PTPRO-related CD8+ T-cell signatures predict prognosis and immunotherapy response in patients with breast cancer

Identification of a unique stress response state of T cells-related gene signature in patients with gastric cancer

Gastric cancer (GC), the third most lethal cancer worldwide, is often diagnosed at an advanced stage, leaving limited therapeutic options. Given the diverse outcomes among GC patients with similar AJCC/UICC-TNM characteristics, there is a pressing need for more reliable prognostic tools. Recent advances in targeted therapy and immunotherapy have underscored this necessity. In this context, our study focused on a novel stress response state of T cells, termed TSTR, identified across multiple cancers, which is associated with resistance to immunotherapy. We aimed to develop a predictive gene signature for the TSTR phenotype within the tumor microenvironment (TME) of GC patients. By categorizing GC patients into high and low TSTR groups based on the infiltration states of TME TSTR cells, we observed significant differences in clinical prognosis and characteristics between the groups. Through a multi-step bioinformatics approach, we established an eight-gene signature based on genes differentially expressed between these groups. We conducted functional validations for the signature gene PDGFRL in GC cells. This gene signature effectively stratifies GC patients into high and low-risk categories, demonstrating robustness in predicting clinical outcomes. Furthermore, these risk groups exhibited distinct immune profiles, somatic mutations, and drug susceptibilities, highlighting the potential of our gene signature to enhance personalized treatment strategies in clinical practice.

Epigenetic modulations in triple-negative breast cancer: Therapeutic implications for tumor microenvironment

Triple-negative breast cancer (TNBC) is an aggressive subtype lacking estrogen receptors, progesterone receptors and lacks HER2 overexpression. This absence of critical molecular targets poses significant challenges for conventional therapies. Immunotherapy, remarkably immune checkpoint blockade, offers promise for TNBC treatment, but its efficacy remains limited. Epigenetic dysregulation, including altered DNA methylation, histone modifications, and imbalances in regulators such as BET proteins, plays a crucial role in TNBC development and resistance to treatment. Hypermethylation of tumor suppressor gene promoters and the imbalance of histone methyltransferases such as EZH2 and histone deacetylases (HDACs) profoundly influence tumor cell proliferation, survival, and metastasis. In addition, epigenetic alterations critically shape the tumor microenvironment (TME), including immune cell composition, cytokine signaling, and immune checkpoint expression, ultimately contributing to immune evasion. Targeting these epigenetic mechanisms with specific inhibitors such as EZH2 and HDAC inhibitors in combination with immunotherapy represents a compelling strategy to remodel the TME, potentially overcoming immune evasion and enhancing therapeutic outcomes in TNBC. This review aims to comprehensively elucidate the current understanding of epigenetic modulation in TNBC, its influence on the TME, and the potential of combining epigenetic therapies with immunotherapy to overcome the challenges posed by this aggressive breast cancer subtype.

New insights into immune cells in cancer immunotherapy: from epigenetic modification, metabolic modulation to cell communication

Cancer is one of the leading causes of death worldwide, and more effective ways of attacking cancer are being sought. Cancer immunotherapy is a new and effective therapeutic method after surgery, radiotherapy, chemotherapy, and targeted therapy. Cancer immunotherapy aims to kill tumor cells by stimulating or rebuilding the body's immune system, with specific efficiency and high safety. However, only few tumor patients respond to immunotherapy and due to the complex and variable characters of cancer immune escape, the behavior and regulatory mechanisms of immune cells need to be deeply explored from more dimensions. Epigenetic modifications, metabolic modulation, and cell-to-cell communication are key factors in immune cell adaptation and response to the complex tumor microenvironment. They collectively determine the state and function of immune cells through modulating gene expression, changing in energy and nutrient demands. In addition, immune cells engage in complex communication networks with other immune components, which are mediated by exosomes, cytokines, and chemokines, and are pivotal in shaping the tumor progression and therapeutic response. Understanding the interactions and combined effects of such multidimensions mechanisms in immune cell modulation is important for revealing the mechanisms of immunotherapy failure and developing new therapeutic targets and strategies.

Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer

BACKGROUND

The leading cause of death related to gynecologic cancer is ovarian cancer, which typically has a poor prognosis. T cells are referred to as key mediators of immunosurveillance and tumor eradication, and unbalanced regulation or lack of T cells in tumors result in immunotherapy resistance.

