Protein tyrosine phosphatase 4A2 expression predicts overall and disease-free survival of human breast cancer and is associated with estrogen and progestin receptor status

A Radiosensitivity Prediction Model Developed Based on Weighted Correlation Network Analysis of Hypoxia Genes for Lower-Grade Glioma

Background and Purpose

Hypoxia is one of the basic characteristics of the physical microenvironment of solid tumors. The relationship between radiotherapy and hypoxia is complex. However, there is no radiosensitivity prediction model based on hypoxia genes. We attempted to construct a radiosensitivity prediction model developed based on hypoxia genes for lower-grade glioma (LGG) by using weighted correlation network analysis (WGCNA) and least absolute shrinkage and selection operator (Lasso).

Methods

In this research, radiotherapy-related module genes were selected after WGCNA. Then, Lasso was performed to select genes in patients who received radiotherapy. Finally, 12 genes (AGK, ETV4, PARD6A, PTP4A2, RIOK3, SIGMAR1, SLC34A2, SMURF1, STK33, TCEAL1, TFPI, and UROS) were included in the model. A radiosensitivity-related risk score model was established based on the overall rate of The Cancer Genome Atlas (TCGA) dataset in patients who received radiotherapy. The model was validated in TCGA dataset and two Chinese Glioma Genome Atlas (CGGA) datasets. A novel nomogram was developed to predict the overall survival of LGG patients.

Results

We developed and verified a radiosensitivity-related risk score model based on hypoxia genes. The radiosensitivity-related risk score served as an independent prognostic indicator. This radiosensitivity-related risk score model has prognostic prediction ability. Moreover, a nomogram integrating risk score with age and tumor grade was established to perform better for predicting 1-, 3-, and 5-year survival rates.

Conclusions

We developed and validated a radiosensitivity prediction model that can be used by clinicians and researchers to predict patient survival rates and achieve personalized treatment of LGG.

Downregulated Expression of miRNA-130a-5p Aggravates Hepatoma Progression via Targeting PTP4A2

Background

Hepatoma is a leading cause of death worldwide, with high metastasis and recurrence rates. The aberrant expression of miRNA-130a-5p is involved in the development and progression of various cancers. However, there are no studies investigating the role of miRNA-130a-5p in hepatoma. The present study is aimed at clarifying the functional role of miRNA-130a-5p in hepatoma progression.

Methods

The expression levels of miRNA-130a-5p in hepatoma tissues and cell lines were detected by qRT-PCR assays. Bioinformatic analysis, gain-/loss-of-function experiments, and luciferase activity assays were conducted to verify whether miRNA-130a-5p is targeted by protein tyrosine phosphatase 4A2 (PTP4A2). The functions of miRNA-130a-5p and PTP4A2 in hepatoma were determined by cell proliferation assays.

Results

The expression of miRNA-130a-5p was downregulated in hepatoma tissues and was related to poor prognosis. However, the expression level of PTP4A2 was contradictory to that of miRNA-130a-5p, and PTP4A2 upregulation could aggravate hepatoma progression. The ectopic overexpression of PTP4A2 promoted hepatoma cell proliferation in vitro, which could be reversed by miRNA-130a-5p.

Conclusions

Our study implies that miRNA-130a-5p, which is downregulated in hepatoma tissues, can suppress hepatoma cell proliferation via targeting PTP4A2.

Circular RNA hsa_circ_0007364 increases cervical cancer progression through activating methionine adenosyltransferase II alpha (MAT2A) expression by restraining microRNA-101-5p

Emerging evidence suggested that circular RNAs (circRNAs) play critical roles in cervical cancer (CC) progression. However, the roles and molecular mechanisms of hsa_circ_0007364 in the tumorigenesis of CC remain unclear. In the present study, we used bioinformatics analysis and a series of experimental analysis to characterize a novel circRNA, hsa_circ_0007364 was up-regulated and associated with advanced clinical features in CC patients. Hsa_circ_0007364 inhibition notably suppressed the proliferation and invasion abilities of CC cells in vitro and reduced tumor growth in vivo. Moreover, hsa_circ_0007364 was uncovered to sponge miR-101-5p. Additionally, methionine adenosyltransferase II alpha (MAT2A) was verified as a target gene of miR-101-5p, and its downregulation reversed the inhibitory effects of hsa_circ_0007364 knockdown on CC progression. Therefore, we suggested that hsa_circ_0007364 might serve as an oncogenic circRNA in CC progression by regulating the miR-101-5p/MAT2A axis, which provides a potential therapeutic target to the treatment. Research highlights hsa_circ_0007364 was upregulated in CC hsa_circ_0007364 promoted CC cell progression hsa_circ_0007364/miR-101-5p/MAT2A axis in CC.

