Dataset Information

Identification of Gαi3 as a novel molecular therapeutic target of cervical cancer.

ABSTRACT: Here we studied expression and potential functions of Gαi3 in cervical cancer. The bioinformatics analysis together with the results from local patients' tissues revealed that Gαi3 expression was remarkably elevated in human cervical cancer tissues and different cervical cancer cells, and was associated with poor overall survival and poor disease-specific survival of patients. Gαi3 depletion resulted in profound anti-cervical cancer activity. In primary or immortalized cervical cancer cells, Gαi3 shRNA or CRISPR/Cas9-caused Gαi3 knockout/KO largely hindered cell proliferation and migration, and provoked apoptosis. On the contrast, ectopic Gαi3 overexpression further enhanced cervical cancer proliferation and migration. Akt-mTOR activation in primary cervical cancer cells was significantly reduced after Gαi3 silencing or KO, but was augmented following Gαi3 overexpression. Further studies revealed that the transcription factor GATA4 binding to Gαi3 promoter region was significantly enhanced in cervical cancer tissues and cells. Gαi3 expression was decreased by GATA4 shRNA, but upregulated following GATA4 overexpression. In vivo, the growth of cervical cancer xenografts was robustly suppressed after Gαi3 silencing or KO. Gαi3 depletion and Akt-mTOR inactivation were detected in Gαi3-silenced/-KO cervical cancer xenograft tissues. Together, upregulated Gαi3 is a valuable oncotarget of cervical cancer.

SUBMITTER: Zhang J

PROVIDER: S-EPMC9576524 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Gαi3 as a novel molecular therapeutic target of cervical cancer.

Zhang Jie J Yin De-Pei DP Zhang Yan Y Zhang Jia-Nan JN Yang Yan Y Zhang Zhi-Qing ZQ Zhou Li L Lv Yan Y Huang Hai-Wei HW Cao Cong C

International journal of biological sciences 20220906 15

Here we studied expression and potential functions of Gαi3 in cervical cancer. The bioinformatics analysis together with the results from local patients' tissues revealed that Gαi3 expression was remarkably elevated in human cervical cancer tissues and different cervical cancer cells, and was associated with poor overall survival and poor disease-specific survival of patients. Gαi3 depletion resulted in profound anti-cervical cancer activity. In primary or immortalized cervical cancer cells, Gαi ...[more]

PMID: 36263185

Similar Datasets

Project description:The increasing mortality rate of pancreatic cancer globally necessitates the urgent identification for novel therapeutic targets. This study investigated the expression, functions, and mechanistic insight of G protein inhibitory subunit 3 (Gαi3) in pancreatic cancer. Bioinformatics analyses reveal that Gαi3 is overexpressed in human pancreatic cancer, correlating with poor prognosis, higher tumor grade, and advanced classification. Elevated Gαi3 levels are also confirmed in human pancreatic cancer tissues and primary/immortalized cancer cells. Gαi3 shRNA or knockout (KO) significantly reduced cell viability, proliferation, cell cycle progression, and mobility in primary/immortalized pancreatic cancer cells. Conversely, Gαi3 overexpression enhanced pancreatic cancer cell growth. RNA-sequencing and bioinformatics analyses of Gαi3-depleted cells indicated Gαi3's role in modulating the Akt-mTOR and PKA-Hippo-YAP pathways. Akt-S6 phosphorylation was decreased in Gαi3-depleted cells, but was increased with Gαi3 overexpression. Additionally, Gαi3 depletion elevated PKA activity and activated the Hippo pathway kinase LATS1/2, leading to YAP/TAZ inactivation, while Gαi3 overexpression exerted the opposite effects. There is an increased binding between Gαi3 promoter and the transcription factor TCF7L2 in pancreatic cancer tissues and cells. Gαi3 expression was significantly decreased following TCF7L2 silencing, but increased with TCF7L2 overexpression. In vivo, intratumoral injection of Gαi3 shRNA-expressing adeno-associated virus significantly inhibited subcutaneous pancreatic cancer xenografts growth in nude mice. A significant growth reduction was also observed in xenografts from Gαi3 knockout pancreatic cancer cells. Akt-mTOR inactivation and increased PKA activity coupled with YAP/TAZ inactivation were also detected in xenograft tumors upon Gαi3 depletion. Furthermore, bioinformatic analysis and multiplex immunohistochemistry (mIHC) staining on pancreatic cancer tissue microarrays showed a reduced proportion of M1-type macrophages and an increase in PD-L1 positive cells in Gαi3-high pancreatic cancer tissues. Collectively, these findings highlight Gαi3's critical role in promoting pancreatic cancer cell growth, potentially through the modulation of the Akt-mTOR and PKA-Hippo-YAP pathways and its influence on the immune landscape.

