bims-lorfki 2022-04-10 papers

Crit Rev Eukaryot Gene Expr. 2022 ;32(1): 79-98

Comprehensive Analysis of N6-Methyladenosine-Related IncRNAs Prognostic Signature and the Associated Immune Infiltrates in Kidney Renal Clear Cell Carcinoma.

Xinyi Chen, Lu Wang, Jingyao Tu, Xin Pan, Yuehan Li, Han Yin, Moran Wang, Xianglin Yuan.

Kidney renal clear cell carcinoma (KIRC) is the most common and aggressive subtype of renal cell carcinoma. N6-methyladenosine (m6A) RNA methylation is the most prevalent epigenetic RNA modification. Long non-coding RNAs (lncRNAs) have emerged as a key role in regulating cancer progression. However, little has been learned about the molecular functions of m6A-related lncRNAs in KIRC. The prognostic value of m6A-related ln-cRNAs was investigated in KIRC samples downloaded from The Cancer Genome Atlas (TCGA) dataset. The m6A-related lncRNAs were further screen out by Pearson correlation test. Then, 27 m6A-related lncRNAs were confirmed as potential prognostic factors through univariate Cox regression analysis. They were entered into Lasso and multivariate Cox regression to build a m6A-related lncRNA prognostic signature, including 14 m6A-related lncRNAs determined as independent prognostic factors. Additionally, a risk score calculated according to the prognostic model could divide KIRC patients into low- and high-risk groups depending on median risk score as cut-off. A prognostic nomogram, derived from the prognostic model and integrating clinical characteristics of patients, was constructed. Three distinct clusters were identified with different immune signatures through consensus clustering analysis according to the expression pattern of m6A-related lncRNAs. Twenty-seven prognostic m6A-related lncRNAs were determined as prognostic lncRNAs from TCGA-KIRC cohort. The m6A-related lncRNA prognostic signature containing 14 independent prognostic lncRNAs exhibited good accuracy in predicting overall survival of KIRC patients. We correlated the three distinct clusters with immune infiltration signature of KIRC for the first time. We found that the worse prognosis of cluster2 was probably mediated by immune evasion. In summary, our study identified a m6A-related lncRNAs prognostic signature which had great clinical value in prognosis assessment. We classified TCGA-KIRC samples into three clusters with distinct immune signatures, which could be considered as potential targets of immunotherapy for KIRC treatment in the future.

DOI: https://doi.org/10.1615/CritRevEukaryotGeneExpr.2021039325

Dis Markers. 2022 ;2022 8131007

Identification of a Twelve Epithelial-Mesenchymal Transition-Related lncRNA Prognostic Signature in Kidney Clear Cell Carcinoma.

Qi-Dong Xia, Yuan Zhang, Li-Sha Li, Jun-Lin Lu, Yang Xun, Jian-Xuan Sun, Jin-Zhou Xu, Chen-Qian Liu, Yu-Chao Lu, Deng He, Shao-Gang Wang.

Background: Epithelial-mesenchymal transition (EMT) plays a vital role in tumor metastasis and drug resistance. It has been reported that EMT is regulated by several long noncoding RNAs (lncRNAs). We aimed to identify EMT-related lncRNAs and develop an EMT-related lncRNA prognostic signature in kidney renal clear cell carcinoma (KIRC).
Materials and Methods: In total, 530 ccRCC patients with 611 transcriptome profiles were included in this study. We first identified differentially expressed EMT-related lncRNAs. Then, all the samples with transcriptional data and clinical survival information were randomly split into training/test sets at a ratio of 1 : 1. Accordingly, we further developed a twelve differentially expressed EMT-related lncRNA prognostic signature in the training set. Following this, risk analysis, survival analysis, subgroup analysis, and the construction of the ROC curves were applied to verify the efficacy of the signature in the training set, test set, and all patients. Besides, we further investigated the differential immune infiltration, immune checkpoint expression, and immune-related functions between high-risk patients. Finally, we explored the different drug responses to targeted therapy (sunitinib and sorafenib) and immunotherapy (anti-PD1 and anti-CTLA4).
Results: A twelve differentially expressed EMT-related lncRNA prognostic signature performed superior in predicting the overall survival of KIRC patients. High-risk patients were observed with a significantly higher immune checkpoint expression and showed better responses to the targeted therapy and immunotherapy.
Conclusions: Our study demonstrates that the twelve differentially expressed EMT-related lncRNA prognostic signature could act as an efficient prognostic indicator for KIRC, which also contributes to the decision-making of the further treatment.

DOI: https://doi.org/10.1155/2022/8131007

BMC Genomics. 2022 Apr 02. 23(1): 254

Predict the role of lncRNA in kidney aging based on RNA sequencing.

Jie Li, Fanfan Gao, Limin Wei, Lei Chen, Ning Qu, Lu Zeng, Yulong Luo, Xinmei Huang, Hongli Jiang.

BACKGROUND: Long noncoding RNAs (lncRNAs) are involved in physiological and pathological processes. However, no studies have been conducted on the relationship between lncRNAs and renal aging.
RESULTS: First, we evaluated the histopathology of young (3-month-old) and old (24-month-old) C57BL/6J mouse kidneys. Masson trichrome staining and PAS staining showed interstitial collagen deposition and fibrosis, mesangial matrix expansion, a thicker basement membrane and renal interstitial fibrosis in old mouse kidneys. Senescence-associated β-galactosidase (SA-β-gal)-positive areas in the kidneys of old mice were significantly elevated compared to those of young mice. Then, we analyzed the differential expression of lncRNAs and mRNAs in the kidneys of young and old mouse kidneys by RNA-seq analysis. 42 known and 179 novel differentially expressed lncRNAs and 702 differential mRNAs were detected in the mouse kidney. Next, we focused on the differentially expressed mRNAs and lncRNAs by RNA-seq. GO and KEGG analyses were performed based on differentially expressed mRNAs between young and old mouse kidneys. Transregulation based on RIsearch and the correlation coefficient of mRNA-lncRNA were also calculated. The mRNA-lncRNA network was constructed by choosing a Spearman correlation coefficient > 0.9 or <-0.9. GO and KEGG pathway enrichment analyses revealed that differentially expressed mRNAs participated in aging-related pathways. A total of 10 lncRNAs and trans-regulated mRNAs were constructed. Finally, we validated the role of lncRNA Gm43360 by CCK-8, flow cytometry, western blot and SA-β-gal staining. The expression level of Adra1a was positively correlated and Csnk1a1 was negatively correlated with lncRNA Gm43360. The cell counting kit-8 (CCK-8) results showed that lncRNA Gm43360 promoted cell viability. LncRNA Gm43360 increased the percentage of S phase cells and decreased the percentage of G1 phase cells compared with the negative control. LncRNA Gm43360 decreased the expression of p53, p21 and SA-β-gal.
CONCLUSIONS: LncRNA Gm43360 may play a protective role in kidney aging.

Keywords: Aging; Kidney; lncRNA

DOI: https://doi.org/10.1186/s12864-022-08479-8