The Role of the Insulin-Like Growth Factor 1 Pathway in Immune Tumor Microenvironment and Its Clinical Ramifications in Gynecologic Malignancies

Yahya, Muna Alemi; Sharon, Shilhav Meisel; Hantisteanu, Shay; Hallak, Mordechai; Bruchim, Ilan

doi:10.3389/fendo.2018.00297

Cited by 22 publications

(12 citation statements)

References 91 publications

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“…FREM1 has been authenticated as an immune-related gene which may be a potential target for immunotherapy in breast cancer and clear cell renal cell carcinoma [ 47 , 48 ]. The insulin-like growth factor 1 (IGF1) pathway has been proven to contribute to the suppression of immune tumor microenvironment (TME) in gynecologic cancers [ 49 ]. IRF4 + Tregs have been confirmed to be correlated with poor prognosis in patients with multiple cancers [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

Zheng

Cao

Zhang

et al. 2020

BioMed Research International

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Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune-related lncRNAs (IRLs) of CC has never been reported. This study is aimed at establishing an IRL signature for patients with CC. A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson correlation analysis between the immune score and lncRNA expression ( p < 0.01 ). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values ( p < 0.05 ) were identified which demonstrated an ability to stratify patients into the low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group in the training set, valid set, and total set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four-IRL signature in predicting the one-, two-, and three-year survival rates was larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four IRLs in the development of CC were ascertained preliminarily.

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Section: Discussionmentioning

confidence: 99%

Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

Zheng

Cao

Zhang

et al. 2020

BioMed Research International

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“…Increased expression of TGB1 has been correlated with EMT, tumor growth and metastasis in ovarian cancer ( 37 , 38 ), while overexpression of BCL2L1 is associated with anti-apoptosis effects and platinum resistance ( 39 , 40 ). In addition, STAT3 signaling in ovarian cancer has been reported to be associated with tumor cell proliferation, survival, stemness and angiogenesis ( 41 ), while the overexpression of IGF1 has been revealed to stimulate the proliferation of ovarian cancer cells, along with its immunosuppressive role in ovarian cancer ( 42 , 43 ). In a similar manner, GHRH , which is endogenously produced in ovarian cancer cells, is involved in ovarian cancer growth and tumor vascularization ( 44 , 45 ).…”

Section: Discussionmentioning

confidence: 99%

Identification of GNA12‑driven gene signatures and key signaling networks in ovarian cancer

Jayaraman

Yan

et al. 2021

Oncol Lett

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With the focus on defining the oncogenic network stimulated by lysophosphatidic acid (LPA) in ovarian cancer, the present study sought to interrogate the oncotranscriptome regulated by the LPA-mediated signaling pathway. LPA, LPA-receptor (LPAR) and LPAR-activated G protein 12 α-subunit, encoded by G protein subunit α 12 ( GNA12 ), all serve an important role in ovarian cancer progression. While the general signaling mechanism regulated by LPA/LPAR/ GNA12 has previously been characterized, the global transcriptomic network regulated by GNA12 in ovarian cancer pathophysiology remains largely unknown. To define the LPA/LPAR/ GNA12 -orchestrated oncogenic networks in ovarian cancer, transcriptomic and bioinformatical analyses were conducted using SKOV3 cells, in which the expression of GNA12 was silenced. Array analysis was performed in Agilent SurePrint G3 Human Comparative Genomic Hybridization 8×60 microarray platform. The array results were validated using Kuramochi cells. Gene and functional enrichment analyses were performed using Database for Annotation, Visualization and Integrated Discovery, Search Tool for Retrieval of Interacting Genes and Cytoscape algorithms. The results indicated a paradigm in which GNA12 drove ovarian cancer progression by upregulating a pro-tumorigenic network with AKT1, VEGFA, TGFB1, BCL2L1, STAT3 , insulin-like growth factor 1 and growth hormone releasing hormone as critical hub and/or bottleneck nodes. Moreover, GNA12 downregulated a growth-suppressive network involving proteasome 20S subunit (PSM) β6, PSM α6, PSM ATPase 5, ubiquitin conjugating enzyme E2 E1, PSM non-ATPase 10, NDUFA4 mitochondrial complex-associated, NADH:ubiquinone oxidoreductase subunit B8 and anaphase promoting complex subunit 1 as hub or bottleneck nodes. In addition to providing novel insights into the LPA/LPAR/ GNA12 -regulated oncogenic networks in ovarian cancer, the present study identified several potential nodes in this network that could be assessed for targeted therapy.

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“…FREM1 has been authenticated as an immune-related gene which may be a potential target for immunotherapy in breast cancer and clear cell renal cell carcinoma [42,43]. The insulin-like growth factor 1(IGF1) pathway has been proven to contribute to the suppression of immune tumor microenvironment(TME) in gynecologic cancers [44]. IRF4 + Tregs have been con rmed to be correlated with poor prognosis in patients with multiple cancers [45].…”

Section: Discussionmentioning

confidence: 99%

Immune‐related Long Noncoding RNA Signature for Patients with Cervical Cancer

Zheng

Tong

Cao

et al. 2020

Preprint

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Background: Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune‐related lncRNAs(IRLs) of CC has never been reported. This study aimed to establish an IRL signature for patients with CC.Methods: The RNA-seq dataset was obtained from the TCGA, GEO, and GTEx database. The immune scores（IS）based on single-sample gene set enrichment analysis (ssGSEA) were calculated to identify the IRLs, which were then analyzed using univariate Cox regression analysis to identify significant prognostic IRLs. A risk score model was established to divide patients into low-risk and high-risk groups based on the median risk score of these IRLs. This was then validated by splitting TCGA dataset(n=304) into a training-set(n=152) and a valid-set(n=152). The fraction of 22 immune cell subpopulations was evaluated in each sample to identify the differences between low-risk and high-risk groups. Additionally, a ceRNA network associated with the IRLs was constructed.Results: A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson’s correlation analysis between immune score and lncRNA expression (P < 0.01). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values (P < 0.05) were identified which demonstrated an ability to stratify patients into low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low‐risk group showed longer overall survival (OS) than those in the high‐risk group in the training-set, valid-set, and total-set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four IRLs signature in predicting the one-, two-, and three-year survival rates were larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Conclusions: Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four-IRLs in the development of CC were ascertained preliminarily.

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The Role of the Insulin-Like Growth Factor 1 Pathway in Immune Tumor Microenvironment and Its Clinical Ramifications in Gynecologic Malignancies

Cited by 22 publications

References 91 publications

Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

Identification of GNA12‑driven gene signatures and key signaling networks in ovarian cancer

Immune‐related Long Noncoding RNA Signature for Patients with Cervical Cancer

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