Project description:Maternal embryo leucine zipper kinase (MELK) is highly expressed in a variety of malignant tumors and involved in cell cycle regulation, cell proliferation, apoptosis, tumor formation etc However, the biological effects of MELK in cervical cancer are still uninvestigated. This study aimed to explore the expression of MELK in cervical cancer, as well as its effects on the proliferation, apoptosis, DNA damage repair on cervical cancer cell line in vitro and to provide novel ideas for further improving the clinical efficacy of cervical cancer. Immunohistochemistry, Western blot, RT-qPCR, CCK8, and immunofluorescence techniques were used to detect the expression of MELK in cervical cancer tissues, paracancerous tissues, and cervical cancer cell lines. Several cervical cancer cell lines were treated with MELK knockdown by siRNA and MELK selective inhibitor OTSSP167. The effects on proliferation, apoptosis, and colony formation capacity, and tumor cell DNA damage repair-related factor were detected in cell lines. Our data showed that the high expression rate of MELK in cervical cancer patients was 56.92%. MELK expression in cervical cancer samples was significantly higher than that in paraneoplastic tissues. Highly expressed MELK correlated with the cervical histopathological grading and greatly increased with the cervical histopathological grading, from normal cervix and cervical intraepithelial neoplasia to cervical cancer. Moreover, the abnormal expression of MELK was related to cervical cancer metastasis at early stage. The knockdown of MELK with siRNA and OTSSP167 had strong inhibition effects on the proliferation, apoptosis, and colony formation of cervical cancer cells. MELK knockdown could also aggravate the DNA damage of cervical cancer cells possibly by homologous recombination repair pathway. Therefore, MELK may be a predicting marker of poor prognosis of cervical cancer and may also be a new therapeutic target for cervical cancer, providing ideas for improving the therapeutic effect of cervical cancer.

Project description:IntroductionCervical cancer has high mortality, high recurrence and poor prognosis. Although prognostic biomarkers such as clinicopathological features have been proposed, their accuracy and precision are far from satisfactory. Therefore, novel biomarkers are urgently needed for disease surveillance, prognosis prediction and treatment selection.MaterialsDifferentially expressed genes (DEGs) between cervical cancer and normal tissues from three microarray datasets extracted from the Gene Expression Omnibus platform were identified and screened. Based on these DEGs, a six-gene prognostic signature was constructed using cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas. Next, the molecular functions and related pathways of the six genes were investigated through gene set enrichment analysis and co-expression analysis. Additionally, immunophenoscore analysis and the QuartataWeb Server were employed to explore the therapeutic value of the six-gene signature.ResultsWe discovered 178 overlapping DEGs in three microarray datasets and established a six-gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) prognostic signature with stable and excellent performance in predicting overall survival in different subgroups. Intriguingly, the six-gene signature was closely associated with the immune response and tumour immune microenvironment. The six-gene signature might be used for predicting response to immune checkpoint inhibitors (ICIs) and the six genes may serve as new drug targets for cervical cancer.ConclusionOur study established a novel six-gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) signature that was closely associated with the immune response and tumour immune microenvironment. The six-gene signature was indicative of aggressive features of cervical cancer and therefore might serve as a promising biomarker for predicting not only overall survival but also ICI treatment effectiveness. Moreover, three genes (UPP1, ISG20 and GLTP) within the six-gene signature have the potential to become novel drug targets.

Project description:BackgroundThe efficacy of therapy in cervical cancer (CESC) is blocked by high molecular heterogeneity. Thus, the sub-molecular characterization remains primarily explored for personalizing the treatment of CESC patients.MethodsDatasets with 741 CESC patients were obtained from TCGA and GEO databases. The NMF algorithm, random forest algorithm, and multivariate Cox analysis were utilized to construct a classifier for defining the sub-molecular characterization. Then, the biological characteristics, genomic variations, prognosis, and immune landscape in molecular subtypes were explored. The significance of classifier genes was validated by quantitative Real-Time PCR, cell transfection, cell colony formation assay, wound healing assay, cell proliferation assay, and Western blot.ResultsThe CESC patients were classified into two subtypes, and the high classifier-score patients with significant differences in ECM-receptor interaction, PI3K-Akt signaling pathway, and MAPK signaling pathway showed a poorer prognosis in OS (p < 0.001), DFI (p = 0.016), PFI (p < 0.001) and DSS (p < 0.001), and with high the M0 Macrophage and resting Mast cells infiltration and low HLA family gene expression. Moreover, the constructed classifier owns a high identified accuracy in the tumor/normal groups (AUC: 0.993), the tumor/CIN1-CIN3 groups (AUC: 0.963), and normal/CIN1-CIN3 groups (AUC: 0.962), and the total prediction performance is better than currently published signatures in CESC (C-index: 0,763). The combined prediction performance further indicated that Nomogram (AUC = 0.837) is superior to the classifier (AUC = 0.835) and Stage (AUC = 0.568), and the C-index of calibration curves is 0.784. The potential biological function of classifier genes indicated that silencing GALNT2 inhibited the cancer cell's proliferation, migration, and colony formation; Conversely, the cancer cell's proliferation, migration, and colony formation were increased after the upregulation of GALNT2. The Epithelial-Mesenchymal Transition Experiment showed that GALNT2 knockdown might reduce the levels of Snail and Vimentin proteins and increase E-cadherin; Conversely, the levels of Snail and Vimentin proteins were increased, E-cadherin was reduced by GALNT2 upregulation.ConclusionThe classifier we constructed may help improve our understanding of subtype characteristics and provide a new strategy for developing CESC therapeutics. Remarkably, GALNT2 may be an option to directly target drivers in CESC cancer therapy.

Dataset Information

Identification of Gαi3 as a novel molecular therapeutic target of cervical cancer.

Publications

Identification of Gαi3 as a novel molecular therapeutic target of cervical cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets