MiR-4327 targets TP53 to promote cervical cancer cell proliferation - Mei-Lin Chen; Chen-Yang Chu; Feng-Xian Zhang; Li-Pei Zhang; Ying Yang; Bai-Zhao Peng; Chuang-Hai Wu; Xiao-Mei Chen; Yan-Ting You; Bing-Ying Rong; Hiu Yee Kwan; Xiao-Shan Zhao; et al. (Functional & Integrative Genomics, 2026)
Cervical cancer is a leading cause of female malignancy worldwide. While microRNA-4327 (miR-4327) has been implicated as a potential oncogene, its functional role and molecular mechanisms in cervical cancer pathogenesis remain unclear. This study aimed to determine the oncogenic function of miR-4327 and elucidate its downstream regulatory mechanism in cervical cancer pathogenesis. We measured miR-4327 expression in clinical cervical cancer tissues and cell lines using quantitative real-time PCR (qRT-PCR). We then assessed its effects on proliferation, migration, invasion, and cell cycle progression through functional assays including cell counting kit-8 (CCK-8), colony formation, transwell, and flow cytometry. To evaluate tumor growth in vivo, we established a xenograft model in non-obese diabetic (NOD)-severe combined immune-deficient (scid) mice. Using bioinformatic analysis and luciferase reporter assays, we identified TP53 as a direct target of miR-4327 and further validated this regulatory relationship with gain- and loss-of-function experiments. We found that miR-4327 was significantly upregulated in cervical cancer and promoted malignant phenotypes such as proliferation, migration, invasion, and cell cycle progression in vitro. Consistent with this, overexpression of miR-4327 accelerated tumor growth in vivo. Mechanistically, we confirmed TP53 as a direct functional target of miR-4327. Knocking down TP53 phenocopied the oncogenic effects of miR-4327, while restoring TP53 expression rescued the tumor-promoting effects mediated by miR-4327. These findings reveal a novel miR-4327/TP53 regulatory axis and nominate miR-4327 as a potential therapeutic target for intervention.

Analysis of the AP2/ERF transcription factor family in Eriobotrya japonica and its role in exogenous melatonin-mediated regulation of salt stress - Ling Zhu; Fuhua Liu; Xin Lin; Tianyu Fu; Lin Zou; Yuanhai Pan; Rong Zou; Yang Zhao; Hanyao Zhang (Functional & Integrative Genomics, 2025)

A new perspective on endometriosis: Integrating eQTL mendelian randomization with transcriptomics and single-cell data analyses - Sheng Dou; Yi Wei; Zongyun Lin; Hui Wu; Fenglian Yang; Xuechang Cen; Wenjing Lu; Haimei Qin; Rong Wang; Junli Wang (Functional & Integrative Genomics, 2025)
Endometriosis is caused by the migration of endometrial cells to locations outside the uterine lining. Despite the increasing prevalence of endometriosis, there has been limited research on genetic effects, and its molecular mechanisms remain unclear. This study aimed to investigate the mechanisms underlying the development of endometriosis and to identify new genetic targets for endometriosis by integrating data from gene chips, single-cell mapping, and genome-wide association study databases. Using the Gene Expression Omnibus database, we downloaded data on normal endometrium, eutopic endometrium, and ectopic lesion tissues to explore the differentially expressed genes (DEGs) between normal and eutopic endometrium, and between eutopic and ectopic endometrium. Assessment of the relationships between DEGs and endometriosis involved differential expression, expression quantitative trait loci (eQTL), and Mendelian randomization (MR) analyses. Two single-cell atlas datasets were then analyzed to explore the mechanisms underlying disease development and progression. Intersection of MR results with DEGs between normal and eutopic endometrium highlighted 28 candidate biomarker genes (17 upregulated and 11 downregulated). Similarly, we identified two additional candidate biomarker genes by intersecting the DEGs between eutopic and ectopic endometrium with MR results. Among these 30 candidates, further filtering using single-cell datasets revealed that the histamine N-methyltransferase ( HNMT ), coiled-coil domain containing 28 A ( CCDC28A ), fatty acid desaturase 1 ( FADS1 ) and mahogunin ring finger 1 ( MGRN1 ) genes were differentially expressed between the normal and eutopic groups, consistent with transcriptomic and MR results. Our findings suggested that eutopic endometrium exhibits epithelial-mesenchymal transition (EMT). Cell communication analysis focused on ciliated epithelial cells expressing CDH1 and KRT23 revealed that, in the eutopic endometrium, ciliated epithelial cells are strongly correlated and interact with natural killer cells, T cells, and B cells. We identified four novel biomarker genes and found evidence for EMT in the eutopic endometrium. The mechanism of endometriosis progression may be closely related to EMT and changes in the immune microenvironment triggered by damage to ciliated epithelial cells.