PRL2 serves as a negative regulator in cell adaptation to oxidative stress

High levels of ROS cause oxidative stress, which plays a critical role in cell death. As a ROS effector protein, PRL2 senses ROS and controls phagocyte bactericidal activity during infection. Here we report PRL2 regulates oxidative stress induced cell death. PRL2 senses oxidative stress via highly reactive cysteine residues at 46 and 101. The oxidation of PRL2 causes protein degradation and supports pro-survival PDK1/AKT signal which in turn to protect cells against oxidative stress. As a result, PRL2 levels have a high correlation with oxidative stress induced cell death. In vivo experiments showed PRL2 deficient cells survive better in inflammatory oxidative environment and resist to ionizing radiation. Our finding suggests PRL2 serves as a negative regulator in cell adaptation to oxidative stress. Therefore, PRL2 could be targeted to modulate cell viability in inflammation or irradiation associated therapy.

Relationships of protein biomarkers of the urokinase plasminogen activator system with expression of their cognate genes in primary breast carcinomas

Background

uPA, its receptor uPAR, and inhibitors PAI‐1 and PAI‐2 play key roles in membrane remodeling/invasion and in predicting response to chemotherapy. We identified novel relationships of these biomarkers with ER/PR that indicate clinical utility for assessing breast carcinoma outcomes.

Methods

Retrospective studies were performed with de‐identified results of (a) uPA, uPAR, and PAI‐1; (b) estrogen (ER) and progestin receptor (PR); and (c) clinical outcomes. Relative expression of 22 000 genes from microarray of RNA from LCM‐procured breast cancer cells was used with R Studio version 3.4.1.

Results

Primary ER/PR status was related to uPA, uPAR, or PAI‐1 levels. ER− or PR− cancers expressed elevated uPA, uPAR, and PAI2 mRNA compared to ER+ or PR+ cells. Inverse relationships between ER/PR protein and expression of uPA, uPAR, and PAI‐2 were observed, whereas HER2 status was unrelated. qPCR analyses showed RERG and NQO‐1 expressions were elevated in uPA− lesions, while CD34 and EDG‐1 were elevated in uPAR− cancers. ERBB4 was overexpressed in PAI‐1+ carcinomas. Cox regression analyses revealed relationships of ER/PR status and uPA system members with regard to clinical outcomes of breast cancer.

Conclusions

uPA, uPAR, PAI1, or PAI2 expression was increased in either ER− or PR− cancers similar to that of protein content in ER−/PR− carcinomas, suggesting sex hormones regulate the uPA system in breast cancer. Results revealed protein content of uPA system members was related to ER/PR status of primary lesions. Use of LCM‐procured carcinoma cells uncovered relationships between expression of known cancer−associated genes and protein content of uPA system members. Collectively, results indicate evaluation of ER and PR protein of primary breast cancers combined with analyses of uPA, uPAR, and PAI‐1 protein content improves assessment of clinical outcomes.

Construction of a novel multi-gene assay (42-gene classifier) for prediction of late recurrence in ER-positive breast cancer patients

PURPOSE

Prediction models for late (> 5 years) recurrence in ER-positive breast cancer need to be developed for the accurate selection of patients for extended hormonal therapy. We attempted to develop such a prediction model focusing on the differences in gene expression between breast cancers with early and late recurrence.

METHODS

For the training set, 779 ER-positive breast cancers treated with tamoxifen alone for 5 years were selected from the databases (GSE6532, GSE12093, GSE17705, and GSE26971). For the validation set, 221 ER-positive breast cancers treated with adjuvant hormonal therapy for 5 years with or without chemotherapy at our hospital were included. Gene expression was assayed by DNA microarray analysis (Affymetrix U133 plus 2.0).

