The phosphatase PTPN1/PTP1B is a candidate marker of better chemotherapy response in metastatic high-grade serous carcinoma

Differences in the expression of the phosphatase PTP-1B in patients with localized prostate cancer with and without adverse pathological features

Introduction

Patients with adverse pathological features (APF) at radical prostatectomy (RP) for prostate cancer (PC) are candidates for adjuvant treatment. Clinicians lack reliable markers to predict these APF preoperatively. Protein tyrosine phosphatase 1B (PTP-1B) is involved in migration and invasion of PC, and its expression could predict presence of APF. Our aim was to compare PTP-1B expression in patients with and without APF, and to explore PTP-1B expression as an independent prognostic factor.

Methods

Tissue microarrays (TMAs) were constructed using RP archival specimens for immunohistochemical staining of PTP-1B; expression was reported with a standardized score (0-9). We compared median PTP-1B score between cases with and without APF. We constructed two logistic regression models, one to identify the independence of PTP-1B score from biologically associated variables (metformin use and type 2 diabetes mellitus [T2DM]) and the second to seek independence of known risk factors (Gleason score and prostate specific antigen [PSA]).

Results

A total of 73 specimens were suitable for TMA construction. Forty-four (60%) patients had APF. The median PTP-1B score was higher in those with APF: 8 (5-9) vs 5 (3-8) (p=0.026). In the logistic regression model including T2DM and metformin use, the PTP-1B score maintained statistical significance (OR 1.21, 95% CI 1.01-1.45, p=0.037). In the model including PSA and Gleason score; the PTP-1B score showed no independence (OR 1.68, 95% CI 0.97-1.41, p=0.11). The area under the curve to predict APF for the PTP-1B score was 0.65 (95% CI 0.52-0.78, p=0.03), for PSA+Gleason 0.71 (95% CI 0.59-0.82, p=0.03), and for PSA+Gleason+PTP-1B score 0.73 (95% CI 0.61-0.84, p=0.001).

Discussion

Patients with APF after RP have a higher expression of PTP-1B than those without APF, even after adjusting for T2DM and metformin exposure. PTP-1B has a good accuracy for predicting APF but does not add to known prognostic factors.

A signature based on anoikis-related genes for the evaluation of prognosis, immunoinfiltration, mutation, and therapeutic response in ovarian cancer

Background

Ovarian cancer (OC) is a highly lethal and aggressive gynecologic cancer, with an overall survival rate that has shown little improvement over the decades. Robust models are urgently needed to distinguish high-risk cases and predict reliable treatment options for OC. Although anoikis-related genes (ARGs) have been reported to contribute to tumor growth and metastasis, their prognostic value in OC remains unknown. The purpose of this study was to construct an ARG pair (ARGP)-based prognostic signature for patients with OC and elucidate the potential mechanism underlying the involvement of ARGs in OC progression.

Methods

The RNA-sequencing and clinical information data of OC patients were obtained from The Center Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A novel algorithm based on pairwise comparison was utilized to select ARGPs, followed by the Least Absolute Shrinkage and Selection Operator Cox analysis to construct a prognostic signature. The predictive ability of the model was validated using an external dataset, a receiver operating characteristic curve, and stratification analysis. The immune microenvironment and the proportion of immune cells were analyzed in high- and low-risk OC cases using seven algorithms. Gene set enrichment analysis and weighted gene co-expression network analysis were performed to investigate the potential mechanisms of ARGs in OC occurrence and prognosis.

Results

The 19-ARGP signature was identified as an important prognostic predictor for 1-, 2-, and 3-year overall survival of patients with OC. Gene function enrichment analysis showed that the high-risk group was characterized by the infiltration of immunosuppressive cells and the enrichment of adherence-related signaling pathway, suggesting that ARGs were involved in OC progression by mediating immune escape and tumor metastasis.

Conclusion

We constructed a reliable ARGP prognostic signature of OC, and our findings suggested that ARGs exerted a vital interplay in OC immune microenvironment and therapeutic response. These insights provided valuable information regarding the molecular mechanisms underlying this disease and potential targeted therapies.