METHODS

The identification of T cell related markers depended on single-cell RNA-seq analysis. Using data from multiple datasets, including TCGA, GSE14764, GSE26193, GSE26712, and GSE140082, we constructed a prognostic signature called TRS (T cell-related signature) using 10 different machine learning algorithms. The correlation between TRS and drug sensitivity were analyzed using the data from GSE91061 and IMvigor210 dataset.

RESULTS

PlsRcox method based TRS was as a risk factor for the clinical outcome of ovarian cancer patients. In comparison with stage, grade and many prognostic signatures, the performance of our TRS in evaluating the clinical outcome was better in ovarian cancer. TRS-based risk score showed distinct association with the level of ESTIMATE score, immune-related function score and immune cells. Moreover, TRS could be used to predict the immunotherapy response and chemotherapy response in ovarian cancer.

CONCLUSION

In conclusion, we constructed a powerful TRS in ovarian cancer, which could accurately predict the clinical outcome of patients and be used to predict the immunotherapy response and chemotherapy response.

Based on whole-exome sequencing to explore the rule of Herceptin and TKI resistance in breast cancer patients

BACKGROUND

Breast cancer is the second leading cause of cancer-related death in women, and drug resistance during treatment is a major challenge. However, the mechanisms underlying drug resistance are not fully understood. Here we applied whole-exome sequencing (WES) to clarify resistant rules to Herceptin and tyrosine kinase inhibitors (TKIs).

METHODS

There are 12 HER2+ breast cancer patients who were done WES. Samples from tumor and surrounding tissues underwent DNA sequencing and analysis. Various experimental and bioinformatics techniques were employed, including genomic capture, mutation analysis (Genome Analysis Toolkit (GATK), etc.), bioinformatics assessments, and drug-gene interaction investigations. Ultimately, the study explored the association of APOB gene expression with breast cancer recurrence rates, immune cell infiltration, and drug response.

RESULTS

The C > T mutation frequency was highest in the Herceptin-insensitive (HI) and verification groups, codenamed YI, contrasting with the Herceptin-sensitive (HE) group. No microsatellite instability (MSI)-H patients were in the HE group, but both HI and YI groups had 1 each. Significant differences in transition-transversion (TiTv) were observed in the HI and YI groups rather than the HE group. In the TKI- insensitive (TI) group, C > T mutations were highest, differing from the TKI-sensitive (TE) group. TE group included 2 MSI-H patients. Significant differences in TiTv were found in the TI group rather than the TE group. Mutated APOB may resist Herceptin and TKI, increasing immune infiltration. We identified potential drugs targeting it.

CONCLUSIONS

Our study suggested that a higher percentage of C > T mutations, significant differences in TiTv, and MSI-H status may indicate Herceptin resistance, while a higher percentage of C > T mutations, significant differences in TiTv, and the absence of MSI-H may indicate TKI resistance in breast cancer patients. For patients resistant to both Herceptin and TKI, mutated APOB may play a crucial role in resistance.

Protein tyrosine phosphatase PTPRO represses lung adenocarcinoma progression by inducing mitochondria-dependent apoptosis and restraining tumor metastasis

Emerging evidence indicates that protein activities regulated by receptor protein tyrosine phosphatases (RPTPs) are crucial for a variety of cellular processes, such as proliferation, apoptosis, and immunological response. Protein tyrosine phosphatase receptor type O (PTPRO), an RPTP, has been revealed as a putative suppressor in the development of particular tumors. However, the function and the underlying mechanisms of PTPRO in regulating of lung adenocarcinoma (LUAD) are not well understood. In this view, the present work investigated the role of PTPRO in LUAD. Analysis of 90 pairs of clinical LUAD specimens revealed significantly lower PTPRO levels in LUAD compared with adjacent non-tumor tissue, as well as a negative correlation of PTPRO expression with tumor size and TNM stage. Survival analyses demonstrated that PTPRO level can help stratify the prognosis of LUAD patients. Furthermore, PTPRO overexpression was found to suppress the progression of LUAD both in vitro and in vivo by inducing cell death via mitochondria-dependent apoptosis, downregulating protein expression of molecules (Bcl-2, Bax, caspase 3, cleaved-caspase 3/9, cleaved-PARP and Bid) essential in cell survival. Additionally, PTPRO decreased LUAD migration and invasion by regulating proteins involved in the epithelial-to-mesenchymal transition (E-cadherin, N-cadherin, and Snail). Moreover, PTPRO was shown to restrain JAK2/STAT3 signaling pathways. Expression of PTPRO was negatively correlated with p-JAK2, p-STAT3, Bcl-2, and Snail levels in LUAD tumor samples. Furthermore, the anti-tumor effect of PTPRO in LUAD was significant but compromised in STAT3-deficient cells. These data support the remarkable suppressive role of PTPRO in LUAD, which may represent a viable therapeutic target for LUAD patients.

