Objective To investigate the effect of the small molecule inhibitor C42 of kallikrein-related peptidase 7(KLK7)on ovarian cancer with elevated expression of KLK7 and evaluate the feasibility of C42 as a new therapeutic strategy for ovarian cancer.Methods The CCK-8 assay,flow cytometry,cell scratch assay,Transwell assay,and Western blotting were employed to assess the effects of C42 on the proliferation,migration,and invasion of the ovarian cancer cell line SKOV3,which was characterized by high KLK7 expression.Additionally,a subcutaneous xenograft model of ovarian cancer was established with SKOV3 cells in nude mice to evaluate the effects of C42 on the tumor growth and metastasis.The expression levels of proteins associated with tumor metastasis and invasion in the tumor tissue were examined by immunohistochemical techniques.Results The cellular experiment showed that C42 suppressed the proliferation,migration,and invasion(all P<0.001)of SKOV3 cells,compared with the control group.The animal experiment showed that compared with the control group,the 10.2 mg/kg C42 group exhibited a decreased tumor weight(P=0.009) and attenuated liver metastases.Immunohistochemical staining revealed that the 10.2 mg/kg C42 group demonstrated down-regulated expression of the tumor proliferation marker Ki-67(P=0.002)and the tumor metastasis and invasion-associated proteins such as matrix metalloproteinase-9(P=0.027)and Vimentin(P=0.039).Conclusion The small molecule inhibitor C42 of KLK7 effectively suppresses the proliferation,migration,and invasion of ovarian cancer SKOV3 cells.

Objective To investigate the expression of SORT1 in the gastric cancer tissue and analyze its relationship with clinical prognosis of patients as well as the pathways and mechanisms involved in gastric cancer progression.Methods The Gene Expression Profiling Interaction Analysis database,Western blot,and immunohistochemistry were employed to predict and analyze the expression of SORT1 in the gastric cancer and the adjacent tissue.The clinical case information of 109 patients who underwent radical surgery for gastric cancer in the First Affiliated Hospital of Bengbu Medical University from April 2015 to April 2017 was collected to analyze the relationship of SORT1 with the clinicopathological parameters and prognosis of the patients.Cell proliferation was detected by the CCK-8 assay and colony formation assay,while cell migration and invasion were assessed by the scratch assay and Transwell assay,respectively.Western blot was employed to determine the expression of proteins related to epithelial-mesenchymal transition(EMT)in gastric cancer cells,followed by further analysis on molecular mechanism through which SORT1 regulates EMT in gastric cancer cells.Results Western blot and immunocytochemistry results showed that SORT1 was highly expressed in the gastric cancer tissue(P=0.003,P<0.001),which was positively correlated with malignant progression of tumors(all P<0.05).The Kaplan-Meier survival analysis revealed shortened postoperative survival periods for the patients with high expression of SORT1(P<0.001).The Cox regression model indicated that SORT1 expression was an independent risk factor affecting the 5-year survival rate after surgery for gastric cancer patients(P<0.001).Up-regulation of SORT1 expression promoted the proliferation,migration,invasion,and EMT of gastric cancer cells(all P<0.05),while down-regulation of SORT1 showed the opposite effects(all P<0.05).Western blot results showed that high expression of SORT1 promoted the expression of β-catenin,cyclin D1,and c-Myc(all P<0.05).Moreover,in vitro use of the Wnt/β-catenin pathway inhibitor(XAV939)effectively suppressed the EMT enhancement caused by high expression of SORT1 in gastric cancer cells(all P<0.05).Conclusions SORT1 is highly expressed in gastric cancer and affects patients' postoperative survival periods.It is involved in the proliferation,migration,and invasion of gastric cancer cells and may promote the EMT of gastric cancer cells by activating the Wnt/β-catenin pathway.

Butyric acid deficiency is implicated in polycystic ovary syndrome (PCOS), as evidenced by reduced levels in both clinical and preclinical models. Sodium butyrate (NaBu),a butyric acid substitute, has demonstrated therapeutic potential through gut-brain axis modulation, anti-inflammatory effects, and reproductive function protection. This study investigates NaBu's mechanistic role in PCOS pathophysiology.

PCOS rats received lipo-coated NaBu diet for three weeks. Systemic and tissue analyses included: serum hormone profiling, lipid metabolism assessment, ovarian/colonic histopathology, Short-chain fatty acids (SCFAs) analysis, and proteomics analysis. Primary granulosa cell cultures with lentiviral transfection elucidated molecular mechanisms. Reproductive performance was evaluated longitudinally.

