To elucidate the diagnostic value and clinical relevance of protein kinase D3 (PRKD3) in hepatocellular carcinoma (HCC), we analyzed data retrieved from The Cancer Genome Atlas (TCGA) database, which revealed high expression of PRKD3 in HCC tissues. Subsequently, we collected a total of 392 clinical plasma samples from healthy individuals, patients with cirrhosis or decompensated cirrhosis, and patients with HCC. Plasma PRKD3 levels were then determined across HCC patients and individuals at high risk of developing the disease. The results revealed significantly elevated PRKD3 concentrations in patients with cirrhosis, decompensated cirrhosis, and HCC compared to healthy controls (P<0.01). The areas under the receiver operating characteristic (ROC) curve for these three groups were 0.8107, 0.7899, and 0.7177, respectively. To further evaluate the efficacy of PRKD3 as an adjunctive diagnostic biomarker for HCC, we employed a panel of machine learning algorithms as primary classifiers, including extra trees (ET), gradient boosting (GB), random forest (RF), and support vector machine (SVM). A multi-parameter joint diagnostic model was constructed by combining PRKD3 expression data with a set of clinical parameters, including gender, age, total bilirubin (TBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), albumin (ALB), alpha-fetoprotein (AFP), and prothrombin induced by vitamin K absence-II (PIVKA-II). This integrated approach exhibited substantially improved diagnostic performance, achieving an accuracy of 0.861, sensitivity of 0.863, specificity of 0.925, and precision of 0.862. Collectively, these findings highlight the potential of PRKD3 as an integral component of a comprehensive diagnostic tool for the early identification of HCC.

Programmable RNA-cleaving DNAzymes (RCDs) represent a unique class of catalytic nucleic acids that couple molecular recognition with enzyme-like activity. While DNAzymes have traditionally been explored for targeted gene regulation, recent advances in nanotechnology have repositioned them as programmable biosensing modules with stimuli-responsive therapeutic potential. When integrated into metal-oxide scaffolds, DNA-framework architectures, or metal-organic frameworks, DNAzymes form hybrid platforms that create confined catalytic microenvironments, provide enriched cofactor availability, and facilitate microenvironment-responsive activation. These engineered systems can function as nanoscale biosensing modules that respond to pH, redox gradients, metal ions, or microRNA signatures and convert these biological cues into catalytic outputs. Beyond enhancing analytical performance, such platforms may also reshape tumor immunometabolism. Through the selective cleavage of metabolic or immune-regulatory transcripts, DNAzyme nanocatalysts can directly reprogram glycolysis, redox balance, oxygen tension, and mitochondrial activity, and these metabolic changes in turn alleviate immunosuppression and promote innate and adaptive immune activation. This review outlines the mechanistic foundations of DNAzyme catalysis, summarizes recent nanoengineering strategies that endow DNAzymes with programmable sensing and stimuli-responsive functions, and discusses how these systems bridge biosensing and catalytic immunometabolic functions. We conclude with perspectives on translational challenges and opportunities, endorsing programmable DNAzyme nanocatalysts as emerging preclinical platforms for biosensing-guided immunometabolic intervention.

The chemotherapy resistance genes in breast cancer are closely related to prognosis. This study is aimed at exploring the key genes that may be involved in chemotherapy resistance of breast cancer and establishing a prognostic model.

Using data from the GEO database, differentially expressed genes (DEGs) related to chemotherapy resistance in breast cancer were identified. Univariate and multivariate Cox regression were used to identify the association between DEGs and prognosis. Subsequently, functional analysis was conducted to characterize the functions of DEGs. In addition, immune-related analysis was performed to study the functions of these hub genes. LASSO-Cox regression analysis narrowed the range of hub genes. A DRFS prognostic nomogram model was constructed using the hub genes. A total of 60 breast cancer patients from the Second Affiliated Hospital of Fujian Medical University were selected as the external validation set.