RESULTS

With the 42 genes differentially expressed in early and late recurrence breast cancers in the training set, a prediction model (42GC) for late recurrence was constructed. The patients classified by 42GC into the late recurrence-like group showed a significantly (P = 0.006) higher late recurrence rate as expected but a significantly (P = 1.62 × E-13) lower rate for early recurrence than non-late recurrence-like group. These observations were confirmed for the validation set, i.e., P = 0.020 for late recurrence and P = 5.70 × E-5 for early recurrence.

CONCLUSION

We developed a unique prediction model (42GC) for late recurrence by focusing on the biological differences between breast cancers with early and late recurrence. Interestingly, patients in the late recurrence-like group by 42GC were at low risk for early recurrence.

Over-expression of protein tyrosine phosphatase 4A2 correlates with tumor progression and poor prognosis in nasopharyngeal carcinoma

Protein tyrosine phosphatase 4A2 (PTP4A2) has been implicated as an oncogenic protein in several human cancers. However, the level of PTP4A2 expression and its prognostic significance in nasopharyngeal carcinoma (NPC) remains unknown. In this study, Western blotting (WB), quantitative real-time PCR (qT-PCR) and immunohischemistry (IHC) was applied to evaluated the expression levels of PTP4A2 in NPC cell lines and tumor tissues combining two independent cohorts. Receiver-operator curve (ROC) analysis was used to assessed the optimal cut-off score in training cohort (266 cases). This cut-off score was subjected to determine the association of PTP4A2 expression with patients’ clinical characteristics and survival outcome in the validation cohort (201 cases) and the overall population (467 cases). We found that PTP4A2 were significantly overexpressed in NPC cell lines compared with normal nasopharyngeal epithelial cell. Moreover, overexpression of PTP4A2 was positively correlated with advanced T classification (P<0.001) and TNM stages (P<0.001). And higher PTP4A2 expression was an independent prognostic factor for adverse overall survival (P<0.05) and poor disease-free survival (P<0.05). Our results demonstrated that the overexpression of PTP4A2 was closely associated with poor survival outcome in patients with NPC and may represent a novel prognostic biomarker and therapeutic target for this disease.

Clinical outcomes linked to expression of gene subsets for protein hormones and their cognate receptors from LCM-procured breast carcinoma cells

PURPOSE

Certain peptide hormones and/or their cognate receptors influencing normal cellular pathways also have been detected in breast cancers. The hypothesis is that gene subsets of these regulatory molecules predict risk of breast carcinoma recurrence in patients with primary disease.

METHODS

Gene expression levels of 61 hormones and 81 receptors were determined by microarray with LCM-procured carcinoma cells of 247 de-identified biopsies. Univariable and multivariable Cox regressions were determined using expression levels of each hormone/receptor gene, individually or as a pair.

RESULTS

Molecular signatures for ER+/PR+, ER-/PR-, and ER- carcinoma cells deciphered by LASSO were externally validated at HRs (CI) of 2.8 (1.84-4.4), 1.53 (1.01-2.3), and 1.72 (1.15-2.56), respectively. Using LCM-procured breast carcinoma cells, a 16-gene molecular signature was derived for ER+/PR+ biopsies, whereas a 10-gene signature was deciphered for ER-/PR- cancers. Four genes, POMC, CALCR, AVPR1A, and GH1, of this 10-gene signature were identified in a 6-gene molecular signature for ER- specimens.

CONCLUSIONS

Applying these signatures, Kaplan-Meier plots definitively identified a cohort of patients with either ER-/PR- or ER- carcinomas that exhibited low risk of recurrence. In contrast, the ER+/PR+ signature identified a cohort of patients with high risk of breast cancer recurrence. Each of the three molecular signatures predicted clinical outcomes of breast cancer patients with greater accuracy than observed with either single-gene analysis or by ER/PR protein content alone. Collectively, our results suggest that gene expression profiles of breast carcinomas with suspected poor prognosis (ER-/PR-) have identified a subset of patients with decreased risk of recurrence.

Discovering Pair-wise Synergies in Microarray Data

Informative gene selection can have important implications for the improvement of cancer diagnosis and the identification of new drug targets. Individual-gene-ranking methods ignore interactions between genes. Furthermore, popular pair-wise gene evaluation methods, e.g. TSP and TSG, are helpless for discovering pair-wise interactions. Several efforts to discover pair-wise synergy have been made based on the information approach, such as EMBP and FeatKNN. However, the methods which are employed to estimate mutual information, e.g. binarization, histogram-based and KNN estimators, depend on known data or domain characteristics. Recently, Reshef et al. proposed a novel maximal information coefficient (MIC) measure to capture a wide range of associations between two variables that has the property of generality. An extension from MIC(X; Y) to MIC(X₁; X₂; Y) is therefore desired. We developed an approximation algorithm for estimating MIC(X₁; X₂; Y) where Y is a discrete variable. MIC(X₁; X₂; Y) is employed to detect pair-wise synergy in simulation and cancer microarray data. The results indicate that MIC(X₁; X₂; Y) also has the property of generality. It can discover synergic genes that are undetectable by reference feature selection methods such as MIC(X; Y) and TSG. Synergic genes can distinguish different phenotypes. Finally, the biological relevance of these synergic genes is validated with GO annotation and OUgene database.

The prognostic significance of protein tyrosine phosphatase 4A2 in breast cancer

Although PTP4A3 has been shown to be a very important factor in promoting cancer progression, the role of its close family member PTP4A2 is still largely unknown. Recent reports have shown contradicting results on the role of PTP4A2 in breast cancer progression. Considering this, we aimed to investigate the prognostic value of PTP4A2 in five independent breast cancer data sets (minimum 198 patients per cohort, totaling 1,124 patients) in the Gene Expression Omnibus Database. We found that high expression of PTP4A2 was a favorable prognostic marker in all five independent breast cancer data sets, as well as in the combined cohort, with a hazard ratio of 0.68 (95% confidence interval =0.56–0.83; P<0.001). Low PTP4A2 expression was associated with estrogen receptor-negative tumors and tumors with higher histological grading; furthermore, low expression was inversely correlated with the expression of genes involved in proliferation, including MKI67 and the MCM gene family encoding the minichromosome maintenance proteins. These findings suggest that PTP4A2 may play a role in breast cancer progression by dysregulating cell proliferation. PTP4A2 expression was positively correlated with ESR1, the gene encoding estrogen receptor-alpha, and inversely correlated with EGFR expression, suggesting that PTP4A2 may be involved in these two important oncogenic pathways. Together, our results suggest that expression of PTP4A2 is a favorable prognostic marker in breast cancer.

Molecular characterization of adipose tissue in the African elephant (Loxodonta africana)

Adipose tissue (AT) is a dynamic and flexible organ with regulatory roles in physiological functions including metabolism, reproduction and inflammation; secreted adipokines, including leptin, and fatty acids facilitate many of these roles. The African elephant (Loxodonta africana) is experiencing serious challenges to optimal reproduction in captivity. The physiological and molecular basis of this impaired fertility remains unknown. AT production of leptin is a crucial molecular link between nutritional status, adiposity and fertility in many species. We propose that leptin has a similar function in the African elephant. African elephant visceral and subcutaneous adipose tissue (AT) was obtained from both sexes and a range of ages including females with known pregnancy status. RNA was extracted and histological sections created and analyzed by microarray, PCR and immunohistochemistry respectively. Gas-chromatography was used to determine the fatty acid composition of AT. Microarray expression profiling was used to compare gene expression profiles of AT from pre-pubertal versus reproductively competent adult African elephants. This study demonstrates, for the first time, leptin mRNA and protein expression in African elephant AT. The derived protein sequence of the elephant leptin protein was exploited to determine its relationship within the class I helical cytokine superfamily, which indicates that elephant leptin is most closely related to the leptin orthologs of Oryctolagus cuniculus (European rabbit), Lepus oiostolus (woolly hare), and members of the Ochotonidae (Pika). Immunohistological analysis identified considerable leptin staining within the cytoplasm of adipocytes. Significant differences in fatty acid profiles between pregnant and non-pregnant animals were revealed, most notably a reduction in both linoleic and α linoleic acid in pregnant animals. This report forms the basis for future studies to address the effect of nutrient composition and body condition on reproduction in captive and wild elephants.