Integrated Bioinformatics Analysis to Identify a Novel Four-Gene Prognostic Model of Breast Cancer and Reveal Its Association with Immune Infiltration

Liquid-liquid phase separation (LLPS) impact immune signaling in cancer and related genes have shown prognostic value in breast cancer (BRCA). However, the crosstalk between LLPS and immune infiltration in BRCA remain unclear. Therefore, we aimed to develop a novel prognostic model of BRCA related to LLPS and immune infiltration. BRCA-related, liquid-liquid phase separation (LLPS)-related genes, and differentially expressed genes (DEGs) were identified using public databases. Mutation and drug sensitivity analyses were performed using Gene Set Cancer Analysis database. Univariate cox regression and LASSO Cox regression were used for the construction and verification of prognostic model. Kaplan-Meier analysis was performed to evaluate overall survival (OS). Gene set variation analysis was conducted to analyze key pathways. CIBERSORT was used to assess immune infiltration and its correlation with prognostic genes was determined through Pearson analysis. A total of 6056 BRCA-associated genes, 3775 LLPS-associated genes, and 4049 DEGs, resulting in 314 overlapping genes. Twenty-eight prognostic genes were screened, and some of them were mutational and related to drug sensitivity Subsequently, a prognostic model comprising L1CAM, EVL, FABP7, and CST1 was built. Patients in high-risk group had shorter OS than those in low-risk group. The infiltrating levels of CD8+ T cells, macrophages M0, macrophages M2, dendritic cells activated, and mast cells resting was altered in high-risk group of breast cancer patients compared to low-risk group. L1CAM, EVL, FABP7, and CST1 were related to these infiltrating immune cells. L1CAM, EVL, FABP7, and CST1 were potential diagnostic biomarkers and therapeutic targets for BRCA.

Study on the Relationship Between PTPRO Methylation in Plasma and Efficacy Neoadjuvant Chemotherapy in Patients with Early Breast Cancer

Objective

This study aimed to explore the correlation between PTPRO methylation in plasma and the efficacy of neoadjuvant chemotherapy (NAC) for early breast cancer (BC).

Methods

Eighty-two patients with early BC undergoing NAC were included. PTPRO methylation status in plasma before and after NAC was detected using methylation-specific PCR and the relationship between PTPRO methylation and NAC efficacy was analyzed.

Results

The rate of pathologic complete response (pCR) was only 25.0% (12/48) in patients with positive PTPRO methylation result before NAC, but 61 0.8% (21/34) in pre-NAC methylation-negative patients (OR = 0.24, 95% CI: 0.09-0.65, P = 0.005). In addition, the pCR rate was 12.1% (4/33) in patients with positive PTPRO methylation results both before and after NAC, but 53.3% (8/15) in patients with pre-NAC positive methylation and post-NAC negative methylation results (OR = 0.12, 95% CI: 0.03-0.52, P = 0.004).

Conclusion

Plasma PTPRO methylation is a potential biomarker for predicting the efficacy of NAC in early BC.

PTPRO suppresses lymph node metastasis of esophageal carcinoma by dephosphorylating MET

Protein tyrosine phosphatase receptor-type O (PTPRO) is a membrane-bound tyrosine phosphatase. Notably, epigenetically silenced PTPRO due to promoter hypermethylation is frequently linked to malignancies. In this study, we used cellular and animal models, and patient samples to demonstrate that PTPRO can suppress the metastasis of esophageal squamous cell carcinoma (ESCC). Mechanistically, PTPRO can inhibit MET-mediated metastasis by dephosphorylating Y1234/1235 in the kinase activation loop of MET. Patients with PTPRO^low/p-MET^high had significantly poor prognosis, suggesting that PTPRO^low/p-MET^high can serve as an independent prognostic factor for patients with ESCC.