POLE-mutated (POLEmut) endometrial cancer (EC) represents a distinct molecular subtype with a favorable prognosis. However, current knowledge is derived largely from Western-centric datasets, and population-specific differences in mutational landscapes remain insufficiently explored. In addition, the biological relevance of variant type and the evolutionary dynamics of rare tumors with concurrent POLEmut and microsatellite instability-high (MSI-H) are poorly understood. We performed a comprehensive multi-cohort analysis by integrating the largest real-world dataset of POLEmut EC to date from a Chinese medical center (QDFY, n = 1,274) with public data from TCGA and CPTAC. Clinicopathological features, mutational spectra, and survival outcomes were compared across cohorts. In addition, multi-regional whole-exome sequencing was conducted to reconstruct the clonal architecture of a rare case harboring a concurrent POLE P286R mutation and MSI-H. In the QDFY cohort, we identified a distinct mutational profile in which the prevalence of the V411L variant (36.8

Medullary thyroid carcinoma (MTC) is characterized by frequent RET mutations, while non-RET alterations remain less well studied. Previous reports have identified a recurrent STK11 c.1062 C > G (p.Phe354Leu) variant in MTC, but its clinicopathologic and functional significance remains uncertain. A total of 129 MTCs (128 families) were analyzed by Sanger sequencing to screen for the STK11 c.1062 C > G variant. Germline status was assessed in cases with available normal tissue. Targeted next-generation sequencing was performed in 30 tumors (29 families). Functional effects of the STK11 c.1062 C > G variant were evaluated using an overexpression model in TT cells, with assessment of AMPKα phosphorylation. Progression-free survival was analyzed using Kaplan-Meier methods. The STK11 c.1062 C > G variant was identified in 12 of 129 MTCs (9.3

Multiple instance learning (MIL) regards a whole slide image (WSI) as a bag, from which image instances (patches) are cropped to extract features, thereby addressing the challenge that the ultra-high resolution of WSIs makes direct feature extraction infeasible. However, in positive WSIs (malignant or tumor), negative (benign or normal tissue) instances can significantly impair the effectiveness of feature extraction, and due to the high cost of labeling a large number of instances, it is currently difficult to construct well-annotated datasets to train highly accurate instance classifiers for filtering negative instances. To address this limitation, we propose PGPFMIL, a MIL framework that removes negative instances under the guidance of prior prototypes. The core idea is based on the property that negative WSIs never contain positive instances, thus leveraging a small set of negative WSIs as a support set with instance-level annotations, and applying prototype learning to classify instances and filter noisy ones in positive WSIs. Furthermore, to compensate for the potential loss of spatial information between instances caused by the filtering module, we incorporate an instance spatial-semantic fusion module and an attention module based on deficiency compensation, which supplement possibly misfiltered positive instances. We conduct experiments on one in-house dataset and three public datasets, and extensive results demonstrate that our method consistently outperforms prior state-of-the-art models across multiple tasks while showing superior generalization ability.

Accurate non-invasive tools for bladder cancer detection and preoperative assessment of muscle invasion remain limited. We developed a plasma cell-free DNA (cfDNA) fragmentomics assay to support two clinically-related tasks: detection of bladder cancer and preoperative estimation of muscle-invasive risk. Using low-pass whole-genome sequencing, we extracted fragment size coverage, copy-number variation, and nucleosome positioning features. The multicenter cohort included 656 participants from the Affiliated Hospital of Qingdao University and Yantai Yuhuangding Hospital, with an independent external validation set processed centrally using the same laboratory workflow. An integrated classifier was first trained for cancer detection. Subsequently, a separate non-muscle-invasive bladder cancer (NMIBC) versus muscle-invasive bladder cancer (MIBC) classifier was developed using definitively staged cases pooled from the training and internal validation cohorts, and tested externally. For cancer detection, the model achieved AUCs of 0.9484 (training), 0.9446 (internal validation), and 0.9390 (external validation). At a prespecified threshold, sensitivities were 81.0%, 80.0%, and 82.9%, with specificities of 95.0%, 94.7%, and 92.7% against healthy controls and 93.3% and 91.7% against benign disease controls in internal and external validation, respectively. For invasion stratification, the NMIBC/MIBC classifier achieved AUCs of 0.9378 and 0.9290 in the development and external validation cohorts, respectively, with 94.7% sensitivity and 88.4% specificity for MIBC detection externally. The assay demonstrated high reproducibility across storage conditions and sequencing batches. This blood-based framework provides accurate, multicenter bladder cancer detection and preoperative stratification of muscle invasion, demonstrating strong potential to complement current diagnostic pathways.

