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As the primary component of anti-tumor immunity, T cells are prone to exhaustion and dysfunction in the tumor microenvironment (TME). A thorough understanding of T cell exhaustion (TEX) in the TME is crucial for effectively addressing TEX in clinical settings and promoting the efficacy of immune checkpoint blockade therapies. In eukaryotes, numerous cell surface proteins are tethered to the plasma membrane via Glycosylphosphatidylinositol (GPI) anchors, which play a crucial role in facilitating the proper translocation of membrane proteins. However, the available evidence is insufficient to support any additional functional involvement of GPI anchors. Here, we investigate the signature of GPI-anchor biosynthesis in the TME of breast cancer (BC)patients, particularly its correlation with TEX. GPI-anchor biosynthesis should be considered as a prognostic risk factor for BC. Patients with high GPI-anchor biosynthesis showed more severe TEX. And the levels of GPI-anchor biosynthesis in exhausted CD8 T cells was higher than normal CD8 T cells, which was not observed between malignant epithelial cells and normal mammary epithelial cells. In addition, we also found that GPI -anchor biosynthesis related genes can be used to diagnose TEX status and predict prognosis in BC patients, both the TEX diagnostic model and the prognostic model showed good AUC values. Finally, we confirmed our findings in cells and clinical samples. Knockdown of PIGU gene expression significantly reduced the proliferation rate of MDA-MB-231 and MCF-7 cell lines. Immunofluorescence results from clinical samples showed reduced aggregation of CD8 T cells in tissues with high expression of GPAA1 and PIGU.

Background: Thyroid nodules, although mostly benign and symptomless, have a small chance of being cancerous, necessitating accurate diagnosis. This study aims to develop and validate a nomogram for differentiating malignant and non-malignant thyroid nodules in individuals with type 2 diabetes. Methods: The study included 484 patients with both thyroid nodules and type 2 diabetes who underwent thyroid gland lobectomy at Wenzhou Medical University Hospital. Optimal cutoff values for continuous variables were determined using ROC curve analysis. Significant factors identified in univariable analysis were used to construct the nomogram. The monocyte-to-high-density lipoprotein cholesterol ratio (MHR) was visualized through a histogram and scatter diagram. Discriminatory power was assessed using ROC analysis, and calibration curves ensured consistency. Decision curve analysis (DCA) evaluated clinical benefits. Results: The cohort was divided into a training group (70%) and an internal validation group (30%). The scatter diagram revealed a correlation between MHR levels and the proportion of goiter cases, with higher MHR levels associated with increased goiter incidence. The histogram showed higher average MHR levels in goiter patients compared to those with papillary thyroid carcinoma (PTC) in both groups. Multivariate logistic regression identified age, total cholesterol (TC), triglyceride (TG), fasting blood sugar (FSG), fibrinogen, lymphocyte-to-monocyte ratio (LMR), and MHR as independent predictive factors for malignancy in thyroid nodules with type 2 diabetes. The nomogram achieved high discrimination, with C-index values of 0.901 (training data set) and 0.760 (internal validation data set). Calibration curves displayed good agreement, and DCA demonstrated significant net clinical benefits. Conclusions: MHR is associated with sex, serum cholesterol levels, and peripheral blood cell counts, making it a potential novel biomarker for differentiating between PTC and goiter in type 2 diabetes patients.

Human epidermal growth factor receptor 2 (HER2) plays a critical role in breast cancer progression in patients with HER2 overexpression, thereby driving the development of targeted drugs and advancing therapy strategies targeting this gene. Pyrotinib is a novel irreversible pan-ErbB kinase inhibitor, primarily suppresses the downstream MAPK and PI3K/AKT pathways. Alpelisib, a selective PI3K p110α inhibitor, has been approved for clinical application in HR+, HER2-, PIK3CA mutated breast cancers and is also being developed for use in other breast cancer subtypes. In this study, we hypothesised that combining pyrotinib with alpelisib would yield superior results compared to single-drug treatment. Our data demonstrated that the combination of alpelisib and pyrotinib exhibited a synergistic effect in HER2+ breast cancer both in vitro and in vivo. This combination led to decreased cell proliferation and migration, G0-G1 cell cycle arrest, and increased apoptosis rates. Additionally, the deactivation of ErbB receptors and sustained activation of PI3K/AKT pathway by upstream compensatory pathways induced acquired pyrotinib resistant cells resistant to pyrotinib treatment, thus alpelisib combined with pyrotinib showed a tremendous synergistic effect and reverse pyrotinib resistance in acquired pyrotinib resistant cells by suppressing the activated PI3K/AKT pathway. Our results revealed a combination of pyrotinib and alpelisib as an effective therapeutic strategy in treating HER2+ breast cancer, whether sensitive or resistant to pyrotinib treatment.

Abstract Recently some evidence has demonstrated the significance of PSMB8 in various malignancies. Nevertheless, PSMB8 (proteasome subunit beta 8), more familiar in the field of immunology contributing to the process of antigen presentation, is indeterminate in the role as a survival predictor of human pan-cancer. Besides, how PSMB8 interacts with immune cell infiltration in the tumor microenvironment requires further research. We then penetrated into the analysis of the PSMB8 expression profile among 33 types of cancer in the TCGA database. The results show that overexpression of PSMB8 was associated with poor clinical outcomes in overall survival (Sartorius et al. in Oncogene 35(22):2881–2892, 2016), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in most cancer varieties. In addition, there existed distinctly positive correlations between PSMB8 and immunity, reflected straightforwardly in the form of immune scores, tumor-infiltrating immune cells (TIICs) abundance, microsatellite instability, tumor mutation burden, and neoantigen level. Notably, specific markers of dendrite cells exhibited the tightest association with PSMB8 expression in terms of tumor-related immune infiltration patterns. Moreover, gene enrichment analysis showed that elevated PSMB8 expression was related to multiple immune-related pathways. We finally validated the PSMB8 expression in our local breast samples via quantitative PCR assays and concluded that PSMB8 appeared to perform well in predicting the survival outcome of BRCA patients. These findings elucidate the pivotal role of the antigen presentation-related gene PSMB8, which could potentially serve as a robust biomarker for prognosis determination in multiple cancers.

Breast cancer (BC) accounts for the highest proportion of the all cancers among women, and necroptosis is recognized as a form of caspase-independent programmed cell death. We created prognostic signatures using univariate survival analysis, and lasso regression, to assess immune microenvironments between subgroups. We then used network pharmacology to bind our drugs to target differentially expressed genes (DEGs). A signature comprising a set of necroptosis-related genes was established to predict patient outcomes based on median risk scores. Those above and below the median were classified as high-risk group (HRG) and low-risk group (LRG), respectively. Patients at high risk had lower overall survival, and poorer predicted tumor, nodes, and metastases stages (TNM). The novel prognostic signature can effectively predict the prognosis of breast cancer patients docking of β,β-dimethyl acryloyl shikonin (DMAS) to possible targets to cure breast cancer. We found that all current prognostic models do not offer suitable treatment options. In additional, by docking drugs DMAS that have been initially validated in our laboratory to treat breast cancer. We hope that this novel approach could contribute to cancer research.

Given the relatively poor understanding of the expression and functional effects of the N6-methyladenosine (m6A) RNA methylation on colorectal cancer (CRC), we attempted to measure its prognostic value and clinical significance. We comprehensively screened 37 m6A-related prognostic long non-coding RNAs (lncRNAs) with significant differences in expression based on 21 acknowledged regulators of m6A modification and data on 473 colorectal cancer tissues and 41 para-cancer tissues obtained from the TCGA database. Accordingly, we classified 473 CRC patients into two clusters by consensus clustering on the basis of significantly different survival outcomes. We also found a potential correlation between m6A-related prognostic lncRNAs and BRAF-KRAS expression, as well as immune cell infiltration. Then, we established a prognostic model by selecting 16 m6A-related prognostic lncRNAs via LASSO Cox analysis and grouped the CRC patients into low- and high-risk groups to calculate risk scores. Then, we performed stratified sampling to validate and confirm our model by categorising the 473 samples into a training group (N = 208) and a testing group (N = 205) in a 1:1 ratio. The survival curve showed a distinct clinical outcome in the low- and high-risk subgroups. We reconfirmed the reliability and independence of the prognostic model through various measures: risk curve, heat map and univariate and multivariate Cox analyses. To ensure that the outcomes were applicable to clinical settings, we performed stratified analyses on different clinical features, such as age, lymph node status and clinical stage. CRC patients with downregulated m6A-related gene expression, lower immune score, distant metastasis, lymph node metastasis or more advanced clinical staging had higher risk scores, indicating less-desirable outcomes. Moreover, we explored the immunology of colorectal cancer cells. The risk score showed positive correlations with eosinophils, M2 macrophages and neutrophils. In summary, our effort revealed the significance of m6A RNA methylation regulators in colorectal cancer, and the prognostic model we constructed may be used as an essential reference for predicting the outcome of CRC patients.