Genetic scores for predicting longevity in the Croatian oldest-old population

Longevity is a hallmark of successful ageing and a complex trait with a significant genetic component. In this study, 43 single nucleotide polymorphisms (SNPs) were chosen from the literature and genotyped in a Croatian oldest-old sample (85+ years, sample size (N) = 314), in order to determine whether any of these SNPs have a significant effect on reaching the age thresholds for longevity (90+ years, N = 212) and extreme longevity (95+ years, N = 84). The best models were selected for both survival ages using multivariate logistic regression. In the model for reaching age 90, nine SNPs explained 20% of variance for survival to that age, while the 95-year model included five SNPs accounting for 9.3% of variance. The two SNPs that showed the most significant association (p ≤ 0.01) with longevity were TERC rs16847897 and GHRHR rs2267723. Unweighted and weighted Genetic Longevity Scores (uGLS and wGLS) were calculated and their predictive power was tested. All four scores showed significant correlation with age at death (p ≤ 0.01). They also passed the ROC curve test with at least 50% predictive ability, but wGLS90 stood out as the most accurate score, with a 69% chance of accurately predicting survival to the age of 90.

Exploring the Antiovarian Cancer Mechanisms of Salvia Miltiorrhiza Bunge by Network Pharmacological Analysis and Molecular Docking

Background

Ovarian cancer was one of the gynecological malignant tumors. Salvia miltiorrhiza Bunge (SMB) was a kind of herbal medicine with an antitumor effect. However, the inhibitory effect of SMB on ovarian cancer and its potential mechanism were still unclear.

Objective

The antitumor effect of SMB on ovarian cancer was studied by network pharmacology and molecular docking techniques, and its possible molecular mechanisms were analyzed.

Method

The active ingredients of SMB and the target data of ovarian cancer were obtained from the Traditional Chinese Medicines for Systems Pharmacology Database (TCMSP) and the GeneCards database. The relationship between active ingredients of SMB and ovarian cancer targets was analyzed by String database, David 6.8 online database, and Cytoscape 3.7.2 software, and then potential pathways were screened out. In addition, molecular docking technology was used to verify further the binding effect of antiovarian cancer pathway targets with active ingredients of SMB. Finally, survival analysis was performed for all potential targets.

Results

We analyzed 71 SMB-ovarian cancer common targets, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the PI3K-Akt signaling pathway might be an essential pathway for SMB to inhibit ovarian cancer. Luteolin, Tanshinone IIA, and Cryptotanshinone in SMB might play an important role. HSP90AA1, CDK2, and PIK3CG might be potential targets of SMB in inhibiting ovarian cancer.

Conclusion

Through network pharmacology and molecular docking analysis, we found that SMB might partially inhibit ovarian cancer by the PI3K-Akt signaling pathway. We believe that SMB might be a potential therapeutic agent for ovarian cancer patients.

The role of PTP1B (PTPN1) in the prognosis of solid tumors: A meta-analysis

BACKGROUND

Protein tyrosine phosphatase 1B (PTP1B) played different role in different solid tumors, and was associated with the prognosis of solid tumors. However, the roles existed controversy. This meta-analysis was performed to determine whether PTP1B was relevant to the prognosis of solid tumors.

MATERIALS AND METHODS

A literature search in Web of Science, Embase and PubMed databases were performed up to November 1, 2021. A meta-analysis dealed with PTP1B assessment in solid tumors, providing clinical stages and survival comparisons according to the PTP1B status.

RESULTS

High PTP1B expression was significantly associated with later clinical stage of solid tumors (Odds ratio [OR] 2.25, 95% confidence interval [CI]: 1.71-2.98, P < .001). For solid tumors, the hazard ratio (HR) for disease free survival (DFS) detrimental with high PTP1B expression compared with low PTP1B expression was 1.07 (95%CI: 0.67-1.73, P = .77) with the obvious heterogeneity (P = .03, I2 = 66%). The HR of overall survival (OS) for solid tumors with high PTP1B expression versus low PTP1B expression was 1.26 (95%CI: 1.03-1.55, P = .03) with significant publication bias (t = 3.28, P = .005). Subgroup analysis indicated that the high expression of PTP1B was remarkably correlated with poor OS in colorectal carcinoma, only (HR = 1.43; 95%CI: 1.18-1.74; P = .003).

CONCLUSIONS

High PTP1B expression is significantly associated with later clinical stage of solid tumors. The high expression of PTP1B is remarkably correlated with poor OS in colorectal carcinoma, only. There is no definite conclusion that PTP1B was, or not associated with DFS and OS of solid tumors because of heterogeneity and publication bias. Whether PTP1B can be used as a biomarker for predicting the prognosis of solid tumors needs further study.