ObjectiveThe purpose of this study was to identify the clinical features of endometrial cancers (EC) with microsatellite instability-high (MSI-H) and BRCA1/2 mutations (BRCAm).MethodsWe selected patients diagnosed with EC who were MSI-H from the Affiliated Hospital of Qingdao University between March 2021 and December 2024. The clinical information was collected after applying the inclusion and exclusion criteria. Based on BRCA1/2 status, we divided the patients into two groups: the MSI-H only group (M group), and the MSI-H and BRCAm group (MB group). After comparing the clinical characteristics of the two groups, Kaplan-Meier (K-M) curves were employed to analyze the distribution of progression-free survival (PFS) between them. Finally, both univariate and multivariate Cox proportional hazards regression models were utilized to assess various prognostic variables.ResultsA total of 177 patients were included in the final analysis, of whom 28 were identified as having BRCAm. The rate of laparoscopic surgery in M group was higher than that in MB group (87.25% vs. 67.86%, p-value=0.022). The lymph node metastasis rate in MB group was significantly higher than that in M group (14.29% vs. 2.01%, p-value=0.011). Additionally, a higher proportion of patients received immunotherapy in MB group (7.14% vs. 2.68%, p-value=0.011). The recurrence rates in M group and MB group were 1.34% and 17.86%, respectively (p-value=0.003). K-M analysis indicated that there was statistically significant difference in PFS between the two groups (p-value=0.006). Furthermore, we did not identify any independent risk factors that influenced prognosis in our study.ConclusionThe co-occurrence of BRCAm and MSI-H is associated with high rates of lymph node metastasis and recurrence. However, BRCAm was not an independent prognostic factor influencing PFS of EC with MSI-H.

BACKGROUND:Endometrial clear cell carcinoma (ECCC) is a rare and highly aggressive histological subtype of endometrial cancer with marked metastatic potential. The molecular characteristics and underlying mechanisms governing its metastatic behaviour remain poorly understood. This study aimed to delineate molecular distinctions between metastatic (Pm) and non-metastatic (Pn) primary ECCC tumours, elucidate DNA methylation-mediated regulatory mechanisms driving metastasis, and identify potential epigenetic biomarkers and therapeutic targets. METHODS:This multicentre study involved 51 individuals diagnosed with ECCC, leading to the establishment of two independent cohorts: a sequencing cohort (n = 35) for integrated whole-genome methylation and transcriptomic analysis, and a tissue microarray (TMA) cohort (n = 16) to validate key findings. FINDINGS:Tumours exhibiting metastasis were found to possess a profoundly immunosuppressive tumour microenvironment (TME), evidenced by reduced density of tumour-infiltrating lymphocytes (TILs), especially within subsets of anti-tumour immune cells. Further analysis highlighted differential hypermethylation events in Pm tumours that acted as crucial epigenetic switches regulating immune responses. Specifically, methylation at ETS1-binding sites influenced ETS1 regulon activity, thus broadly regulating immune response processes. Epigenetic silencing of key genes in the T cell receptor (TCR) signalling pathway, such as LCK, CD3E, and ZAP70, impaired T cell activation and inhibited the activity of interacting immune pathways. Additionally, we developed a Lasso-derived metastatic risk score model, incorporating TME features (TIL density) and epigenetic predictors (LCK methylation), which demonstrated strong predictive performance (area under the curve [AUC] = 0.859). INTERPRETATION:This study illuminated the "epigenetic-immune axis" as a central regulatory mechanism driving ECCC metastasis. DNA methylation systematically silenced immune response genes by targeting ETS1-binding sites and TCR signalling components, thus reconstructing the immunosuppressive TME to facilitate metastasis. The development of the metastatic risk score model and identification of LCK as a potential therapeutic target provide valuable strategies for precision treatment decisions and advancing targeted epigenetic-immune therapies in ECCC. FUNDING:This work was supported by the National Natural Science Foundation of China, Joint Foundation Programme, Qingdao Municipal Science and Technology Bureau Municipal Science, Shenzhen Science and Technology Programme, and the Affiliated Hospital of Qingdao University Young Investigator Fund.