Mitochondria-related lncRNAs: predicting prognosis, tumor microenvironment and treatment response in lung adenocarcinoma - Qianhui Zhou; Jiali Xiong; Yan Gao; Rong Yi; Yuzhu Xu; Quefei Chen; Lin Wang; Ying Chen (Functional & Integrative Genomics, 2023)
Lung cancer is the most common type of malignant tumor that affects people in China and even across the globe, as it exhibits the highest rates of morbidity and mortality. Lung adenocarcinoma (LUAD) is a type of lung cancer with a very high incidence. The purpose of this study was to identify potential biomarkers that could be used to forecast the prognosis and improve the existing therapy options for treating LUAD. Clinical and RNA sequencing data of LUAD patients were retrieved from the TCGA database, while the mitochondria-associated gene sets were acquired from the MITOMAP database. Thereafter, Pearson correlation analysis was carried out to screen mitochondria-associated lncRNAs. Furthermore, univariate Cox and Lasso regression analyses were used for the initial screening of the target lncRNAs for prognostic lncRNAs before they could be incorporated into a multivariate Cox Hazard ratio model. Then, the clinical data, concordance index, Kaplan–Meier (K-M) curves, and the clinically-relevant subjects that were approved by the Characteristic Curves (ROC) were employed for assessing the model's predictive value. Additionally, the differences in immune-related functions and biological pathway enrichment between high- and low-risk LUAD groups were examined. Nomograms were developed to anticipate the OS rates of the patients within 1-, 3-, and 5 years, and the differences in drug sensitivity and immunological checkpoints were compared. In this study, 2175 mitochondria-associated lncRNAs were screened. Univariate, multivariate, and Lasso Cox regression analyses were carried out to select 13 lncRNAs with an independent prognostic significance, and a prognostic model was developed. The OS analysis of the established prognostic prediction model revealed significant variations between the high- and low-risk patients. The AUC-ROC values after 1, 3, and 5 years were seen to be 0.746, 0.692, and 0.726, respectively. The results suggested that the prognostic model riskscore could be used as an independent prognostic factor that differed from the other clinical characteristics. After analyzing the findings of the study, it was noted that both the risk groups showed significant differences in their immune functioning, immunological checkpoint genes, and drug sensitivity. The prognosis of patients with LUAD could be accurately and independently predicted using a risk prediction model that included 13 mitochondria-associated lncRNAs.

GmPGIP3 enhanced resistance to both take-all and common root rot diseases in transgenic wheat - Aiyun Wang; Xuening Wei; Wei Rong; Liang Dang; Li-Pu Du; Lin Qi; Hui-Jun Xu; Yanjun Shao; Zengyan Zhang (Functional & Integrative Genomics, 2015)

Expression of a potato antimicrobial peptide SN1 increases resistance to take-all pathogen Gaeumannomyces graminis var. tritici in transgenic wheat - Wei Rong; Lin Qi; Jingfen Wang; Lipu Du; Huijun Xu; Aiyun Wang; Zengyan Zhang (Functional & Integrative Genomics, 2013)

Cytoplasmic male sterility-regulated novel microRNAs from maize - Yaou Shen; Zhiming Zhang; Haijian Lin; Hailan Liu; Jie Chen; Hua Peng; Moju Cao; Tingzhao Rong; Guangtang Pan (Functional & Integrative Genomics, 2011)