Inhibin Is a Novel Paracrine Factor for Tumor Angiogenesis and Metastasis

Singh, Priyanka; Jenkins, Laura M.; Horst, Ben; Alers, Victoria; Pradhan, Shrikant; Kaur, Prabhjot; Srivastava, Tapasya; Hempel, Nadine; Győrffy, Balázs; Broude, Eugenia V.; Lee, Nam Y.; Mythreye, Karthikeyan

doi:10.1158/0008-5472.can-17-2316

Cited by 34 publications

(57 citation statements)

References 48 publications

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“…TGFβ1 and 2 have demonstrated roles in ovarian cancers, however, it is not clear if TGFβ3 plays a direct role in EOC despite a few lines of evidence indicating potential roles in ovarian angiogenesis [ 60 ]. While other members including BMPs, Activins and Inhibins’ have important physiological and pathological roles in the ovary and in ovarian cancer [ 61 – 65 ], here, we focus solely on the TGFβ isoforms.…”

Section: Tgfβ Family In Ovarian and Related Cancersmentioning

confidence: 99%

TGFβ signaling networks in ovarian cancer progression and plasticity

Asha

Shonibare

Monavarian

et al. 2021

Clin Exp Metastasis

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Epithelial ovarian cancer (EOC) is a leading cause of cancer-related death in women. Late-stage diagnosis with significant tumor burden, accompanied by recurrence and chemotherapy resistance, contributes to this poor prognosis. These morbidities are known to be tied to events associated with epithelial-mesenchymal transition (EMT) in cancer. During EMT, localized tumor cells alter their polarity, cell–cell junctions, cell–matrix interactions, acquire motility and invasiveness and an exaggerated potential for metastatic spread. Key triggers for EMT include the Transforming Growth Factor-β (TGFβ) family of growth factors which are actively produced by a wide array of cell types within a specific tumor and metastatic environment. Although TGFβ can act as either a tumor suppressor or promoter in cancer, TGFβ exhibits its pro-tumorigenic functions at least in part via EMT. TGFβ regulates EMT both at the transcriptional and post-transcriptional levels as outlined here. Despite recent advances in TGFβ based therapeutics, limited progress has been seen for ovarian cancers that are in much need of new therapeutic strategies. Here, we summarize and discuss several recent insights into the underlying signaling mechanisms of the TGFβ isoforms in EMT in the unique metastatic environment of EOCs and the current therapeutic interventions that may be relevant.

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Section: Tgfβ Family In Ovarian and Related Cancersmentioning

confidence: 99%

TGFβ signaling networks in ovarian cancer progression and plasticity

Asha

Shonibare

Monavarian

et al. 2021

Clin Exp Metastasis

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“… 24 Singh et al demonstrated that INK, as a good diagnostic and prognostic marker of ovarian cancers, also plays a role in promoting tumor metastasis and angiogenesis in other cancers, which may offer new vascular targets for cancer therapy. 25 ANGPTL4 has an effect on enhancing lung cancer cell invasion and migration partially through the ERK signaling pathway. 26 LGR4 belongs to a G-protein coupled receptor and is involved in activating the Wnt signaling pathway to influence tumor progression.…”

Section: Discussionmentioning

confidence: 99%

The Combined Detection of Immune Genes for Predicting the Prognosis of Patients With Non-Small Cell Lung Cancer