PURPOSE:The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). MATERIALS AND METHODS:Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. RESULTS:A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A-PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. CONCLUSION:USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Background Immune checkpoint blockade (ICB) therapies, particularly anti-PD-1, benefit only a limited subset of colorectal cancer (CRC) patients. G-protein signaling modulator 1 (GPSM1) is implicated in immunity and oncology, yet its role in regulating the CRC tumor microenvironment (TME) and contributing to anti-PD-1 resistance remains poorly understood.Methods We employed single-cell RNA sequencing and multiplex immunofluorescence on tumor samples from anti-PD-1-resistant CRC patients to evaluate GPSM1 expression and its impact on macrophage polarization. An orthotopic CRC xenograft model in C57BL/6 mice was used to assess the role of GPSM1 in vivo. An in vitro co-culture system, alongside mass cytometry and flow cytometry, explored GPSM1’s biological functions within the TME. We further used ChIP-PCR, mass spectrometry, and co-immunoprecipitation to elucidate the mechanisms regulating GPSM1 activity.Results GPSM1 expression was significantly elevated in anti-PD-1-resistant CRC tissues. Enhanced GPSM1 levels promoted anti-PD-1 resistance by driving macrophage polarization toward an immunosuppressive M2 phenotype, facilitating their infiltration into the TME. We identified the deubiquitinase USP9X as a key factor preventing GPSM1 degradation through K63-polyubiquitination. This stabilization of GPSM1 led to MEIS3 nuclear translocation, activating macrophage colony-stimulating factor expression. Importantly, ruxolitinib emerged as a promising GPSM1-targeting candidate, demonstrating improved efficacy in combination with anti-PD-1 therapy in both microsatellite instability-high and microsatellite stable CRC models.Conclusions Our findings highlight the pivotal role of GPSM1-driven M2 macrophage infiltration in mediating anti-PD-1 resistance in CRC. Targeting GPSM1 offers a novel therapeutic strategy to enhance ICB efficacy, potentially broadening the patient population that may benefit from these therapies.

This study aimed to investigate whether human periodontal ligament stem cells (hPDLSCs)-derived small extracellular vesicles (P-sEVs) can improve the periodontal inflammatory microenvironment and promote periodontal tissue regeneration by regulating macrophage pyroptosis. The expression of the GSDMD and CD68 were examined using HE and IHC in healthy and periodontitis gingival tissues. Pyroptotic levels in macrophages co-cultured with hPDLSCs or P-sEVs were assessed using various methods in vitro. The hydroxybutyl chitosan hydrogel (HBCH)/P-sEVs repair system was implanted into a rat periodontitis bone defect model in vivo. GSDMD and CD68 were significantly elevated in inflamed gingival tissues. Treatment with P. gingivalis-LPS and ATP significantly upregulated the expression of NF-κB, NLRP3, caspase-1, GSDMD-N, IL-1β, and so on at both mRNA and protein levels, and significantly enhancing lactate dehydrogenase release, the percentage of cells with damaged membranes and so on. However, these pathological effects were mitigated by the paracrine effects of hPDLSCs or direct action of P-sEVs. The HBCH/P-sEVs repair system enhanced hPDLSCs proliferation and osteogenesis, while simultaneously reducing pyroptosis and promoting alveolar bone regeneration in rats. P-sEVs significantly reduced macrophages pyroptosis induced by P. gingivalis-LPS/ATP by inhibiting the NF-κB/NLRP3/GSDMD signalling pathway in vitro. Furthermore, P-sEVs could be integrated with temperature-sensitive HBCH to establish a repair and regeneration system with potential clinical applications in the treatment of periodontitis.

Among patients with colorectal cancer (CRC), metastasis accounts for the majority of deaths, and epithelial-mesenchymal transition (EMT) is important in the metastatic process. However, the mechanism underlying the correlation between the two in CRC is unknown. Here, we verified that a receptor-independent protein, G-protein signaling modulator 1 (GPSM1), was increased in CRC and had a significant positive correlation with matrix metalloproteinase 19 (MMP19). GPSM1 and MMP19 knockdown or overexpression decreased and increased proliferation, migration and invasion of CRC cells, respectively. In addition, overexpression or knockdown of GPSM1 and MMP19 upregulated and inhibited EMT, respectively. Interfering with MMP19 reversed EMT activation via GPSM1 overexpression. Apoptosis was induced by GPSM1 and MMP19 knockdown and activated the caspase3/Bcl-2/Bax signaling pathway. In conclusion, these results support the role of GPSM1 and MMP19 in CRC progression.

