The marked heterogeneity of primary liver cancer (PLC), together with the dynamic influence of the tumor microenvironment (TME), remains a major challenge to precision oncology. As currently available therapies provide limited benefit for many patients and robust preclinical platforms for rapid, patient-specific treatment stratification are lacking, there is an urgent need for models that faithfully preserve individual tumor architecture and cellular diversity. We established three-dimensional bioprinted primary liver cancer (3DP-PLC) models comprising 61 patient-derived monocultures and 34 co-culture models with patient-matched cancer-associated fibroblasts (CAFs). To explore the correlation between ex vivo models and clinical drug response, we developed a clinically anchored hybrid stratification framework for response classification. In parallel, the 3DP-PLC/CAF co-culture biobank was used to investigate stromal regulation of therapeutic response. These 3DP-PLC constructs preserved the histological features, biomarker expression patterns, mutational landscapes, and transcriptomic profiles of their corresponding parental tumors. Drug-sensitivity profiling across the biobank revealed substantial intertumoral heterogeneity in therapeutic responses. The clinically anchored hybrid stratification framework integrating ex vivo pharmaceutical profiles with external clinical benchmark data enabled interpretable response classification and demonstrated clinical relevance in patients receiving neoadjuvant or adjuvant targeted therapy. In parallel, the 3DP-PLC/CAF co-culture biobank, combined with single-cell transcriptomic analysis, recapitulated fibrous ring-like architecture and revealed CAF-associated drug-resistant states. These findings support 3DP-PLC as a high-fidelity and scalable platform for personalized therapeutic stratification and mechanistic investigation of tumor–stroma interactions in PLC.

e16251 Background: Postoperative recurrence remains a major challenge in hepatocellular carcinoma (HCC), particularly among patients with high-risk pathological features. Currently, no globally accepted standard adjuvant therapy exists after curative resection. This study reports an interim analysis evaluating the efficacy and safety of adjuvant donafenib combined with transarterial chemoembolization (TACE) in patients with high-risk HCC following surgery. Methods: This prospective, single-arm, single-center study enrolled patients with hepatocellular carcinoma who underwent curative resection and had predefined high-risk recurrence features, including tumor size > 5 cm, microvascular invasion, satellite lesions, or portal vein tumor thrombus. Patients received donafenib (200 mg BID) combined with a fixed single session of postoperative transarterial chemoembolization for a planned duration of 6 months. The primary endpoint was 12-month recurrence-free survival rate, with secondary endpoints including recurrence-free survival, overall survival, time to recurrence, and safety. This study was registered at ClinicalTrials.gov (NCT05161143). Results: As of December 10, 2025, 25 patients were enrolled, with a median follow-up of 9.7 months. High-risk features included tumor size ≥5 cm (56.0%), MVI (56.0%), satellite lesions (20.0%), and multiple concurrent high-risk factors (36.0%), and notably, the inclusion of patients with concomitant PVTT (n = 2). At data cut-off, 4 patients experienced recurrence, including one death. The 6-month RFS rate was 95.2% (95% CI, 86.6-100), and the estimated 12-month RFS rate was 74.9% (95% CI, 56.0-100); median RFS was not reached. In subgroup analyses, 12-month RFS rates were 81.5% and 66.7% in patients with tumor size ≥5 cm and < 5 cm, respectively. Patients without MVI showed a numerically higher 12-month rate than those with MVI (80.8% vs 66.7%). No stable subgroup-specific differences were observed according to satellite lesions or PVTT. Overall survival data remain immature. Treatment-emergent adverse events (TEAEs) occurred in 84.0% of patients, with grade ≥3 TEAEs reported in 36.0%. No grade 4 or 5 treatment-related adverse events were observed. ALBI scores remained stable during treatment, with no significant difference between baseline and end of treatment (median −3.12 vs −3.14, p = 0.68), indicating preserved liver function. Conclusions: This interim analysis suggests that adjuvant donafenib combined with a single session of postoperative TACE demonstrates encouraging antitumor activity and a manageable safety profile in patients with high-risk HCC after curative resection. Longer follow-up and larger studies are warranted to confirm the durability of benefit. Clinical trial information: NCT05161143 .

