 μL of Matrigel matrix (Cat# 354234, Corning, USA) and seeded into 24-well plates. The plates were incubated at 37 °C to allow Matrigel polymerization, followed by the addition of 750 μL serum-free medium per well. The medium was refreshed on days 3, 5, and 7. Sphere morphology was observed and imaged using an inverted microscope (IX73, Olympus, Japan). After 7 days, tumor spheres with diameters exceeding 75 μm were counted. 2.11 Wound Healing Assay Cells were seeded uniformly into 6-well plates and cultured until they reached approximately 90% confluence. A sterile 200 μL pipette tip was used to generate a straight scratch in the monolayer. Wound images were captured at 0, 24, and 48 hours using an inverted microscope (IX73, Olympus, Japan). 2.12 Transwell Invasion Assay Cell invasion ability was assessed using 24-well Transwell chambers with 8.0 μm pores (Cat# 3422, Corning, USA), pre-coated with Matrigel. Cells from each group were resuspended in serum-free medium at a density of 5×10⁴ cells/100 μL and seeded into the upper chamber. The lower chamber was filled with 800 μL of complete medium containing 10% FBS. The plates were incubated at 37 °C in 5% CO₂ for 24-48 hours. Invaded cells were fixed with 4% paraformaldehyde, stained with 0.1% crystal violet. 2.13 Immunohistochemistry (IHC) Paraffin-embedded tissue sections were dewaxed, rehydrated, and subjected to antigen retrieval using citrate buffer under high-pressure heating. Endogenous peroxidase activity was quenched with 3% H₂O₂, followed by blocking with 5% BSA. Antibodies were applied and incubated. The sections were visualized using DAB substrate (Cat# DA1010, Solarbio, China), counterstained with hematoxylin for 2 minutes, differentiated in acid alcohol, blued in ammonia water, dehydrated, cleared, and mounted with neutral resin. The following antibodies were used: Ki67 (Huabio, HA721115, 1:1000), E-Cadherin (Abclonal, A20798, 1:1600), N-Cadherin (Proteintech, 66219-1-Ig, 1:15000), Vimentin (Proteintech, 60330-1-Ig, 1:8000), and anti-mouse IgG HRP-conjugated secondary antibody (1:5000, Proteintech, SA00001-21). 2.14 In Vivo Xenograft Tumor Assay Four- to six-week-old female BALB/c nude mice were maintained under specific pathogen-free conditions. To establish xenograft models, HEC-1-A and Ishikawa cells stably transduced with sh-KRT17 or sh-NC were harvested and resuspended in phosphate-buffered saline. Each mouse received a subcutaneous injection of 2 × 10⁶ cells in a 100 μL volume into the right flank, with five mice per experimental group. Tumor growth was measured every three days using a digital caliper. Upon reaching the experimental endpoint, xenograft tumors were harvested, photographed, and weighed. For subsequent molecular analyses, one portion of each tumor was snap-frozen in liquid nitrogen and stored at -80°C for protein and RNA extraction. The remaining tumor tissue was fixed in 4% paraformaldehyde for 24 hours, followed by paraffin embedding for IHC. 2.15 Statistical Analysis All quantitative data are expressed as the mean ± standard deviation (mean ± SD). Statistical analyses were performed using GraphPad Prism 9.3.0 software. Comparisons between two groups were conducted using the unpaired Student’s t-test, while multiple group comparisons were analyzed by one-way ANOVA followed by Tukey’s post hoc test. Survival analysis was performed using the Kaplan-Meier method, and differences between survival curves were assessed with the log-rank test. Correlation analysis was carried out using Pearson correlation. A P-value < 0.05 was considered statistically significant. 3. Results 3.1 KRT17 is Highly Expressed in EC and Correlates with Adverse Clinicopathological Features and Poor Prognosis Integrative analysis of transcriptomic data from the TCGA-UCEC cohort revealed a distinct expression profile and clinical relevance of KRT17 in EC. Comparative analysis revealed a marked elevation in KRT17 expression levels in EC tissues relative to normal endometrial specimens. (Figure 1A). Further stratified analysis revealed a significant correlation between high KRT17 expression and the menopausal status (Figure 1B) as well as obesity (Figure 1C) in EC patients. The association of KRT17 expression with hormonal status and obesity is consistent with findings from previous studies (Bendinelli et al., 2025; Leitzmann, Stein, Baurecht, & Freisling, 2025). Across histological subtypes, elevated KRT17 levels were detected in mixed carcinoma, endometrioid carcinoma, and serous carcinoma compared with normal endometrial samples (Figure 1D). Furthermore, KRT17 expression correlated positively with higher histological grade (Figure 1E), advanced FIGO stage (Figure 1F), and greater tumor invasiveness (Figure 1G), indicating its role in promoting aggressive tumor behavior. Survival analyses indicated that patients with high KRT17 expression had significantly shorter OS and DSS (P < 0.05; Figure 1H–I). KRT17 demonstrated favorable diagnostic performance in endometrial cancer, with an area under the curve (AUC) of 0.791 (95% confidence interval [CI]: 0.712–0.870; Figure 1J), supporting its potential utility as an auxiliary diagnostic biomarker. Time-dependent receiver operating characteristic (ROC) analysis for 1-, 3-, and 5-year survival revealed limited prognostic performance of KRT17 when assessed independently (AUCs: 0.557, 0.547, and 0.517, respectively; Figure 1K), suggesting that integration with complementary biomarkers may enhance predictive accuracy for prognostic risk stratification in endometrial cancer. Figure 1 . KRT17 expression and its clinical relevance in EC. (A) KRT17 expression in tumor vs. normal endometrial tissues. (B–G) Correlations between KRT17 expression and clinicopathological parameters: (B) menopausal status (Post, postmenopausal; Peri, perimenopausal; Pre, premenopausal), (C) body mass index (BMI), (D) histological type, (E) histologic grade, (F) FIGO stage, and (G) tumor invasiveness. (H) OS and (I) DSS of EC patients stratified by high/low KRT17 expression. (J) ROC curve illustrating the diagnostic utility of KRT17 in discriminating EC from non-malignant tissues. (K) AUC values for predicting 1-, 3-, and 5-year survival (*P < 0.05, **P < 0.01, ***P < 0.001). 3.2 Single-cell Sequencing Reveals Expression Characteristics and Functional Heterogeneity of KRT17 Previous studies utilizing single-cell sequencing have demonstrated pronounced transcriptional heterogeneity among malignant epithelial cells in endometrial cancer, evidenced by significantly elevated copy number variation (CNV) scores in cancer cells relative to other epithelial cell types and distinct, group-specific clustering patterns of epithelial cells across pathological subtypes (Ren et al., 2024). Building upon this foundation, the present study specifically investigates the heterogeneous expression profile of KRT17 within malignant epithelial cells of endometrial cancer. Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction analysis revealed marked heterogeneity in KRT17 expression, delineating two functionally distinct subpopulations: KRT17-positive (KRT17⁺) and KRT17-negative (KRT17⁻) cells (Figure 2A-B), thereby highlighting functional state diversity within the same epithelial-derived tumor cell population. To delineate the molecular characteristics of KRT17⁺ and KRT17⁻ cell subpopulations, this study performed differential gene expression analysis to systematically compare their transcriptomic profiles. Volcano plot (Figure 2C) revealed that the expression of mucin 4 (MUC4), follistatin-like 1 (FSTL1), insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), and L1 cell adhesion molecule (L1CAM) was significantly upregulated in KRT17⁺ cells. Concurrently, compared with KRT17⁻ cells, the expression of polymeric immunoglobulin receptor (PIGR), progesterone receptor (PGR), and activated leukocyte cell adhesion molecule (ALCAM) was markedly downregulated in KRT17⁺ cells. This distinctive transcriptional signature provides a molecular foundation for elucidating the biological properties of the KRT17⁺ subpopulation. Further functional enrichment analysis revealed distinct molecular functions between the two cell types: KRT17⁺ cells were significantly enriched in pathways closely associated with tumor progression, including “cytokine signaling in immune system,” “vascular endothelial growth factor A (VEGFA)/VEGF receptor (VEGFR) signaling,” “proteasome degradation,” and “actin cytoskeleton organization.” These findings align with the established role of KRT17 in promoting tumor cell proliferation and migration, further confirming that KRT17 enhances malignant behaviors such as migration and invasion (Figure 2D). In contrast, KRT17⁻ cells were enriched in functions related to tissue differentiation, basal metabolism, and cellular homeostasis, such as “peptide chain elongation,” “respiratory chain complex I,” and “mammary gland epithelium development,” suggesting their potential involvement in regulating metabolic reprogramming within the tumor microenvironment (Figure 2E). 3.3 KRT17⁺ Cells Exhibit Pro-Tumorigenic Signaling and EMT Enrichment in EC Further GSEA demonstrated that KRT17⁺ cells exhibited significantly higher activity in multiple pro-tumorigenic pathways, with marked enrichment in signaling pathways such as EMT and phosphoinositide 3-kinase (PI3K)/AKT, as well as inflammation-related pathways. In contrast, KRT17⁻ cells were predominantly associated with core metabolic processes, particularly glycolysis and fatty acid oxidation (Figure 3A). Quantitative analysis of key phenotypic pathway activities revealed that KRT17-positive cells possessed significantly higher EMT enrichment scores (Figure 3B), suggesting that EMT may be a critical mechanism by which KRT17 drives the malignant progression of endometrial cancer. Collectively, single-cell transcriptomic analysis systematically elucidates the significant heterogeneity between KRT17-positive and KRT17-negative cell subpopulations in endometrial cancer regarding cell clustering, gene expression, functional enrichment, and pathway activity. 