Ruijun Zhao

Background Poor immunogenicity and extensive immunosuppressive T-cell infiltration in the tumor immune microenvironment (TIME) have been identified as potential barriers to immunotherapy success in “immune-cold” breast cancers. Thus, it is crucial to identify biomarkers that can predict immunotherapy efficacy. Protein tyrosine phosphatase receptor type O (PTPRO) regulates multiple kinases and pathways and has been implied to play a regulatory role in immune cell infiltration in various cancers. Methods ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) were performed to uncover the TIME landscape. The correlation analysis of PTPRO and immune infiltration was performed to characterize the immune features of PTPRO. Univariate and multivariate Cox analyses were applied to determine the prognostic value of various variables and construct the PTPRO-related CD8 + T-cell signatures (PTSs). The Kaplan–Meier curve and the receiver operating characteristic (ROC) curve were used to estimate the performance of PTS in assessing prognosis and immunotherapy response in multiple validation datasets. Results High PTPRO expression was related to high infiltration levels of CD8 + T cells, as well as macrophages, activated dendritic cells (aDCs), tumor-infiltrating lymphocytes (TILs), and Th1 cells. Given the critical role of CD8 + T cells in the TIME, we focused on the impact of PTPRO expression on CD8 + T-cell infiltration. The prognostic PTS was then constructed using the TCGA training dataset. Further analysis showed that the PTS exhibited favorable prognostic performance in multiple validation datasets. Of note, the PTS could accurately predict the response to immune checkpoint inhibitors (ICIs). Conclusion PTPRO significantly impacts CD8 + T-cell infiltration in breast cancer, suggesting a potential role of immunomodulation. PTPRO-based PTS provides a new immune cell paradigm for prognosis, which is valuable for immunotherapy decisions in cancer patients.

Background: Protein tyrosine phosphatase non-receptor type 1 (PTPN1), a member of the protein tyrosine phosphatase superfamily, has been identified as an oncogene and therapeutic target in various cancers. However, its precise role in determining the prognosis of human cancer and immunological responses remains elusive. This study investigated the relationship between PTPN1 expression and clinical outcomes, immune infiltration, and drug sensitivity in human cancers, which will improve understanding regarding its prognostic value and immunological role in pan-cancer. Methods: The PTPN1 expression profile was obtained from The Cancer Genome Atlas and Cancer Cell Line Encyclopedia databases. Kaplan-Meier, univariate Cox regression, and time-dependent receiver operating characteristic curve analyses were utilized to clarify the relationship between PTPN1 expression and the prognosis of pan-cancer patients. The relationships between PTPN1 expression and the presence of tumor-infiltrated immune cells were analyzed using Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data and Tumor Immune Estimation Resource. The cell counting kit-8 (CCK-8) assay was performed to examine the effects of PTPN1 level on the sensitivity of breast cancer cells to paclitaxel. Immunohistochemistry and immunoblotting were used to investigate the relationship between PTPN1 expression, immune cell infiltration, and immune checkpoint gene expression in human breast cancer tissues and a mouse xenograft model. Results: The pan-cancer analysis revealed that PTPN1 was frequently up-regulated in various cancers. High PTPN1 expression was associated with poor prognosis in most cancers. Furthermore, PTPN1 expression correlated highly with the presence of tumor-infiltrating immune cells and the expression of immune checkpoint pathway marker genes in different cancers. Furthermore, PTPN1 significantly predicted the prognosis for patients undergoing immunotherapy. The results of the CCK-8 viability assay revealed that PTPN1 knockdown increased the sensitivity of MDA-MB-231 and MCF-7 cells to paclitaxel. Finally, our results demonstrated that PTPN1 was associated with immune infiltration and immune checkpoint gene expression in breast cancer. Conclusion: PTPN1 was overexpressed in multiple cancer types and correlated with the clinical outcome and tumor immunity, suggesting it could be a valuable potential prognostic and immunological biomarker for pan-cancer.

Purpose: Breast cancer is the most common type of cancer and the leading cause of cancer-related death in women worldwide. In this study, we aimed to construct an inflammatory response-related gene model for predicting the immune status and prognosis of breast cancer patients. Methods: We obtained the inflammatory response-related genes from the Molecular Signatures Database. Furthermore, we used univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression to construct an inflammatory response-related gene signature (IRGS) model based on dataset obtained from The Cancer Genome Atlas (TCGA). Patients were consequently categorized into high-risk and low-risk groups. Kaplan-Meier analysis was used to compare the overall survival (OS) of high-risk and low-risk groups. Following that, we validated the model using a dataset (GSE96058) acquired from Gene Expression Omnibus (GEO) database. Univariate and multivariate Cox analyses were used to determine the independent prognostic value of the IRGS in the TCGA and GSE96058 cohorts. A nomogram was constructed to predict the OS in the TCGA cohort. Further, we used Gene Set Enrichment Analysis (GSEA), CIBERSORT, and single-sample Gene Set Enrichment Analysis (ssGSEA) to evaluate the associations of IRGS with immune-associated pathways and immune infiltration. Finally, the relationship between the expression of the signature genes and drug sensitivity was conducted using Pearson correlation analysis. Results: We established an IRGS to stratify breast cancer patients into the low-risk and high-risk groups. In both the training and validation sets, patients in the high-risk group had significantly shorter OS than those in the low-risk group. The risk score was significantly correlated with the clinical characteristics and could be used as a tool to predict the prognosis of breast cancer. Moreover, we found that the IRGS risk score was an independent predictor of OS in breast cancer patients, and a nomogram model based on IRGS risk score and other clinical factors could effectively predict the prognosis of breast cancer patients. Furthermore, the IRGS risk score was correlated with immune characteristics and was inversely associated with the abundance of immune cell infiltration. Patients with a low IRGS risk score had higher expression levels of immune checkpoint genes, suggesting that IRGS can be used as a potential indicator for immunotherapy. Finally, we found that the expression levels of prognostic genes were significantly correlated with tumor cell sensitivity to chemotherapeutic drugs. Conclusion: Overall, these findings suggest that the IRGS can be used to predict the prognosis and immune status of breast cancer patients and provide new therapeutic targets for the treatment of these patients.

Breast cancer heterogeneity is not only involved by genetic and epigenetic alterations, but may also associated with the complexities at levels of protein modifications. Estrogen receptor (ER) positive breast cancer constitutes approximately 70% of all breast cancer cases, significantly impacting global female morbidity and mortality. Nuclear receptor co-activator 6 (NCOA6, also referred as AIB3) is a coregulator of sex hormone receptors as well as other transcription factors. Although the expression and functions of NCOA6 have been studied in breast, colon, lung, pancreatic cancers, and hepatocellular carcinoma, post-tranlational modification of NCOA6 is barely known. This study aims to study the NCOA6 phosphorylation, in particular at Serine 884, and its relevance to breast tumor aggressiveness and the prognostic significance. We used bioinformatics and immunohistochemistry to detect NCOA6 expression and Ser884 phosphorylation in ER-positive breast cancer tissues. Cell proliferation, migration, and invasion were measured using CCK-8, transwell, and wound healing assays. Immunoblotting was used to detect protein levels and phosphorylation. Mouse xenograft models were established to evaluate tumor growth in vivo. Transcriptome and proteome analyses were performed to identify related signaling pathways. Total NCOA6 expression was not linked to cancer stage, subtype, or prognosis. However, phosphorylation at Ser884 was significantly increased in ER-positive breast cancer and associated with poorer outcomes, indicating its potential as an independent prognostic marker. Functional studies demonstrated that Ser884 phosphorylation promoted tumor cell proliferation, migration, and invasion in vitro and enhanced tumor growth in vivo. Mechanistically, ERK2 activation induced NCOA6 phosphorylation at Ser884, promoting epithelial-mesenchymal transition (EMT) and metastatic behavior. Only the phosphomimetic S884E mutant, not the non-phosphorylatable S884F mutant, restored migration and invasion in NCOA6-deficient cells. Transcriptomic and proteomic analyses further suggested that NCOA6 influences cell cycle, PI3K/AKT/mTOR signaling, and protein synthesis. Phosphorylation of NCOA6 at Ser884 is markedly increased in ER-positive breast cancer, associates with aggressive clinicopathologic features, and portends poor prognosis. Functionally, enhanced NCOA6 phosphorylation promotes invasion and metastasis of ER-positive breast cancer cells. Collectively, these findings identify phospho-NCOA6 (Ser884) as a promising prognostic biomarker and potential therapeutic target, supporting more personalized management of ER-positive disease.

Breast cancer is a prevalent and deadly disease affecting women worldwide. Recent studies have shown that γ-glutamyl cyclotransferase (GGCT), an enzyme involved in glutathione metabolism, is consistently upregulated in various cancers. However, its specific role in breast cancer remains poorly understood. This study aimed to investigate the functional role of GGCT in breast cancer. Bioinformatics, immunohistochemistry and immunoblotting analysis revealed that GGCT is significantly upregulated in breast cancer tissues, and its high expression is associated with poor survival outcomes. The knockdown of GGCT significantly suppressed MCF-7 and SKBR-3 cell activities. Cell proliferation decreased by 29.4-45.9%, and colony formation reduced by 51.5-56.6%. Migratory ability diminished by 36.8-49.1%, while invasion capability declined by 35.2-55.0%. Moreover, GGCT silencing reduced epithelial-mesenchymal transition (EMT) and inhibited the PI3K/AKT/mTOR signaling pathway. Notably, E-cadherin expression significantly increased in MCF-7 and SKBR-3-shGGCT cells, with changes ranging from 2.1-fold to 5.4-fold. Conversely, N-cadherin expression decreased by 54.2-84.2% in both cell lines. Vimentin expression also decreased significantly, with reductions of 58.8-83.0%. Further analyses indicated that p-AKT expression in MCF-7 and SKBR-3-shGGCT cells decreased by 51.4-84.8%. Additionally, p-mTOR expression was reduced by 71.2-87.2% in both cell lines, compared to shCtrl. Our data highlights the crucial role of GGCT in regulating EMT and the progression of breast cancer. The findings suggest that GGCT not only serves as a valuable prognostic marker but also represents a potential target for therapeutic interventions in breast cancer patients.