Three-dimensional (3D) bioprinting is an emerging strategy for constructing tissues and organsin vitro. Here, we achieved long-term expansion of primary mouse hepatocytes using a defined medium and constructed liver tissue using 3D bioprinting. The 3D-printed liver tissue demonstrated several essential liver functions and was able to prolong the survival of mice with acute liver failure due to extreme hepatectomy afterin vivotransplantation, and the transplanted artificial liver tissue showed distinct functional partitioning. Overall, our results develop a method for long-termin vitroculture of primary hepatocytes and demonstrate the potential of 3D bio-printed liver tissue for clinical translational applications.

DNA damage exhibits a strong correlation with gastric cancer (GC). However, there is still a paucity of comprehensive, in-depth investigations into this relationship. We aimed to explore the association between DNA damage-related genes and GC to provide insights into its molecular mechanisms and potential biomarkers. For this study, Bulk RNA sequencing data of GC were obtained from The Cancer Genome Atlas (TCGA), single-cell RNA sequencing datasets were retrieved from the Gene Expression Omnibus (GEO), and a DNA damage-associated gene set was sourced from the GeneCards database. Through the application of survival analysis, differential expression gene analysis, and weighted gene co-expression network analysis, we identified DNA damage-related genes potentially linked to GC. Subsequently, multiple machine learning approaches were employed to screen out hub genes with considerable diagnostic potential. Analysis of bulk RNA sequencing data verified gene expression patterns in GC. Single-cell analysis further demonstrated cell-type-specific gene expression, and immunohistochemical experiments were conducted to validate the potential biomarker utility of key genes. Our findings revealed that thirteen DNA damage-related genes that may be linked to GC were identified. Subsequently, CLSPN and SALL4 were screened out as hub genes possessing considerable diagnostic potential. Analysis of bulk RNA sequencing data verified the upregulated expression of these two genes in GC, thereby underscoring their predictive significance. Across multiple machine learning methods, CLSPN was consistently ranked as the gene with the highest importance. Single-cell analysis further demonstrated that CLSPN is predominantly highly expressed in tumor cells, which emphasizes its cell-type-specific function in GC. To validate CLSPN’s potential as a biomarker, we conducted immunohistochemical experiments; these experiments showed high CLSPN expression in GC tissues, and the expression levels were significantly correlated with age, tumor size, pT stage and lymph node metastasis. This study reinforces the link between DNA damage and GC and offers fresh perspectives on its underlying molecular mechanisms. Nonetheless, further validation in clinical evaluation is essential to confirm its practical value for GC management strategies.

Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignancy with a dismal prognosis, and pronounced interpatient heterogeneity severely limits the efficacy of systemic therapies, underscoring the need for rapid and accurate functional platforms to guide individualized drug selection. Here, we develop a clinically oriented, patient-derived, 3D bioprinted in vitro model for personalized drug sensitivity assessment in ICC. Using a compositionally defined and cost-effective GelMA/HAMA composite hydrogel, we reconstruct a tumor microenvironment that supports rapid self-organization and sustained viability of primary ICC cells. Histological analyses, marker expression profiling, and bright-field imaging demonstrate close similarity to matched patient tumor tissues. Genomic and transcriptomic fidelity are further confirmed by whole-exome and RNA sequencing, revealing preserved driver mutations and transcriptional programs. Drug sensitivity testing was performed on tumor samples from 21 ICC patients using clinically relevant agents. Notably, in patients receiving neoadjuvant therapy, in vitro drug responses were fully consistent with clinical outcomes. Longitudinal follow-up further showed that recurrence occurred exclusively in patients who did not receive the predicted sensitive therapies. Importantly, clinically actionable drug response profiles were generated within 10 days. Collectively, this platform provides a rapid, reproducible, and patient-specific functional drug testing strategy with strong potential for clinical translation.

Cholangiocarcinoma (CCA) is an aggressive biliary tract cancer with limited treatment options, underscoring the need for breakthrough precision therapies. Neoantigen-based therapy is a promising novel strategy for cancer treatment. This study investigates the potential of neoantigen peptides in CCA, emphasizing their role in personalized immunotherapy and providing insights for vaccine design. Paired samples from 33 CCA patients underwent whole-exome sequencing and RNA sequencing to profile the mutational and neoantigen landscape. Besides, personalized neoantigen peptides were synthesized and immunogenicity was validated through enzyme-linked immunospot assay. Meanwhile, corresponding T cell receptor (TCR) sequences were predicted by bioinformatics. TP53 was the most frequently mutated gene (57.58