3.4 KRT17 Promotes Endometrial Cancer Cell Proliferation In Vitro Stable KRT17 knockdown models were established in HEC-1-A and Ishikawa cells using shRNAs (sh-KRT17-1, sh-KRT17-2, sh-KRT17-3), with knockdown efficiency confirmed at both mRNA and protein levels (Figure 4A-B). Consistent with the CCK-8 and EdU assay results, genetic ablation of KRT17 led to a pronounced inhibition of cellular viability and proliferative capacity in both tested cell lines (Figure 4C-D). Furthermore, colony and tumor sphere formation assays additionally confirmed that KRT17 knockdown substantially compromised clonogenic potential. (Figure 4E-F), indicating a critical role for KRT17 in sustaining the clonogenic proliferation of tumor cells. Collectively, these results demonstrate that KRT17 enhances the ability of cells to proliferate. 3.5 KRT17 Facilitates EC Cell Migration and Invasion via EMT Regulation To elucidate the functional role of KRT17 in EC cell motility and underlying mechanisms, we performed a series of functional assays. Genetic depletion of KRT17 markedly attenuated the migratory (Figure 5A) and invasive (Figure 5B) capacities of HEC-1-A and Ishikawa cells. At the molecular level, KRT17 silencing triggered a transcriptional program consistent with EMT, characterized by upregulated E-cadherin expression and concurrent downregulation of N-cadherin, Vimentin, and Snail1 mRNA (Figure 5C). Western blot analysis confirmed the cadherin switch and the reduction in Vimentin expression (Figure 5D). Thus, KRT17 enhances the metastatic potential of EC cells by activating EMT. 3.6 In Vivo Validation of KRT17-Driven Malignancy via EMT Activation To definitively establish the oncogenic function of KRT17, we employed subcutaneous xenograft models. KRT17 knockdown potently inhibited tumor growth and decreased final tumor mass in both HEC-1-A and Ishikawa models (Figure 6A-B). Molecular analysis of the xenografts revealed that KRT17 silencing induced an EMT-reversal signature, characterized by increased E-cadherin and decreased N-cadherin and Vimentin at the mRNA level (Figure 6C). These protein-level observations were validated through Western blot and immunohistochemical analyses, which consistently demonstrated increased E-cadherin expression along with decreased levels of N-cadherin, Vimentin, and Ki67 following KRT17 knockdown (Figure 6D-E). Collectively, these in vivo findings substantiate that KRT17 drives endometrial carcinogenesis and EMT, supporting its potential value as a therapeutic target in preclinical models. 4. Discussion To date, only one study has preliminarily suggested, through a pan-cancer analysis, that KRT17 may serve as a negative prognostic biomarker in high-grade endometrial cancer (Bai et al., 2019). However, that study did not explore the molecular function or underlying mechanisms of KRT17, nor did it analyze its relationship with clinicopathological characteristics. Through integrated bioinformatics coupled with experimental validation both in vitro and in vivo, this study comprehensively delineates the expression patterns, functional roles, and molecular mechanisms of KRT17 in EC, offering novel theoretical insights and potential therapeutic targets for EC diagnosis and treatment. First, we established the clinical relevance of KRT17 in EC. Analysis of the TCGA-UCEC dataset revealed significant upregulation of KRT17 in endometrial carcinoma tissues compared with normal endometrial tissues. Furthermore, KRT17 expression levels correlated significantly with postmenopausal status, obesity, higher histologic grade, advanced FIGO stage, and deeper myometrial invasion. Additionally, in some paired samples, KRT17 expression in tumor tissues was lower than in normal tissues, which may be attributed to biological heterogeneity caused by different molecular subtypes of the tumor, or spatial heterogeneity due to genetic mutations or epigenetic modifications in different tumor regions. KRT17 exerts context-dependent functions across breast cancer molecular subtypes: elevated KRT17 expression correlates with adverse clinical outcomes in triple-negative breast cancer, whereas it serves as a favorable prognostic indicator in patients with HER2-enriched breast cancer (Merkin et al., 2017; S. Tang et al., 2022). Further molecular subtyping and stratified analysis are required to determine whether KRT17 expression correlates with specific subtypes. Survival analysis confirmed that high KRT17 expression serves as an independent risk factor for reduced OS and DSS. These findings align with established literature characterizing KRT17 as an indicator of unfavorable prognosis in multiple malignancies, such as pancreatic carcinoma (Roa-Peña et al., 2021) and non-small cell lung cancer (Babu et al., 2024). Second, this study delineates the mechanism by which KRT17 drives EC malignancy, primarily through activating the EMT pathway. In vitro, KRT17 knockdown suppressed EC cell (HEC-1-A and Ishikawa) proliferation, migration, and invasion, which was associated with an increase in E-cadherin and decreases in N-cadherin and Vimentin. These findings were corroborated in vivo, where KRT17 depletion attenuated xenograft tumor growth and reversed EMT. This finding is consistent with prior reports in gastric cancer (H. Hu et al., 2018), suggesting that the mechanism by which KRT17 regulates EMT may be evolutionarily conserved across multiple epithelial-derived malignancies. Single-cell functional enrichment analysis further confirmed significantly elevated EMT pathway activity in KRT17⁺ cells relative to KRT17⁻ cells, indicating that KRT17 may serve as an upstream regulator driving these pro-invasive phenotypes. Single-cell transcriptomic analysis revealed that KRT17⁺ cells exhibited not only significant enrichment in the EMT pathway but also activation of cytokine signaling and VEGFA/VEGFR signaling pathways, suggesting a pivotal role for KRT17 in tumor microenvironment remodeling. Our study identified a co-expression signature of MUC4, IGF2BP2, and FSTL1 in KRT17⁺ cells, forming a potential regulatory network. As a membrane-bound mucin, MUC4 promotes tumor migration and invasion by modulating cell adhesion and signal transduction, with its elevated expression associated with poor prognosis in endometrial cancer (Dreyer, VanderVorst, Free, Rowson-Hodel, & Carraway, 2021; C. M. Hu et al., 2023). IGF2BP2, an RNA-binding protein, drives malignant progression across multiple malignancies—including thyroid carcinoma (Chen et al., 2026), colorectal cancer (Niu et al., 2026), lung adenocarcinoma (Ling et al., 2025), and pancreatic ductal adenocarcinoma (Ge et al., 2025)—by recognizing m⁶A-modified target mRNAs to regulate their stability and translational efficiency. Notably, recent evidence indicates that IGF2BP2 facilitates efficient protein synthesis through liquid-liquid phase separation-mediated formation of ribonucleoprotein granules (Xiong et al., 2025). Functionally context-dependent, the secreted glycoprotein FSTL1 suppresses M2 macrophage recruitment to exert protective effects in triple-negative breast cancer (Yang, Lu, Jia, & Gao, 2023), whereas in other tumor contexts it promotes progression by inducing EMT (S. Yu et al., 2024), enhancing stemness properties (Zhou et al., 2024), and remodeling the immune microenvironment (H. Zhang et al., 2025). In glioblastoma, FSTL1 sustains tumor stem cell self-renewal and drives M2 macrophage polarization via autocrine and paracrine signaling, establishing a pro-tumorigenic feedback loop (Zhou et al., 2024). Collectively, these findings suggest that in endometrial cancer, KRT17 may orchestrate malignant progression by coordinately regulating effector molecules such as FSTL1 to integrate EMT activation with immune microenvironment remodeling. KRT17 likely drives the malignant progression of EC by orchestrating pivotal oncogenic processes, including EMT. Direct evidence supporting this role comes from our observation that KRT17⁺ cells exhibit a marked increase in the activity of EMT pathway compared to their KRT17⁻ counterparts, positioning KRT17 as a potential upstream master regulator of these pro-invasive phenotypes. Mechanistically, EMT is known to be finely regulated by key signaling pathways such as Janus Kinase 2/STAT3, AKT, and MAPK, which act in concert to enhance tumor cell invasiveness and immune evasion (Shen et al., 2024; Xiao, Zhang, Peng, Wei, & Ma, 2021; Y. Yu et al., 2023). We thus speculate that KRT17 may promote EMT through activation of, or synergy with, one or more of these signaling axes, although the precise mechanisms require further investigation. In summary, our work identifies KRT17 as a key driver of endometrial carcinoma progression that promotes tumor invasion by activating the EMT program. While this study systematically demonstrates that KRT17 promotes the malignant progression of EC through EMT activation, several limitations should be acknowledged. First, the upstream signaling mechanisms by which KRT17 regulates EMT remain incompletely understood. Although KRT17 knockdown resulted in increased E-cadherin and decreased N-cadherin and vimentin expression, the precise molecular pathways through which KRT17 modulates key signaling effectors require further elucidation. Second, the direct regulatory relationship between KRT17 and signature genes of KRT17 + cells—including MUC4, IGF2BP2, and FSTL1, as identified by single-cell analysis—has not been functionally validated. Future studies should employ techniques such as co-knockdown assays, chro matin immunoprecipitation (ChIP), and RNA immunoprecipitation (RIP) to delineate the regulatory network linking KRT17 to these downstream effectors. Such investigations would provide a mechanistic foundation for developing targeted therapies against KRT17 and its associated regulatory network. 