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Gene Expression Analysis Identifies Novel Targets for Cervical Cancer Therapy.

ABSTRACT: Although there has been significant progress in prevention and treatment of cervical cancer, this malignancy is still a leading cause of cancer death for women. Anti-angiogenesis and immunotherapy approaches have been providing survival benefits, however, response rates and durability of response need to be improved. There is a clear need for combination therapies that increase effectiveness of these agents and further improve patient outcome. Previous studies have largely focused on gene expression and molecular pathways in untreated cervix cancer. The goal of this study was to evaluate cancer-specific molecular pathways and their correlation with tumor immune profile in recurrent cervical cancer. Tumor and adjacent normal tissues were used to identify potential combination therapy targets. We found that DNA damage repair pathway genes were significantly overexpressed in the tumor. Based on our results and other recent investigations, we suggest that combination immune checkpoint and PARP inhibitor therapy is a high priority consideration for patients with recurrent, previously treated cervical cancer. We also show that multiple epithelial-mesenchymal transition-related genes, including MAP2K4, ID2, JAK1, FGF2, PIK3R1, AKT3, FGF13, and STAT3 may be potential targets. Interestingly, high-throughput analysis of Cancer Genome Atlas data identified distinct targets, including Fatty acid synthase FASN and Matrix Metallopeptidase 1 MMP1 as novel, promising combination therapy partners.

SUBMITTER: Roszik J

PROVIDER: S-EPMC6156434 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Gene Expression Analysis Identifies Novel Targets for Cervical Cancer Therapy.

Roszik Jason J Ring Kari L KL Wani Khalida M KM Lazar Alexander J AJ Yemelyanova Anna V AV Soliman Pamela T PT Frumovitz Michael M Jazaeri Amir A AA

Frontiers in immunology 20180919

Although there has been significant progress in prevention and treatment of cervical cancer, this malignancy is still a leading cause of cancer death for women. Anti-angiogenesis and immunotherapy approaches have been providing survival benefits, however, response rates and durability of response need to be improved. There is a clear need for combination therapies that increase effectiveness of these agents and further improve patient outcome. Previous studies have largely focused on gene expres ...[more]

PMID: 30283446

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Project description:ObjectivePreeclampsia (PE) is a pregnancy-specific multisystem disease as well as an important cause of maternal and perinatal death. This study aimed to analyze the placental transcriptional data and clinical information of PE patients available in the published database and predict the target genes for prevention of PE.MethodsThe clinical information and corresponding RNA data of PE patients were downloaded from the GEO database. Cluster analysis was performed to examine the correlation between different genotyping genes and clinical manifestations. Then, bioinformatic approaches including GO, KEGG, WGCNA, and GSEA were employed to functionally characterize candidate target genes involved in pathogenesis of PE.ResultsTwo PE datasets GSE60438 and GSE75010 were obtained and combined, thereby providing the data of 205 samples in total (100 non-PE and 105 PE samples). After eliminating the batch effect, we grouped and analyzed the integrated data, and further performed GSEA analysis. It was found that the genes in group 1 and group 2 were different from those in normal samples. Moreover, WGCNA analysis revealed that genes in group 1 were up-regulated in turquoise module, including SASH1, PIK3CB and FLT-1, while genes in group 2 were up-regulated in the blue and brown modules. We further conducted GO and KEGG pathway enrichment analyses and found that the differential genes in turquoise module were mainly involved in biological processes such as small molecular catabolic process, while being highly enriched in pathways, including MAPK signaling pathway and Rap1 signaling pathway.ConclusionFLT-1 was conventionally used to predict PE risk, and sFLT-1 could also be used as an indicator to evaluate PE treatment effect. As a candidate biomarker for predicting PE, SASH1 may participate in proliferation, migration, invasion and epithelial mesenchymal transformation of human trophoblast cells by regulating MAPK pathway and Rap1 signaling pathway, thus affecting the progression of PE. The mechanism allowing PIK3CB to regulate PE development was not clear, while the gene could be another candidate biomarker for PE risk prediction. This is an exploratory study and our findings were still required verification in further studies.

Project description:The zinc-finger protein which regulates apoptosis and cell cycle arrest 1 (Zac1), encoded by Plagl1 gene, is a seven-zinc-finger containing transcription factor belonging to the imprinted genome and is expressed in diverse types of embryonic and adult human tissues. Zac1 is postulated to be a tumor suppressor by inducing cell cycle arrest and apoptosis through interacting and modulating transcriptional activity of p53 as it was named. Correspondingly, the reduction or loss of Zac1 expression is associated with the incidence and progression of several human tumors, including cervical cancer, breast cancer, ovarian cancer, pituitary tumors, and basal cell carcinoma, implying the rationality of utilizing Zac1 expression as novel a biomarker for the evaluation of cervical cancer prognosis. However, to date, it has not been elucidated whether Zac1 expression is related to the prognosis of patients in clinical cervical cancer tumor samples. To address the questions outlined above, we report here a comprehensive investigation of Zac1 expression in biopsies of clinical cervical carcinoma. By analyzing Zac1 expression in various gene expression profiling of cervical cancer databases, we show the association between high Zac1 expression and poor prognosis of cervical cancer. Functional enrichment analysis showed that high Zac1 expression was associated with epithelial-mesenchymal transition (EMT), which was further observed in clinical characteristics and metastatic carcinoma samples using immunohistochemical staining. Correspondingly, hypomethylation of CpG island on Zac1 promoter was observed in samples with high Zac1 expression in cervical carcinoma. Finally, overexpression of Zac1 in a variety of cervical cancer cell lines increase their mesenchymal biomarker expression and migration, strengthening the correlation between cervical cancers with high Zac1 expression and metastasis in clinical. In summary, this research firstly revealed that identifying Zac1 expression or the methylation status of CpG site on Zac1 promoter may provide us with novel indicators for the evaluation of cervical cancer metastasis.

Project description:Breast cancer is one of the primary threats to women's health worldwide. However, the molecular mechanisms underlying the development of breast cancer remain to be fully elucidated. The present study aimed to investigate specific target gene expression profiles in breast cancer tissues in general and in different breast cancer stages, as well as to explore their functions in tumor development. For integrated analysis, a total of 5 gene expression profiling datasets for 3 different stages of breast cancer (stages I-III) were downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information. Pre-processing of these datasets was performed using the Robust Multi-array Average algorithm and global renormalization was performed for all studies. Differentially expressed genes between breast cancer patients and controls were estimated using the empirical Bayes algorithm. The Database for Annotation, Visualization and Integrated Discovery web server was used for analyzing the enrichment of the differentially expressed genes in Gene Ontology terms of the category biological process and in Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, breast cancer target genes were downloaded from the Thomson Reuters Integrity Database. We merged these target genes with the genes in breast cancer datasets. Analysis of anti-breast cancer gene networks was performed using the Genome-scale Integrated Analysis of Gene Networks in Tissues web server. The results demonstrated that the normal functions of the cell cycle, cell migration and cell adhesion were altered in all stages of breast cancer. Furthermore, 12 anti-breast cancer genes were identified to be dysregulated in at least one of the three stages. Among all of these genes, ribonucleotide reductase regulatory subunit M2 (RRM2) exhibited the highest degree of interaction with other interacting genes. Analysis of the network interactions revealed that the transcription factor of RRM2 is crucial for cancer development. Other genes, including mucin 1, progesterone receptor and cyclin-dependent kinase 5 regulatory subunit associated protein 3, also exhibited a high degree of interaction with the associated genes. In conclusion, several key anti-breast cancer genes identified in the present study are mainly associated with the regulation of the cell cycle, cell migration, cell adhesion and other cancer-associated cell functions, particularly RRM2.

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Gene Expression Analysis Identifies Novel Targets for Cervical Cancer Therapy.

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Gene Expression Analysis Identifies Novel Targets for Cervical Cancer Therapy.

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