By comparing the gene expression profiles of the Rx_Insensitive group and the Rx_Sensitive group, 162 DEGs were screened out, among which 53 DEGs were upregulated and 109 DEGs were downregulated. Univariate Cox regression analysis of the 162 DEGs with survival showed that GREB1, DACH1, STAP1, TDRD12, and SCGB1D2 were significantly associated with prognosis (all p < 0.05). Further multivariate Cox regression analysis revealed that GREB1 (HR = 0.653), DACH1 (HR = 1.217), STAP1 (HR = 1.140), and SCGB1D2 (HR = 1.074) were independent risk factors for prognosis (all p < 0.05). Moreover, the expression levels of GREB1, DACH1, STAP1, and SCGB1D2 were significantly correlated with the infiltration levels of various immune cells (p < 0.05). Based on these five breast cancer chemotherapy resistance-related genes, a new prognostic model for breast cancer was constructed. The 1-year AUC of this model was 0.748, 3-year AUC was 0.735, and 5-year AUC was 0.679. In the validation set, the 1-year AUC was 0.744, 3-year AUC was 0.696, and 5-year AUC was 0.650. The calibration curve showed that the predicted probabilities of the model were close to the true values. The model's prediction accuracy on the external validation set for 1 year was 0.823.

The prognostic model developed based on the five breast cancer chemotherapy resistance-related genes (GREB1, DACH1, STAP1, TDRD12, and SCGB1D2) has good predictive performance for BRCA patients.

To report the management of an advanced cutaneous squamous cell carcinoma (SCC) with parotid gland invasion, emphasizing surgical treatment with facial nerve preservation and reconstruction using a supraclavicular fasciocutaneous flap. A 64-year-old man presented with a rapidly growing ulcerated lesion in the right malar region measuring approximately 5.0 cm × 4.0 cm. Imaging suggested parotid gland involvement without regional lymph node metastasis (cT3N0M0), which was subsequently confirmed histopathologically. The patient underwent wide local excision and parotidectomy extending to the deep lobe following identification of a positive deep margin on frozen-section analysis, while preserving the facial nerve. Reconstruction was performed using a supraclavicular fasciocutaneous flap. Histopathological examination confirmed a moderately differentiated SCC with parotid gland invasion and clear surgical margins. Adjuvant radiotherapy was subsequently administered. Advanced cutaneous SCC of the face requires multidisciplinary management. Radical surgical resection with intraoperative margin assessment may allow preservation of critical structures such as the facial nerve, while the supraclavicular fasciocutaneous flap remains a reliable reconstructive option for extensive cervicofacial defects.

This study aimed to evaluate the first-line treatment patterns and prognostic factors associated with survival in patients with driver gene-negative non-small cell lung cancer (NSCLC) and liver metastases, in order to identify the optimal treatment strategy.

A Bayesian network meta-analysis was performed using R software (version 4.2.3) and RevMan (version 5.4) to systematically compare the efficacy of various first-line treatment regimens, including chemotherapy, immunotherapy, and combination therapy, in patients with driver gene-negative NSCLC with liver metastases.

A total of 20 randomized controlled trials were included. Among patients with driver gene-negative NSCLC and liver metastases: (1) PD-1 inhibitor plus chemotherapy significantly improved progression-free survival (PFS) (HR = 0.572, 95% CI: 0.435-0.754) and overall survival (OS) (HR = 0.681, 95% CI: 0.559-0.830) compared with chemotherapy alone. (2) In the patients with non-squamous NSCLC, PD-1/PD-L1 inhibitor plus chemotherapy resulted in a greater PFS benefit than chemotherapy alone. (3) A similar PFS advantage was observed in patients with squamous NSCLC receiving PD-1 inhibitor plus chemotherapy versus chemotherapy alone (HR = 0.583, 95% CI: 0.386-0.882). (4) Camrelizumab plus chemotherapy (CAM+CT) ranked highest in the network meta-analysis, with the top SUCRA values for both PFS (84.18%) and OS (96.38%).

In treatment-naive driver gene-negative NSCLC with liver metastases: PD-1 inhibitor plus chemotherapy conferred more significant PFS and OS benefits than chemotherapy alone. CAM+CT appeared to rank favorably among the evaluated regimens, particularly in patients with squamous NSCLC and liver metastases, suggesting it may represent a candidate treatment strategy. However, given that these findings were derived from a network meta-analysis based on indirect comparisons, they should be interpreted with caution.

https://www.crd.york.ac.uk/PROSPERO/view/CRD42025632364, identifier CRD42025632364.