5. Conclusion In conclusion, this study systematically elucidated the critical role of KRT17 in the pathogenesis and progression of endometrial cancer. For the first time, it was demonstrated that KRT17 drives malignant tumor progression through activation of the EMT program and is significantly associated with reduced overall survival in patients with endometrial cancer. These findings offer a strong rationale for developing KRT17-targeted therapies, such as siRNA-based nanomedicines or small-molecule inhibitors. Our work thus provides a solid experimental foundation for incorporating KRT17 targeting into the precision medicine arsenal for endometrial carcinoma. Abbreviations EC Endometrial cancer KRT17 Keratin 17 qRT-PCR Quantitative reverse transcription polymerase chain reaction EMT Epithelial-mesenchymal transition OS Overall survival DSS Disease-specific survival MSI-H Microsatellite instability-high dMMR Mismatch repair-deficient NSMP No specific molecular profile AKT Protein kinase B mTOR Mechanistic target of rapamycin HIF-1α Hypoxia-inducible factor 1α GLUT1 Glucose transporter 1 MCL1 Myeloid cell leukemia 1 VEGF Vascular endothelial growth factor TME Tumor microenvironment UCEC Uterine corpus endometrial carcinoma TCGA The Cancer Genome Atlas ANOVA One-way analysis of variance GSEA Gene Set Enrichment Analysis BSA Bovine serum albumin HRP Horseradish peroxidase FBS Fetal bovine serum IHC Immunohistochemistry TGF-β Transforming growth factor-β MUC4 Mucin 4 IGF2BP2 Insulin-like growth factor 2 mRNA binding protein 2 FSTL1 Follistatin-like 1 STAT3 Signal transducer and activator of transcription 3 Declarations Ethics approval and consent to participate All animal experiments were performed in accordance with the Guidelines for the Welfare and Use of Experimental Animals of China and were approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (Approval No. 2025-KY-1306-001). Availability of data and materials Not applicable. Declaration of interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This work was supported by the Henan Academy of Medical Sciences and the Henan Provincial Health Commission [Grant No. HNCRD202429]; and the Henan Provincial Health Commission [Grant No. SBGJ202302075]. Authors' contributions Xiaole Song, Xuerou Chen: methodology, investigation, data curation, formal analysis, writing – original draft. Qianwen Liu, Yajuan Ma, Xiaoran Zhang: investigation, visualization, writing – original draft. Fang Ren: conceptualization, supervision, formal analysis, funding acquisition, resources, visualization, writing – review and editing. Acknowledgements We gratefully acknowledge Dr. Lin Shitong from Huazhong University of Science and Technology for his valuable contributions to our endometrial cancer cell line. Author information Department of Gynecologic Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China. Xiaole Song ( [email protected] ); Xuerou Chen ( [email protected] ); Qianwen Liu ( [email protected] ); Yajuan Ma ( [email protected] ); Xiaoran Zhang ( [email protected] ); Fang Ren ( [email protected] ) References Babu, S., Horowitz, M., Delgado-Coka, L. A., Roa-Peña, L., Akalin, A., Escobar-Hoyos, L. F., et al. (2024). Keratin 17 and A2ML1 are negative prognostic biomarkers in non-small cell lung cancer. Pathol Res Pract, 263 , 155643. doi:10.1016/j.prp.2024.155643 Bai, J. D. K., Babu, S., Roa-Peña, L., Hou, W., Akalin, A., Escobar-Hoyos, L. F., et al. (2019). Keratin 17 is a negative prognostic biomarker in high-grade endometrial carcinomas. 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BMC Urol, 25 (1), 77. doi:10.1186/s12894-025-01760-4 Zhou, F., Tao, J., Gou, H., Liu, S., Yu, D., Zhang, J., et al. (2024). FSTL1 sustains glioma stem cell stemness and promotes immunosuppressive macrophage polarization in glioblastoma. Cancer Lett, 611 , 217400. doi:10.1016/j.canlet.2024.217400 Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial2.pdf SupplementaryMaterial1.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 18 May, 2026 Reviewers invited by journal 27 Apr, 2026 Editor assigned by journal 12 Apr, 2026 Submission checks completed at journal 11 Apr, 2026 First submitted to journal 10 Apr, 2026 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-9264510","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":630196299,"identity":"9eaaa11f-a4f0-4671-90a8-53c0a85fc207","order_by":0,"name":"Xiaole Song","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xiaole","middleName":"","lastName":"Song","suffix":""},{"id":630196302,"identity":"c2f4aafd-7a72-4b9e-bbc0-13c9b5e049ab","order_by":1,"name":"Xuerou Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xuerou","middleName":"","lastName":"Chen","suffix":""},{"id":630196306,"identity":"3040de3a-ba1b-4b27-86e8-ee298720ced1","order_by":2,"name":"Qianwen Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Qianwen","middleName":"","lastName":"Liu","suffix":""},{"id":630196308,"identity":"55994347-80a7-4105-a60b-2fc58a124d4f","order_by":3,"name":"Yajuan Ma","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yajuan","middleName":"","lastName":"Ma","suffix":""},{"id":630196309,"identity":"5e19f333-8486-4dc1-825a-19381c666bc7","order_by":4,"name":"Xiaoran Zhang","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoran","middleName":"","lastName":"Zhang","suffix":""},{"id":630196310,"identity":"ce69927b-c713-4833-87e2-046a36298cfb","order_by":5,"name":"Fang Ren","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYJCCD0Asx94AYhpYEKWDcQaQMOY5ANYiQbyWxB6wFgYitJi39x5s+LmjNr2Hvcd0w48CCQb+9u4EvFpkzpxLbOw9czy3h+dY2s0eoMMkzpzdgFeLhESO+QPetmO5+yWSj93gAWoxkMgloEX+jWHj37Zj6TwSiW03/xClRYLHsJm3rSaBB2jLbeJs4ckxbJZtO2AI8sttGQMJHsJ+YT9j2Pi2rU6eh73H7OabPzZy/O29+LVAwWE4i4cY5SBQR6zCUTAKRsEoGIkAADtRRbpibXHkAAAAAElFTkSuQmCC","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"Fang","middleName":"","lastName":"Ren","suffix":""}],"badges":[],"createdAt":"2026-03-30 08:54:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9264510/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9264510/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108630527,"identity":"c65e380c-36f1-4bc7-8b81-fd6e70c12aed","added_by":"auto","created_at":"2026-05-06 16:37:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":594316,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKRT17 expression and its clinical relevance in EC. (A)\u003c/strong\u003e KRT17 expression in tumor vs. normal endometrial tissues.\u003cstrong\u003e (B–G)\u003c/strong\u003e Correlations between KRT17 expression and clinicopathological parameters:\u003cstrong\u003e (B)\u003c/strong\u003e menopausal status (Post, postmenopausal; Peri, perimenopausal; Pre, premenopausal), \u003cstrong\u003e(C) \u003c/strong\u003ebody mass index (BMI), \u003cstrong\u003e(D)\u003c/strong\u003e histological type, \u003cstrong\u003e(E) \u003c/strong\u003ehistologic grade, \u003cstrong\u003e(F) \u003c/strong\u003eFIGO stage, and \u003cstrong\u003e(G)\u003c/strong\u003e tumor invasiveness. \u003cstrong\u003e(H) \u003c/strong\u003eOS and \u003cstrong\u003e(I) \u003c/strong\u003eDSS of EC patients stratified by high/low KRT17 expression. \u003cstrong\u003e(J) \u003c/strong\u003eROC curve illustrating the diagnostic utility of KRT17 in discriminating EC from non-malignant tissues. \u003cstrong\u003e(K) \u003c/strong\u003eAUC values for predicting 1-, 3-, and 5-year survival (*P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/0b0781e53ba2cd58b40395c0.png"},{"id":108806332,"identity":"7177fe18-111a-45db-a647-b896fc20ac18","added_by":"auto","created_at":"2026-05-08 15:28:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":505693,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSingle-cell sequencing reveals KRT17 heterogeneity in EC. (A-B) \u003c/strong\u003eUMAP dimensionality reduction analysis revealed significant heterogeneity in KRT17 expression, identifying two functionally distinct subpopulations: KRT17⁺ and KRT17⁻ cells. \u003cstrong\u003e(C)\u003c/strong\u003e Volcano plot of differentially expressed genes between KRT17⁺ (right) and KRT17⁻ (left) cells. \u003cstrong\u003e(D-E) \u003c/strong\u003eFunctional enrichment analysis of genes upregulated in KRT17⁺\u003cstrong\u003e (D) \u003c/strong\u003eand KRT17⁻ \u003cstrong\u003e(E) \u003c/strong\u003ecells.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/47953bad98d4b6ebaeae5477.png"},{"id":108630523,"identity":"1e4dc5cd-20c3-4cef-9289-459efe4cc781","added_by":"auto","created_at":"2026-05-06 16:37:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":427017,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKRT17 Drives EMT and Pro-Tumorigenic Signaling. (A-B) \u003c/strong\u003eGSEA confirms significant enrichment of pro-tumorigenic signaling and epithelial-mesenchymal transition (EMT) pathways in KRT17-positive cells in endometrial cancer.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/6d09a019b1a1f348194e0858.png"},{"id":108805012,"identity":"93452d3f-5980-45bc-8b3d-0699153a1113","added_by":"auto","created_at":"2026-05-08 15:24:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":590015,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKRT17 promotes proliferation in EC cells in vitro.\u003c/strong\u003e \u003cstrong\u003e(A-B) \u003c/strong\u003eEfficiency of KRT17 knockdown in stably transduced HEC-1-A and Ishikawa cells. \u003cstrong\u003e(C-D)\u003c/strong\u003e CCK-8 \u003cstrong\u003e(C)\u003c/strong\u003e and EdU assays \u003cstrong\u003e(D)\u003c/strong\u003e measuring cell viability and proliferation after KRT17 knockdown. \u003cstrong\u003e(E-F) \u003c/strong\u003eColony formation \u003cstrong\u003e(E)\u003c/strong\u003e and tumor sphere formation \u003cstrong\u003e(F) \u003c/strong\u003eassays evaluating the clonogenic ability of cells upon KRT17 depletion. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001,****P \u0026lt; 0.001; ns, not significant.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/2a664a70f9721dda018c2eb5.png"},{"id":108630525,"identity":"10b93174-509a-460b-9e59-1369794d0235","added_by":"auto","created_at":"2026-05-06 16:37:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":584707,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKRT17 knockdown inhibits migration, invasion, and EMT in EC cells. (A-B) \u003c/strong\u003eKRT17 depletion significantly attenuated the migratory \u003cstrong\u003e(A) \u003c/strong\u003eand invasive\u003cstrong\u003e (B)\u003c/strong\u003eabilities of HEC-1-A and Ishikawa cells. \u003cstrong\u003e(C-D)\u003c/strong\u003e The effect of KRT17 knockdown on EMT was evaluated by measuring the expression of EMT markers at the mRNA \u003cstrong\u003e(C) \u003c/strong\u003eand protein \u003cstrong\u003e(D)\u003c/strong\u003e levels. Data are mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001,****P \u0026lt; 0.001; ns, not significant.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/f117f1038313f6cb60181482.png"},{"id":108630526,"identity":"a9273b0d-9aee-4a6b-919f-e75c97565d3a","added_by":"auto","created_at":"2026-05-06 16:37:10","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":550048,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIn vivo suppression of tumor growth and EMT by KRT17 knockdown.\u003c/strong\u003e \u003cstrong\u003e(A-B)\u003c/strong\u003e Potent suppression of tumor growth \u003cstrong\u003e(A) \u003c/strong\u003eand reduction in final tumor weight \u003cstrong\u003e(B)\u003c/strong\u003e in xenografts derived from sh-KRT17-expressing HEC-1-A and Ishikawa cells, compared to sh-NC controls. \u003cstrong\u003e(C-E) \u003c/strong\u003eKRT17 knockdown reversed EMT in xenograft tissues, as shown by upregulation of E-cadherin and downregulation of N-cadherin and Vimentin at the mRNA \u003cstrong\u003e(C) \u003c/strong\u003eand protein \u003cstrong\u003e(E) \u003c/strong\u003elevels, and confirmed by IHC staining \u003cstrong\u003e(D)\u003c/strong\u003e. Proliferation marker Ki67 was also reduced \u003cstrong\u003e(D)\u003c/strong\u003e. Data are mean ± SD (n = 5 mice/group). *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001,****P \u0026lt; 0.001, ns,not significant.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/1ee79a74dd759d8bc7d767ba.png"},{"id":108810033,"identity":"cc1d7daa-d80e-4d4a-8237-d7f3459f7774","added_by":"auto","created_at":"2026-05-08 15:57:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3574276,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/a6ca830e-f8c1-4ffd-8c51-e331c2600e60.pdf"},{"id":108630520,"identity":"f0f3b3bb-ff54-4197-87d1-9d4393e07876","added_by":"auto","created_at":"2026-05-06 16:37:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":5595102,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/a7c254fb3d83fd7099c0834c.pdf"},{"id":108630521,"identity":"9f5e84e9-f275-40c4-8fdf-75b52bc522f7","added_by":"auto","created_at":"2026-05-06 16:37:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20090,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9264510/v1/c490d5528f5cc477e41c0335.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Keratin 17 Drives Endometrial Cancer Aggressiveness via Epithelial-Mesenchymal Transition: A Single-Cell Transcriptomic and Integrative Bioinformatics Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEndometrial cancer (EC) represents one of the most prevalent malignancies of the female reproductive system globally, with a continuously rising incidence. In 2020 alone, EC was responsible for over 417,000 new cases and approximately 97,000 deaths worldwide. Within China, EC constituted 3.9% of all new cancer diagnoses in women, with a concerning trend toward earlier onset (Henley et al., 2020; Morice, Leary, Creutzberg, Abu-Rustum, \u0026amp; Darai, 2016; Sung et al., 2021). While patients with early-stage disease typically achieve favorable outcomes through surgery and adjuvant therapy, the prognosis for those with advanced-stage (FIGO 2009 Stage III-IV) EC remains dismal, with a median overall survival (OS) of less than three years (Kalampokas et al., 2022). The advent of molecular classification has revolutionized the understanding of EC, categorizing it into four distinct subtypes based on genomic and histopathological features: POLE-mutated, TP53-abnormal, microsatellite instability-high (MSI-H)/mismatch repair-deficient (dMMR), and no specific molecular profile (NSMP). This molecular classification framework provides a critical foundation for precision medicine in EC; however, significant disparities in treatment response and clinical outcomes persist among the different subtypes (Kandoth et al., 2013). For instance, patients with MSI-H/dMMR tumors exhibit favorable responses to immune checkpoint inhibitors due to their high tumor mutational burden (O\u0026apos;Malley et al., 2022; Talhouk et al., 2017). However, targeted therapy options remain extremely limited for the NSMP subtype, which accounts for 40%\u0026ndash;50% of cases. Therefore, there is an urgent need to identify novel biomarkers and therapeutic targets that are specific to distinct molecular subtypes (Karpel, Slomovitz, Coleman, \u0026amp; Pothuri, 2023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKeratin 17 (KRT17) is a type I intermediate filament protein that polymerizes into non-covalent filament networks, contributing to structural integrity and repair processes in epithelial tissues (Baraks et al., 2022). Pan-cancer analysis revealed significant upregulation of KRT17 in endometrial carcinoma tissues compared with normal endometrial tissues (Bai et al., 2019), suggesting its potential oncogenic role in endometrial carcinoma pathogenesis. Accumulating evidence indicates that KRT17 is aberrantly overexpressed in various malignancies, including head and neck cancer, non-small cell lung cancer, and gastric carcinoma (H. Hu et al., 2018; W. Wang et al., 2022; Z. Wang et al., 2019). In gynecological oncology, KRT17 is significantly upregulated in cervical cancer. Its elevated expression correlates strongly with histological poor differentiation, lymph node metastasis, and human papillomavirus type 16 (HPV16) infection, and serves as an independent predictor of poor prognosis beyond conventional serum biomarkers. Mechanistically, KRT17 attenuates the efficacy of platinum-based chemotherapy by modulating the Hippo signaling pathway and microtubule-mediated cell migration, thereby indirectly inducing chemoresistance and promoting lymph node metastasis in vivo (Escobar-Hoyos et al., 2014). Given that endometrial carcinoma is also an epithelial-derived malignancy and KRT17 has been established as an oncogenic driver in cervical and other gynecological cancers, its functional role in endometrial carcinoma warrants dedicated investigation. Notably, the clinical implications of KRT17 are highly context-dependent: in human epidermal growth factor receptor 2 (HER2)-positive breast cancer, high KRT17 expression associates with favorable survival outcomes (S. Tang et al., 2022), underscoring that its functional duality is shaped by tumor type and microenvironmental cues. At the molecular level, KRT17 drives tumorigenesis through multiple signaling axes. KRT17 upregulation activates protein kinase B (AKT) signaling, inducing EMT\u0026mdash;a process marked by loss of epithelial polarity and cell-cell junctions coupled with acquisition of mesenchymal traits\u0026mdash;thereby enhancing tumor cell migration and invasion. This mechanism underpins KRT17-mediated progression in esophageal and bladder cancers (Liu et al., 2020; Wu et al., 2017; P. Zhang et al., 2025). Additionally, KRT17 regulates metabolic reprogramming in osteosarcoma via the AKT/mechanistic target of rapamycin (mTOR)/hypoxia-inducible factor 1-alpha (HIF-1\u0026alpha;) pathway (Yan et al., 2020). Emerging evidence also implicates KRT17 in immune microenvironment modulation: in colorectal cancer, KRT17 promotes ubiquitin-proteasome\u0026ndash;mediated degradation of YTH N6-methyladenosine RNA binding protein 2 (YTHDF2), thereby alleviating N6-methyladenosine (m⁶A)-dependent repression of C-X-C motif chemokine ligand 10 (CXCL10), enhancing T lymphocyte infiltration, and potentiating response to immunotherapy (Liang et al., 2023). These findings collectively highlight KRT17\u0026rsquo;s multifaceted and context-dependent roles in tumor progression and tumor\u0026ndash;immune crosstalk.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Cell Culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll human endometrial cancer cell lines were maintained at 37\u0026deg;C in a humidified 5% CO₂ atmosphere, using culture media supplemented with 10% fetal bovine serum (FBS; Procell, Cat# 164210) and 1% penicillin\u0026ndash;streptomycin (Solarbio, Cat# P1400). Specifically, Ishikawa cells were cultured in Dulbecco\u0026rsquo;s Modified Eagle Medium (Gibco, Cat# C11965500BT), and HEC-1-A cells were cultured in McCoy\u0026rsquo;s 5A Medium (Gibco, Cat# 16600082). Upon reaching 60%\u0026ndash;70% confluency, cells were passaged with 0.25% trypsin-EDTA (Solarbio, Cat# T1300), and all functional assays were performed during the logarithmic growth phase.