Liver tumors exhibit significant heterogeneity in etiology, pathology, and treatment response, making accurate differential diagnosis critical for diagnosis and management. While multi-phase contrast-enhanced computed tomography (CT) provides valuable imaging patterns for differentiation, visual assessment alone is often limited by overlapping features. To address this, we present MCT-LTDiag, a comprehensive Multi-phase CT dataset for Liver Tumor Diagnosis, comprising 517 cases with four-phase contrast-enhanced CT scans (non-contrast, arterial, portal venous, and delayed phases) and five tumor subtypes: hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), colorectal liver metastasis (CRLM), breast cancer liver metastasis (BCLM), and hepatic hemangioma (HH). The dataset features standardized preprocessing, rigorous quality control, and expert-annotated tumor masks. Baseline experiments using radiomics-based machine learning and deep learning models demonstrate the dataset’s utility, with multi-phase integration significantly improving diagnostic performance. MCT-LTDiag serves as a benchmark for advancing automated liver tumor subtype classification and is publicly available to support future research.

Urine, a rich biological resource containing diverse metabolites, proteins, exfoliated cells, and cell-free DNA, provides valuable insights into physiological and pathological states. Its noninvasive nature and ease of collection have established urinary biomarkers as promising tools for detecting urological cancers, particularly bladder, prostate, and cervical malignancies. Advances in multi-omics technologies, including genomics, proteomics, and metabolomics, have significantly enhanced analytical sensitivity and specificity, improving diagnostic accuracy and disease monitoring. This comprehensive review systematically examines recent progress in biomarker discovery and clinical applications across various cancers, critically evaluating their diagnostic potential while addressing current limitations and challenges. The insights provided in this study aim to facilitate the optimization of urinary biomarker-based strategies and promote their broader integration into clinical practice for improved cancer detection and management.

INTRODUCTION AND IMPORTANCE:Giant splenic hemangiomas are rare and pose diagnostic and management challenges, particularly during pregnancy. This case highlights the need for multidisciplinary approach to manage such a massive splenic lesion in the second trimester. CASE PRESENTATION:A 34-year-old woman with pre-pregnancy splenic cysts developed left upper quadrant distension at 19 weeks of gestation. Physical examination and preoperative ultrasound confirmed splenic enlargement. Due to concerns for splenic rupture from uterine compression, open splenectomy was performed at 19 weeks + 5 days. Histopathology analysis confirmed splenic hemangioma. CLINICAL DISCUSSION:Management of splenic hemangioma or other types of massive splenic mass lacks standardized guideline. And imaging alone cannot reliably differentiate type of splenic lesions. In pregnant patients, management should be individualized based on lesion size, symptoms, gestational age, and complication risk of conservative approaches. Treatment options necessitate multidisciplinary collaboration to balance maternal-fetal safety. CONCLUSION:This case of giant splenic hemangioma during pregnancy demonstrates that splenectomy in the second trimester is feasible after balancing balance maternal-fetal risks. It emphasizes the necessity of multidisciplinary decision-making to optimize maternal and fetal outcomes in management of complex abdominal masses during pregnancy.

e16230 Background: Chronic hepatitis B (CHB) can result in hepatocellular carcinoma (HCC) imposing a substantial health and economic burden worldwide. Early detection of hepatitis B virus-related HCC (HBV-HCC) in CHB with potential biomarkers has emerged as an urgent and challenging task. Recent progression of urinary proteomics provides a promising method for HBV-HCC biomarker discovery. Methods: This single-center case-control study, conducted at Peking Union Medical College Hospital, enrolled 33 patients with HBV-HCC, 26 patients with CHB, 30 healthy controls, and 33 controls with other types of cancer. Urine proteomes were analyzed using liquid chromatography with tandem mass spectrometry by data-dependent acquisition or parallel reaction monitoring, respectively. Differential analysis was carried out with limma package in R software, and the origin of selected proteins was confirmed with immunohistochemistry of surgical specimens. The diagnostic performance of the biomarker panel was evaluated with area under receiver operator curves (AUROC). Results: 21 urinary proteins were significantly upregulated in HBV-HCC compared with CHB samples, playing key roles in vesicular transportation, cytoskeleton-extracellular matrix interaction, and tumor development according to enrichment analysis. Immunohistochemistry validated the differential expression of 4 urinary proteins (4UP: HNRNPM, ADGRG1, APOC1, and RALA) across cancerous and adjacent normal liver tissues. These proteins were specifically found in HBV-HCC but not in CHB, healthy control, or other cancer controls. The AUROCs of 4UP individually (0.642 for APOC1, 0.780 for HNRNPM, 0.755 for ADGRG1, 0.729 for RALA) were no worse than that of serum α-fetoprotein (AUROC = 0.751), and the 4UP panel unified via logistic regression showed an AUROC of 0.828. Conclusions: Urinary proteomics revealed HNRNPM, ADGRG1, APOC1, and RALA as biomarkers to distinguish HBV-HCC from CHB. The 4UP could be traced back to HBV-HCC tumor cells, shedding light on pathogenesis of HBV-HCC. [Table: see text]

