The prognostic value of the hemoglobin/red blood cell distribution width ratio in primary hepatocellular carcinoma remains unknown. This study aimed to analyze the correlation between hemoglobin/red blood cell distribution width ratio and hepatocellular carcinoma prognosis. Medical records of hepatocellular carcinoma patients were analyzed retrospectively. The hemoglobin/red blood cell distribution width ratio cut-off value was determined as 0.987 by receiver operating characteristic curve analysis. Patients were divided into high- and low-level groups, and the clinical data were compared. The correlation among the ratio levels, progression-free survival, and overall survival was measured with univariate and multivariate Cox regression analyses. The prognostic utility of the ratio combined with alpha-fetoprotein was analyzed using Kaplan-Meier survival curves and log-rank detection, and the correlation between the ratio and tumor staging was studied using one-way analysis of variance. This study included 252 patients. Sex, smoking and alcohol consumption history, body mass index, surgery, staging, platelet/lymphocyte ratio, and hemoglobin/red blood cell distribution width ratio were associated with progression-free and overall survival (P<0.05). The ratio, alpha-fetoprotein, hemoglobin, staging, and surgery were independent risk factors for progression-free survival (P<0.05), and the ratio, alpha-fetoprotein, hemoglobin, body mass index, HBsAg, staging, and surgery were independent risk factors for overall survival (P<0.05). Patients with low ratio levels and high alpha-fetoprotein levels had the worst prognosis. Low hemoglobin/red blood cell distribution width ratio levels are associated with poor patient prognosis and are potential tumor prognosis markers.

Purpose: Heat shock protein 90α (HSP90α) is highly expressed in tumors, and predicts tumor progression. This study analyzed the correlation between the expression level of HSP90α in the serum and the prognosis of patients with lung adenocarcinoma. Patients and methods: The medical records of patients with 228 lung adenocarcinoma from September 2015 to December 2021 were analyzed. HSP90α expression in the patients’ serum was detected by ELISA and the cut-off value (93.76 ng/mL) was determined according to the ROC curve, then the patients were divided into high- and low-level groups. The differences in the medical records of the two groups were compared using the X² test, and Univariate and multivariate Cox regression analyses showed that serum HSP90α level were independent risk factors for both PFS and OS (P < 0.05). Results: HSP90α was positively correlated with TNM staging (P < 0.01) by One-way analysis of variance. The results of the correlation analysis and the Kaplan–Meier survival curve showed that the expression levels of HSP90α and CEA of patients were positively correlated (R=0.54, P < 0.001), and patients with high HSP90α and CEA levels had the worst OS (P < 0.001). Conclusion: HSP90α expression is negatively correlated with the prognosis of patients with lung adenocarcinoma and is a potential prognostic marker.

Background: Radiation therapy is an important treatment method for non-small-cell lung cancer (NSCLC). However, predicting patient prognosis remains challenging due to considerable interpatient heterogeneity. The TP53 signaling pathway, implicated in tumor radiosensitivity and treatment outcomes, represents a promising predictive biomarker. Accordingly, in this study, we aimed to identify TP53-signaling pathway-related genes and develop a novel prognostic model for risk stratification for NSCLC patients undergoing radiation therapy. Methods: Publicly available NSCLC transcriptomic datasets were obtained from the GEO and TCGA databases. Utilizing bioinformatics approaches, we identified differentially expressed genes (DEGs) associated with the TP53 signaling pathway. Feature selection was performed using LASSO regression, followed by the construction of a multivariate-Cox-regression-based prognostic prediction model. In vitro validation was performed using a cell viability assay, colony formation, cell cycle analysis, apoptosis detection, γH2AX immunofluorescence staining and comet electrophoresis. In vivo validation was performed utilizing a subcutaneous tumor-bearing mouse model, where radiosensitivity was assessed by monitoring tumor volume post-irradiation. Results: We constructed a robust prognostic prediction model based on five TP53-signaling-pathway-related genes (MDM2, THBS1, TP53I3, ATM, and SESN3), achieving a 5-year AUC of 0.828 in the training set and a 3-year AUC of 0.824 in the validation set. The model exhibited a significant ability to stratify patients into distinct high- and low-risk groups, demonstrating good predictive performance. The poor prognosis observed in the high-risk group was associated with lower infiltration of anti-tumor immune cells but higher infiltration of immunosuppressive cells. Both in vitro and in vivo experiments demonstrated that TP53I3 knockdown significantly enhanced the radiosensitivity of NSCLC through increased DNA damage, cell cycle arrest and apoptosis. Conclusions: In this study, a five-gene signature derived from the TP53 signaling pathway was developed, and the model was shown to effectively predict the prognoses of NSCLC patients undergoing radiotherapy. This signature has the potential to be developed into a clinically applicable tool for personalizing radiotherapy regimens for NSCLC.

Background: Serpin B9 is highly expressed in breast cancer, melanoma, and various malignant cells and inhibits NK cell killing through the Serpin B9-GrB axle. However, the current studies have only validated the role of Serpin B9 in vivo and vitro, and lack of systematic studies on the expression of Serpin B9 in patients’ tumor tissues and its prognostic implications. In this study, we propose to further validate the role of Serpin B9 by comparing its expression level in tissues of lung adenocarcinoma patients and its correlation with the efficacy of immunotherapy. Methods: This study included 200 patients with LUAD between Feb 2022 and Feb 2023. IHC scoring assessed Serpin B9 expression in the tumor and adjacent tissues, with an H-score of 2 as the cutoff value. Patients were divided into high- and low-expression groups. T-tests were used to compare Serpin B9 expression and treatment efficacy between the tumor and adjacent tissues in both groups. Baseline characteristics were compared using X2 tests. Prognostic risk factors were identified using Cox regression and Kaplan-Meier survival curves. Results: The expression level of Serpin B9 in LUAD tumor tissues are higher than adjacent tissues and positively correlated with the TNM stage and negative correlated with PFS in patients with LUAD. Additionally, immunotherapy efficacy was inversely correlated with Serpin B9 expression. Conclusion: The increased expression of Serpin B9 in LUAD tumor tissues is negatively linked to prognosis and immunotherapy efficacy. This underscores their potential as prognostic and therapeutic targets.

Quantitative surface‐enhanced Raman spectroscopy (SERS) has long been impeded by stochastic hotspot formation, signal instability, and limited chemical fidelity in complex environments. Overcoming these intrinsic limitations requires structural control at the nanoscale rather than incremental improvements in signal amplification. Here, we introduce a mesoporous‐shell monolayer plasmonic architecture that enables quantitative and decision‐guided SERS by integrating deterministic hotspot geometry with regulated molecular accessibility and chemical stabilization of photosensitive analytes. This architecture produces predictable and reproducible SERS responses, shifting SERS from stochastic enhancement toward quantitative sensing. Using chemotherapeutic drugs as representative small‐molecule targets, the platform demonstrates ultrasensitive, multiplexed, and reproducible detection in standard solutions and complex biological matrices. Machine learning–assisted spectral analysis further enables accurate concentration prediction in patient blood samples in close agreement with liquid chromatography–mass spectrometry. Importantly, SERS‐guided dose adjustment in an orthotopic breast cancer mouse model maintains therapeutic efficacy while significantly reducing systemic toxicity, establishing a direct link between plasmonic sensing and decision‐guided intervention. This work defines a materials‐based framework for quantitative and decision‐enabled SERS, in which mesoporous‐shell monolayer architectures transform plasmonic nanostructures into functional platforms for real‐world molecular quantification and feedback‐controlled biomedical applications.