Since the introduction of the hallmarks of cancer framework over 25 years ago, treatment approaches have evolved into personalized medicine, offering benefits to select patient populations. However, three major components of heterotypic interactions in cancer-mutational evolution of cancer stem cells, epithelial-mesenchymal plasticity (EMP), and cancer-remodeled extracellular matrix (ECM)-remain critical barriers to therapy, particularly in patients who have failed treatment. EMP encompasses a spectrum of to-and-fro transitions between mesenchymal and epithelial states, yielding hybrid phenotypes of evolutionary heterogeneity. These are embedded in the vascular, metabolic, mutational, and immune-suppressive reprogramming of the tumor microenvironment (TME), induced and advanced by the hypoxia-reactive oxygen species (ROS)-hypoxia-inducible factor-1α (HIF-1α)-transforming growth factor-β (TGF-β) signaling axis. This review systematically examines the molecular mechanisms underlying EMP, tumor heterogeneity, and the hallmarks of cancer. It explores pharmacological strategies to target tumor burden, epigenetically revert transitional states, and restore immune-editing functions. Based on this analysis, we propose a phased anti-hallmark Combinations, Timing, and Sequencing (CTS) protocol. The methodology integrates vascular normalization, epigenetic modifiers, trimodal radiotherapy or stereotactic body radiotherapy (SBRT), chemotherapy (CT), and immunotherapy optimization, aiming to improve outcomes while minimizing toxicities. Also, mechanistically, by reverting mesenchymal phenotypes and normalizing the vasculature, the CTS protocol is designed to rescue the immune-suppressive tumor microenvironment-curtailing the recruitment of myeloid-derived suppressor cells (MDSCs) and regulatory T (Treg) cells. This restores cytotoxic T-cell homing, thereby converting immunologically "cold" tumors into "hot," immunotherapy-responsive lesions.

Immunotherapy has transformed the therapeutic landscape of advanced cervical cancer, yet clinical benefit remains limited by a highly heterogeneous and immunosuppressive tumor microenvironment. Traditional paradigms, including binary M1/M2 macrophage polarization and models that interpret T-cell dysfunction solely through checkpoint expression, are insufficient to capture the localized intercellular dynamics that drive immune evasion. Recent advances in single-cell and spatial multi-omics have fundamentally reshaped our understanding of this landscape. In this review, we synthesize emerging high-dimensional atlases to reframe macrophage-T-cell crosstalk from simple ligand-receptor interactions into a spatially organized ecological model. We highlight the paradigm shift toward highly resolved myeloid programs, particularly SPP1⁺ and C1QC⁺ macrophage states, and discuss how these programs interact with stromal barriers, regulatory T cells, and metabolic checkpoints to restrict, exclude, or functionally constrain effector T cells within suppressive niches. Crucially, we position persistent high-risk human papillomavirus infection not merely as an initiating carcinogenic trigger, but as an upstream and continuous programmer that rewires innate immune sensing, including context-dependent cGAS-STING-related circuits, to stabilize local immune tolerance throughout disease progression. Finally, we propose translational strategies for distilling complex multi-omic atlases into pathology-compatible prognostic and predictive biomarker signatures. Ultimately, by deciphering these spatially organized networks, this review aims to provide actionable translational insights for targeting macrophage vulnerabilities, guiding biomarker-driven combinatorial immunotherapies, and overcoming immune resistance in cervical cancer.

A subset of cancer patients receiving monoclonal antibody PD-1/PD-L1 inhibitors may develop immune checkpoint inhibitor (ICI)-related neurological complications, such as ICI-related myasthenia gravis(MG)-myositis overlap syndrome and ICI-related myocarditis. Standard management typically involves intravenous immunoglobulin (IVIG), plasma exchange (PE), and high-dose corticosteroids. The use of efgartigimod, a neonatal Fc receptor blocker, for the treatment of ICI-related MG-myositis overlap syndrome remains investigational, with only four relevant cases all representing overlap syndromes (MG with myositis, with or without myocarditis) - reported to date.

This report examines the therapeutic effect of efgartigimod in a patient with cervical cancer who developed ICI-related MG-myositis overlap syndrome after receiving tislelizumab, an anti-PD-1 antibody.

Clinical data from the patient was collected. Relevant laboratory tests and examinations were conducted. Efgartigimod treatment was administered, and clinical severity was evaluated using standardized assessment scales.

A 69-year-old female with cervical cancer developed bilateral ptosis, dysarthria, and limb weakness following tislelizumab therapy. Examination revealed asymmetric ptosis, weak eye closure, and positive fatigability test. Serum creatine kinase was markedly elevated (553.82 U/L); electromyography showed myopathic changes with fibrillation potentials, while repetitive nerve stimulation was negative. Neostigmine test was positive, and anti-acetylcholine receptor antibodies were detected. She was diagnosed with ICI-related MG-myositis overlap syndrome. After four infusions of efgartigimod (10 mg/kg), creatine kinase normalized, the Activities of Daily Living (ADL) score decreased from 10 to 1, and the Quantitative Myasthenia Gravis (QMG) score improved from 16 to 5. The patient was asymptomatic at the 5 months follow-up with no need for a second treatment cycle.

Efgartigimod produced a positive therapeutic effect in this case with ICI-related MG-myositis overlap syndrome. The therapy was well-tolerated, and no adverse events were reported.

Prostate cancer is a common malignancy and major cause of cancer mortality among men worldwide. Early detection improves outcomes, but participation depends on awareness, perceived risk, and attitudes toward testing and diagnostic pathways. In Armenia, many cases are diagnosed at advanced stages, partly due to limited screening practices and low public awareness. This study assessed Armenian men's knowledge of prostate cancer, perception of personal risk, and attitudes toward prostate MRI within early-detection pathways, including perceived barriers to undergoing MRI.

A cross-sectional study was conducted from December 2024 to March 2025 at the Proton Diagnostic and Educational Center in Yerevan, Armenia. The study included 196 men aged ≥45 years undergoing MRI examinations unrelated to prostate conditions. Participants completed a structured 38-item questionnaire adapted from validated international surveys assessing awareness, perceived risk, screening attitudes, and barriers to MRI screening. Four perception scores were derived from Likert-scale responses. Associations between sociodemographic factors and perception scores were examined using multivariable linear regression analysis.

The mean perceived risk score was 2.95 (SD = 0.73) and the mean awareness score was 3.21 (SD = 0.72). Men aged 56-65 years had a 0.30-point higher perceived risk than those aged 45-55 years (mean difference. = 0.30; 95% CI: 0.05-0.55). Awareness was 0.32 points lower among men with secondary education or less (mean difference = -0.32; 95% CI: -0.57 to -0.07). The mean screening confidence score was 3.45 (SD = 0.81). Perceived barriers to MRI screening were higher among men with secondary education or less (mean difference = 0.39; 95% CI: 0.18-0.60) and those with vocational or technical education (adjusted mean difference = 0.40; 95% CI: 0.19-0.61) than among those with higher education.

Awareness of prostate cancer and early detection among Armenian men moderate and varied by education level. Lower educational attainment was consistently associated with lower awareness and greater perceived barriers to MRI-based diagnostic evaluation. Targeted health education and more equitable access to diagnostic services may support earlier detection and help reduce the burden of prostate cancer in Armenia.

To evaluate inflammatory-nutritional indices in relation to breast cancer (BC) risk and mortality and develop a cross-ethnically validated prediction model.

From National Health and Nutrition Examination Survey (NHANES) 2005-2018, 485 BC patients and 16,838 female controls were included, with mortality follow-up through 2019. Weighted multivariate logistic and Cox regression assessed associations between seven inflammatory indices, two composite indicators, and BC risk/mortality. Multiple machine learning (ML) algorithms, including XGBoost, were used to construct risk models. The model was externally validated (NHANES other periods:1999-2004) and cross-ethnic validated. We prospectively enrolled Chinese treatment-naïve breast cancer patients and matched healthy controls for external validation.

In fully adjusted models, the Advanced Lung Cancer Inflammation Index (ALI) was inversely associated with BC risk and all-cause mortality (highest vs. lowest tertile: odds ratio [OR] 0.64, 95% CI 0.45-0.91; hazard ratio [HR] 0.41, 95% CI 0.18-0.90). Conversely, neutrophil percentage-to-albumin ratio (NPAR), systemic inflammation response index (SIRI), and neutrophil-to-lymphocyte ratio (NLR) showed positive associations. ALI outperformed other indices in predicting mortality. XGBoost identified NPAR as the top predictive feature; the model incorporating inflammatory indices and age achieved an AUC of 0.832 on the test set, and a web-based dynamic nomogram incorporating these factors was developed. External validation yielded AUCs of 0.781 (NHANES) and 0.730 (Chinese cohort).

ALI (protective) and NPAR/SIRI/NLR (detrimental) are robust predictors of BC risk and mortality. The ML model demonstrates good predictive performance, but cross-ethnic validation highlights the need for population-specific calibration, which indicated the potential of ML approaches leveraging inflammatory-nutritional indices to enhance BC risk stratification and inform clinical decision-making.