Gallbladder carcinoma (GBC) is a malignant hepatobiliary cancer characterized by an intricate tumor microenvironments (TME) and heterogeneity. The traditional GBC 2D culture models cannot faithfully recapitulate the characteristics of the TME. Three-dimensional (3D) bioprinting enables the establishment of high-throughput and high-fidelity multicellular GBC models. In this study, we designed a concentric cylindrical tetra-culture model to reconstitute the spatial distribution of cells in tumor tissue, with the inner portion containing GBC cells, and the outer ring containing a mixture of endothelial cells, fibroblasts, and macrophages. We confirmed the survival, proliferation, biomarker expression and gene expression profiles of GBC 3D tetra-culture models. Hematoxylin-eosin (HE) and immunofluorescence staining verified the morphology and robust expression of GBC/endothelial/fibroblast/macrophage biomarkers in GBC 3D tetra-culture models. Single-cell RNA sequencing revealed two distinct subtypes of GBC cells within the model, glandular epithelial and squamous epithelial cells, suggesting the mimicry of intratumoral heterogeneity. Comparative transcriptome profile analysis among various in vitro models revealed that cellular interactions and the TME in 3D tetra-culture models reshaped the biological processes of tumor cells to a more aggressive phenotype. GBC 3D tetra-culture models restored the characteristics of the TME as well as intratumoral heterogeneity. Therefore, this model is expected to have future applications in tumor biology research and antitumor drug development.

Gallbladder cancer (GBC) is a highly aggressive malignancy, with limited survival profiles after curative surgeries. This study aimed to develop a practical model for predicting the postoperative overall survival (OS) in GBC patients. Patients from three hospitals were included. Two centers (N = 102 and 100) were adopted for model development and internal validation, and the third center (N = 85) was used for external testing. Univariate and stepwise multivariate Cox regression were used for feature selection. A nomogram for 1-, 3-, and 5-year postoperative survival rates was constructed accordingly. Performance assessment included Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves. Kaplan-Meier curves were utilized to evaluate the risk stratification results of the nomogram. Decision curves were used to reflect the net benefit. Eight factors, TNM stage, age-adjusted Charlson Comorbidity Index (aCCI), body mass index (BMI), R0 resection, blood platelet count, and serum levels of albumin, CA125, CA199 were incorporated in the nomogram. The time-dependent C-index consistently exceeded 0.70 from 6 months to 5 years, and time-dependent ROC revealed an area under the curve (AUC) of over 75

