BACKGROUND

Early-stage endometrial cancer often presents with favorable survival rates, but high-risk factors, including TP53 mutations and high-grade serous pathology, can lead to recurrence and poor prognosis. The standard primary treatment for endometrial cancer is surgical staging, and lymph node metastases significantly impact adjuvant therapy decisions. The subgroup of p53-abnormal (p53abn) indicates the worst prognosis and potential benefits from adjuvant chemotherapy. Molecular classification, while recommended, faces practical challenges due to resource constraints.

OBJECTIVES

The study aimed to assess the incidence of p53 abnormal expression in clinical stage 1 endometrial cancer cases that underwent surgery at a government tertiary hospital, and assess its relationship with clinicopathologic factors and pelvic and paraaortic lymph node metastasis (LNM).

METHODS

A cross-sectional retrospective analysis was conducted on clinical early-stage endometrial cancer cases that underwent surgical primary treatment between January 2018 and December 2022. Patient records were reviewed to gather demographics, surgical information, and pathological evaluations. Preoperative clinical staging was determined through imaging, and surgical staging involved comprehensive lymphadenectomy. Immunohistochemistry studies for p53 were carried out on formalin-fixed paraffin-embedded tissue samples.

RESULTS

A total of 233 endometrial cancer cases were included. The mean age at diagnosis was 53.7 years. Common comorbidities included hypertension (47.2%) and dyslipidemia (20.6%). Most cases were endometrioid histology (82.8%) and low-grade tumors (85.8%). Tumor grade (p=0.010), myometrial invasion (p<0.001) and lymphovascular space invasion (p<0.001) significantly correlated with lymph node metastasis. However, tumor size and p53abn were not significantly associated with lymph node metastasis. p53abn overexpression was significantly associated with non-endometrioid histology at 33% and Grade 3 tumors at 23%. Preoperative grading demonstrated moderate reliability (0.51) with postoperative grading, with an agreement of 65.4%.

CONCLUSION

Tumor grade, myometrial invasion, and LVSI were all significantly associated with lymph node involvement. While p53 immunohistochemical stains show promise in predicting metastasis and has been associated with tumor aggressiveness, this should still be correlated with clinicopathological parameters to carry out a more accurate risk stratification of early-stage patients.

Therapeutics ; Survival Rate ; Risk Factors ; Recurrence ; Prognosis ; Pathology ; Endometrial Neoplasms ; Immunohistochemistry ; Tumor Suppressor Protein P53 ; Lymph Node Excision ; Risk Assessment

BACKGROUND AND OBJECTIVES

Orthodontic tooth movement is driven by bone remodeling influenced by systemic factors, including caffeine and ethanol. This study aimed to investigate the effects of caffeine and ethanol on the expression of Receptor Activator of Nuclear Factor κβ (RANK) and Osteoprotegerin (OPG), key bone remodeling biomarkers, during orthodontic tooth movement.

METHODS

A laboratory experimental study was conducted on 30 male Wistar rats divided into three groups: K1 (orthodontic force only), K2 (force + caffeine), and K3 (force + ethanol). Orthodontic force was applied using Ni-Ti coil springs. Caffeine and ethanol were administered orally daily. On days 7 and 14, maxillary tissues were collected and analyzed via immunohistochemistry for RANK and OPG expression. Data were analyzed using One-Way ANOVA and Independent Sample T-tests with significance at pRESULTS

Caffeine and ethanol administration increased RANK and OPG expression compared to controls; however, only the ethanol group showed a significant increase in RANK expression on day 14 (p = 0.044). OPG expression was significantly higher in treatment groups at both time points (pCONCLUSION

Caffeine and ethanol modulate bone remodeling marker expression during orthodontic force application, with ethanol significantly increasing RANK expression at later stages. Further studies are needed to clarify the clinical implications for orthodontic treatment.