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Bioinformatics Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study utilized publicly accessible data from the uterine corpus endometrial carcinoma (UCEC) cohort within The Cancer Genome Atlas (TCGA) database, systematically integrating transcriptomic profiles and comprehensive clinical information\u0026mdash;including disease stage, histological grade, lymph node metastasis status, and survival outcomes (Z. Tang et al., 2017). To investigate the clinical significance of KRT17 in endometrial carcinoma, the study first employed one-way analysis of variance (ANOVA) to evaluate the correlation between KRT17 expression levels and key clinical parameters, thereby clarifying its association patterns with critical indicators of tumor progression. Building on this foundation, Kaplan-Meier survival curves were constructed and Log-rank tests were applied to quantitatively analyze the association between KRT17 expression levels and patient survival outcomes, with specific emphasis on evaluating its independent predictive value for overall survival (OS) and disease-specific survival (DSS). To elucidate the functional mechanisms of KRT17, the study incorporated previously published single-cell RNA sequencing (scRNA-seq) datasets (https://ngdc.cncb.ac.cn/gsa-human/browse/; ID: HRA006322) from the research team to systematically characterize the expression patterns of KRT17 in endometrial carcinoma (Ren et al., 2024). Subsequently, based on the results of differential gene expression analysis, gene set enrichment analysis (GSEA) was performed using the Hallmark gene set to explore the key signaling pathways potentially implicated in tumorigenesis and progression associated with KRT17.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Cell Transfection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe human KRT17 gene (Gene ID: HGNC:6427) was retrieved from the GeneCards database. Three distinct short hairpin RNA (shRNA) sequences specifically designed to target KRT17 were synthesized (Supplementary Table 1). Logarithmically growing Ishikawa and HEC-1-A cells were seeded in 6-well plates (2\u0026times;10⁵ cells/well) and cultured for 24 hours. Upon reaching 50-60% confluence, the cells were subjected to viral transduction using lentiviral particles. To establish stable knockdown pools, puromycin (Cat# BL528A, Biosharp, China) selection was initiated at a concentration of 2 \u0026mu;g/mL at 48 hours after transduction. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 RNA Extraction and cDNA Synthesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from EC cell lines and tissues using TRIzol reagent (Cat# 15596026, Invitrogen, USA). RNA purity and concentration were assessed with a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). cDNA was synthesized from 1 \u0026mu;g of total RNA using the NovoScript\u0026reg; Plus All-in-One 1st Strand cDNA Synthesis SuperMix (with gDNA Purge; Cat# E047, Novoprotein, China). The reverse transcription reaction was performed under the following conditions: 50 \u0026deg;C for 15 min, 85 \u0026deg;C for 10 s, and a final hold at 4 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eqRT-PCR was performed using NovoStart\u0026reg; SYBR qPCR SuperMix Plus (Cat# E096, Novoprotein, China). Each 10 \u0026micro;L reaction contained 5 \u0026micro;L of SYBR Mix, 0.5 \u0026micro;L each of forward and reverse primers, 2 \u0026micro;L of cDNA template, and 2 \u0026micro;L of RNase-free water. Amplification was carried out on a LightCycler\u0026reg; 96 Real-Time PCR System (Roche, Switzerland) under the following cycling conditions: initial denaturation at 95 \u0026deg;C for 20 s, followed by 45 cycles of 60 \u0026deg;C for 30 s and 72 \u0026deg;C for 30 s. GAPDH was used as the endogenous control. Relative gene expression was calculated using the 2^(-\u0026Delta;\u0026Delta;Ct) method. The primer sequences utilized in this experiment are displayed in Supplementary Tables 2-3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Western Blot Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells and tissue specimens were lysed in RIPA buffer (Cat# PC101, EpiZyme, China) containing 1% phenylmethylsulfonyl fluoride (Cat# ST506, Beyotime, China). Protein concentrations were quantified with a BCA protein assay kit (Cat# P1513, Pulilai, China) with bovine serum albumin (BSA) as the standard. Equal amounts of protein were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and subsequently transferred onto polyvinylidene fluoride membranes (Cat# BL712A, Biosharp, China). Following blocking with 5% non-fat milk, membranes were immunoprobed with specific primary antibodies at 4 \u0026deg;C overnight, and subsequently with horseradish peroxidase (HRP)-conjugated secondary antibodies for 1 h at room temperature. Protein bands were visualized using an ultrasensitive chemiluminescence substrate (Cat# P1050, Pulilai, China). Antibody details are as follows: KRT17 (abcam, ab51056, 1:1000), GAPDH (Proteintech, 60004-1-Ig, 1:50000), E-Cadherin (Proteintech, 60335-1-Ig, 1:3000), N-Cadherin (Proteintech, 66219-1-Ig, 1:5000), Vimentin (Proteintech, 60330-1-Ig, 1:5000), anti-rabbit IgG-HRP (1:5000, Proteintech, SA00001-2), anti-mouse IgG-HRP (1:5000, Proteintech, SA00001-21).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Cell Viability Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLogarithmically growing cells with normal morphology and free of microbial contamination were trypsinized to generate a single-cell suspension. Cells were seeded into 96-well plates at a density of 1,500 cells per well, with the peripheral wells filled with an equal volume of phosphate-buffered saline (PBS) to minimize evaporation-induced edge effects. After seeding, plates were incubated in a humidified incubator at 37 \u0026deg;C with 5% CO₂ for 24 hours, designated as day 1. Cell proliferation was monitored daily for five consecutive days at a consistent time point. For each measurement, 100 \u0026mu;L of freshly prepared Cell Counting Kit-8 (CCK-8) working solution\u0026mdash;prepared by diluting CCK-8 reagent (Cat# SC119, SEVENbio, China) in serum-free medium at a 1:10 ratio\u0026mdash;was added to each well. Following a 1.5-hour incubation, absorbance was measured at 450 nm using a multifunctional microplate reader. Absorbance values were recorded daily to construct cell proliferation curves.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 EdU Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell proliferation was evaluated using the EdU Cell Proliferation Detection Kit (Cat# C0078S, Beyotime, China). Cells were seeded into 24-well plates at a density of 5\u0026times;10⁴ cells per well and cultured for 24 hours. The EdU working solution was then added to each well at a final concentration of 50 \u0026mu;mol/L, followed by incubation for 2 hours at 37\u0026deg;C. After removal of the medium, cells were fixed with 4% paraformaldehyde (Cat# P1110, Solarbio, China) and permeabilized with 0.3% Triton X-100 in phosphate-buffered saline. Nuclei were counterstained with Hoechst 33342. Fluorescence images were captured using an inverted fluorescence microscope (IX73, Olympus, Japan).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.9 Colony Formation Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells from each group were plated in 6-well plates at a density of 1,500 cells per well in triplicate and cultured for 14 days at 37\u0026deg;C with 5% CO₂. The culture medium was refreshed every three days. After the incubation period, cells were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet solution (Cat# C0121, Beyotime, China). ImageJ software was used to count positive colonies and calculate the colony formation rate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.10 Sphere Formation Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells from each group were suspended at a density of 7,000 cells per 25 \u0026mu;L of Matrigel matrix (Cat# 354234, Corning, USA) and seeded into 24-well plates. The plates were incubated at 37 \u0026deg;C to allow Matrigel polymerization, followed by the addition of 750 \u0026mu;L serum-free medium per well. The medium was refreshed on days 3, 5, and 7. Sphere morphology was observed and imaged using an inverted microscope (IX73, Olympus, Japan). After 7 days, tumor spheres with diameters exceeding 75 \u0026mu;m were counted. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.11 Wound Healing Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were seeded uniformly into 6-well plates and cultured until they reached approximately 90% confluence. A sterile 200 \u0026mu;L pipette tip was used to generate a straight scratch in the monolayer. Wound images were captured at 0, 24, and 48 hours using an inverted microscope (IX73, Olympus, Japan). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.12 Transwell Invasion Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell invasion ability was assessed using 24-well Transwell chambers with 8.0 \u0026mu;m pores (Cat# 3422, Corning, USA), pre-coated with Matrigel. Cells from each group were resuspended in serum-free medium at a density of 5\u0026times;10⁴ cells/100 \u0026mu;L and seeded into the upper chamber. The lower chamber was filled with 800 \u0026mu;L of complete medium containing 10% FBS. The plates were incubated at 37 \u0026deg;C in 5% CO₂ for 24-48 hours. Invaded cells were fixed with 4% paraformaldehyde, stained with 0.1% crystal violet.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.13 Immunohistochemistry (IHC)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParaffin-embedded tissue sections were dewaxed, rehydrated, and subjected to antigen retrieval using citrate buffer under high-pressure heating. Endogenous peroxidase activity was quenched with 3% H₂O₂, followed by blocking with 5% BSA. Antibodies were applied and incubated. The sections were visualized using DAB substrate (Cat# DA1010, Solarbio, China), counterstained with hematoxylin for 2 minutes, differentiated in acid alcohol, blued in ammonia water, dehydrated, cleared, and mounted with neutral resin. The following antibodies were used: Ki67 (Huabio, HA721115, 1:1000), E-Cadherin (Abclonal, A20798, 1:1600), N-Cadherin (Proteintech, 66219-1-Ig, 1:15000), Vimentin (Proteintech, 60330-1-Ig, 1:8000), and anti-mouse IgG HRP-conjugated secondary antibody (1:5000, Proteintech, SA00001-21).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.14 In Vivo Xenograft Tumor Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour- to six-week-old female BALB/c nude mice were maintained under specific pathogen-free conditions. To establish xenograft models, HEC-1-A and Ishikawa cells stably transduced with sh-KRT17 or sh-NC were harvested and resuspended in phosphate-buffered saline. Each mouse received a subcutaneous injection of 2 \u0026times; 10⁶ cells in a 100 \u0026mu;L volume into the right flank, with five mice per experimental group. Tumor growth was measured every three days using a digital caliper. Upon reaching the experimental endpoint, xenograft tumors were harvested, photographed, and weighed. For subsequent molecular analyses, one portion of each tumor was snap-frozen in liquid nitrogen and stored at -80\u0026deg;C for protein and RNA extraction. The remaining tumor tissue was fixed in 4% paraformaldehyde for 24 hours, followed by paraffin embedding for IHC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.15 Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll quantitative data are expressed as the mean \u0026plusmn; standard deviation (mean \u0026plusmn; SD). Statistical analyses were performed using GraphPad Prism 9.3.0 software. Comparisons between two groups were conducted using the unpaired Student\u0026rsquo;s t-test, while multiple group comparisons were analyzed by one-way ANOVA followed by Tukey\u0026rsquo;s post hoc test. Survival analysis was performed using the Kaplan-Meier method, and differences between survival curves were assessed with the log-rank test. Correlation analysis was carried out using Pearson correlation. A P-value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 KRT17 is Highly Expressed in EC and Correlates with Adverse Clinicopathological Features and Poor Prognosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntegrative analysis of transcriptomic data from the TCGA-UCEC cohort revealed a distinct expression profile and clinical relevance of KRT17 in EC. Comparative analysis revealed a marked elevation in KRT17 expression levels in EC tissues relative to normal endometrial specimens. (Figure 1A). Further stratified analysis revealed a significant correlation between high KRT17 expression and the menopausal status (Figure 1B) as well as obesity (Figure 1C) in EC patients. The association of KRT17 expression with hormonal status and obesity is consistent with findings from previous studies (Bendinelli et al., 2025; Leitzmann, Stein, Baurecht, \u0026amp; Freisling, 2025). Across histological subtypes, elevated KRT17 levels were detected in mixed carcinoma, endometrioid carcinoma, and serous carcinoma compared with normal endometrial samples (Figure 1D). Furthermore, KRT17 expression correlated positively with higher histological grade (Figure 1E), advanced FIGO stage (Figure 1F), and greater tumor invasiveness (Figure 1G), indicating its role in promoting aggressive tumor behavior. Survival analyses indicated that patients with high KRT17 expression had significantly shorter OS and DSS (P \u0026lt; 0.05; Figure 1H\u0026ndash;I). KRT17 demonstrated favorable diagnostic performance in endometrial cancer, with an area under the curve (AUC) of 0.791 (95% confidence interval [CI]: 0.712\u0026ndash;0.870; Figure 1J), supporting its potential utility as an auxiliary diagnostic biomarker. Time-dependent receiver operating characteristic (ROC) analysis for 1-, 3-, and 5-year survival revealed limited prognostic performance of KRT17 when assessed independently (AUCs: 0.557, 0.547, and 0.517, respectively; Figure 1K), suggesting that integration with complementary biomarkers may enhance predictive accuracy for prognostic risk stratification in endometrial cancer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e. KRT17 expression and its clinical relevance in EC. (A)\u003c/strong\u003e KRT17 expression in tumor vs. normal endometrial tissues.\u003cstrong\u003e\u0026nbsp;(B\u0026ndash;G)\u003c/strong\u003e Correlations between KRT17 expression and clinicopathological parameters:\u003cstrong\u003e\u0026nbsp;(B)\u003c/strong\u003e menopausal status (Post, postmenopausal; Peri, perimenopausal; Pre, premenopausal), \u003cstrong\u003e(C)\u0026nbsp;\u003c/strong\u003ebody mass index (BMI), \u003cstrong\u003e(D)\u003c/strong\u003e histological type, \u003cstrong\u003e(E)\u0026nbsp;\u003c/strong\u003ehistologic grade, \u003cstrong\u003e(F)\u0026nbsp;\u003c/strong\u003eFIGO stage, and \u003cstrong\u003e(G)\u003c/strong\u003e tumor invasiveness. \u003cstrong\u003e(H)\u0026nbsp;\u003c/strong\u003eOS and \u003cstrong\u003e(I)\u0026nbsp;\u003c/strong\u003eDSS of EC patients stratified by high/low KRT17 expression. \u003cstrong\u003e(J)\u0026nbsp;\u003c/strong\u003eROC curve illustrating the diagnostic utility of KRT17 in discriminating EC from non-malignant tissues. \u003cstrong\u003e(K)\u0026nbsp;\u003c/strong\u003eAUC values for predicting 1-, 3-, and 5-year survival (*P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Single-cell Sequencing Reveals Expression Characteristics and Functional Heterogeneity of KRT17\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrevious studies utilizing single-cell sequencing have demonstrated pronounced transcriptional heterogeneity among malignant epithelial cells in endometrial cancer, evidenced by significantly elevated copy number variation (CNV) scores in cancer cells relative to other epithelial cell types and distinct, group-specific clustering patterns of epithelial cells across pathological subtypes (Ren et al., 2024). Building upon this foundation, the present study specifically investigates the heterogeneous expression profile of KRT17 within malignant epithelial cells of endometrial cancer. Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction analysis revealed marked heterogeneity in KRT17 expression, delineating two functionally distinct subpopulations: KRT17-positive (KRT17⁺) and KRT17-negative (KRT17⁻) cells (Figure 2A-B), thereby highlighting functional state diversity within the same epithelial-derived tumor cell population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo delineate the molecular characteristics of KRT17⁺ and KRT17⁻ cell subpopulations, this study performed differential gene expression analysis to systematically compare their transcriptomic profiles.\u0026nbsp;Volcano plot (Figure 2C) revealed that the expression of mucin 4 (MUC4), follistatin-like 1 (FSTL1), insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), and L1 cell adhesion molecule (L1CAM) was significantly upregulated in KRT17⁺ cells. Concurrently, compared with KRT17⁻ cells, the expression of polymeric immunoglobulin receptor (PIGR), progesterone receptor (PGR), and activated leukocyte cell adhesion molecule (ALCAM) was markedly downregulated in KRT17⁺ cells. This distinctive transcriptional signature provides a molecular foundation for elucidating the biological properties of the KRT17⁺ subpopulation.\u003c/p\u003e\n\u003cp\u003eFurther functional enrichment analysis revealed distinct molecular functions between the two cell types: KRT17⁺ cells were significantly enriched in pathways closely associated with tumor progression, including \u0026ldquo;cytokine signaling in immune system,\u0026rdquo; \u0026ldquo;vascular endothelial growth factor A (VEGFA)/VEGF receptor (VEGFR) signaling,\u0026rdquo; \u0026ldquo;proteasome degradation,\u0026rdquo; and \u0026ldquo;actin cytoskeleton organization.\u0026rdquo; These findings align with the established role of KRT17 in promoting tumor cell proliferation and migration, further confirming that KRT17 enhances malignant behaviors such as migration and invasion (Figure 2D). In contrast, KRT17⁻ cells were enriched in functions related to tissue differentiation, basal metabolism, and cellular homeostasis, such as \u0026ldquo;peptide chain elongation,\u0026rdquo; \u0026ldquo;respiratory chain complex I,\u0026rdquo; and \u0026ldquo;mammary gland epithelium development,\u0026rdquo; suggesting their potential involvement in regulating metabolic reprogramming within the tumor microenvironment (Figure 2E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 KRT17⁺ Cells Exhibit Pro-Tumorigenic Signaling and EMT Enrichment in EC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFurther GSEA demonstrated that KRT17⁺ cells exhibited significantly higher activity in multiple pro-tumorigenic pathways, with marked enrichment in signaling pathways such as EMT and phosphoinositide 3-kinase (PI3K)/AKT, as well as inflammation-related pathways. In contrast, KRT17⁻ cells were predominantly associated with core metabolic processes, particularly glycolysis and fatty acid oxidation (Figure 3A). Quantitative analysis of key phenotypic pathway activities revealed that KRT17-positive cells possessed significantly higher EMT enrichment scores (Figure 3B), suggesting that EMT may be a critical mechanism by which KRT17 drives the malignant progression of endometrial cancer. Collectively, single-cell transcriptomic analysis systematically elucidates the significant heterogeneity between KRT17-positive and KRT17-negative cell subpopulations in endometrial cancer regarding cell clustering, gene expression, functional enrichment, and pathway activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 KRT17 Promotes Endometrial Cancer Cell Proliferation In Vitro\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStable KRT17 knockdown models were established in HEC-1-A and Ishikawa cells using shRNAs (sh-KRT17-1, sh-KRT17-2, sh-KRT17-3), with knockdown efficiency confirmed at both mRNA and protein levels (Figure 4A-B). Consistent with the CCK-8 and EdU assay results, genetic ablation of KRT17 led to a pronounced inhibition of cellular viability and proliferative capacity in both tested cell lines (Figure 4C-D). Furthermore, colony and tumor sphere formation assays additionally confirmed that KRT17 knockdown substantially compromised clonogenic potential. (Figure 