Tian

Liu

2020

Technol Cancer Res Treat

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Lung cancer is one of the leading causes of cancer-related death. In recent years, there has been an increasing interest in the fields of tumor and immunity. This study focused on the possible prognostic value of immune genes in non-small cell lung cancer patients. We used The Cancer Genome Atlas (TCGA) to download gene expression data and clinical information of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). The immune gene list was downloaded from the Immport database. We then constructed immune gene prognostic models on the basis of Cox regression analysis. We further evaluated the clinical significance of the models via survival analysis, receiver operating characteristic (ROC) curves, and independent prognostic factor analysis. Moreover, we analyzed the associations of prognostic models with both mutation burdens and neoantigens. Using the Gene Expression Omnibus (GEO) and Kaplan–Meier plotter databases, we evaluated the validity of the prognostic models. The prognostic model of LUAD included 13 immune genes, and the prognostic model of LUSC contained 10 immune genes. High-risk patients based on prognostic models had a lower 5-year survival rate than did low-risk patients. The ROC curve analysis demonstrated the prediction accuracy of the prognostic models, as the area under the curve (AUC) was 0.742, 0.707, and 0.711 for LUAD, and 0.668, 0.703, and 0.668 for LUSC, when the predicted survival times were 1, 3, and 5 years, respectively. The mutation burden analysis showed that mutation level was associated with the risk score in patients with LUAD. The analysis based on GEO and Kaplan–Meier plotter demonstrated the prognostic validity of the models. Therefore, immune gene-related models of LUAD and LUSC can predict prognosis. Further study of these genes may enable us to better distinguish between LUAD and LUSC and lead to improvement in immunotherapy for lung cancer.

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“…Our results showed that INHA was a marker of poor prognosis in lung adenocarcinoma. The possible mechanism was that INHA was involved in tumor angiogenesis, leading to tumor metastasis and poor prognosis (28). Further studies are required to elucidate the roles of these hub genes in the TME in the pathogenesis of lung adenocarcinoma.…”

Section: Discussionmentioning

confidence: 99%

Immune-Stromal Score Signature: Novel Prognostic Tool of the Tumor Microenvironment in Lung Adenocarcinoma

Qin

et al. 2020

Front. Oncol.

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Background: Immune and stromal cells in the tumor microenvironment (TME) significantly contribute to the prognosis of lung adenocarcinoma; however, the TME-related immune prognostic signature is unknown. The aim of this study was to develop a novel immune prognostic model of the TME in lung adenocarcinoma. Methods: First, the immune and stromal scores among lung adenocarcinoma patients were determined using the ESTIMATE algorithm in accordance with The Cancer Genome Atlas (TCGA) database. Differentially expressed immune-related genes (IRGs) between high and low immune/stromal score groups were analyzed, and a univariate Cox regression analysis was performed to identify IRGs significantly correlated with overall survival (OS) among patients with lung adenocarcinoma. Furthermore, a least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate TME-related immune prognostic signatures. Gene set enrichment analysis was performed to analyze the mechanisms underlying these immune prognostic signatures. Finally, the functions of hub IRGs were further analyzed to delineate the potential prognostic mechanisms in comprehensive TCGA datasets. Results: In total, 702 intersecting differentially expressed IRGs (589 upregulated and 113 downregulated) were screened. Univariate Cox regression analysis revealed that 58 significant differentially expressed IRGs were correlated with patient prognosis in the training cohort, of which three IRGs (CLEC17A, INHA, and XIRP1) were identified through LASSO regression analysis. A robust prognostic model was generated on the basis of this three-IRG signature. Furthermore, functional enrichment analysis of the high-risk-score group was performed primarily on the basis of metabolic pathways, whereas analysis of the low-risk-score group was performed primarily on the basis of immunoregulation and immune cell activation. Finally, hub IRGs CLEC17A, INHA, and XIRP1 were considered novel prognostic biomarkers for lung adenocarcinoma. These hub genes had different mutation frequencies and forms in lung adenocarcinoma and participated in different signaling pathways. More importantly, these hub genes were significantly correlated with the infiltration of CD4+ T cells, CD8+ T cells, macrophages, B cells, and neutrophils. Qi et al. Prognostic Signature of Tumor Microenvironment Conclusions: The robust novel TME-related immune prognostic signature effectively predicted the prognosis of patients with lung adenocarcinoma. Further studies are required to further elucidate the regulatory mechanisms of these hub IRGs in the TME and to develop new treatment strategies.

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Inhibin Is a Novel Paracrine Factor for Tumor Angiogenesis and Metastasis

Cited by 34 publications

References 48 publications

TGFβ signaling networks in ovarian cancer progression and plasticity

TGFβ signaling networks in ovarian cancer progression and plasticity

The Combined Detection of Immune Genes for Predicting the Prognosis of Patients With Non-Small Cell Lung Cancer

Immune-Stromal Score Signature: Novel Prognostic Tool of the Tumor Microenvironment in Lung Adenocarcinoma

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