Treatment with NaBu in PCOS rats resulted in reduced food intake, inhibited weight gain, improved abnormal lipid metabolism, restored estrus cycles and ovulation, lower serum levels of testosterone (T), insulin (INS), and luteinizing hormone (LH), and higher levels of estradiol (E₂) and progesterone (P₄). Additionally, NaBu treatment improved the morphology of polycystic ovaries, elevated colonic levels of G protein-coupled receptor 41 (GPR41), peptide tyrosine-tyrosine (PYY), and butyric acid, and enhanced reproductive performance in PCOS rats. Proteomic analysis and cell experiments suggested that upregulation of Cytochrome P450 1b1 (Cyp1b1) may play a crucial role in regulating E₂ metabolism and P₄ production, potentially contributing to the pathogenesis of PCOS and ovarian dysfunction.

These findings indicate that NaBu may exert its regulatory effects on appetite and hormone levels in the hypothalamus through the gut-brain-ovary axis, modulating the expression of ovarian steroidogenic factors, thereby improving follicular development and granulosa cell function, and enhancing reproductive performance.

Cancer cachexia is a complex, multifactorial syndrome characterized by severe weight loss, muscle wasting, and systemic inflammation, significantly contributing to cancer-related morbidity and mortality. Signal transducer and activator of transcription 3 (STAT3) has emerged as a central mediator in the pathogenesis of this multifactorial condition. STAT3 regulates a broad range of cellular processes including inflammation, proteolysis, and mitochondrial dysfunction across multiple tissues, particularly skeletal muscle and adipose tissue. Persistent activation of STAT3 in response to tumor-derived and host-derived cytokines drives catabolic signaling cascades, disrupts anabolic pathways, and impairs energy homeostasis. Recent studies have illuminated the cross-talk between STAT3 and other signaling pathways that exacerbate cachexia-related metabolic imbalances. These findings position STAT3 not only as a critical mediator of cachexia progression but also as a promising therapeutic target. Pharmacological inhibition of STAT3 signaling has demonstrated efficacy in preclinical models, offering potential avenues for clinical intervention. This review provides a comprehensive overview of the molecular mechanisms by which STAT3 contributes to cancer cachexia and discusses emerging therapeutic strategies aimed at modulating STAT3 activity to mitigate the progression of this debilitating syndrome.

While surgery remains the standard treatment for tongue cancer, it is associated with a range of functional and aesthetic sequelae. Additionally, ultrasound-guided microwave ablation (MWA) represents a promising minimally invasive alternative for patients with poor performance status or those unwilling to undergo surgery.

We report a 50-year-old male patient diagnosed with advanced tongue squamous cell carcinoma and cervical lymph node metastases. Microwave ablation was performed using a power setting of 30 W. Contrast-enhanced ultrasound conducted immediately afterward revealed no enhancement in the ablation area. Following the ablation, the patient received adjuvant radiotherapy and chemotherapy. During the procedure, the patient experienced minimal pain and no significant complications. After more than two years of follow-up, no evidence of metastasis or recurrence was observed, and the patient retained normal speech and swallowing functions.

Ultrasound-guided MWA combined with radiotherapy and chemotherapy offers a safe, effective, and minimally invasive approach to the treatment of advanced tongue cancer.

Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults, characterized by high mortality despite its relatively low incidence. This study aimed to utilize unsupervised learning techniques to identify a high immune infiltration subtype of UVM and improve patient stratification based on mortality risk.

A total of 70 hematoxylin and eosin (H&E) stained whole-slide images (WSIs) of UVM were collected from the Genomic Data Commons (GDC) data portal, along with genomic and clinical data. An additional validation cohort of 68 UVM patients from West China Hospital was included. Pathomic features were extracted using CellProfiler software, and deep learning models were constructed for classification and survival prediction. Unsupervised clustering was performed to identify critical regions for prognosis prediction and patient classification. The relationship between histopathological features and genomics was explored.

The study achieved accurate prediction and classification of UVM patients using deep learning models and machine learning techniques. A high immune infiltration subtype of UVM was identified, which showed prognostic relevance. Unsupervised clustering categorized UVM patients into three distinct subgroups. The developed deep learning model based on the Inception-V3 architecture demonstrated promising results in survival prediction.

This study demonstrates the potential of unsupervised learning and deep learning techniques in identifying a high immune infiltration subtype of UVM and improving patient stratification based on mortality risk. This research contributes to the field of computational pathology and highlights the potential of utilizing histopathological images, genomic data, and deep learning models in enhancing the management of UVM patients.

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive and heterogeneous malignant tumor. Mast cells are one of the immune cells widely distributed in the tumor microenvironment (TME), and their immune response with various immune cells is essential in promoting or inhibiting tumor growth and metastasis. However, the role played by mast cells in HNSCC has yet to be fully clarified.

We identified mast cell marker genes using single-cell RNA sequencing (scRNA-seq) from the GSE103322 of the GEO database. The HNSCC data from the TCGA databases was divided into training and validation groups. Cox regression and LASSO regression analyses were used to screen the prognostically relevant mast cell-related genes (MRGs) to construct a prognostic signature and differentiate risk groups. The receiver operating characteristic (ROC) and calibration curves were used to test the model's accuracy. We revealed the immune landscape of HNSCC by immune infiltration, immune checkpoint levels, ESTIMATE, and TIDE analyses. Drug sensitivity analyses were used to understand the sensitivity of different risk groups to drug therapy.