4E-F), indicating a critical role for KRT17 in sustaining the clonogenic proliferation of tumor cells. Collectively, these results demonstrate that KRT17 enhances the ability of cells to proliferate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 KRT17 Facilitates EC Cell Migration and Invasion via EMT Regulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the functional role of KRT17 in EC cell motility and underlying mechanisms, we performed a series of functional assays. Genetic depletion of KRT17 markedly attenuated the migratory (Figure 5A) and invasive (Figure 5B) capacities of HEC-1-A and Ishikawa cells. At the molecular level, KRT17 silencing triggered a transcriptional program consistent with EMT, characterized by upregulated E-cadherin expression and concurrent downregulation of N-cadherin, Vimentin, and Snail1 mRNA (Figure 5C). Western blot analysis confirmed the cadherin switch and the reduction in Vimentin expression (Figure 5D). Thus, KRT17 enhances the metastatic potential of EC cells by activating EMT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 In Vivo Validation of KRT17-Driven Malignancy via EMT Activation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo definitively establish the oncogenic function of KRT17, we employed subcutaneous xenograft models. KRT17 knockdown potently inhibited tumor growth and decreased final tumor mass in both HEC-1-A and Ishikawa models (Figure 6A-B). Molecular analysis of the xenografts revealed that KRT17 silencing induced an EMT-reversal signature, characterized by increased E-cadherin and decreased N-cadherin and Vimentin at the mRNA level (Figure 6C). These protein-level observations were validated through Western blot and immunohistochemical analyses, which consistently demonstrated increased E-cadherin expression along with decreased levels of N-cadherin, Vimentin, and Ki67 following KRT17 knockdown (Figure 6D-E). Collectively, these in vivo findings substantiate that KRT17 drives endometrial carcinogenesis and EMT, supporting its potential value as a therapeutic target in preclinical models.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo date, only one study has preliminarily suggested, through a pan-cancer analysis, that KRT17 may serve as a negative prognostic biomarker in high-grade endometrial cancer (Bai et al., 2019). However, that study did not explore the molecular function or underlying mechanisms of KRT17, nor did it analyze its relationship with clinicopathological characteristics. Through integrated bioinformatics coupled with experimental validation both in vitro and in vivo, this study comprehensively delineates the expression patterns, functional roles, and molecular mechanisms of KRT17 in EC, offering novel theoretical insights and potential therapeutic targets for EC diagnosis and treatment.\u003c/p\u003e\n\u003cp\u003eFirst, we established the clinical relevance of KRT17 in EC. Analysis of the TCGA-UCEC dataset revealed significant upregulation of KRT17 in endometrial carcinoma tissues compared with normal endometrial tissues. Furthermore, KRT17 expression levels correlated significantly with postmenopausal status, obesity, higher histologic grade, advanced FIGO stage, and deeper myometrial invasion. Additionally, in some paired samples, KRT17 expression in tumor tissues was lower than in normal tissues, which may be attributed to biological heterogeneity caused by different molecular subtypes of the tumor, or spatial heterogeneity due to genetic mutations or epigenetic modifications in different tumor regions. KRT17 exerts context-dependent functions across breast cancer molecular subtypes: elevated KRT17 expression correlates with adverse clinical outcomes in triple-negative breast cancer, whereas it serves as a favorable prognostic indicator in patients with HER2-enriched breast cancer (Merkin et al., 2017; S. Tang et al., 2022). Further molecular subtyping and stratified analysis are required to determine whether KRT17 expression correlates with specific subtypes. Survival analysis confirmed that high KRT17 expression serves as an independent risk factor for reduced OS and DSS. These findings align with established literature characterizing KRT17 as an indicator of unfavorable prognosis in multiple malignancies, such as pancreatic carcinoma (Roa-Pe\u0026ntilde;a et al., 2021) and non-small cell lung cancer (Babu et al., 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecond, this study delineates the mechanism by which KRT17 drives EC malignancy, primarily through activating the EMT pathway. In vitro, KRT17 knockdown suppressed EC cell (HEC-1-A and Ishikawa) proliferation, migration, and invasion, which was associated with an increase in E-cadherin and decreases in N-cadherin and Vimentin. These findings were corroborated in vivo, where KRT17 depletion attenuated xenograft tumor growth and reversed EMT. This finding is consistent with prior reports in gastric cancer (H. Hu et al., 2018), suggesting that the mechanism by which KRT17 regulates EMT may be evolutionarily conserved across multiple epithelial-derived malignancies. Single-cell functional enrichment analysis further confirmed significantly elevated EMT pathway activity in KRT17⁺ cells relative to KRT17⁻ cells, indicating that KRT17 may serve as an upstream regulator driving these pro-invasive phenotypes.\u003c/p\u003e\n\u003cp\u003eSingle-cell transcriptomic analysis revealed that KRT17⁺ cells exhibited not only significant enrichment in the EMT pathway but also activation of cytokine signaling and VEGFA/VEGFR signaling pathways, suggesting a pivotal role for KRT17 in tumor microenvironment remodeling. Our study identified a co-expression signature of MUC4, IGF2BP2, and FSTL1 in KRT17⁺ cells, forming a potential regulatory network. As a membrane-bound mucin, MUC4 promotes tumor migration and invasion by modulating cell adhesion and signal transduction, with its elevated expression associated with poor prognosis in endometrial cancer (Dreyer, VanderVorst, Free, Rowson-Hodel, \u0026amp; Carraway, 2021; C. M. Hu et al., 2023). IGF2BP2, an RNA-binding protein, drives malignant progression across multiple malignancies\u0026mdash;including thyroid carcinoma\u0026nbsp;(Chen et al., 2026), colorectal cancer\u0026nbsp;(Niu et al., 2026), lung adenocarcinoma\u0026nbsp;(Ling et al., 2025), and pancreatic ductal adenocarcinoma\u0026nbsp;(Ge et al., 2025)\u0026mdash;by recognizing m⁶A-modified target mRNAs to regulate their stability and translational efficiency. Notably, recent evidence indicates that IGF2BP2 facilitates efficient protein synthesis through liquid-liquid phase separation-mediated formation of ribonucleoprotein granules\u0026nbsp;(Xiong et al., 2025). Functionally context-dependent, the secreted glycoprotein FSTL1 suppresses M2 macrophage recruitment to exert protective effects in triple-negative breast cancer\u0026nbsp;(Yang, Lu, Jia, \u0026amp; Gao, 2023), whereas in other tumor contexts it promotes progression by inducing EMT\u0026nbsp;(S. Yu et al., 2024), enhancing stemness properties\u0026nbsp;(Zhou et al., 2024), and remodeling the immune microenvironment\u0026nbsp;(H. Zhang et al., 2025). In glioblastoma, FSTL1 sustains tumor stem cell self-renewal and drives M2 macrophage polarization via autocrine and paracrine signaling, establishing a\u0026nbsp;pro-tumorigenic feedback loop\u0026nbsp;(Zhou et al., 2024). Collectively, these findings suggest that in endometrial cancer, KRT17 may orchestrate malignant progression by coordinately regulating effector molecules such as FSTL1 to integrate EMT activation with immune microenvironment remodeling.\u003c/p\u003e\n\u003cp\u003eKRT17 likely drives the malignant progression of EC by orchestrating pivotal oncogenic processes, including EMT. Direct evidence supporting this role comes from our observation that KRT17⁺ cells exhibit a marked increase in the activity of EMT pathway compared to their KRT17⁻ counterparts, positioning KRT17 as a potential upstream master regulator of these pro-invasive phenotypes. Mechanistically, EMT is known to be finely regulated by key signaling pathways such as Janus Kinase 2/STAT3, AKT, and MAPK, which act in concert to enhance tumor cell invasiveness and immune evasion (Shen et al., 2024; Xiao, Zhang, Peng, Wei, \u0026amp; Ma, 2021; Y. Yu et al., 2023). We thus speculate that KRT17 may promote EMT through activation of, or synergy with, one or more of these signaling axes, although the precise mechanisms require further investigation. In summary, our work identifies KRT17 as a key driver of endometrial carcinoma progression that promotes tumor invasion by activating the EMT program.\u003c/p\u003e\n\u003cp\u003eWhile this study systematically demonstrates that KRT17 promotes the malignant progression of EC through EMT activation, several limitations should be acknowledged. First, the upstream signaling mechanisms by which KRT17 regulates EMT remain incompletely understood. Although KRT17 knockdown resulted in increased E-cadherin and decreased N-cadherin and vimentin expression, the precise molecular pathways through which KRT17 modulates key signaling effectors require further elucidation. Second, the direct regulatory relationship between KRT17 and signature genes of KRT17\u003csup\u003e+\u003c/sup\u003e cells\u0026mdash;including MUC4, IGF2BP2, and FSTL1, as identified by single-cell analysis\u0026mdash;has not been functionally validated. Future studies should employ techniques such as co-knockdown assays, chro matin immunoprecipitation (ChIP), and RNA immunoprecipitation (RIP) to delineate the regulatory network linking KRT17 to these downstream effectors. Such investigations would provide a mechanistic foundation for developing targeted therapies against KRT17 and its associated regulatory network.