Non-coding RNAs in renal cell carcinoma: Implications for drug resistance

Liu, Yi-Qi; Zhang, Hu; Fang, Yuan; Tang, Dongshan; Luo, Zhigang

doi:10.1016/j.biopha.2023.115001

Cited by 2 publications

(3 citation statements)

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“… 31 The differential expression levels of lncRNAs are closely related to the occurrence and development of ccRCC. 32 , 33 Hu et al. found that hypoxic RCC cells secrete exosomes packaged with lncHILAR, which are taken up by normoxic RCC cells, and promote normoxic RCC cell invasion and metastasis via ceRNA for the miR‐613/206/1–1‐3p/Jagged‐1/Notch/CXCR4 axis.…”

Section: Introductionmentioning

confidence: 99%

“…LncRNAs are primarily defined as RNAs ≥200 nucleotides long and can range up to 100 kb 31 . The differential expression levels of lncRNAs are closely related to the occurrence and development of ccRCC 32,33 . Hu et al.…”

Section: Introductionmentioning

confidence: 99%

“…ceRNA network, clear cell renal cell carcinoma, exosome, lncRNA, machine learning, precision medicine, tumor microenvironment occurrence and development of ccRCC. 32,33 Hu et al found that hypoxic RCC cells secrete exosomes packaged with lncHILAR, which are taken up by normoxic RCC cells, and promote normoxic RCC cell invasion and metastasis via ceRNA for the miR-613/206/1-1-3p/ Jagged-1/Notch/CXCR4 axis. 34 Zhang et al found that lncARSR acts as a signaling molecule delivered by RCCderived exosomes to induce macrophage polarization by activating the STAT3 signaling pathway, thus promoting the occurrence and development of ccRCC.…”

Section: Introductionmentioning

confidence: 99%

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Exosome‐related lncRNA score: A value‐based individual treatment strategy for predicting the response to immunotherapy in clear cell renal cell carcinoma

Yang,

Zhang,

Zhan

et al. 2024

Cancer Medicine

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BackgroundExosomes play a crucial role in intercellular communication in clear cell renal cell carcinoma (ccRCC), while the long non‐coding RNAs (lncRNAs) are implicated in tumorigenesis and progression.AimsThe purpose of this study is to construction a exosomes‐related lncRNA score and a ceRNA network to predict the response to immunotherapy and potential targeted drug in ccRCC.MethodsData of ccRCC patients were obtained from the TCGA database. Pearson correlation analysis was used to identify eExosomes‐related lncRNAs (ERLRs) from Top10 exosomes‐related genes that have been screened. The entire cohort was randomly divided into a training cohort and a validation cohort in equal scale. LASSO regression and multivariate cox regression was used to construct the ERLRs‐based score. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and drug susceptibility between the high‐ and low‐risk groups were also investigated. Finally, the relevant ceRNA network was constructed by machine learning to analyze their potential targets in immunotherapy and drug use of ccRCC patients.ResultsA score consisting of 4ERLRs was identified, and patients with higher ERLRs‐based score tended to have a worse prognosis than those with lower ERLRs‐based score. ROC curves and multivariate Cox regression analysis demonstrated that the score could be considered as a risk factor for prognosis in both training and validation cohorts. Moreover, patients with high scores are predisposed to experience poor overall survival, a larger prevalence of advanced stage (III‐IV), a greater tumor mutational burden, a higher infiltration of immunosuppressive cells, and a greater likelihood of responding favorably to immunotherapy. The importance of EMX2OS was determined by mechanical learning, and the ceRNA network was constructed, and EMX2OS may be a potential therapeutic target, possibly exerting its function through the EMX2OS/hsa‐miR‐31‐5p/TLN2 axis.ConclusionsBased on machine learning, a novel ERLRs‐based score was constructed for predicting the survival of ccRCC patients. The ERLRs‐based score is a promising potential independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics. Meanwhile, we screened out key lncRNAEMX2OS and identified the EMX2OS/hsa‐miR‐31‐5p/TLN2 axis, which may provide new clues for the targeted therapy of ccRCC.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%