The 14-MRGs prognostic signature classified patients into high- and low-risk groups, and the overall survival (OS) of the low-risk group was significantly higher than that of the high-risk group (p < 0.05). The areas under the ROC curves of the nomogram were 0.740, 0.737 and 0.707 at 1-, 3-, and 5-year, and they also showed better detection efficacy in the validation group than other independent predictors. The low-risk group had richer immune cell infiltration and higher immune scores. The lower TIDE score in the low-risk group demonstrates that patients in this group were less prone to have immune escape and more likely to benefit from immunotherapy. In addition, the low-risk group was more sensitive to a broader range of drugs than the high-risk group.

We combined scRNA-seq data and bulk RNA-seq data to construct a 14-MRGs-based prognostic model capable of well predicting the prognosis of HNSCC patients. This model may also help identify patients who can benefit from immunotherapy.

Lymphoma is a highly heterogeneous hematologic malignancy characterized by intricate molecular and pathological mechanisms. Key mechanisms contributing to its complexity include malignant clonal evolution driven by somatic mutations, epigenetic modifications affecting gene regulation and cellular behavior, and dynamic tumor microenvironment remodeling. These factors collectively undermine the efficacy of conventional therapeutic strategies. Differences in the molecular mechanisms of different subtypes lead to heterogeneity in treatment response and recurrence of drug resistance. Current and future investigative priorities emphasize molecular stratification, precision diagnosis and therapeutic strategies, advancement of novel diagnostic tools, and the implementation of artificial intelligence (AI) for integrative analysis of high-dimensional biological data. Moreover, emerging areas such as microbiome-targeted interventions are being explored to improve clinical outcomes and support the evolution of precision oncology in lymphoma treatment.

Ovarian cancer remains the most lethal gynecologic malignancy, largely due to its late-stage diagnosis and immunosuppressive tumor microenvironment (TME). A key mediator of immune evasion in ovarian cancer is the infiltration and activation of regulatory T cells (Tregs), which suppress antitumor immunity and foster therapeutic resistance. Emerging therapeutic strategies to target Tregs-such as cytokine modulation, checkpoint blockade, metabolic inhibitors, and epigenetic regulators-are critically evaluated for their potential to restore antitumor immunity. This review synthesizes recent advances in understanding how the ovarian TME shapes Treg biology, highlighting mechanisms such as cytokine signaling, chemokine-driven recruitment, metabolic reprogramming, and immune checkpoint interactions, as well as the phenotypic and functional heterogeneity of tumor-infiltrating Tregs, including tissue-resident and follicular subsets, and their clonal expansion in response to tumor antigens. By elucidating the dynamic crosstalk between Tregs and the ovarian TME, this review provides a framework for developing novel immunotherapies to overcome Treg-mediated immunosuppression and improve clinical outcomes.

Colorectal cancer (CRC) remains a predominant contributor to cancer-related mortality globally, with its resistance to immunotherapeutic strategies presenting a formidable challenge in patient management. Recent investigations have illuminated the prospective involvement of ferroptosis, a regulated form of cell death, in both cancer progression and the development of resistance to therapeutic interventions.

This study aims to elucidate the prognostic significance of CPLX1 in CRC, specifically its correlation with immunotherapy resistance and its association with ferroptosis, thereby contributing to a deeper understanding of tumor biology and therapeutic vulnerability.

We conducted an integrative analysis of RNA-seq datasets from the TCGA-COAD and TCGA-READ projects, along with the GEO GSE156451 dataset, to discern differentially expressed genes. Expression levels of CPLX1 were evaluated utilizing the TIMER 2.0 database, and survival analyses were performed via Kaplan-Meier plots and Cox regression modeling to assess prognostic implications. Additionally, mutational analyses through cBioPortal and COSMIC datasets were employed to identify CPLX1 mutations in COAD. Co-expression and functional enrichment analyses, alongside Gene Set Enrichment Analysis (GSEA), were also conducted to delineate pathways impacted by CPLX1.

Our findings indicate that high expression levels of CPLX1 are significantly correlated with poor prognostic outcomes in CRC patients. Through immune infiltration analyses employing ssGSEA, we observed notable associations between CPLX1 expression and specific immune cell populations. Furthermore, the interaction between CPLX1 and ferroptosis-related genes suggests a potential mechanistic linkage that could underpin therapeutic resistance.

CPLX1 is identified as a novel prognostic biomarker in CRC, exhibiting clear correlations with both immunotherapy resistance and ferroptosis. These findings indicate that targeting CPLX1 may provide novel therapeutic strategies to ameliorate treatment resistance in CRC.