Longke Ran

Prof. Longke Ran


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 February 2023 in Scientific Reports
Verified
Journal Article
Open access
PDF file
JLJiayi Lai
Jiayi Lai
SMShiqi Miao
Shiqi Miao
LRLongke Ran
Longke Ran
Clear cell Renal Cell Carcinoma (ccRCC), the most deadly and life-threatening tumor in the urinary system, has a dismal prognosis and a high risk of metastasizing. Regulation of ferroptosis is a prospective therapeutic target to eradicate malignant cells. Our objective was to seek ferroptosis-associated long non-coding RNAs (FALs) and developed a prediction signature for ccRCC. We extracted transcriptome data and clinical information from The Cancer Genome Atlas (TCGA) databases. Ferroptosis-associated genes (FAGs) were obtained from FerrDb database. A ferroptosis-associated lncRNA prognostic signature (FLPS) of ccRCC was generated utilizing univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, sequentially, based on 8 lncRNAs (LINC00460, AC124854.1, AC084876.1, IGFL2-AS1, LINC00551, AC083967.1, AC073487.1, and LINC02446). The signature's independent predictive value for ccRCC was demonstrated using univariate and multivariate regression analysis (P < 0.05). Subsequently, by combining independent predictive factors, a prognostic nomogram was established. Immunity analysis proclaimed a striking difference in terms of cells, function, checkpoints, and ESTIMATE scores between low- and high-risk groups. Overall, the innovative signature of ferroptosis-associated signatures may have a considerable effect on the immune response and prognosis for ccRCC.

9 November 2021 in Frontiers in Immunology
Verified
Journal Article
Open access
JSJing Song
Jing Song
YTYongyao Tang
Yongyao Tang
XLXiaoyong Luo
Xiaoyong Luo
XSXinpeng Shi
Xinpeng Shi
FSFangzhou Song
Fangzhou Song
LRLongke Ran
Longke Ran
Transmembrane Channel-like (TMC) genes are critical in the carcinogenesis, proliferation, and cell cycle of human cancers. However, the multi-omics features of TMCs and their role in the prognosis and immunotherapeutic response of human cancer have not been explored. We discovered that TMCs 4-8 were commonly deregulated and correlated with patient survival in a variety of cancers. For example, TMC5 and TMC8 were correlated with the relapse and overall survival rates of breast cancer and skin melanoma, respectively. These results were validated by multiple independent cohorts. TMCs were regulated by DNA methylation and somatic alterations, such as TMC5 amplification in breast cancer (523/1062, 49.2%). Six algorithms concordantly uncovered the critical role of TMCs in the tumor microenvironment, potentially regulating immune cell toxicity and lymphocytes infiltration. Moreover, TMCs 4-8 were correlated with tumor mutation burden and expression of PD-1/PD-L1/CTLA4 in 33 cancers. Thus, we established an immunotherapy response prediction (IRP) score based on the signature of TMCs 4-8. Patients with higher IRP scores showed higher immunotherapeutic responses in five cohorts of skin melanoma (area under curve [AUC] = 0.90 in the training cohort, AUCs range from 0.70 to 0.83 in the validation cohorts). Together, our study highlights the great potential of TMCs as biomarkers for prognosis and immunotherapeutic response, which can pave the way for further investigation of the tumor-infiltrating mechanisms and therapeutic potentials of TMCs in cancer.

27 March 2019 in Scientific Reports
Verified
Journal Article
Open access
PDF file
SWSen Wang
Sen Wang
LRLongke Ran
Longke Ran
WZWanfeng Zhang
Wanfeng Zhang
XLXue Leng
Xue Leng
KWKexin Wang
Kexin Wang
FSFangzhou Song
Fangzhou Song
Gastric cancer (GC) is the fourth most common malignant neoplasm and the second leading cause of cancer death. Identification of key molecular signaling pathways involved in gastric carcinogenesis and progression facilitates early GC diagnosis and the development of targeted therapies for advanced GC patients. Emerging evidence has revealed a close correlation between forkhead box (FOX) proteins and cancer development. However, the prognostic significance of forkhead box S1 (FOXS1) in patients with GC and the function of FOXS1 in GC progression remain undefined. In this study, we found that upregulation of FOXS1 was frequently detected in GC tissues and strongly correlated with an aggressive phenotype and poor prognosis. Functional assays confirmed that FOXS1 knockdown suppressed cell proliferation and colony numbers, with induction of cell arrest in the G0/G1 phase of the cell cycle, whereas forced expression of FOXS1 had the opposite effect. Additionally, forced expression of FOXS1 accelerated tumor growth in vivo and increased cell migration and invasion through promoting epithelial–mesenchymal transition (EMT) both in vitro and in vivo. Mechanistically, the core promoter region of FOXS1 was identified at nucleotides −660~ +1, and NFKB1 indirectly bind the motif on FOXS1 promoters and inhibit FOXS1 expression. Gene set enrichment analysis revealed that the FOXS1 gene was most abundantly enriched in the hedgehog signaling pathway and that GLI1 expression was significantly correlated with FOXS1 expression in GC. GLI1 directly bound to the promoter motif of FOXS1 and significantly decreased FOXS1 expression. Finally, we found that miR-125a-5p repressed FOXS1 expression at the translational level by binding to the 3′ untranslated region (UTR) of FOXS1. Together, these results suggest that FOXS1 can promote GC development and could be exploited as a diagnostic and prognostic biomarker for GC.

28 July 2020 in Aging
Verified
Journal Article
Open access
RLRuihan Luo
Ruihan Luo
JSJing Song
Jing Song
XXXiao Xiao
Xiao Xiao
ZXZhengbo Xie
Zhengbo Xie
ZZZhiyuan Zhao
Zhiyuan Zhao
LRLongke Ran
Longke Ran
Epigenetic alterations are crucial to oncogenesis and regulation of gene expression in non–small-cell lung carcinoma (NSCLC). DNA methylation (DNAm) biomarkers may provide molecular-level prediction of relapse risk in cancer. Identification of optimal treatment is warranted for improving clinical management of NSCLC patients. Using machine learning algorithm we identified 4 recurrence predictive CpG methylation markers (cg00253681/ART4, cg00111503/KCNK9, cg02715629/FAM83A, cg03282991/C6orf10) and constructed a risk score model that potently predicted recurrence-free survival and prognosis for patients with NSCLC (P = 0.0002). Integrating genomic, transcriptomic, proteomic and clinical data, the DNAm-based risk score was observed to significantly associate with clinical stage, cell proliferation markers, somatic alterations, tumor mutation burden (TMB) as well as DNA damage response (DDR) genes, and potentially predict the efficacy of immunotherapy. In general, our identified DNAm signature shows a significant correlation to TMB and DDR pathways, and serves as an effective biomarker for predicting NSCLC recurrence and response to immunotherapy. These findings demonstrate the utility of 4-DNAm-marker panel in the prognosis, treatment decision-making and evaluation of therapeutic responses for NSCLC.

1 October 2019 in Biochimie
Verified
Journal Article
Closed access
WZWanfeng Zhang
Wanfeng Zhang
SWSen Wang
Sen Wang
XZXianqin Zhang
Xianqin Zhang
KLKun Liu Kun Liu
Kun Liu Kun Liu
JSJing Song
Jing Song
LRLongke Ran
Longke Ran

23 October 2019 in Journal of Cellular Biochemistry
Verified
Journal Article
Closed access
PDF file
CTChuntao Tao
Chuntao Tao
RLRuihan Luo
Ruihan Luo
JSJing Song
Jing Song
WZWanfeng Zhang
Wanfeng Zhang
LRLongke Ran
Longke Ran