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, this study systematically elucidated the critical role of KRT17 in the pathogenesis and progression of endometrial cancer. For the first time, it was demonstrated that KRT17 drives malignant tumor progression through activation of the EMT program and is significantly associated with reduced overall survival in patients with endometrial cancer. These findings offer a strong rationale for developing KRT17-targeted therapies, such as siRNA-based nanomedicines or small-molecule inhibitors. Our work thus provides a solid experimental foundation for incorporating KRT17 targeting into the precision medicine arsenal for endometrial carcinoma.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eEndometrial cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eKRT17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eKeratin 17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eqRT-PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eQuantitative reverse transcription polymerase chain reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eEMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eEpithelial-mesenchymal transition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eOverall survival\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eDSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eDisease-specific survival\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eMSI-H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMicrosatellite instability-high\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003edMMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMismatch repair-deficient\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eNSMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eNo specific molecular profile\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eAKT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eProtein kinase B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003emTOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMechanistic target of rapamycin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eHIF-1\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eHypoxia-inducible factor 1\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eGLUT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eGlucose transporter 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eMCL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMyeloid cell leukemia 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eVEGF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eVascular endothelial growth factor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eTME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eTumor microenvironment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eUCEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eUterine corpus endometrial carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eTCGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eThe Cancer Genome Atlas\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eANOVA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eOne-way analysis of variance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eGSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eGene Set Enrichment Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eBSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eBovine serum albumin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eHRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eHorseradish peroxidase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eFBS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eFetal bovine serum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eIHC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eImmunohistochemistry\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eTGF-\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eTransforming growth factor-\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eMUC4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eMucin 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eIGF2BP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eInsulin-like growth factor 2 mRNA binding protein 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eFSTL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eFollistatin-like 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eSTAT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eSignal transducer and activator of transcription 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments were performed in accordance with the Guidelines for the Welfare and Use of Experimental Animals of China and were approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (Approval No. 2025-KY-1306-001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Henan Academy of Medical Sciences and the Henan Provincial Health Commission [Grant No. HNCRD202429]; and the Henan Provincial Health Commission [Grant No. SBGJ202302075].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXiaole Song, Xuerou Chen: methodology, investigation, data curation, formal analysis, writing \u0026ndash; original draft. Qianwen Liu, Yajuan Ma, Xiaoran Zhang: investigation, visualization, writing \u0026ndash; original draft. Fang Ren: conceptualization, supervision, formal analysis, funding acquisition, resources, visualization, writing \u0026ndash; review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge Dr. Lin Shitong from Huazhong University of Science and Technology for his valuable contributions to our endometrial cancer cell line.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Gynecologic Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China.\u003c/p\u003e\n\u003cp\u003eXiaole Song ([email protected]); Xuerou Chen ([email protected]); Qianwen Liu ([email protected]); Yajuan Ma ([email protected]); Xiaoran Zhang ([email protected]); Fang Ren ([email protected])\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBabu, S., Horowitz, M., Delgado-Coka, L. 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FSTL1 sustains glioma stem cell stemness and promotes immunosuppressive macrophage polarization in glioblastoma. \u003cem\u003eCancer Lett, 611\u003c/em\u003e, 217400. doi:10.1016/j.canlet.2024.217400\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-cancer-research-and-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocr","sideBox":"Learn more about [Journal of Cancer Research and Clinical Oncology](https://www.springer.com/journal/432)","snPcode":"432","submissionUrl":"https://submission.nature.com/new-submission/432/3","title":"Journal of Cancer Research and Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Endometrial cancer, Epithelial mesenchymal transition, KRT17, Migration, Proliferation","lastPublishedDoi":"10.21203/rs.3.rs-9264510/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9264510/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEndometrial cancer (EC) is a common gynecological malignancy with increasing incidence, and advanced or recurrent cases have limited treatment options. The role of Keratin 17 (KRT17), a type I intermediate filament protein implicated in tumor progression in other cancers, remains unclear in EC. This study aimed to investigate the expression, prognostic significance, and functional mechanisms of KRT17 in EC. Bioinformatics analysis revealed significant upregulation of KRT17 in EC tissues, with elevated expression strongly correlated with adverse clinical outcomes and reduced overall survival. Single-cell RNA sequencing (scRNA-seq) analysis elucidated the distribution and expression profiles of KRT17 in malignant epithelial cells of endometrial cancer, and differential expression analysis combined with gene set enrichment analysis (GSEA) further confirmed the significant enrichment of KRT17 in the EMT pathway. In vitro functional assays confirmed that stable knockdown of KRT17 significantly inhibited the proliferation, migration, invasion, and spheroid formation of EC cells, and altered the expression of key EMT markers. In vivo animal models demonstrated that KRT17 knockdown effectively suppressed tumor growth and reversed the EMT process. Collectively, KRT17 functions as an oncogene in EC by activating EMT to drive malignant progression, representing a potential therapeutic target.\u003c/p\u003e","manuscriptTitle":"Keratin 17 Drives Endometrial Cancer Aggressiveness via Epithelial-Mesenchymal Transition: A Single-Cell Transcriptomic and Integrative Bioinformatics Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-06 16:37:01","doi":"10.21203/rs.3.rs-9264510/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"150559612135142605575953929572294144951","date":"2026-05-19T01:48:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-27T09:35:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-12T09:17:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-11T13:52:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cancer Research and Clinical Oncology","date":"2026-04-10T18:51:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cancer-research-and-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocr","sideBox":"Learn more about [Journal of Cancer Research and Clinical Oncology](https://www.springer.com/journal/432)","snPcode":"432","submissionUrl":"https://submission.nature.com/new-submission/432/3","title":"Journal of Cancer Research and Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c3a8f1cc-cefe-483b-bcfd-8f561488c125","owner":[],"postedDate":"May 6th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"150559612135142605575953929572294144951","date":"2026-05-19T01:48:52+00:00","index":45,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T16:37:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-06 16:37:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9264510","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9264510","identity":"rs-9264510","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}