Animals ; Tooth Movement Techniques ; Tooth Movement ; Osteoprotegerin ; Role ; Movement ; Ethanol ; Bone Remodeling ; Caffeine ; Immunohistochemistry

Abstract Embryonal rhabdomyosarcoma (ERMS) is a primitive and aggressive soft tissue tumor that arises from premature mesenchymal cells and accounts for less than 1% of prostate malignancies. We present the case of a 26-year-old Filipino male who initially sought consultation and work-up for acute urinary retention. Although his prostate-specific antigen (PSA) level was normal, a kidney-ureter-bladder (KUB) ultrasound revealed an incidental finding of an enlarged prostate gland. Subsequent imaging tests (MRI and CT) identified a large, partially exophytic mass on the prostate with intravesical extension. The patient underwent a biopsy via transurethral resection at another institution, which yielded findings of a poorly differentiated carcinoma, primarily suggesting prostatic adenocarcinoma with a Gleason score of 10 (5+5). A request for slide review was submitted to our institution, and subsequent immunohistochemistry (IHC) studies—highlighting the tumor's immunoreactivity to myogenin and desmin—confirmed the diagnosis of ERMS. In this report, we discuss the clinical features, pathogenesis, treatment, diagnosis, and prognosis of this rare prostate tumor.
Embryonal rhabdomyosarcoma ; Immunohistochemistry ; Prostate ; Young adult

Angiomyolipoma with epithelial cysts (AMLEC) is a rare subtype of angiomyolipoma that may closely mimic both malignant and benign neoplasms. We report a case of AMLEC in an 18-year-old female presenting with acute flank pain and radiologic suspicion for malignancy. This case highlights the diagnostic challenges posed by AMLEC, emphasizes its characteristic histopathologic and immunohistochemical features, and reviews current concepts regarding its pathogenesis. This case represents the first documented case of AMLEC in the Philippines.

Human ; Angiomyolipoma ; Kidney Neoplasms ; Immunohistochemistry

OBJECTIVES: Multiple myeloma (MM) is a hematologic malignancy characterized by clonal proliferation of plasma cells and remains incurable. Patients with primary refractory multiple myeloma (PRMM) show poor response to initial induction therapy. This study aims to develop a machine learning-based model to predict treatment response in newly diagnosed multiple myeloma (NDMM) patients, in order to optimize therapeutic strategies. METHODS: NDMM and post-treatment MM patients hospitalized in the Department of Hematology, Third Xiangya Hospital, Central South University, between August 2022 and July 2023 were enrolled. Post-treatment MM patients were categorized into PRMM patients and treatment-responsive MM (TRMM) patients based on therapeutic efficacy. Serum metabolites were detected and analyzed via metabolomics. Based on the metabolomics analysis results and combined with transcriptomic sequencing data of NDMM patients from databases, differentially expressed amino acid metabolism-related genes (AAMGs) among post-treatment NDMM patients with varying therapeutic outcomes were screened. Using bioinformatics analyses and machine learning algorithms, a predictive model for treatment response in NDMM was constructed and used to identify patients at risk for PRMM. RESULTS: A total of 61 patients were included: 22 NDMM, 23 TRMM, and 16 PRMM patients. Significant differences in metabolite levels were observed among the 3 groups, with differential metabolites mainly enriched in amino acid metabolism pathways. Follow-up data were available for 16 of the 22 NDMM patients, including 12 treatment responders (ND_TR group) and 4 with PRMM (ND_PR group). A total of 23 differential metabolites were identified between these 2 groups: 6 metabolites (e.g., tryptophan) were upregulated and 17 (e.g., citric acid) were downregulated in the ND_TR group. Transcriptomic data from 108 TRMM and 77 PRMM patients were analyzed to identify differentially expressed AAMGs, which were then used to construct a prediction model. The area under the receiver operating characteristic curve (AUC) for the model exceeded 0.8, and AUC values in 3 external validation cohorts were all above 0.7. CONCLUSIONS This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.
Humans ; Multiple Myeloma/drug therapy* ; Machine Learning ; Male ; Female ; Metabolomics/methods* ; Middle Aged ; Aged ; Treatment Outcome ; Transcriptome ; Computational Biology ; Adult ; Multiomics

Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Molecular Probes ; Molecular Imaging/methods* ; Magnetic Resonance Imaging ; Positron-Emission Tomography ; Tomography, Emission-Computed, Single-Photon ; Ultrasonography ; Optical Imaging ; Biomarkers, Tumor ; Precision Medicine/methods*

