The effects of PTPN2 loss on cell signalling and clinical outcome in relation to breast cancer subtype

Veenstra, Cynthia; Karlsson, Elin; Mirwani, Sanam Mirwani; Nordenskjöld, Bo; Fornander, Tommy; Pérez-Tenorio, Gizeh; Stål, Olle

doi:10.1007/s00432-019-02918-y

Cited by 14 publications

(14 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In breast cancer, PTPN2 is not expressed in half of breast cancer patients. These findings show that PTPN2 plays a crucial role in the different subtypes of breast cancer, and affects the prognosis and treatment response of breast cancer (38).…”

Section: Discussionmentioning

confidence: 64%

Identification of potential biomarkers in ovarian carcinoma and an evaluation of their prognostic value

Cai¹,

Qiu²,

Wang³

et al. 2021

Ann Transl Med

View full text Add to dashboard Cite

Background: Ovarian cancer is one of the most common malignant tumors in female genital organs, and its incidence rate is high. However, the pathogenesis and prognostic markers of ovarian cancer are unclear.This study sought to screen potential markers of ovarian cancer and to explore their prognostic value.Methods: The Cancer Genome Atlas, Gene Expression Omnibus, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were used in this study. The least absolute shrinkage and selection operator (LASSO), multivariate Cox regression and stepwise regression analysis were chosen to screen genes and construct risk model. Gene Set Enrichment Analysis (GSEA) and an immune-infiltration analysis were performed.Results: One hundred thirty two co-expressed genes were found. They involved in metabolism, protein phosphorylation, mitochondria, and immune signaling pathways. Twelve genes significantly related to the survival of ovarian cancer were identified. Eight risk genes (i.e., CACNB1, FAM120B, HOXB2, MED19, PTPN2, SMU1, WAC.AS1, and BCL2L11) were further screened and used to construct the risk model. The risk status might be an independent prognostic factor of ovarian cancer, and most of the biological functions of genes expressed in high-risk ovarian cancer were related to synapse, adhesion, and immune-related functions. The clusters of CD4+ T cells and M2 macrophages were high in high-risk status samples.Conclusions: In ovarian cancer, the abnormal expression of 8 genes, including CACNB1, FAM120B, HOXB2, MED19, PTPN2, SMU1, WAC.AS1, and BCL2L11, is closely related to ovarian cancer progression, and these genes can serve as independent prognosis markers of ovarian cancer.

show abstract

Section: Discussionmentioning

confidence: 64%

Identification of potential biomarkers in ovarian carcinoma and an evaluation of their prognostic value

Cai¹,

Qiu²,

Wang³

et al. 2021

Ann Transl Med

View full text Add to dashboard Cite

show abstract

“…In breast cancer, PTPN2 protein is lost in half of breast cancer patients. The role of PTPN2 is related to the subtype of breast cancer, and PTPN2 affects the prognosis and treatment response of breast cancer (24).…”

Section: Discussionmentioning

confidence: 99%

Screening and prognostic value of potential biomarkers for ovarian cancer

Tang

et al. 2021

Ann Transl Med

View full text Add to dashboard Cite

Background: Ovarian cancer is a common gynecological malignant tumor that greatly threatens women's health, so we screened potential biomarkers of ovarian cancer and analyzed their prognostic value. Methods:The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to analyze the ovarian cancer-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the function of ovarian cancer-related genes. The survival-related genes were screened out through the least absolute shrinkage and selection operator (LASSO) method. Multivariate Cox regression model and stepwise regression analysis were performed to construct the risk model. The receiver operating characteristic (ROC) and the area under the ROC curve (AUC) were used to evaluate the prediction accuracy of risk score model. Finally, gene set enrichment analysis (GSEA) and immune cell infiltration analysis were performed to investigate the biological function and immune cell infiltration.Results: A total of 111 genes were found to have common effects on survival. These genes were mainly involved in metabolism, protein phosphorylation and immune-related signaling pathways. Seven risk genes (AP3D1, DCAF10, FBXO16, LRFN4, PTPN2, SAYSD1, ZNF426) were screened out. Among these genes, AP3D1 and LRFN4 are risk genes and DCAF10, FBXO16, PTPN2, SAYSD1, and ZNF426 are protective genes. These findings suggest that risk status may be an independent prognostic factor. The risk score had a high predictive value for the prognosis of ovarian cancer. In addition, GSEA revealed that the biological function of genes expressed in patients at a high risk was mostly related to immune-related function. The contents of CD4 + T cells, macrophages, myeloid dendritic cells (mDC) and neutrophils were high in samples at a high risk for ovarian cancer. Conclusions:The abnormal expression of AP3D1, DCAF10, FBXO16, LRFN4, PTPN2, SAYSD1 and ZNF426 is highly related to the progression of ovarian cancer. These seven genes can be used as independent prognostic markers of ovarian cancer. This study not only adds evidence to the pathogenesis of ovarian cancer but also provides scientific basis for judging the prognosis of ovarian cancer.

show abstract

“…Interestingly, glucosamine is found to suppress the activation of STAT3 and decrease breast cancer stemness and progression [21]. Additionally, knockdown of PTPN2 leads to EGF-mediated STAT3 activation [22]. The association of chronic inflammation with breast cancer progression is widely recognized, but it can be inhibited by blocking STAT3 [23].…”

Section: Advances In the Study Of Stat3 Signaling Pathways In Breast mentioning

confidence: 99%

Role of STAT3 signaling pathway in breast cancer

2020

View full text Add to dashboard Cite

Breast cancer has grown to be the second leading cause of cancer-related deaths in women. Only a few treatment options are available for breast cancer due to the widespread occurrence of chemoresistance, which emphasizes the need to discover and develop new methods to treat this disease. Signal transducer and activator of transcription 3 (STAT3) is an early tumor diagnostic marker and is known to promote breast cancer malignancy. Recent clinical and preclinical data indicate the involvement of overexpressed and constitutively activated STAT3 in the progression, proliferation, metastasis and chemoresistance of breast cancer. Moreover, new pathways comprised of upstream regulators and downstream targets of STAT3 have been discovered. In addition, small molecule inhibitors targeting STAT3 activation have been found to be efficient for therapeutic treatment of breast cancer. This systematic review discusses the advances in the discovery of the STAT3 pathways and drugs targeting STAT3 in breast cancer.

show abstract

The effects of PTPN2 loss on cell signalling and clinical outcome in relation to breast cancer subtype

Cited by 14 publications

References 22 publications

Identification of potential biomarkers in ovarian carcinoma and an evaluation of their prognostic value

Identification of potential biomarkers in ovarian carcinoma and an evaluation of their prognostic value

Screening and prognostic value of potential biomarkers for ovarian cancer

Role of STAT3 signaling pathway in breast cancer

Contact Info

Product

Resources

About