Epidemiological investigations indicate that hexavalent chromium [Cr(VI)] exposure induces lung carcinogenesis, but the underlying epigenetic mechanisms of Cr(VI)-induced carcinogenesis remain to be further investigated. In this study, we used a Cr(VI)-exposed mouse model to demonstrate elevated m6A modification levels in lung tissues, and further used Cr(VI) transformed cell model (CrT) to identify that Cr(VI) induced the expression of Wilms' tumor 1-associated protein (WTAP), a key localization gene for m6A RNA methylation modification, in a time and concentration-dependent manner, and proved that WTAP enhanced cell proliferation and was involved in the maintenance of cellular stemness through up-regulating CD133 expression. Additionally, WTAP upregulated the expression of hexokinase 2 (HK2), a rate-limiting glycolytic enzyme, while knocking down HK2 significantly reduced WTAP's ability to promote CD133 expression. Furthermore, we identified m6A modification site on HK2 mRNA bound to the WTAP-VIRMA complex by molecular docking model and m6A MeRIP-qPCR assay. Notably, both WTAP and HK2 were significantly high expression in blood samples from chromium-exposed occupational workers, and their expressions were significantly positively correlated. We also demonstrated that WTAP was significantly overexpressed in lung cancer cell, and found that the overall survival rate of lung squamous cell carcinoma patients with high expression of WTAP was significantly reduced. Collectively, our study demonstrated that WTAP is a novel mechanism of Cr(VI)-induced malignant transformation of cells, and further revealed that WTAP mediates the Cr(VI)-induced glycolytic remodeling and enhances the cellular stemness via HK2. WTAP and HK2 represent promising biomarkers for chromium-exposed populations.

Rationale and Objectives Accurately predicting the pathological response to chemotherapy before treatment is important for selecting the appropriate treatment groups, formulating individualized treatment plans, and improving the survival rates of patients with gastric cancer (GC). Methods We retrospectively enrolled 151 patients diagnosed with GC who underwent preoperative chemotherapy and surgical resection at the Affiliated Hospital of Qingdao University between January 2015 and June 2023. Both pretreatment-enhanced computer technology images and whole slide images of pathological hematoxylin and eosin-stained sections were available for each patient. The image features were extracted and used to construct an ensemble radiopathomics machine learning model. In addition, a nomogram was developed by combining the imaging features and clinical characteristics. Results In total, 962 radiomics and 999 pathomics signatures were extracted from 106 patients in the training cohort. A fusion radiopathomics model was constructed using 13 radiomics and 5 pathomics signatures. The fusion model showed favorable performance compared to single-omics models, with an area under the curve (AUC) of 0.789 in the validation cohort. Moreover, a combined radiopathomics nomogram (RPN) was developed based on radiopathomics features and the Borrmann type, which is a classification method for advanced GC according to tumor growth pattern and gross morphology. The RPN showed superior predictive performance in the training (AUC 0.880) and validation cohorts (AUC 0.797). The decision curve analysis showed that RPN could provide favorable clinical benefits to patients with GC. Conclusions RPN was able to predict the pathological response to preoperative chemotherapy with high accuracy, and therefore provides a novel tool for personalized treatment of GC.

Background Ovarian cancer is the leading cause of death from gynecological malignancies. Investigating the HRR-related gene status, notably BRCA1/2 in different regions and populations is of great significance for formulating accurate target therapy. Methods We collected 124 ovarian cancer cases from the Affiliated Hospital of Qingdao University, detected the genomic alteration of 32 genes by NGS, including 19 HRR-related genes, 9 proto-oncogenes and 4 tumor suppressor genes. Clinicopathological characteristics, variants, clinical significance, and correlation with prognosis were analyzed. Results The incidence of HRR-related gene mutation was 59.68% and no statistical significance was found with multiple clinicopathological characteristics. BRCA1/2 (27.42%) were the most frequent mutated HRR genes. 23 (18.55%) cases harbored gBRCA1/2 mutation, with all BRCA1 mutations were pathogenic/likely pathogenic and 2 cases of BRCA2 mutation was variant of uncertain significance. Somatic BRCA1/2 mutations were found in 12 (9.68%) cases, and sBRCA1/2 had a higher frequency in less common ovarian cancer than high-grade serous carcinoma. HRR-related gene mutation status was associated with better prognosis than HRR wild-type. Conclusions Somatic BRCA1/2 mutation has higher incidence in less common ovarian cancer. HRR gene mutation status is an independent prognosis factor in ovarian cancer. Clarifying the HRR gene status is important for the selection of target therapy as well as the evaluation of prognosis.

Objective: To investigate the immunohistochemistry (IHC) staining pattern and prognostic significance of p53 in non-endometrioid endometrial cancer (non-EEC). Methods: This study retrospectively included 212 non-EEC patients, with histological types including serous carcinoma (SC), clear cell carcinoma (CCC), mixed carcinoma (MC), undifferentiated carcinoma (UC), and carcinosarcoma (CS). p53 IHC was interpreted as normal/wild-type and abnormal/mutant-type, the latter including overexpression, complete absence, and cytoplasmic staining patterns. Moreover, uncommon p53 subclonal/heterogeneous staining patterns were described. Disease-free survival (DFS) and overall survival (OS) were employed as endpoints to evaluate the prognostic significance of p53. Results: In 212 non-EEC cases, 50 (23.6 %) were p53 wild-type, while 162 (76.4 %) displayed abnormal p53 staining. Overexpression was the predominant abnormal p53 staining pattern (122/162), complete absence followed (33/162). All SCs exhibited the mutant p53 staining pattern. The p53 abnormal expression rates in CCC, MC, UC, and CS were 37.5 %, 78.9 %, 35.7 %, and 75.7 %, respectively. Interestingly, of the 12 MC cases with SC components, barring one with p53 subclonal staining, all showed the mutant-type staining. The concordance rate for p53 expression between epithelial and mesenchymal components of CS was 94.3 % (66/70). Kaplan-Meier curves indicated patients with p53 abnormalities had worse DFS compared to those with wild-type p53 (P=0.025). =0.025). Multivariate Cox regression confirmed that p53 (HR: 2.270, 95 % CI: 1.124-4.586, P=0.022) independently predicted DFS in non-EEC patients, though not for OS. Conclusions: Non-EEC patients with various histological types exhibit different p53 staining patterns. However, abnormal p53 expression, regardless of histological type, implies a poor DFS in non-EEC patients.

BACKGROUND Myeloid sarcoma (MS), also referred to as granulocytic sarcoma or chloroma, is a rare type of extramedullary malignant tumor. MS comprises primitive granulocytic precursor cells that play a key role in the early stages of white blood cell development. Notably, the occurrence of this tumor in the gingiva is rare. CASE SUMMARY The present study reported the case of MS with gingival swelling in the maxillary region, with aleukemic presentation in a 32-year-old male patient. Following two courses of chemotherapy, computed tomography of the region demonstrated complete clearance of the tumor. At the 12-month follow-up appointment, the patient was in a stable condition with the absence of progression. The etiology, clinical features, diagnosis, and relevant treatment of MS are discussed in the present study. CONCLUSION Diagnosis of MS may be confirmed following histological and immunohistochemical examinations.

Tongue squamous cell carcinoma (TSCC) is one of the most common malignant tumors with high mortality and poor prognosis. Its incidence rate is increasing gradually. Tumor necrosis factor receptor-associated factor interacting protein (TRAIP), as a factor related to several tumors, reveals that its gene expression is different between normal tissue and primary tumor of head and neck squamous cell carcinoma using bioinformatics analysis. In our study, TCGA database, immunohistochemistry, proliferation assay, colony formation, wound healing assay, Transwell, cell cycle analysis and tumor xenografts model were used to determine the expression and functions of TRAIP in TSCC. We found that TRAIP may promote the proliferation, migration and invasion of TSCC. Furthermore, the results of bioinformatics analysis, mass spectrometry and co-immunoprecipitation suggested that DDX39A may be a TRAIP interacting protein. DDX39A has been proven to be an oncogene in several tumors, which may have an important effect on cell proliferation and metastasis in multiple tumors. In addition, the high expression of DDX39A implies the poor prognosis of patients. Our study demonstrated that TRAIP probably interact with DDX39A to regulate cell progression through epithelial-mesenchymal transition and Wnt/β-catenin pathway. In addition, we show that the necessary domain of DDX39A for the interaction between DDX39A and TRAIP region. These results indicate that TRAIP is important in occurrence and development of TSCC and is expected to become the new promising therapeutic target.

160 Background: Cancer patient’s unique genomic profile can help oncologists select a course of precise personalized treatment for the subject. High throughput next-generation sequencing (NGS) technology allows us to identify genomic alterations simultaneously within a patient’s tumor tissue and blood-circulating tumor DNA (ctDNA) in a single test, however, robust tool for accessing mutation-treatment matching is limited. Methods: OncoGPT was built on a cloud-based elastic computing platform. The NGS data analytical module consists of a cascade of computational algorithms for NGS data processing and gene variant calling. The interactive and univariate Cox proportional hazards models were used for mutation-treatment matching and prognostic effect analysis, respectively. Machine learning algorithms including decision tree, random forest, and neural network were trained and tested with novel features for tissue-of-origin (TO) classification across 8 caner types. Results: We built an AI-driven NGS data analytical platform by integrating computational models, matching algorithms and variant annotation databases to highly accurate achieve cancer-related gene mutations, copy number variation, and structure variants using NGS data from 35,122 tumors across 8 cancer types from three institutions. Next, an AI-driven TO classifier was developed and achieved a weighted F1 score of 0.926 for high confidence predictions (≥ 0.9) on tumor samples. Furthermore, augmented AI matching algorithms were applied to match the optimal personalized treatment and provide prognostic prediction for cancer patients with significantly bett survival outcomes (hazard ratio (HR) = 0.326; 95% confidence interval (CI) = 0.213–0.565; P = 2.52×10−5). Conclusions: We have successfully developed an innovative intelligent system (OncoGPT) with AI capabilities to help accurately find actionable targets from patient tumor or blood ctDNA NGS sequencing data and precisely match individualized therapeutic and clinical trial options for patients. In addition, OncoGPT classified primary tumor sites across 8 different cancer types with high confidence predictions. We believe that OncoGPT would help clinicians make optimal treatment decisions for cancer patients through genomic-driven precision oncology.

Targeted therapy for malignancies has developed rapidly in recent years, benefiting patients harboring genetic mutations sensitive to relevant tyrosine kinase inhibitors (TKIs). With the development of targeted sequencing techniques, an increasing number of detectable genomic alterations in malignancies, including MET fusions, have been revealed. MET fusions, although rare among malignancies, might be functional driver genes that participate in activating downstream signaling pathways and promoting cell proliferation. Therefore, it is believed that MET fusions could be targetable genomic variants of MET , and inhibition of MET is considered an optionable therapeutic choice for patients harboring MET fusions. According to the summary presented in this review, we recommend MET-TKIs as suitable treatment agents for patients harboring primary MET fusions. For patients harboring acquired MET fusions after the development of resistance to TKIs targeting primary genomic alterations, such as sensitive EGFR mutations, treatment with a MET-TKI alone or in combination with TKIs targeting primary genomic alterations, such as EGFR-TKIs, is hypothesized to be a reasonable option for salvage treatment. In summary, MET fusions, despite their low incidence, should be taken into consideration when developing treatment strategies for cancer patients.

The purpose of this study is to investigate the characteristics and significance of tertiary lymphoid structures (TLSs) in endometrial cancer (EC) based on molecular subtypes. A total of 220 patients with EC were retrospectively enrolled, including 20 with polymerase epsilon ultramutated (POLE-mut), 63 with mismatch repair deficient, 32 with p53 abnormal, and 105 with no specific molecular profile. The presence and maturity of TLSs were determined by immunohistochemical markers (CD3, CD20, CD21, and Bcl6). Disease-free survival served as the endpoint event. TLSs were found in 91 out of 220 patients (41.1%), with 68 located in peritumoral tissues and 37 exhibiting well-formed germinal center structures. The presence and different maturity of TLSs were closely associated with tumor-infiltrating lymphocytes and the programmed cell death ligand-1 expression. Moreover, TLSs displayed heterogeneity across different molecular subtypes. Notably, the TLSs, tumor-infiltrating lymphocytes, and expression of the programmed cell death ligand-1 were significantly enriched in POLE-mut EC. Multivariate logistic regression analysis showed the presence of TLSs (odds ratio: 3.483, 95% CI: 1.044-11.623, P = 0.042) as a potential predictor of POLE-mut EC. Kaplan-Meier survival curves revealed that molecular subtypes significantly stratified prognosis in patients with EC (P = 0.002), whereas TLSs did not. Multivariate Cox regression analysis indicated that The International Federation of Gynecology and Obstetrics stage and Ki-67 expression were independent prognostic factors affecting disease-free survival in patients with EC, and TLSs were not included. In conclusion, TLSs in EC exhibit heterogeneity based on molecular subtypes, necessitating further exploration to determine their clinical application value.