Objective:To explore the effect, postoperative mucosal pathological changes and molecular biological changes of reboot operation for type 2 inflammation chronic rhinosinusitis with nasal polyps（CRSwNP） patients, and to provide theoretical basis for the clinical application of this kind of operation. Methods:We collected 29 patients who were diagnosed with CRSwNP with type 2 inflammatino response and underwent Reboot surgery from June 2022 to August 2023, and 27 patients who were diagnosed with deviated septum and underwent simple submucosal resection of the septum as the control group. We conducted nasal symptom scoring, endoscopic sinusitis scoring, and CT scanning of the sinuses before and after surgery, as well as HE staining, immunohistochemical staining, and detection of inflammatory factors using Elisa kits at the time of surgery, 1, 3, and 6 months postoperatively. We also observed the ultrastructural changes using transmission electron microscopy and scanning electron microscopy, and performed proteomic analysis of the mucosa in the ethmoid sinus area of the sinusitis patients at the time of surgery and 6 months postoperatively. Results:After 6 months of postoperative follow-up, CT scores of the nasal cavity and sinuses had gradually decreased compared with the preoperative period. The VAS score of main symptoms, SNOT-22 score and Lund-Kennedy endoscopic score were decreased after 12 months follow-up. The histological morphology of the mucosa in the area of the screen was significantly improved compared with the preoperative period, with a reduction in the number of eosinophils. The levels of inflammatory factors such as IL-4 and IL-5 et al. in the mucosa of the area of the screen were gradually reduced compared with the preoperative period. The histological morphology, ultrastructure, and cilia structure of the mucosa in the area of the screen were gradually improved compared with the preoperative period, though not recovered completely. The number of CD4⁺T and CD8⁺T cells not changed significantly before and after the surgery yet. By conducting proteomic analysis of the ethmoidal sinus mucosa before and after surgery, differential proteins were selected, and bioinformatics analysis was conducted on the differentially expressed proteins. By using cytoHubba to identify hub genes and intersecting them with the genes related to chronic sinusitis, we found that MMP9 expression increased in non-type 2 CRS and type 2 CRS in sequence, while ACTC1 expression decreased in non-tpye 2 CRS and type 2 CRS in sequence. Conclusion:Reboot surgery can improve the postoperative symptoms and signs of patients, improve the pathological morphology of the mucosa, and influence the expression of protein after surgery. However, the surgery may not have a significant impact on the distribution of T cell subpopulations and inflammation signal pathway in the nasal mucosa.
Humans ; Sinusitis/metabolism* ; Nasal Polyps/metabolism* ; Nasal Mucosa/ultrastructure* ; Chronic Disease ; Rhinitis/complications* ; Inflammation ; Male ; Female ; Postoperative Period ; Adult ; Interleukin-5/metabolism* ; Interleukin-4/metabolism* ; Middle Aged ; Proteomics ; Rhinosinusitis

Objective:Proteins are closely associated with the development, progression, and immunotherapy of head and neck squamous cell carcinoma（HNSCC）. However, few clinical models utilize proteomics to predict prognosis and immunotherapy efficacy. In this study, we developed a protein prognostic model（PPM） to stratify survival outcomes and differential immunotherapy responses in HNSCC patients. Methods:Based on proteomic profiling, we constructed a PPM comprising 11 protein markers. Patients were classified into high-and low-risk groups according to PPM scores. The prognostic value of risk scores was evaluated using Cox regression analysis, and predictive accuracy was assessed via time-dependent receiver operating characteristic（ROC） curves. Additionally, we analyzed treatment responses to PD1/CTLA4 immunotherapy in PD1-or CTLA4-positive patients across risk groups. Results:Cox regression confirmed the risk score as an independent prognostic factor（HR=1.161, 95%CI 1.112-1.213, P<0.001）, with high-risk patients exhibiting significantly poorer survival than low-risk counterparts. The model demonstrated robust predictive accuracy, with 1-year and 3-year time-dependent ROC areas under the curve（AUC） of 0.713 and 0.707, respectively. In PD1/CTLA4-positive subgroups, low-risk patients showed superior immunotherapy responses compared to high-risk patients. Conclusion:The PPM can provide reliable prognostic stratification and preliminary guidance for immunotherapy in HNSCC. However, further clinical studies and basic experiments are needed for further verification.
Humans ; Immunotherapy ; Squamous Cell Carcinoma of Head and Neck/therapy* ; Prognosis ; Head and Neck Neoplasms/genetics* ; Proteome ; Proteomics ; Gene Expression Profiling ; Transcriptome ; CTLA-4 Antigen ; Programmed Cell Death 1 Receptor ; Male ; Female ; Middle Aged