The overexpression of Kruppel-like factor 5 (KLF5) appears in several types of cancer. KLF5 may be an effective therapeutic target for treating OC, but its function in ovarian cancer (OC) remains unknown. The KLF5 mRNA expression levels in several OC cell lines were analyzed using RT-qPCR. Then, NC-siRNA or KLF5-siRNA was transfected into SK-OV-3 and OVCAR-3 cells. RT-qPCR and WB were used to detect the efficiency of KLF5 silence, CCK-8, colony formation assay, IHC staining, flow cytometry, and WB were performed to investigate the KLF5 function on OC cell proliferation and the activation of the extracellular signal-regulated Kinase (ERK)/mitogen-activated protein kinase (MAPK) signaling pathway. Next, a dual-luciferase and IF assay were used to determine the relationship between KLF5 and the Ras response element-binding protein (RREB1). SK-OV-3 and OVCAR-3 cells were treated with KLF5-siRNA and C16-PAF + EGF (MAPK agonist), separately or in combination. Proteins including KLF5, RREB1, p-p38, p-ERK1/2, ERK5, p-ERK5, Cyclin D1, CDK4, and CDK6 were quantified by WB. Finally, CCK-8, colony formation assay, and flow cytometry were employed again. KLF5 is highly expressed in OC cells compared with normal cells. When KLF5 knockdowns in SK-OV-3 and OVCAR-3 cells, the cell proliferation restrains, and the G1 phase prolongs. In addition, KLF5 silence caused a decrease of Cyclin D1, CDK4, CDK6, p-p38, p-ERK1/2, and p-ERK5/ERK5 expression levels. However, these statuses could be revised by C16-PAF + EGF. Results also found that when the ERK/MAPK signaling is activating, RREB1 is expressed low. The KLF5 silence could up-regulate the RREB1 expression. The KLF5 silence could restrain the OC cell proliferation and cell cycle. KLF5-siRNA may target upregulating RREB1 expression, thereby inhibiting the activation of the ERK/MAPK signaling pathway in OC cells.

Introduction Pancreatic cancer (PC) remains a challenging malignancy, and adjuvant chemotherapy is critical in improving patient survival post-surgery. However, the intrinsic heterogeneity of PC necessitates personalized treatment strategies, highlighting the need for reliable preclinical models. Objectives This study aimed to develop novel patient-derived preclinical PC models using three-dimensional bioprinting (3DP) technology. Methods Patient-derived PC models were established using 3DP technology. Genomic and histological analyses were performed to characterize these models and compare them with corresponding patient tissues. Chemotherapeutic drug sensitivity tests were conducted on the PC 3DP models, and correlations with clinical outcomes were analyzed. Results The study successfully established PC 3DP models with a modeling success rate of 86.96%. These models preserved genomic and histological features consistent with patient tissues. Drug sensitivity testing revealed significant heterogeneity among PC 3DP models, mirroring clinical variability, and potential correlations with clinical outcomes. Conclusion The PC 3DP models demonstrated their utility as reliable preclinical tools, retaining key genomic and histological characteristics. Importantly, drug sensitivity profiles in these models showed potential correlations with clinical outcomes, indicating their promise in customizing treatment strategies and predicting patient prognoses. Further validation with larger patient cohorts is warranted to confirm their potential clinical utility.

Acoustic holography (AH), a promising approach for cell patterning, emerges as a powerful tool for constructing novel invitro 3D models that mimic organs and cancers features. However, understanding changes in cell function post-AH remains limited. Furthermore, replicating complex physiological and pathological processes solely with cell lines proves challenging. Here, we employed acoustical holographic lattice to assemble primary hepatocytes directly isolated from mice into a cell cluster matrix to construct a liver-shaped tissue sample. For the first time, we evaluated the liver functions of AH-patterned primary hepatocytes. The patterned model exhibited large numbers of self-assembled spheroids and superior multifarious core hepatocyte functions compared to cells in 2D and traditional 3D culture models. AH offers a robust protocol for long-term in vitro culture of primary cells, underscoring its potential for future applications in disease pathogenesis research, drug testing, and organ replacement therapy.

Cell-laden bioprinting is a promising biofabrication strategy for regenerating bioactive transplants to address organ donor shortages. However, there has been little success in reproducing transplantable artificial organs with multiple distinctive cell types and physiologically relevant architecture. In this study, an omnidirectional printing embedded network (OPEN) is presented as a support medium for embedded 3D printing. The medium is state-of-the-art due to its one-step preparation, fast removal, and versatile ink compatibility. To test the feasibility of OPEN, exceptional primary mouse hepatocytes (PMHs) and endothelial cell line-C166, were used to print hepatospheroid-encapsulated-artificial livers (HEALs) with vein structures following predesigned anatomy-based printing paths in OPEN. PMHs self-organized into hepatocyte spheroids within the ink matrix, whereas the entire cross-linked structure remained intact for a minimum of ten days of cultivation. Cultivated HEALs maintained mature hepatic functions and marker gene expression at a higher level than conventional 2D and 3D conditions in vitro. HEALs with C166-laden vein structures promoted endogenous neovascularization in vivo compared with hepatospheroid-only liver prints within two weeks of transplantation. Collectively, the proposed platform enables the manufacture of bioactive tissues or organs resembling anatomical architecture, and has broad implications for liver function replacement in clinical applications.

AbstractBackgroundThis study explores molecular features associated with better prognosis in cholangiocarcinoma (CCA).Methods and ResultsThe transcriptomic and whole‐exome sequencing data obtained from paired tissues of 70 were analyzed, grouping them based on progression‐free survival (PFS), differentiation degree, and lymph node metastasis. Among the 70 patients, the TP53 gene mutation frequency was the highest (53%), while FLG gene mutation occurred exclusively in the long PFS group. In the comparison between long and short survival groups, the short PFS group exhibited higher monocyte infiltration levels (p = 0.0287) and upregulation of genes associated with cancer‐related transcriptional misregulation, chemokine signaling, and cytokine‐cytokine receptor interactions. Differences in immune cell infiltration and gene expression were significant across differentiation and lymph node metastasis groups. Particularly noteworthy was the marked increase in CD8 T cell and NK cell infiltration (p = 0.0291, 0.0459) in the lymph node metastasis group, significantly influences prognosis. Additionally, genes related to platinum resistance, Th17 cell differentiation, and Th1 and Th2 cell differentiation pathways were overexpressed in this group. In summary, higher monocyte infiltration levels in the short PFS group, along with elevated expression of genes associated with cancer‐related pathways, suggest a poorer prognosis. The significant increase in CD8 T cell and NK cell infiltration reflects an enhanced anti‐tumor immune response, underscoring the relevance of immune infiltration levels and gene expression in predicting outcomes for CCA patients.ConclusionsIn this study, we elucidated the pertinent molecular mechanisms and pathways that influence the prognosis of CCAs through comprehensive multi‐omics analysis.

Cellular immunotherapy has shown considerable potential for the treatment of primary liver cancer (PLC), particularly hepatocellular carcinoma (HCC), although it is in the early stages of development. This study used bibliometric methods to delineate the evolution of research on cellular immunotherapy for PLC. Data were sourced from the Web of Science Core Collection (WoSCC) on April 22, 2024. Using the “Bibliometrix” R package, we examined primary bibliometric features, collaboration frequency between countries, and article output of the journals. Furthermore, we employed VOSviewer for coauthorship analysis and visualization and CiteSpace to assess keyword co-occurrence, as well as to spotlight keywords and references with the strongest citation bursts. Our analysis encompassed 492 publications focused on PLC and cellular immunotherapy, and we pinpointed China, Japan, and the USA as the foremost contributing nations and identified “Cancer Immunology Immunotherapy” as the journal with the most contributions in this area. Sun Yat-sen University emerged as the institution with the most significant output, and Li Zonghai authored the greatest number of leading articles. Prominent keywords that displayed a notable citation burst in the later years included “chimeric antigen receptor,” “combination therapy”, “CAR-T cells,” “TCR-T cells,” and “liver transplantation.” This bibliometric study outlined a foundational knowledge framework, surveyed over three decades of research on cellular immunotherapy for PLC, and revealed the key players and trends, thereby offering a thorough understanding of the field, especially in relation to HCC.

BackgroundLong noncoding RNAs (lncRNAs) have emerged as critical regulators of colorectal cancer (CRC) progression, but their roles and underlying mechanisms in colorectal cancer liver metastases (CRLMs) remain poorly understood.MethodsTo explore the expression patterns and functions of lncRNAs in CRLMs, we analyzed the expression profiles of lncRNAs in CRC tissues using the TCGA database and examined the expression patterns of lncRNAs in matched normal, CRC, and CRLM tissues using clinical samples. We further investigated the biological roles of LINC02257 in CRLM using in vitro and in vivo assays, and verified its therapeutic potential in a mouse model of CRLM.ResultsOur findings showed that LINC02257 was highly expressed in metastatic CRC tissues and its expression was negatively associated with overall survival. Functionally, LINC02257 promoted CRC cell growth, migration, metastasis, and inhibited cell apoptosis in vitro, and enhanced liver metastasis in vivo. Mechanistically, LINC02257 up-regulated phosphorylated c-Jun N-terminal kinase (JNK) to promote CRLM.ConclusionsOur study revealed that LINC02257 played a key role in the proliferation and metastasis of CRC cells through the LINC02257/JNK axis. Targeting this axis may represent a promising therapeutic strategy for the treatment of liver metastases in patients with CRC.