Association of biobehavioral factors with non-coding RNAs in cervical cancer

Liu, Qiyu; Lu, Chong; Dai, Wanjun; Li, Ké; Xu, Jing; Huang, Yunke; Li, Guiling; Kang, Yu; Sood, Anil K.; Xu, Congjian

doi:10.5582/bst.2017.01325

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…ZNF683, as a transcription factor, disrupts transcriptional processes in tissue-resident memory T and natural killer T cells, supplying immune protection when the body is re-infected ( Van Gisbergen et al, 2012 ; Mackay et al, 2016 ). Liu et al (2018) conducted analysis to clarify the potential mechanism of biological behavior factors that cause cervical cancer. Their results elucidated that the ZNF683 mRNAs are linked to the GO term “adaptive immune response.” This result is consistent with ours.…”

Section: Discussionmentioning

confidence: 99%

Identification of Biomarkers for Cervical Cancer Radiotherapy Resistance Based on RNA Sequencing Data

Feng

Wang

Yang

et al. 2021

Front. Cell Dev. Biol.

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Cervical cancer as a common gynecological malignancy threatens the health and lives of women. Resistance to radiotherapy is the primary cause of treatment failure and is mainly related to difference in the inherent vulnerability of tumors after radiotherapy. Here, we investigated signature genes associated with poor response to radiotherapy by analyzing an independent cervical cancer dataset from the Gene Expression Omnibus, including pre-irradiation and mid-irradiation information. A total of 316 differentially expressed genes were significantly identified. The correlations between these genes were investigated through the Pearson correlation analysis. Subsequently, random forest model was used in determining cancer-related genes, and all genes were ranked by random forest scoring. The top 30 candidate genes were selected for uncovering their biological functions. Functional enrichment analysis revealed that the biological functions chiefly enriched in tumor immune responses, such as cellular defense response, negative regulation of immune system process, T cell activation, neutrophil activation involved in immune response, regulation of antigen processing and presentation, and peptidyl-tyrosine autophosphorylation. Finally, the top 30 genes were screened and analyzed through literature verification. After validation, 10 genes (KLRK1, LCK, KIF20A, CD247, FASLG, CD163, ZAP70, CD8B, ZNF683, and F10) were to our objective. Overall, the present research confirmed that integrated bioinformatics methods can contribute to the understanding of the molecular mechanisms and potential therapeutic targets underlying radiotherapy resistance in cervical cancer.

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Section: Discussionmentioning

confidence: 99%

Identification of Biomarkers for Cervical Cancer Radiotherapy Resistance Based on RNA Sequencing Data

Feng

Wang

Yang

et al. 2021

Front. Cell Dev. Biol.

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“…It has been demonstrated that lncRNAs can regulate the activity of transcription factors or modulate alternations in chromatin structure [86]. An lncRNA plus mRNA microarray was conducted and revealed that 1621 lncRNA and 1345 mRNAs were differentially expressed between high-risk and low-risk squamous cervical cancer [87]. Another group reported that 5844 lncRNAs and 4436 mRNAs were differentially expressed in cervical cancer compared with normal cervical tissues [88].…”

Section: Systems Biology Approaches In Cervical Cancermentioning

confidence: 99%

Recent Advances on the Molecular Mechanism of Cervical Carcinogenesis Based on Systems Biology Technologies

Lin

Zhou

et al. 2019

Computational and Structural Biotechnology Journal

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Cervical cancer is one of the common malignancies in women worldwide. Exploration of pathogenesis and molecular mechanism of cervical cancer is pivotal for development of effective treatment for this disease. Recently, systems biology approaches based on high-throughput technologies have been carried out to investigate the expression of some genes and proteins in genomics, transcriptomics, proteomics, and metabonomics of cervical cancer. Compared with traditional methods，systems biology technology has been shown to provide large of information regarding prognostic biomarkers and therapeutic targets for cervical cancer. These molecular signatures from system biology technology could be useful to understand the molecular mechanisms of cervical cancer development and progression, and help physicians to design targeted therapeutic strategies for patients with cervical cancer.

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