OBJECTIVES: To explore the potential of pyrroline-5-carboxylate reductase 1 (PYCR1) as a pan-cancer biomarker and investigate its expression, function, and clinical significance in bladder cancer (BLCA). METHODS: Bioinformatics analysis was conducted to evaluate the associations of PYCR1 with prognosis, immune microenvironment remodeling, tumor mutation burden (TMB), and microsatellite instability (MSI) in cancer patients. Using the TCGA-BLCA dataset, univariate and multivariate regression analyses were performed to assess the potential of PYCR1 as an independent prognostic risk factor for BLCA, and a clinical decision model was constructed. The IMvigor210 cohort was utilized to evaluate the potential of PYCR1 for independently predicting the efficacy of immunotherapy. The pRRophetic was employed to screen candidate chemotherapeutic agents for treating BLCA with high PYCR1 expression. The CMap-XSum algorithm and molecular docking techniques were used to explore and validate small molecule inhibitors of PYCR1. RESULTS: A high expression of PYCR1 was significantly associated with poor prognosis, immune cell infiltration, TMB and MSI in various tumors (r>0.3). PYCR1 was overexpressed in BLCA, and high PYCR1 expression was closely related to poor prognosis in BLCA patients (HR: 1.14, 95% CI: 1.02-1.68, P=0.006). The IC₅₀ of the anti-cancer drugs cetuximab, 5-fluorouracil, and doxorubicin increased significantly in BLCA cell lines with high PYCR1 expressions (P<0.0001). CONCLUSIONS High PYCR1 expression is an independent risk factor for poor prognosis in BLCA patients and can serve as a significant indicator for clinical decision-making as well as a marker for predicting sensitivity to chemotherapeutic agents and the efficacy of immunotherapy.
Humans ; Urinary Bladder Neoplasms/genetics* ; Immunotherapy ; Prognosis ; Pyrroline Carboxylate Reductases/metabolism* ; Biomarkers, Tumor/genetics* ; delta-1-Pyrroline-5-Carboxylate Reductase ; Microsatellite Instability ; Tumor Microenvironment ; Mutation ; Computational Biology ; Molecular Docking Simulation

OBJECTIVES: To explore the therapeutic mechanism of Arctium lappa extract for treatment of Post-Viral Pneumonia Pulmonary Fibrosis (PPF). METHODS: The chemical constituents of Arctium lappa extracts were identified using UHPLC-Q-TOF-MS/MS. Mouse models of pulmonary fibrosis established by tracheal instillation of bleomycin were treated with Arctium lappa extract, and body weight changes were recorded and lung tissue pathology was examined using HE and Masson staining. Metabolomics analysis was used to identify the differential metabolites and the associated metabolic pathways in the treated mice. The common targets of viral pneumonia and pulmonary fibrosis were acquired from the publicly available databases, and the core targets and active constituents were screened using the protein-protein interaction (PPI) network, GO and KEGG enrichment analyses, and molecular docking, and a "gene-metabolite" regulatory network was constructed. The expressions of the core targets were detected in the lung tissues of the treated mice using Western blotting. RESULTS: Fifty-three chemical constituents were identified from Arctium lappa extract. In the mouse models of pulmonary fibrosis, treatment with Arctium lappa extract significantly improved weight loss and ameliorated lung inflammation and fibrosis. The differential metabolites in the treated mice were enriched in energy metabolism pathways involving citrate cycle, pentose phosphate pathway, glycolysis, tryptophan metabolism, glutamate metabolism and glutathione metabolism, which regulated the production of energy metabolism intermediates. Twenty-three key active compounds (mostly lignans and phenolic acids) and 82 core targets were screened, which were associated with the non-canonical Smad signaling pathways (including PI3K/AKT, HIF-1, MAPK, and Foxo) that participated in the regulation of energy metabolism. Arctium lappa extract also regulated the expressions of epithelial-mesenchymal transition (EMT)‑related proteins (fibronectin, vimentim, and Snail, etc.) and inhibited MAPK signaling pathway activation. CONCLUSIONS Preliminary findings suggest that Arctium lappa treats fibrosis by regulating metabolism to inhibit EMT and involves the modulation of non-canonical Smad signaling pathways, such as MAPK providing theoretical support for its clinical application and further research in treating PPF.
Arctium/chemistry* ; Animals ; Pulmonary Fibrosis/metabolism* ; Mice ; Metabolomics ; Network Pharmacology ; Plant Extracts/pharmacology* ; Signal Transduction ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation